Modeling of Acacia tortilis (Forssk.) Hayne habitat suitability using maximum entropy method in Hormozgan province

Subject Areas : Applications in biodiversity conservation and management

cyrus madahi nejad ¹ , Yahya Esmaeilpour ^{2 *} , Marziyeh Rezai ³

1 - Ph.D. Candidate of Combatting desertification, Natural Resources Engineering Department, Faculty of Agriculture and Natural Resources, University of Hormozgan, Bandar Abbas, Hormozgan, Iran
2 - Assistant Professor, Department of Natural Resources Engineering, Faculty of Agriculture and Natural Resources, Hormozgan University, Bandar Abbas
3 - Assistant Professor of Natural Resources Engineering, University of Hormozgan, Bandar Abbas, Iran

Received: 2021-12-27 Accepted : 2022-02-04 Published : 2023-03-21

Keywords: Climatic factors, Acacia tortilis (Forssk. Hayne), Maximum Entropy, Habitat suitability,

Abstract :

Factors affecting the distribution of plant species include climate, soil properties, topography, land use, and total biological relationships. Climate is one of the most important factors in the distribution of plant species. The present study was conducted to predict the geographical distribution of Acacia tortilis (Forssk. Hayne), to find important environmental factors and to investigate the tolerance of the species to environmental factors in Hormozgan province. According to the purpose, vegetation information and habitat factors such as elevation, climate, geology and soil were collected. Vegetation sampling was done randomly-systematically by plotting along 4 transects of 200-1000 m. Map of environmental variables was prepared using GIS. Then, prediction maps related to species distribution were prepared using entropy modeling method. The accuracy of the obtained prediction models was evaluated using AUC statistics. In general, the results showed that the variables of total rainfall in the hottest season, seasonal changes of rainfall (coefficient of variation), total rainfall of the lowest rainfall of the year, average temperature of the driest season, average of the warmest season are the most important climatic characteristics. They affect the distribution of Acacia tortilis (Forssk. Hayne).characteristics. They affect the distribution of Acacia tortilis (Forssk. Hayne).The results of this study can solve the problems facing habitat management. In fact, when a species is threatened by habitat destruction, by recognizing the factors to which the species is highly dependent, conservation plans can be proposed according to the habitat needs of the species.

References:

1. Allen, A. W., Jordan, P. A., & Terrell, J. W. 1987. Habitat suitability index models: moose, Lake Superior region (Vol. 82). US Department of the Interior, Fish and Wildlife Service, Research and Development.‏
2. Anand, V., Oinam, B., & Singh, I. H. 2021. Predicting the current and future potential spatial distribution of endangered Rucervus eldii eldii (Sangai) using MaxEnt model. Environmental Monitoring and Assessment, 193(3), 147.‏
3. Bhandari, M.S., Shankhwar, R., Maikhuri, S., Pandey, S., Meena, R.K., Ginwal, H.S., Kant, R., Rawat, P.S., Martins-Ferreira, M.A.C. and Silveira, L.H.C., 2021. Prediction of ecological and geological niches of Salvadora oleoides in arid zones of India: causes and consequences of global warming. Arabian Journal of Geosciences, 14(6), pp.1-18.
4. Du, Z., He, Y., Wang, H., Wang, C. and Duan, Y., 2021. Potential geographical distribution and habitat shift of the genus Ammopiptanthus in China under current and future climate change based on the MaxEnt model. Journal of Arid Environments, 184, p.104328.
5. Ebrahimi, M. Piri Sahragard, H. madahinejad, c. 2015. Modeling the habitat suitability of plant species using MaxEnt method in Jiroft plain. MS.c Thesis, Zabol University, Faculty of Natural Resources (in Persian).
6. Edgar, P., and Bird, D.R. 2006: Action Plan for the Conservation of the Meadow Viper (Vipera ursinii) in Europe. Convention on the Conservation of European Wildlife and Natural Habitats Standing Committee, 26th meeting, Strasbourg, 27-29.
7. Emtehani, M.H. 2003. Native acacias of Iran. 1sd edn, Yazd University Press, Yazd, Iran, 122 pp (In Persian).
8. Teimoori Asl, S., Naghipour, A. A., Ashrafzadeh, M. R., & Haidarian Aga Khani, M. 2020. Predicting the effects of the climate change on the geographical distribution of Astragalus verus Olivier in the Central Zagros region. Journal of RS and GIS for Natural Resources, 11(2), 68-85 (In Persian).
9. Khalil, T., Asad, S. A., Khubaib, N., Baig, A., Atif, S., Umar, M., ... & Baig, S. (2021). Climate change and potential distribution of potato (Solanum tuberosum) crop cultivation in Pakistan using Maxent. AIMS Agriculture and Food, 6(2), 663-676.‏
10. Kong, F., Tang, L., He, H., Yang, F., Tao, J. and Wang, W., 2021. Assessing the impact of climate change on the distribution of Osmanthus fragrans using Maxent. Environmental Science and Pollution Research, pp.1-9.
11. Kumar, S., and Stohlgren, T. 2009. Maxent modeling for predicting suitable habitat for threatened and endangered tree Canacomyrica monticola in New Caledonia Journal of Ecology and Natural Environment. 1(4): 094-098.
12. Khanum, R., Mumtaz, A.S. and Kumar, S., 2013. Predicting impacts of climate change on medicinal asclepiads of Pakistan using Maxent modeling. Acta Oecologica, 49, pp.23-31.
13. Loth, P.E., Boer, W.F.de, Heitkönig, I.M.A. and Prins, H.H.T., 2005. Germination strategy of the East Africa savanna tree Acacia tortilis. Journal of Tropical Ecology, 21: 509-517
14. Mechergui, K., Altamimi, A. S., Jaouadi, W., Naghmouchi, S., & El Wellani, S. 2021. Modelling current and future potential distributions of Vachellia tortilis (Forssk.) Hayne subsp. raddiana (Savi.) Brenan var. raddiana under climate change in Tunisia. African Journal of Ecology, 59(4), 944-958.‏
15. Mgaywa, W. J. (2018). Influence of environmental variables on the distribution of selected tree species in lake Manyara upper catchment, northern-Tanzania (Doctoral dissertation, Sokoine University of Agriculture).‏
16. Naghiloo, M., Jafari, M., Tahmoures, M., Kohandel, A., & Hamedanian, F. 2010. An Investigation on Relationships between Soil Physiochemical Attributes and Vegetation Cover for DeterminingIndex Species in Savoj-bolagh Region. Journal of Range and Watershed Managment, 63(1), 119-11, (in Persian).
17. Phillips, S. J., Dudík, M., & Schapire, R. E. 2004. A maximum entropy approach to species distribution modeling. In Proceedings of the twenty-first international conference on Machine learning (p. 83).‏
18. Purohit, S. and Rawat, N., 2021. MaxEnt modeling to predict the current and future distribution of Clerodendrum infortunatum L. under climate change scenarios in Dehradun district, India. Modeling Earth Systems and Environment, pp.1-13.
19. Qayyumi, R., Ebrahimi, A., Hosseini Taifeh, F, Keshtkar, M. 2019. Predicting the effects of climate change on the distribution of mangrove forests in Iran using the maximum entropy model, Remote Sensing and GIS in Natural Resources, 10 (2), pp. 34-47. (in Persian)
20. Saha, A., Rahman, S., & Alam, S. 2021. Modeling current and future potential distributions of desert locust Schistocerca gregaria (Forskål) under climate change scenarios using MaxEnt. Journal of Asia-Pacific Biodiversity, 14(3), 399-409.‏
21. Scott, J.M., P.J. Heglund., M.L. Morrison., J.B. Haufler., M.G. Raphael, W.A. Wall and F.B. Samson, 2002. Predicting Species Occurrences: Issues of Accuracy and Scale. Island Press, Washington DC.
22. Sinclair, S. J., White, M. D., & Newell, G. R. 2010. How useful are species distribution models for managing biodiversity under future climates? Ecology and Society, 15(1).‏
23. Teymouri Asl, S., Naghipour Borj, A., Ashrafzadeh, M., Heidarian Agakhani, M. 2020. Predicting the Consequences of Climate Change on the Geographical Distribution of Yellow Astragalus (Astragalus verus Olivier) in the Central Zagros', Remote Sensing and Geographic Information System in Natural Resources, 11 (2), pp. 68-85 (in Persian).
24. Wei, B., Wang, R., Hou, K., Wang, X. and 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, p.e00477.
25. Zare Chahouki, M.A., Khalasi Ahvazi, L. and Azrnivand, H. 2012. Comparison of three modelin approaches for predictiong species distribution in mountainous scrub vegetation (Semnan rangelands, Iran). Polish Journal of Ecology, 60(2): 105-117.
26. Zarinkamar, F. 1996. Investigation of anatomical and ecological characteristics of 14 species of Astragalus spp. Research Institute of Range and Forest, 98p.
27. Zhang, H., & Zhao, H. 2021. Study on rare and endangered plants under climate: maxent modeling for identifying hot spots in northwest China. Cerne, 27, e-102667.‏
28. Zhao, Y., Deng, X., Xiang, W., Chen, L. and Ouyang, S., 2021. Predicting potential suitable habitats of Chinese fir under current and future climatic scenarios based on Maxent model. Ecological Informatics, 64, p.101393.
29. Zhao, Y., Zhao, M., Zhang, L., Wang, C. and Xu, Y., 2021. Predicting Possible Distribution of Tea (Camellia sinensis L.) under Climate Change Scenarios Using MaxEnt Model in China. Agriculture, 11(11), p.1122.