Habitat suitability modelling of Persian squirrel (Sciurus anomalus) in Zagros forests, western Iran


  • Farzaneh Khalili Department of Natural Resources, Isfahan University of Technology
  • Maedeh Sadeghi Department of Natural Resources, Isfahan University of Technology
  • Mansoureh Malekian Department of Natural Resources Isfahan University of Technology, Isfahan




Species distribution model, Habitat Selection, MaxEnt, Oak forests, Zagros Mountains


Habitat is one of the key parameters for species conservation and having adequate knowledge of the habitat requirements of a particular species is inevitable for developing conservation plans. In the current study habitat suitability of the Persian squirrel (Sciurus anomalus) was evaluated in four protected areas in southwestern Iran, using maximum entropy method (MaxEnt). We combined presence-only field data with nine environmental variables including aspect, slope, elevation, distance to river, distance to road, distance to village, climate type, landuse and vegetation types to map the species probability of presence and determine the factors limit its distribution. MaxEnt performed well at predicting the potential suitable habitats of the Persian squirrel with a mean AUC of 0.937. Results of the model indicated that landuse, climate type and distance from roads had the most contribution to the model performance. Persian squirrels have a strong preference for forests, therefore, land cover change due to human activities seems to be an important threat to the squirrel viability. Consequently minimizing anthropologic disturbances is required to maintain the number of Persian squirrels in the region.


Aghtari, H. 2014. Habitat suitability modeling of Persian squirrel using ENFA model in Dena ‎proteced area. M.Sc. Thesis, Payame Noor University Tehran, Iran.‎

Albayrak, U. and Arslan, A., 2006. Contribution to the taxonomical and biological ‎characteristics Sciurus anomalus in Turkey (Mammalia: Rodentia). Turkish journal of Zoology ‎‎30: 111-116.‎

Allen, A. W. 1987. Habitat Suitability index Models: Gray squirrel, U.S.A., Fish and Wildlife ‎Service. FWS/OBS-82/10.19.11pp.‎

Anderson, R. P. and Martı́, E., 2004. Modeling species’ geographic distributions for preliminary ‎conservation assessments: an implementation with the spiny pocket mice (Heteromys) of ‎Ecuador. Biological Conservation 116(2): 167-179.‎

Brown, J. L., 2014. SDMtoolbox: a python-based GIS toolkit for landscape genetic, ‎biogeographic and species distribution model analyses. Methods in Ecology and Evolution 5‎‎(7): 694-700.‎

Elith, J., Phillips, S. J., Hastie, T., Dudík, M., Chee, Y. E. and Yates, C. J., 2011. A statistical ‎explanation of MaxEnt for ecologists. Diversity and Distributions 17 (1): 43-57.‎

Fecske, D. M., Barry, R. E., Precht, F. L., Quigley, H. B., Bittner, S. L. and Webster, T., 2002. ‎Habitat Use by Female Black Bears in Western Maryland. Southeastern Naturalist 1(1): 77-92.‎

Forman, R. T. 2006. Good and bad places for roads: effects of varying road and natural pattern ‎on habitat loss, degradation, and fragmentation. Proceedings of the 2005 International ‎Conference on Ecology and Transportation. North Carolina State University, Raleigh, NC. C.L. ‎Irwin, P. Garrett and K.P. McDermott. .‎

Fourcade, Y., Engler, J. O., Rödder, D. and Secondi, J., 2014. Mapping species distributions ‎with MAXENT using a geographically biased sample of presence data: a performance ‎assessment of methods for correcting sampling bias. PloS one 9 (5): e97122.‎

Guinotte, J. M. and Davies, A. J., 2014. Predicted deep-sea coral habitat suitability for the US ‎West Coast. PloS one 9(4): e93918.‎

Guisan, A. and Thuiller, W., 2005. Predicting species distribution: offering more than simple ‎habitat models. Ecology Letters 8: 993–1009.‎

Guisan, A. and Zimmermann, N. E., 2000. Predictive habitat distribution models in ecology. ‎Ecological modelling 135 (2): 147-186.‎

Hernandez, P. A., Graham, C. H., Master, L. L. and Albert, D. L., 2006. The effect of sample ‎size and species characteristics on performance of different species distribution modeling ‎methods. Ecography 29 (5): 773-785.‎

Hirzel, A. H., Hausser, J., Chessel, D. and Perrin, N., 2002. Ecological-niche factor analysis: ‎How to compute habitat-suitability maps without absence data? Ecology 83: 2027-2036.‎

Khalili, F., Malekian, M. and Hemami, M. R., 2015. Characteristics of den, den tree and sites ‎selected by the Persian squirrel in Zagros forests, western Iran. Mammalia DOI ‎‎10.1515/mammalia-2015-0059.‎

Kumar, S. and Stohlgren, T. J., 2009. Maxent modeling for predicting suitable habitat for ‎threatened and endangered tree Canacomyrica monticola in New Caledonia. Journal of Ecology ‎and Natural Environment 1(4): 094-098.‎

Liu, C., Berry, P. M., Dawson, T. P. and Pearson, R. G., 2005. Selecting thresholds of ‎occurrence in the prediction of species distributions. Ecography 28(3): 385-393.‎

MacKenzie, D. I., Nichols, J. D., Lachman, G. B., Droege, S., Royle, J. A. and Langtimm, C. A., ‎‎2002. Estimating site occupancy rates when detection probabilities are less than one. Ecology ‎‎83(8): 2248-2255.‎

Mirzaei , R., Hemami , M. R., Esmaili Sari , A. and Rezaei, H. R., 2014. Distribution modelling ‎of Lesser Kestrel (Falco naumanni) in Golestan Province, Iran. Environmental Research 4(8): ‎‎149-156.‎

Monk, J., Ierodiaconou, D., Versace, V. L., Bellgrove, A., Harvey, E., Rattray, A., Laurenson, L. ‎and Quinn, G. P., 2010. Habitat suitability for marine fishes using presence-only modelling and ‎multibeam sonar. Marine Ecology Progress Series 420: 157-174.‎

Murienne, J., Guilbert, E. and Grandcolas, P., 2009. Species' diversity in the New Caledonian ‎endemic genera Cephalidiosus and Nobarnus (Insecta: Heteroptera: Tingidae), an approach ‎using phylogeny and species' distribution modelling. Biological Journal of the Linnean Society ‎‎97(1): 177-184.‎

Pearson, R. G. 2007. Species’ distribution modeling for conservation educators and ‎practitioners, American Museum of Natural History, Retrieved from: http://ncep.amnh.org.‎

Phillips, S. J., Anderson, R. P. and Schapired, R. E., 2006. Maximum entropy modeling of ‎species geographic distributions. Ecological Modelling 190: 231–259.‎

Phillips, S. J., Dudik, M. and Schapire, R. E., 2004. A maximum entropy approach to species ‎distribution modeling. Proceedings of the Twenty-First International Conference on Machine ‎Learning, Alberta, Canada.‎

Reynolds-Hogland, M. J. and Mitchell, M. S., 2007. Effects of roads on habitat quality for bears ‎in the southern Appalachians: a long-term study. Journal of Mammalogy 88(4): 1050-1061.‎

Rood, E., Ganie, A. A. and Nijman, V., 2010. Using presence-only modelling to predict Asian ‎elephant habitat use in a tropical forest landscape: implications for conservation. Diversity and ‎Distributions 16(6): 975-984.‎

Sarhangzadeh, J., Yavari, A. R., Hemami, M. R., Jafari, H. R. and Shams-Esfandabad, B., 2013. ‎Habitat suitability modeling for wild goat (Capra aegagrus) in a mountainous arid area, central ‎Iran. Caspian Journal of Environmental Science 11(1): 41-51.‎

Seoane, J., Viñuela, J., Dıaz-Delgado, R. and Bustamante, J., 2003. The effects of land use and ‎climate on red kite distribution in the Iberian peninsula. Biological Conservation 111(3): 401-‎‎414.‎

Stabach, J. A., Laporte, N. and Olupot, W., 2009. Modeling habitat suitability for Grey ‎Crowned-cranes (Balearica regulorum gibbericeps) throughout Uganda. International Journal of ‎Biodiversity and Conservation 1(5): 177-186.‎

Tittensor, D. P., Baco, A. R., Brewin, P. E., Clark, M. R., Consalvey, M., Hall-Spencer, J., ‎Rowden, A. A., Schlacher, T., Stocks, K. I. and Rogers, A. D., 2009. Predicting global habitat ‎suitability for stony corals on seamounts. Journal of Biogeography 36(6): 1111-1128.‎

Wang, X., Huang, X., Jiang, L. and Qiao, G., 2010. Predicting potential distribution of chestnut ‎phylloxerid (Hemiptera: Phylloxeridae) based on GARP and Maxent ecological niche models. ‎Journal of Applied Entomology 134(1): 45-54.‎

Wisz, M. S., Hijmans, R. J., Li, J., Peterson, A. T., Graham, C. H. and Guisan, A., 2008. Effects ‎of sample size on the performance of species distribution models. Diversity and Distributions ‎‎14: 763-773.‎

Yarrow, G. 2009. Gray squirrel biology & management, Fact sheet 13, Department of Forestry ‎& Natural Resources, Clemson University ‎

Yigit, N., Krystufek, B., Sozen, M., Bukhnikashvili, A. and Shenbrot, G. (2012). "Sciurus ‎anomalus. In: IUCN 2008. IUCN Red List of Threatened Species." from ‎http://www.iucnredlist.org/details/20000/0.‎

Ziaie, H., 2009. A field guide to the mammals of Iran. Tehran, Iran, Iranian Wildlife Center.‎




How to Cite

Khalili, F., Sadeghi, M., & Malekian, M. (2018). Habitat suitability modelling of Persian squirrel (Sciurus anomalus) in Zagros forests, western Iran. Journal of Wildlife and Biodiversity, 2(2), 56–64. https://doi.org/10.22120/jwb.2018.85771.1025