مدل¬سازی توزیع جغرافیایی و مطلوبیت زیستگاه جربیل بزرگ (Rhombomys opimus) در استان گلستان با استفاده از مدل بیشینه آنتروپی
محورهای موضوعی : اکوسیستم ها
محسن احمدپور
1
(
استادیار گروه علوم محیط‌زیست، دانشکده علوم دریایی و محیطی، دانشگاه مازندران، بابلسر، ایران. *(مسول مکاتبات)
)
حسین وارسته مرادی
2
(
دانشیار گروه محیط زیست، دانشکده شیلات و محیط زیست، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان، ایران.
)
حمید رضا رضایی
3
(
دانشیار گروه محیط زیست، دانشکده شیلات و محیط زیست، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان، ایران.
)
محمدعلی عشاقی
4
(
استاد گروه حشره‌شناسی پزشکی و مبارزه با ناقلین، دانشکده بهداشت، دانشگاه علوم پزشکی تهران، تهران، ایران.
)
اباصلت حسین زاده کلاگر
5
(
استاد گروه زیست‌شناسی سلولی و مولکولی، دانشکده علوم پایه، دانشگاه مازندران، بابلسر، ایران.
)
کلید واژه: مدل مطلوبیت زیستگاه, MaxEnt, جربیل بزرگ, متغیرهای محیط‌زیستی.,
چکیده مقاله :
زمینه و هدف: امروزه مدل¬سازی توزیع جغرافیایی يک گونه به روش بیشینه آنتروپی با استفاده از اطلاعات مکانی حاصل از سنجش از دور، سامانه اطلاعات جغرافیایی و تکنیک¬های آماری سهم بسیار زیادی در مدیریت حفاظت گونه¬ها دارد. هدف این مطالعه، ارزیابی اثرات متغیرهای محیط‌زیستی بر توزیع و مطلوبیت زیستگاه جربیل بزرگ (Rhombomys opimus) و پیش¬بینی زیستگاه آن در استان گلستان است. روش بررسی: در این تحقیق، 272 نقطه حضور جربیل بزرگ و 13 متغیر محیط‌زیستی به عنوان متغیرهای مستقل مورد انتخاب قرار گرفتند. سپس با استفاده از نرم‌افزار مکسنت، مدل‌سازی مطلوبیت زیستگاه و توزیع جغرافیایی گونه با استفاده از این نقاط حضور و متغیرها به روش بیشینه آنتروپی، انجام شد. یافته¬ها: نتايج نشان داد برخی از متغیرهای محیطی، از جمله متغیرهای ارتفاع، شاخص نرمال شده تفاوت پوشش گياهی (NDVI)، تیپ خاک و اقلیم بیشترین اثر را در توزیع جغرافیایی و مطلوبیت زیستگاه گونه در مناطق مورد مطالعه داشته¬اند. در حالی که متغیر شیب کمترین اثر را نسبت به سایر متغیرها دارا بود. بحث و نتیجه¬گیری: براساس مدل¬سازی انجام شده در اين تحقيق، زیستگاه جربیل بزرگ به صورت پیوسته است. به طوري¬که حدود 1/10 درصد از سطح استان گلستان به عنوان زیستگاه مطلوب جربیل بزرگ پيش¬بينی شده¬است.
Background and Objective: Today, the geographical distribution of a species based on maximum entropy using spatial data from geographical information system, remote sensing data and statistical techniques have a great contribution on conservation management of species. The aim of this study is evaluate the effects of environmental variable on distribution and habitat suitability of great gerbil (Rhombomys opimus) and predicting its habitat in Golestan province, Iran. Material and Methodology: For this purpose, 272 presence-only data and 13 environment variables as independent variables were selected for this species. Then, geographic distribution and habitat suitability modeling were performed by maximum entropy approach in MaxEnt software, using to these presence data and variables. Findings: Our results showed that, some of the habitat variables including: altitude, NDVI, soil type and climate had the greatest plays for habitat suitability and geographical distribution of R. opimus in this area. While that, aspect had less effects than other variables. Discussion and conclusion: Based on our findings, habitats of R. opimus was continues and about 10.1% of Golestan province pereidicted as a suitable habitat for the great gerbil.
1. Riva, F. and Fahrig, L., 2022. Landscape-scale habitat fragmentation is positively related to biodiversity, despite patch-scale ecosystem decay. Ecology Letters. Vol. 26, No. 2, pp:268-277.
2. Mancini, G., Benítez-López, A., Di Marco, M., Pacifici, M., Rondinini, C. and Santini, L., 2023. Synergistic effects of habitat fragmentation and hunting on the extinction risk of neotropical primates. Biodiversity and Conservation. pp: 1-15. https://doi.org/10.1007/s10531-023-02623-w
3. Heinrichs, J.A., Bender, D.J., Gummerb, D.L. and Schumaker, N.H., 2010. Assessing critical habitat: Evaluating the relative contribution of habitats to population persistence. Biological Conservation. Vol. 143, pp: 2229-2237.
4. Margules, C.R. and Pressey, R.L., 2000. Systematic conservation planning. Nature. Vol. 405, pp: 243-253.
5. Ortega-Huerta, M.A. and Peterson, A.T., 2004. Modelling spatial patterns of biodiversity for conservation prioritization in North-eastern Mexico. Diversity and Distributions. Vol. 10, pp: 39-54.
6. Sánchez-Cordero, V., Cirelli, V., Munguía, M. and Sarkar, S., 2005. Place prioritization for biodiversity content using species ecological niche modeling. Biodiversity Information. Vol. 2, pp: 11-23.
7. Graham, C.H., Ferrier, S., Huettman, F., Moritz, C. and Peterson, A.T., 2004. New developments in museum-based informatics and application in biodiversity analysis. Trends in Ecology and Evolution. Vol. 19, pp: 497-503.
8. Zaniewski, A.E., Lehmann, A. and Overton, J.M., 2002. Predicting species spatial distributions using presence-only data: a case study of native New Zealand ferns. Ecological Modelling. Vol. 157, pp: 261–280.
9. Elith, J., Graham, C.H., Anderson, R.P., Dudík, M., Ferrier, S., Guisan, A., Hijmans, R.J., Huettmann, F., Leathwick, J.R., Leahmann., A., Li, J., Lohmann, L.G., Loiselle, B.A., Manion, G., Moritz, C., Nakamura, M., Nakazawa, Y., Overton, J.M., Peterson, A.T., Phillips, S.J., Richardson, K., Scachetti-Pereira, R., Schapire, R.E., Soberón, J., Williams, S., Wisz, M.S. and Zimmermann, N.E., 2006. Novel methods improve prediction of species’ distributions from occurrence data. Ecography. Vol. 29, pp: 129-151.
10. Hirzel, A.H., Helfer, V. and Metral, F., 2001. Assessing habitat-suitability models with a virtual species. Ecological Modelling. Vol. 145, pp: 111-121.
11. Bedia, J., Busqué, J., and Gutiérrez, J.M., 2011. Predicting plant species distribution across an alpine rangeland in northern Spain: a comparison of probabilistic methods. Applied Vegetation Science. Vol. 14, pp : 415-432.
12. Ziaei, H., 2008. A field guide to the mammals of Iran, second ed. Iran Wildlife Center, Tehran, Iran. (In Persian)
13. Doroudgar, A. and Dehghani, R., 2000. A study of wild rodents’ fauna and their biological activities (Cutaneous Leishmaniasis reservoirs) in the desert region of Kashan, 1996. Feyz, Kashan University of Medical Sciences & Health Services. Vol. 15, pp: 56-64.
14. Jafari, R., Mohebali, M., Dehghan Dehnavi, A.R., Soleymani, H., Akhavan, A.A., Hajaran, H., Dehghan Shadkam, A. and Fatahi, J., 2007. Journal of Shahid Sadoughi University of Medical Sciences. Vol. 15, No. 2, pp: 76-83. (In Persian)
15. Ahmadpour, M., Moradi, H.V., Rezaei, H.R., Oshaghi, M.A., Hapeman, P. and Hosseinzadeh Colagar, A., 2020. Genetic diversity and structure of the Great Gerbil, Rhombomys opimus, in Iran (Mammalia: Rodentia). Zoology in the Middle East. Vol. 66, No. 1, pp:1-12.
16. Ahmadpour, M., Shokri, S., Varasteh-Moradi, H., Waltert, M., Khorozyan, I. and Soofi, M., 2021. The occurrence of rare corsac fox (Vulpes corsac) in Iran is mainly determined by prey presence and land use. Journal of Arid Environments. Vol. 189, p:104475.
17. Shar, S., Lkhagvasuren, D. and Molur, S., 2008. Rhombomys opimus. The IUCN red list of threatened species: e.T19686A9003460.
18. Zhao, T.B., Wu, J.P., Zhang, Z.B., Zhang, C.F. and Qi, L., 2001. Preliminary observation on some habits of Rhombomys Opimus. Journal of Inner Mongolia Normal University. Vol. 30, pp: 57-60.
19. Wang, S.B. and Yang, G.Y., 1983. Rodent fauna of Xinjiang. Xinjiang People’s Publishing House, Urumqi. pp: 164-167.
20. Zhang, S.L., Kou, M.J., Bing, J.C., Niu, B. and Wang, Z.Y., 2001. Investigation of forest rodents’ fauna in Gansu Province. Forest pest and disease. Vol. 6, pp: 26-28.
21. Nannizzi, M., 2002. "Rhombomys opimus" (On-line), Animal Diversity Web, Accessed June 16, 2016. See information in: http://animaldiversity.org/accounts/Rhombomys_opimus/.
22. Jiang, H.P., Wu, N. and Yang, W.K., 2007. Effects of Rhombomys opimus on microbial quantity, soil moisture content and soil nutrient content in a desert. Arid Zone Research. Vol. 24, pp: 187-192.
23. Yang, W.K., Jiang, H.P., Wang, X.Q. and Xu, W.X., 2009. Disturbance effects of Rhombomys opinums on desert plant community in Gurbantonggut. Chinese Journal of Ecology. Vol. 28, pp: 2020-2025.
24. Pollitzer, R., 1966. Plague and plague control in the Soviet Union, Bronx, NY: Fordham University.
25. Gage, K.L. and Kosoy, M.Y., 2004. Natural history of plague: perspectives from more than a century of research. Annual Review Entomology. Vol. 50, pp: 505-528.
26. Macdonald, D., 1984. The encyclopedia of mammals, New York: Fact on File Publications.
27. Nowak, R., 1999. Walkers mammals of the world, sixth edition, Baltimore, MD: Johns Hopkins University Press.
28. Mapelli, F.J. and Kittlein, M.J., 2009. Influence of patch and landscape characteristics on the distribution of the subterranean rodent Ctenomys porteousi. Landscape Ecology. Vol. 24, pp: 723-733.
29. Hoshino, B., Ganzorig, s., Sawamukai, M., Kawashima, K., Baba, K., Kai, K. and Nurtazin, S., 2014. The impact of land cover change on patterns of zoogeomorphological influence: Case study of zoogeomorphic activity of Microtus brandti and its role in degradation of Mongolian steppe. IGARSS. Vol. 978, pp: 3518-3521.
30. Bean, W.T., Prugh, L.R., Stafford, R., Butterfield, H.S., Westphal, M. and Brashares, J.S., 2014. Species distribution models of an endangered rodent offer conflicting measures of habitat quality at multiple scales. Journal of Applied Ecology. Vol. 51, pp: 1116-1125.
31. Lay, D.M., 1967. A study of the mammals of Iran resulting from the street expedition of 1962–63. Field Zoology. V. 54, pp: 1-282.
32. Wei, L., Wenxuan, X., Weikang, Y., Cong, G., David, B., Canjun, X., Jie, L., Feng, X. and Honghai, Q., 2012. Food habits of the great gerbil (Rhombomys opimus) in the southern Gurbantunggut Desert, Xinjiang, China. Pakistan Journal of Zoology. Vol. 44, pp: 931-936.
33. Gao, M., Li, Q., Cao, C. and Wang, J., 2014. Spatial distribution and ecological environment analysis of great gerbil in Xinjiang Plague epidemic foci based on remote sensing. IOP Conference Series: Earth and Environmental Science. Vol. 17, pp: 1-6.
34. Siahsarvie, R. and Darvish, J., 2007. Rodents diversity of central desert of Iranian plateau. Hystrix 18 (N. S.), Supplement 1, pp : 168.
35. Misonne, X., 1959. Analysis zoogeographique des mammiferes de l’ Iran. Memoires de l’Institut Royal des Sciences Naturelles de Belgique, Deuxième Série. Vol. 59, pp : 1-157.
36. Golestan province., 2016. Natural geography of the province. See information in: http://golestanp.ir/moarefi.html. (In Persian)
37. Phillips, S.J., Anderson, R.P. and Schapire, R.E., 2006. Maximum entropy modeling of species geographic distributions. Ecological Modeling Vol. 190, pp: 231-259.
38. Stevens, D.L. and Olsen A. R., 2004. Spatially Balanced Sampling of Natural Resources. Journal of the American Statistical Association. Vol. 465, pp: 262-278.
39. Scott, D.A., 2007. A review of the status of the breeding waterbirds in Iran in the 1970s. Podoces. Vol. 2, pp: 1-21.
40. Rothschild, V.E., 1978. Spatial structure of plague natural focus and methods of its study. Publishing House of Moscow University, Moscow, Russia.
41. Randall, J.A. and Rogovin, K.A. 2002. Variation in and meaning of alarmcalls in a social desert rodent Rhombomys opimus. Ethology. Vol. 108, pp: 513-527.
42. Kearney, M. and Porter, W.P., 2009. Mechanistic niche modelling: combining physiological and spatial data to predict species’ ranges. Ecology Letters. Vol. 12, pp: 334-350.
43. Khaleghizadeh, A. and Javidkar, M., 2007. Past and present population and rodent diet of the Lesser Kestrel (Falco Naumanni) in northern Iran. Falco. Vol. 29, pp: 12-16.
44. Parr, S., Collin, P., Silk, S., Wilbraham, J., Williams, N.P. and Yarar, M., 1995. A baseline survey of Lesser Kestrels Falco naumanni in central Turkey. Bilogical Conservation. Vol. 72, pp : 45-53.
45. Giovanelli, J.G.R., De Siqueira, M.F., Haddad, C.F. B. and Alexandrino, J., 2010. Modeling a spatially restricted distribution in the Neotropics: how the size of calibration area affects the performance of five presence-only methods, Ecological Modelling. Vol. 221, pp: 215-224.
46. Soofi, M., Ghoddousi, A., Zeppenfeld, T., Shokri, S., Soufi, M., Egli, L., Jafari, A., Ahmadpour, M., Qashqaei, A., Ghadirian, T. and Filla, M., 2019. Assessing the relationship between illegal hunting of ungulates, wild prey occurrence and livestock depredation rate by large carnivores. Journal of Applied Ecology. Vol. 56, No. 2, pp: 365-374.
47. Molur, S., Srinivasulu, C., Srinivasulu, B., Walker, S., Nameer, P.O. and Ravikumar, L., 2005. Status of non-volant small mammals. Conservation Assessment and Manage ment Plan (CAMP) Workshop Report, Coimbatore, India.