سطح مطلوبیت و اثر عوامل محیطی بر انتخاب زیستگاه خرس قهوه‌ای (Ursus arctos) در ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه علوم و مهندسی محیط زیست ، دانشکده محیط زیست ، سازما ن حفاظت محیط زیست، کرج، ایرا ن

2 گروه محیط زیست طبیعی و تنوع زیستی، دانشکده محیط زیست، سازمان حفاظت محیط زیست، کرج، ایرا ن

3 گروه تنوع زیستی و ایمنی زیستی ، پژوهشکده محیط زیست و توسعه پایدار ، سازمان حفاظت محیط زیست ، تهرا ن، ایرا ن

4 گروه محیط زیست دریایی، دانشکده محیط زیست، سازمان حفاظت محیط زیست، کرج، ایرا ن

5 گرو ه ارزیابی و مخاطرات محیط زیست ، پژوهشکده محیط زیست و توسعه پایدار، سازمان حفاظت محیط زیست ، تهرا ن، ایرا ن

چکیده

سابقه و هدف: خرس قهوه‌ای (Ursus arctos) بزرگترین گوشتخوار کشور است که گستره حضور وسیعی داشته اما همانند سایر گوشتخواران بزرگ جثه از فراوانی اندک در سطح گسترده کشور برخوردار است. زیستگاه‌های این گونه در کشور به ویژه در سطح محلی از هم گسیختگی زیادی دارند، از اینرو ارزیابی و شناسایی مناطق بالقوه زیستگاهی دارای مطلوبیت بالاتر، اهمیت زیادی در حفاظت از این گونه دارد. همچنین شناخت اثر عوامل زیست، زمین و اقلیمی بر انتخاب زیستگاه نقش مهمی برای توصیف توزیع گونه داشته و این امکان را فراهم می‌کند تا بتوان بین زیستگاه‌های مختلف از نظر کیفیت تفاوت قایل شد و از آن در مدیریت موثر استفاده کرد.
مواد و روش‌ها: این مطالعه در محدوده شمال غرب ایران در بخش ارسباران انجام شد که بعنوان اقلیم جغرافیایی قفقازی شناخته می‌شود. بخش قفقاز ایران دارای دو جامعه گیاهی مجزای هیرکانی و ارسبارانی است. با انجام بازدیدهای میدانی و گردآوری مشاهدات و گزارشات تائید شده محیط‌بانان و متخصصین، نقاط حضور قطعی گونه شناسایی شد. پس از صحت سنجی نقاط بدست آمده و اعمال بافر، 64 نقطه در مدلسازی استفاده شدند. به منظور ایجاد یک مدل توزیع گونه‎ای کارآمد و شناسایی مناطق مطلوب بالقوه، از شش تکنیک مدل‎سازی در بسته BIOMOD نرم افزار R استفاده شد. در نهایت از خروجی‌های بدست آمده با استفاده از روش ترکیبی Ensemble نقشه مطلوبیت زیستگاه بدست آمد.
نتایج و بحث: نتایج حاصل از خروجی مدل‎ها و رویهم‎گذاری نقشه مناطق تحت مدیریت نشان داد که بیش از دو سوم از این مناطق، برای خرس قهوه‌ای از مطلوبیت برخوردار هستند. متغیرهای درصد شیب و شاخص پوشش گیاهی بیشترین سهم را در تعیین مطلوبیت زیستگاهی داشت به شکلی که شیب متوسط و تراکم پوشش گیاهی بالاتر، مطلوبیت بیشتری را برای گونه به همراه داشت. متغیرهای فاصله از رودخانه اثر کم و فاصله از روستا نقش زیادی در تعیین مطلوبیت زیستگاه خرس قهوه‎ای نداشت. هموار بودن مناطق، با توجه به اینکه دسترسی انسان را افزایش می­ دهد، سطح امنیت و مطلوبیت را کاهش خواهد داد. احتمال حضور گونه در محدوده شیب حدود 10 تا 40 درصد بیشتر بود که با افزایش تراکم پوشش گیاهی نیز مطلوبیت زیستگاه با شیب ملایمی افزایش یافت. همچنین مناطق با بارندگی متوسط و ارتفاع بالاتر در جذب خرس‌ها و افزایش مطلوبیت زیستگاه اهمیت دارند. در مقابل افزایش دما، تراکم جاده‌ها و افزایش فعالیت‌های متمرکز انسانی مطلوبیت زیستگاه را با شیب تقریبا تندی کاهش می‌دهند. 67 درصد از زیستگاه‌های مطلوب گونه داخل محدوده مناطق چهارگانه و 33 درصد آنها خارج از مناطق تحت حفاظت واقع شده‎اند. با وجودی که بخش وسیعی از مناطق تحت حفاظت از مطلوبیت برخوردارند اما تراکم خرس قهوه‌ای در این بخش از کشور بسیار پائین‌تر از سایر گستره حضور گونه در شمال و غرب کشور است. این امر احتمالا به دلیل تلفات زیاد انسانی در این محدوده و اینکه اغلب مناطق آنقدر وسعت و یکپارچگی ندارند که بتوانند تمام گستره خانگی گونه را پوشش دهند، است.
نتیجه­ گیری: یکی از مهمترین استراتژی­ های حفاظتی برای گونه گوشتخوار بزرگ جثه‌ای مانند خرس که رفتار جابجایی بلند، تراکم جمعیت کم، تعارض بالا و نیازمندی‌های حفاظتی وسیع دارد، اتصال زیستگاه­ ها و تعریف مناطق حفاظت شده جدید بینابینی در این منطقه براساس خروجی‌های نقشه‌های مطلوبیت زیستگاه است. همچنین ساماندهی دامداری‌های پراکنده در مناطق مطلوب، اجرای برنامه‌های آموزشی و مهمتر از آن پرداخت خسارات وارد شده از سوی خرس به جوامع روستایی اهمیت زیادی در کاهش تعارض و اقدامات تلافی‌جویانه دارد.

کلیدواژه‌ها

عنوان مقاله [English]

Habitat suitability and effect of environmental parameters on brown bear (Ursus arctos) habitat selection in Iran

نویسندگان [English]

  • Masoumeh Sharifi 1
  • Bagher Nezami Balouchi 2
  • Javad Ramezani 3
  • Behzad Rayegani 4
  • Ali Jahani 5
1 Department of Environmental Science and Engineering, Faculty of Environment, Department of Environment, Karaj, Iran
2 Department of Natural Environment and Biodiversity, Faculty of Environment, Karaj, Iran
3 Department of Biodiversity and Department of Biodiversity and Biosafety, Research Center for Environment and Sustainable Development,, Department of Environment, Tehran, Iran
4 Department of Marine Science, Faculty of Environment, Karaj, Iran
5 Department of Environmental and Risk Assessment, Research Center for Environment and Sustainable Development, Department of Environment, Tehran, Iran
چکیده [English]

Introduction: The brown bear (Ursus arctos) is the largest carnivore which has a wide range of distribution but like other large carnivores, there are low frequency in the country. Habitats of this species in the country, especially at the local level are very fragmented. Therefore, investigation and recognition of the potentially suitable habitat regions are of great importance in the conservation of this species. Also, identifying the factors affecting the selection of habitat plays an important role in describing species behavior and allows to compare different habitats in terms of their quality and to use it in the effective management. Evaluating the response of models and impacts of the biogeoclimatic factors, on habitat suitability, are the other goals of this study.
Material and methods: This study was performed in the northwestern part of Iran in the Arasbaran ecoregion, which is known as the Caucasian geographical climate. The Caucasus ecoregion part of Iran has two separate plant communities, Hyrcanian and Arasbarani. The definite presence points of this species were identified by conducting field visits and collecting confirmed observations and reports of game wardens and experts and 64 points were employed in modeling after validating the obtained points and applying the buffer. Six modeling techniques were used in the BIOMOD package of software to create an efficient species distribution model and identify potentially suitable regions. Finally, the habitat suitability map was acquired from the resulting outputs using the combined Ensemble method.
Results and discussion: The results from the models’ outputs and overlapping the map of the protected areas indicated that more than two-thirds of these areas are suitable for the brown bears. based on results, the variables of slop percentage and vegetation index involve the largest share in determining habitat desirability, so moderate slop and higher vegetation density will lead to more suitability for the species. In determining the desirability of the habitat of the brown bear, the variable of distance from rivers has less effect, and distance from the village did not play an important role. The flatness of areas, as it increase human access, reduced the level of security and thus reduced the suitability of the habitat of this species. There is more probability of the presence of species in the slope range of 10 to 40% and the suitability of habitat was raised in the moderate slope and increased the vegetation density. Regions with moderate rainfall and higher altitudes also play an important role in attracting bears and increasing habitat suitability. On the other hand, rising temperature, congested roads, and increasingly concentrated human activities reduce habitat desirability with an almost steep trend. 67% of the identified suitable and preferred habitats of the species have been located within the four protected areas category and 33% of them are outside of these areas, which is an acceptable level for conservation. Although a wide range of the protected areas in the study area is suitable for the species, the density of the brown bears in this part of the country is much lower than in the north and west of the country. This is maybe due to the high number of human casualties and damages in these areas and that most areas are not broad and wide enough to cover the entire home range of this species in the northwest. The most common reason for habitat fragmentation is the local road network, dispersion of rural areas and dispersed villages, and scattered individual livestock farming.
Conclusion: One of the most significant conservation strategies for the large carnivorous species, such as the brown bear, with high mobility behavior, low population density, high conflict, and extensive conservation requirements is connectivity between the species habitats by defining new protected areas according to the suitable habitats maps. Also, the most important actions to reduce conflict and retaliatory measures are organizing the scattered livestock farming, implementing the educational programs, and more importantly, compensating the damages caused by bears to rural communities.

کلیدواژه‌ها [English]

  • Species distribution model
  • Caucasian ecoregion Habitat suitability
  • Slope
  • Vegetation density Conservation performance

مراجع

 Asef, M.R. and Muradov, P., 2012. Lepiotaceous fungi (Agaricaceae) in the Iranian part of Caucasia. Turkish Journal of Botany. 36, 289-294.
Ataei, F., Karami, M. and Kaboli, M., 2012. Summer habitat suitability modelling of Brown Bear (Ursus arctos) southern Alborz Protected Area. Iranian Journal of Natural Resources. 65(2), 235-245. (in Persian with English abstract).
Barabanov, A. and Litvinchuk, S., 2015. A new record of the Kurdistan newt (Neurergus derjugini) in Iran and potential distribution modeling for the species. Russian Journal of Herpetology. 22(2),107-115.
Baruch-Mordo, S., Breck, S.W., Wilson, K.R. and Theobald, D.M., 2008. Spatiotemporal distribution of black bear–human conflicts in Colorado, USA. J. Wildl. Manag. 72(8), 1853-1862. https://doi.org/10.2193/2007-442.
Boitani, L. and Powell, R.A., 2012. Carnivore Ecology and Conservation, A Handbook of Techniques. Oxford University Press., USA.
Bojarska, K. and Selva, N., 2012. Spatial patterns in brown bear Ursus arctos diet: the role of geographical and environmental factors. Mammal Review. 42(2), 120-143. https://doi.org/10.1111/j.1365-2907.2011.00192.x.
Breiman, L., 2001. Random forests. Machine Learning. 45(1), 5-32. https://doi.org/10.1023/A:1010933404324.
Breiman, L., Friedman, J., Stone, Ch.J. and Olshen, R.A., 1984. Classification and Regression Trees. Chapman and Hall/CRC.
Calvignac, S., Hughes, S. and Hanni, C., 2009. Genetic diversity of endangered brown bear (Ursus arctos) population at the cross road of Europe, Asia and Africa. Diversity and Distributions. 15, 742-750. https://doi.org/10.1111/j.1472-4642.2009.00586.x.
Can, Ö.E. and Togan, I., 2004. Status and management of brown bears in Turkey. Ursus. 15(1), 48-53. https://doi.org/10.2192/1537-6176(2004)015<0048:SAMOBB>2.0.CO;2.
CITES. 2020. Appendices I, II and III. Available from http://www.cites.org.
DeNormandie, J. and Edwards Jr, T.C., 2002. The umbrella species concept and regional conservation planning in southern California: A comparative study. Conservation Biology. 16(2), 573-586.
Dickman, A.J., Macdonald, E.A. and Macdonald, D.W., 2011. A review of financial instruments to pay for predator conservation and encourage human–carnivore coexistence. PNAS. 108, 13937-13944. https://doi.org/10.1073/pnas.1012972108.
Eklund, A., López-Bao, J.V., Tourani, M., Chapron, G. and Frank, J., 2017. Limited evidence on the effectiveness of interventions to reduce livestock predation by large carnivores. Scientific Reports. 7, 2097. https://doi.org/10.1038/s41598-017-02323-w.
Elith, J., Leathwick, J.R. and Hastie, T., 2008. A working guide to boosted regression trees. Journal of Animal Ecology. 77(4), 802-813. https://doi.org/10.1111/j.1365-2656.2008.01390.x.
Elith, J., Graham, C.H., Anderson, R.P., Dudı´k, 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. Mc, C., Peterson, A.T., Phillips, S.J., Richardson, K.S., Scachetti-Pereira, R., Schapire, R.E., Sobero´n, J., Williams, S., Wisz, M.S. and Zimmermann, N.E., 2006. Novel methods improve prediction of species’ distributions from occurrence data. Ecography. 29, 129-151. https://doi.org/10.1111/j.2006.0906-7590.04596.x.
Falcucci, A., Ciucci, P., Maiorano, L., Gentile, L. and Boitani, L., 2009. Assessing habitat quality for conservation using an integrated occurrence-mortality model. Journal of Applied Ecology. 46, 600-609. https://doi.10.1111/j.1365-2664.2009.01634.x.
Farhadinia, M.S., Ahmadi, M., Sharbafi, E., Khosravi, S., Alinezhad, H. and Macdonald, D.W., 2015. Leveraging trans-boundary conservation partnerships: Persistence of Persian leopard (Panthera pardus saxicolor) in the Iranian Caucasus. Biological Conservation. 191, 770-778. http://dx.doi.org/10.1016/j.biocon.2015.08.027.
Farhadinia, M.S., Moqanaki, E.M. and Ekrami, B., 2019. A Manual on Human-Large Carnivore Conflict Management in Iran. Department of Environment, Tehran, Iran.
Franklin, J., 2010. Mapping Species Distributions: Spatial Inference and Prediction. Cambridge University Press, Cambridge, UK.
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). Iran Biology Journal. 23(2), 215-233. (In Persian with English abstract).
Giovanelli, J., Siqueira, M.F.D., Haddad, C. 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. 221(2), 215-224. http://doi:10.1016/j.ecolmodel.2009.10.009.
Guisan, A. and Zimmermann, N.E., 2000. Predictive habitat distribution models in ecology. Ecological Modelling. 135(2), 147-186. https://doi.org/10.1016/S0304-3800(00)00354-9.
Gutleb, B. and Ziaie, H., 1999. On the distribution and status of the brown bear Ursus arctos and the Asiatic black bear U. thibetanus in Iran. Zoology in the Middle East. 18(1), 5-8. http://doi:10.1080/09397140.1999. 10637777.
Habibzadeh, N. and Ashrafzadeh, M.R., 2018. Habitat suitability and connectivity for an endangered brown bear population in the Iranian Caucasus. Wildlife Research. 45(7), 602-610. http://doi:10.1071/WR17175.
Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P. and Jarvis, A., 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology. 25(15), 1965-1978. http://doi:10.1002/ joc.1276.
Holderegger, R. and Giulio, M.D., 2010. The genetic effects of roads: a review of empirical evidence. Basic and Applied Ecology. 11(6), 522-531. https://doi.org/10.1016/j.baae.2010.06.006.
Hoseinnezhad, Z., Karami, P., Goshtasb, H. and Nezami Balouchi, B., 2021. Spatial Distribution Analysis of index Mammals in the Eshkevarat no hunting area Using the Random Forest Tree Learning Method. Journal of Animal Environment, 13(1), 37-46. (in Persian with English abstract). http://doi:10.22034/aej.2021.132684.
Jowkar, H., Ostrowski, S., Tahbaz, M. and Zahler, P., 2016. The Conservation of Biodiversity in Iran: Threats, Challenges and Hopes. Iranian Studies. 49(6), 1065-1077. http://dx.doi.org/10.1080/00210862.2016.1241602.
Kaboli, M., Aliabadian, M., Tohidifar, M., Hashemi, A. and Roselaar, C.C., 2016. Atlas of Birds of Iran. Department of Environment of Iran, Tehran, Iran.
Karami, M., Ghadirian, T. and Faizolahi, K., 2016. The atlas of the mammals of Iran. Department of the Environment of Iran, Tehran, Iran.
Kouchali, F., Nezami, B., Goshtasb, H., Rayegani, B. and Ramezani, J., 2019. Brown Bear (Ursus arctos) habitat suitability modelling in the Alborz Mountains. International Journal of Environmental Science and Bioengineering. 1, 45-54. https://doi.10.22034/uoe.2019.103620.
Kouchali, F., Nezami Baloochi, B., Goshtasb, H. and Raygani, B., 2018. Identification of the key habitats for the conservation of Brown bear (Ursus arctos) in the northern slopes of Alborz. Journal of Animal Environment. 10(3), 1-8. (in Persian with English abstract).
Madadi, M., Nezami Balouchi, B., Kabli, M., Rezaei, H.R. and Mohammadi, A., 2021. A Survey of the Attitudes of Local Communities of Mazandaran Province towards Brown Bear (Ursus arctos). Journal of Animal Environment. 13(1), 11-18. (in Persian with English abstract). http://doi:10.22034/aej.2021.132597.
Mateo-Sanchez, M.C., Cushman, S.A. and Saura, S., 2014. Scale dependence in habitat selection: the case of the endangered brown bear (Ursus arctos) in the Cantabrian Range (NW Spain). International Journal of Geographical  Information Science 28(8), 1531-1546. https://doi.org/10.1080/13658816.2013.776684.
McCullagh, P. and Nelder, J.A., 2019. Generalized linear models. Taylor francis. New York, Routledge, 2nd Edition. https://doi.org/10.1201/9780203753736.
Mohammadi, A. and Kaboli, M., 2016. Evaluating wildlife–vehicle collision hotspots using kernel-based estimation: a focus on the endangered Asiatic cheetah in central Iran. Human-Wildlife Interaction. 10(1), 13.
Mohammadi, A., Almasieh, K., Nayeri, D., Ataei, F., Khani, A., López‑Bao, J.V., Penteriani, V. and Cushman, S.A., 2021. Identifying priority core habitats and corridors for effective conservation of brown bears in Iran. Scientific Reports. 11(1), 1044. https://doi.org/10.1038/s41598-020-79970-z.
Nezami, B. and Farhadinia, M.S., 2011. Litter Size of Syrian Brown Bear Ursus arctos syriacus in Central Alborz Protected Area, Iran. Ursus. 22(2), 167–171. https://doi.org/10.2192/URSUS-D-10-00026.1.
Ordiza, A., Bischof, R. and Swenson, J.E., 2013. Saving large carnivores, but losing the apex predator? Biological Conservation. 168, 128-133. https://doi.org/10.1016/j.biocon.2013.09.024.
Phillips, S.J., Anderson, R.P. and Schapire, R.E., 2006. Maximum entropy modeling of species geographic distributions. Ecological Modeling. 190(3), 231-259. https://doi.org/10.1016/j.ecolmodel.2005.03.026.
Piédallu, B., Quenette, P.Y., Bombillon, N., Gastineau, A., Miquel, C. and Gimenez, O., 2017. Determinants and patterns of the endangered brown bear Ursus arctos in the French Pyrenees revealed by occupancy modelling. Oryx. 53(2), 334-343. http://doi:10.1017/S0030605317000321.
R Development Core Team, 2014. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. Available online at: http://www.R-project.org/.
Ripple, W.J., Estes, J.A., Beschta, R.L., Wilmers, Ch.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. (New York, N.Y.), 343(6167), 1241484. https://doi.org/10.1126/science.1241484.
Sanderson, E.W., Jaiteh, M., Levy, M.A., Redford, K.H., Wannebo, A.V. and Woolmer, G., 2002. The human footprint and the last of the wild. BioScience. 52(10), 891-904. http://doi:10.1641/0006-3568(2002)052 [0891: THFATL]2.0.CO;2.
Sergio, F., Caro, T., Brown, D., Clucas, B., Hunter, J., Ketchum, J., McHugh, K. and Hiraldo, F., 2008. Top predators as conservation tools: ecological rationale, assumptions, and efficacy. Annual Review of Ecology, Evolution and Systematics. 39, 1-19. https://doi.org/10.1146/annurev.ecolsys.39.110707.173545.
Seryodkin, I.V., Kostyria, L.V., Goodrich, J.M., Miquelle, D.G., Smirnov, E.N., Kerley, L.L., Quigley, H.B. and Hornocker, M.G., 2003. Denning ecology of brown bears and Asiatic black bears in the Russian Far East. Ursus. 14(2), 153-161.
Shaffer, M.J. and Bishop, J.A., 2016. Predicting and preventing elephant poaching incidents through statistical analysis, GIS-based risk analysis, and aerial surveillance flight path modeling. Tropical Conservation Science. 9(1), 525-548. https://doi.org/10.1177/194008291600900127.
Simberloff, D., 1997. Flagships, umbrellas, and keystones: is single-species management passe in the landscape era? Biological Conservation. 83(3), 247-257.
Soofi, M., Qashqaei, A.T., Trei, J.N., Shokri, Sh., Selyari, J., Ghasemi, B., Sepahvand, P., Egli, L., Nezami, B., Zamani, N., Yusefi, Gh.H., Kiabi, B.H., Balkenhol, N., Royle, A., Pavey, Ch.R., Redpath, S.M. and Waltert, M., 2022. A novel application of hierarchical modelling to decouple sampling artifacts from socio-ecological effects on poaching intensity. Biological Conservation. 267, 109488. https://doi.org/10.1016/j.biocon.2022.109488.
Thuiller, W., Lafourcade, B., Engler, R. and Araújo, M.B., 2009. BIOMOD – a platform for ensemble forecasting of species distributions. Ecography. 32(3), 369-373. https://doi.org/10.1111/j.1600-0587.2008.05742.x.
Trisurat, Y., Bhumpakphan, N., Reed, D.H. and Kanchanasaka, B., 2012. Using species distribution modeling to set management priorities for mammals in northern Thailand. Natural Conservation. 20(5), 264-273. https://doi.org/10.1016/j.jnc.2012.05.002.
Vapnik, V., 1995. The nature of statistical learning theory. Springer-Verlag, New York. https://doi.org/10.1007/978-1-4757-2440-0.
Zarei, A.A., Abedi, S., Mahmoodi, M. and Peyrovi Latif, Sh., 2015. Habitat Assessment of Brown Bear (Ursus arctos syriacus) Hibernation Density with use of Generalized Linear Model (GLM) and Geographically Weighted Logistic Regression (GWR) in South of Iran. Practical Ecology. 4(4), 75-85. (in Persian with English abstract).
Zarzo-Arias, A., Penteriani, V., Mar Delgado, M., Peon Torre, P., Garcia- Gonzalez, R., Mateo- Sanchez, M.C., Garcia, P.V. and Dalerum, F., 2019. Identifying potential areas of expansion for the endangered bear (Ursus arctos) population in the Cantabrian Mountains (NW Spain). PLoS ONE. 14(1), e0209972. http://doi:10.1371/journal.pone.0209972.
فصلنامه علوم محیطی
دوره 21، شماره 2
1402
صفحه 49-68

فایل ها

هم رسانی

ارجاع به این مقاله

آمار