Habitat Suitability Mapping of Anatololacerta danfordi (Günter, 1876) in Isparta-Sütçüler District

Öz

Anatololacerta danfordi (Günter, 1876) is an endemic lizard species of the Lacertidae family in Turkey herpetofauna. This lizard species is spreading in the Taurus Mountains and in the appropriate habitats around it. This study was carried out with the aim of determining and mapping suitable habitats for the target species with Maximum Entropy method in Sütçüler (Isparta) region in Western Mediterranean. As a result of the field work between May-October of 2014, 33 present data of this species were obtained. Relationships between the 21 environmental variables and present data of target species, which do not correlate with each other, such as bio climate variables, vegetation indices derived from satellite data or digitized baseline maps, are modeled and mapped by MaxEnt software. According to the habitat suitability model of Anatololacerta danfordi (training data set AUC: 0.916, test data set AUC: 0.898); bedrock, stream density, slope, ruggedness, landform index, radiation index, and land cover/use classes have been the limiting factors in the distribution of Anatololacerta danfordi.

Anahtar Kelimeler

• Anatololacerta danfordi,Endemic,Sütçüler district,Lizard,MaxEnt

Isparta-Sütçüler Yöresinde Anatololacerta danfordi (Günter, 1876)’nin Habitat Uygunluk Haritalaması

Öz

Anatololacerta danfordi (Günter, 1876) Türkiye herpetofaunasında Lacertidae familyasına ait endemik bir kertenkele türüdür. Bu tür Toros Dağları ve çevresindeki uygun habitatlarda yayılış göstermektedir.  Bu çalışma Batı Akdeniz de yer alan Sütçüler (Isparta) yöresinde Maksimum Entropi yöntemi ile hedef tür için uygun habitatları belirlemek ve haritalandırmak amacı ile gerçekleştirilmiştir. 2014 yılının Mayıs-Ekim ayları arasında gerçekleştirilen arazi çalışması sonucunda sahada türe ait 33 örnek alanda var verisi elde edilmiştir. Bio iklim değişkenleri, uydu verilerinden türetilen bitki indeksleri ve coğrafi bilgi sistemleri kullanılarak üretilen veya sayısallaştırılan altlık haritalar olmak üzere toplamda birbiriyle korelasyon göstermeyen 21 çevresel değişken ile hedef türe ait var verileri arasındaki ilişkiler MaxEnt yazılımı ile modellenmiş ve haritalanmıştır. Anatololacerta danfordi için elde edilen habitat uygunluk modeline göre (eğitim veri seti AUC: 0.916,  test veri seti AUC: 0.898) türünün dağılımını etkileyen çevresel değişkenlerin anakaya, dere yoğunluğu, eğim, engebelilik, arazi yüzü şekli, radyasyon indeksi ve arazi örtü/kullanım sınıfları olduğu belirlenmiştir. 

Anahtar Kelimeler

• Anatololacerta danfordi,Endemik,Sütçüler yöresi,Kertenkele,MaxEnt

Kaynakça

1. Arnold, E.N., Arribas, O., Carranza, S., 2007. Systematics of the Palaearctic and Oriental lizard tribe Lacertini (Squamata: Lacertidae: Lacertinae), with descriptions of eight new genera. Zootaxa 1430. 20-21 p.
2. Baldwin, R.A., 2009. Use of Maximum Entropy Modeling in Wildlife Research. Entropy, 11(4), 854-866.
3. Baran, İ., Ilgaz Ç., Avcı, A., Kumlutaş, Y., Olgun, K., 2012. Türkiye Amfibi ve Sürüngenleri. Tübitak Popüler Bilim Kitapları, 204s., Ankara.
4. Bellati, A., Carranza, S., Garcia-Porta, J., Fasola, M., Sindaco, R., 2015. Cryptic Diversity within the Anatololacerta species complex (Squamata: Lacertidae) in the Anatolian Peninsula: Evidence from a multi-locus approach. Molecular Phylogenetics and Evolution, 82: 219-233.
5. Boubli, J.P., Lima, M.G., 2009. Modeling the geographical distribution and fundamental niches of Cacajao spp. and Chiropotes israelita in Northwestern Amazonia via a Maximum Entropy Algorithm, International Journal of Primatology, 30, 217–228.
6. Clark, J.D., Dunn, J.E., Smith, K.G., 1993. A Multivariate Model of Female Black Bear Habitat Use for A Geographic İnformation System. The Journal of Wildlife Management, 519-526.
7. Corsi, F., Duprè, E., Boitani, L., 1999. A Large‐Scale Model of Wolf Distribution in Italy for Conservation Planning. Conservation Biology, 13(1), 150-159.
8. Çevik, E., Başkale, E., Kaya, U., Turgay, F., 2006. Taxonomic Status of Some Lacerta danfordi (GÜNTHER, 1876) Populations. Russian Journal of Herpetology, Vol. 13, No. 2, pp. 89-92.

9. DeMatteo, K.E., Loiselle, B.A., 2008. New Data on the Status and Distribution of the Bush Dog (Speothos venaticus): Evaluating Its Quality of Protection and Directing Research Efforts, Biological Conservation, 141, 2494–2505.
10. DMİ, 2011. T.C. Orman ve Su İşleri Bakanlığı Devlet Meteoroloji İşleri Genel Müdürlüğü, Türkiye Meteorolojik Veri Arşiv Sistemi (TMVAS). 1974-2011 Yılları Arasında Isparta (Sütçüler) Yöresine Ait Çok Yıllık İklim Verileri, (Sayısal veri), Ankara.
11. Eiselt, J. Schmidtler, J. F. 1987. Der Lacerta danfordi complex. Spixiana, 9: 289-328.
12. Elith J., Graham C.H., Anderson R.P., Dudik M., Ferrier S., Guisan A., Hijmans R.J., Huettmann F., Leathwick J.R., Lehmann A., Li J., Lohmann L.G., Loiselle B.A., Manion G., Moritz C., Nakamura M., Nakazawa Y., Overton J.McC., Peterson A.T., Phillips S.J., Richardson K.S., Scachetti-Pereira R., Schapire R.E., Soberon J., Williams S., Wisz M.S., Zimmermann N.E. 2006, Novel methods improve prediction of species’ distributions from occurrence data. Ecography, 29, 129-151.
13. Elith, J., Phillips, S., Hastie, T., Dudik, M., Chee, Y.E., Yates, C.J., 2011. A Statistical Explanation of MavEnt for Ecologist. A Journal of Conservation Biogeography, 17, 43-57.
14. Güçlü, Ö., Kurtuluş, O., 2008. Present Status of Lacerta danfordi Complex (GUNTHER, 1876) in Southwestern Anatolia, Turkey. Russian Journal of Herpetology, Vol. 15, No. 3, pp. 179-188.
15. Hernandez, P.A., Graham, C.H., Master, L.L., 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.
16. Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G., Jarvis, A., 2005. Very High Resolution İnterpolated Climate Surfaces for Global Land Areas. International Journal of Climatology, 25(15), 1965-1978.
17. Hoenes, B.D., Bender, L.C., 2010. Relative Habitat- and Browse-Use of Native Desert Mule Deer and Exotic Oryx in the Greater San Andres Mountains, New Mexico, Human–Wildlife Interactions, 4(1), 12–24.
18. Jenness, J., 2006. Topographic Position Index (tpi_jen. avx) Extension for ArcView 3. x version 1.2. Jenness Enterprises, Flagstaff, AZ.
19. Mert, A., Şentürk, Ö., Güney, C.O., Akdemir, D., Özkan, K., 2013. Mapping of Some Distal Variables Available for Mapping Habitat Suitabilities of The Species: A Case Study of Buldan District. GeoMed 2013 The 3rd International Geography Symposium, Eds: Atalay, İ., Efe, R., 10-13 June, 2013, Kemer Antalya, pp. 210.
20. MTA, 2011. Maden Tetkik ve Arama Genel Müdürlüğü, http://www.mta.gov.tr, Erişim tarihi:07.02.2015
21. Özkan, K., 2009. Yaban Hayatı Ekolojisi’nde Analitik Değerlendirme Açısından Uygun Envanter Metodu Üzerine Bir Öneri. Süleyman Demirel Üniversitesi, Orman Fakültesi Dergisi Seri: A, Sayı 2, 160-169.
22. Özkan, K., Gülsoy, S., 2009. Effect of Environmental Factors On The Productivity of Crimean Pine (Pinus nigra ssp. pallasiana)’in Sutculer, Turkey. Journal of Environmental Biology, 30(6), 965-970.
23. Pearson, R.G., Raxworthy, C.J., Nakamura, M., Peterson, A.T., 2007, Predicting Species Distributions from Small Numbers of Occurrence Records: A Test CaseUsing Cryptic Geckos in Madagascar, Journal of Biogeography, 34, 102- 117.
24. Phillips, S.J., Anderson, R.P., Schapire, R.E., 2006. Maximum Entropy Modeling of Species Geographic Distributions. Ecological Modelling, 190(3), 231-259.
25. Phillips, S.J., Dudík, M., Schapire, R.E., 2004. A Maximum Entropy Approach To Species Distribution Modeling. Proceedings of The Twenty-First International Conference On Machine Learning, ACM, 83p.
26. Rödder, D., Weinsheimer, F., 2009. Will Future Anthropogenic Climate Change İncrease the Potential Distribution of the Alien İnvasive Cuban treefrog (Anura: Hylidae), Journal of Natural History, 43, 1207–1217.
27. Sargın, S., 2006. Sütçüler’de Kır Yerleşmeleri ve Yerleşme Düzenine Etki Eden Faktörler. Fırat Üniversitesi, Sosyal Bilimler Dergisi, 1(16), 63-88.
28. Sillero, N., Gonçalves-Seco, L., 2014. Spatial Structure Analysis of a Reptile Community With Airborne LiDAR Data. International Journal of Geographical Information Science, Vol. 28, No. 8, 1709–1722.
29. Suárez-Seoane, S., Moren, E.L.G., Prieto, M.B.M., Osborne, P.E., Juana, E., 2008. Maximum Entropy Niche-Based Modelling of Seasonal Changes in Little Bustard (Tetrax tetrax) Distribution, Ecological Modelling, 219, 17–29.
30. Süel, 2014. Isparta-Sütçüler Yöresinde Av Türlerinin Habitat Uygunluk Modellemesi, 2014. SDÜ Fen Bilimleri Enstitüsü Orman Mühendisliği Anabilim Dalı, 151s., Isparta.
31. Thorn, J. S., Nijman, V., Smith, D., Nekaris, K. A. I., 2009. Ecological Niche Modelling as a Technique for Assessing Threats and Setting Conservation Priorities for Asian Slow Lorises (Primates: Nycticebus), Diversity & Distributions 15(2): 289-298.
32. Wisz, M.S., Hijmans, R., Li, J., Peterson, A.T., Graham, C., Guisan, A., 2008. Effects of Sample Size on the Performance of Species Distribution Models. Diversity and Distributions, 14(5),763-773.
33. Yost, A.C., Petersen, S.L., 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(6), 375-386.