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اثر تغییر اقلیم بر پراکنش رویشگاه گونه Platychaete aucheri. Boiss در استان سیستان و بلوچستان بر پایه مدل پیش‌بینی اقلیم | ||
| تحقیقات مرتع و بیابان ایران | ||
| مقاله 6، دوره 31، شماره 3، مهر 1403، صفحه 284-300 اصل مقاله (1.05 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/ijrdr.2024.132036 | ||
| نویسندگان | ||
| معصومه ناروئی* 1؛ مرتضی خداقلی2؛ راضیه صبوحی3 | ||
| 1محقق، بخش تحقیقات جنگل و مرتع، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی بلوچستان، سازمان تحقیقات، آموزش و ترویج کشاورزی، ایرانشهر، ایران | ||
| 2استاد پژوهش، بخش تحقیقات مرتع، موسسه تحقیقات جنگل ها و مراتع کشور، سازمان تحقیقات ، آموزش و ترویج کشاورزی، تهران، ایران | ||
| 3دکترای علوم مرتع، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان اصفهان، سازمان تحقیقات، آموزش و ترویج کشاورزی، اصفهان، ایران. | ||
| چکیده | ||
| سابقه و هدف: شناخت عوامل محیطی مؤثر در استقرار پوشش گیاهی، میتواند به مدیریت صحیح اکوسیستم‌های مرتعی کمک کند. رویشگاه مطلوب، تأثیر به سزایی بر بقا و تولیدمثل گونه ها دارد. آشکارسازی تغییرات پارامترهای اقلیمی، بیانگر آن است که تغییرات اقلیمی در ایران شروع شده و ضرورت دارد که رویشگاه بالقوه گونههای شاخص، در حال حاضر و سال‌‌های آینده، تحت مدل‌‌های هشدار اقلیمی، مشخص گردد. با پیشرفت علم آمار و سیستم اطلاعات جغرافیایی، پیش‌بینی رویشگاه گونههای گیاهی با استفاده از روش های مدل‌سازی ، میسر شده است. ازاین‌رو، این پژوهش با هدف تهیه نقشه پیش‌بینی رویشگاه‌های گونه Platychaete aucheri بر پایه مدل پیش‌بینی اقلیمی، در استان سیستان و بلوچستان انجام شد. مواد و روشها: ابتدا با استفاده از 8 ایستگاه سینوپتیک داخل و مناطق مجاور، پایگاه داده‌ها شامل متغیرهای بارش، دمای شبانه، دمای روزانه و متوسط دما، از سال تاسیس هر ایستگاه تا سال 2019 تشکیل و 19سنجه اقلیمی محاسبه شد. همچنین با استفاده از مدل رقومی ارتفاع با دقت 30 متر، سه متغیر فیزیوگرافی شامل شیب، جهت و ارتفاع تهیه گردید. سپس با استفاده از نقشه‌های بهنگام شده طرح شناخت مناطق اکولوژیک و بازدیدهای میدانی، نقاط حضور و غیاب گونه P.aucheri مشخص شد. اساس تجزیه و تحلیل به کار برده شده در این تحقیق را رگرسیون لجستیک تشکیل می‌دهد که بر اساس مقادیر محیط زیستی مربوط به نقاط حضور و غیاب گونه می‌باشد. با استفاده از رگرسیون لجستیک، رفتار رویش این گونه در منطقه سیستان و بلوچستان مشخص و نقشه مدل‌سازی شده و معادلات مربوطه در شرایط کنونی محاسبه شد. پس از اطمینان از کارآمد بودن مدل، از داده‌های اقلیمی پیش‌بینی شده توسط مدل گردش عمومی MRI-ESM2-0تحت سناریو 5/4 و 5/8 استفاده گردید و با استفاده از معادلات فعلی و قرار دادن داده‌های استخراج شده ازپایگاه، Worldclimeنقشه پراکنش آینده گونه P.aucheriبرای سال 2050 تحت سناریوهای اقلیمی RCP4.5وRCP8.5تولیدگردید. بدین صورت که در مرحله تعریف مدل رگرسیون لجستیک در ArcGIS، به جای نقشه متغیرهای اقلیمی که در مدل وجود دارند نقشه‌های همان متغیرها که برای سال 2050 پیش‌بینی شده‌اند، جایگذاری گردیدند. نتایج: نتایج حاصل از نقشه‌های بالقوه نشان داد که پراکنش فعلی گونه، P.aucheriدر بخش‌های مرکزی و جنوبی حضور پر رنگ‌تری داشته و با حرکت به سمت مناطق شمالی از درصد حضور گونه کاسته شده است. سطح رویشگاه مناسب (احتمال وقوع بیشتر از 75 درصد) گونه P.aucheri در استان معادل 12873269 هکتار ، تقریبا 71 درصد می‌باشد. ارزشیابی مدل با استفاده از داده‌های حضور و عدم حضور گونه و با استفاده از ضریب آماری کاپا انجام شد در این ارتباط مقدار ضریب آماری کاپا 85/0به دست آمد که با توجه به طبقه بندی ارائه شده از ضرایب کاپا، مدل از دقت خوب و قابل قبولی برخوردار است. نقشه‌های حاصل از پیش‌بینی مدل رگرسیون لجستیک نشان می‌دهد که سطح رویشگاه گونه P.aucheri در سال 2050 تحت هر دو سناریو RCP4.5 و RCP8.5افزایش چشمگیری خواهد یافت و در احتمال وقوع بیشتر از 75 درصد مشاهده می‌شود که مساحت رویشگاه گونه P.aucheri در استان به ترتیب برابر 15506391 و 17788376 هکتار خواهد شد که به ترتیب سطحی معادل3/85 و 85/97 درصد را به خود اختصاص خواهد داد. تحت سناریوRCP8.5 احتمال وقوع حضور گونه به شدت افزایش خواهد یافت و مشاهده می‌شود که احتمال حضور این گونه در طبقات پایین 50 درصد به صفر می‌رسد. نتیجه گیری: در مجموع، تغییر اقلیم و به تبع آن افزایش شاخصه‌‌های دمایی، باعث حفظ رویشگاه فعلی، افزایش احتمال حضور گونه در سطح کل استان و گسترش عمودی گونه P.aucheri و حرکت آن به سمت عرض‌‌های جغرافیایی بالاتر در امتداد گرادیان ارتفاعی منطقه، خواهد شد. از این رو، حد بالای مورد انتظار گستره رویشی گونه P.aucheri، طی سه دهه آینده، دستخوش تغییر قرار خواهد گرفت. | ||
| کلیدواژه‌ها | ||
| گردش عمومی جو؛ رگرسیون لجستیک؛ سناریوی اقلیمی؛ اکوسیستم‌های مرتعی | ||
| عنوان مقاله [English] | ||
| The effect of climate change on the habitat distribution of Platychaete aucheri. Boiss species in Sistan and Baluchestan province based on climate prediction model | ||
| نویسندگان [English] | ||
| Masome Narouei1؛ Morteza Khodagholi2؛ Razieh Saboohi3 | ||
| 1Researcher, Forest and Rangeland Research Division, Baluchestan Agriculture and Natural Resources Research and Education Center, Agricultural Research Education and Extension Organization (AREEO), Iranshahr, Iran | ||
| 2Research Professor, Rangeland Research Division, Research Institute of Forests and Rangelands, Agricultural Research Education and Extension Organization (AREEO), Tehran, Iran | ||
| 3Ph.D. of Range Management, Isfahan Agriculture and Natural Resources Research and Education Center, Agricultural Research Education and Extension Organization (AREEO), Isfahan, Iran | ||
| چکیده [English] | ||
| Abstract Background and objectives: Knowing the effective environmental factors in the establishment of vegetation can help the proper management of pasture ecosystems. A suitable habitat has a significant effect on the survival and reproduction of species. Revealing changes in climate parameters indicates that climate changes have started in Iran and it is necessary to determine the potential habitats of indicator species, now and in the coming years, under climate warning models. With the advancement of statistics and geographic information system, it has become possible to predict the habitat of plant species using modeling methods. Therefore, this research was conducted with the aim of preparing a forecast map of Platychaete aucheri habitats based on the climate forecast model in Sistan and Baluchestan province. Methodology: First, using 8 synoptic stations inside and nearby areas, the database including precipitation variables, night temperature, daily temperature and average temperature, from the year of establishment of each station until 2019, and 19 climate parameters were calculated. Also, three physiographic variables, including slope, direction and height, were prepared using a digital height model with an accuracy of 30 meters. Then, by using the updated maps of the ecological zones recognition plan and field visits, the presence and absence points of P.aucheri species were determined. The basis of the analysis used in this research is logistic regression, which is based on environmental values related to the presence and absence of species. Using logistic regression, the growth behavior of this species in Sistan and Baluchestan region was determined and the map was modeled and the relevant equations were calculated in the current conditions. After ensuring the efficiency of the model, the climate data predicted by the general circulation model MRI-ESM2-0 were used under the scenarios 4.5 and 8.5, and by using the current equations and placing the data extracted from the database, Worldclime, the future distribution map of the species P.aucheri was produced for 2050 under RCP4.5 and RCP8.5 climate scenarios. In this way, at the stage of defining the logistic regression model in ArcGIS, instead of the map of the climate variables that exist in the model, the maps of the same variables predicted for the year 2050 were placed. Results: The results of the potential maps showed that the current distribution of the species, P.aucheri, had a more colorful presence in the central and southern parts, and the percentage of the presence of the species decreased by moving towards the northern regions. The area of suitable habitat (probability of occurrence greater than 75%) of P.aucheri species in the province is equal to 12873269 hectares, approximately 71%. The evaluation of the model was done using the data of the presence and absence of the species and using the Kappa statistical coefficient. In this connection, the value of the Kappa statistical coefficient was obtained as 0.85, which according to the presented classification of the Kappa coefficients, the model has good and acceptable accuracy. It is acceptable. The maps resulting from the prediction of the logistic regression model show that the habitat area of P.aucheri species will increase significantly in 2050 under both RCP4.5 and RCP8.5 scenarios, and it is observed that the habitat area of P.aucheri species is more than 75% more likely to occur. In the province, it will be equal to 15506391 and 17788376 hectares, respectively, which will occupy a surface equivalent to 85.3 and 97.85%, respectively. Under the RCP8.5 scenario, the probability of the presence of the species will increase greatly, and it can be seen that the probability of the presence of this species in the lower floors reaches 50% to zero. Conclusion: In general, climate change and the consequent increase in temperature indicators will preserve the current habitat, increase the probability of the presence of the species in the entire province, and the vertical expansion of the P.aucheri species and its movement to higher latitudes along the altitude gradient of the region. Therefore, the expected upper limit of the vegetative range of P. aucheri species will undergo changes during the next three decades. | ||
| کلیدواژه‌ها [English] | ||
| Atmospheric general circulation, Logistic regression, Climate scenario, Grassland ecosystems | ||
| مراجع | ||
|
Abolmaali, S.M.R., Tarkesh Esfahani, M. and Bashri, H., 2017. Assessing impacts of climate change onendangered Kelossia odoratissima Mozaff species distribution using Generalized Additive Model. Journal of Natural Environment, 70(2): 243-254. doi: 10.22059/jne.2017.63853 (In Persian).
Abolmaali, S.M.R., Tarkesh, M. and Bashari, H., 2018. MaxEnt modeling for predicting suitable habitats and identifying the effects of climate change on a threatened species, Daphne mucronata, in central Iran. Ecological Informatics, 43: 116-123. doi: 10.1016/j.ecoinf.2017.10.002
Akhani, H., 2007. Diversity, biogeography and photosynthetic pathways of Argusia and Heliotropium (Boraginaceae) in South-West Asia with an analysis of phytogeographical units. Botanical Journal of the Linnean Society, 155: 401-425. doi: 10.11111/j.1095-8339.2007.00707
Beaumont, L.J., Hughes, L. and Poulsen, M., 2005. Predicting species distributions: use of climatic parameters in BIOCLIM and its impact on predictions of species’ current and future distributions. Ecological Modelling, 186: 250-269. doi: 10.1016/j.ecolmodel.2005.01.030
Elith, J., Kearney, M. and Phillips, S., 2010. The art of modelling range-shifting species. Methods in Ecology and Evolution, 1(4): 330–342. doi: 10.1111/j.2041-210x.2010.00036.x
Elith, J. and Franklin, J., 2013. Species distribution modelling: 692-705. In: Levin, S. A., (Ed.). Encyclopedia of Biodiversity. Academic Press, Waltham, MA, 1216 p.
fakhimi, E. and Khodagholi, M., 2023. Effects of climate change on the vegetation range of Bromus tomentellus Boiss species in the pasture habitats of central Zagros, Chaharmahal and Bakhtiari provinces. Environmental Science Studies, 8(2): 6730-6740. doi: 10.22034/JESS.2023.380017.1949 (In Persian).
Fayaz, M., 2016. The Plan to Recognize the Ecological Regions of the Country: Plant Types of Sistan and Baluchestan Province. Research Institute of Forests and Pastures of the country, Tehran, 244 P (In Persian).
Food and Agriculture Organization of the United Nations, FAO., 2007. Adaptation to Climate Change in Agriculture, Forestry and Fisheries: Perspective, Framework and Priorities. FAO, Rome, 32p.
Ghanbarian, Gh.A. and Yazdanpanahi, Z., 2016. Autecology study of Plantychaete aucheri BOISS. in arid ecosystems, south of Fars province. Journal of Range and watershed management (Iranian Journal of Natural Resources), 68(4): 869-884. https://sid. ir/paper/ 162267/fa (In Persian).
Ghorbani, A., Samadi Khanghah, S. and Esfanjani, J., 2020. Predicting the distribution of Leucanthemum vulgare using logistic regression in Fandoghlou rangelands of Ardabil province, Iran. Journal of Rangeland Science, 10(1): 98-111.
Gray, A., 2018. The ecology of plant extinction: rates, traits and island comparisons. Oryx, 53: 424-428. doi:10.1017/S0030605318000315
Guisan, A. and Zimmermann, N.E., 2000. Predictive habitat distribution models in ecology. Ecological Modelling, 135(2): 147-186. doi: 10.1016/s0304-3800(00)00354-9
Haidarian, M., Tamartash, R., Jafarian-Jeloudari, Z., Tarkesh, M. and Tatian, M.R., 2021.The effects of climate change on the future distribution of Astragalus adscendens in Central Zagros, Iran. Journal of Rangeland Science, 11(2): 152-170. sid.ir/paper/1032457/en
Haidarian Aghakhani, M., Tamartash, R., Jafarian, Z., TarkeshEsfahani, M. and Tatian, M.R., 2017. Predicting the effects of climate change on the potential distribution of the species (Amygdalus scoparia) using consensus modeling in Central Zagros. Remote Sensing and Geographic Information System in Natural Resources, 8(3):1-14. sid.ir/paper/189530/fa (In Persian).
Hedge, I.C. and Wendelbo, P., 1978. Patterns of distribution and endemism in Iran. Notes from the Royal Botanic Garden, Edinburgh, 36: 441–464.
Heshmati, Q.A. and Karimian, V., 2014. Predictingthe richness distribution of rangeland species using environmental variables using species distribution models (SDM). Journal of Agricultural Engineering and Natural Resources, 46: 1-38. magiran.com/p1379304 (In Persian).
Hosseini, s.s., Tavili, A., Naghipoor Borj, A.A. and Khalighi Sigaroodi, Sh., 2022. Potential effects of climate change on the geographic distribution of the Hordeum bulbosum L. in the Central Zagros region, Journal of Natural Environment, 74(4): 747-758. magiran.com/p2444341 (In Persian).
Humphreys, A.M., Govaerts, R., Ficinski, S.Z., Lughadha, E.N. and Vorontsova, M.S., 2019. Global dataset shows geography and life form predict modern plant extinction and rediscovery. Nature Ecology & Evolution, 7: 1043 –1047. doi: 10.1038/s41559-019-0906-2
IPCC., 2001. Climate change 2001. In: Watson and the Core Writing Team (Eds). Synthesis Report,A Contribution of Working Groups. I, II and III to the third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK and New York, USA, 1032 p
IPCC., 2007. Climate change 2007. The physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge.
Jafarian, Z., Arzani, H., Jafari, M., Zahedi, Q. and Azarnivand, H., 2012. Preparation of spatial prediction map of plant species using Logisticregression (Case study: Rineh Rangelands, Damavand Mountain). Natural Geography Research, 44(1): 1-18. doi: 10.22059/JPHGR.2012.24731 (In Persian).
Jafari Takhtinejad, E., Asadpour, R., Soltanipour, M.A. and Tavousi, S., 2018. Investigation of the phenological stages of the kalajok species (Platychaete aucheri) in the Dehgin watershed of Hormozgan province. the 13th National Conference on Watershed Engineering and Science and the 3rd National Conference on Conservation of natural resources and the environment with a focus on watershed management and protection of natural resources and the environment, Mohaghegh Ardabili University, October 10 -11, 67-75 (In Persian).
Kamali, N., 2022 Investigating the Effect of Climate Change on Habitat of Important Rang Species Base on Climate Prediction Model in Bushehr Province. Final Report of Project ,Agricultural Research, Education & Extention Organization, Research Institute of Forests and Rangelands,Tehran,121p (In Persian).
Khajei, N., Etemad, V. and Bazrafshan, J., 2025. Predicting climate change impacts on distribution of Brant s oak trees (Quercus. brantii lindi) in the zagros foreste, Fars province. Iranian Jurnal of Forest, 15(4): 393-409. doi: 10.22034/ijf.2023.344228.1876 (In Persian).]
Khodagholi, M., Saboohi, R., Ashoori, P., Zare, N.,Borhani, M., Bayat, M., Khodahami, Q. and Jaberolansar, Z., 2022. Investigating the effect of climate change on habitat of important rang speciesbase on climate prediction model in Fars povince.Final report, Research Institute of Forests and Rangelands,Tehran,143p (In Persian).
Khodagholi, M., Saboohi, R., Bayat, M., Ashouri, P. and Motamedi, J., 2022. Effects of climate change on the habitat of Bromus tomentellus Boiss in south Zagros based on climate prediction model. Iranian Journal of Range and Desert Research, 29(4): 530-541. doi: 10.22092/ijrdr.2022.128073 (In Persian).
Krebs, C.J., 2009. Ecology: The Experimental Analysis of Distribution and Abundance. Benjamin Cummings, San Francisco. 655p.
Mehrabian, A.R., Khajoei Nasab, F. and Amini Rad, M., 2021. Distribution patterns and priorities for conservation of Iranian Endemic Monocots: determining the Areas of Endemism (AOEs). Journal of Wildlife and Biodiversity, 5(2): 69-87. doi: 10.22120/jwb.2020.136616.1188
Miri, H.R. and Rasteghar, A., 2012. Effect of CO2 enrichment on growth and competitiveness of soyben and millet against lambs auarters and pigewwd. Electronic Journal of Crop Production, 5(1): 1-18. sid.ir/paper/135147/fa (In Persian).
Motamedi, J., Khodagholi, M. and Khalifezadeh, R., 2022. Prediction of current and future potential range of Artemisia aucheri under two climate warning models (Rcp4.5 and Rcp8.5) in southern Alborz rangeland habitats, Qazvin province. Journal of Environmental Science Studies, 2: 5015-5023. doi: 10.22034/jess.2022.331331.1732 (In Persian).
Mozaffarian, V.A., Mir Vakili, M. and Farming, G.R., 2017. Flora of Iran. Publications of the Research Institute of Forests and Pastures of the Country, Tehran, 1026 p (In Persian).
Naqipour Borj, A.A., .Heydarian Aghakhani. and Sanguni, H., 2019. Application of consensus modeling method in forecasting the effects of climate change on the distribution of tulip species Vajgun (Fritilla riaimperialis L.) . Journal of Plant Research (Iranian Journal of Biology), 32(3): 747-758. dor: 20.1001.1.23832592.1398.32.3.8.5(In Persian).
Narouei, M., Javadi, S.A., Khodagholi, M., Jafari, M. and·Azizinejad, R., 2022. Modeling the effects of climate change on the potential distribution of the rangeland species Gymnocarpus decander Forssk (case study: Arid region of southeastern Iran). Environmental Monitoring and Assessment, 194(33): 359-374. doi: 10.1007/s10661-021-09657-z
NCCOI., 2014. Third national communication to UNFCCC. National Climate Change Office of Iran. Accessed on 2020-07-26, http://climate change.ir.
Parmesan, C., Gaines, S., Gonzalez, L., Kaufman, D.M., Kingsolver, J., Townsend Peterson, A. and Sagarin, R., 2005. Empirical perspectives on species borders: from traditional biogeography to global change. Oikos, 108(1): 58-75. doi: 10.1111/j.0030-1299.2005.13150.x
Pejhan, A., 2013. Effects of climate change on spatial distribution of Artemisia sieberi species in Isfahan province using species distribution prediction models (Case study: Isfahan province). Master thesis, Departeman of Rangeland, Isfahan University of Technology, Isfahan, 119p (In Persian).
Pressey, R.L., Cabeza, M., Watts, M.E., Cowling, R.M. and Wilson, K.A., 2007. Conservation planning in a changing world. Trends in Ecology & Evolution, 22(4): 583–592. doi: 10.1016/j.tree.2007.10.001
Qazi Moradi, M., Tarkash Esfahani, M., Bashari, H. and Wahhabi, M.R., 2016. Determination of potential habitat of Coma species (Festuca ovina) using generalized incremental model (GAM) in Fereydunshahr area of Isfahan province. Journal of Rangeland and Watershed Management, 69(3): 689- 377. doi: 10.22059/jrwm.2016.61509 (In Persian).
Refeldt, G.E., Crookston, N.L., Seanz Romero, C. and Campbel, E.M., 2012. North American vegetation model for Land-use planning in a changing climate: a solution to larg classification problems. Journal of Ecological Apllication, 22(2):119-141. doi: 10.1890/11-0495.1
Shabani, N., Khoshbakht, M. and Hasani, A., 2023. Predicting the effect of climate change on distribution of valerian (Valeriana sisymbriifolia) species using MaxEnt model in Isfahan province. Integrated Watershed Management, 3(2): 80-98. doi: 10.22034/iwm.2023.2007169.1093 (In Persian).
Shaver, G.R., 2000. Global warming and terrestrial ecosystems: A conceptual framework for analysis. Journal of Bioscience, 50(10): 871- 882.
Taylor, M.A., Stephenson, T.S., Anthony Chen, A. and Stephenson, K.A., 2012. Climate change and the Caribbean. Review and Response. Caribbean Studies, 40(2): 169-200. http://www.redalyc. Org/articulo.oa?id=39226915007
Thomas, L.E., Gerald, S., Rehfeldt, C. and Celestino, F., 2010. Projection of suitable habitate for rare species under global warming scenario. American Journal of Botany, 97(6): 970-987. doi: 10.3732/ajb.0900329
Tongli, W. and Elizabeth, C., 2012. Projecting future distributions of ecosystem climate niches: Uncertainties and management applications. Forest Ecology and Management, 279: 128-140. doi: 10.1016/j.foreco.2012.05.034
Williams, J.N., Seo, C.W., Thorne, J., Nelson, J.K., Erwin, S., O’Brien, J.M. and Schwartz, M.W., 2009. Using species distribution models to predictnew occurrences for rare plants. Diversity and Distributions, 15(4): 565-576. doi: 10.1111/j.1472-4642.2009.00567.x
Zangiabadi, S., Zare-maivan, H., Mostafavi, H. and Ranjbar, H., 2021. Impact of climate change on the distribution range of Prunus eburnea (Spach) Aitch. & Hemsl. using Maxcent. Journal of Arid Biome, 11(1): 63-75. doi: 10.29252/ARIDBIOM.2021.16797.1861 (In Persian).
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آمار تعداد مشاهده مقاله: 333 تعداد دریافت فایل اصل مقاله: 202 |
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