Forecasting habitat changes of Vimba persa (Pallas, 1814) under climate change using machine learning techniques in the southern Caspian Sea basin

Najmeh Tabasinezhad; Hamed Mousavi-Sabet; Hossein Mostafavi

doi:10.22034/ijab.v12i1.2125

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Najmeh Tabasinezhad Fisheries Department, Faculty of Natural Resources, University of Guilan, Sowmeh Sara, Iran.
Hamed Mousavi-Sabet Fisheries Department, Faculty of Natural Resources, University of Guilan, Sowmeh Sara, Iran.
Hossein Mostafavi
[email protected]
Department of Biodiversity and Ecosystem Management, Environmental Sciences Research Institute, Shahid Beheshti University, Tehran, Iran.

Vol. 12 No. 1 (2024): February

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February 25, 2024

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The global climate change will decrease species distribution, loss of biodiversity, and decreased food security. The main purpose of this study was to forecast the distribution of Vimba persa in the southern Caspian Sea basin under two optimistic and pessimistic scenarios in 2050 and 2080 by the MaxEnt model in R software. Five environmental variables ?were used for the modeling: annual ?mean temperature, annual temperature range, annual ?precipitation, flow accumulation, and slope. The results demonstrated that the model's performance in predicting species distribution was "Good" (0.862) based on the Area Under the Curve criterion. The annual temperature range variable had the greatest impact (61.5) on determining the distribution of the studied species among the environmental variables used in modeling. Moreover, the results indicate that the distribution range of the Caspian vimba is likely to be reduced in 2050 and 2080 under both optimistic and pessimistic climate change scenarios. Hence, the decreasing distribution of this fish, an economic species interested in sport fishing, poses a serious threat to food security and livelihoods for local communities. In conclusion, policymakers should focus on increasing public awareness, implementing correct management practices, taking preventive measures, developing protection plans, allocating more funds for reconstruction and the restoration of aquatic ecosystems, and trying to reduce the accelerating factors of climate change.

Tabasinezhad, N., Mousavi-Sabet, H., & Mostafavi, H. (2024). Forecasting habitat changes of Vimba persa (Pallas, 1814) under climate change using machine learning techniques in the southern Caspian Sea basin. International Journal of Aquatic Biology, 12(1), 109–119. https://doi.org/10.22034/ijab.v12i1.2125

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