The Influence of Climate Change on distribution of an Endangered Medicinal Plant (Fritillaria Imperialis L.) in Central Zagros
محورهای موضوعی : Modeling
Ali Asghar Naghipour borj
1
(Department of Natural Resources and Earth Science, Shahrekord University, Shahrekord, Iran.)
Zeinab Ostovar
2
(Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, Iran.)
Esmaeil Asadi
3
(Department of Natural Resources and Earth Science, Shahrekord University, Shahrekord, Iran.)
کلید واژه: MaxEnt, Bioclimatic variables, Species distribution modelling, Suitable habitat, Chaharmahal-va-Bakhtiari province,
چکیده مقاله :
Climate change has a great impact on the species distribution range and many endangered plant species. Fritillaria imperialis as a species that is native to Central Zagros, Iran is a medicinal plant with great ecological and commercial profits. Its population has decreased considerably and the species would be endangered in later decades. Understanding the habitat needs of this species, evaluating habitat conditions, and forecasting its potential habitat are important for protecting F. imperialis. The presence of F. imperialis points recorded from our field surveys in Chaharmahal-va-Bakhtiari province as a part of Central Zagros, Iran in spring 2017. In order to model its distribution based on correlation analysis, two topographic variables and eight bioclimatic ones as the input of Maximum Entropy model (MaxEnt) were used. The results showed that temperature seasonality (55.1%) and precipitation of driest quarter (22.9%) were important factor drivers of F. imperialis suitable habitat. The accuracy of the maximum entropy model in predicting the distribution of the studied species was high (AUC=0.91) as 2.33% (37986 ha) in Chaharmahal-va-Bakhtiari Province for the F. imperialis, which has had suitability. About 18% and 16.5% of F. imperialis habitats in the area may be lost due to climate change by 2070 under two climate warming scenarios (RCP4.5 and RCP8.5, given by the IPCC). As shown by the model, under the current climatic conditions, the suitable habitat would be rendered to an unsuitable one in the future resulting in local extinction. The results of this study can be used to identify sites with high extinction probability of F. imperialis and protect susceptible habitats against the effects of climate change.
Adhikari, D., Barik, S. and Upadhaya, K. 2012. Habitat distribution modelling for reintroduction of Ilex khasiana purk., a critically endangered tree species of northeastern India. Ecological Engineering, 40: 37-43.
Badfar-Chaleshtori, S., Shiran, B. Kohgard, M. Mommeni, H. Hafizi, A. Khodambashi, M. Mirakhorli, N. and Sorkheh, K. 2012. Assessment of genetic diversity and structure of Imperial Crown (Fritillaria imperialis L.) populations in the Zagros region of Iran using AFLP, ISSR and RAPD markers and implications for its conservation. Biochemical systematics and ecology, 42: 35-48.
Barrett, M.A., Brown, J.L. Junge, R.E. and Yoder, A.D. 2013. Climate change, predictive modeling and lemur health: Assessing impacts of changing climate on health and conservation in Madagascar. Biological Conservation, 157: 409-422.
Bonyadi, A., Mozaffarpur, S. Azadbakht, M. and Mojahedi, M. 2017. The emergence of Fritillaria imperialis in written references of traditional persian medicine: a historical review. Herbal Medicines Journal, 1(2): 39-42.
Ebrahimie, E., Mohammadi-Dehcheshmeh, M. and Sardari, M. 2006. Fritillaria species are at risk of extinction in Iran: Study on effective factors and necessity of international attention. Hortscience, 41(4): 1002.
Elith, J., Graham, C.H. Anderson, R.P. Dudík, M. Ferrier, S. Guisan, A. and et al., 2006. Novel methods improve prediction of species’ distributions from occurrence data. Ecography, 29(2): 129–151.
Elith, J., Phillips, S.J. Hastie, T. Dudík, M. Chee, Y.E. and Yates, C.J. 2011. A statistical explanation of maxent for ecologists. Diversity and distributions, 17: 43-57.
Estes, L., Bradley, B. Beukes, H. Hole, D. Lau, M. Oppenheimer, M. Schulze, M. Tadross, A. and Turner, W.R. 2013. Comparing mechanistic and empirical model projections of crop suitability and productivity: Implications for ecological forecasting, Global Ecology and Biogeography, 22: 1007-1018.
Fattahi, B., Jafari, M. Azarnivand, H. and Tahmasebi, P. 2017. Relationships between species diversity and biomass in mountainous habitats in Zagros rangeland (case study: Baneh, Kurdistan, Iran). Journal of Rangeland Science, 7(4): 316-330.
Ferrier, S. 2002. Mapping spatial pattern in biodiversity for regional conservation planning: Where to from here? Systematic biology, 51: 331-363.
Gama, M., Crespo, D. Dolbeth, M. and Anastácio, P. 2016. Predicting global habitat suitability for Corbicula fluminea using species distribution models: The importance of different environmental datasets. Ecological Modelling, 319: 163-169.
Guisan, A., Theurillat, J.P. and Kienast, F. 1998. Predicting the potential distribution of plant species in an alpine environment. Journal of Vegetation Science, 9(1): 65-74.
Haidarian Aghakhani, M., Tamartash, R. Jafarian, Z. Tarkesh Esfahani, M. and Tatian, M.R. 2017. Forecasts of climate change effects on Amygdalus scoparia potential distribution by using ensemble modeling in Central Zagros. Jour. RS & GIS for Natural Resources, 8(3): 1-14. (In Persian)
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 Program. Global Environment Facility, Project No. PIMS 2278, 2011.
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., Gholami, D.M. and Zenner, E.K., 2017. A Bayesian modeling of wildfire probability in the Zagros Mountains, Iran. Ecological informatics, 39: 32-44.
Khanum, R., Mumtaz, A. and Kumar, S. 2013. Predicting impacts of climate change on medicinal asclepiads of Pakistan using maxent modeling. Acta Oecologica, 49: 23-31.
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 the Natural Environment, 1: 094-098.
Loehle, C. and LeBlanc, D. 1996. Model-based assessments of climate change effects on forests: a critical review. Ecological Modelling, 90: 1–31.
Mahmoudi, S., Khoramivafa, M. and Hadidi, M., 2018. Investigation of the relationship between altitude and aspect with plant diversity: a case Study from Nawa mountain ecosystem in Zagros, Iran. Journal of Rangeland Science, 8(2), pp.129-142.
Manel, S., Williams, H.C. and Ormerod, S.J. 2001. Evaluating presence–absence models in ecology: the need to account for prevalence. Journal of Applied Ecology, 38(5): 921-931.
Mazangi, A., Ejtehadi, H. Mirshamsi, O. Ghassemzadeh, F. and Hosseinianyousefkhani, S.S. 2016. Effects of climate change on the distribution of endemic Ferula xylorhachis, Russian Journal of Ecology, 47(4): 349-354.
Mohammadi-Dehcheshmeh, M., Khalighi, A. Naderi, R. Sardari, M. and Ebrahimie, E. 2008. Petal: a reliable explant for direct bulblet regeneration of endangered wild populations of Fritillaria imperialis L. Acta Physiologiae Plantarum, 30(3): 395-399.
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.
Pettorelli, N., Chauvenet, A.L. Duffy, J.P. Cornforth, W.A. Meillere, A. and Baillie, J.E. 2012. Tracking the effect of climate change on ecosystem functioning using protected areas: Africa as a case study. Ecological Indicators, 20: 269-276.
Phillips, S.J., Dudík, M. and Schapire, R.E. 2004. A maximum entropy approach to species distribution modeling. In: Proceedings of the Proceedings of the twenty-first international conference on Machine learning, ACM, 83.
Phillips, S.J., Anderson, R.P. and Schapire, R.E. 2006. Maximum entropy modeling of species geographic distributions. Ecological modeling, 190: 231-259.
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: 558-570.
Tarkesh, M. and Jetschke, G. 2016. Investigation of current and future potential distribution of Astragalus gossypinus in central Iran using species distribution Modeling. 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. 2007. Biodiversity: climate change and the ecologist. Nature, 448: 550-2.
Walther, G.R., Post, E. Convey, P. Menzel, A. Parmesan, C. Beebee, T.J. Fromentin, J-M. Hoegh-Guldberg, O. and Bairlein, F. 2002. Ecological responses to recent climate change. Nature, 416(6879): 389-395.
Wang, Y., Xie, B. Wan, F. and Xiao, Q. 2007. Application of roc curve analysis in evaluating the performance of alien species potential distribution models. Biodiversity Science, 15(4): 365-372.
Yi, Y-j., Zhou, Y. Cai, Y-p. Yang, W. Li, Z-w. and Zhao, X. 2017. The influence of climate change on an endangered riparian plant species: The root of riparian Homonoia. Ecological Indicators, 23: 1-11.
