Incorporation of optimal environmental signals in the prediction of fish recruitment using random forest algorithms

The drivers of recruitment of selected Baltic sprat (Sprattus sprattus) and herring (Clupea harengus) stocks were investigated. Data on the interaction dynamics among fish species, the biological characteristics of the stocks, the biomass of the main predators, and the hydroclimatic environmental factors (Baltic Sea Index and sea surface temperature) were used in the analysis. The combination of random forest (Boruta algorithm) and “sliding...