Improving the interpretability of the effects of environmental factors on abundance of fish stocks

Abstract

Adequately assess the environmental effects on commercially exploited fish stocks is one of the main challenges faced by stock managers in their attempt to achieve ecosystemic management. In this study, we have developed a methodology which allows simulate the evolution of abundance or biomass of a fish population and calculate two indexes (the significant effect of the environmental parameter-EF-and the relative weight index-RW-) that improve the interpretability of the environmental effects on abundance of fish stocks. This methodology is based on the assumption that under the premise of environmental invariability the variation in the abundance of a population is linearly dependent on its abundance in the past. These indexes have been integrated into a decision support system namely SFish SubClass 1.1, specifically designed to disaggregate the effects of different environmental factors on a commercially exploited fish population. We have applied our model to the fishery of Pagellus bogaraveo in a complex environmental area (Strait of Gibraltar). The results show that the developed methodology provides plausible simulations. Finally, the RW and EF indexes indicated that the most influential variables were salinity, sea temperature and salinity flux.

Historical changes of Blackspot seabream (Pagellus bogaraveo) landing patterns in the Strait of Gibraltar from 1983 to 2016: Environmental and legislation effects

“…This also supports the results reported by Gutiérrez‐Estrada et al. (2020). In this study, the authors developed two new indexes (the significant effect of the environmental parameter—EF—and the relative weight index—RW) that allow to improve the interpretability of the environmental effects on abundance of fish stocks applied to the same data set.…”

“…Again, these periods coincide with those in which the EF and RW indexes for SST and NAO are significant in Gutiérrez‐Estrada et al. (2020) which reinforce the idea that it is very difficult to establish causal relations between atmospheric indexes as NAO and parameters of the dynamic of commercially exploited fish population.…”

“…Likewise, its geographical location makes it sensitive to atmospheric variations with ocean‐scale teleconnections. For example, different studies show how the North Atlantic Oscillation index (NAO) may have an effect on the Blackspot seabream abundance in the Strait of Gibraltar (Báez et al., 2014; Gutiérrez‐Estrada et al., 2017, 2020; Sanz‐Fernández et al., 2019).…”

North Atlantic Oscillation and fisheries management during global climate change

“…Fishing is primarily an economic activity; therefore, some researchers have suggested the integration of economic drivers of change into ecological-economic models to forecast the effects of climate change (Quaas et al 2015). Although in principle this may be advisable, climatic variability can also affect economic performance by driving changes in catch prices due to the effects of the NAO on catchability (Ferna ´ndez et al 2020). Oremus (2019) obtained positive correlation between NAO and employment in the extraction industry of New England.…”