1400 10 2 36 97

پایش محدوده‌های زوال پوشش گیاهی جنگلی و مرتعی در استان چهارمحال‌وبختیاری با استفاده از تصاویر ماهواره‌ای Monitoring Rangeland and Forest Vegetation Decline Regions in Chaharmahal and Bakhtiari Province, Using Satellite Imagery 1 1 اکوسیستم¬های طبیعی به¬شدت تحت تأثیر فعالیت‌های انسانی و عوامل طبیعی قرار دارند. پژوهش حاضر با هدف بررسی تغییرات کاربری- پوشش اراضی و زوال پوشش گیاهی در استان چهارمحال و بختیاری با استفاده از تصاویر ماهواره‌ای لندست انجام شده است. به این منظور تصاویر سال‌های 1382، 1388 و 1395 تهیه و تصحیحات هندسی، اتمسفری و توپوگرافیک بر روی آنها اعمال شد. نقشه‌های کاربری- پوشش اراضی و محدوده¬¬های زوال با استفاده از روش طبقه‌بندی¬کننده حداکثر احتمال استخراج شد که به¬¬ترتیب دارای صحت کلی و ضریب کاپای بیش از 82 درصد و 0/79 با داده¬های زمینی بودند. نتایج نشان داد که در دوره زمانی مورد مطالعه، سطح مراتع از 358355 هکتار به 174735 هکتار و سطح جنگل‌ها از 357190 هکتار به 343970 هکتار کاهش یافته و محدوده¬¬ای معادل 33937 هکتار از جنگل‌ها و مراتع استان در 23 سال گذشته به پدیده زوال دچار شده است. بـا توجه به یافته¬های تحقیق، یک مدیریت فوری و بهینه در جنگل‌ها و مراتع و پوشش گیاهی در حال زوال منطقه مورد مطالعه توسط سازمان¬های ذی¬ربط لازم و ضروری است. در این راستا، پژوهش حاضر توسعه یک نرم¬افزار ساده، آسان و کاربردی پایش پوشش گیاهی با استفاده از تصاویر ماهواره¬ای را پیشنهاد می¬نماید. 2 Natural ecosystems are highly affected by anthropogenic activities and environmental factors. The aim of this study was to detect land use/cover and vegetation decline in Chaharmahal and Bakhtiari province, using Landsat different satellite imageries. For this purpose, images for 1993, 2009 and 2016 were obtained and the geometric, atmospheric and topographic corrections were applied. Land use/cover maps and vegetation decline regions were extracted, using maximum likelihood classifier with an overall accuracy and Kappa coefficient of 82% and 0.79 respectively. Results showed that the area of rangelands and forests has decreased from 358355 to 174735 ha and from 357190 to 343970 ha, respectively. Results also indicated that around 33937 ha of forests and rangelands have been declined in the last 23 years. According to the findings, an urgent and appropriate management of declining rangelands and forests is necessary across the study area. In this regard, developing a simple and applied vegetation cover monitoring software, based on satellite images, is recommended. 1 15 2021/01/6 1399/10/17 2021/06/16 1400/3/26 لیلا یغمایی L. Yaghmaei دانشگاه صنعتی اصفهان ایران leila.yaghmaie@gmail.com رضا جعفری R. Jafari دانشگاه صنعتی اصفهان ایران reza.jafari@iut.ac.ir سعید سلطانی S. Soltani دانشگاه صنعتی اصفهان ایران ssoltani@iut.ac.ir فاطمه هادیان F. Hadian دانشگاه صنعتی اصفهان ایران hadian.fatemeh@gmail.com Decline of plants Land use change Dam construction Landsat خشکیدگی گیاهان تغییر کاربری اراضی سدسازی لندست 1. Abdalizadeh, Z. and A. Ebrahimi. 2016. Change detection of land cover in recent three decades using RS and GIS in Sabzkouh protected area. Journal of Range and Watershed Management 69(3): 621- 631. (in Farsi)##2. Amini, M. R., S. Shataee Joybari, M. H. Moaieri and H. Ghazanfari. 2009. Deforestation modeling and investigation on related physiographic and human factors using satellite images and GIS (Case study: Armerdeh forests of Baneh). Iranian Journal of Forest and Poplar Research 16(3): 431-443. (in Farsi(##3. Attarod, P., S. M. M. Sadeghi, T. G. Pypker and V. Bayramzadeh. 2017. Oak trees decline; a sign of climate variability impacts in the west of Iran. Caspian Journal of Environmental Sciences 15(4): 373-384.##4. Campbell, J. 2007. Introduction to remote sensing, 4th Edition. Guilford Press, New York.##5. Daneshmandparsa, R., R. Mirzaee and N. Bihamta. 2018. Land cover change detection of Chahar Mahal Bakhtiari province using landscape metrics (1994-2015). Iranian Journal of Applied Ecology 7: 17-28. (in Farsi)##6. Dehdari, S., N. Armand, M. Faraji and F. Hadian. 2018. Land use change detection of 3 and 4 Karun Dams using satellite images. Journal of Range and Watershed Management 71(1): 85-96. (in Farsi)##7. Falhatkar, S., A. Soffianian, S. J. Khajeddin and H. Ziaei. 2009. Isfahan land cover change detection in the past 4 decades using remote sensing. Journal of Science and Technology of Agriculture and Natural Resources, Water and Soil Science 13(47): 381-396. (in Farsi)##8. Farajzadeh, M. and H. Rostamzadeh. 2007. Evaluating large dam effects on the land use change using RS & GIS (Case study: Sattarkhan Dam). Human Sciences MODARES 11(1): 47-66. (in Farsi)##9. Fetroos, M., M. Ferdoosi and H. Mehrpeima. 2012. An examination of energy intensity and urbanization effect on environmental degradation in Iran (A cointegration analysis). Journal of Environmental Studies 36(60): 13- 22. (in Farsi)##10. FRWO. 2018. Introduction to Oak decline in Zagros region. Forest, Range and Watershed Management Organization (FRWO), Ministry of Jihad-e-Agriculture, Tehran, Iran. (in Farsi)##11. Gea-Izquierdo, G., B. Viguera, M. Cabrera and I. Cañellas. 2014. Drought induced decline could portend widespread pine mortality at the xeric ecotone in managed mediterranean pine-oak woodlands. Forest Ecology and Management 320: 70-82.##12. Gheitury, M. 2018. Investigation of oak drying trend in Kermanshah province using remote sensing technique (Case study of Kalah Zard Rural). Agricultural Research and Education Organization (AREO), Research Center of Agriculture and Natural Resources of Kermanshah province, Kermanshah, Iran. (in Farsi).##13. Golmohamadi, F., I. Navroodi, A. Islambonyad and J. Mirzaei. 2017. Effects of some environmental factors on dieback severity of trees in Middle Zagros forests of Iran (Case study: strait Daalaab, Ilam province). Plant Reasearch Journal 30(3): 644-655. (in Farsi)##14. Hadian, F., R. Jafari and H. Bashari. 2014. Land cover/use change detection of Solegan Wetland using remote sensing. International Bulletin of Water Resources and Development 1(2): 36-43. (in Farsi)##15. Hadian, F., R. Jafari, H. Bashari and N. Ramezani. 2013. Investigating the effects of Hanna Dam construction on long-term land use/ cover changes. Iranian Journal of Applied Ecology 2(4): 101-114. (in Farsi)##16. Jafari, R. and L. Bakhshandehmehr. 2016. Quantitative mapping and assessment of environmentally sensitive areas to desertification in central Iran. Land Degradation and Development 27(2): 108-119.##17. Jahanbazi, H. and H. Shirmardi. 2014. Mapping rangeland and forest species in Chaharmahal and Bakhtiari province. Reasearch Center of Agriculture and Natural Resources of Chaharmahal and Bakhtiari province, Iran. (in Farsi)##18. Kumar, S., Shwetank and K. Jain. 2020. A multi-temporal Landsat data analysis for land-use/land-cover change in Haridwar region using remote sensing techniques. Procedia Computer Science 171: 1184-1193.##19. Lu, D., P. Mausel, E. Brondízio and E. Moran. 2004. Change detection techniques. International Journal of Remote Sensing 25(12): 2365-2401.##20. Mas, J. F. 1999. Monitoring land-cover changes: a comparison of change detection techniques. International Journal of Remote Sensing 20(1): 139-152.##21. McCoy, R. M. 2005. Field methods in remote sensing. Guilford Press, New York.##22. Melese, S. 2016. Effect of land use land cover changes on the forest resources of Ethiopia. International Journal of Natural Resource Ecology and Management 1(2): 51-57.##23. Moazam, F., R. Jafari, H. Bashari and M. R. Mosaddeghi. 2020. Grazing gradient detection and assessment in arid rangelands of central Iran using remote sensing and soil-vegetation characteristics. The Rangeland Journal. https://doi.org/10.1071/RJ20076.##24. Moghadam, M. R. 1999. Range and range management. Tehran University Press, Tehran. (in Farsi)##25. New, T. and Z. Xie. 2008. Impacts of large dams on riparian vegetation: applying global experience to the case of China’s Three Gorges Dams. Biodiversity and Conservation 17(13): 3149-3163.##26. Riano, D., E. Chuvieco, J. Salas and I. Aguado. 2003. Assessment of different topographic corrections in Landsat-TM data for mapping vegetation types (2003). IEEE Transactions on Geoscience and Remote Sensing 41(5): 1056-1061.##27. Rostamnia, M. and M. Akhoondzadeh Hanzaei. 2017. Assessment of hazardous delnine of Ilam province forests using Landsat satellite images. Journal of Geomatics Science and Technology 6: 131-144.##28. SCI (Statistical Center of Iran). 2016. Statistics of Year 2016, Chaharmahal and Bakhtiari province. Available online at: https://www.amar.org.ir. Accessed December 2016. (in Farsi)##29. Shiravand, H., S. Khaledi, S. Behzadi and H. Shokri Sanjabi. 2020. Monitoring and assessing the changes in the coverage and decline of Oak forests in Lorestan province using satellite images and BFAST model. Journal of Geographical Sciences 20(57): 265-280. (in Farsi)##30. Soltani, Sh., A. Alesheikh, B. Ghermezcheshmeh and S. Mehri. 2018. An evaluation of potential Oak decline forest of the Zagros using GIS, RS, FAHP methods. Iranian Journal of Ecohydrology 5: 713-725.##31. Storkey, J., S. Meyer, K. S. Still and C. Leuschner. 2012. The impact of agricultural intensification and land-use change on the European arable flora. Proceedings of Biological Sciences 279(1732): 1421-1429.##32. Venegas-González, A., F. R. Juñent, A. G. Gutiérrez and M. T. Filho. 2018. Recent radial growth decline in response to increased drought conditions in the northernmost Nothofagus populations from South America. Forest Ecology and Management 409: 94-104.##33. Wang, X., B. Yang and G. Li. 2020. Drought-induced tree growth decline in the desert margins of Northwestern China. Dendrochronologia 60: 125685.##34. Yaghmaei, L., S. Soltani and M. Khodagholi. 2009. Bioclimatic classification of Isfahan province using multivariate statistical methods. International Journal of Climatology 29(12): 1850-1861.##35. Yaghmaei, L., S. Soltani and R. Jafari. 2020. Spatiotemporal response of rangeland NPP to drought in central Iran based on SPDI index. Contemporary Problems of Ecology 13(6): 694-707.##36.Yaghmaei, L. 2021. Factors affecting Astragalus adscendens and Quercus brantii decline in ##Chahar-mahal & Bakhtiari province. Ph.D. thesis, Department of Natural Resources, Isfahan University of Technology, Isfahan, Iran. (In Farsi)##37. Yaghmaei, L., S. Soltani, M. Khodagholi and R. Saboohi. 2011. Bioclimatic classification of Chahar-Mahal & Bakhtiari province using multivariate statistical methods. Journal of Water and Soil Science 14(54): 53-68.##38. Yi, X.S., G.S. Li and Y. Yin. 2012. The impacts of grassland vegetation degradation on soil hydrological and ecological effects in the source region of the Yellow River- A case study in Junmuchang region of Maqin country. Procedia Environmental Sciences 13: 967-981. ##39. Zekeng, J. C., R. Sebego, W. N. Mphinyane, M. Mpalo, D. Nayak, J. L. Fobane, J. M. Onana, F. P. Funwi and M. M. A. Mbolo. 2019. Land use and land cover changes in Doume Communal Forest in eastern Cameroon: implications for conservation and sustainable management. Modeling Earth Systems and Environment 5(4): 1801-1814.##40. Zhao, Q., S. Liu and S. Dong. 2010. Effect of dam construction on spatial-temporal change of land use: a case study of Manwan, Lancang River, Yunnan, China. Procedia Environmental Sciences 2: 852-858.## ##

مقایسه زی‌توده و اندوخته کربن روی زمینی، لاش‌ریزه و خاک در توده‌های جنگلی سالم و دچار زوال بلوط ایرانی (.Quercus brantii Lindl) در استان چهارمحال‌وبختیاری Comparison of Biomass and Carbon Stock on Above ground, Litter and Soil Between Healthy and declined Stands of Brant's Oak in Chaharmahal and Bakhtiari Province 1 1 در اکوسیستم‌های جنگلی، تولید جنگل، ذخیره و جریان کربن بر مبنای اندازه‌گیری‌های زی‌توده محاسبه می‌شوند. این پژوهش با هدف مقایسه زی‌توده و اندوخته کربن روی زمینی، لاش¬ریزه و خاک در توده‌های جنگلی سالم و دچار زوال بلوط ایرانی در استان چهارمحال¬وبختیاری انجام شد. ابتدا چهار قطعه ‌نمونه یک هکتاری در مناطق شاخص متأثر از پدیده زوال بلوط و مناطق سالم انتخاب شد. سپس اطلاعات کمی تمام درختان موجود اندازه‌گیری شد. برای محاسبه زی‌توده و اندوخته کربن روی ‌زمینی از معادلات آلومتری موجود استفاده شد. در هر قطعه ‌نمونه، 10 قاب نیم مترمربعی انداخته و تمام لاش‌ریزه‌های موجود در آنها جمع‌آوری و وزن تر، خشک و کربن نمونه‌ها اندازه‌گیری شد. برای اندازه‌گیری کربن آلی خاک، در هر قطعه ‌نمونه، 5 نمونه خاک برداشت شد. نتایج نشان داد میانگین زی‌توده روی‌ زمینی در قطعه ‌نمونه‌های شاهد 31/4 و در قطعات متأثر از پدیده زوال 15/8 تن در هکتار است. میانگین اندوخته کربن روی ‌زمینی در قطعات شاهد و دچار زوال به‌ترتیب 15/1 و 7/7 تن در هکتار به‌دست آمد. مقدار اندوخته کربن لاش‌ریزه در قطعات شاهد 1584/1 و در قطعات دچار زوال 1148/6 کیلوگرم در هکتار بود. مقدار اندوخته کربن، نیتروژن، فسفر و درصد رطوبت خاک، تفاوت معنی‌داری را بین قطعات نمونه شاهد و دچار زوال نشان داد. نتایج این تحقیق حاکی از تغییرات قابل¬توجه زی‌توده و اندوخته کربن روی ‌زمینی و خاک در توده‌های جنگلی دچار زوال است که در بلند مدت خسارات جبران¬ناپذیری را به اکوسیستم جنگلی غرب کشور وارد خواهد ساخت. این موضوع لزوم توجه مدیران و تصمیم‌سازان منابع طبیعی کشور را به ارائه راهکارهای مدیریتی برای کنترل و مبارزه با این پدیده گوشزد می‌کند. 2 In forest ecosystems, forest production, storage and carbon flow are calculated based on biomass measurements. The aim of this study was to compare the biomass and carbon stock of the above-ground, litter and soil in the oak decline and control plots in Chaharmahal and Bakhtiari province. Four one-hectare sample plots were selected in the healthy (control) and declined stands of oak. Then quantitative information of all trees were measured. Allometric equations were used to calculate the above-ground biomass and carbon stock. Ten microplots were established in each sample plot and all litters were collected. Wet and dry weights and carbon content of the litter samples were measured. To measure soil organic carbon, five soil samples were taken in each sample plot. The results showed that above-ground biomass in the control and decline sample plots were 31.4 and 15.8 tons/hectare respectively. Also, the average of the above-ground carbon stock in the control and decline plots were 15.1 and 7.7 tons/hectare, respectively. The mean of litter carbon in the control plots was 1584.1 kg/ha and in the decline plots was 1148.6 kg/ha. The amount of carbon, nitrogen, phosphorus and soil moisture content showed a significant difference between the control and decline plots. The results of this study indicated significant changes in biomass, carbon stock and soil in declined stands of oak which may cause irreparable damage to the Zagros forest ecosystem, in the long term. This issue highlights the need for the attention of managers and decision makers of natural resources, regarding the provision of management solutions to control this phenomenon. 17 31 2021/01/62021/02/22 1399/12/4 2021/06/162021/06/16 1400/3/26 یعقوب ایران متش Y. Iranmanesh سازمان تحقیقات، آموزش و ترویج کشاورزی شهرکرد ایران y_Iranmanesh@yahoo.com مهدی پورهاشمی M. Pourhashemi سازمان تحقیقات، آموزش و ترویج کشاورزی تهران ایران doveyse@yahoo.com حسن جهانبازی گوجانی H. Jahanbazi سازمان تحقیقات، آموزش و ترویج کشاورزی شهرکرد ایران jahanbazy_hassan@yahoo.com محمود طالبی M. Talebi سازمان تحقیقات، آموزش و ترویج کشاورزی شهرکرد ایران mahmoodtalebi@yahoo.com Biomass Carbon Decline Chaharmahal and Bakhtiari زی‌توده کربن خشکیدگی چهارمحال‌وبختیاری 1. Bakhtiarvand Bakhtiari, S. 2011. Evaluation of methods for estimating the biomass of coniferous and deciduous trees in Mobarakeh Steel afforestation. MSc. Thesis. Faculty of Natural Resources and Land Sciences, Department of Natural Resources Engineering, Shahrekord University. 111 p.##2. Baldwin, L. and K. R. Richards. 2010. Institutional support for an International Forest Carbon Sequestration Agreement. Harward Project on Climate Agreements, Harvard Kennedy school, 33p.##3. Bigler, C. and T. T. Veblen. 2011. Changes in litter and dead wood loads following tree death beneath subalpine conifer species in northern Colorado. Canadian Journal of Forest Research 41: 331-340.##4. Campioli, M., H. Verbeeck, R. Lemeur and R. Samson. 2008. C allocation among fine roots, above and belowground wood in a deciduous forest and its implication to ecosystem C cycling: a modelling analysis. Biogeosciences Discuss 5: 3781-3823.##5. Chambers, J. Q., J. S. Santos, R. J. Ribeiro and N. Higuchi. 2001. Tree damage, allometric relationships, and above-ground net primary production in central Amazon forest. Forest Ecology and Management 152(1–3): 73-84.##6. Cienciala, E., J. Apltauer, Z. Exnerová and F. Tatarinov. 2008. Biomass functions applicable to oak trees grown in Central-European forestry. Journal of Forest Science 54(3): 109-120.##7. Clark, D. A., S. Brown, D. W. Kicklighter, J. Q. Chambers, , J. R. Tomlison and J. Ni. 2001. Measuring net primary production in forests: concepts and field methods. Ecological Applications 11: 356-370.##8. Dang, D. K. D, A. C. Patterson and L. R. Carrasco. 2019. An analysis of the spatial association between deforestation and agricultural field sizes in the tropics and subtropics. PLoS One 14(1): e0209918. https://doi.org/10.1371/journal.pone.0209918##9. Dinakaran, J. and N. S. R. Krishnayya. 2008. Variation in type of vegetation cover and heterogeneity of soil organic carbon in affecting sink capacity of tropical soils. Current Science 94(9): 1144-1150. (In Farsi)##10. FAO. 2006. Global forest resources assessment 2005: progress towards sustainable forest management. Food and Agriculture Organization of the United Nations, Rome.##11. FAO. 2010. Global forest resources assessment 2010. Food and Agriculture Organisation of the United Nations, Rome.##12. Gower, S. T., O. Krankina, R. J. Olson, M. Apps, S. Linder and C. Wang. 2001. Net primary production and carbon allocation patterns of boreal forest ecosystems. Ecological Applications 11: 1395-1411.##13. Huntington, T. G. 2003. Available water capacity and soil organic matter. pp. 1-5, In: R. Lal (ed.), Encyclopedia of Soil Science. Marcel Dekker, New York. ##14. Houghton, R. A. and C. L. Goodale. 2004. Effects of land-use change on the carbon balance of terrestrial ecosystems. pp. 85-98, In: R. DeFries, G. Asner and R.A. Houghton (Eds.), Ecosystems and land use change. American Geophysical Union, North America.##15. Husch, B., T. W. Beers and J. A. Kershaw. 2003. Forest mensuration, 4th Edition. John Wiley & Sons Inc, USA. 443 p.##16. IPCC. 2003. Good practices guidance for land use, land-use change and forestry. Edited by: Penman, J., M. Gytarsky, T. Hiraishi, T. Krug, D. Kruger, R. Pipatti, L. Buendia, K. Miwa, T. Ngara, K. Tanabe and F. Wagner. IGES, Institute for Global Environmental Strategies, Hayama, Japan, 590p.##17. Jordan, C. M., X. Hu, A. Arvesen, P. Kauppi and F. Cheubini. 2018. Contribution of ferest wood products to megative emissions: historical comparative analysis from 1960 to 2015 in Norway, Sweden and Finland. Carbon balance and management 13: 1-16.18. Iranmanesh, Y. 2013. Assessment on biomass estimation methods and carbon sequestration of Quercus brantii Lindl. in Chaharmahal & Bakhtiari Forests, Ph.D. Thesis. Faculty of Natural Resources, Tarbiat Modares University, Noor. 107 p.##19. Iranmanesh, Y., Kh. Sagheb Talebi, H. Sohrabi, S. Gh. Jalali and S. M. Hosseini. 2014. Biomass and carbon stocks of Brant's oak (Quercus brantii Lindl.) in two vegetation forms in Lordegan, Chaharmahal & Bakhtiari Forests. Iranian Journal of Forest and Poplar Research 22(4):749-762. (In Farsi) ##20. Jordan, C. M, X. Hu, A. Arvesen, P. Kauppi and F. Cherubini. 2018. Contributionof ferest wood products to megative emissions: historical comparative analysis from 1960 to 2015 in Norway, Sweden and Finland. Carbon balance and management 13(12). https://doi.org/10.1186/s13021-018-0101-9##21- Khademi, A., S. Babaei and M. Mataji. 2010. The role of coppice oak stand in carbon storage and CO2 uptake (case study: Khalkhal, Iran). Iranian Journal of Forest and Poplar Research 18(2): 242-252. (In Farsi) ##22. Kimble, J. M., C. W. Rice, D. Reed, S. Mooney, R. F Follett and R. Lal. 2007. Soil carbon management, economic, environmental and societal benefits, 1st Edition. CRC Press, New York. 284 p. ##23. Liu, M. Y., Q. R. Chang, Y. B. Qi, J. Liu and T. Chen. 2014. Aggregation and soil organic carbon fractions under different land uses on the tableland of the Loess Plateau of China. Catena 115: 19-28.##24. MacDicken, K. G. 1997. A guide to monitoring carbon storage in forestry and agroforestry projects. Winrock Internationl Institute for Agricultural Development, Forest Carbon Monitoring Program, USA. 87p.##25. Muukkonen, P. 2006. Forest inventory-based large-scale forest biomass and carbon budget assessment: new enhanced methods and use of remote sensing for verification, Ph.D. Thesis of Geography. University of Helsinki, Faculty of Science. 49 p.##26. Nosrati, K. 2011. The effect of land use and soil erosion on soil organic carbon and nitrogen stock. Environmental Erosion Research (3): 127-140. (In Farsi)##27. Olness, A. and D. Archer. 2005. Effect of organic carbon on available water in soil. Soil Science 170(2): 90-101. ##28. Palik, B. J. and N. Pederson. 1996. Over story mortality and canopy disturbances in longleaf pine ecosystems. Canadian Journal of Forest Research 26: 2035-2047.##29. Parvaneh, E., V. Etemad, M. R. Marvie Mohajer, Gh. Zahedi Amiri and P. Attarod. 2016. The relationships between the rate of oak trees decline and forest types, soil characteristics and topographic conditions in Ghalaje Forests of Kermanshah, west of Iran. Iranian Journal of Forest 8(3): 263-275. (In Farsi)##30. Pato, M., A. Salehi, Q. Zahedi Amiri and A. Banj Shafiei. 2017. Estimating the amount of carbon storage in biomass of different land uses in Northern Zagros Forest. Iranian Journal of Forest 9(2): 159-170. (In Farsi)##31. Pourhashemi, M., M. Zandebasiri and P. Panahi. 2014. Structural characteristics of oak coppice stands of Marivan Forests. Journal of Plant Research 27(5): 766-776. (In Farsi)##32. Pourhashemi, M., H. Jahanbazi Goujani, J. Hoseinzade, S. K. Bordbar, Y. Iranmanesh and Y. Khodakaram. 2016. The history of oak decline in Zagros forests. Iran Nature 2(1): 30-37. (In Farsi)##33. Powers, J., S. Sollins, P. Harmon and J. A. Jones. 1999. Plant-pest interaction in time and space: a Douglas-fir bark beetle outbreak as a case study. Landscape Ecology 14: 105-120.##34. Rajan, K. 2010. Soil organic carbon- the most reliable indicator for monitoring land degradation by soil erosion. Current Science 99: 6-25.##35. Rozas, V. and L. Sampedro. 2013. Soil chemical properties and dieback of Quercus robur in Atlantic wet forests after a weather extreme. Plant and Soil 373: 673-685. ##36. Rouvinen S., T. Kuuluvainen and J. Siitonen. 2002. Tree mortality in a Pinus sylvestris dominated boreal forest landscape in Vienansalo wilderness, eastern Fennoscandia. Silva Fennica 36(1): 127-145.##37. Saglant, B., O. Kucuki, E. Bilgili, D. Durmaz and I. Basal. 2008. Estimating fuel biomass of some shrub species (Maquis) in Turkey. Turkish Journal of Agriculture and Forestry 32: 349-356.##38. Sharma, K., A. Saiki, S. Goswami and M. Borthakur. 2020. Aboveground biomass estimation and carbon stock assessment along a topographical gradient in the forests of Manipur, Northeast India. Arabian Journal of Geosciences 13: 1-16.##39. Siitonen, J. 2002. Tree mortality in a Pinus sylvestris dominated boreal forest landscape in Vienansalo wilderness, eastern Fennoscandia. Silva Fennica 36(1): 127-145.##40. Wang, W. J., H. S. He, M. A. Spetich, S. R. Shifley, F. R. Thompson and J. S. Fraser. 2013. Modeling the effects of harvest alternatives on mitigating oak decline in a central hardwood forest landscape. PLoS ONE 8(6): e66713.##41. West, P. W. 2009. Tree and forest measurement. Springer Publisher, Germany. 190p.##42. Zahedi, Gh. and N. Zargham. 2018. Carbon sequestration in Terrestrial Ecosystems, 2nd Edition. University of Tehran Academic Press, Tehran.##43. Zarafshar, M., M. Negahdarsaber, H. Jahanbazi Gojani, M. Pourhashemi, S. K. Bordbar, M. Matinizedeh and A. Abbasi. 2020. Dieback in pure stands of Brant`s oak (Quercus brantii Lindl.) in southern Zagros forests, Kohmareh Sorkhi region of Fars province. Iranian Journal of Forest 12(2): 291-303. (In Farsi)## ##

تحلیل ساختار انرژی و انتشار گازهای گلخانه‌ای در تولید گردو (مطالعه موردی: منطقه ایلام) Analysis of Energy Structure and Greenhouse Gas Emissions of Walnut Orchards; a Case Study in Ilam Region 1 1 هدف از این مطالعه، مقایسه و تحلیل الگوی مصرف انرژی و انتشار گازهای گلخانه‌ای در اندازه‌های مختلف باغات تولید گردو در منطقه ایلام بود. میانگین کل انرژی مورد نیاز برابر با 65334/82 مگاژول بر هکتار برآورد شد. سوخت دیزل، آب آبیاری و ماشین‌ها به‌ترتیب با 57/4، 12/55 و 10/65 درصد، پرمصرف‌ترین نهاده‌های انرژی در تولید گردو بودند. بازده انرژی 1/05 و بهره‌وری 0/04 کیلوگرم بر مگاژول به‌دست آمد. میزان انتشار گازهای گلخانه‌ای برای تولید گردو برابر با 2496/5 کیلوگرم دی¬اکسیدکربن در هکتار محاسبه شد. سه نهاده سوخت دیزل، کود حیوانی و کود نیتروژن با 73/62، 16/82 و 2/92 درصد، بیشترین آلایندگی محیط¬زیستی را در تولید گردو داشتند. ضرایب رگرسیونی به‌دست آمده از تابع کاب-داگلاس برای نهاده‌های نیروی انسانی، ماشین‌ها، سوخت دیزل و سموم شیمیایی، مثبت و در مورد نهاده‌های کود شیمیایی و آبیاری، منفی هستند. نتایج برآورد اقتصادسنجی و تحلیل حساسیت نهاده‌های تولید گردو نشان داد با افزایش یک مگاژول بر هکتار در انرژی نهاده‌های نیروی انسانی، ماشین‌ها، سوخت دیزل، کود شیمیایی، کود دامی، آبیاری، سموم شیمیایی، الکتریسیته و هرس، عملکرد به‌ترتیب معادل 0/26، 0/03، 0/001، 0/25-، 0/004، 0/15-، 0/36، 2/78 و 0/16 کیلوگرم بر هکتار افزایش می‌یابد. 2 The purpose of this study was to compare and analyze the pattern of energy consumption and greenhouse gases emission in different sizes of walnut orchards in Ilam region. The average of total energy requirement was estimated to be 65334.82 MJ/ha. Diesel fuel, irrigation water and machinery with 57.4, 12.55 and 10.65 percent, respectively, were the most consumed energy inputs in walnut production. Energy efficiency and productivity weres estimated to be 1.05 and 0.04 kg per MJ, respectively. The amount of greenhouse gas emissions for walnut production was calculated as 2496.5 kg of CO2 per hectare. The three inputs of diesel fuel, animal manure and nitrogen fertilizer with 73.62%, 16.82% and 2.92%, had the highest environmental pollution in walnut production. Positive regression coefficients were obtained from the Cobb-Douglas function for human labor inputs, machinery, diesel fuel, chemical pesticides and the regression coefficients of chemical fertilizer and irrigation inputs were negative. The results of econometric estimation and sensitivity analysis of walnut production inputs showed that by increasing one megajoule per hectare in energy inputs of human labor, machinery, diesel fuel, chemical fertilizer, animal manure, irrigation, chemical pesticides, electricity and pruning, yield increases by 26%, 03%, 001%, 004%, 36%, 2.78% and 0.16 kg/ha respectively. 33 50 2021/01/62021/02/222021/06/7 1400/3/17 2021/06/162021/06/162021/08/21 1400/5/30 امیر عزیزپناه َََA. Azizpanah دانشگاه ایلام ایران amirazizpanah@gmail.com رستم فتحی R. Fathi دانشکده مهندسی زراعی و عمران روستایی، دانشگاه علوم کشاورزی و منابع طبیعی خوزستان ایران rostamfathi63@gmail.com Cob Douglas Greenhouse Gases Climate Changes Ilam کاب-داگلاس گازهای گلخانه‌ای تغییرات آب و هوایی ایلام 1. Alam, M. S. and K. K. Islam. 2005. Energy flow in agriculture: Bangladesh. American Journal of Environmental Science 1(3): 213-220.##2. Azizpanaha, A. and V. Mohammadi. 2018. Energy modelling and sensitivity analysis of rice production in Ilam, Iran. Journal of Applied Agriculture and Biotechnology 3(1): 01-13.##3. Banaeian, N. and M. Zangeneh. 2011. Estimating production function of walnut production in Iran using Cobb-Douglas method. Agricultura Tropica et Subtropica 44(4): 189-201.‌##4. Baran, M. F., F. Lule and O. Gökdogan. 2017. Energy input-output analysis of organic grape production: a case study from Adiyaman Province. Erwerbs-Obstbau 59(4): 275-279.‌##5. Bartzas, G., D. Vamvuka and K. Komnitsas. 2017. Comparative life cycle assessment of pistachio, almond and apple production. Information processing in agriculture 4(3): 188-198.‌##6. Buckwell, A., A. Nordang Uhre, A. Williams, J. Polakova, W. Blum, J. Schiefer and W. Haber. 2014. Sustainable intensification of European agriculture. A review sponsored by the RISE Foundation.‌ Center for European Policy Studies (CEPS), Brussels.##7. Cambria, D. and D. Pierangeli. 2012. Application of a life cycle assessment to walnut tree (Juglans regia L.) high quality wood production: a case study in southern Italy. Journal of Cleaner Production 23(1): 37-46.‌##8. Ciacci, L. and F. Passarini. 2020. Life Cycle Assessment (LCA) of environmental and energy systems.‌ Energies 13 (5892): 0-8.##9. Cobbenhagen, A. T. J. R., D. J. Antunes, M. J. G. van de Molengraft and W. P. M. H. Heemels. 2021. Opportunities for control engineering in arable precision agriculture. Annual Reviews in Control 51: 47-55.‌##10. De, D., R. Singh and H. Chandra. 2001. Technological impact on energy consumption in rainfed soybean cultivation in Madhya Pradesh. Applied Energy 70(3): 193-213.‌##11. FAO. 2017. The future of food and agriculture, Trends and challenges. Food and Agriculture Organization of the United Nations, Rome. Available online at: http://www.fao.org/3/a-i6583e.pdf. Accessed 15 February 2019.##12. FAO. 2019. Food and Agriculture Organization. Available online at: http://www.fao.org.##13. Fathi, R., M. A. Asoodar and R. Yeganeh. 2020. The role of different levels of utilization in economic and energy indicators of irrigated wheat production (A case study: Dehloran township). Cereal Research 9(4): 373-384. (In Farsi)##14. Fathi, R., A. Azizpanah and S. Yousefenejad. 2020. Evaluation of economic indices, energy and GHG emissions in watermelon production (Case study: Ilam Province). Journal of Crop Production 13(2): 37-50.‌ (In Farsi)##15. Feyzbakhsh, M. T., P. Alizadeh and F. Sheik. 2018. Energy input and energy output of rained wheat and barley and its implication for global warming: Case of Aqqala in Golestan Province. Iranian Journal of Energy 21(2): 33-50. (In Farsi)##16. Ghasemi-Mobtaker, H., F. Mostashari-Rad, Z. Saber, K. W. Chau and A. Nabavi-Pelesarae. 2020. Application of photovoltaic system to modify energy use, environmental damages and cumulative exergy demand of two irrigation systems-A case study: barley production of Iran. Renewable Energy 160: 1316-1334.‌##17. Gundogmus, E. 2013. Modelling and sensitivity analysis of energy inputs for walnut production. Actual Problems of Economics 2(140): 188-197.##18. Hajkova, D. and J. Hurník. 2007. Cobb-Douglas production function: the case of a converging economy. Czech Journal of Economics and Finance (Finance a uver) 57(9-10): 465-476.‌##19. Hatirli, S. A., B. Ozkan and C. Fert. 2005. An econometric analysis of energy input-output in Turkish agriculture. Renewable and sustainable energy reviews 9(6): 608-623.‌##20. Hosseini-Fashami, F., A. Motevali, A. Nabavi-Pelesaraei, S. J. Hashemi and K. W. Chau. 2019. Energy-Life cycle assessment on applying solar technologies for greenhouse strawberry production. Renewable and Sustainable Energy Reviews 116: 109411.‌##21. Iman Mehr, A. and M. Lashkari. 2017. Economic evaluation of walnut production in Tafresh city of Markazi province. In: 10th National Congress of Biosystems Mechanical Engineering (Agricultural Machinery) and Mechanization of Iran. Mashhad, Ferdowsi University of Mashhad. (in Farsi)##22. Khanali, M., A. Akram, J. Behzadi, F. Mostashari-Rad, Z. Saber, K. W. Chau and A. Nabavi-Pelesaraei. 2021. Multi-objective optimization of energy use and environmental emissions for walnut production using imperialist competitive algorithm. Applied Energy 284: 116342.‌##23. Khoshnevisan, B., Sh. Rafiee, M. Omid and H. Mousazadeh. 2013. Applying data envelopment analysis approach to improve energy efficiency and reduce GHG (greenhouse gas) emission of wheat production. Energy 58: 588-593.##24. Khoshnevisan, B., Sh. Rafiee, M. Omid, M. Yousefi and M. Movahedi. 2013. Modeling of energy consumption and GHG emissions in wheat production in Esfahan province of Iran using artificial neural networks. Energy 52: 333-338##25. Manes, G. S. and S. Singh. 2007. Sustainability of cotton cultivation through optimal use of energy inputs in Punjab. International Environment Journal of Agriculture 86(1): 61- 64.##26. Martinez, M. L., D. O. Labuckas, A. L. Lamarque and D. M. Maestri. 2010. Walnut (Juglans regia L.): genetic resources, chemistry, by‐products. Journal of the Science of Food and Agriculture 90(12): 1959-1967.‌##27. Ministry of Jihad-e-Agriculture of Iran. 2019. Annual Agricultural Statistics. Available online at: www.maj.ir. (In Farsi)##28. Mohammadi, A. and M. Omid. 2010. Economical analysis and relation between energy inputs and yield of greenhouse cucumber production in Iran. Applied Energy 87(1): 191-196.‌##29. Mousavi-Avval, S. H., S. Rafiee, A. Jafari and A. Mohammadi. 2011. Optimization of energy consumption for soybean production using Data Envelopment Analysis (DEA) approach. Applied Energy 88(11): 3765-3772.‌##30. Mousavi-Avval, S. H., Sh. Rafiee, A. Jafari and A. Mohammadi. 2010. Econometric modeling and sensitivity analysis of costs of inputs for sunflower production in Iran. International Journal of Applied Engineering Research 1(4): 759-766.##31. Nikkhah, A., B. Emadi, F. Shabanian and H. Hamzeh-Kalkenari. 2014. Energy sensitivity analysis and greenhouse gas emissions for tea production in Guilan province, Iran. Agroecology 6(3): 622-633.##32. Omid, M., F. Ghojabeige, M. Delshad and H. Ahmadi. 2011. Energy use pattern and benchmarking of selected greenhouses in Iran using data envelopment analysis. Energy Conversion and Management 52(1): 153-162.‌##33. Ozkan, B., H. Akcaoz and C. Fert. 2007. Energy input-output analysis in Turkis agriculture. Renewable Energy 29: 39-51.##34. Pahlavan, R., M. Omid, Sh. Rafiee and S. Mousavi-Avval. 2012. Optimization of energy consumption for rose production in Iran. Energy for Sustainable Development 16(2): 236-241.‌##35. Pishgar-Komleh, Sh., M. Ghahderijani and P. Sefeedpari. 2012. Energy consumption and CO2 emissions analysis of potato production based on different farm size levels in Iran. Journal of Cleaner Production 33: 183-191.##36. Rafiee, Sh., S. Mousavi-Avval and A. Mohammadi. 2010. Modeling and sensitivity analysis of energy inputs for apple production in Iran. Energy 35(8): 3301-3306.‌##37. Salami, P. and H. Ahmadi. 2010. Energy inputs and outputs in a chickpea production system in Kurdistan, Iran. African Crop Science Journal 18(2): 51-57.##38. Samavatean, N., Sh. Rafiee, H. Mobli and A. Mohammadi. 2011. An analysis of energy use and relation between energy inputs and yield, costs and income of garlic production in Iran. Renewable Energy 36(6): 1808-1813.‌##39. Shaghozayi, S. and F. Nadi. 2016. Energy modeling of plum production in Golestan province. Iranian Journal of Biosystems Engineering 47(3): 541-549. (In Farsi)##40. Singh, A., B. Ganapathysubramanian, A. K. Singh and S. Sarkar. 2016. Machine learning for high-throughput stress phenotyping in plants. Trends in plant science 21(2): 110-124.‌##41. Springmann, M., M. Clark, D. Mason-D’Croz, K. Wiebe, B. L. Bodirsky, L. Lassaletta and W. Willett. 2018. Options for keeping the food system within environmental limits. Nature 562(7728): 519-525.‌##42. Tabatabaie, S. M. H., S. Rafiee, A. Keyhani and M. Heidari. 2013. Energy use pattern and sensitivity analysis of energy inputs and input costs for pear production in Iran. Renewable Energy 51: 7-12.‌##43. Taheri-Rad, A., A. Nikkhah, M. Khojastehpour and S. Noroozie. 2015. Assessing the GHG emissions, the energy and economic analysis of cotton production in Golestan province. Agricultural Machinery 5(2): 428-445.##44. Taheri-Rad, A., M. Khojastehpour, A. Rohani, S. Khoramdel and A. Nikkhah. 2017. Energy flow modeling and predicting the yield of Iranian paddy cultivars using artificial neural networks. Energy 135: 405-412.‌##45. Taki, M., Y. Ajabshirchi, H. Mobtaker and R. Abdi. 2013. Energy consumption, input-output relationship and cost analysis for greenhouse productions in Esfahan province of Iran. American Journal of Experimental Agriculture 2(3): 485-501.##46. Yadav, S. K. and G. C. Mishra. 2013. Environmental life cycle assessment framework for Sukker production (raw sugar production). International Journal of Environmental Engineering and Management 4(5): 499-506.‌## ##

تحلیل استراتژیک رویکرد پرداخت بابت خدمات اکوسیستم (PES) به‌منظور کاهش بهره‌‌برداری از مرتع Strategic Analysis of Payments Approach for Ecosystem Services in Order to Balance the Utilization Level in Rangeland Ecosystems 1 1 یکی از راهکارهایی که باعث کاهش بهره¬برداری بی¬رویه از اکوسیستم¬های طبیعی می¬شود ارزش¬گذاری اقتصادی کارکردهای این اکوسیستم¬ها و پرداخت به ارائه¬دهندگان خدمات در ازای کاهش عوامل تخریب است. این رویکرد به¬عنوان پرداخت بابت کالاها و خدمات اکوسیستم شناخته می¬شود. در این تحقیق از تحلیل عوامل استراتژیک و تحلیل SWOT به¬منظور شناسایی نقاط قوت و ضعف و فرصت¬ها و تهدیدهای این رویکرد در مراتع استان چهارمحال¬وبختیاری استفاده شد. با استفاده از پرسش¬نامه و روش دلفی با نظرسنجی از 75 نفر از خبرگان، نسبت به شناسایی عوامل اقدام شد. از طریق تصمیم¬گیری چندمعیاره آنتروپی، عوامل وزن¬دهی شده و اولویت هر عامل تعیین شد. نتایج نشان داد عامل کاهش شدت چرا با اجرای طرح پرداخت، مهم¬ترین نقطه قوت با امتیاز 0/149 و مهم¬ترین نقطه ضعف، عدم نظارت بر ظرفیت مرتع با امتیاز 0/165 می¬باشد. افزایش کارکردهای غیربازاری اکوسیستم مرتع، به¬عنوان مهم¬ترین فرصت با امتیاز 0/145 و عامل ترجیح کارکردهای بازاری بر غیربازاری توسط برنامه¬ریزان، به¬عنوان مهم¬ترین عامل تهدید با امتیاز 0/174 تعیین شد. طرح پرداخت درحالتی¬که مرتع¬داران به¬طور داوطلبانه اقدام به کاهش دام مجاز خود نمایند می¬تواند یک گزینه تکمیلی به¬منظور کاهش شدت چرا باشد. 2 One of the ways to reduce the improper utilization on natural ecosystems is the economic valuation of ecosystem services and payment to the service providers in exchange, to reduce the causes of degradation. This approach is known as“Payment for Ecosystem Services (PES). In this research, the strategic factor analysis approach was employed to identify strengths, weaknesses, opportunities and threats (SWOT) in rangelands of Chaharmahal and Bakhtiari province. Using a questionnaire and Delphi method, through a survey of 75 experts, the factors were identified. Weighted factors and priority of each factor were determined through multi-criteria entropy decision making method. Results showed that the most important strength is “reduction of grazing intensity by the implementation of PES” with a score of 0.149, the most important weakness is “the lack of monitoring and inspection of grazing capacity with a score of 0.165, the most important opportunity is “improving non-market services of rangeland ecosystem” with a score of 0.145 and the most important threat is “giving preference to the market functions over non-market functions by policymakers” with the score of 0.174. The payment scheme can be a complementary option to reduce grazing intensity if rangers voluntarily reduce their livestock. 51 65 2021/01/62021/02/222021/06/72021/04/25 1400/2/5 2021/06/162021/06/162021/08/212021/09/4 1400/6/13 علیمحمد محمدی A. M. Mohamadi دانشگاه صنعتی اصفهان ایران Alimmkh1284@yahoo.com سید علیرضا موسوی S. A. Mousavi دانشگاه صنعتی اصفهان ایران sarmousavi@cc.iut.ac.ir سعید سلطانی S. Soltani Koupaei دانشگاه صنعتی اصفهان ایران ssoltani@cc.iut.ac.ir غلامحسین کیانی Gh. H. Kiani دانشگاه اصفهان ایران gh.kiani@ase.ut.ac.ir Economic Valuing Strategic Factor Analysis Market Functions Grazing Intensity Rangelands of Chaharmahal and Bakhtiari Province ارزش‌گذاری اقتصادی تحلیل عوامل استراتژیک کارکردهای بازاری شدت چرا مراتع چهارمحال‌وبختیاری 1. Aguilar, F. X., E. A. Obeng and Z. Cai. 2018. Water quality improvements elicit consistent willingness-to-pay for the enhancement of forested watershed ecosystem services. Ecosystem Services 30: 158-171.##2. Asgharpour, M. J. 2018. Multiple criteria decision making. University of Tehran Press, Tehran. (In Farsi)##3. Asner, G. P., A. J. Elmore, L. P. Olander, R. E. Martin and A. T. Harris. 2004. Grazing systems, ecosystem responses, and global change. Annual Review of Environment and Resources 29: 261-299. ##4. Braat, L. and R. De Groot. 2012. The ecosystem services agenda: bridging words of natural sciences and economics conservation and development and private policy. Ecosystem Services 1(1): 4-15. ##5. Dawes, R. M. 1964. Social selection based on multidimensional criteria. The Journal of Abnormal and Social Psychology 68(1): 104-109.##6. De Groot, R., S. Alkemade, R. Braat, L. Hein and L. Willemen. 2010. Challenges in integrating the concept of ecosystem services and values in landscape planning, management and decision making. Ecological Complexity 7: 260-272.##7. Cochran, W. G. 1963. Sampling techniques, 2nd Edition. John Wiley and Sons, New York.##8. Engel, S., S. Pagiola and S. Wunder. 2008. Designing payment for environmental services in theory and practice: an overview of the issues. Ecological Economics 65: 663-674.##9. Engel, S. and C. Palmer. 2008. Payments for environmental services as an alternative to logging under weak property rights: the case of Indonesia. Ecological Economics 65(4): 799-809.##10. Engel, S. 2016. The devil in the detail: a practical guide on designing payments for environmental services. International Review of Environmental and Resource Economics 9(1-2): 131-177.##11. Eskandari, N., A. Alizadeh and F. Mahdavi. 2008. Range management policy of Iran. Pouneh Publications, Tehran. (In Farsi)##12. Ghodsipour, H. 2018. Multicriteria decision making. University of Amir Kabir Press, Tehran. (In Farsi)##13. Ghorbani, M. and A. Firouzzare. 2010. Introduction of environmental valuation, 2nd Edition. Ferdowsi University of Mashhad Press, Mashhad. (In Farsi) ##14. Grima, N., S. J. Singh, B. Smetschka and L. Ringhofer. 2016. Payment for Ecosystem Services (PES) in Latin America: analyzing the performance of 40 case studies. Ecosystem Services 17: 24-32.##15. Hanley, N., J. Shogren and B. White. 2019. Introduction to environmental economics. Oxford University Press, Oxford.##16. He, J. and T. Sikor. 2015. Notions of justice in payments for ecosystem services: insights from China's Sloping Land Conversion Program in Yunnan Province. Land Use Policy 43: 207-216.##17. Helmer, O. 1977. Problems in futures research: Delphi and causal cross-impact analysis. Futures 9(1): 17-31.##18. Inspection and Law Office. 2010. Laws collection of Iran natural recourses. Forests, Rangelands and Watershed Organization (FRWO), Ministry of Agriculture, Tehran. (In Farsi)##19. Jack, B. K., C. Kousky and K. R. Sims. 2008. Designing payments for ecosystem services: lessons from previous experience with incentive-based mechanisms. Proceedings of the National Academy of Sciences 105(28): 9465-9470.##20. Kajanus, M., J. Kangas and M. Kurttila. 2004. The use of value focused thinking and the A’WOT hybrid method in tourism management. Tourism management 25(4): 499-506.##21. Kinzig, A. P., C. Perrings, F. S. Chapin, S. Polasky, V. K. Smith, D. Tilman and B. Turner. 2011. Paying for ecosystem services promise and peril. Science 334(6056): 603-604.##22. Kolahi, M. 2021. Natural resources stakeholders. Journal of Water and Sustainable Development 8(1): 19-30. (In Farsi)##23. Kotler, P. 1988. Marketing management: analysis, planning, implementation and control, 6th Edition. Prentice Hall International Edition, Englewood Cliffs.##24. Millennium Ecosystem Assessment. 2005. Strengthening capacity to manage ecosystem sustainability for human well-being; a report of the Millennium Ecosystem Assessment. Available online at: www.millenniumassessment.org. ##25. Muradian, R., M. Arsel, L. Pellegrini, F. Adaman, B. Aguilar, B. Agarwal, E. Corbera, D. Ezzine De Blas, J. Farley, G. Froger and E. Garcia. 2013. Payments for ecosystem services and the fatal attraction of win-win solutions. Conservation letters 6(4): 274-279.##26. Natural Resources Council. 2001. National plan of livestock and rangeland balance of Iran. Forests, Rangelands and Watershed Organization (FRWO), Ministry of Agriculture, Tehran. (In Farsi)##27. Pagiola, S. 2008. Payments for environmental services in Costa Rica. Ecological Economics 65(4): 712-724.##28. Pagiola, S., E. Ramírez, J. Gobbi, C. De Haan, M. Ibrahim, E. Murgueitio and J. P. Ruíz. 2007. Paying for the environmental services of silvopastoral practices in Nicaragua. Ecological Economics 64: 374-385.##29. Pagiola, S. 2005. Assessing the efficiency of payments for environmental services programs: a framework for analysis. World Bank, Washington.##30. Parliament Research Center. 2009. Integarated law of livestock husbandry of Iran. Islamic Parliament of Iran, Tehran. (In Farsi) ##31. Rangeland Affairs Office. 2002. Information and audit of rangelands. Natural Resources and Watershed Management General Office of Chaharmahal & Bakhtiari, Shahrekord. (In Farsi) ##32. Rangeland Affairs Office. 2020. Instruction rethinking of rangelands utilization (technical implementation), Forests, Rangelands and Watershed Organization (FRWO), Ministry of Agriculture, Tehran. (In Farsi)##33. Rangeland Affairs Office. 2017. Contract of range management design, No: 96.1.19972. Forests, Rangelands and Watershed Organization (FRWO), Ministry of Agriculture, Tehran. (In Farsi)##34. Rowe, G. and G. Wright. 1999. The Delphi technique as a forecasting tool: issues and analysis. International journal of forecasting 15(4): 353-375.##5 Salzman, J. 2005. Creating markets for ecosystem services: notes from the field. New York University Law Review 80: 870.##36. Shamekhi, T. 2010. Laws and natural resources management (rangelands and forests). Tehran University Press, Tehran. (In Farsi)##37. Simon, H. A. 1955. A behavioral model of rational choice. The quarterly journal of economics 69(1): 99-118.##38. Suttie, J. M., S. G. Reynolds and C. Batello. 2005. Grasslands of the world, Vol. 34. Food & Agriculture Organization (FAO). Available online at: http://www.fao.org/3/y8344e/y8344e05.htm.##39. Smith, S., P. Rowcroft, M. Everard, L. Couldrick, M. Reed and H. Rogers. 2013. Payments for ecosystem services: a best practice guide. Department for Environment, Food and Rural Affairs, London.##40. Tacconi, L. 2012. Redefining payments for environmental services. Ecological Economics 73: 2936.##41. Watershed Management Assistance. 2004. Survey of watershed management of Karsanak basin. Natural Resources and Watershed Management General Office of Chaharmahal & Bakhtiari, Shahrekord. (In Farsi) ##42. Wheelen, T. L. and J. D. Hunger. 2012. Strategic management and business policy, 5th Edition. Pearson Education, New Jersey.##43. Woudenberg, F. 1991. An evaluation of Delphi. Technological forecasting and social change 40(2):131-150.##44. Wunder, S. 2005. Payment for environmental services: some nuts and bolts. Occasional Paper, No. 42. Center for International Forestry Research, Jakarta, Indonesia.##45. Wunder, S., S. Engel and S. Pagiola. 2008. Taking stock: a comparative analysis of payments for environmental services programs in developed and developing countries. Ecological Economics 65(4): 834-852.##46. Wunder, S. 2015. Revisiting the concept of payments for environmental services. Ecological Economics 117: 234-243.##47. Zakeri, A., S. A. Mousavi and H. Karimzadeh. 2020. Strategies for implementing the payment approach for ecosystem services in rangeland management in North Khorasan province. Rangland 14(2): 325-337. (In Farsi)## ##

کاربرد بوم‌شناسی سیمای منظر در ارزیابی تغییرات مکانی و زمانی مناطق خشک، مطالعه موردی: دشت سیستان Application of Landscape Ecology in Spatio-Temporal Change Detection of Arid Regions, Case Study: Sistan Plain 1 1 افزایش جمعیت و به دنبال آن افزایش نیازهای انسان، تغییرات محیطی گسترده‌ای در اکوسیستم‌های مختلف ایجاد نموده است. بررسی تغییرات به¬منظور مدیریت درخور و پایدار اکوسیستم و حفاظت از ساختار و کارکردهای اکوسیستم¬ها اهمیت دارد. بوم¬شناسی سیمای سرزمین، مفاهیم، تئوری و روش¬هایی را برای ارزیابی و مدیریت سرزمین ارائه می¬کند. در این مطالعه، سنجه¬های سیمای سرزمین برای ارزیابی تغییرات زمانی و مکانی در دشت سیستان به¬کار رفت. سنجه¬های سیمای سرزمین در دو سطح کلاس و منظر با استفاده از نقشه‌های طبقات پوشش اراضی سال¬های 1356، 1379، 1394 و 1399 تهیه شد. بررسی سنجه¬های سیمای سرزمین نشان داد که در سطح کلاس، بیشترین تعداد لکه و تکه¬تکه¬شدن طبقه پوشش گیاهی در سال ۱۳۷۹ و کمترین تعداد لکه پوشش گیاهی در سال ۱۳۵۶ وجود داشته است. طی سال¬های ۱۳۹۴ و ۱۳۹۹ با ورود آب رودخانه¬های هیرمند و فراه¬رود، طبقات مرتبط با آب و در نتیجه پوشش گیاهی از جمله انواع گز، بونی و نی افزایش یافته است. در سال¬های ۱۳۹۴ و ۱۳۹۹، پوشش گیاهی دارای تعداد لکه¬های کمتر و با پیوستگی بیشتری در مقایسه با سال ۱۳۷۹ بوده است. به¬دلیل آب¬گیری محدود تالاب هامون، بیشترین تعداد لکه آب در سال ۱۳۹۴ وجود داشته و در سال ۱۳۵۶ کمترین تعداد لکه طبقه آب وجود داشته است. این مطالعه نشان می¬دهد که بوم¬شناسی سیمای منظر و سنجه¬های آن، به¬خوبی می¬تواند تغییرات را در اکوسیستم‎های مناطق خشک مشخص کند. همچنین این سنجه‎ها می‎توانند تغییرات اکوسیستم را کمی¬سازی کنند که در مدیریت اکوسیستم‎ها کاربرد دارد.افزایش جمعیت و به دنبال آن افزایش نیازهای انسان، تغییرات محیطی گسترده‌ای در اکوسیستم‌های مختلف ایجاد نموده است. بررسی تغییرات به¬منظور مدیریت درخور و پایدار اکوسیستم و حفاظت از ساختار و کارکردهای اکوسیستم¬ها اهمیت دارد. بوم¬شناسی سیمای سرزمین، مفاهیم، تئوری و روش¬هایی را برای ارزیابی و مدیریت سرزمین ارائه می¬کند. در این مطالعه، سنجه¬های سیمای سرزمین برای ارزیابی تغییرات زمانی و مکانی در دشت سیستان به¬کار رفت. سنجه¬های سیمای سرزمین در دو سطح کلاس و منظر با استفاده از نقشه‌های طبقات پوشش اراضی سال¬های 1356، 1379، 1394 و 1399 تهیه شد. بررسی سنجه¬های سیمای سرزمین نشان داد که در سطح کلاس، بیشترین تعداد لکه و تکه¬تکه¬شدن طبقه پوشش گیاهی در سال ۱۳۷۹ و کمترین تعداد لکه پوشش گیاهی در سال ۱۳۵۶ وجود داشته است. طی سال¬های ۱۳۹۴ و ۱۳۹۹ با ورود آب رودخانه¬های هیرمند و فراه¬رود، طبقات مرتبط با آب و در نتیجه پوشش گیاهی از جمله انواع گز، بونی و نی افزایش یافته است. در سال¬های ۱۳۹۴ و ۱۳۹۹، پوشش گیاهی دارای تعداد لکه¬های کمتر و با پیوستگی بیشتری در مقایسه با سال ۱۳۷۹ بوده است. به¬دلیل آب¬گیری محدود تالاب هامون، بیشترین تعداد لکه آب در سال ۱۳۹۴ وجود داشته و در سال ۱۳۵۶ کمترین تعداد لکه طبقه آب وجود داشته است. این مطالعه نشان می¬دهد که بوم¬شناسی سیمای منظر و سنجه¬های آن، به¬خوبی می¬تواند تغییرات را در اکوسیستم‎های مناطق خشک مشخص کند. همچنین این سنجه‎ها می‎توانند تغییرات اکوسیستم را کمی¬سازی کنند که در مدیریت اکوسیستم‎ها کاربرد دارد. 2 Population growth followed by increasing human needs has caused widespread environmental changes in various ecosystems. Change detection is necessary to properly manage the ecosystem and protect the structure and functions of ecosystems. Landscape ecology provides concepts, theories, and methods for assessing and managing lands. In the current study landscape metrics were used to assess spatio-temporal changes in the Sistan Plain. Landscape metrics were created at class and landscape levels. These indices were calculated, using land use/cover maps of 1977, 2000, 2015, and 2021. Results showed that at the class level, the highest number of patches and fragmentation of the vegetation cover was occured in 2000 and the lowest number of vegetation patches was in 1977. With the inflow of water from Helmand and Farahrood rivers in 2015 and 2021, the vegetation cover, comprising a variety of Tamarix sp, Aeluropus sp, and Phragmites sp, has increased. Due to the inundation of Hamoun and Farah rood rivers, the water and vegetation cover has fewer patches with more connectivity. The highest number of patches in the water body class was in 2015, due to the limited inflow from the Hamoun wetland and the lowest number of water body patches was observed in 1977. This study shows that landscape metrics can determine changes in arid ecosystems. Also, these metrics can quantify the changes in ecosystems and be used in ecosystem management of arid lands. 67 81 2021/01/62021/02/222021/06/72021/04/252021/05/5 1400/2/15 2021/06/162021/06/162021/08/212021/09/42021/09/2 1400/6/11 محدثه میر M. Mir دانشگاه زابل ایران MIRMOHADDESEH@GMAIL.COM سعیده ملکی S. Maleki دانشگاه زابل ایران smaleki@uoz.ac.ir وحید راهداری V. Rahdari دانشگاه زابل ایران VAHID_RAHDARY@YAHOO.COM Hamoun wetland Satellite image Landscape indices ecosystem Sistan plain تالاب هامون تصاویر ماهواره‌ای سنجه‌های سیمای سرزمین اکوسیستم دشت سیستان 1. Aslami, F., A. Ghorbani, B. Sobhani and M. Panahandeh. 2015. Comparing artificial neural network, support vector machine and object-based methods in preparation of land use/cover maps using Landsat-8 images. RS & GIS Techniques in Natural Resources 6: 1-14. (In Farsi)##2. Bihamtaye Toosi, N., A. Safaian and S. Fakhran. 2013. Investigation of land cover changes in central region of Esfahan by using landscape metrics. Iranian Journal of Applied Ecology 6: 46-61. ##3. Cheng, G. D., D. N. Xiao and G. X. Wang. 2000. Characteristics and construction of landscape ecology in arid regions. Chinese Geographical Science 10(1): 13-19.‌##4. Cowling, R. M., B. Egoh, A. T. Knight, P. J. OFarrell, B. Reyers, M. Rouget’ll, D. J. Roux, A. Welz and A. Wilhelm-Rechman. 2008. An operational model for mainstreaming ecosystem services for implementation. Proc Natl Acad Sci USA 105(28): 9483-9488.##5. Dahmardeh Ghaleno, M. R. 2016. Optimizing the operation of the Chahnimeh reservoirs in Sistan region using goal programming method, PhD thesis in Natural Resources Engineering- Watershed Management. Gorgan University of Agricultural Sciences and Natural Resources, Gorgan. 217p. (In Farsi)##6. Darvishi, A., S. Fakheran, A. Soffianian and M. Ghorbani. 2012. Quantifying landscape spatial pattern changes in the Caucasian Black Grouse (Tetrao mlokosiewiczi) habitat in Arasbaran biosphere reserve. Iranian journal of applied ecology 2(5): 27-38.##7. Ehsani, A. and M. Shakerian. 2018. Determining the optimal method of land use classification and mapping / land cover by comparing artificial neural network algorithms and support vector machines using satellite data (Case study: Hamoon International Wetland). Environmental Science and Technology 20(14): 193-207.##8. Fathizad, H., A. Nohe Gar, M. Faramarzi and M. Tazeh. 2013. Investigation of land use changes based on analysis of landscape metrics by using of remote sensing and GIS in arid and semi-arid region of Dehloran. Journal of Town and Country Planning 3: 79-99.##9. Fennessy, M. S. and D. Wardrop. 2016. Approaches to assessing the ecological condition of wetlands using soil indicators. In: Wetland soils: genesis, hydrology, landscapes, and classification: Second Edition. CRC Press. pp. 425-445.‌##10. Frankenberg, C. and J. Berry. 2018. Solar induced chlorophyll fluorescence: origins, relation to photosynthesis and retrieval. Reference Module in Earth Systems and Environmental Sciences. Comprehensive Remote Sensing 3: 143-162.##11. Ghosh, A., M. Munshi, G. Areendran and P. K. Joshi,. 2012. Pattern space analysis of landscape metrics for detecting changes in forests of Himalayan foothills. Asian Journal of Geoinformatics 12(1): 1-12.##12. Hosseini Verdi, M., A. Mahini, S. M. Monavari and M. S. Khairkhah Zarkash. 2010. Application of landscape measurements in assessing the cumulative effects of road network on tree cover. Iranian Journal of Natural Environment 65( 2): 139-152. (In Farsi)##13. Haghverdi, F., A. Jahani, L. Zebardast, M. Makhdoom and H. Goshtasb. 2009. Assessing the integrity of protected rangeland habitats using the landscape ecology approach. Journal of Plant Ecology 7(14): 1-20. (In Farsi).##14. Huang, J., T.Z henshun and L. Jie. 2010. Detecting spatiotemporal change of land use and landscape pattern in a coastal gulf region, southeast of China. Environment, Development and Sustainability 12(1): 35-48.##15. Karami, A. and J. Feqhhi. 2011. Quantification of landscape measurements in conservation of sustainable land use pattern (Case study: Kohgiluyeh and Boyer-Ahmad Province). Journal of Environmental Studies 60: 79-88. (In Farsi)##16. Kantakomar, L. N. and P. Neelamsetti. 2015. Multi-temporal land use classification using hybrid approach. The Egyptian Journal of Remote Sensing and Space Science 18(2): 289-295.##17. Mehri, A., A. Mahini, A. Mikaeili, E. Tabrizi, S. H. Mirkarimi and A. Saad-al-Din. 2018. Effects of land use change on the natural structure of Qarasu river basin. Town and Country Planning 10(1): 93-116. (In Farsi)##18. Maleki, S., S. Soltani Koupaei, A. Soffianian, S. Saatchi, S. Pourmanafi and V. Rahdari. 2019. Human and climate effects on the Hamoun wetlands. American Meteorological Society 11(3): 609-612.##19. Maleki, S., A. Soffianian and V. Rahdari. 2010. Investigation of landscape ecological changes in Moteh Wildlife Sanctuary using geographical life systems. Iranian Journal of Natural Resources 4: 373-387.##20. Millennium Ecosystem Assessment. 2005. Ecosystems and human well-being: scenarios. Findings of the Scenarios Working Group, Vol. 2. Island Press. 165p.##21. Masoomi, M. and R. Moshiri. 2014. Using spatial landscape metrics and remote sensing data for temporal-spatial analysis of land cover/use changes in urban, Case study: Ardabil region. Journal of Geographic Space 45: 179-196. ##22. Matsushita, B., Y. Wei, C. Jin, O. Yuyichi and Q. Guoyn. 2007. Sensitivity of the Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) to topographic effects: a case study in high-density Cypress forest. Journal List Sensors (Basel) 7(11): 2636-2651.##23. Maleki, S., A. Soffianian, S. Soltani, S. Pourmanafi and V. Rahdari. 2017. Modeling the suitability of waterfowl habitats and shores of Hamoon Wetland using the maximum entropy model. Scientific Journal of Wetland Ecobiology 11(40): 5-14. (In Farsi)##24. Najafi, A., S. Azizi and M. Mokhtari. 2017. Application of support vector machine in land use classification of Cheshmeh Kileh-Chalkroud area. Journal of Watershed Management Research 15: 92-96. ##25. Nemat Elahi, Sh., S. Fakhran, A. Jafari, T. Raeesi and S. Pourmanafi. 2009. Land planning for conservation and ecological effects of road network in Chaharmahal and Bakhtiari province. Applied Ecology 8(4): 67-81. (In Farsi)##26. Nohegar, A., B. Jaberian Amiri and R. Afrakhteh. 2015. Land use analysis on Guilan central district using landscape ecology approach. Geography and Territorial Spatial Arrangement 15(5): 197-213.##27. OFarrell, P. J., B. Reyers, D. C. Le Maitre, S. J. Milton, B. Egoh, A. Maherry and R. M. Cowling. 2010. Multi-functional landscapes in semiarid environments: implications for biodiversity and ecosystem services. Landscape Ecology 25(8): 1231-1246.‌##28. Pettorelli, N., J. O. Vik, A. Mysterud, J. M. Gaillard, C. J. Tucker and N. C. Stenseth. 2005. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology and Evolution 20(9): 503-510.##29. Rahdari, V., S. Maleki, M. Rahdari, S. Mahmoudi, N. Pormollaei, M. R. Alimoradi, E. Abtin, M. Kadkhodaee and S. Pourmanafi. 2016. Investigate the potential of multi-spectral satellite data for mapping the water depth and the area adjacent to reservoir (Case study: Chah Nimeh reservoirs in Sistan). Iran Water Resources Research 12(3): 130-141. (In Farsi)##30. Ramachandra, T. V., K. Utam and N. V. Joshi. 2012. Landscape dynamics in western Hymalia- Mandhala Watreshed, Himachal Pradesh, India. Asian Journal of Geoinformatics 12(1): 1-9.##31. Rahdari, V., A. Soffianian, S. Pourmanafi and H. Qayyumi Mohammadi. 2018. Investigating the time series OLI multi-spectral sensor data capability with the Step by Step method for producing the major cultivation map (a case study: Chadegan city). Journal of Soil and Water Sciences 22(3): 71-80 (In Farsi) ##32. Riitters, K., J. Wickham, J. K. Costanza and P. Vogt. 2016. A global evaluation of forest interior area dynamics using tree cover data from 2000 to 2012. Landscape Ecology 31: 137-148.##33. Salman Mahiny, A. 2007. Landscape metrics and erosion risk as two classes of quantitative indicators for rapid environmental impact assessment. Agricultural Science and Natural Resources 14: 139-150.##34. Salajegheh, B., S. M. Monavari, A. Karbasi, N. Khorasani and S. M. Shariat. 2014. Analysis of land degradation using the detection of changes and measures of land appearance (case study of Kish Island). Special Issue of Environmental Research 99: 1-110. (In Farsi)##35. Salman Mahini, A. 2007. Landscape and erosion criteria as two quantitative index categories for rapid evaluation of the effects of development projects. Journal of Agricultural Sciences and Natural Resources 4(1): 139-149. (In Farsi)##36. Samuel, C., M. Kevin and N. Maile. 2008. Parsimony in landscape metrics: Strength, universality, and consistency. Ecological Indicators 8: 691-703.##37. Sefidiyan, S., A. Mahini, H. Mirkarimi and N. Hasanabasi. 2015. Vegetation classification based on wetland index using remote sensing and sampling land (case study: Alagol International Wetland). Quarterly Journal of Wetland Ecology- Islamic Azad University 7(24): 5-22. (In Farsi)##38. Smiraglia, D., T. Ceccarelli, S. Bajocco, L. Perini and L. Salvati. 2015. Unraveling landscape complexity: land use/land cover changes and landscape pattern dynamics (1954–2008) in contrasting peri-urban and agro-forest regions of Northern Italy. Environmental Management 56: 916-932.##39. Sistan and Baluchestan Regional Water Company. 2014. Status report of Sistan and Baluchestan Province. 41p. (In Farsi)##40. Sheikh Goodarzi, M., A. Alizadeh Shabani, S. Mahini and J. Feghhi. 2012. Landscape ecological metrics based investigation of land cover/use changes in Gorganrud watershed. Journal of Natural Environment, Iranian Journal of Natural Resources 64(4): 431-444. (In Farsi)##41. Sepasi, M., H. Darabi and H. Irani Behbahani. 2013. Analysis of landscape of rural-urban Tarasht. First International Conference of Landscape Ecology. Isfahan University of Technology, Isfahan, Iran.##42. Talebi Amiri, S., F. Azari Dehkordi, S. H. Sadeghi and S. R. Soofbaf. 2009. Study on landscape degradation in Neka watershed using landscape metrics. Environmental Sciences 6(3): 133-144.##43. Turner, M. G. 1989. Landscape ecology: the effect of pattern on process. Annual Review of Ecology and Systematics 20: 171-197. ##44. Turner, M. 2005. Landscape ecology: what is the state of the science. Annual Review of Ecology Evolution and Systematics 1502(36): 319-344.##45. Turner, M. G., R. H. Gardner and R. V. O’Neill. 2001. Landscape ecology in theory and practice: pattern and process. Springer Verlag, New York. 331p. ##46. Tolessa, T., F. Senbeta and M. Kidane. 2016. Landscape composition and configuration in the central highlands of Ethiopia. Ecology and Evolution 6(20): 7409-7421.‌##47. Uuemaa, E., U. Mander and R. Marja. 2013. Trends in the use of landscape spatial metrics as landscape indicators: a review. Ecological Indicators 28: 100-106.##48. Veldkamp, A. and E. F. Lambin. 2001. Predicting land use change. Agriculture, Ecosystem and Environment 85: 1-6.## ##

ارزیابی محدوده پراکنش و پیوستگی ساختاری لکه‌های زیستگاهی چهار گونه از گاوسانان (Bovidae) در استان فارس Assessing Distribution Range and Structural Habitat Connectivity of Four Species of Bovidae in Fars Province 1 1 علف¬خواران بزرگ¬جثه، اساس رویکردهای حفاظتی گونه-محور و مکان-محور در کشور هستند. موفقیت این رویکردها منوط به کاهش تهدیدات ژنتیکی ناشی از انزوای گونه‌ها در زیستگاه‌های کلیدی است. در مطالعه حاضر محدوده پراکنش و پیوستگی لکه‌های زیستگاهی در گوسفند وحشی (Ovis gmelini)، بز وحشی (Capra aegagrus)، آهوی ایرانی (Gazella subgutturosa)، و جبیر (Gazella bennettii) با استفاده از الگوریتم حداکثر آنتروپی و مدل پیوستگی مسیرهای حداقل هزینه فاکتوریل نقشه‌سازی شد. نتایج نشان داد اگرچه پراکنش گونه‌ها تحت تأثیر فاکتورهای متفاوتی قرار دارد، مناطق تحت حفاظت، ناهمواری سیمای سرزمین، و علفزارها مهم‌ترین متغیرها در پراکنش گونه‌ها هستند. بسیاری از لکه‌های زیستگاهی در محدوده مناطق تحت حفاظت قرار گرفت که می‌تواند ناشی از مقاومت محیطی زیاد در خارج از مناطق باشد. به¬رغم پیوستگی ساختاری مناسب در برخی از گونه‌ها، قرارگرفتن نسبت زیادی از کریدورهای مهاجرتی در خارج از مناطق تحت حفاظت و ردپای انسان در زیستگاه می‌تواند عملکرد کریدورهای پیش‌بینی¬شده را کاهش دهد. انتخاب زیستگاه‌های کلیدی و کریدورهای مهاجرتی با نرخ جابه‌جایی بالا به¬عنوان مناطق تحت حفاظت مشارکتی نقش مهمی در افزایش کارایی شبکه حفاظتی موجود دارد. نتایج به¬دست آمده نشان می‌دهد که حفاظت از علف¬خواران، نیازمند مدیریت یکپارچه در سطح سیمای سرزمین با هدف برقراری پیوستگی عملکردی بین مناطق است. 2 Large herbivores play an important role in species-based and site-based conservation approaches in the country. The success of these approaches depends on reducing genetic threats posed by isolation of species in their key habitats. In the present study, we assessed structural connectivity for wild sheep (Ovis gmelini), wild goat (Capra aegagrus), goitered gazelle (Gazella subgutturosa), and Indian gazelle (Gazella bennettii), using species distribution algorithms and connectivity models. Our findings showed that while the distributions of the studied species were correlated to different variables, conservation areas, landscape roughness and grasslands were the most contributing factors in predicting distribution of the species. Majority of habitat patches were located within the boundaries of existing conservation areas, which could be caused by the high environmental resistance outside of conservation areas. Despite the strong structural connectivity in some species, large proportion of migration corridors outside of conservation areas and high degrees of anthropogenic disturbances in natural habitat may reduce functionality of the predicted corridors. The selection of unprotected habitat patches and high-rate migration corridors as Indigenous and Community Conservation Areas (ICCAs) can improve the efficiency of the existing conservation network. The obtained results revealed that the conservation of medium to large-bodied herbivores requires integrated landscape-level management to improve functional connectivity among habitats. 83 97 2021/01/62021/02/222021/06/72021/04/252021/05/52021/07/17 1400/4/26 2021/06/162021/06/162021/08/212021/09/42021/09/22021/09/11 1400/6/20 رسول خسروی R. Khosravi دانشگاه شیراز ایران r-khosravi@shirazu.ac.ir کیمیا رحیمی K. Rahimi دانشگاه شیراز ایران kimia.r.2014@gmail.com Habitat connectivity key habitat migration corridors Bovidae conservation areas پیوستگی زیستگاه زیستگاه کلیدی کریدورهای مهاجرتی گاوسانان مناطق حفاظت‌شده 1.Ahmadi, M., B. N. Balouchi, H. Jowkar, M. R. Hemami, D. Fadakar, S. Malakouti-Khah and S. Ostrowsk. 2017. Combining landscape suitability and habitat connectivity to conserve the last surviving population of cheetah in Asia. Diversity and Distribution 23: 592-603.##2. Ahmadi, M., M. S. Farhadinia, S. A. Cushman, M. R. Hemami, B. Nezami Balouchi, H. Jowkar and D. W. Macdonald. 2020. Species and space: a combined gap analysis to guide management planning of conservation areas. Landscape Ecology 35 :1505-1517.##3. Ahsani, N., M. Kaboli, E. Rastegar-Pouyani, M. Karami and B. B. Kamangar. 2018. Habitat suitability prediction for Salamandra infraimmaculata (Caudata: Amphibia) in western Iran based on species distribution modeling. Journal of Asia-Pacific Biodiversity 11: 203-205.##4. Ashoori, A., A. Kafash, H. Varasteh Moradi, M. Yousefi, H. Kamyab, N. Behdarvand and S. Mohammadi. 2018. Habitat modeling of the common pheasant Phasianus colchicus (Galliformes: Phasianidae) in a highly modified landscape: application of species distribution models in the study of a poorly documented bird in Iran. The European Zoological Journal 85 :372-380.##5. Ashrafzadeh, M. R., R. Khosravi, M. A. Adibi, A. Taktehrani, H. Y. Wan and S. A. Cushman. 2020. A multi-scale, multi-species approach for assessing effectiveness of habitat and connectivity conservation for endangered felids. Biological Conservation 245: 108523.##6. Bagherirad, E., A. Salmanmahiny, N. Ahmad, M. Abdullah and B. Erfanian. 2014. Predicting habitat suitability of the Goitered Gazelle (G. s. subgutturosa) using presence-only data in Golestan National Park, Iran. International Journal of Biological Sciences and Applications 1: 124-136##7. Barve, N., V. Barve, A. Jiménez-Valverde, A. Lira-Noriega, S. P. Maher, A. T. Peterson, J. Soberón and F. Villalobos. 2011. The crucial role of the accessible area in ecological niche modeling and species distribution modeling. Ecological Modelling 222: 1810-1819.##8. Bellard, C., C. Bertelsmeier, P. Leadley, W. Thuiller and F. Courchamp. 2012. Impacts of climate change on the future of biodiversity. Ecology Letters 15: 365-377.##9. Bellard, C., P. Cassey and T. M. Blackburn. 2016. Alien species as a driver of recent extinctions. Biology Letters 12: 24-27.##10. Bleyhl, B., M. Arakelyan, E. Askerov, H. Bluhm, A. Gavashelishvili, M. Ghasabian and T. Kuemmerle. 2019. Assessing niche overlap between domestic and threatened wild sheep to identify conservation priority areas. Diversity and Distributions 25: 129-141.##11. Boitani, L., P. Ciucci, F. Corsi and E. Dupre. .1999. Potential range and corridors for brown bears in the Eastern Alps, Italy. Ursus 11: 123-130##12. Boria, R. A., L. E. Olson, S. M. Goodman and R. P. Anderson. 2014. Spatial filtering to reduce sampling bias can improve the performance of ecological niche models. Ecological modelling 275: 73-77.##13. Caro, T. 2010. Conservation by proxy: indicator, umbrella, keystone, flagship, and other surrogate species. Island Press 10: 1-192.##14. Carpenter, G., A. N. Gillison and J. Winter. 1993. DOMAIN- A flexible modeling procedure for mapping potential distributions of plants and animals. Biodiversity and Conservation 2: 667-680.##15.Chetkiewicz, C. L. B., C. C. St. Clair and M. S. Boyce. 2006. Corridors for conservation: integrating pattern and process. Annual Review of Ecology, Evolution, and Systematics 37: 317-342##16. Crooks, K. R. and M. A. Sanjayan. 2006. Maintaining connections for nature. Connectivity Conservation 14: 1-20.##17. Cushman, S. A., K. S. Mckelvey and M. K. Schwartz. 2009. Using empirically derived source destination models to map regional conservation corridors. Conservation Biology 23: 368-376.##18. Cushman, S. A., N. B. Elliot, D. W. Macdonald and A. J. Loveridge. 2016. A multi-scale assessment of population connectivity in African lions (Panthera leo) in response to landscape change. Landscape Ecology 31: 1337-1353. ##19. Cushman, S. A., E. A. Macdonald, E. L. Landguth, Y. Malhi and D. W. Macdonald. 2017. Multiple-scale prediction of forest loss risk across Borneo. Landscape Ecology 32 :1581-1598. ##20. Dar, S. A., S. K. Singh, H. Y. Wan, V. Kumar, S. A. Cushman and S. Sathyakumar. 2021. Projected climate change threatens Himalayan brown bear habitat more than human land use. Animal Conservation 3: 303-535.##21. Friedman, J. H. 2002. Stochastic gradient boosting. Computer Statistic Data Analysis 38: 367-378.##22. Ghoddousi, A., B. Bleyhl, C. Sichau, D. Ashayeri, P. Moghadas, P. Sepahvand, A. K. Hamidi, M. Soofi and T. Kuemmerle. 2020. Mapping connectivity and conflict risk to identify safe corridors for the Persian leopard. Landscape Ecology 35: 1809-1825.##23. Haghani, A., M. Aliabadian, J. Sarhangzadeh and A. Setoodeh. 2016. Seasonal habitat suitability modeling and factors affecting the distribution of Asian Houbara in East Iran. Heliyon 2: e00142.##24. Hemami, M. R., S. Esmaeili, J. C. Brito, M. Ahmadi, M. Omidi and F. Martínez-Freiría. 2018. Using ecological models to explore niche partitioning within a guild of desert felids. Hystrix, the Italian Journal of Mammalogy 29: 216-222.##25. Hijmans, R. J., S. Phillips, J. Leathwick, J. Elith and M. R. J. Hijmans. 2017. Package DISMO. Circles 9: 1-68. ##26. Hu, J. and Z. Jiang. 2010. Predicting the potential distribution of the endangered Przewalski’s gazelle. Journal of Zoology 282: 54-63.##27. Hu, J., Z. Jiang., J. Chen and H. Qiao. 2015. Niche divergence accelerates evolution in Asian endemic Procapra gazelles. Scientific Reports 5: 1-10.##28. Kaszta, Ż., S. Cushman and D. Macdonald. 2020. Prioritizing habitat core areas and corridors for a large carnivore across its range. Animal Conservation 23: 607-616. ##29. Kazemi, E., M. Kaboli, R. Khosravi and N. Khorasani. 2019. Evaluating the importance of environmental variables on spatial distribution of Caspian cobra Naja oxiana (Eichwald, 1831) in Iran. Asian Herpetological Research 10: 129-138. ##30. Keeley, A. T. H., P. Beier and J. W. Gagnon. 2016. Estimating landscape resistance from habitat suitability: effects of data source and nonlinearities. Landscape Ecology 31: 2151-2162.##31. Khalatbari, L., G. H. Yusefi, F. Martínez-Freiría, H. Jowka and J. C. Brito. 2018. Availability of prey and natural habitats are related with temporal dynamics in range and habitat suitability for Asiatic Cheetah. Hystrix, the Italian Journal of Mammalogy 29: 145-151.##32.Khosravi, R., M. R. Hemami, M. Malekian, A. Flint and L. Flint. 2016. Maxent modeling for predicting potential distribution of goitered gazelle in central Iran: the effect of extent and grain size on performance of the model. Turkish Journal of Zoology 40: 574-585.##33. Khosravi, R., M. R. Hemami and S. A. Cushman. 2018. Multispecies assessment of core areas and connectivity of desert carnivores in central Iran. Diversity and Distributions 24: 193-207.##34. Khosravi, R. and M. R. Hemami. 2019. Identifying landscape species for ecological planning. Ecological Indicators 99: 140-148.##35. Kolahi, M., T. Sakai, K. Moriya, M. F. Makhdoum and L. Koyama. 2013. Assessment of the effectiveness of protected areas management in Iran: Case study in Khojir National Park. Environmental Management 52: 514-530.##36. Lambeck, R. J. 2002. Focal species and restoration ecology: response to Lindenmeyer et al. Conservation Biology 16: 549-551.##37. Landguth, E. L., B. K. Hand, J. Glassy and S. A. Cushman. 2012. UNICOR: a species connectivity and corridor network simulator. Ecography 35: 9-14.##38. Leroy, B., R. Delsol, B. Hugueny, C. Meynard, C. Barhoumi, M. Barbet-Massin and C. Bellard. 2018. Without quality presence-absence data, discrimination metrics such as TSS can be misleading measures of model performance. Journal of Biogeography 10: 1-9.##39. Louppe, V., B. Leroy, A. Herrel and G. Veron. 2020. The globally invasive small Indian mongoose Urva auropunctata is likely to spread with climate change. Scientific Reports 10: 1-11.##40. Malakoutikhah, S., S. Fakheran, M. R. Hemami, M. Tarkesh and J. Senn. 2020. Assessing future distribution, suitability of corridors and efficiency of protected areas to conserve vulnerable ungulates under climate change. Diversity and Distribution 26: 1383-1396.##41. Matteucci, S. D. and M. Camino. 2012. Protected areas isolation in the Chaco Region, Argentina. Journal of Geography and Geology 4: 15.##42. Mowlavi, M .1978. Ecological studies of the goitered gazelle (Gazella Subgutturosa) in Khosh Yeilagh Wildlife Refuge, Iran, MSc thesis. Michigan State University, East Lansing, MI, USA.##43. Najibzadeh, M., A. Gharzi, N. Rastegar-Pouyani, E. Rastegar-Pouyani and A. Pesarakloo. 2017. Habitat suitability and patterns of sex-biased migration of the Iranian long-legged wood frog, Rana pseudodalmatina (Anura: Ranidae). Biologia 72: 686-693.##44. Phillips, S. J., R. P. Anderson and R. E. Schapire. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modeling 190: 231-259.##45. Pascual-Hortal, L. and S. Santiago. 2008. Integrating landscape connectivity in broad scale forest planning through a new graph-based habitat availability methodology: Application to capercaillie (Tetrao urogallus) in Catalonia (NE Spain). European Journal of Forest Research 127: 23-31.##46. Ripple, W. J., J. A. Estes, R. L. Beschta, C. C. Wilmers, E. G. Ritchie, M. Hebblewhite, J. Berger, B. Elmhagen, M. Letnic, M. P. Nelson, O. J. Schmitz, D. W. Smith, A. D. Wallach and A. G. Wirsing. 2014. Status and ecological effects of the world’s largest carnivores. Science 343: 124-148. ##47. Riquelme, C., S. A. Estay, R. López, H. Pastore, M. Soto-Gamboa and P. Corti. 2018. Protected areas effectiveness under climate change: a latitudinal distribution projection of an endangered mountain ungulate along the Andes Range. Peer J 6: e5222.##48. Ruiz-Mondragón, E. D. J., G. Romero-Figueroa, M. A. García-Aranda, E. A. Lozano-Cavazos and R. Valdez. 2018. Potential distribution model of Ovis canadensis in northern Baja California, Mexico. Therya 9(3): 219-226.##49. Sage, K.M., T. L. Johnson, M. B. Teglas, N. C. Nieto and T. G. Schwan. 2017. Ecological niche modeling and distribution of Ornithodoros hermsi associated with tick-borne relapsing fever in western North America. PLoS Neglected Tropical Diseases 11: e0006047.##50. Salas, E. A. L., R. Valdez, S. Michel and K. G. Boykin. 2018. Habitat assessment of Marco Polo sheep (Ovis ammon polii) in Eastern Tajikistan: Modeling the effects of climate change. Ecology and evolution 8: 5124-5138.##51. Sanderson, E. W., K. H. Redford, A. Vedder, P. B. Coppolillo and S. E. Ward. 2002. A conceptual model for conservation planning based on landscape species requirements. Landscape and Urban Planning 58: 41-56. ##52. Sappington, J. M., K. M. Longshore and D. B. Thomson. 2007. Quantifying landscape ruggedness for animal habitat analysis: A case study using bighorn sheep in the Mojave Desert. Journal of Wildlife Management 71: 1419-1426. ##53. Shahnaseri, G., M. R. Hemami, R. Khosravi, S. Malakoutikhah, M. Omidi and S. A. Cushman. 2019. Contrasting use of habitat, landscape elements, and corridors by grey wolf and golden jackal in central Iran. Landscape Ecology 6: 1-15.##54. Urban, D. and T. H. Keitt. 2001. Landscape connectivity: a graph- theoretic perspective. Ecology 82: 1205-1218.##55. Vergara, M., S. A. Cushman, F. Urra and A. Ruiz-González. 2016. Shaken but not stirred: multiscale habitat suitability modeling of sympatric marten species (Martes martes and Martes foina) in the northern Iberian Peninsula. Landscape Ecology 31: 1241-1260.##56. Wiens, J. A. 2001. The landscape concept of dispersal. pp. 96-109, In: J. Clobert, E. Danchin, A. A. Dhondt and J. D. Nichols (eds.), Dispersal. Oxford University Press, New York.##57. Yousefkhani, S. S. H., M. Aliabadian, E. Rastegar-Pouyani and J. Darvish. 2017. Predicting the impact of climate change on the distribution pattern of Agamura persica Dumeril, 1856 (Squamata: Gekkonidae) in Iran. Belgian Journal of Zoology 2: 137-142.##58. Zeller, K. A., M. K. Jennings, T. W. Vickers, H. B. Ernest, S. A. Cushman and W. M. Boyce. 2018. Are all data types and connectivity models created equal Validating common connectivity approaches with dispersal data. Diversity and Distributions 24: 868-879. ##59. Ziółkowska, E., K. Perzanowski, B. Bleyhl, K. Ostapowicz and T. Kuemmerle. 2016. Understanding unexpected reintroduction outcomes: Why aren't European bison colonizing suitable habitat in the Carpathians. Biological Conservation 195: 106-117.## ##