| تعداد نشریات | 284 |
| تعداد نشریات سازمان | 82 |
| تعداد شماره‌ها | 3,081 |
| تعداد مقالات | 34,377 |
| تعداد مشاهده مقاله | 48,030,477 |
| تعداد دریافت فایل اصل مقاله | 78,935,470 |
پیش‌بینی مناطق مناسب رویش گونه آنغوزه (Ferula assa-foetida L.) در شمال‌شرق ایران با استفاده از مدل بیشینه آنتروپی | ||
| تحقیقات مرتع و بیابان ایران | ||
| مقاله 15، دوره 28، شماره 3، مهر 1400، صفحه 578-592 اصل مقاله (853.29 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/ijrdr.2021.125016 | ||
| نویسندگان | ||
| جواد مومنی دمنه1؛ یحیی اسماعیل‌پور* 2؛ حمید غلامی3؛ آزیتا فراشی4 | ||
| 1دانشجوی دکترای بیابان‌زدایی، گروه منابع طبیعی، دانشکده منابع طبیعی و علوم زمین، دانشگاه هرمزگان، بندرعباس، ایران | ||
| 2استادیار، گروه مهندسی منابع طبیعی، دانشکده کشاورزی و منابع طبیعی، دانشگاه هرمزگان، ایران | ||
| 3دانشیار، گروه مرتع و آبخیزداری، دانشکده مهندسی کشاورزی و منابع طبیعی، دانشگاه هرمزگان، بندرعباس، ایران | ||
| 4دانشیار، گروه محیط‌زیست، دانشکده منابع طبیعی و محیط‌زیست، دانشگاه فردوسی مشهد، ایران | ||
| چکیده | ||
| آنغوزه به‌عنوان یکی از مهمترین گیاهان خودروی مرتعی در منطقه شمال‌شرق ایران، اهمیت زیادی در حفاظت خاک و اقتصاد بهره‌برداران مراتع دارد. باوجوداین بهره‌برداری نادرست و تخریب زیستگاه‌های آن ازجمله عوامل تهدید کننده این سرمایه طبیعی است. این پژوهش به‌منظور شناسایی رویشگاه‌های بالقوه این گونه در دو استان خراسان رضوی و خراسان شمالی که می‌تواند گامی برای تسهیل و توسعه عملیات بازکاشت و احیاء این گونه به حساب آید، انجام شد. داده‌های مکانی حضور این گونه با اندازه پیکسل ۱۱۰۰*۱۱۰۰ متر به‌عنوان مکان‌های مناسب بالفعل برای رویش آن و لایه‌های اطلاعات محیطی از قبیل اقلیم، خاک، زمین‌شناسی و فیزیوگرافی به‌عنوان متغیرهای پیش‌بینی مورد استفاده قرار گرفت. ابتدا در نرم‌افزار بیومپر نسخه 4 همبستگی متغیرهای پیش‌بینی بررسی و متغیرهای مستقل انتخاب شدند. سپس نقشه رویشگاه بالقوه حاصل از مدل پراکنش گونه با استفاده از نرم‌افزار 3.3Maxent ایجاد شد. نتایج نشان داد که مدل استفاده شده از دقت مناسب برخوردار بوده و به‌مقدار AUC برابر 97/0 دست یافته است. از نظر میزان اهمیت، بررسی متغیرهای ورودی به مدل با استفاده از آزمون جک‌نایف، نشان داد که به‌ترتیب اجزاء واحد اراضی، دمای فصلی، سازند زمین‌شناسی، شیب غالب اراضی، ارتفاع زیستگاه و متوسط روزانه دما در مناسب بودن رویشگاه بالقوه گونه آنغوزه در سطح منطقه مورد مطالعه بیشترین اهمیت را داشتند. نتایج این مطالعه می‌تواند در شناخت نیازهای اکولوژیک گونه مورد بررسی و توسعه و احیاء رویشگاه‌های آن به‌کار رود. | ||
| کلیدواژه‌ها | ||
| کلیدی: اقلیم؛ حداکثر آنتروپی؛ رویشگاه بالقوه؛ مدل پراکنش گونه | ||
| عنوان مقاله [English] | ||
| Properly predict the growth of (Ferula assa-foetida L.) in northeastern Iran using the maximum entropy model | ||
| نویسندگان [English] | ||
| Javad Momeni Damaneh1؛ Yahya Esmaeilpour2؛ Hamid Gholami3؛ Azita Farashi4 | ||
| 1Ph.D. Student of Desert Management, Department of Natural Resources Engineering, Faculty of Agriculture & Natural Resources, University of Hormozgan, BandarAbbas, Iran | ||
| 2Assistant Professor, Department of Natural Resources Engineering, Faculty of Agriculture & Natural Resources, University of Hormozgan, Iran | ||
| 3Associate Professor, Department of Natural Resources Engineering, Faculty of Agriculture & Natural Resources, University of Hormozgan, BandarAbbas, Iran | ||
| 4Associate Professor, Department of Environment, Faculty of Natural Resource and Environment Engineering, Ferdowsi University of Mashhad, Mashhad, Iran | ||
| چکیده [English] | ||
| Ferula assa-foiteda L., as one of the most important range plants in northeastern Iran, plays an important role in soil conservation and the economy of rangeland stockholder. However, misuse and destruction of its habitats are among the factors threatening this natural capital. This study was conducted to identify potential habitats of this species in the two provinces of Khorasan Razavi and North Khorasan, which can be a step towards to facilitate and develop replanting and rehabilitation operations of this species. Spatial data of the presence of this species with a pixel size of 1100 × 1100 m were used as actual suitable places for its growth and layers of environmental information such as climate, soil, geology and physiography were used as predictor variables. First, in Biomaper Version 4, the correlation of prediction variables was examined and independent variables were selected. The potential habitat areas extracted from the species distribution model mapped with the Maxent 3.3 software. The results showed that the used model had good accuracy and reached to AUC of 0.97. In terms of significance, the study of input variables to the model using the Jackknife test showed that, respectively, land unit components, seasonal temperature, geological formation, dominant land slope, habitat height and daily average temperature are suitable for the potential habitat of Ferula assa-foiteda L. species in the level of the study area is of the utmost importance. The results of this study can be used to identify the ecological needs of the species (Ferula assa-foiteda L.) and to develop and rehabilitate their habitats. | ||
| کلیدواژه‌ها [English] | ||
| Climate, maximum entropy, potential habitat, species distribution model | ||
| مراجع | ||
|
Boyce, M. S., 2006. Scale for resource selection functions. Journal of Diversity and Distributions, 12(3): 269-276. Dirnböck, T., Essl, F. and Rabitsch, W., 2011. Disproportional risk for habitat loss of high-altitude endemic species under climate change. Journal of Global Change Biology, 17(2): 990-996. Elith, J., Kearney, M. and Phillips, S., 2010. The art of modeling range-shifting species. Journal of Methods in ecology and evolution, 1(4): 330-342. Elith, J., Phillips, S. J., Hastie, T., Dudík, M., Chee, Y. E. and Yates, C. J., 2011. A statistical explanation of MaxEnt for ecologists. Journal of Diversity and distributions, 17(1): 43-57. Ghafari, S., Ghorbani, A., Moammeri, M., Mostafazadeh, R., Bidar Lord, M. and Kake Mami, A., 2019. Modeling and determining effective factors in distribution of Festuca ovina using Maxent in rangelands of northern Ardabil province. Iranian journal of Range and Desert Research, 27(3): 433-462. Ghareghan, F., Ghanbarian, G., Pourghasemi, H. R. and Safaeian, R., 2020. Prediction of habitat suitability of Morina persica L. species using artificial intelligence techniques. Journal of Ecological Indicators, 112: 106096. Helm, A., Hanski, I. and Pärtel, M., 2006. Slow response of plant species richness to habitat loss and fragmentation. Journal of Ecology letters, 9(1): 72-77. Hijmans, R. J., 2004. Arc Macro Language (AML®) version 2.1 for calculating 19 bioclimatic predictors: Berkeley, Calif, Museum of Vertebrate Zoology, University of California at Berkeley. Available at http://www.worldclim.org/bioclim. Hirzel, A. H., Hausser, J., Chessel, D. and Perrin, N., 2002. Ecological niche factor analysis: how to compute habitat suitability maps without absence data. Journal of Ecology, 83(7): 2027-2036. Hosseini, S. Z., Kappas, M., Chahouki, M. Z., Gerold, G., Erasmi, S. and Emam, A. R., 2013. Modelling potential habitats for Artemisia sieberi and Artemisia aucheri in Poshtkouh area, central Iran using the maximum entropy model and geostatistics. Ecological Informatics, 18: 61-68. Iranshahy, M. and Iranshahi, M., 2011. Traditional uses, phytochemistry and pharmacology of asafoetida (Ferula assa-foetida oleo-gum-resin)—A review. Journal of Ethnopharmacology, 134(1): 1-10. Jarvie, S. and Svenning, J. C., 2018. Using species distribution modeling to determine opportunities for trophic rewilding under future scenarios of climate change. Philosophical Transactions of the Royal Society B. Biological Sciences, 373(1761): 20170446. Kajimoto, T., Yahiro, K. and Nohara, T., 1989. Sesquiterpenoid and disulphide derivatives from Ferula assa-foetida. Journal of Phytochemistry, 28(6): 1761-1763. Kavoosi, G. and Rowshan, V., 2013. Chemical composition, antioxidant and antimicrobial activities of essential oil obtained from Ferula assa-foetida oleo-gum-resin: effect of collection time. Journal of Food chemistry, 138(4): 2180-2187. Keshtkar, H. R., Azarnivand, H. and Atashi, H., 2009. Effect of prechilling and GA3 on seed germination of Ferula assa-foetida and Prangos ferulacea. Journal of Seed Science and Technology, 37(2): 464-468. Keyghobadi, M., Piri Sahragard, H., Pahlavan Rad, M., Karami, P. and yari, R., 2020. Application of generalized additive model and classification and regression tree to estimate potential habitat distribution of range plant species (Case Study: Khazri Rangelands of Beyaz Plain, Southern Khorasan). Iranian journal of Range and Desert Research, 27(3): 561-576. Khajeh, M., Yamini, Y., Bahramifar, N., Sefidkon, F. and Pirmoradei, M. R., 2005. Comparison of essential oils compositions of Ferula assa-foetida obtained by supercritical carbon dioxide extraction and hydro-distillation methods. Journal of Food chemistry, 91(4): 639-644. Khalasi Ahwazi, L., Zare Chahouki, M. A. and Hosseini, S, Z., 2015. Modeling geographic distribution of Artemisia sieberi and Artemisia aucheriusing presence-only modelling methods (MAXENT & ENFA). Journal of Renewable Natural Resources Research, 6 (1): 57 – 73. Kumar, S. and Stohlgren, T.J., 2009. Maxent modeling for predicting suitable habitat for threatened and endangered tree Canacomyrica monticola in New Caledonia. Journal of Ecology and Natural Environment, 1(4): 94-98. Lemke, D., Hulme, P.E., Brown, J.A. and Tadesse, W., 2011. Distribution modeling of Japanese honeysuckle (Lonicera japonica) invasion in the Cumberland Plateau and Mountain Region, USA. Journal of Forest Ecology and Management, 262(2): 139-149. Moghaddam, M. and Farhadi, N., 2015. Influence of environmental and genetic factors on resin yield, essential oil content and chemical composition of Ferula assa-foetida L. populations. Journal of Applied Research on Medicinal and Aromatic Plants, 2(3): 69-76. Molaei, M., Ghorbani, A., Moameri, M. and Hossainzadeh, A., 2020. Habitat prediction of Artemisia fragrans Willd. and A. chamaemelifolia Vill. in elevation gradient of Ghezelozan-Aghdagh, Khalkhal. Iranian journal of Range and Desert Research, 27(3):545-560. Morovati, M., Karami, M., Kaboli, M., Rousta, Z. and Shorakaei, M., 2015. Modeling the habitat suitability of Ovis orientalis, the most important prey of cheetah (Acinonyx jubatus venaticus) Using Maximum Entropy method In Dareh Anjir Wildlife Refuge. Journal of Animal Environment, 6(4): 135-139. Phillips, S.J., Anderson, R.P. and Schapire, R.E., 2006. Maximum entropy modeling of species geographic distributions. Journal of Ecological modeling, 190(3): 231-259. Phillips, S.J., Dudık, M. and Schapire, R.E., 2009. A maximum entropy approach to species distribution modeling. In: Proceedings of the 21st International Conference on Machine Learning, ACMPress, New York, 655–662. Radnezhad, H., Moshtaghie, M., Amoeian, I. and Jamali, A., 2016. 'Modeling the distribution of (Gazella subgutturosa) in Bamoo National Park with maximum entropy methods: (MAXENT)'. Journal of Animal Environment, 8(2):17-24. Rajabian, T., Saboura, A., Hasani, B. and Falah, H. H., 2007. Effects of GA3 and chilling on seed germination of Ferula assa-foetida, as a medicinal plant. Iranian journal of medicinal and aromatic plants, 23 (3): 391-404. Raney, P. A. and Leopold, D. J., 2018. Fantastic wetlands and where to find them: modeling rich fen distribution in New York State with Maxent. Journal of Wetlands, 38(1): 81-93. Ray, D., Behera, M. D. and Jacob, J., 2017. Evaluating ecological niche models: A comparison between Maxent and GARP for predicting distribution of Hevea brasiliensis in India. Proceedings of the National Academy of Sciences, India Section B: Biological Sciences, 88(4), 1337-1343. Saadatfar, A., Tavassolian, I. and Hossein Jafari, S., 2019. Determination potential habitats of Ferula assa foetida medicinal herb using analytical hierarchy process (AHP) and GIS (Case study: Chatrod region, Kerman). RS & GIS for Natural Resources, 9 (4): 139-155. Silva, L., Dutra, L., Costa, H., Azevedo, E., Medeiros, V., Alves, M. and Elias, R., 2017. Modelling native and invasive woody species: A comparison of Enfa and Maxent applied to the Azorean Forest. International Conference on Dynamics, Games and Science: Springer,. https://doi.org/ 10.1007/978-3-319-55236-1_20. Sweet, J.A., 1988. Measuring the accuracy of a diagnostic systems. Science 240, 1285-1293. Thorn, J. S. V., Nijman, D. and Smith Nekaris, K. A. I., 2009. Ecological niche modeling as a technique for assessing threats and setting conservation priorities for Asian slow lorises (Primates: Nycticebus). Diversity and Distributions, 15(2): 289-298. Webber, B. L., Yates, C. J., Le Maitre, D. C., Scott, J. K., Kriticos, D. J., Ota, N. and Midgley, G. F., 2011. Modeling horses for novel climate courses: insights from projecting potential distributions of native and alien Australian acacias with correlative and mechanistic models. Diversity and Distributions, 17(5): 978-1000. Xue-Qing Yang, S.P.S., Kushwaha, S. S. and Jianchu Xu, P.S. R., 2013. Maxent modeling for predicting the potential distribution of medicinal plant, Justicia adhatoda L. in Lesser Himalayan foothills. Ecological Engineering, 51: 83-87. Zarabi, M., Haghdadi, R. and Yousefi, H., 2018. Modeling the suitability of organic (wild) pistachio (Pistacia vera) habitat using MaxEnt entropy method in Sarakhs forest area (under Gonbadli basin of Khorasan Razavi province). Journal of Echohydrology, 4 (3): 817-824p. Zare Chahouki, M.A., Azarnivand, H., Jafari, M., and Tavili, A., 2010. Multivariate statistical methods as a tool for model based prediction of vegetation types. Russian Journal of Ecology, 41 (1): 84–94. Zare Chahouki, M.A. and Abbasi, M., 2016. Modeling the habitat suitability of Stipa barbata using ecological nest factor analysis method Case study: Middle Taleghan rangelands. Journal of Iranian natural ecosystems, 7(4):1-16. Zare, A. R., Solouki, M., Omidi, M., Irvani, N., Abasabadi, A. O. and Nezad, N. M., 2011. Effect of various treatments on seed germination and dormancy breaking in Ferula assa foetida L. (Asafetida), a threatened medicinal herb. Trakia journal of sciences, 9(2): 57-61. | ||
|
آمار تعداد مشاهده مقاله: 796 تعداد دریافت فایل اصل مقاله: 725 |
||