Predicting and modeling of habitat preferences of fish is a very important issue for aquatic management. Classification trees (CTs) were used to predict the habitat preferences of the Caspian kutum (Rutilus frisii kutum, hereafter kutum) in the southern Caspian Sea. The applied model was optimized with genetic algorithm (GA) and greedy stepwise (GS) to select the most explanatory variables for predicting the presence/absence of kutum. The suitability index was considered to determine the quality and suitability of fish habitat in the sea. The results of Paired Student’s t tests showed that there was a significant difference between predictive performances of models before and after variable selection methods. Both optimizers improved the predictive power of CTs and resulted in a better understanding of CTs by making a selection of the sea characteristics that were used as inputs to the models. The results show that the effect of different seasons, sea depth, and photosyntheticaly active radiation were the main predictors affecting the habitat preferences of kutum in the Caspian Sea. Constructed trees in combination with GA and GS showed high capability when applied to predict the habitat preferences of this valuable commercial fish species. Determining the habitat needs of the target fish will enhance local fisheries performances and the long-term conservation planning of the fish to implement the ecosystem-based management in the Caspian Sea.
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The datasets were provided by the Caspian Sea Ecology Research Centre. The first author would like to thank Iranian national elite centre and Ministry of science, research, and technology.
Handling editor: Gideon Gal
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Haghi Vayghan, A., Zarkami, R., Sadeghi, R. et al. Modeling habitat preferences of Caspian kutum, Rutilus frisii kutum (Kamensky, 1901) (Actinopterygii, Cypriniformes) in the Caspian Sea. Hydrobiologia 766, 103–119 (2016). https://doi.org/10.1007/s10750-015-2446-3
- Caspian kutum
- Caspian Sea
- Habitat preferences
- Habitat modeling