Integrated Watershed Management

Integrated Watershed Management

Predicting the effect of climate change on distribution of valerian (Valeriana sisymbriifolia) species using MaxEnt model in Isfahan province

Document Type : Original Article

Authors
Nassim Shabani 1
Mehdi Khoshbakht 1
Azadeh Hasani 2
1 Department of Range management , Faculty of Natural Resources, Isfahan University of Technology, Isfahan, Iran
2 Department of desertification, Faculty of Natural Resources, Isfahan University of Technology,Isfahan, Iran
10.22034/iwm.2023.2007169.1093
Abstract
Extended Abstract
Introduction
Climate change is one of the most important issues in the world, which has great effects on ecosystems and their diversity. One of the most important factors of climate change is the increase in temperature and change in the precipitation pattern, which affects the distribution of plant species. The use of species distribution models is one of the most reliable techniques for investigating the impact of climate change on the distribution of plant species. One of the methods of plant distribution modeling is using the maximum entropy model. This model uses environmental conditions such as temperature, precipitation, and geographic altitude as inputs, and based on that, plant distribution is predicted. This model predicts the probability of species distribution in the new environment based on the theory of maximum entropy and based on the available data. In this model, based on the information we have about species distribution in different environments, a probability distribution is obtained for species distribution, which has the highest entropy. However, for the best prediction of the distribution of the species, we need to have detailed information about the biophysical, ecological and environmental characteristics of the species in question. In this method, instead of trying to model all aspects of the species and the environment, only the available information about the distribution of the species is used. In this study, the effect of climate change on the distribution of valerian (Valeriana sisymbriifolia) species is predicted using the maximum entropy model in Isfahan province.
Materials and methods
In this study, the effect of climate change on the prediction of the distribution of Valeriana sisymbriifolia species in Isfahan province was investigated using MaxEnt model. For this purpose, 50 points of presence of example in May 2022 in different regions were first registered by GPS device by random sample method and after collecting environmental data including 10 climate changes and 3 physiographic changes, the effect of climate change on the distribution of the plant species Valeriana sisymbriifolia in Isfahan province was investigated using the entropy machine model and in the time periods of 2020, 2050 and 2100, under two scenarios: SSP2 and RCP4.5. To study the effect of climate change on the distribution of Valeriana sisymbriifolia plant species in Isfahan province, new climate scenarios including SSP (Shared Socioeconomic Pathways) and RCP (Representative Concentration Pathways) scenarios were used. The SSP scenarios in the GFDL-ESM4 general circulation model correspond to a combination of paths in which the economy, population, and politics will change in the future. The RCP scenarios in HadGEM2-CC general circulation models also correspond to different levels of future greenhouse emissions.
Results and Discussion
The results showed that the distribution of Valeriana sisymbriifolia species in Isfahan province will decrease from 3.07% to 0.047% under RCP4.5 scenario in 2020 to 2100. Also, the distribution of this species under the SSP2 scenario showed that from 2020 to 2100, the distribution of the species and its favorable habitat will decrease from 3.74% to 1.554%. In fact, under both studied climate scenarios, the ideal habitat of valerian has decreased and will be completely lost in some areas. The entropy machine model showed that there are several factors affecting the distribution of valerian including slope, rainfall in the coldest season of the year, annual rainfall and altitude. Also, this model obtained Auc=0.95 in the evaluation, which shows the excellent prediction of the entropy model in predicting species distribution.
Conclusion
According to the output maps from the MaxEnt model and also according to the influence of important variables in this process, it can be concluded that the distribution of the species in question is decreasing under the influence of climate change in successive years. In addition, according to the response curves of the species in terms of physiography, as the slope and height increase in the area in question, the amount of distribution of the Hyacinth species also increases. Also, according to the field observations, it can be said that the species in question is observed in the slope and at very high altitudes, such that during sample collection the species in question was present at an altitude of 3000 meters, and the reason for this can be attributed to the strong roots of the plant, which creates the ability to reproduce in rocky conditions. On the other hand, because other species do not tolerate the same conditions, their presence decreases and the competition it decreases for the Hyacinth species. The response curves of the species to changes in rainfall also show that the more the annual rainfall and the rainfall in the cold months, the more likely the presence of the species will be, such that the more the annual rainfall exceeds 250 mm, the more likely it will occur.
Keywords
Climate change
Valeriana sisymbriifolia
MaxEnt model
species distribution model

Subjects

Abolmaali, M. (2014). Evaluation of the effect of climate change on the distribution of khashag and mountain celery species in Isfahan province. Pasture master's thesis. Pasture Department. Faculty of Natural Resources. Isfahan University of Technology. Iran. 103 p.
Adhikari, P., Lee, Y.H., Poudel, A., Lee, G., Hong, S.H. & Park, Y.S. (2023). Predicting the impact of climate change on the habitat distribution of Parthenium hysterophorus around the world and in South Korea. Biology. 12(1), 84.
Ahmadi, P. & Mustafavi. N. (2022). Predicting the effects of climate change on the distribution of Mesopotamichthys sharpeyi (Günther, 1874) in different climate scenarios. Iranian Remote Sensing and GIS Journal. (In Persian).
Akbari, M., Jafari, W. & Saadat, F. (2011). Determining the potential habitat of the yellow species using the integration of GIS and remote sensing. Remote sensing and geographic information system in natural resources. 1(1), 15-30.‎
Babaei Dehkordi, E., Naqipour.A. & Heydarian. A. (2022). Potential geographical distribution of Jashir species (Prangos ferulacea (L.) Lindl.) Under climate change scenarios in Chaharmahal and Bakhtiari province. Journal of Plant Ecosystem Protection. 10(20), 207-224.
Canturk, U. & Kulaç, Ş. (2021). The effects of climate change scenarios on Tilia ssp. in Turkey. Environmental Monitoring and Assessment. 193(12), 771.
Chegini, S., Tafvizi, F. & Noorbazargan, H. (2020). Effect of Valeriana Sysimberifolia Extract on VEGF Expression in A549 Cell Line. Journal of Babol University of Medical Sciences. 22(1), 222-228.
Coulibaly, A., Avakoudjo, H.G., Idohou, R., Vodounnon, E.J., Diallo, S. & Cherif, M. (2023). Impact of climate change on the distribution of Bombax costatum Pellegr. & Vuillet in Mali. West Africa. Trees. Forests and People. 11, 100359.
Del Barrio, G., Alvera, B., Puigdefabregas, J. & Diez, C. (1997). Response of high mountainlandscape to topographic variables: Central Pyrenees.Landscape Ecology. 12(2), 95-115.‏
Elith, J., Kearney, M. & Phillips, S. )2010(. The art of modelling range‐shifting species. Methods in ecology and evolution. 1(4), 330-342.‏
Fakhimi, E., Khodaqoli, M., Sabohi, R., Yousefi, Sa. & Shirmardi, Hamza Ali (2022). The effect of climate change on the geographical distribution of Bromus tomentellus species in Central Zagros (Chaharmahal and Bakhtiari Province). The third national conference on natural resources and sustainable development in Zagros, Shahrekord. (In Persian).
Fang, J., Wang, Z., Tang, Z. & Lin, X. (2020). Maximum entropy model-based estimation of vegetation distribution in China. Scientific Data. 7(1), 1-12.
Fricko, O., Havlík, P., Rogelj, J., Klimont, Z., Gusti, M., Johnson, N. & Valin, H. (2017). The marker quantification of the Shared Socioeconomic Pathway 2. A middle-of-the-road scenario for the 21st century. Global Environmental Change. 42, 251-267.
Gao, T., Xu, Q., Liu, Y., Zhao, J. & Shi, J. (2021). Predicting the potential geographic distribution of Sirex nitobei in China under climate change using maximum entropy model. Forests. 12(2), 151.
Gaston, A. & Garcia-Vinas, J.I. (2011). Modelling species distributions with penalised logistic regressions. A comparison with maximum entropy models. Ecological modelling. 222(13), 2037-2041.
HamadAmin, B. A. & Khwarahm, N. R. (2023). Mapping Impacts of Climate Change on the Distributions of Two Endemic Tree Species under Socioeconomic Pathway Scenarios (SSP). Sustainability. 15(6), 5469.
Heydari, F., Sabohi, R., Khodaqoli, M. & Salehpour, S. (2021). Evaluation of the effects of climate change on the habitat of Stipa arabica species in Kohgiluyeh and Boyer Ahmad provinces. The fifth national conference on climate change and its impact on agriculture and environment. Urmia. (In Persian).
IPCC. (2014). Climate Change 2014. Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change
IPCC. (2013). Climate Change 2013. The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change.
Khoshbakht, M. (2013). Prediction impacts of climate change on the potential habitat of Valeriana sisymbrifolia in the Isfahan province. Prediction impacts of climate change on the potential habitat of Valeriana sisymbrifolia in the Isfahan province. Master's thesis. Isfahan University of Technology. Isfahan Iran.
Liu, S., Wang, S., Zhang, Y., Wu, X. & Feng, X. (2021). Impacts of climate change on the distribution of plant species in Asia: a meta-analysis based on ecological niche modeling. Regional Environmental Change, 21(2), 1-13.
Mehdizadeh, S., Ahmadi, F. & Kouzehkalani Sales, A. (2023). Development of wavelet-based hybrid models to enhance daily soil temperature modeling: application of entropy and τ-Kendall pre-processing techniques. Stochastic Environmental Research and Risk Assessment, 37(2), 507-526.
Mirhashemi, H., Heydari, M., Ahmadi, K., Karami, O., Kavgaci, A., Matsui, T. & Heung, B. (2023). Species distribution models of Brant's oak (Quercus brantii Lindl.): The impact of spatial database on predicting the impacts of climate change. Ecological Engineering. 194. 107038.
Momeni Damaneh, J., Tajbakhsh, S.M., Ahmadi, J. & Safdari, A.A. (2023). Comparison of species distribution models in determining the habitat landscape of Pistacia vera L. specie in Razavi Khorasan province. Water and Soil Management and Modeling. 3(4), 77-92. (In Persian)
Naghipour Borj, A.A., Haidarian Aghakhani, M. & Sangoony, H. (2019). Application of ensemble modelling method in predicting the effects of climate change on the distribution of Fritillaria imperialis L. Journal of Plant Research (Iranian Journal of Biology). 32(3), 747-758.
Ngarega, B.K., Masocha, V.F. & Schneider, H. (2021). Forecasting the effects of bioclimatic characteristics and climate change on the potential distribution of Colophospermum mopane in southern Africa using Maximum Entropy (MaxEnt). Ecological Informatics, 65, 101419.
O’Neill, B.C., Kriegler, E., Ebi K.L., Kemp-Benedict, E., Riahi K., Rothman D.S., van Ruijven, B.J., Van Vuuren, D.P., Birkmann, J., Kok, K., Levy, M. & Solecki, W. (2017). The roads ahead: Narratives for shared socioeconomic pathways describing world futures in the 21st century. Global Environmental Change 42, 169–180.
Pashmforosh, N. & Ahmedabadi, M. (2020). Optimization of tissue culture and regeneration of valerian medicinal plant (Valeriana officinalis). Journal of Plant Research (Scientific). 33(1), 156-166.
Patasaraiya, M.K., Devi, R.M., Sinha, B. & Bisaria, J. (2023). Predicting Impacts of Climate Change on Teak and Sal Forests in Central India Using Maximum Entropy Modeling: an Approach for Future Conservation and Silvicultural Strategies. Forest Science. fxad014.
Qi, Y., Yu, H., Fu, Q., Chen, Q., Ran, J. & Yang, Z. (2022). Future changes in drought frequency due to changes in the mean and shape of the PDSI probability density function under RCP4. 5 scenario. Frontiers in Earth Science. 10, 857885.
Rezayi Zaman, M., Massah Bavani, A.R. & Javadi, S. (2023). Evaluation of the effects of SSP scenarios of Coupled Model Intercomparison Project Phase 6 (CMIP6) on water resources and agricultural crop in Hashtgerd region with the approach of applying an adaptation strategy. Journal of Environmental Science and Technology. 24(12), 93-107.
Riahi, K., Van Vuuren, D.P., Kriegler, E., Edmonds, J., O’Neill, B. C., Fujimori, S. & Lutz, W. (2017). The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview. Global Environmental Change.42. 153-168.
Riahi, K., Van Vuuren, D.P., Kriegler, E., Edmonds, J., O’Neill, B.C., Fujimori, S., Bauer, N., Calvin, K., Dellink, R., Fricko, O., Lutz, W., Popp, A., Cuaresma, J.C., Samir, K.C., Leimbach, M., Jiang, L., Kram, T., Rao, S., Emmerling, J., Ebi, K., Hasegawa, T., Havlik, P., Humpenöder, F., Da Silva L.A., Smith, S., Stehfest, E., Bosetti, V., Eom, J., Gernaat, D., Masui, T., Rogelj, J., Strefler, J., Droue, T.L., Krey, V., Luderer, G., Harmsen, M., Takahashi, K., Baumstark, L., Doelman, J. C., Kainuma, M., Klimont, Z., Marangoni, G., Lotze-Campen, H., Obersteiner, M., Tabeau, A. & Tavoni, M. (2017) The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview. Global Environmental Change, 42, 153–168.
Santos, B.A., Barbosa, D.C.A. & Tabarelli, M. (2007). Directional changes in plant assemblages along an altitudinal gradient in northeast Brazil. Brazilian Journal of Biology. 67(4), 777-779.‏
Soliman, M.M., Al-Khalaf, A.A. & El-Hawagry, M.S. (2023). Effects of Climatic Change on Potential Distribution of Spogostylum ocyale (Diptera: Bombyliidae) in the Middle East Using MaxEnt Modelling. Insects, 14(2), 120.
Solow, A.R. & Polasky, S. (1994). Measuring biological diversity.Environmental and Ecological Statistics. 1(2), 95-103.‏
Suleimany, M. (2023). Urban climate justice in hot-arid regions: Vulnerability assessment and spatial analysis of socio-economic and housing inequality in Isfahan. Iran. Urban Climate, 51, 101-612.
Tang, X., Yuan, Y., Li, X. & Zhang, J. (2021). Maximum entropy modeling to predict the impact of climate change on pine wilt disease in China. Frontiers in plant science, 12, 652500.
Wu, X., Tang, Y., Liu, S., Zhao, H. & Li, B. (2022). Impacts of climate change on the distribution of Artemisia sacrorum in the southwestern US based on the maximum entropy model. Environmental Science and Pollution Research, 1-11.
Xu, W., Zhu, S., Yang, T., Cheng, J. & Jin, J. (2022). Maximum entropy niche-based modeling for predicting the potential suitable habitats of a traditional medicinal plant (Rheum nanum) in Asia under climate changconditions. Agriculture, 12(5), 610.

  • Receive Date 16 July 2023
  • Revise Date 02 August 2023
  • Accept Date 09 August 2023