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اثر شدت‌های بهره‌برداری بر تولید کتیرا و سلامت گیاه گون زرد (Astragalus verus) Effects of Harvest Intensities on Tragacanth Gum Production and Health of Astragalus Verus 1 1 در دهه‌های اخیر بهره‌برداری کتیرا از پایه‌های گون (Astragalus verus) در سطح مراتع کشور شدت یافته است. با وجود این، اطلاعات اندکی در زمینه بهترین شیوه برداشت کتیرا، که ضمن دارا بودن بازدهی اقتصادی باعث حفظ سلامت گیاه شود، وجود دارد. پژوهشی به‌صورت آزمایش ترکیب فاکتوریل در قالب طرح کاملاً تصادفی در شرایط طبیعی مراتع برقبان شهرستان خوشاب در بهار و تابستان 1397 و 1398 انجام شد. تیغ‌زدن طوقه در سه سطح (یک، دو و سه تیغ) و همچنین تعداد دفعات برداشت محصول کتیرا در چهار سطح (یک، دو، سه و چهار دفعه برداشت) بر 10 تکرار از هر تیمار (تعداد کل بوته ها 120 عدد) اعمال شد. با افزایش تعداد دفعات برداشت، مقدار محصول کتیرا افزایش یافت، اما با افزایش تعداد تیغ‌ها از یک به دو و سه، افزایش معنی‌داری در عملکرد کتیرا مشاهده نشد. تیغ‌زدن گون حتی در سطح یک تیغ، سبب کاهش شادابی و افزایش خشکیدگی گیاه شد، اما افزایش تعداد تیغ‌ها سبب تشدید خشکیدگی پایه‌های گون نشد. بر اساس ارزیابی اقتصادی (محاسبه هزینه‌ها و درآمدهای برداشت محصول کتیرا) و ارزیابی اکولوژیک انجام شده در این پژوهش، بهترین شیوه برداشت محصول کتیرا که کمترین خسارت را به گیاه مادر وارد کند یک تیغ و چهار دفعه برداشت است.   2 In recent decades, tragacanth gum extraction from Astragalus verus has dramatically increased across Iranian rangelands. However, little information is available about the best method of gum harvest, which is economically efficient and maintains the health of the plant. This research was conducted as a factorial combination and in a completely randomized design, during spring and summer of 2018-2019, at Baraghban rangeland. Three levels of stem cuts (i.e. 1, 2, and 3 cuts on the main stem of each plant) and four frequencies of gum removals (1 to 4 times) with 10 replications were applied on 120 individual plants. Results indicated that all cut and gum removal levels significantly reduced the vigor of A. verus, but no significant relationship was detected between gum removal levels and plant vigor. There was an increase in the gum yield by increasing the number of gum harvests, but no increase was found by increasing cut numbers. Based on the ecological and economic comparisons (estimating costs and benefits), we suggest one cut and four times of gum removal as the most suitable method. 1 13 2019/11/13 1398/8/22 2020/06/6 1399/3/17 هادی آزادروح H. Azadrooh دانشگاه فردوسی مشهد ایران Azadrooh@ymail.com محمد فرزام M. Farzam دانشگاه فردوسی مشهد ایران mjankju@um.ac.ir منصور مصداقی M. Mesdaghi دانشگاه فردوسی مشهد ایران mmesdagh@yahoo.com Plant cuts Medicinal plant Harvest frequency Tragacanth gum تیغ‌زدن گیاه دارویی دفعات برداشت شادابی صمغ کتیرا 1. Abtahi, S.M., K. Bagherzadeh, and E. Zandi Esfahan .2015. Investigating the effects of number and frequency of incisions on production and survival of Astragalus keyserlingii. Journal of Rangelands Science 5(3): 242-250.##2. Akbarian, M. 1999. Final report of Tragacanth utilization in Yahya’abad rangelands of Natanz, Isfahan Natural Resources and Watershed Management Department, Isfahan. (In Farsi).##3. Anonymous. 2017. The studies on range management plans in traditional boundaries of Hojjat-Abad, Khoshab. Sazab Shargh Watershed Extension Company, 105 pp. (In Farsi).##4. Asadi, M. 2001. The flora of Iran. Research Institute of Forests and Rangelands Publication, Tehran. (In Farsi). ##5. Asadian, Gh. and A. Barati. 2006. Investigation of effect of number and type of construct in different times on amount of gum Tracaganth production in white milk-vetch (Astragalus gossypinus). Pajouhesh-va-Sazandegi 19(1): 33-40. (In Farsi).##6. Asadian, Gh., N. Kholahci, and M. R. Sadeghimanesh. 2008. An investigation on the effect and type of construct in different times on amount of gum tracaganth production in yellow milk-vetch (Astragalus parrowianus). Pajouhesh & Sazandegi 81: 170-175. (In Farsi).##7. Emad, M., F. Ghaybi, S. M. Rasouli, R. Khanjanzadeh and S. Mohammadi Jozani. 2012. Medicinal-industrial plants producing Tragacanth gum. Peyman Novandish Publication, Tehran. (In Farsi).##8. Fayaz, M., H. Tavakoli, M. Tabatabaei, H. Pejman and Gh. R. Hosseini. 2013. Understanding ecological areas of Iran (Khorasan Razavi). Research Institute of Forests and Rangelands, Tehran. (In Farsi).##9. Jafari, A. 1995. An investigation on anatomic structure of stems for some species of Astragalus producing Tragacanth gum in Iran. MSc thesis. University of Tehran. Tehran, Iran. (In Farsi).##10. Jafari, A., A. Ghahraman and A. A. Ramak Masoumi. 2001. Investigation on stem cross section and wood analysis kinds of gum producer Astragalus species in Iran. Journal of Pajouhesh-va-Sazandegi 14(3): 34-36. (In Farsi).##11. Mahmoudi, M,. A. A. Masoumi and B. hamzehei .2009. Geographic distribution of Astragalus (Fabaceae) in Iran, Rostaniha 10(1):112-132. (In Farsi).##12. Masoumi, A. A. 1986. The genus Astragalus in Iran, Vol. 3. Research institute of Forests and Rangelands Publication, Tehran. (In Farsi). ##13. Masoumi, A. A. 2000. Iranian Astragalus Spp., Vol. 4. Research Institute of Forests and Rangelands Publication, Tehran. (In Farsi).##14. Naghavizadeh, M. R. 2003. Ecological characteristics of Astragalus’s Tragacanth species in Khorasan Province and providing sustainable harvesting patterns. MSc thesis. Ferdowsi University of Mashhad. Mashhad, Iran. (In Farsi).##15. Robbers, J. E., M. K. Speedie and E. T. V. E. Tyler. 1996. Pharmacognosy and Pharmacobiotechnology. Willians & Wilkins, Maryland.##16. Saffar, M. T. and M. M. Seyed Sharif. 1991. The studies on Tragacanth gum. Isfahan Bureau of Natural Resources, Isfahan. (In Farsi). ##17. Saffar, M. T. and S. M. Razavi. 1993. Project of Tragacanth gum in Mousa-Abad and Natanz. Isfahan Bureau of Natural Resources, Isfahan. (In Farsi). ##18. Soleimani, A., A. Rashed, H. Bagherzadeh Seke, S. Khorramdel and A. M. Farjadian. 2013. An investigation on the economic value of utilization and regeneration of Tragacanth medicinal plant in Akbarabad- Kashmar. In: Proceedings of 1st National Conference on Commercialization of Medicinal Plants and Natural Products. Isfahan, Iran. (In Farsi).##19. Taiz, L. and E. Zeiger. 2003. Plant Physiology (3rd ed.). Sunderland: Sinauer Associates.##20. Vahabi, M. R., M. Basiri, M. R. Moghadam and A. A. Masoumi. 2007. Determination of the most effective habitat indices for evaluation of Tragacanth sites in Isfahan Province. Journal of the Iranian Natural Resources 59(4): 1013-1029. (In Farsi).##21. Whistler, R.L. 1993. Exudate gums. pp. 309-339, In: R. L. Whistler and J. N. BeMiller (Eds.), Industrial gums, polysaccharides and their derivatives. Academic Press, San Diego.##22. Yakhchali, B., A. Afzal Al-Qawm, P. Yegangi, H. Shoorgashti, A. Siami and S. M. Alavi. 2011. Optimization of growth condition of Barvar2 plant growth promoting Bacteria. Iranian Journal of Biology 24(4): 494-506. (In Farsi).##23. Yazdanshenas, H., M. Jafari, H. Azarnivand and H. Arzani. 2015. Fitting suitable models for gum production in Astrgalus gossypinus Fisher based on habitat soil characteristics evidence (Case study: Isfahan Tiran and Karvan region). Journal of Plant Research (Iranian Journal of Biology) 28(3): 666-673. (In Farsi).## ##

ارزیابی و برنامه‌ریزی فضایی پیوستگی بوم شناختی سیمای سرزمین در راستای مدیریت تنوع زیستی (منطقه مورد مطالعه: استان قزوین) Assessment and Spatial Planning of Landscape Ecological Connectivity for Biodiversity Management (Case Study: Qazvin Province) 1 1 گسستگی زیستگاه‌ها و سامانه‌های زیستی و به‌دنبال آن افول پیوستگی بوم‌شناختی سیمای سرزمین، از دلایل اصلی نابودی تنوع زیستی به حساب می‌آیند که جریان ماده، انرژی و اطلاعات را در مقیاس سیمای سرزمین مختل کرده است. نظر به اهمیت این موضوع، هدف از مطالعه حاضر، ارزیابی پیوستگی بوم‌شناختی و برنامه‌ریزی فضایی سیمای سرزمین استان قزوین در جهت احیا و حفاظت از گذرگاه‌های جریان ماده، انرژی و اطلاعات با رویکرد بوم‌شناسی سیمای سرزمین است. بدین منظور با استفاده از نقشه کاربری و پوشش اراضی، نواحی دارای عملکرد بوم‌شناختی شناسایی و شاخص‌های اثر مانع و پیوستگی بوم‌شناختی سیمای سرزمین با استفاده از مدل‌سازی ریاضی با الگوریتم مدل‌ساز در محیط GIS پهنه‌بندی شد. سپس لکه¬های مستعد برای احیا و حفاظت به‌طور مکانی در سیمای سرزمین شناسایی شد. نتایج این تحقیق نشان داد که 90 درصد از مساحت استان دارای عملکرد بوم‌شناختی و 10 درصد از آن فاقد عملکرد بوم‌شناختی است.  3 درصد از نواحی فاقد عملکرد بوم‌شناختی به‌وسیله موانع انسان ساخت مانند ایجاد شبکه جاده‌ای، رشد شهرها و توسعه صنایع، و 7 درصد نیز تحت تأثیر عارضه‌های انسان ساخت، عملکرد بوم‌شناختی خود را از دست داده‌اند. در این تحقیق به‌منظور برنامه‌ریزی فضایی، چهار گذرگاه برای جریانات ماده، انرژی و اطلاعات شناسایی شد. نتایج این تحقیق در برنامه‌های مدیریتی مناطق حفاظت شده و آمایش سرزمین و همچنین ارزیابی اثرات توسعه و ارزیابی راهبردی محیط زیست قابل استفاده است. 2 Habitat and ecosystem fragmentation and, consequently, the loss of landscape connectivity are major causes of biodiversity destruction, leading to disruption of material, energy, and information flow at the landscape scale. Given the importance of this issue, the current study aimed to evaluate the ecological connectivity and spatial planning of Qazvin Province, in order to re-establish and protect material, energy, and information flow corridors, using a landscape ecology approach. With that in mind, land use/land cover map was used to identify ecologically functional areas and to map barrier effect and ecological connectivity indicies by mathematical modeling techniques using model builder algorithms in Geographic Information System (GIS). Appropriate patches were, then, spatially selected for restoration and conservation across the landscape. The results showed that 90% of the province has the ecological function, but 10% of the area lacks the function. Three percent of the area has lost its ecological function by physical barriers such as road networks and industrial and residential expantions, and 7% of the area lost its functionality due to anthropogenic effects. In this research, four corridors were identified for spatial planning. Results of this study can be used for management of protected areas and land use planning, as well as environmental impact assessment and envuronmental strategic assessment. 15 29 2019/11/132019/12/13 1398/9/22 2020/06/62020/06/6 1399/3/17 آصف درویشی A. Darvishi دانشگاه شهید بهشتی تهران ایران asefdarvishi1980@gmail.com نغمه مبرقعی دینان N. Mobarghaee Dinan دانشگاه شهید بهشتی تهران ایران n_mobarghei@yahoo.com شهیندخت برق جلوه Sh. Barghjelveh دانشگاه شهید بهشتی تهران ایران s_barghjelveh@sbu.ac.ir مریم یوسفی M. Yousefi دانشگاه شهید بهشتی تهران ایران yousefi.myb@gmail.com Ecology Landscape Biodiversity Matter-Energy and Information Flow Qazvin Province بوم‌شناسی سیمای سرزمین تنوع زیستی جریان ماده-انرژی و اطلاعات استان قزوین 1. Almasieh, K. and M. Kaboli. 2019. Assessment of landscape connectivity and prediction of migration corridors for the Baluchistan Black Bear (Ursus thibetanus gedrosianus Blanford, 1877) in the southeastern habitats, Iran. Iranian Journal of Applied Ecology 8(1): 33-45. (In Farsi).##2. Andren, H. 1994. Effects of habitat fragmentation on birds and mammals in landscapes with different proportions of suitable habitat: a review. Oikos 71: 355-366.##3. Bani, L., G. Pisa, M. Luppi, G. Spilotros, E. Fabbri, E. Randi and V. Orioli. 2015. Ecological connectivity assessment in a strongly structured fire salamander (Salamandra salamandra) population. Ecology and Evolution 5(16): 3472-3485.##4. Brandt, J. 1995. Ecological networks in Danish planning. Landschap 12(3): 63-76.##5. Casalegno, S., K. Anderson, D. T. Cox, S. Hancock and K. J. Gaston. 2017. Ecological connectivity in the three-dimensional urban green volume using waveform airborne lidar. Scientific Reports 7: 45571.##6. D’acampora, B. H., E. Higueras and E. Román. 2018. Combining different metrics to measure the ecological connectivity of two mangrove landscapes in the Municipality of Florianópolis, Southern Brazil. Ecological Modelling 384: 103-110.##7. Darvishi, A., S. Fakheran, A. Soffianian and M. Ghorbani. 2014. 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. (In Persian).##8. Darvishi, A., M. Ghorbani, S. Fakheran and A. Soffianian. 2014. Network analysis and key actors toward wildlife management (case study: habitat of Caucasian Black Grouse, Arasbaran Biosphere Reserve). Iranian Journal of Applied Ecology 3(9): 29-41. (In Persian).##9. Darvishi, A., S. Fakheran, and A. Soffianian. 2015. Monitoring landscape changes in Caucasian black grouse (Tetrao mlokosiewiczi) habitat in Iran during the last two decades. Environmental Monitoring and Assessment 187(7): 443.##10. Darvishi, A., S. Fakheran, A. Soffianian and M. Ghorbani. 2016. Change detection and land use/cover dynamics in the Arasbaran Biosphere Reserve. Journal of Natural Environment (Iranian Journal of Natural Resources) 68(4): 559-572. (In Persian).##11. Dupras, J., J. Marull, L. Parcerisas, F. Coll, A. Gonzalez, M. Girard and E. Tello. 2016. The impacts of urban sprawl on ecological connectivity in the Montreal Metropolitan Region. Environmental Science & Policy 58: 61-73.##12. Forman, R. T. 2000. Estimate of the area affected ecologically by the road system in the United States. Conservation Biology 14(1): 31-35.##13. Hou, W., M. Neubert and U. Walz. 2017. A simplified econet model for mapping and evaluating structural connectivity with particular attention of ecotones, small habitats, and barriers. Landscape and Urban Planning 160: 28-37.##14. Indrayani, P., Y. Mitani, L. Djamaluddin and H. Ikemi. 2017. A GIS based evaluation of land use changes and ecological connectivity index. Journal of Geomatics and Planning 4(1): 9-18.##15. Jongman, R. H., M. Külvik and I. Kristiansen. 2004. European ecological networks and greenways. Landscape and Urban Planning 68(2-3): 305-319.##16. Kettunen, M., A. Terry, G. Tucker and A. Jones. 2007. Guidance on the maintenance of landscape connectivity features of major importance for wild flora and fauna- Guidance on the implementation of Article 3 of the Birds Directive (79/409/EEC). Institute for European Environmental Policy (IEEP), Brussels..##17. Khosravi, R., M. R. Hemami and M. Malekian. 2018. Assessing landscape connectivity and dispersal corridors for Goitered gazelle in Central Iran. Iranian Journal of Applied Ecology 6(4): 49-64. (In Farsi).##18. LaPoint, S., N. Balkenhol, J. Hale, J. Sadler and R. van der Ree. 2015. Ecological connectivity research in urban areas. Functional Ecology 29(7): 868-878.##19. Liro, A., R. Andrzejewski, W. Różycka and Z. Tederko. (Eds.). 1995. National Ecological Network EECONET-Poland. IUCN Office for Central & Eastern Europe, Warsaw.##20. Loro, M., E. Ortega, R. M. Arce and D. Geneletti. 2015. Ecological connectivity analysis to reduce the barrier effect of roads. An innovative graph-theory approach to define wildlife corridors with multiple paths and without bottlenecks. Landscape and urban planning 139: 149-162.##21. Makki, T., S. Fakheran, H. Moradi, M. Iravani and M. Farahmand. 2013. Ecological impact assessment of Isfahan’s west ringway on Ghamishloo Wildlife Refuge using Habitat Evaluation Procedure (HEP). Iranian Journal of Applied Ecology 1(2): 39-52. (In Farsi).##22. Mallarach, J. M. and J. Marull. 2006. Impact assessment of ecological connectivity at the regional level: recent developments in the Barcelona Metropolitan Area. Impact Assessment and Project Appraisal 24(2): 127-137.##23. Marull, J., G. Cunfer, K. Sylvester and E. Tello. 2018. A landscape ecology assessment of land-use change on the Great Plains-Denver (CO, USA) metropolitan edge. Regional Environmental Change 18(6): 1765-1782.##24. Marull, J., S. Herrando, L. Brotons, Y. Melero, J. Pino, C. Cattaneo and E. Tello. 2019. Building on Margalef: Testing the links between landscape structure, energy and information flows driven by farming and biodiversity. Science of the Total Environment 674: 603-614.##25. Marulli, J. and J. M. Mallarach. 2005. A GIS methodology for assessing ecological connectivity: application to the Barcelona Metropolitan Area. Landscape and Urban Planning 71(2-4): 243-262.##26. O’neill, R. V., R. Gardner and M. G. Turner. 1992. A hierarchical neutral model for landscape analysis. Landscape Ecology 7(1): 55-61.##27. Parcerisas, L., J. Marull, J. Pino, E. Tello, F. Coll and C. Basnou. 2012. Land use changes, landscape ecology and their socioeconomic driving forces in the Spanish Mediterranean coast (El Maresme County, 1850–2005). Environmental Science & Policy 23: 120-132.##28. Pierik, M. E., M. Dell’Acqua, R. Confalonieri, S. Bocchi and S. Gomarasca. 2016. Designing ecological corridors in a fragmented landscape: A fuzzy approach to circuit connectivity analysis. Ecological indicators 67: 807-820.##29. Sepp, K., H. Palang, U. Mander and A. Kaasik. 1999. Prospects for nature and landscape protection in Estonia. Landscape and Urban Planning 46(1-3): 161-167.##30. Shafinejad, S., F. Poodat and F. Farrokhian. 2018. Assessment of ecological connectivity of urban green patches using graph theory: The case study of Ahvaz metropolitan area. Iranian Journal of Applied Ecology 7(1): 1-11. (In Farsi).##31. Turner, M. G. 1990. Spatial and temporal analysis of landscape patterns. Landscape Ecology 4(1): 21-30.##32. Virgós, E., J. L. Tellería and T. Santos. 2002. A comparison on the response to forest fragmentation by medium-sized Iberian carnivores in central Spain. Biodiversity & Conservation 11(6): 1063-1079.##33. With, K. A. and T. O. Crist. 1995. Critical thresholds in species' responses to landscape structure. 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شناسایی زیستگاه‌های مطلوب خرس قهوه‌ای (Ursus arctos) در جنگل‌های زاگرس شمالی Identifying suitable habitats for brown bear (Ursus arctos) in northern Zagros forests 1 1 حیات وحش یکی از شاخص‌های مهم زیستی اکوسیستم‌ها و یکی از معیارهای مهم تنوع زیستی است که حفظ آن مستلزم شناخت خصوصیات گونه‌ها و همچنین زیستگاه آنها است. تعیین مطلوبیت زیستگاه‌ حیات وحش دارای اهمیت بسزایی در برنامه‌های حفاظت و مدیریت حیات وحش است. خرس قهوه‌ای به‌عنوان بزرگترین پستاندار گوشتخوار ایران در بیشتر اکوسیستم‌های جنگلی و کوهستانی پراکنده شده و از اهمیت حفاظتی بالایی برخوردار است. در این پژوهش، مدل¬سازی مطلوبیت زیستگاه خرس قهوه‌ای در استان کردستان با استفاده از الگوریتم آنتروپی بیشینه (مکسنت) انجام شد. بدین منظور پس از جمع‌آوری داده‌های نقاط حضور و لایه‌های محیطی و بررسی همبستگی بین لایه‌ها، اطلاعات به‌دست¬آمده وارد مدل مکسنت شد. نتایج حاصل از مدل¬سازی نشان داد که متغیرهای دمای فصلی، میزان بارندگی سالیانه، شیب، ارتفاع و کاربری/ پوشش اراضی مهم‌ترین متغیرهای تأثیرگذار در مطلوبیت زیستگاه خرس قهوه‌ای است. بر اساس نتایج حاصل، از کل مساحت استان کردستان، 1 درصد دارای مطلوبیت زیاد،11 درصد دارای مطلوبیت متوسطو 5 درصد دارای مطلوبیت کم بوده و 83 درصد در طبقه نامطلوب قرار دارد. بر اساس نتایج حاصل، مناطق حفاظت شده چل¬چمه، شاهو و کوسالان، زیستگاه‌های مطلوبی برای خرس قهوه‌ای هستند. جنگل‌های زاگرس به‌عنوان یکی از زیستگاه‌های اصلی خرس قهوه‌ای در ایران محسوب می‌شود؛ در نتیجه، حفاظت از این زیستگاه‌ها به‌منظور حفظ جمعیت‌های این گونه گوشتخوار ارزشمند ضروری است. 2 Wildlife is an important biological indicator of viability of ecosystems, therefore, understanding habitat requirements of species is essential for biodiversity conservation. Determining the suitability of habitats for wildlife is important for effective management and conservation of species. The brown bear (Ursus arctos), as the largest carnivorous mammal in Iran, is distributed in most forest and mountain ecosystems and has a high conservation value. In the current study, brown bear habitat suitability modelling, in Kurdistan Province, was performed using maximum entropy algorithm (MaxEnt). After collecting the presence data and environmental variables, and examining the correlation between the variables, the obtained data were entered into the MaxEnt model. Results showed that temperature seasonality, annual precipitation, topography and vegetation are the most important variables in predicting habitat suitability of the brown bear in Kurdistan province. From the total area of Kurdistan Province, 1, 5 and 11 % were respectively accounted for habitats of high, moderate and low suitability, and 83% of the area was clssifed as unsuitable habitats. Based on the results, Chehel Cheshmeh, Shaho and Kosalan protected areas are suitable habitats for the brown bear. Zagros forests are considered as one of the main habitats of brown bear in Iran, consequently, the conservation of these habitats is essential to protect populations of this valuable carnivorous species. 31 43 2019/11/132019/12/132019/11/30 1398/9/9 2020/06/62020/06/62020/06/7 1399/3/18 علی لطفی A. lotfi دانشگاه صنعتی اصفهان ایران lotfi@cc.iut.ac.ir یاسر مرادی Y. Moradi دانشگاه صنعتی اصفهان ایران yasermoradi1372@gmail.com Modeling Maximum Entropy Habitat Suitability Map Kurdistan Province Brown Bear مدل‌سازی آنتروپی بیشینه مطلوبیت زیستگاه جنگل‌های زاگرس خرس قهوه‌ای 1. Ataei, F., M. Karami and M. Kaboli. 2012. Summer habitat suitability modeling of Brown Bear (Ursus arctos) Southern Alborz Protected Area. Journal of Natural Environment 65(2): 235-245. (in Farsi).##2. Department of Environmental Protection Agency of Kurdistan Province. 2019. Environmental Scene of Kurdistan Province. Available online at: https://kordestan.doe.ir/portal/home/. Accessed 10 November 2019.##3. Erfanian, B., S. H. Mirkarimi, A. S. Mahini and H. R. Rezaei. 2013. A presence-only habitat suitability model for Persian Leopard (Panthera pardus saxicolor) in Golestan National Park, Iran. Wildlife Biology 19(2): 170-178.##4. Falahati, S., K. Shayesteh and P. Karami. 2019. Quantifying the effect of environmental factors on the distribution of Brown Bears (Ursus arctos) in Zagros oak (Quercus) forests (Case Study: Ghalajeh Protected Area). Journal of Animal Environment 11(4): 1-8. (in Farsi).##5. Farhadinia, M. S., H. Akbari, S. J. Mousavi, M. Eslami, M. Azizi, J. Shokouhi, M. Gholikhani and F. Hosseini- Zavarei. 2013. Exceptionally long movements of the Asiatic cheetah (Acinonyx jubatus venaticus) across multiple arid reserves in central Iran. Oryx 47(3): 427-430.##6. Fernandez, N., N. Selva, C. Yuste, H. Okarma and Z. Jakubiec. 2012. Brown bears at the edge: modeling habitat constrains at the periphery of the Carpathian population. Biological Conservation 153: 134-142.##7. Ghadirian, O., M. R. Hemami, A. Soffianian, M. Malekian, S. Pourmanafi and M. Amiri. 2019. The prediction of Persian squirrel distribution using a combined modeling approach in the forest landscapes of Luristan Province. Iranian Journal of Applied Ecology 8(1): 47-58. (in Farsi).##8. Gholamhosseini A., H. R. Esmaeili, H. Ahani, A. Teimory, M. Ebrahimi, H. GH. Kami and H. Zohrabi. 2011. Study of topography and climate effects on brown bear (Ursus arctos Linneaus, 1758): Carnivora, Ursidae distribution in south of Iran with use of Geographic Information System (GIS), Iranian Journal of Biology 23(2): 215-233. (in Farsi).##9. Gutleb, B. and H. Ziaie. 1999. On the distribution and status of brown bears (Ursus arctos) and the Asiatic black bear,) U. thibetanus) in Iran. Zoology in the Middle East 18: 5-8.##10. Hemami M. R., S. Esmaeili and A. R. Soffianian. 2015. Predicting the distribution of Asiatic Cheetah, Persian Leopard and Brown Bear in response to environmental factors in Isfahan Province. Iranian Journal of Applied Ecology 4(13): 51-64##11. Hernandez, P. A., C. H. Graham, L. L. Master and D. L. Albert. 2006. The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography 29(5): 773-785.##12. Hosseini, S. P. 2019. Impact of land degradation on brown bear (Ursus arctos) habitat in Kurdistan Province using remote sensing and species distribution modeling. MSc thesis. Isfahan University of Technology. Isfahan, Iran. (in Farsi). ##13. IUCN. 2018. The IUCN Red List of Threatened Species. Available online at: www.iucnredlist.org. Accessed 20 October 2018.##14. Kamaei, M. 2013. Evaluation the impacts of land use on Brown Bear habitat suitability in Central Alborz protected area. MSc thesis. Isfahan University of Technology. Isfahan, Iran. (in Farsi). ##15. Kermani, F., B. Raygani, B. Nezami, H. Goshtasb, H. Khosravi and H. Heydari. 2017. Evaluation of environmental index in habitat selection of cheetah (Acinonyx Jubatus Venaticus; Griffith, 1821) using time series data of remote sensing (Case study: Touran management region). Journal of Animal Environment 9(1): 1-12. (in Farsi).##16. Koren, M., S. Findo, M. Skuban and M. Kajba. 2011. Habitat suitability modelling from non-point data: the case study of brown bear habitat in Slovakia. Ecological Informatics 6: 296-302.##17. Lyet, A., Th. Wilfried, Ch. Marc and B. Aurelien. 2013. Fine-scale regional distribution modelling of rare and threatened species: bridging GIS tools and conservation in practice. Diversity and Distributions 19(7):651-663.##18. Madadi, H., H. Varasteh Moradi and M. Madadi. 2019. Evaluating the habitat of brown bears (Ursus arctos syriacus) using Ecological Niche Factor Analysis in Golestan National Park. Journal of Animal Research (Iranian Journal of Biology) 32(4): 315-328. (in Farsi).##19. Nawaz, M. A. 2008. Ecology, genetics and conservation of Himalayan brown bears. PhD Thesis. Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences. Ås, Norway.##20. Nawaz, M. A., J. Martin and J. E. Swenson. 2014. Identifying key habitats to conserve the threatened brown bear in the Himalaya. Biological Conservation 170: 198-206.##21. Nezami, B. 2008. Ecological studies on brown Bear (Ursus Arctos) in the northern part of Central Alborz Protected Area. MSc thesis. Islamic Azad University. Tehran, Iran. (in Farsi).##22. Obeidavi, Z., K. Rangzan, R. Mirzaei and M. Kabolizade. 2017. Habitat suitability modelling of brown bear (Ursus arctos) in Shimbar protected area, Khuzestan Province. Iranian Journal of Applied Ecology 5(18): 61-72. (in Farsi).##23. Phillips, S. J., R. P. Anderson and R. E. Schapire. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling 190: 231-259.##24. Segan, D. B., K. A. Murray and J. E. Watson. 2016. A global assessment of current and future biodiversity vulnerability to habitat loss-climate change interactions. Global Ecology and Conservation 5: 12-21.##25. Seoane, J. 2005. Habitat-suitability modelling to assess the effects of land-use changes on Dupont’s lark Chersophilus duponti: A case study in the Layna Important Bird Area., Biological Conservation 8: 241-252.##26. Trisurat, Y., N. Bhumpakphan, D. H. Reed and B. Kanchanasaka. 2012. Using species distribution modeling to set management priorities for mammals in northern Thailand. Natural Conservation 20: 264-273.##27. Weber, W. and A. Rabinowitz. 1996. A global perspective on large carnivore conservation. Conservation Biology 10(4): 1046-1054.## ##

ارزیابی اکولوژیک آلودگی آلی خلیج گرگان با استفاده از شاخص جلبکی پالمر Ecological Assessment of Organic Pollution in the Gorgan Bay, Using Palmer Algal Index 1 1 در سال‌های اخیر بررسی‌های زیادی بر روی مشکل آلودگی ‌دریای ‌خزر انجام شده، اما اطلاعات مرتبط با آلودگی خلیج ‌گرگان محدود است. بنابراین هدف از این مطالعه ارزیابی آلودگی ‌آلی خلیج ‌گرگان با استفاده از شاخص جلبکی پالمر بود. نمونه‌برداری فصلی از تابستان 1397 تا بهار 1398 با سه تکرار انجام ‌شد. نمونه‌های فیتوپلانکتون توسط بطری با حجم یک لیتر از عمق سطحی (حداکثر تا 0/5 متر) جمع‌آوری و با فرمالین بافر 2/5 درصد در محل تثبیت شدند. در مجموع تعداد 23 ایستگاه در کل خلیج ‌گرگان انتخاب و به سه بخش شرقی ‌(شامل 7 ایستگاه)، مرکزی (شامل 8 ایستگاه) و غربی (شامل 8 ایستگاه) تقسیم¬بندی شدند. نتایج حاصل از شاخص پالمر نشان داد تمام بخش‌های خلیج در هر چهار فصل در دسته‌ آب‌های دارای آلودگی آلی بسیار زیاد قرار می‌گیرند. مقایسه‌ سه بخش خلیج در مطالعه‌ حاضر نشان داد که در فصول تابستان، پاییز و زمستان بخش ‌مرکزی دارای بیشترین میزان آلودگی است و تنها در فصل بهار، بالاترین مقدار شاخص در غرب خلیج مشاهد شد. غالب بودن جنس‌های مقاوم به آلودگی مانند Oscillatoria، Euglena، Cyclotella، Navicula، Nitzschia و Synedra در طول سال نیز از دیدگاه طبقه‌بندی این مکان به‌عنوان یوتروفیک، حمایت می‌کند. به‌طور کلی نتایج شاخص جلبکی نشان می‌دهد که کیفیت آب خلیج‌گرگان به سطح بحرانی رسیده است. 2 The problem of pollution in the Caspian sea has attracted increasing scientific concerns in recent years, but still, there is limited data relevant to the Gorgan bay. The current study aimed to evaluate the organic pollution of the Gorgan Bay, using Palmer Algal Index. Sampling was conducted seasonally in triplicate from summer 2017 to spring 2018. Phytoplankton samples were collected from surface water (maximum depth of 50cm), using a one-liter sampling bottle and fixed in 2.5% formaldehyde buffer solution. A total of 23 stations were selected including, seven stations in the eastern areas, eight stations in the centre, and eight stations in the western part of the bay. The Palmer Index indicated that all parts of the bay are highly polluted, in the four seasons. Comparison of the index among the three parts of the bay indicated that the central areas are more polluted than other areas in the three seasons, from summer to winter, while only in the spring, the western area of the bay showed the highest value of the index. The predominance of the pollution resistant Phyto-genera such as Oscillatoria, Euglena, Cyclotella, Navicula, Nitzschia, and Synedra supports the classification of the bay as eutrophic. Generally, the results of the algal index revealed that the water quality of the bay has reached a critical level. 45 59 2019/11/132019/12/132019/11/302020/02/1 1398/11/12 2020/06/62020/06/62020/06/72020/06/8 1399/3/19 پریسا ملکی P. Maleki دانشگاه گنبد کاووس ایران p.maleki1368@gmail.com رحمان پاتیمار R. Patimar دانشگاه گنبد کاووس ایران rpatimar@gmail.com حجت الله جعفریان H. Jafariyan دانشگاه گنبد کاووس ایران hojat.jafaryan@gmail.com عبدالرسول سلمان ماهینی A. Salman mahiny دانشگاه علوم کشاورزی و منابع طبیعی گرگان ایران rassoulmahiny@gmail.com رسول قربانی R. Ghorbani دانشگاه علوم کشاورزی و منابع طبیعی گرگان ایران rasulghorbani@gmail.com محمد قلی زاده M. Gholizadeh دانشگاه گنبد کاووس ایران gholizade_mohammad@yahoo.com محمد هرسیج M. Harsij دانشگاه گنبد کاووس ایران m_harsij80@yahoo.com Phytoplankton Palmer Index Gorgan Bay Organic Pollution فیتوپلانکتون شاخص پالمر خلیج گرگان آلودگی آلی 1. Abdel Hamed, M. S. 2007. Effect of algal density in bead, bead size and bead concentrations on wastewater nutrient removal. African Journal of Biotechnology 6: 1185-1191.##2. Barbour, M. T., J. Gerritsen, B. D. Snyder and J. B. Stribling. 1999. Rapid bioassessment protocols for use in streams and wadeable rivers: Periphyton, benthic macroinvertebrates and fish, Second Edition. U.S. Environmental Protection Agency, Washington D.C.##3. Bellinger, E. and D. Sigee. 2010. Algae as bioindicators. pp. 99–136, In: E. Bellinger and D. Sigee (eds.), Freshwater algae: identification and use as bioindicators. John Wiley & Sons, Chichester.##4. Carpenter, S. R., N. F. Caraco, D. L. Correll, R. W. Howarth, A. N. Sharpley and V. H. Smith. 1998. Nonpoint pollution of surface waters with phosphorus and nitrogen. 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مکان‌یابی اکوپارک در شهرستان‌های مرکزی استان اردبیل با استفاده از مدل های تحلیل چندمعیاره Ecopark Site Selection in the Central Cities of Ardabil Province, Using Multi-Criteria Analysis Models 1 1 امروزه به‌علت پیشرفت‌های صنعتی و رشد فزاینده محیط‌های شهری، ایجاد اکوپارک، به عنوان مکانی که بتواند شرایط محیط زیست طبیعی را برای بشر فراهم کند، ضروری است. هدف مطالعه حاضر مکان‌یابی تطبیقی اکوپارک در سطح شهرستان‌های اردبیل، مشکین‌شهر، سرعین، نیر و نمین با استفاده از مدل‌های تحلیل چندمعیاره است. در راستای رسیدن به اهداف پژوهش، ابتدا چهار معیار و 15 زیرمعیار به‌عنوان عوامل مؤثر بر مکان‌یابی اکوپارک شناسایی شدند. سپس برای وزن‌دهی عوامل، از روش فرایند تحلیل شبکه‌ای (ANP) و برای تحلیل مدل نهایی از روش میانگین¬گیری وزن¬دار ترتیبی (OWA) به‌عنوان یکی از روش‌های تصمیم‌گیری چندمعیاره استفاده شد. نتایج حاصل از وزن‌دهی معیارها نشان داد که معیار فاصله از رودخانه‌ها بیشترین مقدار ضریب وزنی را به خود اختصاص داده است. برای انتخاب مکان مناسب اکوپارک، محدوده مورد مطالعه به چهار گروه از توان بالا تا فاقد توان طبقه‌بندی شد که ۱۳۰۸۱۵ هکتار از مساحت محدوده در طبقه با توان زیاد و ۱۶۷۲۱۳ هکتار در طبقه با توان متوسط قرار دارد. مناطقی که به‌عنوان نقاط با توان بالا جهت ایجاد اکو پارک شناسایی شدند، به‌طور عمده در کاربری‌های جنگل، مراتع متوسط و باغات قرار دارند. این مناطق، بیشتر در نزدیکی یکی از رودخانه‌های دائمی و بزرگ استان قرار گرفته‌اند. با توجه به نتایج مطالعه، بخش‌های جنوبی مشکین‌شهر و شمال کوه سبلان به‌علت وجود جاذبه‌های متنوع طبیعی و انسانی و داشتن محیط بکر به‌عنوان مناسب‌ترین مکان جهت ایجاد اکوپارک انتخاب شد. 2 Today, due to industrial advances and the expansion of urban environments, it is essential to create ecoparks as places that can provide natural environments for human. The current study performed a comparative ecopark site selection across Ardabil, Meshkinshahr, Sarein, Nir and Namin, using multi-criteria analysis models. To achieve the research objective, four criteria and 15 sub-criteria were identified, as effective factors on ecopark site selection in the region. The analytic network process (ANP) was used to weigh the factors and ordered weighted average (OWA) was employed, as a multi-criteria decision making method, to analyse the final model. Results of the weighting approach showed that distance from rivers accounted for the highest weight coefficient. To select suitable places for ecopark, the study area was classified into four groups of high to low land suitability, including 130815 hectares of high and 167213 hectares of moderate suitability. Lands with high suitablity were mainly located in forests, fair rangelands and orchards. In addition, suitable areas were mostly located near one of the large and permanent rivers of the province. Based on the results, southern parts of Meshkinshahr and the north of Sabalan Mountain were selected as the most suitable areas for ecopark, due to the existence of various natural and human attractions and having a pristine environment.   61 79 2019/11/132019/12/132019/11/302020/02/12019/12/18 1398/9/27 2020/06/62020/06/62020/06/72020/06/82020/06/11 1399/3/22 صیاد اصغری سراسکانرود S. Asghari saraskanroud دانشگاه محقق اردبیلی ایران s.asghari@uma.ac.ir مهدی فعال نذیری M. Faal naziri دانشگاه محقق اردبیلی ایران mehdifn1373@gmail.com الناز پیروزی E. Pirouzi دانشگاه محقق اردبیلی ایران piroozielnaz@gmail.com Site selection Ecopark Multi-criteria analysis Object-oriented classification Ardabil province مکان‌یابی اکوپارک تحلیل چندمعیاره طبقه‌بندی شیء‌گرا استان اردبیل 1. Abbaspour, M. 2007. The position of renewable energy to achieve sustainable development with a focus on green economy in the Islamic Republic of Iran. In: Energy, Environment and Sustainable Development. 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Locating ecopark in Isfahan Province. Applied Ecology 8(2): 47-59. (In Farsi).##8. Faraji Sabokbar, H. A., M. Salmani, F. Fereyduni, H. Karimzadeh and H. Rahimi. 2010. Location of rural landfill sanitation using Network Analysis Process Model (ANP), case study: rural areas of Quchan City. Quarterly Journal of Teacher of Humanities 14 (1): 127-149. (In Farsi).##9. Feizizadeh, J., B. Nazimfar and F. Hossein. 2008. The use of remote sensing data in detecting urban land use changes, Case study of Tabriz green space. Journal of Fine Arts 34: 17-24. (In Farsi).##10. Geology. 2019. American Geological Site. Available online at: https://earthexplorer.usgs.gov/. Accessed 27 june 2019.##11. Georgiou, A. G. and D. Skarlatos. 2017. Optimal site selection for sitting a solar park using multi-criteria decision analysis and geographical information systems. Geoscientific Instrumentation Method and Data Systems 5: 321-332.##12. Huete, A. R. 1988. A soil-adjusted vegetation index SAVI. 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Geographical Space of Ahar 60: 39-54. (In Farsi).##18. Mirzaei, F. 2015. Importance of the relationship between healthy environment and recycling of waste with tourist attraction through ecopark creation. The First National Conference on Tourism, Geography and Clean Environment. Hamedan, Iran. pp. 22-37. (In Farsi).##19. Momeni, M. and A. Sharifi Saleem. 2011. Models and softwares for multi-criteria decision-making. Authors publication, Tehran. (In Farsi).##20. Movahed, S., H. A. Laghaee and F. Habib. 2016. Designing ecological park: a step towards environmental sustainability of cities (Case study: the Southwest mountains of Mashhad). Journal of Environmental Science and Technology 18(2): 203-221.##21. Norouzi, R., H. A. Laghaee and H. Bahmanpour. 2015. Urban ecopark site selection for design, development and equipping using AHP method (case study: Torbat Heydarieh Ecopark). The First International Conference and the Third National Conference on Architecture, Construction & Urban Environment. Hamedan, Iran. pp. 64-88. (In Farsi).##22. Piran, H., R. Maleknia, H. Akbari, J. Soosani and O. Karami. 2013. Site selection for local forest park using analytic hierarchy process and geographic information system (case study: Badreh County). International Research Journal of Applied and Basic Sciences 6(7): 930-935.##23. Qi, J., A. Chehbouni, A. R. Huete, Y. H. Kerr and S. Sorooshian. 1994. A modified soil adjusted vegetation index. Journal of Remote Sensing of Environment 48: 119-126.##24. Rahnama, M. 2009. Research on urban ecoparks. Journal of Environmental Management 3: 243-245. (In Farsi).##25. Richardson, A. J. and C. L. Wieg. 1977. Distinguishing vegetation from soil background information. Photogrammetric Engineering & Remote Sensing 43: 154-168.##26. Roknaddin Eftekhari, A., H. Sajasi Gheidari, M. Pourtaheri and A. Azar. 2013. 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ارزیابی و اولویت‌بندی معیارهای مؤثر بر انتخاب گونه‌‌های سیمای سرزمین با استفاده از سیستم‌‌های تصمیم‌‌گیری چند معیاره Evaluation and Prioritization of Criteria Affecting the Selection of Landscape Species, Using Multi-Criteria Decision-Making Systems 1 1 پیچیدگی سامانه¬های طبیعی، گستردگی مقیاس بحران‌‌های تنوع زیستی و کمبود بودجه، ارائه برنامه‌‌های حفاظتی برای همه گونه‌‌های یک بوم‌‌سازگان را ناممکن ساخته است. اولویت‌‌بندی حفاظتی گونه‌‌ها این مشکل را تا حد زیادی کم¬رنگ می‌‌نماید. برای اولویت‌‌بندی گونه‌‌ها می‌‌توان از معیارهای متعددی استفاده کرد که در برخی موارد بین این معیارها همبستگی وجود دارد. بنابراین، ارزیابی دقیق معیارها یک مسئله تصمیم‌‌گیری چندمعیاره است. مطالعه حاضر که مکمّل پژوهش پیشین ما در خصوص انتخاب گونه‌‌های سیمای سرزمین در مناطق مرکزی ایران است، به بیان جزئیات روش تلفیقی دیمتل و فرایند تحلیل شبکه‌ای (DANP)به منظور ارزیابی معیارهای مورد استفاده در فرایند انتخاب گونه‌‌های سیمای سرزمین می‌‌پردازد. بررسی روابط علّت و معلولی و ارزش¬گذاری معیارها نشان داد که اندازه گستره خانگی تاثیرگذارترین و دسترسی به اطلاعات و قابلیت پایش تاثیرپذیرترین معیارها می‌‌باشند. همچنین، زیرمعیارهای تضاد با منافع انسانی، آسیب‌‌پذیری نسبت به تغییرات اقلیمی، و سطح زیستگاه‌‌های اشغال شده به ترتیب بالاترین اولویت‌‌ها را در انتخاب گونه‌‌های سیمای سرزمین دارند. بر اساس نتایج به¬دست آمده می‌‌توان استنباط نمود که سیستم‌‌های تصمیم‌‌گیری چندمعیاره به شکل مؤثری امکان ارزیابی معیارهای منتخب برای اولویت‌‌بندی حفاظتی گونه‌‌ها را فراهم می‌‌آورد. چارچوب ارائه شده در این مقاله می‌‌تواند به¬عنوان دستورالعملی برای اولویت‌‌بندی حفاظتی گونه‌‌ها با هدف حفاظت مکان-محور به¬کار گرفته شود. 2 It is impractical to implement conservation efforts for all species due to complexity of natural systems, large scale of biodiversity issues, and budget limitations. Prioritizing species of conservation importance can alleviate this issue. Multiple interrelated criteria may be used for conservation prioritization of species. Therefore, the accurate evaluation of criteria is a multi-criteria decision-making problem. In the current paper, which is a complementary study to our previous work on identifying landscape species in central Iran, we aimed to provide more details about the integrated DEMATEL Analytical Network Process (DANP) for evaluating the criteria used for the process of selecting landscape species. The impact-relation map implied that home range size had the greatest effect on other criteria and the feasibility of monitoring received the most impact from other criteria. Also, conflict with human, vulnerability to climate change, and extent of occurrence have the highest priorities for selecting landscape species. Based on our findings, multi-criteria decision making systems effectively evaluate the interrelationships between the criteria affecting the selection process of species and rank the criteria according to their impacts. This framework can be used as a guideline for prioritizing species to increase the efficiency of site-based conservation efforts. 81 96 2019/11/132019/12/132019/11/302020/02/12019/12/182019/12/4 1398/9/13 2020/06/62020/06/62020/06/72020/06/82020/06/112020/07/13 1399/4/23 رسول خسروی R. Khosravi دانشگاه شیراز ایران r-khosravi@shirazu.ac.ir محمودرضا همامی M. R. Hemami دانشگاه صنعتی اصفهان ایران mrhemami@cc.iut.ac.ir Multi-criteria decision-making Analytic network process (ANP) Carnivores Landscape species DANP DEMATEL فرایند تحلیل شبکه (ANP) گوشت‌خواران گونه‌های سیمای سرزمین DANP DEMATEL 1. Ahmadi, M., B. Nezami Balouchi, H. Jowkar, M. R. Hemami, D. Fadakar, S. Malakouti-Khah and S. Ostrowski. 2017. 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