• صفحه اصلی
  • مدل‌سازی مطلوبیت زیستگاه‌ خرس‌قهوه‌ای (Ursus arctos syriacus) در حوزه آبخیز ناپشته چای

اشتراک گذاری

آدرس مقاله


کد مقاله : JEST-1706-3706 (R3) بازدید : 157 صفحه: 139 - 152

10.22034/jest.2019.27977.3706

نوع مقاله: پژوهشی

مدل‌سازی مطلوبیت زیستگاه‌ خرس‌قهوه‌ای (Ursus arctos syriacus) در حوزه آبخیز ناپشته چای

محورهای موضوعی : تنوع زیستی

جلیل سرهنگ زاده 1 , بهمن کیانی 2

1 - دانشگاه یزد
2 - دانشیار گروه محیط‌زیست، دانشکده منابع طبیعی، دانشگاه یزد.

تاریخ دریافت : 1397/03/02 تاریخ پذیرش : 1398/06/06 تاریخ انتشار : 1399/05/01

کلید واژه: بیشینه آنتروپی, مطلوبیت زیستگاه, حوزه آبخیز ناپشته چای, خرس‌قهوه‌ای,

چکیده مقاله :

زمینه و هدف: خرس‌قهوه‌ای (Ursusarctossyriacus) با وجودی که در طبقه‌بندی اتحادیه جهانی حفاظت از طبیعت و منابع طبیعی در طبقه کمترین نگرانی قرار دارد، اما جمعیت و دامنه انتشار آن به‌عنوان بزرگ جثه‌ترین گوشت‌خوار کشور، کاهش یافته است. مطالعه حاضر با هدف ارزیابی مطلوبیت زیستگاه و عوامل موثر بر پراکنش خرس‌قهوه‌ای در حوزه آبخیز ناپشته چای انجام گرفت. روش بررسی: به‌منظور مدل‌سازی مطلوبیت زیستگاه خرس‌قهوه‌ای با استفاده از نقاط حضور (از پائیز 1394 تا پائیز 1395)، از روش بیشینه آنتروپی بهره‌گیری شد. لایه‌های اطلاعاتی انتخاب شده به‌عنوان متغیرهای مؤثر بر حضور گونه شامل طبقات درصد شیب، طبقات جهت جغرافیایی، طبقات ارتفاع از سطح دریا، کاربری اراضی، منابع آبی، متغیرهای توسعه انسانی (روستاها و جاده‌ها) و اقلیم هستند. یافته ها: نتایج بررسی نشان داد که حدود 4/24% از وسعت حوزه آبخیز ناپشته چای، زیستگاه مطلوبی برای خرس‌قهوه‌ای است. همچنین براساس نقشه مطلوبیت زیستگاه، خرس‌ ارتفاع 2100-1000 متر از سطح دریا و شیب 10 تا 60% را ترجیح می‌دهد. به‌علاوه متغیرهای وجود پوشش جنگلی متراکم، اراضی زراعی، منابع آب و روستاها و همچنین جهت دامنه‌ و نوع اقلیم از عوامل مؤثر بر حضور این گونه می‌باشند. بحث و نتیجه گیری: ارزیابی مدل با سطح زیر منحنی ROC برابر 970/0، نشان‌دهنده قدرت تشخیص بسیار عالی می‌باشد. زیستگاه‌های مطلوب یک‌پارچه خرس‌قهوه‌ای در مناطق مکیدی، اسکلو، ناپشته و بالاسنگ قرار دارند. جلوگیری از توسعه گردشگری در محدوده زیستگاه‌های مطلوب خرس‌قهوه‌ای و انجام مطالعات تکمیلی برای تعیین کریدورها و جابجایی خرس‌قهوه‌ای به خارج از منطقه از پیشنهادهای این پژوهش است.

چکیده انگلیسی:

Background and Objective: Brown bear (Ursus Arctos) is classified as a Least Concern (LC) species of the International Union for Conservation of Nature (IUCN), but its population and distribution have decreased during last decades. This study was carried out to assess the habitat suitability for Brown bear and the effective factors affecting its distribution in Naposhteh-Chai watershed. Method: Maximum Entropy (MaxEnt) approach available in MaxEnt software was used for the habitat suitability modeling of this species from autumn 2015 to autumn 2016. Information layers determined as affecting variables on this species include the slope, aspect, elevation, land use, water resources, human development variables (villages and roads) and climate. Findings: Results showed that 24.4 percent of Naposhteh-Chai watershed were suitable for Brown bear. Based on habitat suitability map, Brown bear preferred elevation range of 1000 to 2100 meters and slope of 10 to 60 percent. Furthermore, existing of densed forests, farmlands, water sources, villages and also aspect and climate, are important factors in the presence of this species. Discussion and Conclusion: Results of model evaluation using the area under the curve (ROC= 0.970) showed that prediction of this model are much more accurate than random conditions. Brown bear suitable integrated habitats, are located in Makidi, Oskolu, Naposhteh and Bala Sang areas. Prevention of tourism development in the suitable habitats of Brown bear, and, determination of corridors and movement routs of the species outside of the Naposhteh-Chai watershed in future studies were suggested in the route of this research.

منابع و مأخذ:


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    38.

 

 
 

 
 

 

 

 

 

 

 

_||_

  1. Ziaie, H. 2008. A field guide to the mammals of Iran. Tehran: Department of the Environment. (In Persian).
    2.
  2. IUCN. 2017. The IUCN Red List of Threatened Species. Version 2017.1. <www.iucnredlist.org>. Downloaded on 28 August 2017.
    3.
  3. Imani, J., Kaboli, M., Ahmadi, M., Khosravi, R., and Nazarizadeh, A. 2016. Morphometric variation in the skull of Brown Bear in Alborz and Zagros mountains. Journal of Applied Biology, 29(2): 5–22. (In Persian).
    4.
  4. Nawaz, M. A. 2007. Status of the brown bear in Pakistan. Ursus 18 – Suring L.H. and G. Del Frate. 2002. Spatial analysis of locations of brown bears killed in defense of life or property on the Kenai Peninsula, Alaska, USA. Ursus. 13:237- 245.
    5.
  5. McLellan, B.N., Servheen, C., and Huber, D. 2008. Ursus arctos. In: IUCN 2009.
    6.
  6. Gibbs, J.P. 1998. Amphibian movements in response to forest edges, roads, and streambeds in southern New England Journal of Wildlife Management. 62, pp: 584–589.
    7.
  7. Fahrig, L., and Merriam, G. 1985. Habitat patch connectivity and population survival. Ecology 66, pp: 1762–1768.
    8.
  8. Reh, W., and Seitz, A. 1990. The influence of land use on the genetic structure of populations of the common frog (Rana temporaria). Biological Conservation, 54, pp: 239–249.
    9.
  9. Wilson, P.J., and Provan, J. 2003. Effect of habitat fragmentation on levels and patterns of genetic diversity in natural populations of peat moss Polytrichum commone. Proceedings of the Royal Society Series B: Biological Sciences, 270, pp: 881–886.
    10.
  10. Ceballos, G., and Ehrlich, P. R. 2002. Mammal population losses and the extinction crisis. Science 296, pp: 904–907.
    11.
  11. Geoffrey, M., Carter. Eric D Stolen., and David R. Breininger. 2006. A rapid approach to modeling species-habitat relationships. Biological Conservation. Vol. 127, no. 2, pp: 237-244.
    12.
  12. Swanepoel, L. H., Lindesy, P., Somers, M. J., Hoven, W., and Dalerum, W. 2013. Extent and fragmentation of suitable leopard habitat in South Africa. 16, pp: 41-50.
    13.
  13. Ripple, W.J., Estes, J.A., Beschta, R.L., Wilmers, C.C., Ritchie, E.G., Hebblewhite, M., Berger, J., Elmhagen, B., Letnic, M., Nelson, M.P., Schmitz, O.J., Smith, D.W., Wallach, A.D., and Wirsing, A.J. 2014. Status and ecological effects of the world’s largest carnivores. Science 343:151.
    14.
  14. Maiorano, L., Falcucci, A., and Boitani, L. 2006. Gap analysis of terrestrial vertebrates in Italy: priorities for conservation planning in a human dominated landscape. Biol. Conserv. 133, pp: 455-473.
    15.
  15. Rabinowitz, A., and Zeller, K.A. 2010. A range-wide model of landscape connectivity and conservation for the jaguar, Panthera onca. Biol Conserv 143, pp: 939–945.
    16.
  16. Morato, R.G., Ferraz, K.M.P.Md.B., de Paula R.C., and Campos, C.Bd. 2014. Identification of Priority Conservation Areas and Potential Corridors for Jaguars in the Caatinga Biome. Brazil. PLoS One 9, e92950.
    17.
  17. Brito, J.C., Acosta, A.L., Álvares, F., and Cuzin, F. 2009. Biogeography and conservation of taxa from remote regions: An application of ecological-niche based models and GIS to North-African canids. Biological Conservation. 142, pp: 3020-3029.
    18.
  18. Parra-Quijano, M., Iriondo, J.M., and Torres, E. 2012. Improving representativeness of genebank collections through species distribution models, gap analysis and ecogeographical maps. Biodivers Conserv, 21, pp: 79–96.
    19.
  19. Gholamhosseini, A., Esmaeili, H.R., Ahani, H., Teimory, A., Ebrahimi, M., Kami, H.Gh., and Zohrabi, H. 2010. Study of topography and climate effects on brown bear Ursus arctos (Linneaus, 1758): Carnivora, Ursidae distribution in south of Iran with use of Geographic Information System (GIS). Iranian Journal of Biology; 23, 2: 215-233. (In Persian).
    20.
  20. Nezami, B. 2014. Seasonal food habits of brown bear (Ursus arctos syriacus Linnaeus, 1758) in Central Alborz Protected Area. Taxonomy and Biosystematics, 6(19): 36–27. (In Persian).
    21.
  21. Ataie, F., Karami, M., and Kaboli, M. 2009. Summer Habitat Suitability for Brown Bear (Ursus arctos syriacus) in Southern Alborz Protected Area. Natural Environment Journal; 65 (2): 235-245. (In Persian).
    22.
  22. Moradi, H. 2013. Evaluation of Land Use Effects on suitability habitat of Brown Bear in Alborz Maekazi Protected Area. Master Thesis, Isfahan University of Technology, Faculty of Natural Resources. (In Persian).
    23.
  23. Zarei, A.A., Abedi, S., Mahmoudi, M., and Peyravi Lati, Sh. 2016. Assessment of Brown Bear's (Ursus arctos syriacus) Winter Habitat Using Geographically Weighted Regression and Generalized Linear Model in South of Iran. Iranian Journal of Applied Ecology, 4(14): 75–88. (In Persian).
    24.
  24. Hemami, M.R., Esmaeili, S., and Soffianian, A.R. 2015. Predicting the Distribution of Asiatic Cheetah, Persian Leopard and Brown Bear in Response to Environmental factors in Isfahan Province. Iranian Journal of Applied Ecology, 4(13): 51–64. (In Persian).
    25.
  25. Obeidavi, Z., Rangzan, K., Mirzaei, R., and Kabolizade, M. 2017. Habitat Suitability Modelling of Brown Bear (Ursus arctos) in Shimbar Protected Area, Khuzestan Province. Iranian Journal of Applied Ecology, 5(18): 61–72. (In Persian).
    26.
  26. Sarhangzadeh, J., and Makhdoum, M. F. 2003. Land use planning of Arasbaran protected area. Journal of Envronmental studies, 28(30): 31–42. (In Persian).
    27.
  27. Phillips, S.J., Anderson, R.P., and Schapire, R.E. 2006. Maximum entropy modeling of species geographic distributions. Modelling 190, pp: 231-259.
    28.
  28. Bailey, J.A. 1984. Principles of wildlife management. New York, NY: John Wiley and Sons. 373 p.
    29.
  29. Caughley, G. and Sinclair, A.R.E. 1994. Wildlife Ecology and Management. Blackwell Science, Oxford, UK. 334 p.
    30.
  30. Beauvais, G.P., Keinath D.A., Hernandez P., Master L., and Thurston, R. 2006. Element Distribution Modeling. University of Wyoming.42 p.
    31.
  31. Peterson, A. T., Papes, M., and Eaton, M. 2007. Transferability and model evaluation in ecological niche modeling: A comparison of GARP and Maxent. 30, pp: 550-560.
    32.
  32. Phillips, S.J., Dudik, M., Elith, J., Graham, C.H., Lehmann, A., Leathwick, J., and Ferrier, S. 2009. Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. Ecological Applications 19, pp: 181-197.
    33.
  33. Phillipes, S.J., Dudík, M., and Schapire, R.E. 2004. A maximum entropy approach to species distribution modeling. In Proceedings of the 21st International Conference on Machine Learning. ACM Press: New York, NY, USA, pp: 655–662.
    34.
  34. Doco, T. 2007. Modeling of species geographic distribution for assessing present needs for the ecological networks: case study of Fuji region and Tanzawa region, Japan. Degree of Master. International Institue for Geo-Information Science and Earth Observation Enschede. 1-112.
    35.
  35. Phillipes, S. J. 2012. A brief tutorial on Maxent, versions: 3.3.3. Available online: http://www.cs. princeton.edu /~schapire/maxent/.
    36.
  36. Yost, A. C., Petersen, S. L., Gregg, M., and Miller, R. 2008. Predictive modeling and mapping sage grouse (Centrocercus urophasianus) nesting habitat using Maximum Entropy and a long-term dataset from Southern Oregon. Ecol. Inform.3, pp: 375–386.
    37.
  37. Gormley, A., Forsyth, D., Griffioen, P., Lindeman, M., Ramsey, D., Scroggie, M., and Woodford, L. 2011. Using presence-only and presence-absence data to estimate the current and potential distributions of established invasive species. Journal of Applied Ecology, 48, pp: 25–34.
    38.

 

 
 

 
 

 

 

 

 

 

 

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