Allouche, O, Tsoar, A & Kadmon, R 2006, Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). Journal of Applied Ecology, 43: 1223-1232.
Almasieh, K, Kaboli, M & Beier, P 2016, Identifying habitat cores and corridors for the Iranian black bear in Iran. Ursus, 27: 18-30.
Anderson, RP & Raza, A 2010, The effect of the extent of the study region on GIS models of species geographic distributions and estimates of niche evolution: preliminary tests with montane rodents (genus Nephelomys) in Venezuela. Journal of Biogeography, 37: 1378‐1393.
Barbet‐Massin, M, Jiguet, F, Albert, CH & Thuiller, W 2012, Selecting pseudoabsences for species distribution models: how, where and how many. Methods in Ecology and Evolution, 3: 327–338.
DoE 2018, Department of the Environment of Iran. Accessed 1 October 2018.
Elith, J 2002, Quantitative methods for modeling species habitat: Comparative performance and an application to Australian plants. In S, Ferson and M, Burgman (Eds.). Quantitative methods for conservation biology, Springer-Verlag, New York, pp. 39-58.
Elith, J, Graham, CH, Anderson, R.P. et al 2006, Novel methods improve prediction of species’ distributions from occurrence data. Ecography, 29: 129-151.
Engler, R, Guisan A & Rechsteiner L 2004, An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data. Journal of Applied Ecology, 41: 263-274.
Fick, SE & Hijmans, RJ 2017. Worldclim 2: New 1-km spatial resolution climate surfaces for global land areas.
International Journal of Climatology,
37: 4302-4315.
Firooz, A 1999, Iranian wildlife. University Publishing Center with the collaboration of Green Circle Publishing, Tehran, Iran.P:389-390
Franklin, J 2009, Mapping species distributions: spatial inference and prediction. Cambridge University Press, Cambridge, UK.p:615-615.
Ferretti, F, Bertoldi, G, Sforzi, A & Fattorini, L 2011, Roe and fallow deer: are they compatible neighbors? European Journal of Wildlife Research, 57: 775-783.
FRWMO 2010, Iranian Forests, Range and Watershed Management Organization National Land use/Land cover map. Iranian Forest, Range and Watershed Management Organization, Tehran, Iran,
Gibson, LA,Wilson, BA, Cahill, DM & Hill, J 2004, Modeling habitat suitability of the swamp antechinus (Antechinus minimus maritimus) in the coastal heathlands of southern Victoria, Australia. Biological Conservation, 117: 143-150.
Graham, CH, Ferrier, S, Huettman, F, Moritz, C & Peterson, AT 2004, New developments in museum-based informatics and applications in biodiversity analysis. Trends in Ecology and Evolution, 19: 497-503.
Guisan, A & Zimmermann, N.E 2000, Predictive habitat distribution models in ecology. Ecological Modelling, 135: 147-186.
Heidari Safari Kouchi, A, Moradian Fard, F, Eskandari, A & Rostami Shahraji, T 2015, Investigation of some quantitative and qualitative characteristics of Persian oak (Quercus brantii Lindl) in Bazoft forests of Chahar Mahal and Bakhtiari Province. Zagros Forest Researches, 2: 75-91.
Henareh Khalyani, A, Mayer, AL & Falkowski, MJ 2011, Effects of protection on amount and structure of forest cover at two scales in Bozin and Marakhil protected area, Iran. 1st World Sustain. Forum Conference. Basel, Switzerland,1-6
Hijmans, RJ, Cameron, SE, Parra, JL, Jones, PG & Jarvis, A 2005, Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25: 1965-1978.
Ineichen, P 2015, Habitat selection of roe deer (Capreolus capreolus) in a landscape of fear shaped by human recreation. MSc. Dissertation, Department of Environmental Systems Science (D-USYS). Swiss Federal Institute of Technology(ETH), Zurich, Switzerland, p:1-34
Jiang, G, Zhang, M & Ma, J 2008, Habitat use and separation between red deer Cervus elaphus xanthopygus and roe deer Capreolus pygargus bedfordi in relation to human disturbance in the Wandashan Mountains, Northeastern China. Wildlife Biology, 14: 92-100.
Jimenez-Valverde, A & Lobo, JM 2007, Threshold criteria for conversion of probability of species presence to either-or presence-absence. Acta Oecologica, 31: 361-369.
Kabiri, H. R., Rezaee, H.R & Naderi, S 2017, Genetic diversity of roe deer in Golestan and Mazandaran provinces based on mitochondrial and D-Loop gene sequences. Journal of Animal Ecology, 9: 49-56
Karami, M, Ghadirian, T & Faizolahi, K 2015. The atlas of the mammals of Iran, Iran Department of the Environment, Tehran, Iran, P:181-181
Linnel, JDC, Nilsen, EB & Andersen, R 1999, Selection of bed-sites by roe deer Capreolus capreolus fawns in an agricultural landscape. Acta Theriologica, 49: 103-111.
Lobo, JM, Jime´nez-Valverde, A & Hortal, J 2010, The uncertain nature of absences and their importance in species distribution modeling. Ecography, 33: 103-114.
Lovari, S, Serrao, G & Mori, E 2017, Woodland features determining the home range size of roe deer. Behavioral Processes, 140: 115-120
Morellet, N, Van Moorter, B, Cargnelutti, B, Angibault, JM, Lourtet, B, Merlet, J, Ladet, S & Hewison, AJM 2011, Landscape composition influences roe deer habitat selection at both home range and landscape scales. Landscape Ecology, 26: 999-1010.
Myers, N, Mittermeier, RA, Mittermeier, CG, da Fonseca, GAB & Kent, J 2000, Biodiversity hotspots for conservation priorities. Nature, 403: 853-858.
Mysterud, A & Ostbye, E 1999, Cover as a habitat element for temperate ungulates: effects on habitat selection and demography. Wildlife Society Bulletin, 27: 385-394.
Radeloff, VC, Pidgeon, AM & Hostert, P 1999, Habitat and population modelling of roe deer using an interactive geographic information system. Ecological Modelling, 114: 287-304.
Pellerin, M, Calenge, C, Saïd, S, Gaillard, JM, Fritz, H, Duncan, P & Van Laere, G 2010, Habitat use by female western roe deer (Capreolus capreolus): influence of resource availability on habitat selection in two contrasting years. Canadian Journal of Zoology, 88: 1052-1062.
Phillips, SJ, Anderson, R.P & Schapire, R.E 2006. Maximum entropy modeling of species geographic distributions. Ecological Model, 190: 231-259.
Phillips, SJ, Dudík, M & Schapire, RE 2017, Maxent software for modeling species niches and distributions (Version 3.4.1), http://biodiversityinformatics.amnh.org/open_source/maxent/ (accessed on July 15, 2018).
Sedighi, F, Taheri abkenar, K & Heidari Safari kouchi, A 2020, Effect of physiographic factors on quantitative characteristics of cypress (Juniperus excelsa M. Bieb) trees (case study: Spiro cypress habitat–Damghan), Journal of Forest Research and Development, 6: 29-42.
Soofi, M, Ghoddousi, A, Hamidi, AK, Ghasemi, B, Egli, L 2017, Precision and reliability of indirect population assessments for the Caspian red deer Cervus elaphus maral. Wildlife Biology, doi: 10.2981/wlb.00230p:1-8
Swet, JA 1988, Measuring the accuracy of diagnostic systems. Science, 240: 1285-1293.
Titeux, N, Dufrene, M, Radoux, J, Hirzel, A.H & Defourny, P 2007, Fitness-related parameters improve presence-only distribution modeling for conservation practice: The case of the red-backed shrike. Biological Conservation, 138: 207-223.
Yost, AC, Peterson, SL, Gregg, M & Miller, R 2008, Predictive modeling and mapping sage grouse (
Centrocercus urophasianus) nesting habitat using Maximum Entropy and a long-term dataset from Southern Oregon.
Ecological Informatics, 3: 375-386.