Predicting the effects of the climate change on the geographical distribution of Astragalus verus Olivier in the Central Zagros region

Subject Areas : Agriculture, rangeland, watershed and forestry

Sima  Teimoori Asl ¹ (MSc. Student of Range Management, Faculty of Natural Resources and Earth Science, Shahrekord University, Shahrekord, Iran)
Ali Asghar  Naghipour ² (Assistant Professor, Department of Natural Engineering, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, Iran)
Mohammad Reza  Ashrafzadeh ³ (Assistant Professor, Department of Fisheries and Environmental, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, Iran)
Maryam  Haidarian Aga Khani ⁴ (PhD. of Rangeland Sciences, Faculty of Natural Resources, Sari Agricultural Sciences and Natural Resources University, Sari, Iran)

Received: 2020-03-13 Accepted : 2020-05-06 Published : 2020-06-21

Keywords: Ensemble modeling, Species distribution modeling, Representative concentration pathways (RCPs), Chaharmahal va Bakhtiari province,

Abstract :

Background and ObjectiveClimate, soil characteristics, topography, land use, and biological relationships at various scales are the most important influencing factors on distribution and ecological niches of species. The climate is one of the most important determinants of plant distribution. Therefore throughout the past ecological history, climate change has had profound consequences on the current conditions of the world's ecosystems, including the existing distribution of species. Changes in the distribution of one species in a given geographical area due to the climate change can lead to shifting the presence regions of that species toward higher elevation that leads up to vegetative restriction or even extinction of the species. Shifting, or changing the geographical distribution of species is a strategy to be resistant to the climate change. Therefore, in order to protect the key ecological and valuable plant species, it is necessary to determine suitable habitats via identifying the most important environmental and human factors affecting the species presence in the current and future conditions. Astragalus L. (Fabaceae) is a genus widely distributed throughout the temperate regions. The Astragalus verus Olivier is a small, valuable shrub with many branches. In addition to its protective role from the point of view of the soil, this species has medicinal and industrial values. In recent decades, the geographical range of the A. verus variety has been significantly declined due to factors such as land degradation and over utilization. Despite the national importance of the Astragalus genus, so far little research has been done on the consequences of the climate change on the distribution of species of this genus. The present study was conducted to accomplish the following objectives; 1) To identify suitable habitats and determin the geographical distribution of A. verus in Central Zagros in the current situation; 2) to predict of the consequences of climate change by 2050 and 2070 under different scenarios on geographical distribution of A. verus; 3) to determin the most important factors affecting the distribution of this species. distribution of A. verus; 3) to determin the most important factors affecting the distribution of this species. Materials and Methods This study was carried out in Chaharmahal and Bakhtiari province in an area about 1.65 million hectare thai is totally located in Central Zagros region. Extensive field studies were integrated to collect geographical coordinates of the presence point (112 points) of this species by using Global Positioning System (GPS) throughout Chaharmahal and Bakhtiari province. Bioclimatic (bio1–bio19), Physiographic variables (elevation, aspect, and slope) and land cover/land variables were used for modeling. Before modeling, two methods of Pearson correlation analysis and Variance Inflation Factor (VIF) were used to check out the correlation between the various environmental variables. In order to model, 19 environmental variables including bioclimatic variables, physiography and land cover / land use were applied to model the distribution based on correlation analysis. Variables with Pearson’s correlation coefficient, r2<±0.8, VIF<3) were selected. Finally and after the omission of the layers having high correlation, nine variables were used for modeling. In order to predict the distribution of the suitable habitats of the Astragalus verus Olivier, Biomad2 software package in R environment (3.1.2 version) was used. In this study, ensemble methods including Maximum Entropy (MaxEnt), Artificial Neural Network (ANN), Generalized Boosting Method (GBM), the Generalized Linear Model (GLM), Flexible Discriminant Analysis (FDA), Random Forest (RF) and Multivariate Adaptive Regression Splines (MARS) were used to estimate the suitable habitats. We used 80% of the occurrence points as training data for model calibration and 20% of the rest of the data set to evaluate the predition of the models. Prediction of the geographical distribution of the Astragalus verus Olivier in the future (years 2050 and 2070) was made based on four scenarios of the increase in the greenhouse gases (Representative Concentration Pathways; RCPs) RCP2.6, RCP4.5, RCP6, RCP8.5 in general circulation model MRI-CGCM3. Model performance was assessed by using the area under the receiver operating curve (AUC) and the true skill statistic (TSS). Results and Discussion Our results revealed that the most effective variables in desirability of the study species habitat were the isothermality, mean temperature of the wettest season of the year and seasonal precipitation variables respectively. In keeping with the findings, the Astragalus verus Olivier mostly exists in habitats with Isothermality (bio3) from + 36.8 to + 39.7 °C, Mean Temperature of the Wettest season of the year (bio8) from - 2 to + 3.5 °C, and seasonal precipitation variables (bio15) from 100 to 112 mm and the Annual Precipitation of 280 mm to 490 mm. Based on the results of modeling of current conditions, in comparison to the other regions, northeast and east of the province had the most habitat importance for the Astragalus verus Olivier. Our findings show that about 27.43% of the study area was identified as suitable habitats for the Astragalus verus Olivier. Prediction of the geographical distribution of the Astragalus verus Olivier in the future (years 2050 and 2070) was made based on four scenarios of the increase in the greenhouse gases (Representative Concentration Pathways; RCPs) RCP2.6, RCP4.5, RCP6, RCP8.5 in general circulation model MRI-CGCM3. Based on the future projections were made for the year 2050 and 2070 with four Representative Concentration Pathways (RCPs) scenario (2.6, 4.5, 6 and 8.5) and general circulation model MRI-CGCM3. In keeping with our findings, climate change can have significant consequences for the Astragalus verus Olivier suitable habitats in the study area. Based on various senarios, about 45.70 percent (year 2050, RCP2.6) to 89.88 percent (year 2070, RCP8.5) of the current habitats for the Astragalus verus Olivier will be unsuitable due to the climate change by 2050 and 2070. While in the same period of time, about 1.58 (RCP8.5, 2050) to 13.19 percent (RCP2.6, 2070) may be added to the suitable habitats of this species in areas with higher elevation. According to all scenarios, the suitable habitats of this species will decrease in all habitats, especially in areas with lower elevation. The climate change consequences especially the probability of decling and shifting the geographical range of the plant species in various habitats of Iran especially in the central Zagros and also in Central Iran range are predicted. Assessments showed that the models had acceptable accuracy and Random Forest model was determined as the most reliable model to predict the distribution of this species. Conclusion Generally, this study indicated that ensemble model might predict the potential distribution of the Astragalus verus Olivier with a relatively high accuracy (AUC= 0.92 and TSS= 0.79). The scenarios used in this study predict the probability of the shift of the geographical range of the studied species under climate change scenarios of 2050 and 2070. According to the results, it seems that the suitable habitat extent of the Astragalus verus Olivier in the study area has been decreased and will shit toward the higher elevation. Although land degradation and over utilization may be considered as two important factors in habitat degradation of this species but this study highlights the importance the effects of climate change on the distribution of the Astragalus verus Olivier. As a result of the severe and inappropriate harvest of the Astragalus verus Olivier, the range of its distribution and density has decreased in some areas, which has increased the intensity of phenomena such as soil erosion. This issue requires a double attention of the managers and experts of natural resources to the Astragalus verus Olivier and the other species with similar performance in ecosystems having importance from the view point of economic productivity as well as their ability to conserve the soil.

References:

Abbasian M, Moghim S, Abrishamchi A. 2019. Performance of the general circulation models in simulating temperature and precipitation over Iran. Theoretical and Applied Climatology, 135(3): 1465-1483. doi:https://doi.org/10.1007/s00704-018-2456-y.

Abolmaali MR, Tarkesh M, Bashari H. 2018a. 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:https://doi.org/10.1016/j.ecoinf.2017.10.002.

Abolmaali MR, Tarkesh M, Bashari H. 2017b. Assessing impacts of climate change on endangered Kelossia odoratissima Mozaff species distribution using Generalized Additive Model. Journal of Natural Environment, 70(2): 243-254. (In Persian)

Ahmad R, Khuroo AA, Charles B, Hamid M, Rashid I, Aravind NA. 2019. Global distribution modelling, invasion risk assessment and niche dynamics of Leucanthemum vulgare (Ox-eye Daisy) under climate change. Scientific Reports, 9(1): 1-15. doi:https://doi.org/10.1038/s41598-019-47859-1.

Ali Akbari M, Jafari MR, Saadatfar A. 2011. Determining Potential Site for Astragalus verus with Combination of GIS and Remote Sensing. Journal of RS and GIS for Natural Resources, 1(1): 15-29. (In Persian)

Allouche O, Tsoar A, Kadmon R. 2006. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). Journal of Applied Ecology 43: 1223–1232. doi:https://doi.org/10.1111/j.1365-2664.2006.01214.x.

Al-Qaddi N, Vessella F, Stephan J, Al-Eisawi D, Schirone B. 2016. Current and future suitability areas of kermes oak (Quercus coccifera L.) in the Levant under climate change. Regional Environmental Change, 17: 143-156. doi:https://doi.org/10.1007/s10113-016-0987-2.

Amici V, Marcantonio M, La Porta N, Rocchini D. 2017. A multi-temporal approach in MaxEnt modelling: A new frontier for land use/land cover change detection. Ecological Informatics, 40: 40-49. doi:https://doi.org/10.1016/j.ecoinf.2017.04.005.

Amiri M, Tarkesh M, Jafari R. 2019. Predicting the Climatic Ecological Niche of Artemisia aucheri Boiss in Central Iran using Species Distribution Modeling. Iranian Journal of Applied Ecology, 8(2): 61-79. (In Persian)

Ashrafzadeh MR, Naghipour AA, Haidarian M, Khorozyan I. 2019a. Modeling the response of an endangered flagship predator to climate change in Iran. Mammal Research, 64(1): 39-51. doi:10.1007/s13364-018-0384-y.

Ashrafzadeh MR, Naghipour AA, Haidarian M, Kusza S, Pilliod DS. 2019b. Effects of climate change on habitat and connectivity for populations of a vulnerable, endemic salamander in Iran. Global Ecology and Conservation, 19: e00637. doi:https://doi.org/10.1016/j.gecco.2019.e00637.

Attorre F, Abeli T, Bacchetta G, Farcomeni A, Fenu G, De Sanctis M, Gargano D, Peruzzi L, Montagnani C, Rossi G, Conti F, Orsenigo S. 2018a. How to include the impact of climate change in the extinction risk assessment of policy plant species? Journal for Nature Conservation, 44: 43-49. doi:https://doi.org/10.1016/j.jnc.2018.06.004.

Attorre F, Alfò M, De Sanctis M, Francesconi F, Valenti R, Vitale M, Bruno F. 2011b. Evaluating the effects of climate change on tree species abundance and distribution in the Italian peninsula. Applied Vegetation Science, 14(2): 242-255. doi:https://doi.org/10.1111/j.1654-109X.2010.01114.x.

Benito Garzón M, Sánchez de Dios R, Sainz Ollero H. 2008. Effects of climate change on the distribution of Iberian tree species. Applied Vegetation Science, 11(2): 169-178. doi:https://doi.org/10.3170/2008-7-18348.

Borna F, Tamartash R, Tatian M, Gholami V. 2017. Habitat potential modeling of Astragalus gossypinus using ecological niche factor analysis and logistic regression (Case study: summer rangelands of Baladeh, Nour), Journal of RS and GIS for Natural Resources, 7(4): 45-61. (In Persian)

Byeon D-h, Jung S, Lee W-H. 2018. Review of CLIMEX and MaxEnt for studying species distribution in South Korea. Journal of Asia-Pacific Biodiversity, 11(3): 325-333. doi:https://doi.org/10.1016/j.japb.2018.06.002.

Chahouki MAZ, Sahragard HP. 2016. Maxent modelling for distribution of plant species habitats of rangelands (Iran). Polish Journal of Ecology, 64(4): 453-467. doi:https://doi.org/10.3161/15052249PJE2016.64.4.002.

Cheng L, Lek S, Lek-Ang S, Li Z. 2012. Predicting fish assemblages and diversity in shallow lakes in the Yangtze River basin. Limnologica, 42(2): 127-136. doi:https://doi.org/10.1016/j.limno.2011.09.007.

Ghahremaninejad F, Bagheri A, Maassoumi AA. 2012. Two new species of Astragalus L. sect. Incani DC.(Fabaceae) from the Zanjan province (Iran). Adansonia, 34(1): 59-65. doi:https://doi.org/10.5252/a2012n1a6.

Guisan A, Zimmermann NE. 2000. Predictive habitat distribution models in ecology. Ecological Modelling, 135(2): 147-186. doi:https://doi.org/10.1016/S0304-3800(00)00354-9.

Haidarian, M. 2018. Predicting the impact of climate change on spatial distribution of ecologically important plant species In the Central Zagros. Ph.D. thesis of Rangeland Sciences, Sari Agricultural Sciences and Natural Resources University, 250p. (In Persian)

Haidarian Aghakhani M, Tamartash R, Jafarian Z, Tarkesh Esfahani M, Tatian M. 2017a. 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)

Haidarian Aghakhani M, Tamartash R, Jafarian Z, Tarkesh Esfahani M, Tatian M. 2017b. 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)

Hao T, Elith J, Guillera-Arroita G, Lahoz-Monfort JJ. 2019. A review of evidence about use and performance of species distribution modelling ensembles like BIOMOD. Diversity and Distributions, 25(5): 839-852. doi:https://doi.org/10.1111/ddi.12892.

Hodd RL, Bourke D, Skeffington MS. 2014. Projected range contractions of European protected oceanic montane plant communities: focus on climate change impacts is essential for their future conservation. PloS one, 9(4). doi:https://doi.org/10.1371/journal.pone.0095147.

Hutchinson GE. 1957. Cold spring harbor symposium on quantitative biology. Concluding remarks, 22: 415-427.

Kaky E, Gilbert F. 2016. Using species distribution models to assess the importance of Egypt's protected areas for the conservation of medicinal plants. Journal of Arid Environments, 135: 140-146. doi:https://doi.org/10.1016/j.jaridenv.2016.09.001.

Khodagholi M, Saboohi R. 2019. Delineating changes in climatic variables and its impact on the Astragalus verus Olivier habitats in Isfahan Province. Journal of Range and Watershed Management, 72(2): 359-374. (In Persian)

Lin CT. Chiu CA. 2019. The Relic Trochodendron aralioides Siebold & Zucc.(Trochodendraceae) in Taiwan: Ensemble distribution modeling and climate change impacts. Forests, 10(1): 7. https://doi.org/10.3390/f10010007.

McSweeney CF, Jones RG, Lee RW, Rowell DP. 2015. Selecting CMIP5 GCMs for downscaling over multiple regions. Climate Dynamics, 44: 3237-3260. https://doi.org/10.1007/s00382-014-2418-8.

Naghipour AA, Haidarian M, Sangoony H. 2019a. 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)

Naghipour AA, Ostovar Z, Asadi E. 2019b. 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.

Pachauri RK, Allen MR, Barros V, Broome J, Cramer W, Christ R, Church J, Clarke L, Dahe Q, Dasgupta P. 2014. Climate change 2014: synthesis Report. Contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change, IPCC, 153p.

Potta S. 2004. Application of Stochastic Downscaling Techniques to Global Climate Model Data for Regional Climate Prediction, MSc. Faculty of the Louisiana State University and Agricultural and Mechanical College, Sri Venkateswara University, 153p.

Rana SK, Rana HK, Ghimire SK, Shrestha KK, 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. https://doi.org/10.1007/s11629-015-3822-1.

Rios J, Waterman P. 1997. A review of the pharmacology and toxicology of Astragalus. PhototherapyResearch, 11: 411-418. https://doi.org/10.1002/(SICI)1099-1573(199709).

Safaei M, Tarkesh M, Bashari H, Bassiri M. 2018. Modeling potential habitat of Astragalus verus Olivier for conservation decisions: A comparison of three correlative models. Flora, 242: 61-69. doi:https://doi.org/10.1016/j.flora.2018.03.001.

Sahragard HP, Chahouki MAZ. 2015. An evaluation of predictive habitat models performance of plant species in Hoze soltan rangelands of Qom province. Ecological Modelling, 309-310: 64-71. doi:https://doi.org/10.1016/j.ecolmodel.2015.04.005.

Saki M, Tarkesh M, Bassiri M, Vahabii M R. 2013. Application of Logistic Regression Tree Model in Determining Habitat Distribution of Astragalus verus. Iranian Journal of Applied Ecology, 2013: 1 (2) :27-38. (In Persian)

Sangoony H, Karimzadeh H, Vahabi M, Tarkesh esfahani M. 2014a. Determining the potential habitat of Astragalus gossypinus Fischer in west region of Isfahan, using ecological niche factor analysis. Journal of RS and GIS for Natural Resources, 5(2: 1-13. (In Persian)

Sangoony H, Vahabi MR, Tarkesh M, Soltani S. 2016b. 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. doi:https://dx.doi.org/10.15666/aeer/1404_085100.

Silvertown J. 2004. Plant coexistence and the niche. Trends in Ecology & Evolution, 19(11): 605-611. doi:https://doi.org/10.1016/j.tree.2004.09.003.

Tarkesh M, 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): 80. doi:10.1007/s12517-015-2071-5.

Thuiller W, Georges D, Engler R, Breiner F, Georges MD, Thuiller CW. 2016. Package ‘Biomod2’. https://cran.r-project.org/package=biomod2.

Tilman D, Lehman C. 2001. Human-caused environmental change: impacts on plant diversity and evolution. Proceedings of the National Academy of Sciences, 98(10): 5433-5440.

Vahabi MR, Basiri M, Moghadam MR, Masoumi AA. 2007. Determination of the most effective habitat indices for evaluation of tragacanth sites in Isfahan Province. Iranian Journal of Natural Resources, 59:1013-1029. (In Persian)

Wei B, Wang R, Hou K, Wang X, Wu W. 2018. Predicting the current and future cultivation regions of Carthamus tinctorius L. using MaxEnt model under climate change in China. Global Ecology and Conservation, 16: e00477. doi:https://doi.org/10.1016/j.gecco.2018.e00477.

Woodward FI. 1987. Climate and Plant Distribution. Cambridge University Press, Cambridge. 174p.

Zarinkamar F. 1996. Investigation of anatomical and ecological characteristics of 14 species of Astragalus spp. Research Institute of Range and Forest, 98p.

Zhang X, Li G, Du S. 2018. Simulating the potential distribution of Elaeagnus angustifolia L. based on climatic constraints in China. Ecological Engineering, 113: 27-34. doi:https://doi.org/10.1016/j.ecoleng.2018.01.009.