The Effects of Climate Change on the Future Distribution of Astragalus adscendens in Central Zagros, Iran
محورهای موضوعی : Climate Change
Maryam Haidarian
1
(Sari Agricultural Sciences and Natural Resources University, Sari, Iran)
Reza Tamartash
2
(Department of range management, Sari Agricultural Sciences and Natural Resources University, Iran)
zeinab Jafarian-Jeloudar
3
(Professor of Rangeland and Watershed Management, Faculty of Natural Resources, Sari Agricultural Sciences & Natural Resources University, Iran.)
Mostafa Tarkesh
4
(Isfahan University of Technology)
Mohammad Reza Tataian
5
(Sari Agricultural Sciences and Natural Resources University, Sari, Iran)
کلید واژه: Chaharmahal-va-Bakhtiari province, Species distribution modeling, Ensemble modeling, Biomod2,
چکیده مقاله :
Iran is one of the principal centers of Astragalus genus. Astragalus adscendens is a valuable endemic plant. There is less information about the effect of climate change on Astragalus genus especially A. adscendens. In this study, we used the ensemble modeling based on seven species distribution models to predict the spatial distribution of A. adscendens. The presence of A. adscendens points was recorded from our field surveys in Chaharmahal-va-Bakhtiari province as a semi-arid part of Central Zagros, Iran between 2015 and 2016. The future projections were made for the year 2050 and 2070 with two Representative Concentration Pathways (RCPs) scenarios (4.5 and 8.5). Also, in this approach, species occurrence data (140 points), 19 bioclimatic predictors from HadGEM2-CC (Hadley Centre Global Environmental Model, version two - Carbon Cycle), MRI-CGCM3 (Meteorological Research Institute Coupled Global Climate Model Version three) and three physiographic variables were used. According to the ensemble model, 33.58% of the study area (548678 ha) was suitable for the A. adscendens. This research showed annual precipitation, isothermality, temperature annual range and slope have played the most important role in habitat suitability of this species. The response curves showed that occurrence probability of A. adscendens mostly exists in habitats with annual precipitation from 380 mm to 630 mm, isothermality from 35.7 to 36.8 (dimensionless), temperature annual range from 40.5 to 43°C and slope of 0.1 to 30 degree. The decline of suitable habitats will be 59.3% to 89.7% by 2050 and 2070. In contrast, 18.1% to 56.2% of currently unsuitable habitats can become suitable with climate changes. Evaluations showed that Random Forest was found to be the most reliable model for species prediction. Predicting the potential future changes in suitable habitat for A. adscendens will allow more reliable planning and management of this valuable species for experts.
Abolmaali, SM-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.
Allouche, O., Tsoar, A., and Kadmon, R., 2006. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). Journal of Applied Ecology, 43(6): 1223–1232.
Amiri, M., Tarkesh, M. and Jafari, R., 2019. Predicting the distribution of Artemisia sieberi Besser under climate change in the steppe and semi-steppe of Iran-Touranian region. Desert Management, 7(13): 29-48. (In Persian)
Anderegg, W. R. L., Hicke, J. A., Fisher, R. A., Allen, C.D., Aukema, J., Bentz, B., et al., 2015. Tree mortality from drought, insects, and their interactions in a changing climate. New Phytologist, 208(3): 674–683.
Araújo, M. B., and New, M., 2007. Ensemble forecasting of species distributions. Trends in Ecology & Evolution, 22(1): 42-47.
Ardestani, E. G., Tarkesh, M., Bassiri, M., and Vahabi, M.R., 2015. Potential habitat modeling for reintroduction of three native plant species in central Iran. Journal of Arid Land, 7(3): 381-390.
Arenas-Castro, S., Gonçalves, J., Alves, P., Alcaraz-Segura, D., and Honrado, J. P., 2018. Assessing the multi-scale predictive ability of ecosystem functional attributes for species distribution modelling. PLoS One, 13(6): e0199292.
Arvahi, A., Abolghasemi, S., Nazaridoust, A., Raisdana, P., Hosseininasab, M., and Derakhshandeh, R., 2016. Developing Central Zagros Mountains conservation and sustainable development program with an approach to mainstreaming biodiversity.Journal of Scientific Research and Studies, 3(9): 179-190.
Ashrafzadeh, M. R., Naghipour, A. A., Haidarian, M., and Khorozyan, I., 2019a. Modeling the response of an endangered flagship predator to climate change in Iran. Mammal Research, 64(1): 39-51.
Ashrafzadeh, M. R., Naghipour, A. A., Haidarian, M., Kusza, S., and Pilliod, D. S., 2019b. Effects of climate change on habitat and connectivity for populations of a vulnerable, endemic salamander in Iran. Global Ecology and Conservation, 19: e00637.
Attarod, P., Sadeghi, S. M. M., Taheri Sarteshnizi, F., Saroyi, S., Abbasian, P., Masihpoor, M., kordrostami, F., and Dirikvandi, A., 2016. Meteorological parameters and evapotranspiration affecting the Zagros forests decline in Lorestan province. Iranian Journal of Forest and Range Protection Research, 13(2): 97-112. (In Persian)
Azimi, M., Mesdaghi, M.,and Farohpor, M., 2005. Study of the relationships of cyamophila dicora loginova population and vegetation parameters of Astragalus adscendens in Feridounshahr. Isfahan. Journal of Science and Technology of Agriculture and Natural Research, 9(3): 243-252. (In Persian)
Babaeian, I., Modirian, R., Karimian, M., and Zarghami, M., 2015. Simulation of climate change in Iran during 2071–2100 using PRECIS regional climate modelling system. Desert, 20: 123–134.
Bashari, H., Naghipour, A. A., Khajeddin, S. J., Sangoony, H., and Tahmasebi, P., 2016. Risk of fire occurrence in arid and semi-arid ecosystems of Iran: an investigation using Bayesian belief networks. Environmental monitoring and assessment, 188(9): 531.
Box, E.O., 1981. Predicting physiognomic vegetation types with climate variables. Vegetation, 45(2):127-139.
Breiman, L., 2001. Random forests. Machine learning, 45 (1): 5–32.
Cheng, L., Lek, S., Lek-Ang, S., and Li. Z., 2012. Predicting fish assemblages and diversity in shallow lakes in the Yangtze River basin. Limnologica, 42 (2): 127–136.
Chhetri, P. K., Gaddis, K.D., and Cairns, D. M., 2018. Predicting the suitable habitat of treeline species in the Nepalese Himalayas under climate change. Mountain Research and Development, 38: 153-163.
Dawson, T. P., Jackson, S. T., House, J. I., Prentice, I. C., and Mace, G. M., 2011. Beyond predictions: biodiversity conservation in a changing climate. Science, 332: 53–58.
De Clercq, E., Leta, S., Estrada-Peña, A., Madder, M., Adehan, S., and Vanwambeke, S., 2015. Species distribution modelling for Rhipicephalus microplus (acari: Ixodidae) in benin, West Africa: Comparing datasets and modelling algorithms. Preventive Veterinary Medicine, 118(1): 8-21.
Eeley, H. A., Lawes, M. J., and Piper, S. E., 1999. The influence of climate change on the distribution of indigenous forest in kwazulu‐natal, South Africa. Journal of Biogeography, 26: 595-617.
Elith, J., and Leathwick, J. R., 2009. Species distribution models: Ecological explanation and prediction across space and time. Annual review of ecology, evolution, and systematics, 40: 677-697.
Elith, J., Leathwick J. R., and Hastie. T. 2008. A working guide to boosted regression trees. Journal of Animal Ecology, 77(4): 802-813.
Eskildsen, A., Roux, P. C., Heikkinen, R. K., Høye, T. T., Kissling, W. D., Pöyry, J., Wisz, M. S., and Luoto, M., 2013. Testing species distribution models across space and time: high latitude butterflies and recent warming. Global Ecology Biogeography, 22(12): 1293–1303.
Farashi, A., Shariati, M. and Hosseini, M., 2017. Identifying biodiversity hotspots for threatened mammal species in Iran. Mammalian Biology, 87: 71-88.
Fielding, A. H. and Bell, J. F., 1997. A review of methods for the assessment of prediction errors in conservation presence/ absence models. Environmental Conservation, 24: 38–49.
Forman, R. T., 1964. Growth under controlled conditions to explain the hierarchical distributions of a moss, Tetraphis pellucida. Ecological Monographs, 34(1): 1-25.
Fouladi, Z., 2014. Zoning drying rangeland using landsat ETM+ image data province in Chaharmahal-va-Bakhtiari northwestern rangelands. M.Sc. thesis of Rangeland management, Shahrekord University, 58p. (In Persian).
Ghahremaninejad, F., Bagheri, A., and Maassoumi, A. A., 2012. Two new species of Astragalus l. Sect. Incani dc. (Fabaceae) from the Zanjan province (Iran). Adansonia, 34(1): 59-66.
Grami, B., 1998. Gaz of khunsar: The manna of Persia. Economic botany, 52(2): 183-191.
Grenouillet, G., Buisson, L., Casajus, N., and Lek, S., 2011. Ensemble modelling of species distribution: the effects of geographical and environmental ranges. Ecography, 34 (1): 9–17.
Guillera‐Arroita, G., Lahoz‐Monfort, J. J., Elith, J., Gordon, A., Kujala, H., Lentini, P. E., et al. 2015. Is my species distribution model fit for purpose? Matching data and models to applications. Global Ecology and Biogeography, 24(3): 276-292.
Guisan, A., and Zimmermann, N. E., 2000. Predictive habitat distribution models in ecology. Ecological modeling, 135: 147-186.
Habibi, M., 2016. Investigating the impact of climate changes on qualitative and quantitative growth of oak trees (case study: central Zagros). Open Journal of Ecology, 6: 358–366.
Haidarian Aghakhani, M., Tamartash, R., Jafarian, Z., Tarkesh Esfahani, M., and Tatian, M., 2017a. Predicting the impacts of climate change on Persian oak (Quercus brantii) using species distribution modelling in Central Zagros for conservation planning. Journal of Environmental Studies, 43: 497-511. (In Persian).
Haidarian Aghakhani M, Tamartash R, Jafarian Z, Tarkesh Esfahani M, Tatian M. 2017b. Forecasts of climate change effects on Amygdalus scoparia potential distribution by using ensemble modeling in Central Zagros. Journal of RS and GIS for Natural Resources, 8(3): 1-14. (In Persian)
Hamann, A. and Wang, T., 2006. Potential effects of climate change on ecosystem and tree species distribution in British Columbia. Ecology, 87: 2773-2786.
Hao, T., Elith, J., Guillera-Arroita, G., and Lahoz-Monfort, J. J., 2019. A review of evidence about use and performance of species distribution modelling ensembles like BIOMOD. Diversity and Distributions, 25(5): 839-852.
Hengl, T., Sierdsema, H., Radović, A., and Dilo, A., 2009. Spatial prediction of species’ distributions from occurrence-only records: Combining point pattern analysis, ENFA and regression-kriging. Ecological Modelling, 220(24): 3499-3511.
Hessl, A., Miller, J., Kernan, J., Keenum, D., and McKenzie, D., 2007. Mapping Paleo‐Fire boundaries from binary point data: comparing interpolation methods. The Professional Geographer, 59(1): 87-104.
Hunnam, P., 2011. Conservation of biodiversity in the Central Zagros Landscape conservation zone: Mid-Term evaluation report. Government of the Islamic Republic of Iran, United Nations Development Programme, Global Environment Facility, Project No. PIMS 2278.
IPCC., 2007. Summary for policymakers. In Solomon, S., Qin, D., Manning, M., Chen, Z., Arquis, M., Averyt, K. B., Tignor, M., and Miller, H. L. (Eds.), 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/New York: Cambridge University Press.
Iverson, L.R. and Prasad, A.M., 1998. Predicting abundance of 80 tree species following climate change in the eastern United States. Ecological Monographs, 6(4): 465-485.
Jaafari, A., Mafi Gholami, D., and Zenner, E. K., 2017. A Bayesian modeling of wildfire probability in the Zagros Mountains, Iran. Ecological Informatics, 39: 32-44.
Khajeddin, S., 2001. Impacts of habitat slope on plant from of Astragalus adscendens. JWSS-Isfahan University of Technology, 4: 129-144. (In Persian)
Kuhn, M., 2008. Building predictive models in R using the caret package. Journal of Statistical Software, 28(5): 1-26.
Lüthi, D., Le Floch, M., Bereiter, B., Blunier, T., Barnola, J-M., Siegenthaler, U., Raynaud, M., Jouzel, J., Fischer, H., Kawamura, K., and Stocker. T., 2008. High-resolution carbon dioxide concentration record 650,000–800,000 years before present. Nature, 453: 379-382.
Marmion, M., Luoto, M., Heikkinen, R. K.,and Thuiller, W., 2009. The performance of state-of-the-art modelling techniques depends on geographical distribution of species. Ecological Modelling, 220(24): 3512-3520.
Massoumi, A., 1998. Astragalus in the old world. Research Institute of Forest and Rangelands Pub, Tehran.
Milanesi, P., Holderegger, R., Caniglia, R., Fabbri, E., and Randi, E., 2016. Different habitat suitability models yield different least-cost path distances for landscape genetic analysis. Basic and Applied Ecology, 17(1): 61-71.
McPherson, J.M., Jetz, W. and Rogers, D. J.. 2004. the effects of species’ range sizes on the accuracy of distribution models: ecological phenomenon or statistical artefact? Journal of Applied Ecology, 41: 811–823.
Moghimi, J., 2005. Introduction some important range species suitable for the development and improvement of rangelands Iran. Technical office Range, Arvan publishers, Iran, Tehran, 670 p. (In Persian).
Mousazade, M., Ghanbarian, G., Pourghasemi, H. R., Safaeian, R., and Cerdà, A., 2019. Maxent data mining technique and its comparison with a bivariate statistical model for predicting the potential distribution of Astragalus fasciculifolius boiss. In Fars, Iran. Sustainability, 11(12): 3452.
Naghipour, A.A., Bashari, H., Khajeddin, S.J., Tahmasebi, P. and Iravani, M., 2016. Effects of smoke, ash and heat shock on seed germination of seven species from Central Zagros rangelands in the semi-arid region of Iran. African Journal of Range & Forage Science, 33(1): 67-71.
Naghipour borj, A.A., Ostovar, Z. and Asadi, E., 2019a. The Influence of Climate Change on distribution of an Endangered Medicinal Plant (Fritillaria Imperialis L.) in Central Zagros, Journal of Rangeland Science, 9(2): 159-171.
Naghipour, A. A., Haidarian M. and Sangoony, H., 2019b. Predicting the impact of climate change on the distribution of Pistacia atlantica in the Central Zagros. Journal of Plant Ecosystem Conservation, 6 (13): 197-214. (In Persian)
Neilson, R. P., Pitelka, L. F., Solomon, A. M., Nathan, R., Midgley, G. F., Fragoso, J. M., et al. 2005. Forecasting regional to global plant migration in response to climate change. AIBS Bulletin, 55(9): 749-759.
Pakzad, Z., Raeini Sarjaz, M., and Khodagholi, M. 2013. Evaluation of the effects of climate factors on distribution of the habitats of Astragalus adscendens in Isfahan province. Iranian Journal of Range and Desert Research, 20(1): 199-212. (In Persian)
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.
Pearson, R. G. and Dawson, T. P., 2003. Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Global ecology and biogeography, 12(5): 361-371.
Phillips, G. O., and Williams, P.A., 2009. Handbook of hydrocolloids. Boca Raton, FL: CRC press.
Planton, S., 2013. Annex iii. Glossary: IPCC–intergovernmental panel on climate change. PDF) IPCC Fifth Assessment Report, 1450.
Podlech, D., 1986. Taxonomic and phytogeographical problems in Astragalus of the old world and south-west Asia. Proceedings of the Royal Society of Edinburgh, Section B: Biological Sciences, 89, 37-43.
Priti, H., Aravind, N. A., Uma Shaanker, R., and Ravikanth, G., 2016. Modeling impacts of future climate on the distribution of Myristicaceae species in the Western Ghats, India. Ecological Engineering, 89: 14–23.
Rahimzadeh, F., Fattahi, E., and Hoseini-Dastak, S. E., 2005. Evaluation of variability of climate with applying statistical methods in Iran. Iran Water Resources Research, 1: 61–73. (In Persian)
Rana, S. K., Rana, H. K., Ghimire, S. K., Shrestha, K. K., and Ranjitkar, S. 2017. Predicting the impact of climate change on the distribution of two threatened Himalayan medicinal plants of Liliaceae in Nepal. Journal of Mountain Science, 14(3): 558-570.
R Development Core Team, 2014. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna
Renwick, A. R., Massimino, D., Newson, S. E., Chamberlain, D.E., Pearce‐Higgins, J. W., and Johnston, A., 2012. Modelling changes in species’ abundance in response to projected climate change. Diversity and Distributions, 18(2): 121-132.
Rios, J., and Waterman, P., 1997. A review of the pharmacology and toxicology of Astragalus. Phototherapy Research, 11: 411-418.
Safaei, M., Tarkesh, M., Basiri, M., and Bashari, H. 2013. Determining the potential habitat of Astragalus verus olivier using the geostatistical and logistic regression methods. Arid Biome Scientific and Research Journal, 3(1), 42-54. (In Persian)
Safaei, M., Tarkesh, M., Bashari, H., and Bassiri, M., 2018. Modeling potential habitat of Astragalus verus olivier for conservation decisions: A comparison of three correlative models. Flora, 242: 61-69.
Sangoony, H., Karimzadeh, H. R., Vahabi, M. R., and Tarkesh Esfahani, M. (2012). Determining the potential habitat of Astragalus gossypinus Fischer in west region of Isfahan, using ecological nich factor analysis. Journal of Rs and GIS for natural resources, 3(2): 1-12. (In Persian)
Sangoony, H., Vahabi, M., Tarkesh, M., and Soltani, S., 2016. Range shift of Bromus tomentellus Boiss. As a reaction to climate change in Central Zagros, Iran. Applied Ecology and Environmental Research, 14(4): 85–100.
Sangoony, H., Vahabi, M., Tarkesh, M., Eshghizadeh, H., and Soltani, S., 2017. Characterization of ecosystem’s climate and geographical distribution of two pasture species using random forest modeling in central Zagros region. Plant Ecosystem Conservation, 5: 1-17. (In Persian)
Senay, S. D., Worner, S. P., and Ikeda, T., 2013. Novel three-step pseudo-absence selection technique for improved species distribution modelling. PLoS One, 8: e71218.
Stocker, T.,Qin, D., Plattner, G.K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, V. and Midgley, P.M., 2014. Climate change 2013: The physical science basis: Working group i contribution to the fifth assessment report of the intergovernmental panel on climate change:Cambridge University Press.
Tanaka, N., Nakao, K., Tsuyama, I., Higa, M., Nakazono, E., and Matsui, T., 2012. Predicting the impact of climate change on potential habitats of fir (abies) species in japan and on the East Asian continent. Procedia Environmental Sciences, 13: 455-466.
Tarkesh, M., and Jetschke, G., 2016. Investigation of current and future potential distribution of Astragalus gossypinus in central Iran using species distribution modelling. Arabian Journal of Geosciences, 9: 1-11.
Thomas, C. D., Cameron, A., Green, R. E., Michel, B., and Beaumont, L. J., 2004. Extinction risk from climate change. Nature, 427: 145–147.
Thuiller, W., Lavorel, S. and Araújo, M.B., 2005. Niche properties and geographical extent as predictors of species sensitivity to climate change. Global Ecology and Biogeography, 14: 347–357.
Thuiller, W., Georges, D., Engler, R., Breiner, F., Georges, M. D., and Thuiller, C. W., 2016. Package ‘biomod2’. https://cran.r-project.org/package= biomod2
Townsend, C., and Guest, E., 1974. Flora of Iraq. Ministry of agriculture and agrarian reform. Iraq.
Zipkin, E. F., and Grant, E. H. C., Fagan, W. F., 2012. Evaluating the predictive abilities of community occupancy models using AUC while accounting for imperfect detection. Ecological Applications, 22: 1962e1972.
Zohary, M., 1973. Geobotanical foundations of the Middle East.
