Temporal habitat suitability modeling of Caspian shad (Alosa spp.) in the southern Caspian Sea

Abstract

To comprehensively manage an ecosystem such as that of the Caspian Sea, the world's largest lake, detailed knowledge of the habitat traits of the living organisms in the ecosystem is essential. The present study examined environmental variables and used the Habitat Suitability Index (HSI) model to determine the most preferred seasonal habitat and optimal environmental range of Caspian shad (Alosa spp). The fish preferred deep waters with low levels of total organic matter and sea level anomaly in winter and productive areas with a high concentration of chlorophyll-a (Chla) and relatively high benthos biomass in spring. The number per unit area (NPUA)-based HSI model determined that the geometric mean model (GMM) was the optimal model for defining a suitable habitat in winter. For spring, the arithmetic mean model (or GMM) in the NPUA-based HSI model most accurately predicted preferred habitat for Caspian shad. The average NPUA in both seasons increased with the HSI; areas with an HSI of between 0.4 and 0.6 in spring and between 0.6 and 0.8 in winter had a high percentage of total catch. Areas with an HSI of more than 0.5 had over 91% and 63% of the total catch in spring and winter, respectively, demonstrating the reliability of the NPUA-based HSI model in predicting Caspian shad habitat. The present study shows that remotely sensed data plus depth are the most critical environmental variables in Caspian shad habitats and that Chla and SLA are the most critical remotely sensed parameters for near real-time prediction of Caspian shad habitat.