ACTA GEOGRAPHICA SLOVENICA GEOGRAFSKIZBORNIK 2018 58 1 0101661851779 ISSN 1581-6613 A C TA G E O G R A P H IC A S LO V E N IC A • G E O G R A FS K I Z B O R N IK • 58 -1 • 20 18ACTA GEOGRAPHICA SLOVENICA GEOGRAFSKI ZBORNIK 58-1 • 2018 Contents Milivoj B. Gavrilov, Slobodan B. Marković, Natalija JaNc, Milena Nikolić, aleksandar valJarević, Blaž koMac, Matija ZorN, Milan PuNišić†, Nikola Bačević AssessingaverageannualairtemperaturetrendsusingtheMann–KendalltestinKosovo 7 liza StaNčič, Blaž rePe Post-firesuccession:SelectedexamplesfromtheKarstregion,southwestSlovenia 27 Mirko Grčić, ljiljana Grčić, Mikica SiBiNović ThegeographicalpositionofthetownofRasabasedonPorphyrogenitusandmedievalmaps 39 Special issue – Agriculture in modern landscapes: A factor hindering or facilitating development? Nika raZPotNik viSković, Blaž koMac Agricultureinmodernlandscapes:Afactorhinderingorfacilitatingdevelopment? 51 iwona MarkuSZewSka ConflictsbetweenlegalpolicyandruralareamanagementinPoland 59 Mojca Foški The(non)usefulnessoftheRegisterofExistingAgriculturalandForest LandUseformonitoringtheprocessesinurbanareas 69 Maja PoleNšek, Janez PirNat ForestPatchConnectivity:TheCaseoftheKranj-SoraBasin,Slovenia 83 karmen PaŽek, aleš irGolič, Jernej turk, andreja Borec, Jernej PrišeNk, Matej koleNko, črtomir roZMaN Multi-criteriaassessmentoflessfavouredareas:A statelevel 97 Miomir M. JovaNović, Miško M. MilaNović, Matija ZorN TheuseofNDVIandCORINELandCoverdatabasesforforestmanagementinSerbia 109 Darijo ilić, Jože PaNJaN NitrogenandPhosphorusPollutioninGoričkoNaturePark 125 naslovnica 58-1_naslovnica 49-1.qxd 12.9.2017 7:55 Page 1 ACTA GEOGRAPHICA SLOVENICA GEOGRAFSKI ZBORNIK 58-1 2018 58-1-uvod_00p_uvod49-1.qxd 12.9.2017 7:55 Page 1 2 58-1-uvod_00p_uvod49-1.qxd 12.9.2017 7:55 Page 2 ZNANSTVENORAZISKOVALNI CENTER SLOVENSKE AKADEMIJE ZNANOSTI IN UMETNOSTI GEOGRAFSKI INŠTITUT ANTONA MELIKA • RESEARCH CENTRE OF THE SLOVENIAN ACADEMY OF SCIENCES AND ARTS ANTON MELIK GEOGRAPHICAL INSTITUTE ACTA GEOGRAPHICA SLOVENICA GEOGRAFSKI ZBORNIK 58-1 2018 LJUBLJANA 2018 58-1-uvod_00p_uvod49-1.qxd 12.9.2017 7:55 Page 3 ACTA GEOGRAPHICA SLOVENICA 58-1 2018 ISSN: 1581-6613 COBISS: 124775936 UDC/UDK: 91 © Geografski inštitut Antona Melika ZRC SAZU 2018 International editorial board/mednarodni uredniški odbor: Michael Bründl (Switzerland), Rok Ciglič (Slovenia), Matej Gabrovec (Slovenia), Peter Jordan (Austria), Drago Kladnik (Slovenia), Blaž Komac (Slovenia), Andrej Kranjc (Slovenia), Dénes Lóczy (Hungary), Simon McCharty (United Kingdom), Slobodan Marković (Serbia), Milan Orožen Adamič (Slovenija), Drago Perko (Slovenia), Marjan Ravbar (Slovenia), Aleš Smrekar (Slovenia), Annett Steinführer (Germany), Mimi Urbanc (Slovenia), Matija Zorn (Slovenia). Editor-in-Chief/glavni urednik: Blaž Komac; blaz@zrc-sazu.si Executive editor/odgovorni urednik: Drago Perko; drago@zrc-sazu.si Chief editor for physical geography/glavni urednik za fizično geografijo: Matija Zorn; matija.zorn@zrc-sazu.si Chief editor for human geography/glavna urednica za humano geografijo: Mimi Urbanc; mimi@zrc-sazu.si Chief editor for regional geography/glavni urednik za regionalno geografijo: Drago Kladnik; drago.kladnik@zrc-sazu.si Chief editor for spatial planning/glavni urednik za regionaln o planiranje: Janez Nared; janez.nared@zrc-sazu.si Chief editor for urban geography/glavni urednik za urbano geografijo: David Bole; david.bole@zrc-sazu.si Chief editor for geographic information systems/glavni urednik za geografske informacijske sisteme: Rok Ciglič; rok.ciglic@zrc-sazu.si Chief editor for environmental protection/glavni urednik za varstvo okolja: Aleš Smrekar; ales.smrekar@zrc.sazu Editorial assistant/uredniški pomočnik: Matjaž Geršič; matjaz.gersic@zrc.sazu Published by/izdajatelj: Geografski inštitut Antona Melika ZRC SAZU Issued by/založnik: Založba ZRC Co-issued by/sozaložnik: Slovenska akademija znanosti in umetnosti Address/Naslov: Geografski inštitut Antona Melika ZRC SAZU, Gosposka ulica 13, SI – 1000 Ljubljana, Slovenija The papers are available on-line/prispevki so dostopni na medmrežju: http://ags.zrc-sazu.si (ISSN: 1581–8314) Ordering/naročanje: Založba ZRC Novi trg 2, p. p. 306, SI – 1001 Ljubljana, Slovenija Phone/telefon: +386 (0)1 470 64 64 Fax/faks: +386 (0)1 425 77 94 E-mail/e-pošta: zalozba@zrc-sazu.si Annual subscription/letna naročnina: 20 € for individuals/za posameznike, 28 € for institutions/za ustanove. Single issue/cena posamezne številke: 12,50 € for individuals/za posameznike, 16 € for institutions/za ustanove. Cartography/kartografija: Geografski inštitut Antona Melika ZRC SAZU Translations/prevodi: DEKS, d. o. o. DTP/prelom: SYNCOMP, d. o. o. Printed by/tiskarna: Collegium Graphicum d. o. o. Print run/naklada: 400 copies/izvodov The journal is subsidized by the Slovenian Research Agency/revija izhaja s podporo Javne agencije za raziskovalno dejavnost Republike Slovenije. The journal is indexed also in/revija je vključena tudi v: SCIE – Science citation index expanded, Scopus, JCR – Journal Citation Report/Science Edition, ERIH PLUS, GEOBASE Journals, Current geographical publications, EBSCOhost, Geoscience e-Journals, Georef, FRANCIS, SJR (SCImago Journal & Country Rank), OCLC WorldCat, and Google scholar, CrossRef. Front cover photography: Agriculture plays an important role in both protecting and developing farmland and is an important factor facilitating development of other sectors (photograph: Matej Lipar). Fotografija na naslovnici: Kmetijstvo ima pomembno vlogo pri varovanju in razvoju kmetijskih zemljišč in je pomemben dejavnik tudi pri razvoju drugih sektorjev (fotografija: Matej Lipar). 58-1-uvod_00p_uvod49-1.qxd 12.9.2017 7:55 Page 4 5 ACTA GEOGRAPHICA SLOVENICA ISSN: 1581-6613 UDC: 91 Number: 58-1 Year: 2018 Contents Milivoj B. Gavrilov, Slobodan B. Marković, Natalija JaNc, Milena Nikolić, aleksandar valJarević, Blaž koMac, Matija ZorN, Milan PuNišić†, Nikola Bačević Assessing average annual air temperature trends using the Mann–Kendall test in Kosovo 7 liza StaNčič, Blaž rePe Post-fire succession: Selected examples from the Karst region, southwest Slovenia 27 Mirko Grčić, ljiljana Grčić, Mikica SiBiNović The geographical position of the town of Rasa based on Porphyrogenitus and medieval maps 39 Special issue – Agriculture in modern landscapes: A factor hindering or facilitating development? Nika raZPotNik viSković, Blaž koMac Agriculture in modern landscapes: A factor hindering or facilitating development? 51 iwona MarkuSZewSka Conflicts between legal policy and rural area management in Poland 59 Mojca Foški The (non)usefulness of the Register of Existing Agricultural and Forest Land Use for monitoring the processes in urban areas 69 Maja PoleNšek, Janez PirNat Forest Patch Connectivity: The Case of the Kranj-Sora Basin, Slovenia 83 58-1-uvod_00p_uvod49-1.qxd 12.9.2017 7:55 Page 5 karmen PaŽek, aleš irGolič, Jernej turk, andreja Borec, Jernej PrišeNk, Matej koleNko, črtomir roZMaN Multi-criteria assessment of less favoured areas: A state level 97 Miomir M. JovaNović, Miško M. MilaNović, Matija ZorN The use of NDVI and CORINE Land Cover databases for forest management in Serbia 109 Darijo ilić, Jože PaNJaN Nitrogen and Phosphorus Pollution in Goričko Nature Park 125 6 58-1-uvod_00p_uvod49-1.qxd 12.9.2017 7:55 Page 6 Acta geographica Slovenica, 58-1, 2018, 7–25 ASSESSING AVERAGE ANNUAL AIR TEMPERATURE TRENDS USING THE MANN–KENDALL TEST IN KOSOVO Milivoj B. Gavrilov, Slobodan B. Marković, Natalija Janc, Milena Nikolić, Aleksandar Valjarević, Blaž Komac, Matija Zorn, Milan Punišić†, Nikola Bačević Temperatures were confirmed to rise in Kosovo in the last decades. 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 7 Assessing average annual air temperature trends using the Mann–Kendall test in Kosovo DOI: https://doi.org/10.3986/AGS.1309 UDC: 911.2:551.524(497.115) COBISS: 1.01 Assessing average annual air temperature trends using the Mann–Kendall test in Kosovo ABSTRACT: The annual trends of surface mean monthly air temperature and monthly extreme temper- atures were analyzed from ten meteorological stations in Kosovo. The data refer to observation periods between 1949 and 1999 for four stations, and observation periods between 1965 and 1999 for the remain- ing six stations. Trends were analyzed for nine time series. Positive trends were found in six series, and negative trends were found in three series. After an assessment of these trends using the Mann–Kendall test, positive trends were confirmed in four series, a negative trend was confirmed in one series, and in one series there was no trend, whereas trends were characterized as slightly positive in two time series and slightly negative in one series. Key wORDS: air temperature trends, climate change, Mann–Kendall test, Kosovo Oce na tren dov pov preč nih let nih tem pe ra tur zra ka na Koso vu z upo ra bo Mann-Ken dal lo ve ga testa POVZeTeK: V ra zi ska vi so bili ana li zi ra ni let ni tren di pov preč nih in ekstrem nih meseč nih tem pe ra tur zraka, izmer je nih na dese tih meteo ro loš kih posta jah na Koso vu. Podat ki se pri šti rih posta jah nana ša jo na opazo val no obdob je 1949–1999, pri preo sta lih šestih posta jah pa na opa zo val no obdob je 1965–1999. Tren di so bili ana li zi ra ni za devet časov nih nizov. Pozi tiv ni tren di so bili ugo tov lje ni v še stih nizih, nega - tiv ni pa v treh. Po oce ni teh tren dov z upo ra bo Mann-Ken dal lo ve ga testa so bili pozi tiv ni tren di potr je ni v šti rih nizih, nega tiv ni trend je bil potr jen v enem nizu, v enem nizu tren da ni bilo, rah lo pozi tiv ni tren - di so bili potrjeni v dveh časov nih nizih in rah lo nega tiv ni v enem nizu. KLJUČNe BeSeDe: tren di tem pe ra tur zra ka, pod neb ne spre mem be, Mann-Ken dal lov test, Koso vo Milivoj B. Gavrilov, Slobodan B. Marković, Nikola Bačević Department of Geography, Tourism and Hotel Management, Faculty of Sciences, University of Novi Sad gavrilov.milivoj@gmail.com, slobodan.markovic@dgt.uns.ac.rs, nikolabacevic@yahoo.com Natalija Janc natalijanc@earthlink.net Milena Nikolić Belgrade Business School, Higher education Institution for Applied Studies milenan80@yahoo.com Aleksandar Valjarević Mathematical Institute of the Serbian Academy of Sciences and Arts valjarkosmos@yahoo.com Blaž Komac, Matija Zorn Anton Melik Geographical Institute, Research Centre of the Slovenian Academy of Sciences and Arts blaz@zrc-sazu.si, matija.zorn@zrc-sazu.si 8 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 8 Milan Punišić Ministry of Natural Resources, Mining and Spatial Planning The paper was submitted for publication on November 11th, 2014. Ured niš tvo je pris pe vek pre je lo 11. no vem bra 2014. Acta geographica Slovenica, 58-1, 2018 9 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 9 Assessing average annual air temperature trends using the Mann–Kendall test in Kosovo 10 1 Introduction According to the Intergovernmental Panel on Climate Change (IPCC 2007) report, the average global sur- face air temperature of the world has increased by 0.7 °C in the last hundred years. Klein Tank et al. (2002) showed that trends in average temperature increased in the period between 1946 and 1999 in europe. This increase in global and regional temperature varies seasonally and regionally. In europe the trends are high- er in central and north-eastern areas and in mountainous regions, whereas lower trends are found in the Mediterranean region and temperatures are increasing higher in winter than summer (all during the peri- od from 1977 to 2000; Alcamo et al. 2007). Historically, the climate of Kosovo has generally been analyzed as part of the climate of Serbia and yugoslavia. Using extreme temperatures at fifteen meteorological stations in Serbia, Unkašević and Tošić (2013) suggested that the climate in the region warmed up between 1949 and 2009. Analyzing data between 1949 and 2007, Unkašević and Tošić (2009a) found that a slow decrease in summer temperatures until 1975 was followed by a temperature increase lasting until 2007. In addition to these papers, other recent works address- ing the climate in Serbia with and without Kosovo have been published (Jovanović etal. 2002; Gburčik etal. 2006; Đorđević 2008; Unkašević and Tošić 2009b; Gavrilov etal. 2010; 2013; Pavlović Berdon 2012; Hrnjak etal. 2014; Tošić et al. 2014; Gavrilov et al. 2015; 2016). In addition, the weather and climate of Kosovo were investi- gated in the work of Sokolović et al. (1984). This study focuses on average annual air temperature trends in Kosovo from 1949 to 1999 and from 1965 to 1999. The first period contains nearly two thirty-year-climate cycles, and the second contains more than one thirty-year-climate cycle. Therefore the results are proper indicators for recent climate change. 2 Area and data 2.1 Study area Kosovo is located in the southwestern part of the Balkan Peninsula and covers an area of 10,887km2 (Figure 1). Its geomorphological characteristics and geographical location divide it into two regions; Kosovo proper in the east is a plateau with a relatively consistent elevation, and Metohija in the west is a hilly area bordered by high mountains. The climate of Kosovo is moderate continental with cold winters and warm summers, with a great range of extreme temperatures and a non-uniform distribution of rainfall. The average annual air tem- perature is 10.8 °C, and the annual amount of precipitation between 1949 and 1999 was 669 mm (Internet 1). 2.2 Data This work contains an analysis of surface air temperature trends obtained from ten meteorological sta- tions. The locations of the stations are presented in Figure 1, and their main parameters are given in Table 1 Table 1: List of meteorological stations and their geographical coordinates and elevations. Number Meteorological station Elevation (m) Latitude (°N) Longitude (°E) Stations operated from 1949 to 1999 1 Kosovska Mitrovica 510 42° 53' 20° 52' 2 Peć 498 42° 40' 20° 18' 3 Prizren 402 42° 13' 20° 44' 4 Priština 573 42° 39' 21° 09' Stations operated from 1965 to 1999 5 Istok 465 42° 47' 20° 30' 6 Skivijane 415 42° 28' 20° 21' 7 Suva Reka 420 42° 21' 20° 49' 8 Gnjilane 520 42° 28' 21° 29' 9 Uroševac 580 42° 23' 21° 10' 10 Dragaš 1060 42° 04' 20° 39' 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 10 in accordance with the Republic Hydrometeorological Service of Serbia. Meteorological stations were divid- ed into two groups, depending on the periods in which they were first established and operational. The first group consists of four stations that operated from 1949 to 1999, and the second group consists of the remaining six stations, which operated from 1965 to 1999. Nine of the stations have a relatively uniform elevation, varying between 402 m and 580 m, whereas the Dragaš station has an elevation of 1,060 m (in this paper it is referred to as a mountain station). In order to obtain trends, we used three data sets: monthly mean temperatures, monthly maximum temperatures, and monthly minimum temperatures for all stations. From the monthly temperatures, the average annual mean temperatures, average annual maximum temperatures, and average annual minimum temperatures were calculated. Finally, from these three types of average annual temperatures, new data sets were derived, marked as: T, Tx, and Tn, respectively, for trend calculations for Kosovo (K) over two peri- ods: 1949–1999 (P1) from four stations (Kosovska Mitrovica, Peć, Prizren, and Priština) and 1965–1999 (P2) Acta geographica Slovenica, 58-1, 2018 11 Figure 1: Kosovo. 43° 15' 20° 00' 43° 15' 21° 45' 42° 00' 21° 45' 42° 00' 20° 00' Projection UTM FUSe 34 Meteorological station Border line Rivers Contour line 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 11 Assessing average annual air temperature trends using the Mann–Kendall test in Kosovo from five stations (Istok, Skivijane, Suva Reka, Gnjilane, and Uroševac); whereas Dragaš (D) was treated as a special data set because it is a mountain station, with data available for the period from 1965 to 1999 (P2). each of these data sets is marked with an acronym consisting of the abbreviation for the territory/station, period, and type of temperature. In total, all nine data sets (time series) were used for trend calculation (Table 2). Table 2: List of nine time series to calculate air temperatures trends. Territory/station 1949–1999 (P1) 1965–1999 (P2) K-P1-T K-P2-T Kosovo (K) K-P1-Tx K-P2-Tx K-P1-Tn K-P2-Tn – D-P2-T Dragaš (D) – D-P2-Tx – D-P2-Tn Before the previous calculation, the homogeneity of the temperature data was examined according to the Alexandersson (1986) test. The test showed that the time series are not non-homogeneous for a signif- icance level of 5%. 3 Methods Temperature trends were analyzed for nine time series using two statistical approaches: calculation of the linear temperature trend equation and application of the Mann–Kendall test. The first approach was to calculate the tendency (trend) equation of temperature using linear inter- polation of the average annual temperatures (wibig and Glowicki 2002). This method was used to determine the sign of the temperature trends and the trend magnitude (Gavrilov et al. 2015; 2016) as the difference in temperatures between the beginning and end of both periods P1 and P2. The second statistical approach used the Mann–Kendall test (Kendall 1975; Gilbert 1987) to indicate statistically significant trends. The Mann–Kendall test is widely used in analysis of climatologic time series; for example, temperature and precipitation (Karmeshu 2012), extreme temperatures (wibig and Glowicki 2002), hail (e.g., Gavrilov et al. 2010, 2013), aridity (Hrnjak et al. 2014), evapotranspiration (Tabari et al. 2011), and atmospheric deposition (Drapela and Drapelova 2011), and also in hydrological time series (yue and wang 2004) and other geophysical time series, such as soil freezing and thawing (Sinha and Cherkauer 2007) because it is simple and robust, and it can cope with missing values and values below the detection limit. In using the Mann–Kendall test to define statistically significant trends, two hypotheses were tested: the null hypothesis, H0, that there is no trend in the time series, and the alternative hypothesis, Ha, that there is a trend in the time series for a given significance level. Probability p in percent (Karmeshu 2012; Gavrilov et al. 2016) was calculated to determine the level of confidence in the hypothesis. If the computed value p is lower than the chosen significance level α (e.g., α = 5 %), the H0 (there is no trend) should be reject- ed, and the Ha (there is a significant trend) should be accepted; and if p is greater than the significance level α then the H0 is accepted (or cannot be rejected). For calculating probability p and hypothesis testing, XLSTAT statistical analysis software was employed (Internet 2). It is considered that accepting the Ha indicates that a trend is statistically significant. On the other hand, acceptance of the H0 implies that there is no trend (no change), whereas often in practice the trend equa- tion indicates the opposite; that is, that there is a trend. Therefore, to reduce the contradictions in analyzing the temperature trends between two independent statistical approaches – the trend equation and the Mann–Kendall test – the modified interpretation of the Mann–Kendall test will be offered. Moreover, this interpretation makes it possible to obtain more diverse results. It is quite clear that, with decreasing probability p, statistical confidence in the H0 decreases and con- fidence in the Ha increases, and vice versa. Because probability p takes values between 0% and 100%, for the purposes of this study a modified interpretation of the Mann–Kendall test was introduced and four levels of confidence were defined (Gavrilov et al. 2015; 2016). when the computed probability p is: (1) less or equal to 5%, the trend is significantly positive/negative; (2) greater than 5% and less than or equal to 30%, 12 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 12 the trend is moderately positive/negative; (3) greater than 30% and less than or equal to 50%, the trend is slightly positive/negative; and (4) greater than 50%, there is no trend. As can be seen, in cases (1) and (4) both interpretations of the Mann–Kendall test have the same meaning; namely, that there is a significant trend and that there is no trend. Differences occur in cases (2) and (3), where the Mann–Kendall test claims there is no trend, and the modified Mann–Kendall test allows a trend with reduced levels of confidence. 4 Results and discussion 4.1 The values of trends By applying both statistical approaches to each of the nine time series in Table 2, nine cases are obtained (Table 3). Table 3: The trend equation y, the trend magnitude Δy, and probability p of the confidences for all time series. Time series Trend equation Δy (°C) p (%) K-P1-T y = -0.006 x + 10.97 0.3 25 K-P1-Tx y = 0.013 x + 23.50 –0.7 17 K-P1-Tn y = 0.012 x – 1.40 –0.6 4.5 K-P2-T y = 0.021 x + 10.31 –0.7 1 K-P2-Tx y = 0.024 x + 23.42 –0.8 2 K-P2-Tn y = 0.011 x – 2.17 –0.4 24 D-P2-T y = -0.003 x + 8.31 0.1 89 D-P2-Tx y = 0.070 x + 20.41 –2.5 1 D-P2-Tn y = -0.047 x – 1.76 1.7 1 In Table 3 the first column is the time series; the second column is the linear trend equation, where y is the average annual value of the temperature in °C and x is the time in years; Δy is the trend magnitude in °C; and p is the probability in percent, α = 5% is the significance level (it is the same in all cases). 4.2 Evaluation of trends In strictly formal terms, as evidenced by the trend equations in Table 3, in all cases some trends can be observed. However, not all trends have the same sign, magnitude, and probability. To obtain the final evaluation of temperature trends, values from Table 3, Figures 2–4, and the results of hypothesis testing were used. Figure 2 and the trend equations for the time series K-P1-T, K-P1-Tx, and K-P1-Tn show that the trends are negative once and positive twice, respectively. Mann–Kendall test will prove whether these statements are true. Because the probabilities p are greater than the significance level, α = 5%, the H0 cannot be reject- ed in the first two cases. The risk of rejecting the H0 while it is true are 25% and 17%, respectively. Because the p in K-P1-Tn is lower than the significance level, the H0 should be rejected and the Ha should be accept- ed. The statement that there is a trend is correct with a probability greater than 95%. In accordance with the modified Mann–Kendall test, these three trends are characterized as moderately negative, moderate- ly positive, and significantly positive, respectively. Figure 3 and the trend equations for the time series K-P2-T, K-P2-Tx, and K-P2-Tn show that the trends are positive in all cases. Mann–Kendall test will prove whether these statements are true. Because the prob- abilities p in K-P2-T and K-P2-Tx are lower than the significance level, α = 5%, the H0 should be rejected and the Ha should be accepted in both cases. The statement that there are trends is correct with a proba- bility greater than 98%. Because the p in K-P2-Tn is greater than the significance level, the H0 cannot be rejected. The risk of rejecting the H0 while it is true is 24%. In accordance with the modified Mann–Kendall test, these cases are characterized as significantly positive twice and moderately positive once, respectively. Figure 4 and the trend equations for the time series D-P2-T, D-P2-Tx, and D-P2-Tn show that the trends are negative, positive, and negative, respectively. Mann–Kendall test will prove whether these statements are true. Because probability p in D-P2-T is greater than the significance level, α = 5%, the H0 cannot be rejected. Acta geographica Slovenica, 58-1, 2018 13 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 13 02468 1 0 1 2 1 4 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 Y e a r T(°C) y = – 0. 00 6 x + 1 0. 97 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 Fi gu re 2a 14 Assessing average annual air temperature trends using the Mann–Kendall test in Kosovo 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 14 05 1 0 1 5 2 0 2 5 3 0 Y e a r 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 1964 1963 1962 1961 1960 1959 1958 1957 1956 1955 1954 1953 1952 1951 1950 1949 y = 0 .0 13 x + 2 3. 50 Tx(°C)Fi gu re 2b 15 Acta geographica Slovenica, 58-1, 2018 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 15 – 3 ,5 – 3 ,0 – 2 ,5 – 2 ,0 – 1 ,5 – 1 ,0 – 0 ,5 0 ,0 0 ,5 1 ,0 1 ,5 Tn(°C) y = 0 .0 12 x – 1. 40 Y e a r 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 1964 1963 1962 1961 1960 1959 1958 1957 1956 1955 1954 1953 1952 1951 1950 1949 Fig ur e 2 : D ist rib ut ion by ye ar of th e t hr ee ty pe s o f t em pe rat ur es : T , T x, a nd T n ; th e t ren d l ine s a nd th e t ren d e qu ati on s o f t em pe rat ur es in Ko so vo fo r p eri od P1 on pa ne ls a, b, an d c , re sp ec tiv ely . Fi gu re 2c 16 Assessing average annual air temperature trends using the Mann–Kendall test in Kosovo 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 16 02468 1 0 1 2 1 4 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 Y e a r T(°C) 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 y = 0 .0 21 x + 1 0. 31 Fi gu re 3a 17 Acta geographica Slovenica, 58-1, 2018 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 17 Tx(°C) y = 0 .0 24 x + 2 3. 42 05 1 0 1 5 2 0 2 5 3 0 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 Y e a r 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 Fi gu re 3b 18 Assessing average annual air temperature trends using the Mann–Kendall test in Kosovo 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 18 – 7 – 6 – 5 – 4 – 3 – 2 – 101 Tn(°C) y = 0 .0 11 x – 2. 17 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 Y e a r 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 Fig ur e 3 : A s i n F igu re 2, bu t f or pe rio d P 2. Fi gu re 3c 19 Acta geographica Slovenica, 58-1, 2018 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 19 02468 1 0 1 2 T(°C) y = – 0. 00 x + . 3 8 3 1 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 Y e a r 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 Fi gu re 4a 20 Assessing average annual air temperature trends using the Mann–Kendall test in Kosovo 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 20 Tx(°C) 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 Y e a r 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 y = 0 .0 70 x + 2 0. 41 05 1 0 1 5 2 0 2 5 3 0 Fi gu re 4b 21 Acta geographica Slovenica, 58-1, 2018 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 21 – 5 ,0 – 4 ,5 – 4 ,0 – 3 ,5 – 3 ,0 – 2 ,5 – 2 ,0 – 1 ,5 – 1 ,0 – 0 ,5 0 ,0 Tn(°C) y = 0. 0 x – . 4 7 1 7 6 – 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 Y e a r 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 Fig ur e 4 : A s i n F igu re 2, bu t a t t he D rag aš st ati on . Fi gu re 4c 22 Assessing average annual air temperature trends using the Mann–Kendall test in Kosovo 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 22 23 Acta geographica Slovenica, 58-1, 2018 The risk of rejecting the H0 while it is true is 89%. Because the probabilities p in D-P2-Tx and D-P2-Tn are lower than the significance level, the H0 should be rejected and the Ha should be accepted in both cases. The statement that there are trends is correct with a probability greater than 99%. Now, the trends are char- acterized as no trend, significantly positive, and significantly negative, respectively. It should be noted that in the case D-P2-T the Δy is equal to the standard error of the temperature measurement, and so it is also considered no trend. 5 Conclusions The main results of the analysis of temperature trends in Kosovo are shown in Table 4. Table 4: The main results of the analysis of trends. Time series Trend equation Modified Mann–Kendall test K-P1-T Negative trend Negative moderate trend K-P1-Tx Positive trend Positive moderate trend K-P1-Tn Positive trend Positive significant trend K-P2-T Positive trend Positive significant trend K-P2-Tx Positive trend Positive significant trend K-P2-Tn Positive trend Positive moderate trend D-P2-T Negative trend No trend D-P2-Tx Positive trend Positive significant trend DP-2-Tn Negative trend Negative significant trend Based on the trend equations, positive trends were found in six and negative trends were found in three time series. After applying the Mann–Kendall test, significantly positive trends were confirmed in four time series, a moderately positive trend was found in two time series, and a significantly negative trend, mod- erately negative trend, and no trend were found in a single case each. From the results presented above, it is very difficult to derive an overall general rule, but some con- clusions can be drawn. First, positive temperature trends dominate. All of them could be explained by the effects of global warming on Kosovo. This impact is most evident in the case of representative time series K-P2-T, which covers the 1980s and 1990s, when the effect of global warming was first detected in the region (Gavrilov et al. 2016). On the other hand, the representative case K-P1-T was also influenced by global warming, but no positive trend was noted. This can be explained by impacts from the 1960s and 1970s, when there were no signs of global warming (Hardy 2006). In the case of the Dragaš mountain station, the results were very diverse. There, all three trends were found: positive, negative, and no trend. This case, as well as a detailed explanation of other cases, requires additional research. In spite of the limited meteorological data available, the results presented provide insight into the climate dynamics of the region. 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J., Glowicki, B. 2002: Trends of minimum and maximum temperature in Poland. Climate research 20-2. DOI: http://dx.doi.org/10.3354/cr020123 yue, S., wang, C. 2004: The Mann-Kendall test modified by effective sample size to detect trend in serial- ly correlated hydrological series. water resources management 18-3. DOI: http://dx.doi.org/10.1023/ B:wARM.0000043140.61082.60 Acta geographica Slovenica, 58-1, 2018 25 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 25 26 58-1_01p_1309-Milivoj B Gavrilov_acta49-1.qxd 12.9.2017 7:56 Page 26 Acta geographica Slovenica, 58-1, 2018, 27–38 POST-FIRE SUCCESSION: SELECTED EXAMPLES FROM THE KARST REGION, SOUTHWEST SLOVENIA Liza Stančič, Blaž Repe A young shoot at the base of a flowering ash scrub that had been scorched in a wildfire. L IZ A S T A N Č IČ 58-1_02p_1942-Liza Stancic_acta49-1.qxd 12.9.2017 7:56 Page 27 Liza Stančič, Blaž Repe, Post-fire succession: Selected examples from the Karst region, southwest Slovenia DOI: https://doi.org/10.3986/AGS.1942 UDC: 911.2:581.524.3(497.472Kras) COBISS: 1.01 Post-fire succession: Selected examples from the Karst region, southwest Slovenia ABSTRACT: Forests in Submediterranean Slovenia are threatened by wildfires every year. The article pre- sents the main characteristics of post-fire regeneration in the Karst area. The rate of succession was studied by comparing two burned sites with different periods after the last fire. Field plant sampling was used to determine the plant cover and species composition on each site. Vegetation characteristics were contrasted with nearby unburned sites. We found that the plant species composition of burned areas is similar to that of areas unaffected by wildfire, and that the monitored site has been colonised by specific pioneer plant species five years after the wildfire. KEY WORDS: biogeography, succession, wildfires, pioneer plant species, Kras plateau, Submediterranean Slovenia Po po žar na suk ce si ja: Izbra ni pri me ri rast lin ske suk ce si je na Kra su POVZETEK: Goz do ve obsre do zem ske Slo ve ni je vsa ko leto ogro ža jo poža ri. V pris pev ku pred stav lja mo glav - ne zna čil no sti obnav lja nja rast lin ske ga pokro va po gozd nih poža rih na Kra su. Preu če va li smo hitrost suk ce si je s pri mer ja vo dveh raz lič no sta rih pogo rišč. S te ren skim popi som smo dolo či li pokrov nost posa mez nih rast - lin skih pla sti in vrst no sesta vo. Zna čil no sti rast ja na izbra nih pogo riš čih smo pri mer ja li tudi z ne po go re li mi zem ljiš či v bli ži ni na ena kih rastišč nih pogo jih. Ugo tav lja mo, da je vrst na sesta va rast lins tva na pogo riš - ču podob na kot na nepo go re le mu zem ljiš ču in da so pet let po poža ru na pogo riš ču nase lje ne dolo če ne pio nir ske rast lin ske vrste. KLJUČNE BESEDE: bio geo gra fi ja, suk ce si ja, gozd ni poža ri, pio nir ske rast li ne, Kras, obsre do zem ska Slovenija Liza Stančič lizastanicic@gmail.com Blaž Repe Department of Geography, Faculty of Arts, University of Ljubljana blaz.repe@ff.uni-lj.si The paper was submitted for publication on March 31st, 2015. Uredništvo je prejelo prispevek 31. marca 2015. 28 58-1_02p_1942-Liza Stancic_acta49-1.qxd 12.9.2017 7:56 Page 28 1 Introduction The Submediterranean Slovenia is the country's most fire-threatened area due to the climatic, vegetation and anthropogenic factors. Wildfires usually affect the ground and soils, field and shrub layers in a woodland (Jakša 2002). After the event, the vegetation cover regenerates by the process of succession (Lovrenčak 2003). This paper presents the characteristics of post-fire succession in selected burned areas of the Karst region. Species composition of the various burned areas was examined and typical plant species were determined. Vegetation covers of two burned sites with different periods since the last fire were contrasted. In addi- tion, vegetation characteristics of the burned sites were compared to nearby unburned sites with similar habitat conditions. Changes in plant cover density and species composition through time were noted, as well as the presence of pioneer species. There has been a limited research on the dynamics of post-fire succession in Slovenia. Kovač (2012) examined three burned areas in Slovenian Istria that were affected by fire in a three-year interval. The veg- etation of burned sites consisted mainly of pioneer species. The field layer plant cover density was found to positively correlate with the period since the last fire. Geršič et al. (2014) compiled the characteristics of plant cover regeneration in specific environments – on point bars, rockfall material, screes, construc- tion pits and burned areas. They found a widespread presence of pioneer species. Time was highlighted as the most important factor of succession. Studies of post-fire succession in Mediterranean ecosystems in France (Capitanio and Carcaillet 2008) and California (Harvey and Holzman 2014) have shown that the highest species diversity on burned sites occurs two years after the wildfire. In Spain it was found that the most common species on burned sites are those that are adapted to wildfires (Quercus coccifera, Brachypodium retusuin) (Pausas et al. 1999). In South African Mediterranean-climate ecosystems the field layer cover is greatest one year after the wildfire, while the shrub layer requires more than three years for regeneration (Rutheford et al. 2011). Australian ecosystems recover after longer periods; the shrub and tree layers reach the pre-fire cover after 30 years of succession (Gosper, Yates and Prober 2013). 2 Succession and pioneer species Ecological succession is the process of vegetation cover regeneration following considerable changes in the environment. The process consists of a time specific sequence of animal and plant species replacing each other in a given area (Lovrenčak 2003; Kladnik, Lovrenčak and Orožen Adamič 2005). The most common classification of succession types is based on the starting position. Primary suc- cession takes place in areas where there are no soils, plants or animals (Kladnik et al. 2008). Secondary succession is a more common process that takes place in areas which had already been populated. Certain or most of the species in the community have been removed by a specific extraordinary event. However, other species along with the soil remain, so regeneration does not initiate on completely bare soil (Tarman 1992). Among others, secondary succession takes place on burned areas (Tivy 1993). Succession progresses over a distinctive sequence of stages. Characteristic plant and animal species are present at each successional stage. The early stages are dominated by fast-growing species that are adapt- ed to harsh habitat conditions and rapidly proliferate (Tarman 1992). These pioneer species stabilise the habitat with their extensive root systems and improve soil characteristics by adding organic material. In this way, colonisation of new species is enabled (Lovrenčak 2003). In the Submediterranean Slovenia, the majority of the most characteristic plant species have pioneer features. The wider study area has specific habitat conditions, species that thrive here require more light and heat, and can withstand limited rainfall as well as dry, shallow, skeletal soils. Hop hornbeam (Ostrya carpinifolia), flowering ash (Fraxinus ornus) and whitebeam (Sorbus aria) are plant species that often grow together on carbonate bedrock. They frequently form associations with autumn moor grass (Sesleria autum- nalis, Dakskobler, Kutnar and Zupančič 2014). Other pioneer species, which have modest habitat requirements and therefore promptly colonise degraded areas are common juniper (Juniperus communis), Paliurus spina-christi, blackthorn (Prunus spinosa), blackberry (Rubus spec. div.) and wild asparagus (Asparagus acu- tifolius) (Figure 1) (Kovač 2012). Acta geographica Slovenica, 58-1, 2018 29 58-1_02p_1942-Liza Stancic_acta49-1.qxd 12.9.2017 7:56 Page 29 Liza Stančič, Blaž Repe, Post-fire succession: Selected examples from the Karst region, southwest Slovenia 30 3 Wildfires Wildfires are defined as uncontrolled burning in the forest environment, spreading rapidly and causing damage (Pravilnik o varstvu gozdov 2009). Climate has the largest influence on their emergence and spread. Wildfires are most common in arid, warm, sunny and windy areas (Pečenko 2005). In Slovenia, wildfires are primarily a disturbance in the environment. They affect social, environmental and economic functions of forests. Aesthetic value of forested land is reduced. Forest animals, especially the micro- and mesofauna in the soil, are threatened. Species composition of the vegetation is changed. Timber resources are lost, which reduces financial profits from forests. Infrastructure located in forests as well as property in nearby settlements is at risk (Jakša 2006). Wildfires have significant effects on soil characteristics. A large proportion of organic material is burned therefore the organic horizons on burned sites are usually thinner (Urbančič 2002). Immediately after the wildfire nutrient availability increases due to the elements found in ashes and the release of minerals from the soil (Hernández, García and Reinhardt 1997). On the other hand, the removal or reduction of the veg- etation cover leads to decreased water retention, faster runoff, soil erosion and nutrient leaching which impedes succession (Gimeno-Garcia, Andreu and Rubio 2000; 2007). To improve soil characteristics and accelerate succession some studies suggest adding compost to burned sites (Cellier et al. 2014). Slovenian forests are classified into four levels of potential fire risk – very high, high, medium, and low (Jakša 2006). Of the fourteen forest management areas (GGO) Sežana is the most fire endangered (Poročilo…2014). The high fire risk of the Submediterranean Slovenia stems from physical as well as human geographical factors. The climate, with high temperatures and dry season, plays an important role. The car- bonate bedrock with great permeability reduces water retention, thus increasing drought and the probability Figure 1: Wild asparagus. L IZ A S T A N Č IČ 58-1_02p_1942-Liza Stancic_acta49-1.qxd 12.9.2017 7:56 Page 30 of forest fire occurrence. Strong winds, especially bora, contribute to the rapid spread of fires. Anthropogenic influence on the increased fire risk is manifested in the form of changes in natural vegetation; plantations of Scots pine (Pinus sylvestris) and black pine (Pinus nigra), both very susceptible to fires. The fire risk of the study area is further increased by transport corridors passing through, most notably the railway (Jakša 2002). 4 Methodology The rate of vegetation regeneration is influenced by several factors including soil, climate, slope, aspect, elevation, wind exposure, and various anthropogenic impacts such as afforestation (Geršič et al. 2014). This paper deals exclusively with the role of time; the study sites were chosen accordingly. The time period between wildfires and field observations was chosen according to similar research on ecological succession in the Mediterranean (Lloret 1998; Meira-Neto 2011). The Slovenian Forest Service provided the fire invento- ry, from which Kamarija, burned in 2009, and Podgovec, burned in 2013, were selected (Figure 2). The location of the older burned site was compared against locations of fires in later years to ensure that the selected site was not subsequently affected by fire. It was verified that the same forest association was pre- sent at both locations, suggesting similar habitat conditions and thus allowing a comparison of plant cover primarily with respect to time. No post-fire reconstruction was carried out at any of the selected locations. Direct influence of anthropogenic factors on succession was therefore minimised. In June 2014 four plant samplings were carried out – one on each selected burned site and one on an unburned site close to each study site (Figure 3; Figure 4). Vegetation characteristics of the unburned sites are assumed to be indicative of those of the burned study sites prior to the fire. The assumption is based on the comparable level and circumference of trees on sampling plots, indicating similar habitat condi- tions (Tivy 1993). Comparing the results of plant monitoring on burned sites with those on unburned sites allows an insight into the changes in land cover and species composition. The Braun-Blanquet method of plant sampling (Braun-Blanquet 1932) was used to determine abundance, cover and unity of each plant species Acta geographica Slovenica, 58-1, 2018 31 Kamarija Podgovec Content by: Liza Stanič Map by: Liza Stanič Source: GURS 2009; ZGS 2014 0 5 10 15 202.5 Kilometers Figure 2: Location of study sites. 58-1_02p_1942-Liza Stancic_acta49-1.qxd 12.9.2017 7:56 Page 31 Liza Stančič, Blaž Repe, Post-fire succession: Selected examples from the Karst region, southwest Slovenia present (Lovrenčak 2003). The method is enables quick and accurate vegetation sampling as well as an analysis of species-habitat relationships (Wikum and Shanholtzer 1978). Species were identified using botan- ical identification keys (Pintar and Wraber 1990; Lippert 2000; Fletcher 2007; Schauer 2008; Lang 2013). 32 Content by: Liza Stanič Map by: Liza Stanič Source: GURS 2009; ZGS 2014 0 50 100 150 20025 Meters Legend Burned site 2009 Unburned site Figure 3: Locations of sampling plots at Kamarija. Content by: Liza Stanič Map by: Liza Stanič Source: GURS 2009; ZGS 2014 0 50 100 150 20025 Meters Legend Burned site 2013 Unburned site Figure 4: Location of sampling plots at Podgovec. 58-1_02p_1942-Liza Stancic_acta49-1.qxd 12.9.2017 7:56 Page 32 5 Characteristics of selected burned sites The study burned sites are located in the GGO Sežana in the south-western Slovenia. They lie on the Karst Plateau, where the bedrock is made of permeable Cretaceous limestone (Jurkovšek 2014). The terrain is levelled and no surface watercourses are present (Natek and Natek 2008). The climate is Submediterranean with high summer daytime temperatures and droughts due to the permeable bedrock. Owing to its loca- tion on the border between Mediterranean and continental influences, the region is characterised by strong winds, most notably the north-eastern bora wind (Senegačnik 2012). The most common soil types are redz- inas, chromic cambisols and the region's typical red soil (terra rossa). Natural vegetation has been almost completely removed by intensive logging in the past. Systematic attempts to afforest the barren surface with black pine (Pinus nigra) began in the 19th century (Urbančič, Ferlin and Kutnar 1999; Zupančič and Žagar 2008). Efforts have been successful and today anthropogenic black pine plantations are one of the most common forest associations in the Karst region (Senegačnik 2012). The forest association on both study sites was found to be hop hornbeam with Sesleria autumnalis (Seslerio-Ostryetum) which was at the oldest development stage prior to the fire (ZGS 2009–2013; 2014). This forest association is typical for karst as it thrives on dry, sunny and warm sites with shallow soils on carbonate bedrock (Dakskobler, Kutnar and Zupančič 2014). The older burned study site is Kamarija. It is located north of the town of Sežana, approximately 500 m south of the village Krajna vas along the Dutovlje–Pliskovica road. The second burned study site is Podgovec, which is located northeast of Sežana, 1 km southwest of the village Kreplje along the Sežana–Dutovlje railway line. Selected characteristics of the burned areas are presented in Table 1. Table 1: Selected characteristics of burned study sites (ZGS 2009–2013; 2014). Burned area Kamarija Podgovec Location 45° 45' 50.48'' N 13° 48' 24.01'' E 45° 44' 5.9'' N 13° 49' 55.11'' E Altitude (m) 265 260 Exposition NW N Slope (°) 5 6 Date of fire event 14/04/2009 22/07/2013 Extent of burned area (ha) 2.25 2 Cause of fire Unknown Communications (train) Type of fire Surface Surface Post-fire reconstruction No No 6 Vegetation characteristics of studied burned sites The results of the vegetation monitoring on burned sites were compared with the results from unburned sites nearby. Plant cover characteristics were examined by determining the species composition, abundance, cover and unity according to the Braun-Blanquet method. 6.1 The Kamarija burned site The Kamarija burned site is separated from the comparative unburned site by a firebreak and a distance of 245 m. From this it can be assumed that the comparative unburned site was not affected by the fire that burned the study site (Figure 5). The stoniness amounts to 5% on both sampling plots. The comparison of tree height and breast height circumference returns no significant differences between the burned and unburned site (Table 2). Similar tree heights and circumferences on both sites suggest analogous habitat conditions (Tivy 1993), justifying the comparison between the two sites. The differences in vegetation characteristics can be largely attrib- utable to effects of the fire. Acta geographica Slovenica, 58-1, 2018 33 58-1_02p_1942-Liza Stancic_acta49-1.qxd 12.9.2017 7:56 Page 33 Liza Stančič, Blaž Repe, Post-fire succession: Selected examples from the Karst region, southwest Slovenia Table 2: Comparison of the breast height circumferences and the heights of trees on the Kamarija burned site and unburned comparative site. Burned site Unburned site Mean tree circumference (cm) up to 50 50–100 Mean tree height (m) 10–20 10–20 Greatest tree circumference (cm) 155 97 Greatest tree height (m) 24 20 The comparison of vertical vegetation layers covers reveals differences between sampling plots (Table 3). The biggest discrepancies between the burned and unburned sites are in the shrub layer covers – 5% on the burned site compared to 30% on the unburned site. Small differences were recorded in the tree layer covers. Table 3: Comparison of vertical vegetation layer covers on the Kamarija burned site and comparative unburned site. Burned site Unburned site Cover of specific vertical Tree layer 50 60 vegetation layers on Shrub layer 5 30 sampling plots (%) Field layer 95 95 Total 150 185 The burned site tree layer is dominated by flowering ash (Fraxinus ornus) and sessile oak (Quercus petraea). Both species are also present on the unburned site, but black pine (Pinus nigra) has the greatest cover, abundance and unity. The shrub layer consists of similar species as the tree layer with the addition of common juniper (Juniperus communis). On the burned site, blackberry (Rubus spec. div.) and common privet (Ligustrum vulgare) were also recorded in the shrub layer. The herb layer species composition is similar on both sampling plots. The most common species on both sites is tor-grass (Brachypodium pinnatum). Cirsium pannonicum is also present in an equal extent on both sampling plots. Other abundant plant species on the burned site are common tormentil (Potentilla erecta) and orchard grass (Dactylis glomerata). In contrast, the abundant species on the unburned sites are yellow salsify (Tragopogon dubius), Leucanthemum ircutianum, meadow clary (Salvia pratensis), purple-globe clover (Trifolium alpestre) and hedge bedstraw (Galium mollugo). 6.2 The Podgovec burned site The fire on the Podgovec burned area occurred 11 months prior to the vegetation monitoring. The plot chosen to provide the comparative vegetation characteristics is located 280 m away from the study site and 34 Figure 5: Kamarija burned site (left) and unburned comparative site (right). L IZ A S T A N Č IČ 58-1_02p_1942-Liza Stancic_acta49-1.qxd 12.9.2017 7:56 Page 34 separated by a railway line. Due to these characteristics it can be assumed that the comparative site was not affected by the fire (Figure 6). Traces of fire are clearly visible on the burned site – tree trunks are scorched to a height of 3.5 m, the forest floor is covered with remains of charred twigs and cones. The stoniness on the burned site is 15% compared to 10% on the unburned site. There are no notable differences in tree height and circumference between the two sampling plots (Table 4). This suggests sim- ilarity of habitat conditions, allowing for a meaningful comparison of vegetation characteristics. Table 4: Comparison of the breast height circumferences and the heights of trees on Podgovec burned site and unburned comparative site. Burned site Unburned site Mean tree circumference (cm) over 100 50–100 Mean tree height (m) over 20 over 20 Greatest tree circumference (cm) 142 128 Greatest tree height (m) 30 26 The analysis of differences in tree height and circumference was followed by the comparison of spe- cific vertical vegetation layers covers (Table 5). The difference in tree layer cover between the burned and unburned site is minor. As result of the fire, the shrub layer is considerably sparser. On the burned site its cover amounts to only 5%, while on the unburned site it is 30%. Field layer cover is also noticeably lower on the burned than on the unburned site. From the comparison with the unburned site it can be assumed that prior to the fire the field layer covered almost the entire sampling plot, while following the fire its cover is reduced to less than one third. The moss layer covers 5% of the unburned site but is not present on the burned site. Table 5: Comparison of vertical vegetation layer covers on the Podgovec burned site and comparative unburned site. Burned site Unburned site Cover of specific vertical Tree layer 50 60 vegetation layers on Shrub layer 5 30 sampling plots (%) Field layer 30 95 Moss layer 0 5 Total 85 190 The analysis of species composition revealed that black pine (Pinus nigra) dominates the tree layer on both sampling plots. The species has a lower cover on the burned site (50%) compared to the unburned site (65%) due to fire damage to lower branches. The burned site shrub layer consists mainly of blackthorn (Prunus spinosa) and flowering ash (Fraxinus ornus). All scrubs have bare scorched branches with no leaves. Acta geographica Slovenica, 58-1, 2018 35 Figure 6: Podgovec burned site (left) and unburned comparative site (right). L IZ A S T A N Č IČ 58-1_02p_1942-Liza Stancic_acta49-1.qxd 12.9.2017 7:56 Page 35 Liza Stančič, Blaž Repe, Post-fire succession: Selected examples from the Karst region, southwest Slovenia Some flowering ash scrubs have young shoots at the base. The shrub layer is more diverse on the unburned site. In addition to the blackthorn and flowering ash, there are common juniper (Juniperus communis), blackberry (Rubus spec. div.) and sessile oak (Quercus petraea). The burned site field layer is patchy, com- prising tor-grass (Brachypodium pinnatum), blackberry (Rubus spec. div.) and wild asparagus (Asparagus acutifolius). On the comparative sampling plot the field layer is more uniform. Besides the species present on the burned site, it is made up of Melittis melissophyllum, Helleborus odorus and ivy (Hedera helix). 7 Findings about post-fire vegetation regeneration The results of vegetation monitoring demonstrate that ecological succession of burned areas occurs rapid- ly. The fire-affected Podgovec site can be clearly distinguished from unburned surrounding areas. The extent of the fire is clearly demarcated by a sparse field layer, scorched tree trunks and charred plant remains on forest floor. Three years after a wildfire Kovač (2013) found advancing vegetation recovery, however the burned site could still be clearly distinguished from unburned sites. The Kamarija site, which had been burned five years before the monitoring, can hardly be differentiated from adjacent unburned areas. The differences become apparent only after analysing the results of vegetation monitoring. Five years of eco- logical succession are therefore sufficient for plant cover regeneration to such an extent that burned sites are visually indistinguishable from the surrounding area. A possible explanation for the quick recovery is the wildfire type that occurred on study sites because the surface fire damaged only the field and shrub lay- ers. Studies in Spain showed that if all vegetation layers are removed the colonisation of tree individuals takes at minimum 25 years (Röder et al. 2008). In Mediterranean-climate ecosystems the field layer regen- erates after two years (Pausas etal. 1999; Rutheford etal. 2011), and the shrub layer after 10–15 years (Capitanio and Carcaillet 2008). Analysis of vertical vegetation layers suggests that the cover is greater on older burned areas. The total vegetation cover is 85% at the Podgovec site compared to 150% at the Kamarija site. These differences arise mainly due to the covers of field layer. Both of the burned area plot sites have similar tree and shrub layer covers – 50% and 5% respectively. The field layer, on the other hand, covers 30% of the plot site at Podgovec and 95% at Kamarija. This points to the conclusion that the field layer cannot regenerate to the pre-fire state in one year. However, in five years the field layer returns to its original extent, while the shrub and tree layer covers remain constant. The comparison of vertical vegetation layers covers at the Kamarija site with unburned nearby areas suggests that five years are not sufficient for the regeneration of tree and shrub layers. In addition to vegetation layers covers, this paper examines burned area species composition, focus- ing on the presence of pioneer plant species. Vegetation sampling found similar species on burned sites and nearby unburned sites. This is in line with studies showing demonstrating that species composition of burned sites is affected by adjacent sites (Keeley, Fotheringham and Baer-Keeley 2005). Typical species of burned sites in Slovenian Istria are aspen (Populus tremula), flowering ash (Fraxinus ornus) and downy oak (Quercus pubescens) (Geršič et al. 2014). Our monitoring found a different species composition. On the Podgovec burned site the following pioneer species were detected: flowering ash (Fraxinus ornus), black- thorn (Prunus spinosa), wild asparagus (Asparagus acutifolius) and blackberry (Rubus spec. div.). The same species were also present on the comparative plot. Well-known pioneers flowering ash (Fraxinus ornus) and common juniper (Juniperus communis) were found both on the Kamarija burned site and the near- by unaffected area. Hop hornbeam (Ostrya carpinifolia), blackberry (Rubus spec. div.) and common privet (Ligustrum vulgare) are exceptions because they were recorded only on the Kamarija burned site but are not present on the comparative unburned site. 8 Conclusion Wildfires frequently threaten specific areas particularly in Submediterranean Slovenia. Nevertheless, few geographic studies of post-fire plant succession have been conducted. This paper presents the main find- ings derived from field plant sampling on two selected burned areas in the Karst region. The sampling was carried out using the Braun-Blanquet method. To assess the changes in vegetation characteristics on burned 36 58-1_02p_1942-Liza Stancic_acta49-1.qxd 12.9.2017 7:56 Page 36 areas compared to the state before the wildfire, plants were sampled on comparable unburned areas near- by. Species composition and plant cover densities of individual vertical vegetation layers were recorded. The surface fire affected the selected areas. This type of wildfire damaged the ground, field and shrub vegetation layers. The tree layer remained largely intact except for the lowest branches. The time span between burned areas discussed is five years. In this time, the field layer regenerated to the extent comparable to the unburned area. The plant cover density of the shrub layer remains more modest than before the wild- fire even after five years. The plant species composition of burned areas is similar to that of areas unaffected by wildfire. Five years after the wildfire the monitored site has been colonised by specific pioneer plant species such as hop hornbeam (Ostrya carpinifolia), blackberry (Rubus spec. div.) and wild privet (Ligustrum vulgare). Due to specific habitat conditions with dry, warm and sunny climate, and shallow, rocky soils, many common Submediterranean plant species are classified as pioneers. It is therefore typical for both burned and unburned areas to contain pioneer plant species. Furthermore, surface fires have little effect on higher vertical vegeta- tion layers so there is little change in the insolation of the site. Consequently, there is no mass colonisation of pioneer species, only individual plants are present. 9 References Braun-Blanquet, J. 1932: Plant sociology, the study of plant communities. New York. 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Razprave SAZU 49-1. 38 58-1_02p_1942-Liza Stancic_acta49-1.qxd 12.9.2017 7:56 Page 38 Acta geographica Slovenica, 58-1, 2018, 39–47 THE GEOGRAPHICAL POSITION OF THE TOWN OF RASA BASED ON PORPHYROGENITUS AND MEDIEVAL MAPS Mirko Grčić, Ljiljana Grčić, Mikica Sibinović Detail from an anonymous military map of the Balkans from 1395 (Oračev 2005). 58-1_03p_1949-Mirko Grcic_acta49-1.qxd 12.9.2017 7:57 Page 39 40 DOI: https://doi.org/10.3986/AGS.1949 UDC: 911.375(497.11Rasa)(091) 912.43(497.11Rasa)(091) COBISS: 1.01 The geographical position of the town of Rasa based on Porphyrogenitus and medieval maps ABSTRACT: The town of Rasa was mentioned in the tenth-century work De administrando imperio by Constantine VII Porphyrogenitus. The significance of this town in the Middle Ages is indicated by the fact that this toponym appears on old maps created by the greatest European cartographers from the fif- teenth to nineteenth centuries. Based on cartographic and historical geographical sources, this paper considers various perceptions and texts connecting the town of Rasa with today's town of Ražanj or with the medieval Serbian capital Ras. The subject treated is historical social geography. Five types of sources were used for the historical geography of the Balkans: old maps, chronicles, geographical nomenclature, archeological findings, and ethnographic findings. Based on written sources, geographical names, and geographical logic, the authors provide their own conclusions about the geographical position of the town of Rasa. KEY WORDS: geography, old maps, geographical names, Rasa, Ras, Serbia Geografska lega mesta Rasa na podlagi Porfirogenetovih zapisov in srednjeveških zemljevidov POVZETEK: Mesto Rasa je prvič omenjeno v delu De administrando imperio, ki ga je v 10. stoletju napisal Konstantin VII. Porfirogenet. Na pomembnost mesta v srednjem veku kaže dejstvo, da se ta toponim pojavlja na zemljevidih, ki so jih med 15. in 19. stoletjem izdelali največji evropski kartografi. Na podlagi karto - grafskih in zgodovinskih geografskih virov so v članku obravnavana različna mnenja in besedila, ki Raso povezujejo z današnjim mestom Ražanj ali s srednjeveško srbsko prestolnico Ras. Glavna tema je zgodo - vinska družbena geografija. Za zgodovinsko geografsko obravnavo Balkana so avtorji uporabili pet vrst virov: stare zemljevide, kronike, geografska poimenovanja, arheološke najdbe in etnografske izsledke. Na podlagi pisnih virov, geografskih imen in geografske logike avtorji predstavijo lastne ugotovitve o geograf - ski legi mesta Rasa. KLJUČNE BESEDE: geografija, stari zemljevidi, geografska imena, Rasa, Ras, Srbija Mirko Grčić, Ljiljana Grčić, Mikica Sibinović University of Belgrade, Faculty of Geography, mirko@gef.bg.ac.rs, mirko.grcic@yahoo.com, msibinovic@gef.bg.ac.rs The paper was submitted for publication on April 5th, 2016. Uredništvo je prejelo prispevek 5. aprila 2016. Mirko Grčić, Ljiljana Grčić, Mikica Sibinović, The geographical position of the town of Rasa based on Porphyrogenitus … 58-1_03p_1949-Mirko Grcic_acta49-1.qxd 12.9.2017 7:57 Page 40 41 Acta geographica Slovenica, 58-1, 2018 1 Introduction Localization of geographic places mentioned in historical sources is an important goal of historical geo- graphical research (Gašperič 2007; 2010; Kladnik and Pipan 2008; Vuolteenaho and Berg 2009; Vuolteenaho and Ainiala 2010; Douglas 2014; Fuchs 2015). In Constantine Porphyrogenitus' work De administrando imperio, chapter 32 contains the first mention of the town of Rasa. Namely, in the second Serbian-Bulgarian conflict in »the later period of the reign of Boris around 887 AD,« Boris had made peace with the Serbs, »who escorted him to the border, to Rasa« (Greek: έωζτήζ ͑Ράσης; Vizantijski izvori … 2007, 52). Some authors are uncertain whether this refers to Ras or Rasa. This study uses cartographic and historical sources to determine the location of Rasa, which Porphyrogenitus mentioned as a border town between Serbia and Bulgaria. This is an important question because in the toponymy of medieval Serbia there is the pho- netically similar toponym Ras, which was the capital of the medieval Serbian state of Raška, which also has not been precisely located (Grčić and Grčić 2012; 2014). 2 Theoretical framework The development of historical geography has raised awareness of four sources used in that discipline: 1) old chronicles, 2) ethnography, 3) geographic nomenclature, and 4) archaeology (Grčić and Grčić 2012; 2014). The Polish academy member Tadeusz Kotarbiński, who created »practicology« (or the »science of good work«), recommends that one not observe an object constantly through the same window, but look at it each time from another perspective (Trubačov 2006). This means that one should perceive the meaning of a certain toponym and its logical connection with the geographical area, ethnography, linguistics, writ- ten historical documents, cartographic sources, and archeological artifacts. The value of toponyms as a historical source lies in their relationship with the territory; that is, with the geographical map. Here arises a general question posed by Harley (1990): should a map be understood in a traditional way, as a reflection of the real world, or in the postmodern sense, as graphic language that needs to be decoded at the appropriate time and in a spatial context? In the second case, which is more appropriate for mod- ern conceptions, the map should be considered within the context of historical facts, geographical principles, and maps of a given space and time. Without sufficient evidence, especially cartographic evi- dence, researchers can only point to some assumptions. For example, maps of the Roman provinces transmitted knowledge and expression of remembrance of political traditions more effectively than historical texts (Ćirković 1991). 3 Methods Maps have long been very important to historical geography and the history of cartography, but they were rarely treated as a historical source in the reconstruction of the past (Gašperič 2007; 2010; Kladnik and Pipan 2008). In the development of cartography, there is a visible division between the »decorative« and »scientific« phases of mapping, but Harley (1990) recognized this division as a myth. Old maps have many pieces of information that are not precise and do not represent the only real picture of reality. Maps are socially constructed images of real space in social, political, and cultural contexts and a mirror of the skills and perceptions of the cartographer. This means that a particular map has to be returned to the past and situated in its proper period and place, or even culture (Fürst-Bjeliš and Zupanc 2007). When discussing a map as a text, Harley (1990) points out three aspects of the context: 1) the context of cartographer, 2) the contexts of other maps, and 3) the context of society. For this reason, it is necessary to use a compar- ative method and geographical logic in attempting to identify the Rasa mentioned by Porphyrogenitus in the tenth century. This toponym is studied by comparing selected maps from different times and cultures (see Table 1). In addition to maps, we examined texts by Constantine Porphyrogenitus, the priest of Doclea (Duklja), and some Byzantine and church documents from Antiquity and the Middle Ages. We also considered the opinions of some prominent scholars about the genesis and geographic position of the toponyms Ras and Rasa. 58-1_03p_1949-Mirko Grcic_acta49-1.qxd 12.9.2017 7:57 Page 41 Table 1: Toponyms on old maps denoting the position of Rasa near today's town of Ražanj. Cartographer Map name, place, and year of publication Toponym anonymous* *Military map of the Balkans, 1395–1396 Rossia JacoboCastaldo* Romanie (quae olim Thraciae dicta), Vicinuorumq(ue) regionum, uti Bulgariae, Rezuna Walachiae, Syrfiae etc descriptio, 1584 Gerard Mercator* Walachia. Servia. Bulgaria. Romania; Duisburg, 1589 Resigne G. Cantelli***** Map of Serbia (Rome, G. Rossi), 1689 Razena alt (ats), Rasna Giacomo Cantelli da Vignola* La Bulgaria e la Romania com Parte di Macedonia, Roma, 1689 Rasna Pierre Mortier**** Carte Nouvelle de la Mer Mediterranee, Amsterdam, 1694 Rasena Johann Georg Schreiber* Carte von Romanien mit dennes Dardanelen, Bulgarien und Servien. Leipzig, Raszna end of the seventeenth century MatthäusSeutter* Transylvaniæ, Moldaviæ, Walachiæ, Bulgariæ nova et accurata delineatio; eighteenth Razena century, Augsburg Guillaume Delisle*1 Imperii Orientalis et circumjacentium regionum sub Constantino Porphyrogenito Rhazen et ejuspraedecesforibusDescriptio, made after 1718 Christoph Weigel* Regiones Danubiæ, Pannoniæ, Dacia, Moesiæ cum Vicino Illyrico, studio Christoph; Razena Nuremberg, 1719 Guillaume Delisle* Nova et accurata Regni Hungariæ Tabula, ad usum Serenissimi Burgundiæ Ducis, Razena first quarter of the eighteenth century MatthäusSeutter*** Regnorum et Provinciarum Dalmatia, Croatia, Sclavonia, Bosnia, Servia, Istria et Reip, 1709 Rasena anonymous* Parte della Transilvania, Parte della Banato, Parte della Servia, Parte della Bulgaria, Valachia Rasna Imperiale, Valachia Thurca, 1717–1737 Johann Matthias Hase* Hungariæ, Propriæ, Croatie, Dalmatiæ, Bosniæ, Serviæ, Bulgariæ, Cumaniæ, Principatum: Rasen, Rasna Transsylvanniæ, Despotatus: Walachiæ, Moldaviæ; Nuremberg, 1744 Antonio Zatta* Turchiad'Europa. Divisa Nelle sue Provincie e Governi. Di nuova Proiezione; Venice, 1782 Rozena F. Müller***** Map of Serbia, Vienna, Artaria, 1788 Razena, Ratzana Sources: * Oračev 2005; *1 Ehrenberg, E. R. 2006 (National Geographic); **Nikolić 1983; *** Marković 2002; **** Schüler 2010; ***** Srejović 1991. 4 Research findings 4.1 Historical geography of Rasa According to Castellan (1999) »between 867 and 874, the Serbs were under the control of the Byzantine church. The Serbs, who settled in the territory of Raška, between the Drina and Morava Rivers …«. Near Varvarin (the village of Gornji Katun) was found one of the oldest monuments of Slavic literacy in Serbia and in the Balkans (from the ninth or tenth century): the Temnić inscription (Ivić 1986; Stojanović 1913). In a rel- atively small area between Stalać and Ražanj, on the slopes of the Mojsinje Mountains (Mojsinjske planine) and Poslon Mountains (Poslonske planine), there are a large number of churches and monasteries (includ- ing the ruins of seventy churches and hill forts); this area is known as Holy Mount Mojsinje (Mojsinjska Sveta gora). St. Roman's Monastery, which was founded in the second half of the ninth century, located seven kilometers south of the town of Ražanj (in the Niš District), also has significant cultural and histor- ical value. The monastery was mentioned in a grant issued by Byzantine Emperor Basil II to the Archbishopric of Ohrid in 1020, in which it is recorded as Sfenteroman (Janićijević 1998; Živić 2006; Dumić, Đokić and Stević 2006). A charter issued by Byzantine Emperor Basil II to the Archbishopric of Ohrid in 1020, and confirmed by Emperor Michael Palaeologus in 1272, mentions among other things Raška or the Raska eparchy or diocese (Greek: τὸν δὲ ἐπίσϰοπον Ράσον – tὸn dὲ ἐpisϰopon Rason). The mere fact that the town was the seat of a bishop indicates that it was a remarkable town in a good transport position. Some Bulgarian and Russian authors from the second half of the nineteenth century thought that this referred 42 Mirko Grčić, Ljiljana Grčić, Mikica Sibinović, The geographical position of the town of Rasa based on Porphyrogenitus … 58-1_03p_1949-Mirko Grcic_acta49-1.qxd 12.9.2017 7:57 Page 42 43 Acta geographica Slovenica, 58-1, 2018 to Ras near today's town of Novi Pazar on the Raška River, which flows into the Ibar (Golubinskij 1871; Drinov 1971). Based on the Escorial Taktikon – a list of offices that arose from the need to administer the newly con- quered provinces of Bulgaria at the time of John Tzimiskes (969–975) in the official administration of Byzantium Stanković (2002) points out that to the west there was an administrative unit with its center in Ras. The existence of this administrative unit remained recorded only thanks to a seal by John, the katepan of Ras (Nesbit and Oikonomides 1991). In Greek, a katepanat was a large territory in a border zone that included several themes (administrative units) in which civilian and military power was exercised by a katepan. The katepan (or dux) was a title carried during the Roman and Byzantine period by military comman- ders in a province (Touati 2007). The theme of Morava was also established; this was led by Adralest Diogenes and was located near the confluence of the Morava and Danube Rivers, at the site of the ancient fort called Horreum Margi (Stanković  2002; Pirivatrić  1997). According to Živković (2007), Byzantine seals (Protospatharios John, katepan of Ras, as well as the seal of Adralesta Diogenes, a protospatharios and strate- gist of Morava), are the most reliable indicator that Byzantine reign was established in this border area. The town of Rasa, mentioned at the end of the ninth century, is identified by some authors with Ras, the capital of Stefan Nemanja's Serbia in the second half of the twelfth century (Novaković 1877). Only at the end of the nineteenth century did Ras (i.e., Apostles Peter and Paul Church, which was known to be located in Ras) appear on maps drawn near Novi Pazar (the Austrian military map from 1900). In 1859, the Russian historian Alexander Hilferding, on his way through Old Serbia, thought that he recognized the town of Ras about seven kilometers west of Novi Pazar, in the ruins known as Gradina near Pazarište, near where the Sebečevska River empties into the Raška River. »I have no doubt that these ruins are in fact the old town of Ras, about which a lot was said in ancient Serbian history« (Hilferding 1868cv: Hilferding 1972, 134). According to Ćirković, »although the arguments were insufficient, many scholars (Konstantin Jireček, Stojan Novaković, Jovan Cvijić) agreed with Hilferding's opinion, and so over time identifying Ras with one of the many fort ruins was generally accepted as unproblematic« (Ćirković 1997, 425). It is usually assumed that Ras was several kilometers from Novi Pazar, at a place called Pazarište or Eski Pazar (i.e., ‘old Pazar’). »Here, however, are no ruins« (Dinić 1978, 80). Kalić raises the possibility that the place called Race referred to Arsa (Kalić 1988). According to Ćirković, »It is more likely that this Rasa in the country of Michael or Vlastimir, the successors of Boris, is identical to the fortress (Greek: φρούριον) at Arsa (Greek: Αρσα), which according to the narratives of Procopius was rebuilt by Emperor Justinian in the province of Dardania« (Ćirković 1997, 424). However, the attention of European medieval cartographers was directed toward a town with a similar name, which was located near the present town of Ražanj. 4.2 The toponym Rasa on old geographic maps The old Roman military road (Latin: Via Militaris) known as the Moravian road led through the Roman town of Arsena, where Justinian built a fortress (Jireček 1959). Along the route of the public road (Latin: Via Publica), in the village of Novi Bračin north of the town of Ražanj, there was an ancient settlement called Præsidium Dasmini. The ancient settlements of Præsidium Dasmini and Præsidium Pompeiare shown on the Tabula Peutingeriana, a Roman itinerary map (SegmentumVII; Figure 2). In the centre of the north- ern part of the Aleksinac Basin was Mutatio Cametas, today's town of Ražanj. Felix Kanitz mentioned this as an important point on the route of the ancient Moravian road (Rašković 2002). Separating the last syllable from the word Arsena yields the name Arsa. It can be assumed that the name Rasa is a translation of the Greek word Arsa; today's Raša River in the Istria Peninsula in northwest Croatia was called Arsa in Roman times. The Slavic name Rasena or Rasna undoubtedly inherited the ancient name of the town, Arsena. It seems, however, that the ancient toponym Arsena signified some kind of art or skill. The etymology of the word rasa can be connected with a place of ecclesiastical authority. According to the Bulgarian terminology dictionary (Bălgarski tolkovski rechnik 2013), raso refers to the black, wide, long upper garments of an Orthodox priest. In Greek, rason designates the large wide-sleeved clothing worn by priests and Byzantine church monks (Touati 2007). According to the Klaić dictionary (1970), ras means ‘prince’. Thus, the name Raška could mean ‘principality’. Mihailo Dinić ruled out the possibility that the name of the mediaeval state of Raška came from the name of the town of Ras (Dinić 1966). The place called Rasa was not precisely localized, its name is only known in the form in which it appears in Porphyrogenitus' work (Greek: Ράσης). Porphyrogenitus reported that Rasa was a border crossing between 58-1_03p_1949-Mirko Grcic_acta49-1.qxd 12.9.2017 7:57 Page 43 Figure 1: Part of the military map of the Balkans (Oračev 2005). Figure 2: Fragment of the Tabula Peutingeriana (Segment 7; Sectors 3, 4) (Weltkarte des Castorius, genannt die Peutingersche Tafel 1888). Serbia and Bulgaria. The map by the prominent French cartographer Guillaume Delisle, »Eastern Empire and Neighbouring Regions According to Constantine Porphyrogenitus«, shows Rasa (German: Ratzen) on the Serbian-Bulgarian border, but on the Bulgarian side (Grčić and Grčić 2012, 8). According to Dinić (1966), it should not be excluded that Porphyrogenitus' Rasa belonged to Bulgaria. In any case, it is a border fortress between the two countries (Grčić and Grčić 2014). 44 Mirko Grčić, Ljiljana Grčić, Mikica Sibinović, The geographical position of the town of Rasa based on Porphyrogenitus … 58-1_03p_1949-Mirko Grcic_acta49-1.qxd 12.9.2017 7:57 Page 44 3.1. Rhazen (Guillaume Delisle, Eastern Empire and surrounding regions according to Constantine Porphyrogenitus, 1718). 3.2. Rasena (Guillaume Delisle, Map of the Hungarian Kingdom, first quarter of the eighteenth century). 3.3. Rasen, Rasna (Johann Matthias Haas, Map of Hungary and part of Croatia, Dalmatia, Bosnia, Serbia, Bulgaria, 1744). 3.4. Razena (Mattheus Seutter, Map of Transylvania, Moldavia, Walachia, Bulgaria, beginning of the eighteenth century). 3.5. Raszna (Johann Schreiber, Map of Romania with the Dardanelles, Bulgaria and Serbia, end of the seventeenth century). 3.6. Razena alt (ats), Rasna (Giacomo Cantelli da Vignola, Map of Serbia, 1689). Figure 3: Details of several medieval maps showing what is today Ražanj (Vignola 1689; Delisle 1711; Haas 1744). 45 Acta geographica Slovenica, 58-1, 2018 58-1_03p_1949-Mirko Grcic_acta49-1.qxd 12.9.2017 7:57 Page 45 46 For this discussion, the military map (Figure 1) is of particular importance. It is the work of an anony- mous author and is kept by the National Library in Paris in the Pauli Sanctini manuscript (Codex Latinus Parisinus, register number 7239). This map shows a large part of the Balkan Peninsula, from Belgrade to Istanbul. Estimated on the basis of the Ottoman flags, the possible time of creation of this map is 1395 or 1396 (Beševliev 1963; Oračev 2005). Fortified towns are represented in the form of vignettes. North of the city of Niš is shown a fortified town called Rossia (or Rassia; Figure 1). On this map, the name Rossia is printed on the approximate territory of today's town of Ražanj, as well as on many other old maps (Table 1). On this map, the town of Rasa is shown as a border town in Serbia, and on the other side of the gorge is written Bulgaria. In the fourteenth century in a nearby gorge, between Mounts Ozren and Rtanj, was the Bulgarian-Serbian border (Jireček 1959). The map is striking with its cartographic projection because it reveals some parallels with the Roman itinerary map Tabula Peutingeriana (Figure 2). There are almost no old maps showing the Morava River from the end of the fourteenth century until the twentieth century that do not show a place called Rasen, Rasena, Razena, Rozena, Rasna, Raszna, Resigne, Rhazen, and finally Ražanj (Table 1 and Figure 3). Medieval maps are characterized by the similarity of the location of this place in regard to the relief and river flows (Figure 3). Some data from this and other old medieval maps can possibly provide the key for understanding the localization of the ninth-century border town of Rasa. 5 Conclusion The historiographical text by Byzantine Emperor Constantine VII Porphyrogenitus, De administrando impe- rio, provides a testimony about the geography of settlements in the Balkan Peninsula in the second half of the ninth century and first half of the tenth century. This article addresses the border town of Rasa. Many scholars (Dinić, Ćirković, Kalić) have doubted the traditional theory of the precise location of the place. The issue may be resolved by old maps. Particular support in this regard may be maps created by promi- nent cartographers from the end of the fourteenth century to the end of the eighteenth century. This paper points to Ražanj, which could be the border town of Rasa (Rasen), which was mentioned by Porphyrogenitus as a place near the Serbian-Bulgarian border. ACKNOWLEDGEMENT: This paper is the result of research within project no. 176017 funded by the Ministry of Education and Science of the Republic of Serbia. 6 References Bălgarski tolkovski rechnik, 2013. Nauka i izkustvo. Sofija. Beševliev, V. 1963: Eine Militärkarte der Balkanhalbinsel aus den letzen Jahren des 14. Jahrhunderts. Balkansko ezikoznanie 7-2. Castellan, G. 1999: Histoire des Balkans. Paris. Ćirković, S. 1991: Svedočenje karte. 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EDITORS: Nika Razpotnik Visković Blaž Komac 58-1-Special issue_04p_5170-Nika Razpotnik-uvodni_acta49-1.qxd 12.9.2017 7:57 Page 49 50 58-1-Special issue_04p_5170-Nika Razpotnik-uvodni_acta49-1.qxd 12.9.2017 7:57 Page 50 Acta geographica Slovenica, 58-1, 2018, 51–57 AgrICULtUrE In modErn LAndSCAPES: A fACtor hIndErIng or fACILItAtIng dEvELoPmEnt? Nika Razpotnik Visković, Blaž Komac Suburbanization at the expense of farmland: the example of the Ljubljana Marsh. B O JA N E R H A R T IČ 58-1-Special issue_04p_5170-Nika Razpotnik-uvodni_acta49-1.qxd 12.9.2017 7:57 Page 51 Nika Razpotnik Visković, Blaž Komac, Agriculture in modern landscapes: A factor hindering or facilitating development? 52 DOI: https://doi.org/10.3986/AGS.5170 UDC: 911.53:631(497.4) 711.3(497.4) COBISS: 1.02 Agriculture in modern landscapes: A factor hindering or facilitating development? ABSTRACT: Agriculture plays an important role in both protecting and developing farmland. In Slovenia, the main reasons for this loss are urbanization and the implementation of large development projects that require the destruction of fertile farmland. About 3000 ha of farmland has been lost each year since Slovenia’s independence. The importance of agriculture and farmland is touched upon in this special issue of Acta geographica Slovenica. The authors focus on management of farmland, analyse the development poten- tial for agriculture, observe the changes in the landscape by remote sensing, soil quality and its pollution, and land cover as an element of biodiversity. They draw attention to the lack of participation in spatial planning procedures and the question of the importance of agriculture and jobs in this sector in nation- al economy. This introductory paper brings a short analysis of how the issue of farms’ spatial constraints and moving farm structures to new locations is perceived by municipal offices, nature parks, and the Slovenian Chamber of Agriculture and Forestry and its regional offices. KEY WORDS: agriculture, urbanization, spatial planning, less-favorable areas, limiting factors, karst, Slovenia, European Union Kmetijstvo v sodobni pokrajini: zaviralec ali pospeševalec razvoja? POVZETEK: Kmetijstvo ima pomembno vlogo pri varovanju in razvoju kmetijskih zemljišč. Od osamo - svojitve dalje je Slovenije vsako leto izgubila približno 3000 ha kmetijskih zemljišč. Glavni razlogi za njihovo izgubo so urbanizacija in izvajanje velikih razvojnih projektov, ki zahtevajo uničenje plodnih kmetijskih zemljišč. Pomena kmetijstva in kmetijskih zemljišč smo se dotaknili tudi v tej posebni izdaji revije Acta geographica Slovenica. Avtorji se osredotočajo na upravljanje kmetijskih zemljišč, analizirajo razvojni potencial kmetijstva, opazujejo spremembe v pokrajini z daljinskim zaznavanjem, obravnavajo kakovost in onesnaževanje prsti ter rabo zemljišč kot element biotske raznovrstnosti. Opozarjajo na pomanjkljivo sodelovanje pri prostorskem načrtovanju in na vprašanje pomena kmetijstva oziroma delovnih mest v tem sektorju za nacionalno gospodarstvo. Uvodni članek prinaša kratko analizo o tem, kako občine, naravni parki in Kmetijsko-gozdarska zbornica Slovenije ter njeni regionalni uradi zaznavajo vprašanje prostorskih omejitev kmetij in premikanje struktur kmetij na nove lokacije. KLJUČNE BESEDE: kmetijstvo, urbanizacija, prostorsko planiranje, območja z omejenimi dejavniki za kmetijstvo, omejitveni dejavniki, kras, Slovenija, Evropska unija Nika Razpotnik, Blaž Komac Anton Melik Geographical Institute, Research Center of the Slovenian Academy of Sciences and Arts nika.razpotnik@zrc-sazu.si, blaz@zrc-sazu.si The paper was submitted for publication on July 5th, 2017. Uredništvo je prejelo prispevek 5. julija 2017. 58-1-Special issue_04p_5170-Nika Razpotnik-uvodni_acta49-1.qxd 12.9.2017 7:57 Page 52 Acta geographica Slovenica, 58-1, 2018 1 Introduction The importance of farmland and protecting has been a widely debated issue in Slovenia in recent months. The main reason for this is the planning of certain business development projects, the siting of which will destroy high-quality farmland. According to agricultural experts, this will cause irreparable damage to Slovenian agriculture and food security. Let us mention only two such development projects. The first is the construction of an auto paint shop in the Municipality of Hoče–Slivnica, where a large number of new jobs supposedly justifies the destruction of over 80 ha of high-quality and highly fertile farmland. The sec- ond is the planned construction of the Third Development Axis, the aim of which is to strengthen the economy of secondary urban centers (Nared and Razpotnik Visković 2016). Its northern section from Velenje to Šentrupert is planned to cross 110 ha of Slovenia’s highest-quality farmland. Both cases have certain points in common: they are both development projects of national and region- al importance, the implementation of which requires the destruction of fertile farmland. This is also the main reason for the strong opposition from local civil initiatives, environmental organizations, and indi- viduals. They all draw attention to the lack of participation in spatial planning procedures for siting such projects (Nared et al. 2015) and the insufficient assessment of alternative solutions. The issue of insuffi- cient inclusion of individuals and local initiatives in preparing municipal planning documents (which is even more apparent with national spatial plans) was also highlighted by the Court of Auditors in its recent audit of spatial planning in Slovenia (Revizijsko … 2017). This raises the question of the importance of agriculture and jobs in this sector in the current nation- al economic strategy. Slovenia’s Development Strategy (Strategija … 2005) does not even mention the word agriculture, even though there were 69,902 farms in Slovenia in 2016 (Kmetijska … 2016); something sim- ilar applies to the 2050 Vision of Slovenia (Slovenija … 2017). Such developments have a long-term effect on the overall national economy because, among other things, they also affect biodiversity and forest and water resources. Moreover, the new jobs and economic development promised by the planned projects mentioned above indirectly threaten not only the production of food and national food security, but also jobs in agriculture that are tied to cultivating the farmland that is now threatened. The Alumni Club of the Department of Agronomy at University of Ljubljana’s Biotechnical Faculty responded to these recent events with the roundtable Protecting Agricultural Land (Kako prenesti varo - vanje … 2017), which was held in early May 2017. At this roundtable, participants discussed the farmland protection system over time, presented future changes including the new methodology for defining farm- land of the highest quality, highlighted the importance of urbanization as the main reason for the loss of farmland, and examined the role of agriculture in this. The importance of agriculture and farmland is also touched upon in this special issue of Acta geographica Slovenica. The authors emphasize that high-quality management of farmland involves more than just defin- ing the regulations and the ratio between areas allocated for urban growth and those allocated for rural development (Markuszewska 2017). It is vital to first evaluate the development potential for agriculture in various areas and develop tools that make this possible (Pažek et al. 2017). In this as well as in observing changes in the landscape, land use, and land cover, extensive databases such as NDVI, Corine Land Cover, and the Slovenian Register of Current Agricultural and Forest Land Use have proven helpful for over a decade, but they need to be used with caution, taking into account the pitfalls hidden in the methodological changes in capturing data over time (Foški 2017; Jovanović, Milanović and Zorn 2017). In terms of protecting high- quality farmland, usually only data on area are used, while neglecting two other aspects: first, soil quality and the impact of its pollution on other landscape elements, especially water (Ilić and Panjan 2017), and, second, land cover, which is a vital element of biodiversity, nature conservation, and protection against natural disasters (Polenšek and Pirnat 2017). 2 Agriculture and farmland Agriculture plays an important role in both protecting and developing farmland, considering that there have been constant spatial tensions between agricultural and rural activities in recent decades, usually result- ing in a more or less permanent loss of farmland. Urbanization is the main reason for this loss in Slovenia. Since Slovenia’s independence, 70,000 ha of farmland (or 3.45% of the country’s territory) has been built 53 58-1-Special issue_04p_5170-Nika Razpotnik-uvodni_acta49-1.qxd 12.9.2017 7:57 Page 53 54 Nika Razpotnik Visković, Blaž Komac, Agriculture in modern landscapes: A factor hindering or facilitating development? up, and the current municipal planning documents envisage another 57,000 ha to be earmarked for the construction of housing, business and commercial districts, and transport infrastructure (Kako prenesti varovanje … 2017). In addition, farms also have increasing spatial needs for expanding and modernizing their activities (Razpotnik Visković 2017). Today’s farmyards and the structures in them are unable to meet modern technological needs and regulations (Knific and Bojnec 2015). Farms inside settlements are becom- ing increasingly spatially constrained, with areas for relocation or mere expansion usually only available on the edges of the settlement (i.e., on farmland; Razpotnik Visković 2015), where urbanization is also spreading. The target research project Selecting Farm Structure Sites and Solving Spatial Conflicts (Internet 1) revealed how the issue of farms’ spatial constraints and moving farm structures to new locations is per- ceived by municipal offices, nature parks, and the Slovenian Chamber of Agriculture and Forestry and its regional offices. A full 192 municipalities – or 90% of all Slovenian municipalities, accounting for 90% of Slovenian territory and 90% of the total Slovenian population – responded to the online questionnaire pre- pared as part of this project. Such a wide response already indicates that the spatial constraints on Slovenian farms are a very relevant topic (Polajnar Horvat and Smrekar 2015). A full 85% of the responding munic- ipalities confirmed that their farmers were dealing with spatial constraints and that this was a serious development issue. In twenty-eight municipalities, this problem was not indicated. These were mainly hilly municipalities with an exceptionally low share of developmentally promising farms. On the other hand, only 37% of municipalities had allocated areas for relocating or expanding promis- ing farms in their spatial plans. Considering that as many as 85% of the municipalities acknowledged a spatial constraint problem, this share was modest and lower than expected. The areas envisaged for relocating or expanding promising farms are important not only from the viewpoint of these farms’ economic progress, but also in terms of reducing social tensions within settlements. Lower quality of life due to agricultural activity (noise, odors, mud on the roads, and so on) in (sub)urban settlements (Tiran 2016) is one of the main reasons for disagreements among residents (Guštin and Potočnik Slavič 2015). The majority of munic- ipalities considered suitable adjustments to their spatial plans to be the primary method for resolving such disputes. By adopting suitable planning documents, development can be directed to more suitable areas, thus preserving the highest-quality farmland. An important measure in terms of developing farmland is not only the relocation of farms and the construction of large farm buildings, but also the construction of auxiliary farm structures. The Agricultural Land Act (Zakon o kmetijskih … 2011) provides that in their planning documents local communities may allow the construction of simple farm and forestry outbuildings and other structures on farmland for which a building permit is not required (e.g., hayracks, sheds, greenhouses, or barns). Municipalities assess the suitability of selecting sites for auxiliary farm structures very differently. The main problems observed include inappropriate dimensions and location, inappropriate designs, and disproportionate visual impact. A major problem highlighted by the municipalities is the fact that these structures are not being used for agricul- ture, but as vacation houses, workshops, camper garages, or even housing. It is surprising that farmers were the main developers in only 55% of municipalities; elsewhere, non-farmers predominated or the ratio was half-and-half. The current situation primarily results from a lack of inspection and inadequate activity by inspection services. In their interviews, the representatives of agriculture and forestry institutes highlighted another issue: municipalities provide very different support for the construction of farms and the development of agri- cultural activity on farmland. They believe this is not fair because the same law applies to all of Slovenia. Seventy-eight per cent of municipalities reported that they strategically support the construction of farm structures on farmland, whereas the rest were against it. Reservation toward construction on farm- land was expressed in four urban municipalities (Maribor, Nova Gorica, Murska Sobota, and Ptuj) and many municipalities with well-developed tourism (Ankaran, Bled, Bohinj, Brda, Rogaška Slatina, Šmar- ješke Toplice, Tolmin, and Zreče). In contrast, municipalities with a high share of developmentally promising farms (Cerklje na Gorenjskem, Mozirje, Sveti Jurij ob Ščavnici, and Vrhnika) were in favor of such con- struction. Here it must be added that the lack of support for farm construction on farmland does not mean that these municipalities are against agricultural activity or that they hinder its development; such a stand- point can merely contribute to more long-term protection of farmland, which is also called for by agricultural experts themselves. 58-1-Special issue_04p_5170-Nika Razpotnik-uvodni_acta49-1.qxd 12.9.2017 7:57 Page 54 55 Acta geographica Slovenica, 58-1, 2018 3 Papers in the special issue This special issue begins with a paper on the conflicts between legal policy and rural area management in Poland (Markuszewska 2017), which describes the consequences of rural transformation as witnessed in central and eastern Europe and reflected in many adverse effects that have an impact on the environment and activities in it, and hence also long-term economic development. Spatial management is encumbered due to a lack of strategies and legal documents acknowledging the importance of the development of rural areas, especially where they come in contact with urban areas or in areas of infrastructure use. This is where conflicts arise, the most common consequence of which is a continuous decrease in high-quality land suit- able for agriculture. The author proposes a mechanism for coordinated spatial planning and planning of agricultural activities that would reduce the probability of conflicts. In her paper »The (Non)usefulness of the Register of Current Agricultural and Forest Land Use for Monitoring Processes in Urban Areas,« Mojca Foški (2017) discusses changes in urban land use as a key indicator of spatial processes in Slovenia. She reports that in Slovenia it is only possible to monitor this phenomenon by using the agricultural and forest land use register, and that the methodology for captur- ing these types of data has changed so much that the register does not reflect the actual changes in urban areas. This means there is no systemic and up-to-date data source available to monitor actual changes in urban areas, where extensive use (undeveloped islands within settlements) often occurs, degraded areas form in settlements, and various conflicts arise, especially on the edges of urban and suburban settlements, where they adjoin agricultural and forest land. The paper »Forest Patch Connectivity: The Case of the Kranj–Sora Basin, Slovenia« (Polenšek and Pirnat 2017) focuses on an important but often overlooked cultural landscape element: patches of forest, trees, and shrubs. These areas form an important agricultural landscape element in terms of biodiversi- ty, nature conservation, and protection against natural disasters (e.g., wind). Urbanization and farming exert pressure on these parts of the landscape, resulting in reduction of their area and spatial connectiv- ity. The authors argue that the connectivity of such areas is just as important for the functioning of a natural system as their area; this is especially true for minor agricultural land use types such as forests. This paper features an original methodological approach to studying this issue and proposes certain solutions use- ful for long-term planning of the use of agricultural landscapes. The paper »Multi-Criteria Assessment of Less-Favored Areas: The National Level« deals with less-favored areas for agriculture (Pažek et al. 2017). These areas are highly relevant for agriculture in Europe because they account for as much as 65% of farmland. In Slovenia, this percentage is even higher (73%), covering mountainous areas (72.3% of Slovenia’s total area), special vulnerable areas (10%), and other less-favor- able areas with permanently infertile soil (4%), with karst land not taken into account (Ciglič et al. 2012). The authors present the complex multi-criteria decision-making model DEXi, which makes it possible to assess the most suitable farming method with an emphasis on sustainability. The model can be applied to the analysis of individual farms as well as regional analyses and agricultural policy. The agricultural land- scape is a complex system, in which diverse agricultural activities are impacted by many other landscape processes, which creates conflicts and represents a constant management challenge. The use of models, such as the one presented in this paper, may help solve these issues. The paper »The Use of NDVI and Corine Land Cover Databases for Forest Management in Serbia« (Jovanović, Milanović and Zorn 2017) also examines conflicts within the landscape, but from a different starting point. It presents the use of remote sensing and Corine land use data for managing forests in the Serbian municipalities of Kuršumlija and Topola. Because of the finding that the official data on the for- est area in Serbia are deficient and differ from those in the Corine database, the authors present the use of a normalized vegetation index for calculating the forest area. This method is based on satellite vegeta- tion data and provides fairly accurate results, which will facilitate the management of forest areas in this area, where illegal tree felling is common. This is most likely the reason for the calculated values being lower than the official ones. The authors recommend that the method be used for all geographically sim- ilar areas (e.g., in the Balkan Peninsula) or other areas that face illegal activities and where accurate official data sources are often unavailable. Nitrogen and phosphorus pollution is common in agricultural landscapes and is especially alarming in protected areas. The paper »Nitrogen and Phosphorus Pollution in Goričko Nature Park« (Ilić and Panjan 2017) deals with the long-term impact of diffuse and point sources of pollution on the quality of 58-1-Special issue_04p_5170-Nika Razpotnik-uvodni_acta49-1.qxd 12.9.2017 7:57 Page 55 ecosystems. The authors carried out a comparative analysis by monitoring surface watercourses. They estab- lished elevated levels of nitrogen and phosphorus compounds in the water. Long-term pollution is indicated by the increasing levels of these pollutants, which is especially alarming due to the modest thermal and discharge potential of rivers. The results of the analysis have wider implications because this is not an iso- lated case, but a predominant situation in agricultural landscapes that should receive greater attention. 4 Conclusion The papers in this special issue elucidate the topics described above, each in their own way. Examples from various countries show that spatial planning is a complex process in agricultural landscapes. A large num- ber of stakeholders and diverse long-term impacts at various levels, from legislative to economic, make it difficult to manage these landscapes and cause frequent conflicts. Many of these could be solved through better land-use planning or by directing activities and, first and foremost, through better inclusion of stake- holders in all decision-making processes. This entails planning, preparing, and adopting strategic documents and municipal planning documents, and better harmonization of business, tourism, agricultural, and other strategies. The intensive development of farmland, which has been common in Slovenia since its inde- pendence, calls for more decisive protection of this land, reigning in urbanization tendencies, and efforts to raise awareness about the importance of farmland for the survival and secure future of communities. Or, in the words of Franklin D. Roosevelt: »The nation that destroys its soil destroys itself.« 5 References Ciglič, R., Hrvatin, M., Komac, B., Perko, D. 2012: Kras kot kazalnik za določanje manj primernih območij za kmetijstvo. Acta geographica Slovenica 52-1. DOI: 10.3986/AGS52103 Foški, M. 2018: The (non)usefulness of the Register of Existing Agricultural and Fores Land Use for moni- toring the processes in urban areas. Acta geographica Slovenica 58-1. DOI: https://doi.org/10.3986/ AGS.1805 Guštin, Š., Potočnik Slavič, I. 2015: Prepoznavanje in prostorska razmestitev konfliktov na podeželju. Geografski vestnik 87-1. DOI: http://dx.doi.org/10.3986/GV87105 Ilić, D., Panjan, J. 2018: Nitrogen and Phosphorus Pollution in Goričko Nature Park. Acta geographica Slovenica 58-1. DOI: https://doi.org/10.3986/AGS.727 Internet 1: http://giam.zrc-sazu.si/sl/V6-1629#v (18. 7. 2017). Jovanović, M. M., Milanović, M. M., Zorn, M. 2018: The use of NDVI and CORINE Land Cover data- bases for foresta management in Serbia. Acta geographica Slovenica 58-1. DOI: https://doi.org/10.3986/ AGS.818 Kako prenesti varovanje kmetijskih zemljišč iz deklarativne ravni v prakso. Kmetovalec 6, junij 2017. Kmetijska gospodarstva in popis kmetijstva. Statistični urad Republike Slovenije, 2016. Ljubljana. Internet: http://www.stat.si/StatWeb/Field/Index/11/58 (18. 7. 2017). Knific, K., Bojnec, Š. 2015: Structural changes in land use of agricultural holdings in hilly rural areas. Acta geographica Slovenica 55-2. DOI: http://dx.doi.org/10.3986/AGS.736 Markuszewska, I. 2018: Conflicts between legal policy and rural area management in Poland. Acta geographica Slovenica 58-1. DOI: https://doi.org/10.3986/AGS.1525 Nared, J., Razpotnik Visković, N. 2016: Somestja v Sloveniji. Geografski vestnik 88-2. DOI: http://dx.doi.org/ 10.3986/GV88203 Nared, J., Razpotnik Visković, N., Cremer-Schulte, D., Brozzi, R., Cortines Garcia, F. 2015: Achieving sus- tainable spatial development in the Alps through participatory planning. Acta geographica Slovenica 55-2. DOI: http://dx.doi.org/10.3986/AGS.1631 Pažek, K., Irgolič, A., Turk, J., Borec, A., Prišenk, J., Kolenko, M., Rozman, Č. 2018: Multi-criteria assessment of less favoured areas: a state level. Acta geographica Slovenica 58-1. DOI: https://doi.org/10.3986/ AGS.962 Polajnar Horvat, K., Smrekar, A. 2015: Veljavnost osebnega in spletnega anketiranja v geografskem razisko- vanju. Geografski vestnik 87-2. DOI: https://doi.org/10.3986/GV87208 Nika Razpotnik Visković, Blaž Komac, Agriculture in modern landscapes: A factor hindering or facilitating development? 56 58-1-Special issue_04p_5170-Nika Razpotnik-uvodni_acta49-1.qxd 12.9.2017 7:57 Page 56 Acta geographica Slovenica, 58-1, 2018 57 Polenšek, M., Pirnat, J. 2018: Forest patch connectivity: The Case of the Kranj-Sora Basin, Slovenia. Acta geographica Slovenica 58-1. DOI: https://doi.org/10.3986/AGS.3001 Razpotnik Visković, N. 2015: Evaluating the development potential of farms on urban outskirts: method- ology. Acta geographica Slovenica 55-2.DOI: http://dx.doi.org/10.3986/AGS.704 Razpotnik Visković, N. 2017: Spatial Constraints of Slovenian Farms: What Does Urbanization Have to Do with It? European Countryside 9-2. DOI: https://doi.org/10.1515/euco-2017-0017 Revizijsko poročilo Učinkovitost urejenosti postopka prostorskega načrtovanja občin. Računsko sodišče Republike Slovenije, 2017. Ljubljana. Slovenija 2050. Vizija razvoja Slovenije. Vlada Republike Slovenije, 2017. Internet http://slovenija2050.si/ (18. 7. 2017). Strategija razvoja Slovenije. Vlada Republike Slovenije, 2005. Ljubljana. Internet: (18. 7. 2017). Tiran, J. 2016: Measuring urban quality of life: case study of Ljubljana. Acta geographica Slovenica 56-1. DOI: http://dx.doi.org/10.3986/ags.828 Zakon o kmetijskih zemljiščih. Uradni list Republike Slovenije 71/2011, 27/2016. Ljubljana 58-1-Special issue_04p_5170-Nika Razpotnik-uvodni_acta49-1.qxd 12.9.2017 7:57 Page 57 58 58-1-Special issue_04p_5170-Nika Razpotnik-uvodni_acta49-1.qxd 12.9.2017 7:57 Page 58 Acta geographica Slovenica, 58-1, 2018, 59–67 Agricultural landscape, the environs of Poznań. IW O N A M A R K U S Z E W S K A CONFLICTS BETWEEN LEGAL POLICY AND RURAL AREA MANAGEMENT IN POLAND Iwona Markuszewska 58-1-Special issue_05p_1525-Iwona Markuszewska_acta49-1.qxd 12.9.2017 7:57 Page 59 Iwona Markuszewska, Conflicts between legal policy and rural area management in Poland DOI: https://doi.org/10.3986/AGS.1525 UDC: 911.373:631(438) 711.3:631(438) COBISS: 1.01 Conflicts between legal policy and rural area management in Poland ABSTRACT: This paper refers to the issue of the damaging consequences of the ongoing rural area trans- formation in Poland in a dynamically developing economy, with a simultaneous lack of adequate planning tools of countryside management. Lack of strategic documents recognise the importance of rural area devel- opment leads to irreversible changes, presented on the basis of the issue of farmland merging and the depletion of farmland resources. As a solution guaranteeing comprehensive rural management, agrarian arrange- ment plans of communes (AAPC) and agrarian arrangement projects of villages (AAPV) have been proposed. KEY WORDS: rural geography, spatial planning policy, farmland merging, de-farming, agrarian arrange- ment plans of communes, agrarian arrangement projects of villages, rural area, Poland Neskladje med pravno politiko in upravljanjem podeželja na Poljskem POVZETEK: Avtorica v članku obravnava problematiko škodljivih posledic trenutne preobrazbe poljskega podeželja, ki se odvija v dinamičnem gospodarstvu ob hkratnem pomanjkanju ustreznih načrtovalskih orodij za upravljanje podeželja. Pomanjkanje strateških dokumentov, pomembnih za razvoj podeželskih območij, povzroča nepopravljive spremembe, ki so v članku predstavljene na podlagi problematike zdru - ževanja kmetijskih zemljišč in njihove izgube. Kot rešitev, ki zagotavlja celovito upravljanje podeželja, avtorica predlaga oblikovanje načrtov kmetijske ureditve občin in projektov kmetijske ureditve vasi. KLJUČNE BESEDE: geografija podeželja, politika urejanja prostora, združevanje kmetijskih zemljišč, deagra - rizacija, načrti kmetijske ureditve občin, projekti kmetijske ureditve vasi, podeželje, Poljska Iwona Markuszewska Adam Mickiewicz University Faculty of Geographical and Geological Sciences, Department of Landscape Ecology iwmark@amu.edu.pl The paper was submitted for publication on December 19th, 2014. Uredništvo je prejelo prispevek 19. decembra 2014 60 58-1-Special issue_05p_1525-Iwona Markuszewska_acta49-1.qxd 12.9.2017 7:57 Page 60 Acta geographica Slovenica, 58-1, 2018 61 1 Introduction In Central and Eastern European countries, since the beginning of the 90's of the past century, when instru- ments of market economy were set in motion, an enormous change in the use of agricultural areas has been observed. Unfortunately, in most cases, improper practices in the decision-making process about spa- tial planning are observed. However, it must be explained that a strong desire for land consumption expressed by individuals has enforced legislators to create laws enabling rapid economic development. This situation can be observed in Poland. When it comes to countryside development, in Poland the legal guidelines of spatial planning leave much to be desired (Markuszewska 2012). Although agricultur- al matters are included in many strategies (Figure 1), no planning documents related to agrarian space constantly operated by farmers have yet been elaborated. Yet, not only elaborations about the agronomic utilisation of rural areas are missing, but also documents concerning village renewal and rural heritage protection. In addition, existing legal acts protect poorly against the irretrievable decline of soil resources whilst also not supporting agriculture modernisation in the scope of the improvement of agrarian struc- ture. Not to mention the lack of any legal policy system of rural area development, integrating the various levels of administrative bodies responsible for the decision-making process. This paper discusses the problem of the faulty planning and management system of rural areas in Poland. The aim was to present conflicts between faulty legal policy and negative changes in rural area being a result of implementation of that legislation. On the one hand, remark was concentrated on the issue of the frag- mentation of the agrarian structure. On the other hand, attention was put on the de-farming phenomenon. Finally, suggestions to improve decision-making policies in the field of the management of rural area have been proposed. 2 Methods The faulty planning system of rural areas development, with respects to weaknesses of the legal ground as well as the competence divergence of administrative bodies, is presented in this paper. Several major questions related to rural landscape dynamics and management were identified and were kept as the cen- tre of reflection and comparison: • What are the weak points of rural area development at a local level? • To what extent does the existing spatial planning and management framework take into account the aspect of agrarian production space modernisation as well as farmland resources protection? • Are there any opportunities for slowing down the rate of the negative consequences of controversial policy implementation? The data were gathered from legislation (legal acts referring to the procedures for farmland merging and de-farming) and statistics (describing changes in farmland merging since 1945 as well as agricultur- al land de-farming since 1990). Open interviews with 20 officials, responsible for local and regional planning, were conducted. Additionally, in order to describe the wider context of the research, branch literature was also taken into consideration. As a result, several solutions for improving the current situation in the plan- ning and management of rural areas have been presented. 3 Results 3.1 Stewardship of production space in relation to farmland merging When considering the improvement of agriculture efficiency, one of the rural policy guidelines and an aspiration of the Polish government since the system's transformation, there has been a total rebuild of the agrarian structure. Agrarian structure, defined as a state of agricultural production units, is classified into different groups according to land ownership and land fragmentation. In Poland, a characteristic feature of agrarian production space is land fragmentation, often referred to patchwork fields. Patchwork fields mean that farmland of one ownership is split up into a large num- ber of tiny plots scattered between varied landowners with a complicated arrangement. Land fragmentation is described by the plot distribution pattern, this could be: a small average-sized farm (7 ha), a relatively 58-1-Special issue_05p_1525-Iwona Markuszewska_acta49-1.qxd 12.9.2017 7:57 Page 61 Iwona Markuszewska, Conflicts between legal policy and rural area management in Poland 62 Strategy of Country Development Strategy of Rural Areas and Agriculture Development Concept of the Policy of Spatial Development of the Country Ministry of Agriculture and Rural Development Council of Ministers Strategy of Province Development Province Strategy of Rural Areas Development Province Zoning Plan Province Assembly Strategy of District Development District Strategy of Rural Areas Development District Council (starosta) Strategy of Commune Development Study of Conditions and Directions of Spatial Development Local Zoning Plans (LZP) Municipal Council ( major, city president)vojt, Department of Geodesy and Rural Areas Development AAPC AAPV N at io n al l ev el R eg io n l ev el L o ca l le ve l Figure 1: Selected strategic and planning documents drawn up by different administrative bodies. Strategic documents are marked by red colours, whereas planning documents in yellow. 58-1-Special issue_05p_1525-Iwona Markuszewska_acta49-1.qxd 12.9.2017 7:57 Page 62 high number of land plots per farm (8 pieces) and a small average size of individual plot (0.6ha). Additionally, the distance between the farm and the cultivated fields can be considerably remote, sometimes reaching up to 3 and even 4 km (Woch 2006; Woch et al. 2011). As for spatial distribution, the most unfavourable agrarian structure occurs in south-eastern Poland. However, also in other parts of the country this prob- lematic field mosaic contributes to a serious cultivation inconvenience. In a situation like this, the carrying out of land consolidation can solve the farmland fragmentation issue. Additionally, comprehensive land consolidation includes not only the merging and exchanging of arable land, but also the modernization of rural area. For this reason, farmland consolidation can be a great tool for both, production space upgrading and countryside renewal. But even though these profound changes lead to rural area modernisation, farmland merging is conducted very rarely in Poland. Analysing the effectiveness of land consolidation work in the post-war period, several re-parcelling stages can be distinguished. Between 1945 and 1967 farmland merging work covered 560,000 hectares of agri- cultural land. Until 1980, increased activity was observed – 3,676,000 hectares of land were merged. In the years 1981–1988, consolidation activities decreased noticeably, and during that period only 444,000 hectares of land were merged. Further, through the economic transformation, between 1989 and 1998, a steady decline in land consolidation was still evident, as only 228,000 hectares of farmland were merged. There are several reasons explaining the decreasing interest in land consolidation work, among which the most important are: adverse legislation, declining funds and farmers unwillingness to cooperate (Woch 2006; Wierzchowski 2007; Markuszewska 2013). Nevertheless, for a better understanding of the weaknesses of the land consolidation process, legislation review has been undertaken. First of all, the competences of the public administration are divided between various tiers; some of the responsibilities of land consolidation are under local authorities and yet others are under regional ones (Act on Land Consolidation and Exchange – Ustawa o scalaniu … 1982; Act on Local Government – Ustawa o samorządzie … 1990; Act on Province Government – Ustawa o samorządzie … 1998). For example, head of the district government (Pl. Starosta) at landowners' formal request, issues a positive opinion on farm- land re-parcelling and simultaneously prepares a decision on the initiation of the land consolidation process. Later, a land consolidation project is drawn up by the surveyor-designer from the province government. Despite the fact that the project is drafted by the surveyor-designer, it is head of the district government who is entrusted to approve the document. Additionally, the discrepancy in the administrative competences has not only a detrimental effect on legal processes, but also makes civil servants less involved in the farm- land merging procedures. Before the public administration reform in 1998, the authorisation to conduct farmland merging pro- cedures was at commune level, whereas after the reform this process is controlled by district and provincial levels (Act on Regulations Implementing the Act Reforming Public Administration – Ustawa-Przepisy…1998). As a result the commune authorities have been disregarded, which should not happen, because there are commune officers who are responsible for planning and development at the landscape level, and farm- land merging is a vital aspect of that process. Another aspect is the separation of merging-exchanging work from post-re-parcelling development. As a result, merging-exchanging work, based on a land consolidation project, concerns land parcel con- solidation and relocation, is fully completed by the geodesy department of the province government. In turn, post-consolidation development, including road construction, drainage ditch implementation is under the supervision of the head of the district government who selects a contractor during the tendering pro- cedure. On the other hand, currently in force Act on Land Consolidation and Exchange (Ustawa o scalaniu…1982) gives a too powerful role to the land consolidation committee, represented mostly by landowners. For exam- ple, the decisions of the head of the district government can be undermined at any time and procedures or decisions may be easily prosecuted by the administrative court. Before 1982, when that law was imple- mented, these activities were limited. Even the pre-war regulatory Act on Land Consolidation (Ustawa o scalaniu … 1923) restricted the power of the merging committee when it slowed down the merging work. In such a case it was possible to dismiss all members and to appoint new ones collected from the land con- solidation authorities not landowners. Nowadays it is impossible, even if the advisory group exceeds its power. Furthermore, the provisions of the Act allow for the temporary suspension or even abandonment of the merging activity at the request of only one landowner, regardless of the progress of the work, and sur- Acta geographica Slovenica, 58-1, 2018 63 58-1-Special issue_05p_1525-Iwona Markuszewska_acta49-1.qxd 12.9.2017 7:57 Page 63 Iwona Markuszewska, Conflicts between legal policy and rural area management in Poland prisingly, that person is not fined for any investments already executed. In comparison, again with refer- ence to the pre-war act, Act on Land Consolidation (Ustawa o scalaniu…1982), which imposed the following limitation: interruption of any ongoing land consolidation processes was only possible if the application was submitted by two-thirds of the participants, and only the persons responsible for the procedure defer- ment would bear the cost of any work previously conducted. 3.2 Farmland resources hazard with regard to urban sprawl According to the Act on Agricultural and Forest Land Protection (Ustawa o ochronie … 1995), farmland is subjected to legal protection, which means that the use of farmland for non-agricultural purposes is gen- erally restricted. Nevertheless, in certain situations the Act enables de-faming, which means that agricultural land can be intended for non-agricultural purposes. However, overuse of that regulation can lead to the depletion of farmland resources. For a better understanding of the negative consequences of de-farming process, a brief review of the legislation is given below. In 1966 the first legal act Resolution of the Ministers' Council on Agricultural Land Protection (Rozporządzenie … 1966) came into force. One of the principles emphasised that, »for non-agricultural purposes« can only be assigned to the poorest soils (5th or 6th classes). Although, good farmland quality (1st–4th classes) could be de-farmed, but only when there was a lack of substitute soils in a given area or when the non-farming allocation was justified for particularly important national reasons. However, shortly afterwards, the legislation required streamlining and therefore new legal acts were introduced: Act on Agricultural and Forest Land Protection (Ustawa o ochronie … 1971), Act on Land Consolidation and Exchange (Ustawa o scalaniu … 1982). Here the limitation of agricultural land alloca- tion for non-farming purposes was much more restrictive, and additionally, the power over decisions to be taken was given to the province governor (Pl. Wojewoda), with the objective of discouraging parties from seeking to obtain de-farming decision. The presently enforced law, approved in 1995 – the Act on Agricultural and Forest Land Protection (Ustawa o ochronie … 1995), maintained most of the previously established regulations, and additional- ly, imposed the obligation of the marking of non-agricultural land allocation in local zoning plans. Moreover, in the cases of 1st–4th class soils being de-farmed, the Minister of Rural Development was given author- ity. The amendment of 2008 made the Act more liberal and washed out all previously existing limitations. First of all, for issuing the administrative decision on de-farming, the Marshal from the provincial government was given entitlement. Secondly, only in relation to the de-farming of the 1st–3rd classes of agricultural land, was the obligation to obtain a decision required, and only when the area exceeded 0.5 hectare. This means that such approval was unnecessary in the cases of farmland which 4th–6th class soils, regardless of the size of the area proposed to be de-farmed. Moreover, no permission was requisite for the non-agricultural use of the 1st–3rd classes of farmlands located within administrative boundaries of towns. Finally, the oblig- ation to move the humus layer of 1st–4th soil classes has been withdrawn. Undoubtedly, this policy relaxation has worked against the protection of farmland resources. For example, simply taking into account the area of farmland in towns, theoretically 1 million hectares of agricultural land has supposed to have been irre- versibly lost. This harmfully operated legal regulation has been limited according to the newest alteration of 2013. The new rules indicate that only the Mayor (Pl. Wójt) is authorised to submit an application for de-farming, naturally on the request of landowners (previously it was directly under landowners' power). Furthermore, in relation to the de-farming of agricultural lands of 1st–3rd classes, only the Minister of rural develop- ment is authorised to take the decision (previously, the power was under local government). What is also important, according to the Act on Spatial Planning and Development (Ustawa o planowaniu … 2003) in order to obtain de-farming permission for future building investments, several requirements must be ful- filled, such as: access to public roads, access to water infrastructure and electricity network, and sometimes sewage and the gas system. According to statistical data, in the years 1990–1994, between 5,000 and 7,000 hectares of agricultur- al land were de-farmed each year. In the next period, between 1995 and 2003, the intensity of this process slightly decreased, because every year between 1,000 and 3,000 hectares were allocated for non-farming purposes. However, in the years 2004–2013 the activity increased: from 3,000 to more than 5,000 hectares 64 58-1-Special issue_05p_1525-Iwona Markuszewska_acta49-1.qxd 12.9.2017 7:57 Page 64 were de-farmed annually. Another disturbing matter is the quality of de-farmed soils. The best quality of soils, those including 1st–3rd classes, covers about 26%, however, the first two classes take only 3%. Even if the legal provisions emphasize that only wastelands or the poorest soils should be designated for non-agri- cultural purposes, the conducted analysis revealed that since 1995 the greatest percentage of de-farmed soils covered the richest soils (Environment 2013). The loss of farmland is particularly evident in the range of influence of urban areas, where on the one hand, there is an easy access to »fresh land«, and on the other hand, easy access to urban services. 3.3 Rural area management – searching for a good solution in a long-term perspective The above studies revealed the strong need to improve the existing controversial body of laws as well as to elaborate documents relating to the management of agrarian space, with the emphasis put on com- prehensive rural area development, tailor-made for social demands. As for documentation, agrarian arrangement plans of communes (AAPC) and agrarian arrangement projects of villages (AAPV) can ful- fil that requirement. However, AAPC and AAPV are kinds of so-called »economic programs«, not »planning documents«, which excludes them from the decision-making process of spatial planning. Also, there is no legal obligation to draw up these documents. The underestimation of AAPC or AAPV is proved by the fact that only in one province, the Lower Silesia Province, did the regional government decide to imple- ment agrarian arrangement plans of communes for practical actions to deal with the issue of farmland fragmentation. With regards to the agrarian arrangement plan of commune, the main goals are: the provision of comprehensive and multifunctional development of rural areas, the boosting of farms' effectiveness and improvement of general living conditions, all this with the simultaneous protection of the natural envi- ronment and the preservation of cultural heritage. Accordingly, AAPC is a document clarifying the current stage of a rural area development based on its existing natural potential, people resources, cultural val- ues, as well as presenting scenarios for future changes. The range of agrarian arrangement work proposed to be implement in the AAPC, includes in particular: • improvement of the plot distribution pattern by the reduction of land fragmentation, • modernization of the agrarian structure by the construction of new infrastructure networks including between-fields roads, drainage ditches, • an increase in soil productivity by conducting anti-erosion activities and farmland reclamation, • preservation of landscape by the designation of protected areas and forestation of poor quality farmland, • implementation of non-farming purposes by the designation of land for the development of new resi- dential, service purposes, • revitalization of village by the renewal of existing buildings, implementation of public utility infrastructure, road renovation and plumbing system installation. Among the information related to the characterisation of a plot distribution pattern, the subsequent data are given: the number of parcels in individual farms, size of the individual parcels, and distance between the farmstead and the arable land. Due to this fact, AAPC stands out from other local strategic documents as a useful tool in the assessment of land consolidation demand (Analiza zapotrzebowania … 2010). The guidelines of the AAPC constitute directives on the drafting of the AAPV. It is suggested that the most beneficial way of AAPV utilisation can be the drawing up of Projects for farmland merging and Projects for village renewal. During the procedure of AAPC and AAPV elaboration, an important role is played by the local com- munity; village leaders and farmers as well as the commune council. This way of proceeding, involving all parts of the decision-making process, allows for the working out of commonly accepted findings, which then streamlines the implementation of the agrarian arrangement work. As for the practical application of AAPC, assessment of land consolidation demand in the Lower Silesia Province has been conducted. Based on the AAPC, several elaborations have been prepared by the Department of Geodesy and Cartography (the unit of province government), among which, the most impor- tant are: the Analysis of demand for land consolidation work in communes, the Study of demand for land consolidation work in the province as well as the Database of land consolidation objects (Analiza zapotrzebowania … 2010). It is important to emphasise that for the creation of a proper base for information Acta geographica Slovenica, 58-1, 2018 65 58-1-Special issue_05p_1525-Iwona Markuszewska_acta49-1.qxd 12.9.2017 7:57 Page 65 Iwona Markuszewska, Conflicts between legal policy and rural area management in Poland flow, the Analysis among all sides (landowners and administrative bodies of local and regional govern- ments) involved in land consolidation process, has been disseminated (Markuszewska 2013). 4 Discussion The paper presents the conflicts between legal policy and rural area management and development in the context of the failure of farmland merging and the depletion of farmland resources in Poland. However, this situation is comparable to other countries of Central and Eastern Europe. The land fragmentation issue in Central and Eastern Europe has been widely discussed, for example by van Dijk (2003; 2007), Pasakarnis et al. (2013), King and Burton (1982). Other authors focused on the problem of the degree of fragmentation of agricultural land, which is a big obstacle to the development of modern farming as well as, like similarly in this paper, putting the emphasis on the complicated procedures of farmland merging and the role of the comprehensive approach to the land consolidation process (Kabat and Hagedorn 1997; Sarris et al. 1999, Voltr 2000; Skalenicka and Salek 2008; Vijulie et al. 2012). On the other hand, ongoing urban sprawl and intensive urbanization of rural areas lead to the depletion of farmland resources, which in respect to Central and Eastern European countries should raise particular interest, bearing in mind the role of agriculture in the national economies. This environmental harmful consequence, resulting from unregulated legal policy in many of the post-communist countries of this region of Europe, in several papers has been stressed. It is worth mentioning several examples: Matthew (2000), Hirt (2008), Łowicki (2008), Bălteanu and Popovici (2010), Suditu (2012). 5 Conclusion On the basis of findings discussed in this paper, it has been proved that the problematical situation with management and development of rural areas in Poland is affected, inter alia, by the following reasons a lack of reasonable legal tools for rural area management, a lack of a harmonised policy with a comprehensive approach to the multifunctional development of rural areas, a lack of clarified goals of rural policy that is expected to be achieved by local and regional authorities, and a lack of long-term perspective in the deci- sion-making processes on rural area development. All these aspects lead to disastrous environmental and economic consequences, such as for example, the loos of non-renewable soil resources, rural traditional landscape degradation and rising costs of living. However, a lack of strategic documents focusing on areas where agrarian production is the main purpose of farming development, means that the AAPC and AAPV can gain favour as complementary documents to existing ones, which has been proved above. 6 References Bălteanu, D., Popovici, A. 2010: Land use changes and land degradation in post-socialist Romania. Romanian journal of geography 54-2. Błaż, B., Król, A., Wawro, D. 2010: Analiza zapotrzebowania na scalanie gruntów rolnych wsi województwa dolnośląskiego. Wrocław. Internet: http://wgik.dolnyslask.pl (5. 5. 2015). Environment 2013, Statistical Information and Elaborations, Central Statistical Office, Warsaw. Hirt, S. 2008: Landscapes of postmodernity: changes in the built fabric of Belgrade and Sofia since the end of socialism. Urban geography 29-8. DOI: http://dx.doi.org/10.2747/0272-3638.28.8.755 Kabat L., Hagedorn K. 1997: Privatisation and decollectivisation policies and resulting structural changes of agriculture in Slovakia. Agricultural privatisation, land reform and farm restructuring in Central Europe. Aldershot. King, R., Burton, S. 1982: Land fragmentation: Notes on a fundamental rural spatial problem. Progress in human geography 6-4. DOI: http://dx.doi.org/10.1177/030913258200600401 Łowicki, D. 2008: Land use changes in Poland during transformation. Case study of Wielkopolska region. Landscape and urban planning 87-4. DOI: http://dx.doi.org/10.1016/j.landurbplan.2008.06.010 Markuszewska, I. 2012: Plany urządzeniowo-rolne gmin jako narzędzie planowania prac scaleniowych. Problemy ekologii krajobrazu 33. 66 58-1-Special issue_05p_1525-Iwona Markuszewska_acta49-1.qxd 12.9.2017 7:57 Page 66 Markuszewska, I. 2013: Land consolidation as an instrument of shaping the agrarian structure in Poland: a case study of the Wielkopolskie and Dolnośląskie Voivodeships. Quaestiones geographicae 32-3. DOI: http://dx.doi.org/10.2478/quageo-2013-0027 Matthew, E. K. 2000: The environmental impact of suburbanization. Journal of policy analysis and man- agement 19-4. DOI: http://dx.doi.org/10.1002/1520-6688(200023)19:4<569::AID-PAM3>3.0.CO;2-P Pašakarnis, G., Morley, D., Maliene V. 2013: Rural development and challenges establishing sustainable land use in Eastern European countries. Land use policy 30-1. DOI: http://dx.doi.org/10.1016/ j.landusepol.2012.05.011 Rozporządzenie Rady Ministrów o ochronie gruntów rolnych (Resolution of the Ministers' Council on Agricultural Land Protection). Dziennik Ustaw Polskiej Rzeczypospolitej Ludowej 198/1966. Sarris, A., Doucha, T., Mathijs, E. 1999: Agricultural restructuring in central and eastern Europe: impli- cation for competitiveness and rural development. European review of agricultural economics 26-3. DOI: http://dx.doi.org/10.1093/erae/26.3.305. Sklenicka, P., Salek, M. 2008: Ownership and soil quality as sources of agricultural land fragmentation in highly fragmented ownership patterns. Landscape ecology  23-3. DOI: http://dx.doi.org/10.1007/ s10980-007-9185-4 Suditu, B. 2012: Urban sprawl – the legal context and the territorial practices in Romania. Human geo- graphies – journal of studies and research in human geography 6-1. DOI: http://dx.doi.org/10.5719/ hgeo.2012.61.73 Ustawa – Przepisy wprowadzające ustawy reformujące administrację publiczną (Act on Regulations Implementing the Act Reforming Public Administration). Dziennik Ustaw Rzeczypospolitej Polskiej 133/1998. Ustawa o ochronie gruntów rolnych i leśnych oraz rekultywacji gruntów (Act on Agricultural and Forest Land Protection and Land Reclamation). Dziennik Ustaw Polskiej Rzeczypospolitej Ludowej 27/1971. Ustawa o ochronie gruntów rolnych i leśnych (Act on Agricultural and Forest Land Protection). Dziennik Ustaw Rzeczypospolitej Polskiej 163/1995. Ustawa o planowaniu i zagospodarowaniu przestrzennym (Act on Spatial Planning and Development). Dziennik Ustaw Rzeczypospolitej Polskiej 80/2003. Ustawa o samorządzie gminy (Act on Local Government). Dziennik Ustaw Rzeczypospolitej Polskiej 142/1990. Ustawa o samorządzie województwa (Act on Province Government). Dziennik Ustaw Rzeczypospolitej Polskiej 91/1998. Ustawa o scalaniu gruntów (Act on Land Consolidation). Dziennik Ustaw Rzeczypospolitej 93/1923. Ustawa o scalaniu i wymianie gruntów Act on Land Consolidation and Exchange). Dziennik Ustaw Rzeczypospolitej Polskiej 178/1982. van Dijk, T. 2003: Scenarios of Central European land fragmentation. Land use policy 20-2. DOI: http://dx.doi.org/ 10.1016/S0264-8377(02)00082-0 van Dijk T. 2007: Complications for traditional land consolidation in Central Europe. Geoforum 38-3. DOI: http://dx.doi.org/10.1016/j.geoforum.2006.11.010 Vijulie, I., Matei, E., Manea, G., Octavian, C., Cuculici, R. 2012: Assessment of agricultural land fragmentation in Romania, a case study: Izvoarele commune, Olt county. Acta geographica Slovenica 52-2. DOI: http://dx.doi.org/10.3986/AGS52206 Voltr, V. 2000: EU accession and the land market in the Czech Republic. Land Ownership, Land Markets and their influence on the efficiency of agricultural production in Central and Eastern Europe. Halle. Wierzchowski, M. 2007: Przestrzenne, ekonomiczne i społeczne problemy scalania i wymiany gruntów. Kraków. Woch, F. 2006: Kompleksowe scalanie gruntów rolnych i leśnych oraz jego wpływ na środowisko. Puławy. Woch, F., Wierzbicki, K., Eymontt, A., Dziadkowska-Ilkowska, A., Syp, A., Kopiński, J., Pietruch, C., Nierubaca, M., Miklewski, A. and Maśloch, P. 2011: Efektywność gospodarcza i ekonomiczna scalania gruntów w Polsce. Puławy. Acta geographica Slovenica, 58-1, 2018 67 58-1-Special issue_05p_1525-Iwona Markuszewska_acta49-1.qxd 12.9.2017 7:57 Page 67 68 58-1-Special issue_05p_1525-Iwona Markuszewska_acta49-1.qxd 12.9.2017 7:57 Page 68 Acta geographica Slovenica, 58-1, 2018, 69–82 Urban land use, which covers all built-up areas, areas with infrastructure facilities, and other areas that permanently changed from a natural to a built environment, is in general increasing in all countries and environments. G A Š P E R M R A K THE (NON)USEFULNESS OF THE REGISTER OF EXISTING AGRICULTURAL AND FOREST LAND USE FOR MONITORING THE PROCESSES IN URBAN AREAS Mojca Foški 58-1-Special issue_06p_1805-Mojca Foski_acta49-1.qxd 12.9.2017 7:58 Page 69 70 DOI: https://doi.org/10.3986/AGS.1805 UDC: 711.14(497.4) COBISS: 1.01 The (non)usefulness of the Register of Existing Agricultural and Forest Land Use for monitoring the processes in urban areas ABSTRACT: The changing of urban land use is the key indicator of spatial processes at work. The only systemic data source in Slovenia that can be employed to monitor land use changes is the Register of Existing Agricultural and Forest Land Use. The hypothesis that the Register is not suitable for monitoring urban land use changes was tested by comparing the data in the »built-up and related land« category for 2002, 2005, 2009, 2011, and 2013. The analysis was carried out at the level of Slovenia, and the results were inter- preted in relation to small testing areas in NE Slovenia. We found that the methodology of data capture varied to such a degree that the data fail to reflect the actual changes in urban areas. KEY WORDS: spatial planning, land use, urban land use, spatial monitoring, Register of Existing Agricultural and Forest Land Use, Slovenia (Ne)upo rab nost Evi den ce dejan ske rabe kme tij skih in gozd nih zem ljišč za sprem lja nje pro ce sov na urba nih območ jih POVZETEK: Spre mi nja nje urba ne rabe pro sto ra je ključ ni poka za telj pro stor skih pro ce sov. Edi ni sistemski vir podat kov v Slo ve ni ji, ki je lah ko name njen tudi sprem lja nju spre memb rab pro sto ra, je Evi den ca dejanske rabe kme tij skih in gozd nih zem ljišč. Hipo te zo, da evi den ca ni ustrez na za sprem lja nje spre memb urba ne rabe pro sto ra, smo pre ver ja li s pri mer ja vo podat kov kate go ri je »po zi da na in sorod na zem ljiš ča« v le tih 2002, 2005, 2009, 2011 in 2013. Ana li zo smo opra vi li na rav ni Slo ve ni je in rezul ta te inter pre ti ra li na manj ših test nih območ jih seve ro vz hod ne Slo ve ni je. Ugo to vi li smo, da se je meto do lo gi ja zaje ma podat kov tako spremi - nja la, da podat ki ne odse va jo dejan skih spre memb na urba nih območ jih. KLJUČNE BESEDE: pro stor sko načr to va nje, raba zem ljišč, urba na raba, sprem lja nje sta nja pro sto ra, Evi - den ca dejan ske rabe kme tij skih in gozd nih zem ljišč, Slo ve ni ja Mojca Foški University of Ljubljana, Faculty of Civil and Geodetic Engineering, Chair of Spatial Planning mfoski@fgg.uni-lj.si The paper was submitted for publication on February 6th, 2015. Ured niš tvo je pre je lo pris pe vek 6. fe bruar ja 2015. Mojca Foški, The (non)usefulness of the Register of Existing Agricultural and Forest Land Use for monitoring the processes … 58-1-Special issue_06p_1805-Mojca Foski_acta49-1.qxd 12.9.2017 7:58 Page 70 71 Acta geographica Slovenica, 58-1, 2018 1 Introduction Knowing the situation and trends of land use and land cover changes is essential in order to make informed decisions concerning spatial planning, land management, and economic planning. The changes in land use and land cover are indicative of natural processes (e.g. transition from agricultural to forest land use) or human activities (e.g. transition from agricultural to urban land use). Land use changes are often reflected in changes to land cover, as land cover and land use are often correlated (Arnold et al. 2014; Antrop 2005; Ellis 2010; Tavares, Pato and Magalhaes 2012), except for land use changes in urban areas. In urban space only a small proportion of changes is detected as a change in land cover (e.g. change of a brownfield into a park), while changes from housing to services can only be detected by having insight into social and economic activities in the study area. It is accordingly important to distinguish between land use – defining the purpose of using the Earth's surface (INSPIRE 2013a; INSPIRE 2013b) – and land cover – defining the biological and physical cover of the Earth's surface (INSPIRE 2013a; INSPIRE 2014); by knowing land use and land cover we are able to provide more accurate information about space (Hovenbitzer et al. 2014). Land use is split up into the existing land use, and intended or planned land use (INSPIRE 2013b). Existing land use is independent of legal provisions, which lay down the ways of acquiring ownership and the rights thereof, and can be generally recorded on the ground (Metodologija … 2013), unlike intended land use. Transitions into urban land use are mostly regulated by spatial planning documents. A detailed review of the literature by Slovenian authors dealing with identifying and monitoring land use changes was undertaken by Gabrovec and Kladnik (1997). The studies until 1997, and also thereafter, focused on studying agricultural land use changes (Vrščaj 2007; Miličić and Udovč 2012; Lisec, Pišek and Drobne 2013) or landscape changes (Petek 2002; 2005; 2007; Petek and Urbanc 2004; Kladnik and Petek 2007), and through this lens they indirectly touch upon urban land use areas. Urban land use changes have been addressed by Bogataj and Drobne (2002), Krevs (2004), and Topole et al. (2006). Bole (2014, 2015) focused on identifying Slovenian traffic areas and how they are changing. The data on the surface area of urban land for Slovenia could be acquired from the Statistical GIS Land Cover and Land Use database (Skumavec and Šabić 2005, SURS 2007), but since 2005 it is no longer updat- ed, while already Krevs (2004) pointed out to its deficiencies. The CORINE Land Cover (CLC) database of the European Environment Agency (EEA) (Corine…2014) provides the data for Slovenia for 1995, 2000 and 2006, which are shown in the Environmental Atlas (Atlas … 2014) and the Urban Atlas (Urban … 2014). This grid density is too low (cell spatial resolution is 100 × 100 m) to identify the existing land cover changes in urban areas. Many authors (Ilešič  1950; Medved  1970; Gabrovec and Kladnik  1997; Gabrovec, Kladnik and Petek 2000; Lisec, Pišek and Drobne 2013; Bole 2014, 2015) used land cadastre data. The Surveying and Mapping Authority of the Republic of Slovenia stopped updating these data, but instead acquires them from the records kept by other sectors (Metodologija … 2013). The Register of Existing Agricultural and Forest Land Use (hereinafter: Register) is based on the method of visual interpretation of orthophotos (DOF) with a resolution of 1 m, and the result is a topologically correct vector database of existing agricultural and forest land use. Vector data for 2002, 2005, 2009, 2011, and 2013 are publicly accessible at the website of the ministry responsible for agriculture (Internet 1). Although the register was set up for agricultural policy needs, it was used in real property valuation (Zakon o množičnem vrednotenju … 2006), pursuant to the Spatial Planning Act (2007) and the Rules on Land Use and Legal Regimes Data (2008), as well as for showing the discrepancy between the existing and the planned land use and for calculating the environmental indicator TP03 Built-up Land (Kazalci okolja v Sloveniji 2014). The data from the Register were used to test the hypothesis on the suitability of the register on mon- itoring urban land use changes and the processes therein. We compared the categories of »built-up and related land« (hereinafter: PiSZ) at different time points, i.e. for 2002, 2005, 2009, 2011, and 2013, and, based on the findings, we gave recommendations with a view to establishing better and more wide-scale use of the EDRKGZ. 58-1-Special issue_06p_1805-Mojca Foski_acta49-1.qxd 12.9.2017 7:58 Page 71 Mojca Foški, The (non)usefulness of the Register of Existing Agricultural and Forest Land Use for monitoring the processes … 2 Data and methodology 2.1 Data from the Register and interpretation keys The data from the Register for 2002, 2005, 2009, 2011, and 2013 are freely available at the Ministry of Agriculture, Forestry and Food's website (Internet 1). The Register's timeline is presented in detail in the paper by Miličić and Udovč (2012). The key to understanding and interpreting data is to know the interpretation keys (here- inafter:  IK) (Interpretation Key  1.0  2002; Interpretation Key  2.0  2004; Interpretation Key 3.0  2005; Interpretation Key 4.0 2006; Interpretation Key 4.1 2008; Interpretation Key 5.0 2009; Interpretation Key 5.2 2011; Interpretation Key 6.0 2013) with a comprehensive description of land use capture, illustrative examples, and size of the areas. There are major modifications in IK 2.0, 3.0, 4.0, 5.0, and 6.0, and only minor modifications in 4.1, 5.1, and 5.2, which relate to agricultural land and do not influence the PiSZ land use capture. The IK structure from versions 2.0 to 6.0 remained the same. In IK (2004), the use of PiSZ is defined as land with buildings, roads leading to urban areas and houses, parking lots, mines, quarries and other infrastructures intended for human activities. This category includes undeveloped land that is insepara- bly connected with human activities, such as: • industrial and domestic waste sites, • abandoned land inside built-up areas, • city parks and gardens, • recreational areas, • gardens and extensive orchards next to buildings if they are smaller than the minimum area prescribed, and appertaining land of buildings, • weirs, embankments and bridges if larger than 25 m2, • hay barns fall within this category if they have a roof or are situated in land zoned for building, • permanent buildings in agricultural land if they are larger than 25 m2 (apiaries, barns, sheds, etc.), • zones along motorways, sown with grasses, trees and shrubs, and enclosed by fencing, are part of the motorway, • grass-covered areas at airfields and airports are included only if enclosed by fencing, • rural roads and forest roads are included in agricultural and forest land, respectively, • land within urban areas exceeding 5000 m2 is excluded. Changes regarding PiSZ land use capture were made to the following versions of interpretation keys: IK 4.0, 2006: changed the criteria for connecting too small pieces of land to neighbouring land, IK 4.1, 2008: all GERKs (Graphical Agricultural Unit of a Farm Holding) smaller than 5000 m2 and mead- ow orchards in appertaining land of structures exceeding 5000 m2 are excluded from PiSZ use; smaller pieces of land are excluded only if they are classified as a GERK, IK 5.0, 2009: all roads, cart tracks, and ditches wider than 2 m are excluded from primary land use and classified as PiSZ, IK 5.2, 2011: walled slurry pits larger than 25 m2 are included under PiSZ land use, IK 6.0, 2013: grass runway surfaces in small airfields are included under PiSZ, The smallest surface area of PiSZ land use capture increased from 10 m2 in 2002 to 25 m2 in 2005, and then stabilised (Table 1). The number of polygons of PiSZ land use capture significantly increased, i.e. from 71,279 in 2002 to 171,165 in 2013, possibly indicating the increased level of data capture accuracy. To understand the Register it is necessary to know the general instructions for data capture, where the emphasis is on the generalisation of linear structures narrower than 2 m, and the exclusion of details small- er than 2 m, the criteria of merging and connecting polygons that do not meet the minimum illustration criteria, and simplifications and positioning of lines. Since IK 2.0 (2004) onwards, the general instructions for data capture did not significantly change, and we feel that they did not affect the quality of data. 2.2 Methods The analysis was carried out at the level of Slovenia, as well as at the level of small testing areas. At the level of Slovenia, the data for 2009, 2011 and 2013 are divided into four areas (Figure 1), and the polygons are designated as OB_ID_1, 2, 3, 4. The data of 2002 and 2005 are adapted to these territorial areas. 72 58-1-Special issue_06p_1805-Mojca Foski_acta49-1.qxd 12.9.2017 7:58 Page 72 Acta geographica Slovenica, 58-1, 2018 73 Table 1: Basic characteristics of PiSZ land use category at various points in time (Interpretacijski ključi … MKGP, author's calculations). Basic data 2002 2005 2009 2011 2013 Year of digital ortophoto image production as the 1997–2002 2000–2003 2006 2010, 2011 2011, 2012, 2013 source of data capture Minimum PiSZ land use capture area 10 m 2 25 m2 25 m2 25 m2 25 m2 No. of independent PiSZ 71,279 (654,270) 79,340 (715,243) 140,226 (965,793) 170,250 (1,481,001) 171,165 (1,639,321) and use polygons out (10.8%) (11.1%) (14.5%) (11.5%) (10.4%) of all polygons Interpretation Key (version) 1.0 2.0, 3.0 4.0, 4.1 5.0, 5.1, 5.2 6.0, 6.1 Distinctive features All land smaller than Cart tracks and rural The built-up and in interpretation keys 5000 m2 and the land roads wider than 2 m related land use for PiSZ land use classified as GERK and walled slurry pits includes grass-covered is excluded. larger than 25 m2 runways at small are captured. airfields. A detailed data analysis was conducted for NE Slovenia (area 4 designated as NES, Figure 1), where the A5 Maribor–Pince motorway section was built or upgraded. Because the data for area 4 NES do not reflect the expected increase in PiSZ land use, a further analy- sis in selected testing areas was conducted: • an analysis of three continuous and three dispersed rural settlements, • an analysis of infrastructure installations (motorway, rural roads and cart tracks, railway, small airfields and energy facilities). The analysis was performed in 0.5 × 0.5 km quadrants, where the DOFs of 2002 and 2013 show no con- siderable changes that could be reflected in PiSZ land use data. The selection of areas without any actual changes in space is essential, because then the data acquired would reflect both the methodological changes in data capture as well as the capturer's interpretive abilities. The data analysis and processing were performed by using the functions of merging, overlaying and clipping of vector data layers in ArcMap 10.2 and Excel 2007. area 3: NWS area 1: SWS area 2: SES area 4: NES Figure 1: Data processing areas for the territory of Slovenia. 3 Results 3.1 Analysis of land use »built-up and related land« for the territory of Slovenia The graphic calculation of PiSZ land use for each study area (Figure 1), and for the entire Slovenia is given in Table 2 and Figure 2. The proportion of PiSZ land use related to the surface of all land uses in the Register is 58-1-Special issue_06p_1805-Mojca Foski_acta49-1.qxd 12.9.2017 7:58 Page 73 Table 2: The graphic calculation of PiSZ land use per individual areas in Slovenia (Figure 1) and for the entire Slovenia in 2002, 2005, 2009, 2011 and 2013 (MKGP 2013; authors' calculation). Year of the data from 2002 2005 2009 2011 2013the Register analysed Quantified graphic surface of all land uses 2,036,575 2,032,733 2,032,617 2,032,712 2,032,710 in the Register (ha) Built-up and related Built-up and related Built-up and related Built-up and related Built-up and related land (PiSZ) land (PiSZ) land (PiSZ) land (PiSZ) land (PiSZ) (ha) (%) (ha) (%) (ha) (%) (ha) (%) (ha) (%) area 1: SWS 35,026 1.72 37,160 1.83 36,509 1.80 37,179 1.83 37,016 1.82 Study area 2: SES 15,338 0.75 16,230 0.80 15,688 0.77 15,567 0.77 15,640 0.77 area area 3: NWS 15,382 0.76 16,067 0.79 14,889 0.73 15,913 0.78 16,096 0.79 area 4: NES 42,727 2.10 44,999 2.21 40,310 1.98 40,173 1.98 40,443 1.99 Slovenia 108,473 5.33 114,456 5.63 107,397 5.28 108,832 5.35 109,195 5.37 0 20.000 40.000 60.000 80.000 100.000 120.000 140.000 SWS SES NWS NES Slovenia Testing area h a 2002 2005 2009 2011 2013 Figure 2: Illustration of PiSZ surface changing per individual study areas (Figure 1) in various periods (MKGP 2013; author's illustration). 74 also calculated. The surface of all land uses in the Register varied between 2,036,575ha in 2002 and 2,032,710ha in 2013, i.e. by 3.865 ha. The total surface of all land uses in the Register stabilised in 2011 and 2013, as there was only a 2-ha variation between the last two periods. First, the PiSZ surface and proportion from the first data capture in 2002 until 2005 rose substantial- ly from 108,473 ha to 114,456 ha (by 2983 ha) or 0.3%, and then in 2009 they decreased to the lowest level of 107,397 ha or a 5.28% proportion of all land uses. From 2011 to 2013, the PiSZ land use surface area grew by 363 ha or 0.02%. Mojca Foški, The (non)usefulness of the Register of Existing Agricultural and Forest Land Use for monitoring the processes … 58-1-Special issue_06p_1805-Mojca Foski_acta49-1.qxd 12.9.2017 7:58 Page 74 Figure 3: The progression of the A5 Maribor–Pince motorway construction in the Register by years, shown on the grid of sheets of the Basic Topographic Map (Arh 2012). Table 3: Built-up and related land associated to the A5 Maribor–Pince motorway section (Arh 2012). Year Built-up and related land (PiSZ), associated to the Maribor–Pince A5 motorway section (ha) 2002 0 2005 76 2009 198 2011 465 75 Acta geographica Slovenica, 58-1, 2018 Between 2002 and 2005 the data capture methodology's criterion regarding PiSZ increased from 10 m2 to 25 m2. It can be said that the accuracy of acquisition decreased, which probably affected the determi- nation of the maximum PiSZ land use in the time period in question. Based on the reduced surface in 2009 we can conclude that in the previous observation cycle there was no significant urbanisation growth. The reduced surface in 2009 could result from the changed data capture methodology concerning agricultur- al land within urban areas, since until 2008 it only covered continuous agricultural land larger than 5000 m2, while after 2008 also land smaller than 5000 m2, complying with the criteria for capturing other types of existing use, and extensive meadow orchards smaller than 1000 m2 if they are inscribed as GERKs. 3.2 Analysis of »built-up and related land« land use acquisition for NE Slovenia During 2000–2009 the construction of the A5 Maribor–Pince motorway section was underway in area 4 NES (Figure 1). The Pomurje motorway branch consists of seven sections, and the connecting regional roads Legend Motorway in Register 58-1-Special issue_06p_1805-Mojca Foski_acta49-1.qxd 12.9.2017 7:58 Page 75 Mojca Foški, The (non)usefulness of the Register of Existing Agricultural and Forest Land Use for monitoring the processes … 76 0,00 2,00 4,00 6,00 8,00 10,00 12,00 2002 2005 2009 2011 2013 Dispersed settlement Dispersed settlement Dispersed settlement Continuous settlement Continuous settlement Continuous settlement h a Figure 4: PiSZ use from the Register in testing areas of settlements (MKGP, author's illustration). to Murska Sobota are included in the total length. The construction of the first motorway section Vučja vas–Beltinci in a length of 14.6 km started in 2000, and was put into service in 2002/2003, while the rest of the motorway of 71.2 km was completed between 2006 and 2008 (DARS 2006). As this was the only major building intervention in the 2000–2009 period, we analysed the PiSZ land use change in area 4NES. From the data from the Register we specifically excluded the motorway A5 branch (Figure 3) and graph- ically calculated the associated motorway area (Table 3). The 2011 data from the Register show that the surface of the A5 Maribor–Pince section is 465 ha. From 2002 to 2011, the surface of PiSZ land use should increase by at least this amount, but this is not reflect- ed in the data, as shown in Table 2 and Graph 1. On the contrary, in this period PiSZ decreased in area 4 NES, – the most among all Slovenian areas in question. 3.3 Analysis of PiSZ land use capture on the sample of settlements We selected three dispersed and three continuous test settlements, and calculated, for 0.5 × 0.5 km areas, the graphic surface of PiSZ land use from the Register. The results are presented in Table 4 and Figure 4. The decrease in PiSZ land use surface between 2011 and 2013 was established in three testing areas, even though, based on the results for the entire Slovenia, we thought that the data capture methodology had stabilised. In testing area 6 (Figure 5), the surface reduction was mostly due to the exclusion of exten- sive orchards in the settlements and at their edges. Extensive orchards in the settlements right next to housing and agricultural structures are the appertaining land of the structures and thus in spatial sciences con- sidered as part of the built-up area. 58-1-Special issue_06p_1805-Mojca Foski_acta49-1.qxd 12.9.2017 7:58 Page 76 Acta geographica Slovenica, 58-1, 2018 77 Table 4: PiSZ use from the Register in testing areas of settlements (MKGP, author's calculation). Testing area 1 Testing area 2 Testing area 3 Testing area 4 Testing area 5 Testing area 6 dispersed dispersed dispersed continuous continuous continuous settlement settlement settlement settlements settlements settlements Area centroid Y: 578989 Y: 584012 Y: 614838 Y: 595499 Y: 613490 Y: 579040 X: 165290 X: 185752 X: 157074 X: 171530 X: 159598 X: 167805 Built-up and related land (PiSZ) in the Register in testing areas 0.5 × 0.5 km (ha) (ha) (ha) (ha) (ha) (ha) 2002 4.986 2.417 4.221 6.647 2.576 10.677 2005 3.718 2.417 3.600 6.531 2.418 10.561 2009 3.815 1.357 3.174 6.807 2.144 10.753 2011 3.469 1.543 3.565 6.957 1.275 8.302 2013 3.021 1.568 3.565 6.514 1.275 7.792 3.4 Analysis of PiSZ land use acquisition for infrastructure We randomly selected six testing areas of a size of 0.5 × 0.5 km with various infrastructure facilities and installations. Even though there are no methodological changes in the interpretation keys concerning motorways, there are significant discrepancies in the surface area of PiSZ land use (testing areas 7 and 8 in Table 5, Figure 6). In the testing area of a small airfield (testing area 10) the impact of the changed data capture methodology 0 0.2 km Content by: Mojca Foški Map by: Mojca Foški Source: Ministrstvo za kmetijstvo © 2015, UL FGG Testing area 0.5 km × 0.5 km Legend PiSZ_2013 PiSZ_2011 PiSZ_2009 PiSZ_2005 PiSZ_2002 Figure 5: PiSZ use from the Register in the case of testing area 6 (MKGP, author's illustration). 58-1-Special issue_06p_1805-Mojca Foski_acta49-1.qxd 12.9.2017 7:58 Page 77 Mojca Foški, The (non)usefulness of the Register of Existing Agricultural and Forest Land Use for monitoring the processes … 78 Table 5: PiSZ use from the Register in the area of infrastructures (MKGP, author's calculation) *In 2002 and 2005 there was no motorway yet, so the PiSZ land use was not captured. Testing area 7 Testing area 8 Testing area 9 Testing area 10 Testing area 11 Testing area 12 motorway. motorway _2 cart tracks/ small airfield railway power plant rural roads Area centroid Y: 588188 Y: 575096 Y: 596278 Y: 590505 Y: 589637 Y: 560870 X: 166209 X: 160374 X: 164261 X: 165752 X: 170578 X: 145147 Built-up and related land (PiSZ) in the Register in testing areas 0.5 × 0.5 km (ha) (ha) (ha) (ha) (ha) (ha) 2002 0* 0.510 0 1.326 1.862 7.658 2005 0* 0.246 0 1.073 0.925 7.636 2009 4.039 2.124 0.282 1.499 1.336 6.530 2011 2.652 5.231 0.453 1.377 1.037 6.577 2013 2.917 2.998 0.363 6.749 1.064 7.931 0,00 1,00 2,00 3,00 4,00 5,00 6,00 7,00 8,00 9,00 Motorway 2002 2005 2009 2011 2013 h a Motorway Cart tracks Small airfield Railway Power plant Figure 6: »Built-up and related land« from the Register in the area of infrastructures ((MKGP, author's illustration). 58-1-Special issue_06p_1805-Mojca Foski_acta49-1.qxd 12.9.2017 7:58 Page 78 is evident (IK 6.0 2013), because the runway previously classified under the category of permanent mead- ows is now also classified as PiSZ. The surface changes in testing area 12 (power plant) cannot be attributed to the changed data capture methodology; we think that the discrepancy is the result of the capturer's inter- pretive abilities. The smallest discrepancies are associated with the railway area. 4 Discussion Urban land use, which covers all built-up areas, areas with infrastructure facilities, and other areas that permanently changed from a natural to a built environment, is in general increasing in all countries and environments. We are certain that this is also the case in Slovenia, since SURS data (2013) show that, from 2007 to 2013, 29,972 building permits were issued for new spatial interventions. In Slovenia there are no in-depth analyses of the situation and trends concerning the urban area changes; Topole etal. (2006) and Bole etal. (2007) analysed several rural settlements, Ravbar (2007) noticed the trend of increasing settlement surfaces in suburban settlements and on urban outskirts, while Bole (2015) noticed the trend of increasing traffic sur- faces. The data from the Register for the level of Slovenia in the first three data capture campaigns (2002, 2005, 2009) vary considerably and indicate even a decrease in PiSZ surfaces, which is a rare occurrence, i.e. that urban land would be restored to its original use. Golobič (2013) reports only one such case, i.e. the Gorenjska motorway section between Črnivec and the Peračica viaduct, which the municipality converted back to agricultural land after the completion of the motorway. After 2009 there are no major variations in PiSZ use, so the change in PiSZ land use could be the reflec- tion of increased urbanisation. However, the results for testing area 4 of NE Slovenia (NES) (Figure 1) rejected this claim, as between 2005 and 2011 there was no considerable increase in surface area by 465 ha, i.e. the surface area of the newly built motorway A5 Maribor–Pince branch. Urbanisation cannot be accountable for the rise by 0.02% or 360 ha of PiSZ land use from 2011 to 2013, because in the most recent period the analysis of 12 testing areas also revealed huge discrepancies in the data capture methodology. The increase in PiSZ areas is the result of methodological changes of settle- ment data capture (exclusion of agricultural land from settlements), capture of rural roads and cart tracks wider than 2 m, and some other types of land (the case of small airports). There is a general tendency that the PiSZ land use is captured increasingly closer to the structures, as also reported by Arh (2012). There is a particularly large discrepancy concerning dispersed settlements where the PiSZ land use is limited by many polygons. Land use by appertaining land of structures was not captured. We can confirm the hypothesis that the existing Register is not suitable for determining urban land use areas and their changes, and also not for formulation of the indicator of urban land use changes in the territorial monitoring system (Poročilo … 2015). The deficiency of the Register for determining the areas zoned for development is also pointed out by Lampič and Repe (2012). At the same time, we draw attention to the fact that its use for determining the discrepancy between the actual situation in space and the planned land use in the illustration of spatial situation in the Municipal Spatial Plan Preparation Procedure is unsuitable, even though the use of the Register is prescribed both by the Spatial Planning Act (2007) and the Rules on Land Use and Legal Regimes Data (2008). The dis- crepancies in the illustration of spatial condition may be due to the Register's shortcomings, and do not necessarily reflect the spatial potential; indeed, this can lead to professional errors. Next to the spatial non-homogeneity of the source DOFs in various periods, as pointed out by Krevs (2004), we find that the data capture methodology is inhomogeneous as well, and that there are missing urban land use subcategories, which causes problems in data interpretation. Miličić and Udovč (2012), Mivšek et al. (2012), Lisec, Pišek and Drobne (2013), and Nastran and Žižek Kulovec (2014) also point- ed out the deficiencies of the Register. We propose that a single record be established, i.e. as those used in Austria (Land Information System Austria 2014), Germany (Hovenbitzer et al. 2014), Spain (Valcarcel et al. 2008) and the Netherlands (Hazeu 2014), which keep, maintain and interconnect data on land cover and land use in a single system. The integrated systems for establishing spatial and environmental monitoring, thus supporting spatial, eco- nomic and social planning and decision-making, are affected positively by the results of the project HELM (internet 2; HELM 2014), which dealt with the methodology of establishing a land use and land cover sys- tem, and the ongoing project EAGLE (EAGLE-Eionet … 2014). Acta geographica Slovenica, 58-1, 2018 79 58-1-Special issue_06p_1805-Mojca Foski_acta49-1.qxd 12.9.2017 7:58 Page 79 80 5 Conclusion Currently, the data from the Register are the only systemic and updated data source of the existing land use. By analysing records from the period between 2002 and 2013 we found that the methodological changes of urban use capture were so significant that the data do not reflect the actual urban land change. This is why the Register is unsuitable for spatial monitoring – the necessary component of spatial planning and its related activities. 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Vrščaj, B. 2007: Urbanizacija tal v Sloveniji. Strategija varovanja tal v Sloveniji. Ljubljana. Zakon o množičnem vrednotenju nepremičnin. Uradni listi Republike Slovenije 50/2006, 87/2011 in 40/2012. Ljubljana. Zakon o prostorskem načrtovanju. Uradni listi Republike Slovenije 33/2007, 70/2008, 108/2009, 80/2010 in 106/2010. Ljubljana. Mojca Foški, The (non)usefulness of the Register of Existing Agricultural and Forest Land Use for monitoring the processes … 58-1-Special issue_06p_1805-Mojca Foski_acta49-1.qxd 12.9.2017 7:58 Page 82 Acta geographica Slovenica, 58-1, 2018, 83–95 FOREST PATCH CONNECTIVITY: THE CASE OF THE KRANJ-SORA BASIN, SLOVENIA Maja Polenšek, Janez Pirnat Western part of the Kranj–Sora Basin viewed from Ambrož pod Krvavcem. M A JA P O L E N Š E K 58-1-Special issue_07p_3001-Janez Pirnat_acta49-1.qxd 12.9.2017 7:58 Page 83 84 DOI: https://doi.org/10.3986/AGS.3001 UDC: 911.53:630*(497.45) COBISS: 1.01 Forest Patch Connectivity: The Case of the Kranj-Sora Basin, Slovenia ABSTRACT: This article features a spatial analysis of forest patches, trees, and shrubs outside forests in part of the Kranj-Sora Basin in central Slovenia. Forest patch connectivity is explored using methods derived from graph theory. The graph nodes represent the forest patches and the edges between them represent the shortest connections calculated using a raster layer containing data on the resistance of individual land- use types. The contribution of an individual forest patch to habitat connectivity and availability is calculated using selected indicators. The findings show that the largest forest patches complemented by smaller patches constitute the basic connectivity tool. Thus, habitat size and close-to-nature structure are vital for the con- servation of species over short distances. In conclusion, guidelines are presented for managing and mitigating the effects of further clearing the remaining natural vegetation. KEY WORDS: forestry, geography, forest habitat patches, patch connectivity, graph theory, Kranj-Sora Basin, Slovenia Po ve za nost gozd nih za plat na pri me ru Kranj sko-Sorš ke ga po lja POVZETEK: V pris pev ku obrav na va mo pro stor sko ana li zo gozd nih za plat, dre ves in gr mov zu naj goz da na pri me ru dela Kranj sko-Sorš ke ga po lja v osred nji Slo ve ni ji. S po moč jo me tod, ki iz ha ja jo iz teo ri je gra - fov, smo pre ve ri li po ve za nost gozd nih za plat. Voz liš ča gra fa pred stav lja jo gozd ne za pla te, po ve za ve med nji mi pa naj kraj še po ve za ve, ki smo jih izra ču na li na pod la gi iz de la ne ga ra str ske ga slo ja, ki vse bu je upo - re po sa mez ne rabe zem ljišč. Pris pe vek po sa mez ne gozd ne za pla te k po ve za no sti in do stop no sti ha bi ta tov smo izra ču na li s po moč jo iz bra nih ka zal ni kov. Ugo to vi li smo, da so te melj no ogrod je za po ve za nost naj - več je gozd ne za pla te, ki jih do pol nju je jo manj še za pla te. Za ohra nja nje vrst sta tako pri krat kih raz da ljah naj po memb nej ši sta ve li kost in so na rav na zgrad ba ha bi ta ta. Na kon cu smo po da li us me ri tve za us mer ja - nje in bla ži tev učin kov na dalj njih kr či tev os tan kov na rav ne ve ge ta ci je. KLJUČNE BESEDE: goz dars tvo, geo gra fi ja, gozd ne ha bi tat ne za pla te, po ve za nost za plat, teo ri ja gra fov, Kranj - sko-Sorš ko po lje, Slo ve ni ja Maja Polenšek maja.polensek@gmail.com Janez Pirnat University of Ljubljana, Biotechnical faculty, Department of Forestry and Renewable Forest Resources janez.pirnat@bf.uni-lj.si The paper was submitted for publication on September 16th, 2015. Ured niš tvo je pre je lo pris pe vek 16. sep tem bra 2015. Maja Polenšek, Janez Pirnat, Forest Patch Connectivity: The Case of the Kranj-Sora Basin, Slovenia 58-1-Special issue_07p_3001-Janez Pirnat_acta49-1.qxd 12.9.2017 7:58 Page 84 1 Introduction According to traditional landscape-ecology theory, a landscape consists of a matrix as the predominant land-use type, in which other uses are distributed as patches and corridors (Forman 1995). In agricultural landscapes, forest habitat patches are extremely important for ensuring biodiversity. Landscape structure analyses have a significant impact on both the landscape division criteria (Petek 2005) and the understanding of changes occurring within a landscape. Habitat reduction and fragmentation are among the main rea- sons for biodiversity decline (Collinge 1996; Bailey 2007). Several studies have shown that the entire area of the habitat regardless of its spatial distribution is a dominant factor influencing the survival of a par- ticular species. When the total habitat area within a landscape falls below 50% (Flather and Bevers 2002; Crouzeilles et al. 2014) or, as reported by Andren (1994), below 30%, the distribution of habitat patches becomes equally important as the habitat area. The concept of habitat connectivity makes it possible to understand and measure the interconnected ecological impacts of habitat loss and fragmentation (Laita, Kotiaho and Mönkkönen 2011). The aim of this study is to determine whether the forest habitat patches in the selected study area are functionally connected and to identify the most important connecting for- est patches that contribute the most to maintaining forest patch connectivity. 1.1 Habitat patch connectivity and graph theory Over the past decade, a number of habitat patch connectivity studies have relied on mathematical graph theory and the network theories derived from it (Bunn et al. 2000; Zetterberg, Mörtberg and Balfors 2010; Saura et al. 2011; Zetterberg 2011; Mazaris et al. 2013). In graph theory, graphs make it possible to com- bine population processes with spatial patterns and their connectivity at both the level of landscapes and individual patches (Urban and Keitt 2001). A habitat patch connectivity analysis using graph theory methods makes it possible to assess the functional connectivity of individual patches (Laita, Kotiaho and Mönkkönen 2011). In this way one can assess the spatial importance of habitats and their connectivity (Bunn et al. 2000). 1.2 Habitat patch connections The findings of several studies show that matrix heterogeneity has a strong impact on movement between habitat patches (Ricketts 2001; Russell, Swihart and Feng 2003; Revilla et al. 2004). The matrix is composed of various elements that have different effects on the spatial movement of species. Some land-use types represent barriers that are difficult to cross (e.g., rivers and freeways), whereas others make movement easier, often by providing shelter and food. This determines the resistance – that is, how demanding a spe- cific land-use type is for crossing. Based on this, effective distances are calculated; they represent the shortest functional connections between habitat patches. From the biological perspective, identifying resistance is the most important step in calculating effective distance (Adriaensen et al. 2003). Methods derived from graph theory were used to calculate the effective distance, whereby the graph nodes were the forest patches and the graph edges with the least resistance for species movement between them were the shortest effective distances (Polenšek 2015). The predominantly flat northeastern part of the Kranj-Sora Basin was selected as the study area, as shown in Figure 1. This area is strongly affected by intensive farming (Rejec Brancelj 2001) and urbanization. The study area covers 10,423.65 ha, of which the forest covers 3,901.46 ha or 37.4%; in the flat part of the study area forest coverage is even smaller (27.7%). Across the entire study area, the forest is fragmented into 150 patches, ranging in size from 0.25 ha to 718.97 ha (Polenšek 2015). 2 Methods 2.1 Connectivity indicators Proceeding from graph theory, researchers specializing in landscape ecology and other related disciplines have developed a number of indicators for assessing patch connectivity in landscapes. Bodin and Saura (2010) 85 Acta geographica Slovenica, 58-1, 2018 58-1-Special issue_07p_3001-Janez Pirnat_acta49-1.qxd 12.9.2017 7:58 Page 85 0 1 2 3 4 km0.5 Legend Study area boundary Content by: Maja Polenšek Map by: Maja Polenšek Source: © 2011, GURS Scale: Figure 1: Study area. BC g k gk ij ijji = ∑∑ ( ) IIC a a nl A i j ij j n i n L = +== ∑∑ 111 2 86 suggested the indicators IIC and PC and their three fractions, and the indicator BC to calculate habitat connectivity and availability. These indicators should provide a sufficiently broad picture of habitat con- nectivity and availability without the unnecessary duplication of indicators. The Betweenness Centrality (BC) indicator is a centrality measure, which means it measures how often a specific node lies on the shortest path between all pairs of nodes. It is expressed with the following equa- tion (Zetterberg 2011): (1) gij = the number of the shortest paths between i and j, gij(k) = the number of the shortest paths actually crossing node k. Bodin and Norberg (2007) successfully used this indicator to identify the connecting patches between habitat patches. The Integral Index of Connectivity (IIC) is expressed as (Pascual-Hortal and Saura 2006): (2) where ai and aj are the areas of habitat patches i and j, nlij is the number of all the links on the shortest path between patches i and j, and AL is the total landscape area (the habitat and the matrix). Maja Polenšek, Janez Pirnat, Forest Patch Connectivity: The Case of the Kranj-Sora Basin, Slovenia 58-1-Special issue_07p_3001-Janez Pirnat_acta49-1.qxd 12.9.2017 7:58 Page 86 PC a a p A PCnum A i jj n i n ij L L = === ∗∑∑ 11 2 2 dPC PC PC PC PC PCk remove k k= ⋅ − = ⋅100 100, ∆ 87 Acta geographica Slovenica, 58-1, 2018 IIC is based on a binary connectivity model, which means that two patches are either connected or not (e.g., because the distance is too great) with no intermediate modulation of the connection strength (Saura and Pascual-Hortal 2007). The Probability of Connectivity (PC) indicator is a measure that reflects the availability of a given habi- tat within a landscape. It is defined as the probability that two randomly placed points within the landscape fall into habitat areas that are reachable from one another (interconnected) given a set of n habitat patches and the direct connections between them (pij; Saura and Pascual-Hortal 2007). It is expressed with the fol- lowing formula: (3) where ai and aj are the areas of habitat patches i and j (they can also refer to some other patch character- istic such as quality, core area, habitat suitability, etc.), AL is the total landscape area (the habitat and the matrix), and pij is the maximum product probability of all possible paths between patches i and j. The significance of an individual habitat patch is computed from the variation in PC (dPCk) or IIC (dIICk) caused by the removal of each individual element from the landscape (Saura and Rubio 2010): (4) where dPCk is the importance of element k for maintaining overall habitat availability in the landscape, PC is the metric value in the original intact landscape where all elements including k are present, and PCremove,k is the metric value after the removal of k. The dPCk (or dIICk) values can be composed of three distinct fractions considering the different ways in which a certain landscape element k can contribute to habitat availability and connectivity in the land- scape (Saura and Rubio 2010): dPCk = dPCintrak + dPCfluxk + dPCconnectork (5) • dPCintrak is the habitat connectivity or availability within patch k that depends on patch characteris- tics such as habitat area or quality (e.g., the state of its conservation) and is independent of how patch k may be connected to other patches; • dPCfluxk is the area-weighted dispersal flux through the connections of patch k to or from all of the other patches in the landscape when k is either the starting or ending patch of that connection or flux. It depends on the attribute of patch k and its position within the landscape network. It measures how well patch k is connected to other patches rather than how important that patch is for maintaining connectivity between the rest of the patches; • dPCconnectork is the contribution of patch or link k to the connectivity between other patches as a con- necting element between them. It depends only on the topological position of a patch or link in the landscape network. 2.2 Producing a resistance digital data layer Forest animals that also feed on farmland were used as hypothetical species for determining the relative resistance of individual land-use types. Resistances used by Adriaensen et al. (2003) were used as a basis and adjusted to individual land-use type (Table 1). A smaller number indicates lower resistance for crossing a certain land-use type, and a larger number indicates higher resistance. Forestland has the lowest resis- tance and represents the graph nodes. The woody growth outside the forest was assigned the same resistance as the forest areas, but it does not form nodes because its area is too small. Regardless of the crop type, farmland was assigned a slightly higher resistance because it mostly does not provide the same shelter as forest areas. Infrastructural areas were divided into highways, state roads, and major municipal roads that differ from one another largely by the volume of traffic and the average vehicle speed. With regard to free- ways, passages were also taken into account (primarily underpasses in this case). Freeways, urban land, 58-1-Special issue_07p_3001-Janez Pirnat_acta49-1.qxd 12.9.2017 7:58 Page 87 θPCfraction dPCfraction dPC kk n kk n= = = ∑ ∑ 1 1 88 and bodies of water, which represent a relative rather than absolute barrier for many animal species, were identified as land types that are the most difficult to cross. In determining the resistance of land-use types that are the most difficult to cross, the findings of Driezen et al. (2007) were taken into account. They show that the distinct difference between the resistances of land-use types that are more difficult to cross and those that are easier to cross is vital in determining resistance. Table 1: Cell resistance by individual land-use type (Polenšek 2015). Land-use type Cell resistance Forestland (habitat) 1 Trees and shrubs (woody growth) 1 Farmland 5 State roads 20 Municipal roads 10 Urban land 200 Bodies of water 200 Freeways 200 Freeways (municipal road underpass) 50 Freeways (forest road underpass) 30 Freeways (bridge across a river) 20 The land-use vector digital data layer (Grafični podatki RABA … 2012) was converted into a raster data layer with a 1 × 1 m cell size using ArcMap/ArcInfo10.0 in order to correctly capture the line elements and the smallest woody growth (individual trees). The reviewed land-use raster data layer was exported into GEOTIFF format. 2.3 Computing forest patch connectivity The edge-to-edge inter-patch connections were computed using the Graphab 1.1 software package (Foltête, Clauzel and Vuidel 2012), which makes possible calculations across larger areas with a high raster reso- lution. This software computes the least-cost distances by using Dijkstra’s algorithm (Foltête, Clauzel and Vuidel 2012). The movement cost was computed by adding up all of the cell costs within a connection. A connection is measured from the center of the neighboring cell, whereby its cost corresponds to half of the sum of both cells’ costs. In the case of a diagonal movement between two cells, the cost sum is multi- plied by (Drielsma, Manion and Ferrier 2007). 2.4 Habitat connectivity and availability The indicators were computed using Conefor 2.6 (Saura and Torné 2009) based on the data charts export- ed from the Graphab 1.1 software package (Foltête, Clauzel and Vuidel 2012). Computations were made for inter-patch distances ranging from 100 to 20,000 m at 100 m intervals. For every distance, the relative contribution of the intra, flux, and connector fractions for the dIIC and dPC indicators was calculated (Saura and Rubio 2010): (6) Based on an analysis of distances up to 20,000 m across the entire landscape, the distances with the greatest changes in the dPC and dIIC metric values were identified. 2.5 The most important connecting patches Baranyi et al. (2011) established that the indicators BC, dIICconnector, and dPCconnector are the most suc- cessful among the thirteen indicators most commonly used for identifying the most important connecting Maja Polenšek, Janez Pirnat, Forest Patch Connectivity: The Case of the Kranj-Sora Basin, Slovenia 58-1-Special issue_07p_3001-Janez Pirnat_acta49-1.qxd 12.9.2017 7:58 Page 88 Figure 2: Sums of indicator changes. 0 50 100 150 200 250 300 350 Transition distance (m) A) dPCΣ A) dIICΣ S u m v a lu es o f in d ic at o r 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0 2 5 0 0 3 0 0 0 3 5 0 0 4 0 0 0 4 5 0 0 5 0 0 0 5 5 0 0 6 0 0 0 6 5 0 0 7 0 0 0 7 5 0 0 8 0 0 0 8 5 0 0 9 0 0 0 9 5 0 0 1 0 0 0 0 1 0 5 0 0 1 1 0 0 0 1 1 5 0 0 1 2 0 0 0 1 2 5 0 0 1 3 0 0 0 1 3 5 0 0 1 4 0 0 0 1 4 5 0 0 1 5 0 0 0 1 5 5 0 0 1 6 0 0 0 1 6 5 0 0 1 7 0 0 0 1 7 5 0 0 1 8 0 0 0 1 8 5 0 0 1 9 0 0 0 1 9 5 0 0 89 Acta geographica Slovenica, 58-1, 2018 patches. They are used to assess not only how well a specific patch is connected with other patches, but also how important it is for maintaining connectivity. The method of ranking forest patches by priority in terms of their contribution to connectivity was adopted from Lee, Woddy, and Thompsonu (2001), whereby forest patches were ranked by individual indi- cators (BC, dIICconnector, and dPCconnector). Then their rankings were added up, based on which a new cumulative ranking was defined. For selected movement distances, forest patches were ranked in IBM SPSS Statistics 21 such that a ranking of 1 was ascribed to the forest patch with the highest score for individual indicator. All of the three indicator rankings by individual forest patch were added up and based on the ranking sums the forest patches were ranked such that the highest ranking was ascribed to the patch with the lowest-ranking sum. Forest patches were divided into three groups according to their contribution to connectivity: connect- ing patches with high impact, connecting patches with low impact, and patches with no impact on connectivity. Based on the indicator-based forest-patch contribution to connectivity within various distances of movement, the first twenty forest patches within the same ranking were ranked under the first group. These patches contribute the most to connectivity according to all three indicators. The second group included for- est patches that still have some impact on connectivity in terms of the indicators selected. The last group included those that do not contribute anything to connectivity in terms of any of the three indicators selected. 3 Results The study area includes 150 forest patches that are connected with 268 functional links. The number of links depends on the longest possible movement distance: the longer the distance, the more links between the forest patches. The threshold where the number of links no longer increased was recorded at a dis- tance of 14,400 m. The distances ranged between 4 and 14,361 m and the median distance was 2,289 m. 3.1 Forest-patch contribution to maintaining habitat connectivity and availability within various movement distances The changes in dIIC and dPC, which depend on the longest possible distances, are presented in Figure 2. The dIIC scores change incrementally, with the highest score being reached at distances of up to 2,900 and 58-1-Special issue_07p_3001-Janez Pirnat_acta49-1.qxd 12.9.2017 7:58 Page 89 Table 2: Forest patches ranked by importance as connecting patches within various distances (n = 150). Forest patches Most important connecting patches Less important connecting patches Without impact on connectivity Distance (m) n ha n ha n ha 800 20 1,728.27 63 1,991.61 67 181.58 1,500 20 1,838.22 71 1,910.21 59 153.03 3,000 20 2,777.40 95 1,067.75 35 56.31 7,100 20 3,371.04 103 482.36 27 48.06 15,500 20 3,355.27 105 499.28 25 46.92 90 3,000 m, and the second-highest scores being reached at distances of up to 200, 1,500, and 2,300 m. The dPC scores do not show such distinct variations as dIIC. The highest score is achieved at a distance of up to 15,500 m. Slightly greater changes in the dPC indicator are evident within distances of up to 700 or 800 m and 7,300 m. Within these distances, the importance for connectivity is the greatest, and the role of patch- es in maintaining the connectivity of the overall forest-patch network decreases with the increase in distance. Individual relative fraction contributions for dIIC are presented in Figure 3. Within movement distances of up to 100 m, the majority of forest patches are not connected with one another, which is reflected in both the large number of graph components and the high contribution of the dIICintra fraction. The contribu- tion of dIICintra already decreases significantly within distances of up to 200 m, whereas the contribution of dIICflux increases. Within distances of up to 1,500 m, the contribution of dIICconnector increases. A major increase in dIICconnector then occurs within distances of up to 2,300m. The dIICconnector fraction contributes the most within distances between 2,900 and 3,200m. Within distances up to 5,100m, the fraction ratio slow- ly stabilizes at two-thirds of dIICflux and one-fifth of dIICconnector, and the remainder pertains to dIICintra. The contributions of the dPC fraction are presented in Figure 4. Similarly, the dPCintra fraction pre- dominates within short movement distances, whereas dPCflux predominates within distances of up to 500m. Within distances of up to 8,200 m, the ratios slowly stabilize, with one-third pertaining to dPCconnector, 9% to dPCintra, and the rest to dPCflux. 3.2 The most important connecting patches within the movement distances selected Based on the changes in dIIC and dPC scores within various distances, the distances where both indica- tors feature the greatest changes in habitat connectivity and availability were selected. Thus, five distances were selected: 800, 1,500, 3,000, 7,100, and 15,500 m. In Figure 5, forest patches are ranked into three groups by their importance for maintaining connectivity between other forest patches within all five distances. The area of the twenty most important connecting patches increases with the greatest possible dis- tance, so that they cover 44% of the forest in the study area within distances of up to 800 m, and 86% within distances of up to 15,500 m (Table 2). Forty-one most important connecting patches were identified with- in all of the distances examined in greater detail. Eight forest patches are important within all distances and eighteen patches only occur within one distance. The areas of important connecting patches range from 0.62 to 718.98 ha, with larger patches predominating. In addition to the twenty most important forest patches identified, other forest patches also contribute to maintaining connectivity to some degree. With the increase in distance, their number increases from 42 to 70% of all forest patches and, vice versa, their total area decreases from 51 to 13% of the total forest area. A part of the forest patches does not have any impact on connectivity. Just under half (45%) of such patches are within short distances, but they cover only 5% of the total forest area. Their number decreas- es significantly with distance: to at least as little as one-sixth of all forest patches or 1% of the forest area. 4 Discussion The Integral Index of Connectivity (dIIC) most clearly shows the critical distances because it uses a binary con- nections model, in which the connection either exists or does not. However, this index divides the landscape Maja Polenšek, Janez Pirnat, Forest Patch Connectivity: The Case of the Kranj-Sora Basin, Slovenia 58-1-Special issue_07p_3001-Janez Pirnat_acta49-1.qxd 12.9.2017 7:58 Page 90 0% 20% 40% 60% 80% 100% 50 0 10 00 15 00 20 00 25 00 30 00 35 00 40 00 45 00 50 00 55 00 60 00 65 00 70 00 75 00 80 00 85 00 90 00 95 00 10 00 0 10 50 0 11 00 0 11 50 0 12 00 0 12 50 0 13 00 0 13 50 0 14 00 0 14 50 0 15 00 0 15 50 0 16 00 0 16 50 0 17 00 0 17 50 0 18 00 0 18 50 0 19 00 0 19 50 0 Transition distance (m) 10% 30% 50% 70% 90% C o n tr ib u ti o n t o o ve ra ll h ab it at a cc es si b il it y θIICintra θIICflux θIICconnector 0% 20% 40% 60% 80% 100% 10% 30% 50% 70% 90% Transition distance (m) C o n tr ib u ti o n t o o ve ra ll h ab it at a cc es si b il it y 50 0 10 00 15 00 20 00 25 00 30 00 35 00 40 00 45 00 50 00 55 00 60 00 65 00 70 00 75 00 80 00 85 00 90 00 95 00 10 00 0 10 50 0 11 00 0 11 50 0 12 00 0 12 50 0 13 00 0 13 50 0 14 00 0 14 50 0 15 00 0 15 50 0 16 00 0 16 50 0 17 00 0 17 50 0 18 00 0 18 50 0 19 00 0 19 50 0 θIICintra θIICflux θIICconnector Figure 3: Relative contribution of an individual dIICk fraction. Figure 4: Relative contribution of an individual dPCk fraction. 91 Acta geographica Slovenica, 58-1, 2018 58-1-Special issue_07p_3001-Janez Pirnat_acta49-1.qxd 12.9.2017 7:58 Page 91 Legend Least-cost paths Study area boundary Most important connectivity patches Less important connectivity patches Patches with no in!uence on connectivity Scale: Content by: Maja Polenšek Map by: Maja Polenšek Source: © 2005, GURS 0 4 8 12 16 km2 Figure 5: Forest patches by importance. network into two unconnected parts (Bodin and Saura 2010). With the Probability of Connectivity (PC) indi- cator, the critical distances are much less clear because it uses a probability model, in which the loss of a connecting patch only reduces the amount of flux. Unlike dIIC, thanks to the probability model dPC also detects changes in landscape network connectivity within longer distances. Within short distances, the share of connected patches is small, resulting in a higher share of completely isolated patches. The land-use types that are more difficult to cross have a greater impact on movement than those easier to cross. In the case at hand, the negative impact of roads and settlements within short distances is greater than the positive impact of woody growth. The spatial distribution of patches does not 92 Maja Polenšek, Janez Pirnat, Forest Patch Connectivity: The Case of the Kranj-Sora Basin, Slovenia 58-1-Special issue_07p_3001-Janez Pirnat_acta49-1.qxd 12.9.2017 7:58 Page 92 93 Acta geographica Slovenica, 58-1, 2018 play a significant role. The importance of habitat patch connectivity increases rapidly with the increase in the longest possible distance. Within medium distances, the connecting patches are the most important, enabling the connectivity of more remote patches. Contrary to short distances, the areas within the matrix that are easier to cross (in this case, woody growth) have a greater impact. Within longer distances, forest patches again lose importance as connecting patches because of the increased number of direct connec- tions. Remote patches also become interconnected and depend less on the connecting patches. The selection of the most important connecting patches that contribute the most to maintaining habitat connectivity and availability compared to other forest patches showed that large forest patches in particular are the most important because the movement distances increase significantly with their loss. At the same time, they are complemented by smaller forest patches, whose distribution contributes to better connectivity of remote forest patches. A comparison of selected movement distances showed that within all of the distances exam- ined the most important connecting patches do not change significantly. In Europe, a new 2014–2020 agricultural policy is under preparation, which also includes a green com- ponent, for which a third of subsidy funds will be earmarked (Overview of CAP…2013). This green component will also include areas with ecological significance. Based on the study presented here, as well as other stud- ies, it is recommended that these areas also include habitat-significant forest patches, especially those whose area, close-to-nature structure, and spatial distribution are vital to maintaining spatial connectivity. This especially applies to intensively cultivated landscapes with a small share of natural vegetation, which should include a wide range of forest patches and woody growth typical of individual landscapes. 5 Conclusion Based on the findings presented here, the main guidelines for maintaining forest-patch connectivity in future clearing of forests in agricultural landscapes can be summed up as follows: • Individual forest-patch characteristics such as habitat size and close-to-nature structure are the most important for species conservation over short distances; • Priority should be given to conserving the largest forest patches, especially those with a higher share of core area; • Priority should be given to conserving all of the most important connecting patches, especially those with the most natural structure; • When clearing part of a patch, this should be done in a way that divides its shape and affects its core environment as little as possible; • Forest patches that make it possible to conserve the most vital functions should be maintained; • Another goal is to conserve larger forest patches, even though their current structure has been severely altered. It is much easier to manage the development of existing forest areas than to plan new ones on predominantly intensively farmed land. All of these guidelines also have solid support in established literature on landscape ecology (Forman 1995) because the pattern of large natural vegetation patches with corresponding connections is considered the most suitable support for biodiversity conservation in agricultural landscapes. 6 References Adriaensen, F., Chardon, J. P., De Blust, G., Swinnen, E., Villalba, S., Gulinck, H., Matthysen, E. 2003: The application of »least-cost« modelling as a functional landscape model. Landscape and Urban Planning 64-4. DOI: http://dx.doi.org/10.1016/S0169-2046(02)00242-6 Andren, H. 1994: Effects of habitat fragmentation on birds and mammals in landscapes with different pro- portions of suitable habitat: a review. Oikos 71-3. Bailey, S. 2007: Increasing connectivity in fragmented landscapes: an investigation of evidence for biodi- versity gain in woodlands. 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DOI: http://dx.doi.org/10.1890/0012-9658(2001)082[1205:LCAGTP]2.0.CO;2 Zetterberg, A. 2011: Connecting the dots: network analysis, landscape ecology, and practical application. Stockholm. Zetterberg, A., Mörtberg, U. M., Balfors, B. 2010: Making graph theory operational for landscape ecological assessments, planning, and design. Landscape and Urban Planning 95-4. DOI: http://dx.doi.org/10.1016/ j.landurbplan.2010.01.002 58-1-Special issue_07p_3001-Janez Pirnat_acta49-1.qxd 12.9.2017 7:58 Page 95 96 58-1-Special issue_07p_3001-Janez Pirnat_acta49-1.qxd 12.9.2017 7:58 Page 96 Acta geographica Slovenica, 58-1, 2018, 97–108 MULTI-CRITERIA ASSESSMENT OF LESS FAVOURED AREAS: A STATE LEVEL Karmen Pažek, Aleš Irgolič, Jernej Turk, Andreja Borec, Jernej Prišenk, Matej Kolenko, Črtomir Rozman Less Favoured Areas (LFAs) where production conditions are difficult. K A R M E N P A Ž E K 58-1-Special issue_08p_962-Karmen Pazek_acta49-1.qxd 12.9.2017 7:58 Page 97 Karmen Pažek, Aleš Irgolič, Jernej Turk, Andreja Borec, Jernej Prišenk, Matej Kolenko, Črtomir Rozman, Multi-criteria … 98 DOI: https://doi.org/10.3986/AGS.962 UDC: 332.6:631(497.4) COBISS: 1.01 Multi-criteria assessment of less favoured areas: A state level ABSTRACT: The paper present a multi-criteria decision DEXi model for assessment of less favoured areas (LFAs). The tool enables easier assessment of farming in different areas of Slovene LFAs with respect to criteria of sustainability. Analysis of LFAs and final integration of the assessment of LFAs depend upon various criteria. In this paper we analyze individual LFAs and farming systems in these areas at the state level with respect to criteria of sustainability and farming potential. KEY WORDS: geography, less favoured areas, agricultural policy, multi-criteria decision analysis, DEXi Večkriterijska ocena območij z omejenimi možnostmi za kmetijsko dejavnost: stanje v državi POVZETEK: V pris pev ku je pred stav ljen več kri te rij ski odlo či tve ni model DEX i za oce no obmo čij z omejeni - mi možnostmi za kme tij sko dejav nost (OMD). Raz vi to orod je omo go ča oce no nači na kme to va nja s pou dar kom na kri te ri ju trajnostnosti v raz lič nih OMD območ jih. Ana li za OMD obmo čij in model na inte gral na konč na ocea na kaže ta na odvi snost več kri te ri jev. Pri oce ni posa mez ne ga OMD območ ja in nači na kme to va nja na nivo ju Slo ve ni je ima ta tako pomemb no vlo go kri te rij traj no sti in poten cial posa mez ne ana li zi ra ne kme ti je. KLJUČNE BESEDE: geo gra fi ja, območ ja z ome je ni mi možnostmi, kme tij ska poli ti ka, več kri te rij ska odloči - tve na ana li za, DEX i Karmen Pažek, Aleš Irgolič, Jernej Turk, Andreja Borec, Jernej Prišenk, Matej Kolenko, Črtomir Rozman University of Maribor, Faculty of Agriculture and Life Sciences karmen.pazek@um.si, ales.irgolic@um.si, jernej.turk@um.si, andreja.borec@um.si, jernej.prisenk@um.si, matej.kolenko@gmail.com, crt.rozman@um.si The paper was submitted for publication on October 9th, 2013. Ured niš tvo je pre je lo pris pe vek 9. ok to bra 2013. 58-1-Special issue_08p_962-Karmen Pazek_acta49-1.qxd 12.9.2017 7:58 Page 98 1 Introduction The proportion of the total utilized agricultural area (UAA) classified as less favoured areas (LFAs) has raised from 33% to 65% in European Union in the last two decades. A substantial amount of the utilized agricultural area is classified as mountain areas (MacDonald etal. 2000). This situation is also seen in Slovenia, where 491.000 hectares or 72.3% of the UAA are located in mountainous and hilly areas (LFAs). Almost two-thirds of it is in permanent pasture, and arable land accounts for less than 30%. The proposed European Union indicators for defining areas less suitable for agriculture (there are eight European criteria) in Slovenia are not entirely appropriate because taking them into account would omit some distinctly and clearly unsuit- able areas, i.e. karst areas (Ciglič et al. 2012). However, as other European Union Alpine regions, Slovenia is characterized by one of the most difficult conditions for agricultural production in Europe. Overutilization of agricultural land is becoming a serious problem, although the reasons for overutilization are not the same everywhere. Efforts to combat overutilization and understanding of the background to the problem are of particular importance for improvement of agricultural land quality (Borec et al. 2004). The current rural development European policy includes significant evolution of support schemes for LFAs. Agricultural production in LFAs is usually extensive and less suited for different farming systems and agri-food pro- duction. Some authors have suggested development strategies for LFAs based on interdisciplinary research of the coupling of human and natural systems approaches (Ruben et al. 2005). Sheate et al. (2008) examined the sustainability of various scenarios for reconciling biodiversity conservation with declining agriculture use in mountain areas of Europe. Their methodology was grounded in baseline of ecological and socio-economic data. Terluin et al. (1995) examined agricultural incomes in LFAs from an economic per- spective. In their scenario, income was based on the typology of European countries and the relationship of regional gross domestic product per inhabitant and farm net value added per annual work unit. They confirmed that within the analyzed geographical areas, farmers in LFAs receive a higher amount of direct income subsidies than farmers in regions not classified as LFAs. The links between size, subsidies and per- formance for Slovenian farms were presented by Bojnec and Latruffe (2013). The study concludes that Slovenian farms have always been small and highly subsidized. Further, a conception of developmental types of mountain is presented regarding the state of developmental potentials on farms by Kerbler (2003). Assessment of farming potential on individual LFA is usually related to multiple criteria (Pažek et al. 2010). Tiwari et al. (1999) asserted that the rural reality system is complex and that the use of economic or envi- ronmental criteria alone may be insufficient. Multiple competitive criteria are likely to influence the decision-making process. A decision model must be able to evaluate all the options when considering those factors influencing the decision. A multi-criteria decision analysis approach was used in this paper to assess different organizational and planning decisions in farm management, such as the DEXi methodology (Bohanec et al. 1995; Bohanec, Zupan and Rajkovič 2000; Pažek et al. 2006; Rozman et al. 2006; Bohanec, Džeroski and Žnidaršič, 2004; Bohanec et al. 2007; Pavlovič et al. 2011, Pažek, Rozman and Irgolič 2012a). The theoretical background of hierarchical multi-attribute decision models is based on the dissection of a complex decision problem into smaller and less complex subproblems. In this context, the DEXi method uses qualitative variables and utility functions in the form of decision rules and provides qualitative assess- ments of alternatives. Subproblems are represented by variables, which are organized into a hierarchy (Pažek et al. 2012b). The aim of this paper is to present a DEXi multi-criteria decision support tool for assessment of LFAs and farming systems in these areas at the state level. 2 Materials and methods The DEXi method is a combination of traditional multi-attribute decision-making processes and spe - cific elements of expert system and machine learning techniques (Bohanec 2003). Computer program for multi-attribute decision making is called DEXi. It is aimed at interactive development of qualitative multi-attribute decision models and the evaluation of options. This is useful for supporting complex deci- sion-making tasks, where there is a need to select a particular option from a set of possible ones so as to satisfy the goals of the decision maker (Bohanec 2014). Variables are connected by utility functions. Utility Acta geographica Slovenica, 58-1, 2018 99 58-1-Special issue_08p_962-Karmen Pazek_acta49-1.qxd 12.9.2017 7:58 Page 99 Karmen Pažek, Aleš Irgolič, Jernej Turk, Andreja Borec, Jernej Prišenk, Matej Kolenko, Črtomir Rozman, Multi-criteria … functions in DEXi are adjusted to qualitative variables and, therefore, represented by »if/then« decision rules (elementary decision rules), which are usually given in a tabular form. The DEXi method can be used for solving various decision problems regarding real-world decisions (Bohanec et al. 1995; Bohanec and Rajkovič 1999; Bohanec, Zupan and Rajkovič 2000; Bohanec et al. 2006). The DEXi models are developed by defining: • attributes (a): qualitative variables that represent decision subproblems (for instance farm size, as demon- strated in Table 1); • scales: ordered or unordered sets of symbolic values that can be assigned to attributes (for instance for farm size: small to 6.00 ha, average (between 6.00 and 7.00 ha) and big (farm size is over 7.00 ha; as demon- strated in Table 2); • tree of attributes: a hierarchical structure representing the decomposition of the decision problem; • utility functions: rules that define the aggregation of attributes from bottom to the top of the tree of attrib- utes. In the evaluation and analysis stage, DEXi facilitates: • description of options: defining the values of basic attributes (terminal nodes of the tree); • evaluation of options: a bottom up aggregation of basic attributes values based on utility functions; • analysis of options: »what-if« analysis, »plus-minus-1« analysis, selective explanation and comparison of options, and • reporting: graphical and textual presentation of models, options and evaluation results. The hierarchical model structure for the assessment of LFAs that represents the decomposition of the decision problem into subproblems, was defined by the policy decision maker expert group of the Agency of the Republic of Slovenia for agricultural markets and rural development (AKTRP 2012; Irgolič 2011). The main criteria included in the model structure are: description of the farm, farm holder age structure, 100 Table 1: Hierarchical model structure for assessment of LFAs. Attribute (a) Amount of protein crops payments and nuts payments Amount of additional payments for milk Amount of additional payments for beef – – – Final assessment – Farm description – Farm size – Usage type of agricultural land – Number of assigned points – Amount of LFA payments – Social structure – Farm holder´s age – Successor or not – Successor´s age – Amount of natural handicap payments – Number of payment entitlements – Value of payment entitlements for arable land – Value of payment entitlements for pasture – Amount of payment entitlements – Amount of agri-environment payments – Organic farming – Integrated crop production – Implementation of other agri-environmental measures – Amount of payments – Amount of direct payments 58-1-Special issue_08p_962-Karmen Pazek_acta49-1.qxd 12.9.2017 7:58 Page 100 amount of natural handicap payments, amount of agri-environmental payments, and amount of direct pay- ments. Aggregate criteria were divided into groups of criteria (as seen in Table 1) and in the final evaluation of the LFAs areas: other areas, hill areas, karst areas, steep slopes, and mountain areas. The attributes at the lowest level are basic descriptors of options (in our case individual LFAs), These represent model inputs and must be provided by the decision maker. Table 2 presents the sets of scales that were defined for all attributes in the model. The decision rules are presented in a so-called complex form, with headings displaying approximate weights assigned to the attributes (second row in Table 3). The so-called »weight-based strategy« of defin- ing decision rules was used. In terms of the subattributes and the number of points assigned, if the value of the assessment points by the agency for the observed farm was less than 310, this subattribute was assigned the discrete value »bad« by the the DEXi model. If the farm was awarded between 311 and 350 points, then the discrete value was »good.« Finally, if the farm received more than 351 points, the discrete value assigned by the DEXi model was »excellent.« The symbols »≤«, »≥« define value intervals for the relevant attribute. The asterisk »*« defines any possible value. The relative importance of the attributes was expressed by weights (as seen at the top of Table 3). These weights were estimated by DEXi using a linear regression method (according to Rozman et al. 2009), where DEXi interpolates the values of previously undefined rules in the table. Linear coefficients respond to the required weights, and its surface lies as close as pos- sible to the initially specific subset of rules (Pavlovič et al. 2011). In practical use, this means the higher the weight, the more important the attribute. After each attribute was assigned to a scale, the utility functions were defined (Table 3). The utility functions evaluate and define individual attributes with respect to their immediate descendants in the hier- archy. The utility function procedure was derived for each level in the hierarchy (partial utility function for aggregate attributes and overall utility function for the whole model, except for the lowest level in the Acta geographica Slovenica, 58-1, 2018 101 Amount of protein crops payments and nuts payments Amount of additional payments for milk Amount of additional payments for beef – – – (€) (€) (€) Final assessment – Farm description – Farm size – Usage type of agricultural land – Number of assigned points – Amount of LFA payments (ha) (points) (€) – Social structure – Farm holder´s age – Successor or not – Successor´s age (years) (years) – Amount of natural handicap payments – Number of payment entitlements – Value of payment entitlements for arable land – Value of payment entitlements for pasture – Amount of payment entitlements (€) (€) (€) – Amount of agri-environment payments – Organic farming – Integrated crop production – Implementation of other agri-environmental measures – Amount of payments (%) (%) (%) (€) – Amount of direct payments Table 2: Basic structure of the decision model, with sets of values (scales). Attribute (a) Scale INAPPROPRIATE; RATHER INAPPROPRIATE; APPROPRIATE; EXCELLENT BAD; GOOD; EXCELLENT SMALL; AVERAGE; BIG Meadows; Plantations; Fields < 310; 310–350; > 350 < 500; 500–1000; > 1000 BAD; GOOD > 55; 40–55; 18–25; 25–40 No; Yes > 55; 40–55; 18–25; 25–40 Bad; Good; Very good < 6,5; 6,5–7,5; > 7,5 < 380; 380–400; > 400 < 160; 160–180; > 180 < 1000; 1000–1500; 1500–2000; > 2000 Bad; Good; Excellent < 2; 2–4; 4–6; > 6 < 2; 2–4; 4–6; > 6 < 20; 20–30; 30–40; > 40 < 1200; 1200–1600; 160–2000; > 2000 Bad; Good < 150; 150–250; > 250 < 500; 500–1000; > 1000 < 650; 650–750; > 750 58-1-Special issue_08p_962-Karmen Pazek_acta49-1.qxd 12.9.2017 7:58 Page 101 Karmen Pažek, Aleš Irgolič, Jernej Turk, Andreja Borec, Jernej Prišenk, Matej Kolenko, Črtomir Rozman, Multi-criteria … hierarchy). According to Pavlovič et al. (2011), for each attribute y, whose descendants in the hierarchi- cal tree of attributes are x1, x2, … xn, the corresponding utility function f defines the mapping: f: x1 × x2 × … xn → y, where x1, x2, … xn and y denote values in the domains of the attributes a1, a2, … an and y. These rules define the mapping of four subattributes and the assessment of the cumulative descriptive attributes of the farm in the overall final assessment of the LFAs according to defined decision rules. Table 3: Example of decision rules, with a utility function of the presented case. Decision rules Farm size Usage type Number of assigned Amount of LFA Farm of agricultural land points payments description 26% 26% 31% 17% 1 SMALL Meadows < 310 * BAD 2 SMALL Meadows * < 500 BAD 3 SMALL * < 310 < 500 BAD 4 ≤ AVERAGE ≤ Plantations ≥ 310–350 ≥ 500–1000 GOOD 5 * ≤ Plantations 310–350 ≥ 500–1000 GOOD 6 ≤ AVERAGE Plantations * ≥ 500–1000 GOOD 7 * Plantations ≤ 310–350 ≥ 500–1000 GOOD 8 * ≥ Plantations < 310 ≥ 500–1000 GOOD 9 ≤ AVERAGE Plantations ≥ 310–350 * GOOD 10 ≤ AVERAGE ≥ Plantations ≥ 31–350 < 500 GOOD 11 * Plantations 310–350 * GOOD 12 * ≥ Plantations 310–350 < 500 GOOD 13 AVERAGE ≤ Plantations * * GOOD 14 AVERAGE * * < 500 GOOD 15 ≥ AVERAGE ≤ Plantations ≤ 310–350 * GOOD 16 ≥ AVERAGE * < 310 * GOOD 17 ≥ AVERAGE * ≤ 310–350 < 500 GOOD 18 * Fields ≥ 310–350 ≥ 500–1000 EXCELLENT 19 BIG * > 350 * EXCELLENT The single line in Table 3, i.e., single decision rule, defines the value of the final assessment of LFAs for one combination of values of the former four attributes. The description of the farm, amount of nat- ural handicap, and agri-environmental payments can take three different discrete values (part of the decision rules for the farm description attribute with the utility function is presented in Table 3), and the age struc- ture and amount of direct payments can take two different values. Consequently, there are 108 possible combinations (3 × 3 × 3 × 2 × 2) and thus 108 decision rules. In the next step, the attribute values for each options were placed in the DEXi evaluation table, and the evaluation analysis of the LFA assessment was evaluated. Data for specific criteria compiled by the Agency of the Republic of Slovenia for agricultural markets and rural development were used. The sample size was 42.856 Slovenian farms that are registered and finan- cial supported by the government through different environmental programs, including support for farming in LFA areas (D – 8.413 farms, H – 13.193 farms, K – 5.975 farms, S – 2.269 farms and V – 13.006 farms). The average value of attributes from this database was used as input in the DEXi multi-criteria model (attrib- utes at the leaves of the hierarchical tree as presented in Table 1). 102 58-1-Special issue_08p_962-Karmen Pazek_acta49-1.qxd 12.9.2017 7:58 Page 102 Acta geographica Slovenica, 58-1, 2018 103 3 Result and discussion The following Slovenian LFAs were included in the analysis (Irgolič 2011): hill areas (H), karst areas (K), steep slopes (S), other areas (D), and mountain areas (V). Numerical and qualitative data compiled by the Agency of the Republic of Slovenia for Agricultural Markets and Rural Development were employed. The data were divided into five aggregate attributes (Table 4) according to the utility function, and an integrated assessment of a particular LFA was performed at the end as the last step in the analysis. The classification of particular areas was enabled by the multi-criteria decision model. The developed DEXi model shows that the mountain areas were assigned a value of »excellent,« the best possible out- come. As seen in the integrated assessment (Table 4 and Figure 1), most of the main attributes in this scenario were assigned the highest value, except the attribute amount of agri-environmental payments, where the utility function was assigned a value of »good.« This outcome is expected because there are more than 6% of organic farms in mountain areas (awarded the highest discrete value) but less than 2% of integrated farms (awarded the discrete value bad). Consequently, the implementation of other agri-environmental mea- sures by those farms is between 30–40%, and the total amount of payments are €1.200–1.600/farm. Both attributes intervals are assigned a neutral value in the model. The karst areas and steep slopes received the worst assessments score (Figure 1 and Figure 2). Other areas and hill areas were evaluated as »appropri- ate,« as seen in Table 4. According to the lowest value assigned to two attributes in the assessment (amount of agri-environ- mental and direct payments in the karst areas, where meadows predominate (33.133 ha meadows in comparison with 9.791 ha of fields), the karst areas (K) results with the inappropriate final assessment. Steep slopes (S) areas were assessed as »rather inappropriate.« In the hierarchical model, the farm description attribute was assessed as »excellent.« Besides the subattribute »usage type of agricultural land« where mead- ows predominate, all other subcriteria were assigned the highest discrete value. In contrast to the karst areas, the neutral value (»very good«) was determined by the amount of nat- ural handicap payments attribute. On the other site, two main attributes received the worst assessment (»bad«), i.e., the amount of agri-environmental payments (weight 38%) and the amount of direct payments (weight 11%). The same integrated assessment was determined for the other areas and hill areas. In both alterna- tives, the assessment of the attributes was the same. The description of farms in both areas was »excellent,« the age structure criteria was assigned the value »good« (age of farm holder was between 40 and 55 years, the farm has a successor), and amounts of both attributes were assessed as »good.« The DEXi software also enables »what-if analysis.« For instance, one might consider how the overall assessment can be improved. Table 5 shows the sensitivity (so called ± 1 analysis) for the areas K that was originally assessed as »inappropriate«. The analysis shows, for example, which attributes considerably affect the evaluation of areas K. When attribute Number of payment entitlements or Integrated crop produc- tion increase the overall assessment of areas K improves to »rather inappropriate«. The final assessment of the areas confirmed that selecting specific types of farming and other socio-eco- nomic parameters in a particular LFA depends on various criteria, which were taken into consideration in the multi-attribute decision model. The developed model enabled a final assessment of the LFAs based on the defined attributes and the decision rules within the defined utility functions for the observed problem. Moreover, the results show that the developed decision model could be a suitable methodological tool to aid the practical evaluation of different farming systems in LFAs and aid future political decision making. As this seems the use of pro- gram desirable for many practical problems such as assessment of the service quality that embeds many qualitative attributes or that cannot be easily numerically quantified further study should be particularly focused on the integration of qualitative and quantitative modeling techniques in the assessment of ser- vice quality as well as the inclusion of direct farm activities in the DEXi tree. However, despite the use of qualitative data only, we found that the approach fulfilled most of our expectations and revealed considerable advantages in comparison with other approaches. In particular, we emphasize the use of the qualitative multi-criteria DEXi model, which was suitable in a field where judgment prevails, thus making it diffi- cult to give numeric answers. This kind of model is comprehensible to a wide range of users in the evaluation process. 58-1-Special issue_08p_962-Karmen Pazek_acta49-1.qxd 12.9.2017 7:58 Page 103 Karmen Pažek, Aleš Irgolič, Jernej Turk, Andreja Borec, Jernej Prišenk, Matej Kolenko, Črtomir Rozman, Multi-criteria … 104 Am ou nt o f p ro te in cr op s p ay m en ts a nd n ut s p ay m en ts Am ou nt o f a dd iti on al p ay m en ts fo r m ilk Am ou nt o f a dd iti on al p ay m en ts fo r b ee f – – – (€ ) (€ ) (€ ) Fi na l a ss es sm en t – Fa rm d es cr ip tio n – Fa rm si ze – Us ag e ty pe o f a gr icu ltu ra l l an d – Nu m be r o f a ss ig ne d po in ts – Am ou nt o f L FA p ay m en ts (h a) (p oi nt s) (€ ) – So ci al st ru ct ur e – Fa rm h ol de r´ s a ge – Su cc es so r o r n ot – Su cc es so r´ s a ge (y ea rs ) (y ea rs ) – Am ou nt o f n at ur al h an di ca p pa ym en ts – Nu m be r o f p ay m en t e nt itl em en ts – Va lu e of p ay m en t e nt itl em en ts fo r a ra bl e la nd – Va lu e of p ay m en t e nt itl em en ts fo r p as tu re – Am ou nt o f p ay m en t e nt itl em en ts (€ ) (€ ) (€ ) – Am ou nt o f a gr i- en vi ro nm en t p ay m en ts – Or ga ni c f ar m in g – In te gr at ed cr op p ro du ct io n – Im pl em en ta tio n of o th er a gr i- en vi ro nm en ta l m ea su re s – Am ou nt o f p ay m en ts (% ) (% ) (% ) (€ ) – Am ou nt o f d ire ct p ay m en ts Ta ble 4: In teg rat ed fin al as se ssm en t o f L FA s. At tr ib ut e (a ) EV AL UA TI ON R ES UL TS D H K S V AP PR OP RIA TE AP PR OP RIA TE IN AP PR OP RIA TE RA TH ER IN AP PR OP RIA TE EX CE LL EN T EX CE LL EN T EX CE LL EN T GO OD EX CE LL EN T EX CE LL EN T AV ER AG E SM AL L AV ER AG E BIG BIG Fie lds Fie lds M ea do ws M ea do ws M ea do ws > 35 0 31 0– 35 0 < 31 0 > 35 0 > 35 0 50 0– 10 00 50 0– 10 00 > 10 00 > 10 00 > 10 00 GO OD GO OD GO OD GO OD GO OD 40 –5 5 40 –5 5 40 –5 5 40 –5 5 40 –5 5 Ye s Ye s Ye s Ye s Ye s 40 –5 5 40 –5 5 40 –5 5 40 –5 5 40 –5 5 Go od Go od Go od Ve ry go od Ve ry go od 6,5 –7 ,5 < 6,5 6,5 –7 ,5 > 7,5 > 7,5 < 38 0 > 40 0 38 0– 40 0 > 40 0 > 40 0 < 16 0 > 18 0 16 0– 18 0 > 18 0 > 18 0 > 20 00 10 00 –1 50 0 15 00 –2 00 0 > 20 00 15 00 –2 00 0 Go od Go od Ba d Ba d Go od < 2 2– 4 2– 4 2– 4 > 6 > 6 2– 4 < 2 < 2 < 2 20 –3 0 20 –3 0 < 20 20 –3 0 30 –4 0 > 20 00 < 12 00 12 00 –1 60 0 12 00 –1 60 0 12 00 –1 60 0 Ba d Ba d Ba d Ba d Go od 15 0– 25 0 > 25 0 15 0– 25 0 < 15 0 15 0– 25 0 < 50 0 < 50 0 < 50 0 50 0– 10 00 > 10 00 > 75 0 < 65 0 < 65 0 > 75 0 65 0– 75 0 58-1-Special issue_08p_962-Karmen Pazek_acta49-1.qxd 12.9.2017 7:58 Page 104 Acta geographica Slovenica, 58-1, 2018 105 Good Amount of direct payments Amount of agri-environmental payments Final assessment Amount of natural handicap payments Social structure Farm description Good Good Amount of direct payments Amount of agri-environmental payments Final assessment Amount of natural handicap payments Social structure Farm description Figure 1: Graphical presentation of the final assessment mountain areas (V)/gafični prikaz končne ocene gorsko-višinskih območij. Figure 2: Graphical presentation of the final assessment of the karst (K) areas. 58-1-Special issue_08p_962-Karmen Pazek_acta49-1.qxd 12.9.2017 7:58 Page 105 Karmen Pažek, Aleš Irgolič, Jernej Turk, Andreja Borec, Jernej Prišenk, Matej Kolenko, Črtomir Rozman, Multi-criteria … 4 Conclusion According to the results the multi – attribute DEXi model can be regarded and applied practically to small- er number of farms as well as to a broader sphere of scientifically research work. The developed model may also be used in further development of agricultural policy, it also can be upgraded with the latest infor- mation and adopted it to specific requirements. The multi – criteria methodology cannot replace or exclude the policy decision maker experts but can serve as an additional instrument that enables faster analysis. The model can be good basis and support tool for further development of more complex models that are designed primarily for planning and decision-making process in agricultural policy especially by defini- tion of different payments types in agriculture. ACKNOWLEDGEMENTS: We express our grateful thanks to the anonymous reviewers and editor in chief for the useful suggestion to improve the paper. 6 References AKTRP 2012: Agency of the Republic of Slovenia for agricultural markets and rural development. Internet: http://www.arsktrp.gov.si/en (20. 12. 2012). Bohanec, M.  2014: DEXi. A  Program for multi-attribute decision making, version 4.00. Internet: http://www-ai.ijs.si/MarkoBohanec/dexi.html (5. 11. 2014). 106 Amount of protein crops payments and nuts payments Amount of additional payments for milk Amount of additional payments for beef – – – (€) (€) (€) Final assessment – Farm description – Farm size – Usage type of agricultural land – Number of assigned points – Amount of LFA payments (ha) (points) (€) – Social structure – Farm holder´s age – Successor or not – Successor´s age (years) (years) – Amount of natural handicap payments – Number of payment entitlements – Value of payment entitlements for arable land – Value of payment entitlements for pasture – Amount of payment entitlements (€) (€) (€) – Amount of agri-environment payments – Organic farming – Integrated crop production – Implementation of other agri-environmental measures – Amount of payments (%) (%) (%) (€) – Amount of direct payments Table 5: The sensitivity analysis (± 1) for the karst areas (K). 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E., Meyer, H., Post, J. H., Strijker, D. 1995: Agricultural income in less favoured areas of the EC: a regional approach. Journal of rural studies 11-2. DOI: http://dx.doi.org/10.1016/ 0743-0167(95)00012-C. Tiwari, D. N., Loof, R., Paudyal, G. N. 1999: Environmental-economic decision-making in lowland irrigated agriculture using multi-objectives analysis techniques. Agricultural systems 60. DOI: http://dx.doi.org/ 10.1016/S0308-521X(99)00021-9. 108 58-1-Special issue_08p_962-Karmen Pazek_acta49-1.qxd 12.9.2017 7:58 Page 108 Acta geographica Slovenica, 58-1, 2018, 109–123 An example of illegal logging from the Municipality of Kuršumlija in southern Serbia in 2013. M IT A R P E R IĆ THE USE OF NDVI AND CORINE LAND COVER DATABESES FOR FOREST MANAGEMENT IN SERBIA Miomir M. Jovanović, Miško M. Milanović, Matija Zorn 58-1-Special issue_09p_818-Miomir M Jovanovic_acta49-1.qxd 12.9.2017 7:59 Page 109 Miomir M. Jovanović, Miško M. Milanović, Matija Zorn, The use of NDVI and CORINE Land Cover databases for forest … DOI: https://doi.org/10.3986/AGS.818 UDC: 91:630*6(497.11) 630*6:528.8(497.11) COBISS: 1.01 The use of NDVI and CORINE Land Cover databases for forest management in Serbia ABSTRACT: This article evaluates the possible use of normalized difference vegetation index (NDVI) and CORINE Land Cover (CLC) databases for better forest management in the municipalities of Kuršumlija and Topola in Serbia. The forest areas obtained using CLC were up to 11.5% larger than the official forest area estimates, whereas NDVI gave more precise results. Hence, NDVI can efficiently provide local forest managers with essential annual information about the forest inventory.This is of a crucial importance for preventing illegal logging, which is very prevalent in southern Serbian municipalities, which have sub- stantial forested territory. NDVI thus very promising for Serbia and also for countries that rarely carry out national forest inventories. This method can also easily be applied to other Balkan countries with a sim- ilar situation regarding local forest management. KEY WORDS: NDVI, CORINE Land Cover, forest management, illegal logging, Serbia Raba podat kov nih zbirk NDVI in CORINE pri gos po dar je nju z goz do vi v Sr bi ji POVZETEK: V član ku avtor ji preu ču je jo mož nost rabe podat kov nih zbirk NDVI in CORINE za bolj še gos - po dar je nje z goz do vi v srb skih obči nah Kuršumlija in Topo la. Povr ši na goz da, ugo tov lje na z upo ra bo CLC, je bila do 11,5 % več ja od urad no oce nje ne, med tem ko so bili rezulta ti NDVI toč nej ši. NDVI lahko lokalnim upravljavcem gozdov zagotavlja pomembne informacije o gozdu na letni ravni. To je izjem no pomemb - no za pre pre če va nje neza ko ni te seč nje, zna čil ne za obči ne v juž ni Srbi ji, ki so boga te z goz dom. Upo ra ba NDVI zato obe tav na za Srbi jo in tudi dru ge drža ve, ki red ko izva jajo nacio nal ne popi se goz dov. Meto da je pri mer na tudi za dru ge bal kan ske drža ve s po dob ni mi raz me ra mi na področ ju lokal ne ga gos po dar jenja z goz do vi. KLJUČNE BESEDE: NDVI, CORINE, gos po dar je nje z goz do vi, neza ko ni ta seč nja, Srbi ja Miomir M. Jovanović, Miško M. Milanović University of Belgrade, Faculty of Geography miomir.m.jovanovic@gmail.com, milanovic.misko@gmail.com Matija Zorn Anton Melik Geographical Institute, Research Centre of the Slovenian Academy of Sciences and Arts matija.zorn@zrc-sazu.si The paper was submitted for publication on February 1st, 2014. Ured niš tvo je pris pe vek pre je lo 1. fe bruar ja 2014. 110 58-1-Special issue_09p_818-Miomir M Jovanovic_acta49-1.qxd 12.9.2017 7:59 Page 110 Acta geographica Slovenica, 58-1, 2018 111 1 Introduction Permanent clearing of forest cover was typical in the industrialized world until a few decades ago. Vast areas of Europe and North America were cleared for industrial expansion and development of infrastructure. Today deforestation is largely occurring in tropical countries in Africa, Asia, and Latin America (Steiningeretal. 2001; Chowdhury 2006), as well as in taiga regions, especially in Russia (Tracy 1994; Deforestation … 2014). Most reasons for deforestation are due to market imperfections (Jovanović 2012). Market imperfections arise when property cannot be clearly defined, when property cannot be freely transferred, when the use of goods cannot exclude others from such use, and when private rights cannot be protected (McKean 2000; Tietenberg and Lewis 2012). Evidence convincingly shows that illegal and corrupt activities are a major underlying cause of forest decline (Contreras-Hermosilla 2002; Brack 2003). The main reason for this is that governments and private landowners cannot control these illegal operations. In addition, this lack of control may be deliberate, is often corrupt, or may be determined by the limitations of administrative capac- ity. One way or another, illegal use of forests is rampant (Contreras-Hermosilla 2002; Amacher et al. 2009). Remote sensing is the detection, recognition, or evaluation of objects by means of distant sensing or recording devices (Oštir 2006). Historically, digital remote sensing developed rapidly from aerial photography and photo interpretation. Information extracted visually from remote sensing is widely used in forestry (Franklin 2001; Hočevar and Kobler 2001; Hočevar and Hladnik 2006; Kobler 2012). Given the importance and complexity of forest preservation and sustainable forest management (Pagiola et al. 2002; Lee 2008; Ojea et al. 2012), an attempt was made to evaluate the possible use of a nor- malized difference vegetation index (NDVI; Weier and Herring 2000) and Coordination of Information on the Environment (CORINE) Land Cover (CORINE … 1994) in local forest management. NDVI is one of the most widely used vegetation indices (VIs) and CORINE Land Cover (CLC) is in official use in the EU. One of the main differences between NDVI and CLC is that, whereas NDVI focuses on the vegeta- tion cover and its status, CLC has a much broader scope and distinguishes agricultural areas, forests and semi-natural areas, artificial surfaces, urban fabric, industrial, commercial, and transport units, bodies of water, wetlands, glaciers and perpetual snow, and other features (Jensen 2007). NDVI is actually a simple graphic indicator that can be used to analyze remote sensing measurements, whether the target observed contains live green vegetation or not (Chen 2008). NDVI was one of the most successful of many attempts to simply and quickly identify vegetated areas and their »condition,« and it remains the best-known and most-used index for detecting live green plant canopies in multispectral remote sensing data (Fuller 2006; Milanović et al. 2008; Campbell and Wynne 2011; Ne Win et al. 2012). NDVI also has the advantage of allowing comparisons between images acquired at different times (Lillesand et al. 2004). It belongs to the VIs related to vegetation cover and its status, and it provides useful information on bio- mass productivity and health. VIs have a direct correlation with leaf chlorophyll content and leaf area index (LAI) and vary in relation to vegetation cycle and phenology (Vohlandetal. 2007; Montandon and Small 2008). They are also sensitive to other external factors, such as the contribution of the soil and background opti- cal behavior where the vegetation does not completely cover the ground, the geometry of view due to sensor angle of acquisition and to Sun position, atmospheric effects, and other factors (Franklin 2001; De Jong and Van der Meer 2005; Jensen 2007; Campbell and Wynne 2011). NDVI, like all VIs, relates the spectral absorption of chlorophyll in the red with a reflection phenomenon in the near infrared, influenced by the leaf structure type (Wang and Tenhunen 2004). In contrast, CLC is a European program launched in 1985 by the European Commission, aimed at obtain- ing a unique and comparable dataset of land cover for Europe. The aim of CLC is to gather information related to the environment on certain priority topics for the European Union: air, water, soil, land cover, coastal erosion, biotopes, and so on. The main goals of the CLC program are to acquire information about the environment to address the European Community policy, to assess the effectiveness of legislation, to integrate environmental and political aspects, to unify heterogeneous thematic cartographies of Europe at various levels (international, national, regional, local), and to update data at regular intervals, every five to ten years (Bossard et al. 2000; Neumann et al. 2007). CLC is a map of the European environmental land- scape based on interpretation of satellite images. The data have been validated using local cartography and ground surveys (Heymannetal. 1994; Perdigão and Annoni 1997; Genovese et al. 2001). CLC also has an NDVI module for creating vegetation maps, but the deviations in its final results are substantial due to the highly inappropriate scale of Serbian data. 58-1-Special issue_09p_818-Miomir M Jovanovic_acta49-1.qxd 12.9.2017 7:59 Page 111 Miomir M. Jovanović, Miško M. Milanović, Matija Zorn, The use of NDVI and CORINE Land Cover databases for forest … For creating CLC maps for the municipalities of Kuršumlija and Topola, image processing was car- ried out and a digital elevation model was made based on the municipalities' boundaries and Landsat satellite color composites, and a pseudo-color composite with bands 4, 5, 1 and adequate contrast was applied. Datasets and maps for Serbia, mainly IMAGE2000 and CLC2000  class, were extracted from the European Environmental Agency (EEA) website, with a transfer data scale of 1 : 100,000, which resulted in a very high level of imprecision (Büttner and Kleeschulte 2005). Of particular interest to this study is that the smallest unit is 25 ha in the original CLC project, although a recent approach yields more precise results because changes < 25 ha and > 5 ha are mapped (CLC2006 … 2007). Nevertheless, even the smallest 5 ha areas, which are highly appropriate at the EU scale, do not properly reflect the land-use situation at the local scale in a country where landscapes and land-use change across very short distances (Hočevar and Kobler 2001; Gabrovec and Petek 2004). This article shows that remote sensing data collection and analysis methods have great importance for local forest management in Serbia. In Serbia around 30% of land is forested (of which 50% is state-owned forests and 50% privately owned). Forest management (of both privately owned and state-owned forests) is also very poor (Forestry … 2006). The purpose of this article is to improve the local forest management system in Serbia through more precise methods for assessing land-use changes in forest areas. The study evaluated NDVI and CLC, which are viewed as very efficient tools for classifying and estimating different land cover types of large and remote areas (Meng et al. 2009). Although they both proved to be very effective in the EU, CLC is mostly used as a regional database. Nonetheless, in Serbia they both (recently) became very popular tools for studies at the local level (Report … 2009). This article shows that they are not equally effective at the local level in the Serbian context. 112 LEGEND Municipality of Topola2 1 Municipality of Kuršumlija Content by: Miško Milanović Map by: Miško Milanović © 2014, University of Belgrade, Faculty of Geography EUROPE SERBIA 1 2 Serbia Kosovo Figure 1: Location of the municipalities of Kuršumlija and Topola (Serbia). 58-1-Special issue_09p_818-Miomir M Jovanovic_acta49-1.qxd 12.9.2017 7:59 Page 112 2 Materials and methods In the study it was not possible to make a reliable long-term comparative analysis between NDVI and CLC data and official forest inventories because national forest inventories have very rarely been carried out in Serbia. Such inventories were carried out at roughly twenty-year intervals: in 1961, 1979, and 2003–2006. Since 2007, official estimates of forest areas have been made annually. The study was carried out for the municipalities of Topola and Kuršumlija (Figure 1). Data obtained using NDVI and CLC for spring/summer 2006 were analyzed and compared to official forest area esti- mates for 2006 created at the end of the same year. The Municipality of Topola is located in central Serbia, and the Municipality of Kuršumlija lies in southern Serbia. NDVI and CLC data for both municipalities are based on Landsat 5 Thematic Mapper (TM) satellite images (Figures 2 and 3) for 2006, which were created during spring/summer (August), with minimum clouds (10 to 20%; Chavez 1996). In order to remove atmospheric effects from the NDVI final results, Idrisi software was used for data preprocessing. For calculating NDVI, satellite (Landsat) imagery (which has a resolution of approximately 30 m) and pan-sharpening images (with 15 m resolution) were used to obtain more precise results. Acta geographica Slovenica, 58-1, 2018 113 0 5 10 km2.5 Content by: Miško Milanović Map by: Miško Milanović Source: U.S. Geological Survey, 2014 © 2014, University of Belgrade, Faculty of Geography Figure 2: The Municipality of Kuršumlija. L A N D S A T I M A G E 58-1-Special issue_09p_818-Miomir M Jovanovic_acta49-1.qxd 12.9.2017 7:59 Page 113 Miomir M. Jovanović, Miško M. Milanović, Matija Zorn, The use of NDVI and CORINE Land Cover databases for forest … NDVI was used and necessary corrections/transformations were applied for visible red in constellation with the infrared spectrum of satellite images using the following procedure: GIS Analysis / Mathematical Operation / Image Calculator, and then the equation NDVI = (NIR – RED) / (NIR + RED), in which NIR is the near-infrared channel and RED is the red channel from the visible part of the spectrum (Hájek 2008; Johnson and Trout 2012). Basic tasks included analysis and photo interpretation of elements, occurrences, and processes detect- ed on images using specialized GIS software (Idrisi 15-Andes) for processing remotely sensed images through application of NDVI. Shadows can cause NDVI values to be lower than their actual values. In this sense, »empirical topo- graphic corrections have proven only marginally successful« (Franklin 2001). Because shadow areas were less than 5% in the Municipality of Kuršumlija and less than 3% in the Municipality of Topola, no topo- graphic corrections were made. Characteristic NDVI signatures are as follows: NDVI of dense vegetation canopy tends to have positive values (0.3 to 0.8); clouds and snowfields are characterized by negative values of this index; bodies of water (e.g., oceans, seas, lakes, and rivers) has rather low reflectance in both spectral bands (at least away from shores), thus resulting in very low positive or even slightly negative NDVI values; soils generally exhibit a near-infrared spectral reflectance somewhat larger than the red, and thus also tend to generate rather small positive NDVI values (0.1 to 0.2); very low values of NDVI (0.1 and below) correspond to barren areas of rock, sand, or snow; moderate values represent shrub and grassland (0.2 to 0.3); and high values (0.6 to 0.8) indicate tem- 114 L A N D S A T I M A G E Content by: Miško Milanović Map by: Miško Milanović Source: U.S. Geological Survey, 2014 © 2014, University of Belgrade, Faculty of Geography 0 5 10 km2.5 Figure 3: The Municipality of Topola. 58-1-Special issue_09p_818-Miomir M Jovanovic_acta49-1.qxd 12.9.2017 7:59 Page 114 Acta geographica Slovenica, 58-1, 2018 115 0.3 0.4 0.5 0.6 0.7 NDVI Index 0 2 4 6 8 10 km Content by: Miško Milanović Map by: Miško Milanović © 2014, University of Belgrade, Faculty of Geography Figure 4: Vegetation cover in the Municipality of Kuršumlija for 2006 obtained from NDVI. perate and tropical rainforests (Finelli et al. 1996; Schmitt and Ruppert 1996). Negative values of NDVI rang- ing from 0 to –0.3 are displayed in shades from light green to dark purple. These low negative values are detected in arable agricultural land (without vegetation) and are shown in shades of light green. On the other hand, vegetation areas are presented with values between 0 and 1. Grassy areas, meadows, and pastures have values that range from zero (in yellow, due to more intense reflectance of infrared radiation) up to 0.13 (light orange tones). Shrub vegetation has an NDVI value of 0.25 because reflectance of infrared rays decreases (darker red tones). Forest vegetation, with maximal positive NDVI values of 0.85 (due to minimal reflectance of infrared rays), is easily observed. Coniferous forest has an NDVI value above 0.5, mixed forest between 0.35 and 0.5, and broad-leaved forest between 0.3 and 0.4 (Bakx 1995; De Jong and Van der Meer 2005). 3 Results After image processing it was determined (Table 1) that forest areas encompass 529.83 km2 or 55.7% of the total area of the Municipality of Kuršumlija, much higher than the average 30% for Serbia; and 50.73 km2 or 14.2% of the total area of the Municipality of Topola, which is approximately half of the Serbian average. 58-1-Special issue_09p_818-Miomir M Jovanovic_acta49-1.qxd 12.9.2017 7:59 Page 115 Miomir M. Jovanović, Miško M. Milanović, Matija Zorn, The use of NDVI and CORINE Land Cover databases for forest … When these NDVI results are compared with official forest area estimates for the same year (2006) (Municipalities … 2007), there is only +0.12 km2 of difference for Topola's forest area, and –27 km2 differ- ence for Kuršumlija (Table 3). Figures 4 and 5 present a raster of NDVI (NIR band and RED band) from Landsat 5 TM (bands 4, 5, 1) satellite images. The images were created in August 2006. Figures 6 and 7 present vegetation cover obtained from CLC. When the (latest available) CLC results for 2006 were compared with official forest area estimates for the same year (Tables 1–3), some inconsistencies became apparent: • The total areas for the municipalities of Kuršumlija and Topola obtained from CLC were smaller than the official forest statistics: instead of 952 km2 only 942.9 km2 for Kuršumlija, and instead of 356 km2 only 348.9 km2 for Topola; • Forest areas obtained from CLC were up to  11.5% larger than the official forest area estimates. Kuršumlija's forest area obtained from CLC (630.45 km2) is 26 km2 larger than the official forest area estimates (604.41km2) for this municipality (+4.3%), and Topola's forest area obtained from CLC (58km2) is 6 km2 larger than the official forest area estimates (52 km2, + 11.5%). 116 Content by: Miško Milanović Map by: Miško Milanović © 2014, University of Belgrade, Faculty of Geography 0 2 4 6 8 10 km NDVI Index 1 –1 Figure 5: Vegetation cover in the Municipality of Topola for 2006 obtained from NDVI. 58-1-Special issue_09p_818-Miomir M Jovanovic_acta49-1.qxd 12.9.2017 7:59 Page 116 Acta geographica Slovenica, 58-1, 2018 117 0 2 4 6 8 10 km Content by: Miško Milanović Map by: Miško Milanović © 2014, University of Belgrade, Faculty of Geography Settlements Non-irrigated arable land Complex cultivation patterns Land principally occupied by agriculture, with signi$cant areas of natural vegetation Natural grasslands Pastures Broad/leaved forest Coniferous forest Mixed forest Transitional woodland-shrub Sparsely vegetated areas LEGEND Figure 6: Vegetation cover in the Municipality of Kuršumlija for 2006 obtained from CLC. Table 1: Vegetation cover in the municipalities of Kuršumlija and Topola for 2006 obtained from NDVI. Land cover Kuršumlija Topola (km2) (%) (km2) (%) Broad-leaved forest 562.71 59.10 49.40 13.84 Coniferous forest 6.46 0.68 0.62 0.17 Mixed forest 8.23 0.86 2.10 0.59 Pastures 32.20 3.40 – – Transitional woodland-shrub 51.55 5.41 – – Sparsely vegetated areas 9.48 0.99 – – Land principally occupied by agriculture, with significant areas of natural vegetation – – 63.25 17.72 Other 281.37 29.56 241.63 67.68 Total 952.00 100.00 357.00 100.00 58-1-Special issue_09p_818-Miomir M Jovanovic_acta49-1.qxd 12.9.2017 7:59 Page 117 Miomir M. Jovanović, Miško M. Milanović, Matija Zorn, The use of NDVI and CORINE Land Cover databases for forest … 118 0 2 4 6 8 10 km Content by: Miško Milanović Map by: Miško Milanović © 2014, University of Belgrade, Faculty of Geography Boundary Settlements Green urban areas Non–irrigated arable land Natural grasslands Complex cultivation patterns Land principally occupied by agriculture, with signi$cant areas of natural vegetation Vineyards Broad-leaved forest Coniferous forest Mixed forest LEGEND Transitional woodland-shrub Pastures Figure 7: Vegetation cover in the Municipality of Topola for 2006 obtained from CLC. Table 2: Land cover in the municipalities of Kuršumlija and Topola for 2006 obtained from CLC. Land cover Kuršumlija Topola (km2) (%) (km2) (%) Settlements 4.60 0.49 9.11 2.61 Green urban areas – – 0.82 0.23 Non-irrigated arable land 0.42 0.04 36.51 10.46 Natural grasslands 25.74 2.73 14.44 4.14 Complex cultivation patterns 78.73 8.35 154.94 44.41 Land principally occupied by agriculture, with significant areas of natural vegetation 102.25 10.84 73.17 20.97 Broad-leaved forest 620.68 65.82 55.68 15.96 Coniferous forest 3.63 0.38 0.19 0.05 Mixed forest 6.14 0.65 2.12 0.61 Pastures 24.18 2.56 1.11 0.32 Transitional woodland-shrub 75.78 8.04 0.81 0.23 Sparsely vegetated areas 0.78 0.08 – – Total 942.93 100.00 348.90 100.00 58-1-Special issue_09p_818-Miomir M Jovanovic_acta49-1.qxd 12.9.2017 7:59 Page 118 4 Discussion Although both CLC and NDVI have recently been used in Serbia for studies at the local level, the main problem with CLC data is that: a) although CLC data are produced at various levels (international, nation- al, regional, and local; Bossard et al. 2000; Neumann et al. 2007), CLC is actually a predominantly regional database, updated rarely (every five to ten years), whereas NDVI is available for every year; and b) NDVI is much more precise than CLC. When official statistics and NDVI and CLC forest areas were compared for the same year (2006), NDVI was more precise than CLC. Because both NDVI and CLC used the same Landsat satellite images and the same (NDVI) methodology, these major differences in the data obtained were due to the different spatial resolution of NDVI and CLC. Whereas CLC does not go below the range of 4 to 5 ha, NDVI easily deals with minimum space units of 25 m2. This proved to be decisive for Serbia, where privately owned forest parcels, which account for half of the total forest area of the country, usually cover much smaller areas (the average private holding is 0.5 ha; Glavonjić et al. 2005). In short, CLC proved not to be very suitable for local forest management in Serbia (questionable results regarding forests were also determined in Slovenia; e.g., Gabrovec and Petek 2004). In addition, apart from the obvious CLC imprecision for studies at the local level, CLC data are not available for every year. When compared with official forest area estimates, the NDVI results show a mere +0.12 km2 (+0.2%) difference for the Municipality of Topola's forest area, and a –27.01km2 (–4.7%) difference for the Municipality of Kuršumlija (Table 3). Not only do these results completely fit within the ± 5% margin of error allowed for this method (Eastman 2001; Lunetta et al. 2007), but they also allow room for further analysis and inves- tigation. Because the NDVI aerial photos were taken during spring/summer, whereas official forest area esti- mates are made at the end of the year, NDVI values would be expected to be higher, not lower–at least for the Municipality of Kuršumlija (known for its illegal logging). Moreover, because additional NDVI for- est area estimates were made for 2011 (Table 4), it seems that even for 2006 this study's NDVI results better fit the forest area trajectory of Kuršumlija for the 2006–2011 period than do the official statistics (the offi- cial forest inventory for 2006 is 604.41 km2 and NDVI results 577.4 km2; and the official forest inventory for 2011 is 544.3 km2 and NDVI results 529.8 km2). Acta geographica Slovenica, 58-1, 2018 119 Table 3: Forest areas according to official statistics and calculated on the basis of NDVI and CLC for 2006. Municipality Municipality: Forest area NDVI – official CLC – official total area Official statistics Calculated on the Calculated on the statistics difference statistics difference (km2) (km2)* basis of NDVI basis of CLC (km2) (km2) (km2) (km2) Topola 356 52.00 52.12 57.99 +0.12 +5.99 Kuršumlija 952 604.41 577.40 630.45 –27.01 +26.04 *Source: Municipalities…2008. Table 4: Forest areas according to official statistics and calculated on the basis of NDVI for 2011 and CLC for 2006. Municipality Municipality: Forest area NDVI – official CLC – official total area Official statistics Calculated on the Calculated on the statistics difference statistics difference (km2) (km2)* basis of NDVI basis of CLC (km2) (km2) (km2) (km2) Topola 357 52.0494 50.73 57.99 –1.3194 +5.9407 Kuršumlija 952 544.2856 529.83 630.45 –14.4556 +86.1644 *Source: Municipalities…2013. 58-1-Special issue_09p_818-Miomir M Jovanovic_acta49-1.qxd 12.9.2017 7:59 Page 119 Miomir M. Jovanović, Miško M. Milanović, Matija Zorn, The use of NDVI and CORINE Land Cover databases for forest … The main reason that the (slightly smaller) NDVI results possibly better fit the forest area trajectory of Kuršumlija than the official inventory is that this municipality is known for illegal logging. According to the state-owned forest-management company Srbijašume, in Kuršumlija more than 40,000 m3 of timber was illegally cut during the last thirteen years alone, and that municipality also experienced a 10% loss in for- est area in the last few years alone (Forestry…2006; Anfodilloetal. 2008; Illegal…2009, Municipalities…2013). Obviously, governments often cannot efficiently control these illegal operations. As Contreras-Hermosilla (2000) points out: »This lack of control can be either deliberate, often corrupt, or determined by the limita- tions of administrative capacity. One way or the other, illegal use of forests is rampant in most forested countries. By their very nature, the true extent of illegal operations in the forestry sector cannot be known with preci- sion, but evidence suggests that such activities are important and that they constitute an important underlying cause of forest decline.« Because this research strongly implies that illegal logging in Kuršumlija is not properly covered by cur- rent official forest area estimates, further NDVI research on the extent of illegal logging in southern Serbian municipalities is of the utmost importance. In short, because the Municipality of Kuršumlija has a large territory (952 km2), with more than 544 km2 (or 55.7%) of its total area covered by forests, and because NDVI can be performed very quickly, it is obvi- ous that NDVI can provide local forest managers in Kuršumlija with much essential annual information about the forest inventory (Chen et al. 2004; Bellone 2009; Fensholt et al. 2009; Martinez and Gilabert 2009; Alessandrini et al. 2010; Corral-Rivas 2010). This is of crucial importance for preventing illegal logging, which is very prevalent in this southern Serbian municipality (Forestry … 2006; Anfodillo et al.  2008; Illegal … 2009). 5 Conclusion Despite certain shortcomings (Franklin 2001; Campbell and Wynne 2011), classification and area estimation of various land-cover types based on remote sensing has obviously advanced to a point where it surpasses old wood inventory techniques, especially in the case of Serbia. Specifically: • It is relatively cheap and quick, and it can provide forest managers with essential information; • It is easy to implement, which is of crucial importance for Serbia, where national forest inventories have been carried out very rarely. The last three national forest inventories were carried out at roughly twen- ty-year intervals; however, since the last national forest inventory (2003–2006), necessary updates have been made every year, but only at the municipality level; • The objectivity of these methods can significantly help in avoiding corruption in forest management because corruption is one of the main weaknesses of Serbia's economy. Through this analysis of NDVI and CLC results for the municipalities of Kuršumlija and Topola, CLC was shown not to be a very suitable tool for local forest management in Serbia. On the other hand, it is evident that NDVI, especially in southern Serbian municipalities with prevalent illegal logging (like Kuršumlija), can provide local forest managers with much annual information about forest areas. This is of crucial importance for monitoring (and consequently preventing) illegal logging. NDVI is also very promising for countries like Serbia, which very rarely carry out national forest inven- tories. It is easy implemented and it has objectivity that can greatly help avoid corruption and illegal logging in forest management. ACKNOWLEDGEMENT: This work was supported by the Ministry of Science and Technological Development of the Republic of Serbia under grant no. 37010. 6 References Alessandrini, A., Vessella, F., Di Filippo, A., Salis, A., Santi, L., Schirone, B., Piovesan, G. 2010: Combined dendroecological and normalized difference vegetation index analysis to detect regions of provenance in forest species. Scandinavian Journal of Forest Research  25-8. DOI: http://dx.doi.org/10.1080/ 02827581.2010.485776 120 58-1-Special issue_09p_818-Miomir M Jovanovic_acta49-1.qxd 12.9.2017 7:59 Page 120 Amacher, G., Ollikainen, M., Koskela, E. 2009: Economics of forest resources. Cambridge. 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Acta geographica Slovenica, 58-1, 2018 123 58-1-Special issue_09p_818-Miomir M Jovanovic_acta49-1.qxd 12.9.2017 7:59 Page 123 124 58-1-Special issue_09p_818-Miomir M Jovanovic_acta49-1.qxd 12.9.2017 7:59 Page 124 Acta geographica Slovenica, 58-1, 2018, 125–136 NITROGEN AND PHOSPHORUS POLLUTION IN GORIČKO NATURE PARK Darijo Ilić, Jože Panjan Ledava River at Domajinci. D a r ij o i l ić 58-1-Special issue_10p_727-Darijo Ilic_acta49-1.qxd 12.9.2017 7:59 Page 125 Darijo Ilić, jože Panjan, Nitrogen and Phosphorus Pollution in Goričko Nature Park DOI: https://doi.org/10.3986/AGS.727 UDC: 913:504.5(497.411) 504.5:546.17/.18(497.411) COBISS: 1.01 Nitrogen and Phosphorus Pollution in Goričko Nature Park ABSTRACT: This article deals with the impact of diffuse and point sources of nitrogen and phosphorus pollution on the environment in Goričko Nature Park. The park was divided into three parts: the Ledava, Big Krka (Velika Krka), and Kobilje Creek (Kobiljski potok) basins, which were then compared. The sur- face waters were monitored and their chemical composition was examined. All three areas are characterized by elevated levels of nitrogen and phosphorus compounds in the water. Nitrogen and phosphorus pollu- tion results from unregulated manure pits on livestock farms, unregulated sewage systems, and runoff of nitrogen and phosphorus compounds from farmland. KEY WORDS: geography, nature protection, pollution, nitrogen, phosphorus, Goričko Nature Park, Slovenia One sna že nje z du ši kom in fos for jem v Kra jin skem par ku Gorič ko POVZETEK: Čla nek obrav na va vpliv raz pr še nih in toč kov nih virov na obre me nje va nje oko lja z du ši kom in fos for jem na območ ju Kra jin ske ga par ka Gorič ko. Kra jin ski park Gorič ko smo raz de li li na tri dele: porečja Leda ve, Veli ke Krke in Kobilj ske ga poto ka ter med območ ji izved li pri mer jal no ana li zo. Z mo ni to rin gom povr šin skih teko čih voda smo preu či li nji ho vo kemij sko sta nje. Za vsa tri območ ja so zna čil ne povi ša ne kon cen tra ci je duši ko vih in fos for je vih spo jin v vodi. One sna že nje z du ši ko vi mi in fos for je vi mi spo ji nami, je posle di ca neu re je nih gnoj nih jam na živi no rej skih obra tih, neu re je na kana li za cij ska infra struk tu ra in izgu be duši ko vih in fos for je vih spo jin s kme tij skih zem ljišč. KLjUČ NE BESE DE: geo gra fi ja, vars tvo oko lja, one sna že nje, dušik, fos for, Kra jin ski park Gorič ko, Slo ve nija Darijo Ilić Public communal enterprise Šalovci, d. o. o. darioilic@yahoo.com Jože Panjan University of Ljubljana, Faculty of Civil and Geodetic Engineering joze.panjan@gov.si The paper was submitted for publication on june 6th, 2013. Ured niš tvo je pre je lo pris pe vek 6. ju ni ja 2013. 126 58-1-Special issue_10p_727-Darijo Ilic_acta49-1.qxd 12.9.2017 7:59 Page 126 Acta geographica Slovenica, 58-1, 2018 127 1 Introduction Factors that alter the chemical, biological, physical, and hydromorphological properties of water are those that pollute water and thus have an impact on its condition. Nutrient sources of water contamination (pri- marily nitrogen and phosphorus) can be divided into point and diffuse sources (Novotny 1988). The point sources of one or more pollutants can be defined and illustrated as points on the map from which pollu- tion spreads into the surrounding areas; the impact decreases with distance. Point sources include industrial and domestic wastewater, direct discharges from livestock farms, and so on. Diffuse pollution sources, which cannot be defined as a single point but rather originate from a specific area, include settlements, agricul- ture, and traffic infrastructure. Diffuse pollution is the leading form of pollution that is difficult to control (Novotny 2003; De Wit and Behrendt 1999). Intensive agriculture is especially problematic in this regard, because increased fertilizer use and intensive livestock farming increase nutrient inputs. Healthy drinking water (ground or surface) is recognized as one of the fundamental environmental problems. Water is a partially renewable resource, but excessive contamination, especially by inorganic matter, can turn it into a health risk. In order to prevent this type of contamination as much as possible, water pollution sources must be determined to the greatest possible extent. This is an especially big chal- lenge in the case of diffuse water pollution because the sources must be defined locally. An expressly local approach is required because each area has its own special features. Nitrogen is an important element of the global ecosystem and a component of many organic and inor- ganic substances (Williams 2001). Water contains low levels of nitrogen in the form of organic or inorganic compounds (Ibanez et al. 2007). The most important inorganic forms of nitrogen include ammonium (as the ammonium ion NH4 + and ammonia or NH3, which are in balance in a water solution; they have an oxi- dation number of –3), nitrate (NO3 – with an oxidation number of +5), and nitrite (NO2 – with an oxidation number of +3). These ionic forms play an important role in the nitrogen cycle. After nitrogen, phosphorus is the second most important element in primary production (Green etal. 2007) and it is the most important nutrient to cause the eutrophication of fresh water (Lemmunyon and Daniel 1998), which stimulates algal growth, decreases dissolved oxygen levels, and reduces water transparency (Wood 1998). Excess phosphorus in water from both point and diffuse sources can result in increased primary production and eutrophication, with the potential for seasonal toxic algal blooms, which can have a major negative impact on global water quality (Worsfold 2005). The majority of phosphorus is washed from farmland into surface waters, whereas only small amounts are washed into the groundwater (Bryant 2004). Phosphorus losses from farmland amount to 0.97–1.85 kg/ha a year (Baker 1984). Phosphorus losses from farmland in Goričko Nature Park can be up to 8.2 kg/ha (Karta presežkov fosforja 2006) as a result of surface runoff (Karta površinskega odtoka 2003). 2 Methods Water quality in Goričko Nature Park was monitored through field measurements and laboratory analy- ses. Field research included measurements of water and air, pH, electrical conductivity, redox potential, turbidity, and oxygen. Sampling was carried out in line with the Slovenian Standard (Kakovost vode…2007). Eleven sites were used for sampling, which was carried out once a month from May 28th, 2008 to May 20th, 2009. Discharge was measured using the float method (Brilly 1992), and chemical parameters (i. e., ammonium, nitrate, nitrite, total nitrogen, orthophosphate, total phosphorus, potassium, chemical oxygen demand (COD), five-day biochemical oxygen demand (BOD5), and undissolved matter) were determined using standard methods (Eaton et al. 1995). 2.1 Description of the study area Goričko Nature Park is located in the extreme north-east of Slovenia. Most of the area (96%) is a Natura 2000 site (Uredba … 2004). This is a hilly area with an average elevation between 300 and 350 m above sea level and intermittent valleys at an elevation of 220–260 m (Digitalni … 2001). Acid to neutral soil developed on noncarbonate bedrock (Internet 3). Average annual air temperature is 9.7 °C and the average annual precipitation is 761.8 mm (Meteorološki podatki … 2009). According to 58-1-Special issue_10p_727-Darijo Ilic_acta49-1.qxd 12.9.2017 7:59 Page 127 Darijo Ilić, jože Panjan, Nitrogen and Phosphorus Pollution in Goričko Nature Park 128 Gabrovec and Kastelec (1998), the annual quasi-global radiation energy (the sum of direct and diffuse solar radiation) on inclined surfaces ranges from 3,300 Mj/m2 at lower elevations of the central and eastern parts of Goričko Nature Park to around 4,000–4,800 Mj/m2 in the remaining parts. Goričko Nature Park was divided into three parts: the Ledava, Big Krka (Velika Krka), and Kobilje Creek (Kobiljski potok) basins. The Ledava Basin (Internet 1) covers 21.4 km2 (46.3%) of Goričko Nature Park, the Big Krka Basin covers 14.6km2 (31.6%), and the Kobilje Creek Basin covers 7.9km2 (17%). The total length of all watercourses in the nature park is 664 km: 309 km in the Ledava Basin, 95 km in the Big Krka Basin, and the rest in the Kobilje Creek Basin. These three basins cover a total of nearly 95% of the area of Goričko Nature Park. There are differences (Internet 4) in the land use structure (Figure 1) between individual basins. The share of forest increases from the west; it accounts for 42% of land use in the Ledava Basin, 49% in the Big Krka Basin, and 52% in the Kobilje Creek Basin in the east. The Kobilje Creek Basin has a significantly small- er share of grassland (9%) compared to the Big Krka and Ledava basins, where the percentages are 16% and 18%, respectively. There are no significant differences between the basins in other land use categories. 3 Results Pollution sources are studied in relation to discharge. In watercourses with predominantly diffuse pollu- tion sources, pollution increases with discharge (Novotny 1988). The opposite is typical of point pollution sources, where pollutant concentration decreases with increased discharge. 3.1 Nitrogen compounds The presence of ammonium nitrogen (NH4+) in river water is the result of faecal pollution (with people and livestock farming being its main sources; Ibanez et al. 2007). The recommended ammonium levels of 0.04 mg/l 10 20 30 40 50 60 ForestFields ad gardens Grassland Other farming areas Other non- farming areas- Permanent crops 0 (% ) Kobiljski potok watershed Velika Krka watershed Ledava watershed Figure 1: Land use by basin in Goričko Nature Park. 58-1-Special issue_10p_727-Darijo Ilic_acta49-1.qxd 12.9.2017 7:59 Page 128 Acta geographica Slovenica, 58-1, 2018 129 Ta ble 1: Co rre lat ion co eff ici en ts at sa m pli ng si tes r2 Le da va Le da va Bo do nc i Bo kra či Ad rija nc i Do len ci Big Sm all Ko bil je Bu ko vn ica Bo go jin a Nu sk ov a Do m aji nc i Cre ek Cre ek Cre ek Cre ek Kr ka Kr ka Cre ek Cre ek Cre ek [W ate rT] /[A irT ] 0.9 2 0.8 8 0.9 2 0.9 3 0.9 3 0.8 5 0.8 7 0.9 4 0.9 4 0.9 2 0.9 1 [W ate rT] /[O xy ge n co nc en tra tio n] –0 .50 –0 .84 –0 .89 –0 .87 –0 .80 –0 .76 –0 .42 –0 .88 –0 .07 –0 .82 –0 .84 [N itr ite ]/ [A m m on ium ] 0.2 7 –0 .27 –0 .17 0.0 3 –0 .11 0.0 0 0.3 3 0.3 1 0.7 6 0.0 2 0.4 6 [Tu rb idi ty] / [D isc ha rg e] 0.0 2 –0 .05 0.5 5 0.8 9 0.7 7 0.6 1 0.4 7 0.7 5 0.3 7 0.4 8 0.8 6 [Tu rb idi ty] / [U nd iss olv ed m att er] 0.9 4 0.9 3 0.9 5 0.8 8 0.9 9 1.0 0 0.3 5 0.1 0 0.8 7 0.9 0 1.0 0 [U nd iss olv ed m att er] / [D isc ha rg e] –0 .01 –0 .15 0.7 5 0.9 3 0.7 7 0.6 2 0.1 4 0.3 6 0.3 3 0.7 5 0.8 7 [O rth op ho sp ha te] / [U nd iss olv ed m att er] 0.7 9 –0 .06 0.7 0 0.9 1 0.8 7 0.4 7 0.1 5 0.2 5 0.2 2 0.1 6 0.9 0 [To tal ph os ph or us ]/ [U nd iss olv ed m att er] 0.9 5 0.7 3 0.9 1 0.8 7 0.9 9 0.5 8 0.5 3 0.3 9 0.8 1 0.5 8 0.9 8 [N itr ate ]/[ Di sc ha rg e] 0.9 5 0.4 7 0.6 7 0.8 1 0.5 9 0.5 7 0.3 1 0.9 1 0.4 5 0.2 7 0.7 6 58-1-Special issue_10p_727-Darijo Ilic_acta49-1.qxd 12.9.2017 7:59 Page 129 Darijo Ilić, jože Panjan, Nitrogen and Phosphorus Pollution in Goričko Nature Park specified in the Decree on the Quality of Surface Waters for the Life of Freshwater Fish Species for Salmonid Waters (Uredba … 2002) are regularly exceeded at all the sampling sites. It can be established that the aver- age ammonium levels at the Ledava Nuskova sampling site before its inflow into Lake Ledava are lower than at the Ledava Domajinci sampling site after its outflow from Lake Ledava. On the other hand, the mean nitrate levels (NO3–) before Lake Ledava are higher than after Lake Ledava. Hence it can be concluded that denitrification is taking place in the predominantly anaerobic conditions in the reservoir Lake Ledava. Because the standard deviation for nitrate at the Ledava Domajinci sampling site is typically smaller than at the Ledava Nuskova sampling site, this seems to be an ongoing process. Nitrate is a soluble form of nitrogen that usually seeps into groundwater quickly and is then released into the river water as base runoff. Table 1 shows the correlation coefficients for [NITRATE]/[DISCHARGE], r2 >0.4. It can be concluded that this results from the nitrate being washed from farmland due to poor soil perme- ability. The nitrate levels do not exceed the limits specified in the Rules on Drinking Water, but the levels measured in the surface watercourses are nonetheless high. A seasonal impact of nitrate being washed from farmland can also be observed, with excesses after spring or fall fertilization, depending on precipitation. Based on what is known about the nitrogen cycle, nitrites result from nitrification processes. Compared to the levels recommended in the Decree on the Quality of Surface Waters for the Life of Freshwater Fish Species for Salmonid Waters (Uredba…2002), these levels are elevated, and they are constant. Some sampling sites (Kobilje Creek, Bogojina Creek, Small Krka, and Big Krka) have a high correlation for [NITRITE]/[AMMO- NIUM], r2 > 70, which may be due to nearby settlements, unregulated sewage systems, and livestock farming. Such correlations were not established at sampling sites for which the impact of settlements is smaller. Pollution by total nitrogen compounds is presented in Figures 2 to 4. The pollution curves indicate a significant impact of diffuse sources on the watercourses in Goričko Nature Park. The impact is less pro- nounced at the Ledava Domajinci sampling site, which is most likely due to the influence of Lake Ledava, in which chemical processes and accumulation take place. This impact is also less pronounced at the Bukovnica Creek sampling site, which is probably due to the creek's lower flow rate, which is regulated by the artifi- cial reservoir Lake Bukovnica. This is a tourist area, where a large number of visitors can influence the current conditions in the watercourse. 130 y = 5.451 x – 0.4869 = 0.9383R 2 y = 2.5233 x – 0.0067 0.8454R = 2 y = 8.6945 x – 0.336 R = 2 0.9308 –2 2 4 6 8 10 12 0.5 1.0 1.5 2.0 2.5 Linear (Ledava Nuskova) Linear (Ledava Domajinci) Linear (Bokra ki potok)č Discharge (m /s) 3 Ledava Nuskova Ledava Domajinci Bodonski potok Bokra ki potokč 0 B u rd en o f jo in t co m p o u n d s (g /s ) Figure 2: Total nitrogen pollution in the Ledava Basin. 58-1-Special issue_10p_727-Darijo Ilic_acta49-1.qxd 12.9.2017 7:59 Page 130 Acta geographica Slovenica, 58-1, 2018 131 yAdrijanski potok = 3.4686 x - 0.0481 R = 2 0.9655 yVelika Krka = 3.2979 x + 0.1949 R = 2 0.939 yMala Krka = 6.3466 x – 0.3201 R = 2 0.9423 –2 2 4 6 8 10 12 14 16 18 1 2 3 4 5 6 Linear (Adrijanski potok) Linear (Velika Krka ) Linear (Mala Krka) 0 Adrijanski potok Velika Krka Mala Krka B u rd en o f jo in t n it ro ge n c o m p o u n d s (g /s ) Discharge (m /s) 3 yKobiljski potok = 4.5538 x – 0.1149 R = 2 0.989 y = 2.9894 x + 0.0071Bukovniški potok yBogojinski potok = 6.4345 x – 0.1407 R = 2 0.9537 –2 2 4 6 8 10 12 14 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Kobiljski potok Bukovniški potok Bogojinski potok Linear (Kobiljski potok) Linear (Bukovniški potok) Linear (Bogojinski potok) Discharge (m /s) 3 0 B u rd en o f jo in t n it ro ge n c o m p o u n d s (g /s ) Figure 3: Total nitrogen pollution in the Big Krka Basin. Figure 4: Total nitrogen pollution in the Kobilje Creek Basin. 58-1-Special issue_10p_727-Darijo Ilic_acta49-1.qxd 12.9.2017 7:59 Page 131 Darijo Ilić, jože Panjan, Nitrogen and Phosphorus Pollution in Goričko Nature Park 3.2 Phosphorus compounds The moderate correlation of [TOTAL PHOSPORUS]/[UNDISSOLVED MATTER], r2 >0.5 stands out. When water erodes the soil, the phosphorus bound in the soil particles is washed into watercourses (the impact of diffuse source pollution; Pierzynsky et al. 1994). During periods of low discharge, total phosphorus con- centrations are typically smaller, but constant, and are the result of unregulated sewage systems and manure pits on farms (the impact of point source pollution by total phosphorus). just like with total phosphorus, the correlation for [ORTHOPHOSPHATE]/[UNDISSOLVED MATTER] is also high: r2 > 0.7 is typical of the Ledava Basin, except at the Ledava Domajinci sampling site, where there is hardly any correlation. It can be concluded that this is due to the accumulation of orthophosphate in Lake Ledava, which is a hyper- trophic lake according to the OECD criteria (Poročilo … 2007). Pollution by total phosphorus compounds is shown in Figures 5 to 7. The impact of point sources on pollution in the Ledava Basin is small, but constant. Based on these results it can be concluded that unreg- ulated sewage systems and farming (livestock breeding) contribute to both point and diffuse source pollution. 4 Discussion Extensive surface water quality monitoring was performed in Goričko Nature Park in order to determine the level of nitrogen and phosphorus pollution and other accompanying parameters. The study area was divid- ed into three subareas or third-order basins: the Ledava, Big Krka, and Kobilje Creek basins. Measurements were taken once a month over the course of 1.5 years. Pollution in relation to discharge was calculated for each sampling site. The results show that the nutrient release dynamics in Goričko Nature Park are in high correlation with precipitation events. Similar dynamics have also been established for the Krka River Basin (Drolc 1998) and the Padež Basin (Rusjan 2008). The chemical composition of the waters included in the study is poor at all sampling sites. During the study the total nitrogen concentrations were high and fair- ly stable. Ammonium and nitrite (as an intermediate product of nitrification) stand out more than nitrogen. 132 yLedava Nuskova = 0.7145 x 0.0669– R = 2 0.8651 yLedava Domajinci = 0.1967 x + 0.0383 R = 2 0.5405 yBokra ki potokč = 11.226 x 0.6557– R = 2 0.7698 –2 2 4 6 8 10 12 0.5 1.0 1.5 2.0 2.5 Linear (Ledava Nuskova) Linear (Ledava Domajinci) Linear (Bokra ki potok)č B u rd en o f jo in t p h o sp h o ru s (g /s ) 0 Ledava Nuskova Ledava Domajinci Bodonski potok Bokra ki potokč Discharge (m /s) 3 Figure 5: Pollution by total phosphorus compounds in the Ledava Basin. 58-1-Special issue_10p_727-Darijo Ilic_acta49-1.qxd 12.9.2017 7:59 Page 132 Acta geographica Slovenica, 58-1, 2018 133 y Adrijanski potok = 1.3852 x – 0.1129 R = 2 0.587 y Velika Krka = 0.7176 x – 0.0102 R = 2 0.7082 y Mala Krka = 0.9606 x – 0.0728 R = 2 0.6723 –0.5 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 1 2 3 4 5 6 Discharge (m /s) 3 0.0 B u r d e n o f j o i n t p h o s p h o r u s ( g / s ) Linear (Adrijanski potok) Linear (Velika Krka ) Linear (Mala Krka) Adrijanski potok Velika Krka Mala Krka yKobiljski potok = 1.0719 x + 0.0515 R = 2 0.703 yBukovniški potok = 0.7164 x + 0.0043 R = 2 0.9114 yBogojinski potok = 4.0899 x – 0.1594 R = 2 0.7847 –0.5 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Kobiljski potok Bukovniški potok Bogojinski potok Linear (Kobiljski potok) Linear (Bukovniški potok) Linear (Bogojinski potok) Discharge (m /s) 3 B u rd en o f jo in t p h o sp h o ru s (g /s ) 0.0 Figure 6: Pollution by total phosphorus compounds in the Big Krka Basin. Figure 7: Pollution by total phosphorus compounds in the Kobilje Creek Basin. 58-1-Special issue_10p_727-Darijo Ilic_acta49-1.qxd 12.9.2017 7:59 Page 133 Darijo Ilić, jože Panjan, Nitrogen and Phosphorus Pollution in Goričko Nature Park It can be concluded that unregulated manure pits on livestock farms are the main reason for the high lev- els of ammonium release. In a study conducted by Lapajne (2006), no final conclusions were reached on the high ammonium levels in the Ledava Valley, but the researchers did conclude that they were due to emissions from the livestock farms or wastewater from unregulated sewage systems. The main reasons for the high levels of nitrogen compounds lie in the chemical composition of nitrogen and the nitrogen releas- es from intensively farmed land (Eickhout et al. 2006), as well as the low effectiveness of nitrogen fertilizers (Strebel etal. 1989). Beaudoin etal. (2005) established that the levels of nitrates washed from farmland depend primarily on the type of soil: low levels were determined in deep, poorly permeable clay soil and the high- est levels were found in shallow, permeable sandy soil. ju et al. (2006) established a high correlation between the intensity of farming and nitrate levels in groundwater. Another important factor in nutrient release is the natural conditions that affect land use and the use structure of farmland. The total phosphorus concentration is highly correlated with precipitation events, because it binds to sus- pended particles and erodes into the drains. Likewise, the excessive levels of phosphorus compounds in the Ledava River also result from farm runoff via precipitation (Lapajne 2006). Sharpley et al. (1999) also deter- mined that the concentration of phosphorus compounds increases with precipitation, and Hanrahan etal. (2003) concluded that the majority of phosphorus transfer takes place periods of intense precipitation. Measures for reducing nutrient pollution in rivers should focus on decreasing the nutrient concen- trations at the outflows through tertiary treatment at treatment plants and significant reduction of inputs from agriculture. Drolc and Končan (2002) believe that by implementing all of these water management measures, the total phosphorus emissions in river basins could decrease by 40%. In order to reduce the nutrient release caused by diffuse pollution, certain measures have been proposed (Internet 2) to increase fertilizer effectiveness and hence decrease erosion from farmland (Komac and Zorn 2005; Zorn 2009), and to promote unconventional farming in environmentally more sensitive regions. Some measures for decreas- ing diffuse sources of pollution do not comply with agricultural practice and economics. Tertiary treatment of phosphorus and nitrogen at large treatment plants can also help reduce water pollution. Despite the work carried out by large treatment plants, minor point sources of pollution still remain a problem. In order to solve it effectively, tertiary treatment at small treatment plants should be introduced. These treatment plants release water into small, environmentally more sensitive creeks in the countryside (Wheater and Daldorf 2003), where tertiary treatment could help reduce the pollution of river basins. 5 Conclusion The acquired data show that rivers have only moderate thermal potential and that weather has the most significant impact on watercourse conditions. This is primarily reflected in the high correlations between water and air temperature. Subsequently, the thermal potential of watercourses has a strong impact on the concentration of dissolved oxygen in water. A comparative analysis was conducted using the data collected from eleven sampling sites used to monitor the surface waters in Goričko Nature Park. Because the study area was divided into three parts, the data obtained were also compared by river basin. All three basins are characterized by increased concentrations of nitrogen and phosphorus compounds, which resulted in poor chemical composition of surface waters at all sampling sites. The results of this study show that the watercourses in the entire study area are polluted by nitrogen and phosphorus compounds. A trend of significant nitrate increase can be observed in the Mura Basin and the watersheds of Adriatic rivers, and orthophosphate pollution is increasing as well (Internet 5). 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D. 2005: Sampling, sample treatment and quality assurance issues for the determination of phosphorus species in natural waters and soils. Talanta 66. DOI: http://dx.doi.org/10.1016/j.talanta.2004.09.006 Wood, C. W. 1998: Agricultural phosphorus and water quality: an overview. Southern cooperative series, Bulletin 389. Zorn, M. 2009: Erosion processes in Slovene Istria – part 1: Soil erosion. Acta geographica Slovenica 49-1. Ljubljana. 136 58-1-Special issue_10p_727-Darijo Ilic_acta49-1.qxd 12.9.2017 7:59 Page 136 Guidelines for contributing authors in Acta geographica Slovenica EDITORIAL POLICIES 1 Focus and scope The Slovenian geographical journal Acta geographica Slovenica (print version: ISSN: 1581-6613, digital ver- sion: ISSN: 1581-8314) is published by the Anton Melik Geographical Institute of the Slovenian Academy of Sciences and Arts Research Center. 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Geografski zbornik 34. • de Kerk, G. V., Manuel, A. R. 2008: A comprehensive index for a sustainable society: The SSI – the Sustainable Society Index. Ecological Economics 66-2,3. DOI: https://doi.org/10.1016/j.ecolecon.2008.01.029 • van Hall, R. L., Cammeraat, L. H., Keesstra, S. D., Zorn, M. 2016: Impact of secondary vegetation suc- cession on soil quality in a humid Mediterranean landscape. Catena, In press. DOI: https://doi.org/10.1016/ j.catena.2016.05.021 (25. 11. 2016). 3.2 Citing books • Cohen, J. 1988: Statistical power analysis for the behavioral sciences. New York. • Nared, J., Razpotnik Visković, N. (eds.) 2014: Managing cultural heritage sites in Southeastern Europe. Ljubljana. • Fridl, J., Kladnik, D., Perko, D., Orožen Adamič, M. (eds.) 1998: Geografski atlas Slovenije. Ljubljana. • Luc, M., Somorowska, U., Szmańda, J. B. (eds.) 2015: Landscape analysis and planning. Heidelberg. DOI: https://doi.org/10.1007/978-3-319-13527-4 3.3 Citing parts of books or proceedings • Zorn, M., Komac, B. 2013: Land degradation. Encyclopedia of Natural Hazards. Dordrecht. DOI: https://doi.org/10.1007/978-1-4020-4399-4_207 • Hrvatin, M., Perko, D., Komac, B., Zorn, M. 2006: Slovenia. Soil Erosion in Europe. Chichester. DOI: https://doi.org/10.1002/0470859202.ch25 • Gams, I. 1987: A contribution to the knowledge of the pattern of walls in the Mediterranean karst: a case study on the N. island Hvar, Yugoslavia. Karst and man, Proceedings of the International Symposium on Human Influence in Karst. Ljubljana. • Komac, B., Zorn, M. 2010: Statistično modeliranje plazovitosti v državnem merilu. Od razumevanja do upravljanja, Naravne nesreče 1. Ljubljana. 3.4 Citing expert reports, theses, and dissertations • Breg Valjavec, M. 2012: Geoinformatic methods for the detection of former waste disposal sites in karstic and nonkarstic regions (case study of dolines and gravel pits). Ph.D. thesis, University of Nova Gorica. Nova Gorica. • Hrvatin, M. 2016: Morfometrične značilnosti površja na različnih kamninah v Sloveniji. Ph.D. thesis, Univerza na Primorskem. Koper. • Holmes, R. L., Adams, R. K., Fritts, H. C. 1986: Tree-ring chronologies of North America: California, Eastern Oregon and Northern Great Basin with procedures used in the chronology development work including user manual for computer program COFECHA and ARSTAN. Chronology Series 6. University of Arizona, Laboratory of tree-ring research. Tucson. • Šifrer, M. 1997: Površje v Sloveniji. Elaborat, Geografski inštitut Antona Melika ZRC SAZU. Ljubljana. 3.5 Citing online material with authors and titles • Bender, O., Borsdorf, A., Heinrich, K. 2010: The interactive alpine information system GALPIS. Challenges for mountain regions, Tackling complexity. Internet: http://www.mountainresearch.at/images/Publikationen/ Sonderband/bender-borsdorf-heinrich.pdf (4. 8. 2014). 3.6 Citing online material without authors • Internet: http://giam.zrc-sazu.si (18. 11. 2016). • Internet 1: http://giam.zrc-sazu.si/ (22. 7. 2012). • Internet 2: http://ags.zrc-sazu.si (23. 7. 2012). Acta geographica Slovenica, 58-1, 2018 58-1-navodila za avtorje_koncni kolofon_11p_acta49-1.qxd 12.9.2017 7:59 Page 140 141 Acta geographica Slovenica, 58-1, 2018 3.7 Citing sources without authors • WCED – World commission on environmental and development: Our common future – Brundtland report. Oxford, 1987. • Popis prebivalstva, gospodinjstev, stanovanj in kmečkih gospodarstev v Republiki Sloveniji, 1991 – končni podatki. Zavod Republike Slovenije za statistiko. Ljubljana, 1993. 3.8 Citing cartographic sources • Državna topografska karta Republike Slovenije 1 :25.000, list Brežice. Geodetska uprava Republike Slovenije. Ljubljana, 1998. • Franciscejski kataster za Kranjsko, k. o. Sv. Agata, list A02. Arhiv Republike Slovenije. Ljubljana, 1823–1869. • Buser, S. 1986: Osnovna geološka karta SFRJ 1 : 100.000, list Tolmin in Videm (Udine). Savezni geološki zavod. Beograd. • The vegetation map of forest communities of Slovenia 1 : 400,000. Biološki inštitut Jovana Hadžija ZRC SAZU. Ljubljana, 2002. • Digitalni model višin 12,5. Geodetska uprava Republike Slovenije. Ljubljana, 2005. 3.9 Citing official gazettes • Zakon o kmetijskih zemljiščih. Uradni list Republike Slovenije 59/1996. Ljubljana. • Zakon o varstvu pred naravnimi in drugimi nesrečami. Uradni list Republike Slovenije 64/1994, 33/2000, 87/2001, 41/2004, 28/2006 in 51/2006. Ljubljana. • 1999/847/EC: Council Decision of 9 December 1999 establishing a Community action programme in the field of civil protection. Official Journal 327, 21. 12. 1999. 3.10 In-text citations Please ensure that every reference cited in the text is also in the reference list (and vice versa). In-text cita- tions should state the last name of the author(s) and the year, separate individual citations with semicolons, order the quotes according to year, and separate the page information from the name of the author(s) and year information with a comma; for example: (Melik 1955), (Melik, Ilešič and Vrišer 1963; Kokole 1974, 7–8; Gams 1982a; Gams 1982b). For sources with more than three authors, list only the first followed by et al.: (Melik et al. 1956). Cite page numbers only for direct citations: Perko (2016, 25) states: »Hotspots are …« To cite online material with authors, cite the name: (Zorn 2010). To cite online material without authors, cite only Internet fol- lowed by a number: (Internet 2). 3.11 Works cited list Arrange references alphabetically and then chronologically if necessary. Identify more than one reference by the same author(s) in the same year with the letters a, b, c, etc., after the year of publication: (1999a, 1999b). Use this format for indirect citations: (Gunn 2002, cited in Matei et al. 2014). Include the Digital Object Identifier (DOI) in the reference if available. Format the DOI as follows: https://doi.org/… (for example: https://doi.org/10.3986/AGS.1812). 4 Tables and figures Number all tables in the paper uniformly with their own titles. The number and the text are separated by a colon, and the caption ends with a period. Example: Table 1: Number of inhabitants of Ljubljana. Table 2: Changes in average air temperature in Ljubljana (Velkavrh 2009). 58-1-navodila za avtorje_koncni kolofon_11p_acta49-1.qxd 12.9.2017 7:59 Page 141 142 Tables should contain no formatting and should not be too large; it is recommended that tables not exceed one page. Upload figures to the OJS as separate supplementary files in digital form. If the graphic supplements prepared cannot be uploaded using these programs, consult the editorial board in advance. Number all figures (maps, graphs, photographs) in the paper uniformly with their own titles. Example: Figure 1: Location of measurement points along the glacier. All graphic materials must be adapted to the journal’s format. Illustrations should be exactly 134 mm wide (one page) or 64 mm wide (half page, one column), and the height limit is 200 mm. To make anonymous peer review possible, include the name of the author(s) with the title of the illus- tration in the supplementary file metadata, but not in the paper text. Maps should be made in digital vector form with Corel Draw, Adobe Illustrator, or a similar program, espe- cially if they contain text. They can exceptionally be produced in digital raster form with at least 300 dpi resolution, preferably in TIFF or JPG format. For maps made with CorelDraw or Adobe Illustrator, two separate files should be prepared; the original file (.cdr or .ai format) and an image file (.jpg format). For maps made with ArcGIS with raster layers used next to vector layers (e.g., .tif of relief, airborne or satellite image), three files should be submitted: the first with a vector image without transparency togeth- er with a legend and colophon (export in .ai format), the second with a raster background (export in .tif format), and the third with all of the content (vector and raster elements) together showing the final ver- sion of the map (export in .jpg format). Do not print titles on maps; they should appear in a caption. Save colors in CMYK, not in RGB or other formats. Use Times New Roman for the legend (size 8) and colophon (size 6). List the author(s), scale, source, and copyright in the colophon. Write the colophon in English (and Slovenian, if applicable). Example: Scale: 1 : 1,000,000 Content by: Drago Perko Map by: Jerneja Fridl Source: Statistical Office of the Republic of Slovenia, 2002 © 2005, ZRC SAZU Anton Melik Geographical Institute Graphs should be made in digital form using Excel on separate sheets and accompanied by data. Photos must be in raster format with a resolution of 240 dots per cm or 600 dpi, preferably in .tif or .jpg formats; that is, about 3,200 dots per page width of the journal. Figures containing a screenshot should be prepared at the highest possible screen resolution (Control Panel\All Control Panel Items\Display\Screen Resolution). The figure is made using Print Screen, and the captured screen is pasted to the selected graphic program (e.g., Paint) and saved as .tif. The size of the image or its resolution must not be changed. Examples of appropriate graphic data forms: see the templates of maps in cdr and mxd files for a whole- page map in landscape view and an example of correct file structure for submitting a map made with ESRI ArcGIS. SUBMISSION PREPARATION CHECKLIST As part of the submission process, check your submission’s compliance with the following items. Submissions may be returned to author(s) that do not follow these guidelines. 1. The journal policies have been reviewed. 2. The submission has not been previously published and is not being considered for publication else- where (or an explanation has been provided in comments to the editor). 3. The metadata (title, abstract, key words, full address, etc.) are provided in English and Slovenian, when applicable. 4. The submission is in Microsoft Word format and the document template was used (single-spaced text, 12-point font, no formatting except italics and bold). Acta geographica Slovenica, 58-1, 2018 58-1-navodila za avtorje_koncni kolofon_11p_acta49-1.qxd 12.9.2017 7:59 Page 142 143 Acta geographica Slovenica, 58-1, 2018 5. The manuscript has been checked for spelling and grammar. 6. All figure locations in the text are marked. Figures are not in the text and are provided as supplementary files: cdr, .ai for maps and illustrations; .tif for photographs; xlsx for graphs. 7. Tables are placed in the text at the appropriate place. 8. The reference list was prepared following the guidelines. 9. All references in the reference list are cited in the text, and vice versa. 10. Where available, URLs and DOI numbers for references are provided. 11. Supplementary files are in one .zip file not exceeding 50 MB. 12. I agree for this article to be translated or copyedited at my expense AFTER the article is accepted for publication (see guidelines for details). 13. Permission has been obtained for the use of copyrighted material from other sources, including online sources; see the copyright notice below. 14. The instructions for ensuring a double-blind review have been followed. ACTA GEOGRAPHICA SLOVENICA EDITORIAL REVIEW FORM Acta geographica Slovenica editorial review form 1 The paper is an original scientific one – the paper follows the standard IMRAD scheme and is original and the first presentation of research results with the focus on methods, theoretical aspects or case study.) Yes No 2 The paper's content is suitable for publishing in the AGS journal – the paper is from the field of geog- raphy or related fields of interest, the presented topic is interesting and well presented. In case of negative answer add comments below.) Yes No 3 Editorial notes regarding the paper's content. 4 Length of the paper is acceptable for further processing (20.000 characters including space). If longer, the paper has to be shortened by the author and resubmitted. • The paper has less than 20.000 characters. • The paper has more than 20.000 characters, but less than 25.000. • The paper has more than 25.000 characters. 5 The style and formatting of the paper is according to the AGS guidelines – the paper is prepared in plain text, no other text formatting is used than bold and italic. See the Guidelines of AGS journal for details.) Yes No 6 Notes regarding style and formatting. 7 Citing in the paper is according to the AGS guidelines and style, including DOI identificators. Yes No 8 The reference list is suitable (the author cites previously published papers with similar topic from other relevant scientific journal). Yes, the author cited previously published papers on similar topic. No, the author did not cite previously published papers on similar topic. 9 Scientific language of the paper is appropriate and understandable. Yes No 58-1-navodila za avtorje_koncni kolofon_11p_acta49-1.qxd 12.9.2017 7:59 Page 143 144 10 Supplementary files (ai, cdr, pdf, tif, jpg, xlsx etc.) that were added to the paper are in proper format and resolution (including the introductory photo), maps are prepared according to the AGS Guidelines. (In this step contact the technical editor [rok.ciglic@zrc-sazu.si] for assistance if needed). • Supplementary files are correct. • Supplementary files are not appropriate and need a major correction. • Some supplementary files need corrections. 11 Describe the possible deficiencies of the supplementary files: 12 DECISION OF THE RESPONSIBLE EDITOR The paper is accepted for further processing and may be sent to the reviewer. The paper is accepted for further processing but needs technical improvements (see notes). The paper is accepted for further processing but its content needs additional improvements (see notes). The paper is not accepted for publication because: • It is more suitable for a specialized journal. • Does not fit the aims and scopes of the AGS journal. • Is not an original scientific paper. • The presentation of the results is poor. • The paper is of very low quality. • The paper has already been published elsewhere. • Other (see comments below). • Other reasons for rejection of the paper. ACTA GEOGRAPHICA SLOVENICA REVIEW FORM 1 RELEVANCE 1a) Are the findings original and the paper is therefore a significant one? Yes No Partly 1b) Is the paper suitable for the subject focus of the AGS journal? Yes No 2 SIGNIFICANCE 2a Does the paper discuss an important problem in geography or related fields? Yes No Partly 2b Does it bring relevant results for contemporary geography? Yes No Partly 2c What is the level of the novelty of research presented in the paper? High Middle Low 3 ORIGINALITY 3a Has the paper been already published or is too similar to work already published? Yes No Acta geographica Slovenica, 58-1, 2018 58-1-navodila za avtorje_koncni kolofon_11p_acta49-1.qxd 12.9.2017 7:59 Page 144 145 Acta geographica Slovenica, 58-1, 2018 3b Does the paper discuss a new issue? Yes No 3c Are the methods presented sound and adequate? Yes No Partly 3d Do the presented data support the conclusions? Yes No Partly 4 CLARITY 4a Is the paper clear, logical and understandable? Yes No 4b If necessary, add comments and recommendations to improve the clarity of the title, abstract, keywords, introduction, methods or conclusion: 5 QUALITY 5a Is the paper technically sound? (If no, the author should discuss technical editor [rok.ciglic@zrc-sazu.si] for assistance.) Yes No 5b Does the paper take into account relevant current and past research on the topic? Yes No Propose amendments, if no is selected: 5d Is the references list the end of the paper adequate? Yes No Propose amendments, if no is selected: 5e Is the quoting in the text appropriate? Yes No Partly Propose amendments, if no is selected: 5f Which tables are not necessary? 5g Which figures are not necessary? 6 COMMENTS OF THE REVIEWER Comments of the reviewer on the contents of the paper: Comments of the reviewer on the methods used in the paper: 7 RECOMMENDATION OF THE REVIEWER TO THE EDITOR-IN-CHIEF My recommendation is: Please rate the paper from 1 [low] to 100 [high]: Personal notes of the reviewer to editor-in-chief. 58-1-navodila za avtorje_koncni kolofon_11p_acta49-1.qxd 12.9.2017 7:59 Page 145 146 COPYRIGHT NOTICE The Acta geographica Slovenica editorial board and the publisher, the ZRC SAZU Anton Melik Geographical Institute, are committed to ensuring ethics in publication and the quality of published books and jour- nals by following the Acta Geographica Slovenica Publication Ethics and Publication Malpractice Statement. Authors must respect the copyright rules of data owners; for example, the rules of the Slovenian Surveying and Mapping Authority are available at its webpage. For paper sent to Acta geographica Slovenica, authors agree that all moral rights of the authors remain with the authors; material rights to reproduction and distribution in Slovenia and other countries are exclusively ceded to the publisher for no fee, for all time, for all cases, for unlimited editions, and for all media; and mate- rial rights to the paper figures (maps, photos, graphs, etc.) are ceded to the publisher on a non-exclusive basis. Authors allow publication of the paper or its components on the internet. Authors give permission to the publisher to modify the paper to conform to its guidelines, including the length of the paper. Authors shall provide a professional translation of papers not originally in English. The name of the translator must be reported to the editor. No honoraria are paid for papers in Acta geographica Slovenica or for the reviews. The first author of the paper shall receive one free copy of the publication. FAQ Some common questions and answers are available on the journal webpage: ags.zrc-sazu.si. PRIVACY STATEMENT The names and e-mail addresses provided to this journal site will be used exclusively for the stated purposes of this journal and will not be made available for any other purpose or to any other party. PUBLISHER Anton Melik Geographical Institute Research Center of the Slovenian Academy of Sciences and Arts PO Box 306 SI–1001 Ljubljana Slovenia SOURCES OF SUPPORT Slovenian Academy of Sciences and Arts Slovenian Research Agency JOURNAL HISTORY Acta geographica Slovenica (print version: ISSN: 1581-6613, digital version: ISSN: 1581-8314) was founded in 1952. It was originally named Geografski zbornik / Acta geographica (ISSN 0373-4498). Altogether 42 volumes were published. In 2002 Geographica Slovenica (ISSN 0351-1731, founded in 1971, 35 volumes) was merged with the journal. Since 2003 (from volume 43 onward) the name of the joint journal has been Acta geographica Slovenica. The journal continues the numbering system of the journal Geografski zbornik / Acta geographica. Acta geographica Slovenica, 58-1, 2018 58-1-navodila za avtorje_koncni kolofon_11p_acta49-1.qxd 12.9.2017 7:59 Page 146 147 Acta geographica Slovenica, 58-1, 2018 Those interested in the history of the journal are invited to read the paper »The History of Acta geo- graphica Slovenica.« All published issues of Acta geographica Slovenica are available free of charge at http://ags.zrc-sazu.si or http://ojs.zrc-sazu.si/ags. 58-1-navodila za avtorje_koncni kolofon_11p_acta49-1.qxd 12.9.2017 7:59 Page 147 ISSN: 1581-6613 UDC – UDK: 91 ACTA GEOGRAPHICA SLOVENICA GEOGRAFSKI ZBORNIK 58-1 2018 © Geografski inštitut Antona Melika ZRC SAZU, 2018 Print/tisk: Collegium Graphicum d. o. o. Ljubljana 2018 58-1-navodila za avtorje_koncni kolofon_11p_acta49-1.qxd 12.9.2017 7:59 Page 148 ACTA GEOGRAPHICA SLOVENICA GEOGRAFSKIZBORNIK 2018 58 1 0101661851779 ISSN 1581-6613 A C TA G E O G R A P H IC A S LO V E N IC A • G E O G R A FS K I Z B O R N IK • 58 -1 • 20 18ACTA GEOGRAPHICA SLOVENICA GEOGRAFSKI ZBORNIK 58-1 • 2018 Contents Milivoj B. Gavrilov, Slobodan B. Marković, Natalija JaNc, Milena Nikolić, aleksandar valJarević, Blaž koMac, Matija ZorN, Milan PuNišić†, Nikola Bačević AssessingaverageannualairtemperaturetrendsusingtheMann–KendalltestinKosovo 7 liza StaNčič, Blaž rePe Post-firesuccession:SelectedexamplesfromtheKarstregion,southwestSlovenia 27 Mirko Grčić, ljiljana Grčić, Mikica SiBiNović ThegeographicalpositionofthetownofRasabasedonPorphyrogenitusandmedievalmaps 39 Special issue – Agriculture in modern landscapes: A factor hindering or facilitating development? Nika raZPotNik viSković, Blaž koMac Agricultureinmodernlandscapes:Afactorhinderingorfacilitatingdevelopment? 51 iwona MarkuSZewSka ConflictsbetweenlegalpolicyandruralareamanagementinPoland 59 Mojca Foški The(non)usefulnessoftheRegisterofExistingAgriculturalandForest LandUseformonitoringtheprocessesinurbanareas 69 Maja PoleNšek, Janez PirNat ForestPatchConnectivity:TheCaseoftheKranj-SoraBasin,Slovenia 83 karmen PaŽek, aleš irGolič, Jernej turk, andreja Borec, Jernej PrišeNk, Matej koleNko, črtomir roZMaN Multi-criteriaassessmentoflessfavouredareas:A statelevel 97 Miomir M. JovaNović, Miško M. MilaNović, Matija ZorN TheuseofNDVIandCORINELandCoverdatabasesforforestmanagementinSerbia 109 Darijo ilić, Jože PaNJaN NitrogenandPhosphorusPollutioninGoričkoNaturePark 125 naslovnica 58-1_naslovnica 49-1.qxd 12.9.2017 7:55 Page 1