87-4 Overfishing or Environmental Change: What Causes Changes in the Productivity of Marine Fish Stocks
The relative importance of environmental conditions and stock abundance in determining the productivity of fish stocks has been the subject of an on-going debate. There are three main perspectives: productivity is driven by fishing pressure; productivity is environmentally driven presenting regimes of good and bad productivity; productivity varies randomly. These hypotheses are not mutually exclusive: both stock size and fishing pressure can affect productivity, and productivity may occur randomly or alternate between regimes of good and bad conditions.
This project used historic data from worldwide assessments from the RAM II legacy database. The RAM II Legacy database was a resource of data on biomass and catch of 417 stocks of marine fish and invertebrates. 276 of these stocks had suitable time series to calculate the history of the production in each year. These stocks represented 29 large marine ecosystems over 60 years period.
The drivers of fish productivity were identified using AICc model selection to compare three models: a regime shift model accounting for states of high and low productivity; a production model relating surplus production to stock size; and a null model that assumes productivity to be random. AICc multi-model weighting were used to evaluate the relative explanatory power of these three alternative hypotheses. It was found that more then 70% of the stocks were driven by regime shifts in environment, 18% were driven by fishing pressure and the 12% of the stocks had a productivity that varies randomly.
This project used historic data from worldwide assessments from the RAM II legacy database. The RAM II Legacy database was a resource of data on biomass and catch of 417 stocks of marine fish and invertebrates. 276 of these stocks had suitable time series to calculate the history of the production in each year. These stocks represented 29 large marine ecosystems over 60 years period.
The drivers of fish productivity were identified using AICc model selection to compare three models: a regime shift model accounting for states of high and low productivity; a production model relating surplus production to stock size; and a null model that assumes productivity to be random. AICc multi-model weighting were used to evaluate the relative explanatory power of these three alternative hypotheses. It was found that more then 70% of the stocks were driven by regime shifts in environment, 18% were driven by fishing pressure and the 12% of the stocks had a productivity that varies randomly.