A recent update introduced to the CMSY methodology used for assessing the status of fish stocks has proven to be more accurate in predicting the catch that a population can support than highly-valued data-intensive models.
In a paper published in the journal Acta Ichthyologica et Piscatoria, the international team of researchers that shaped the improved CMSY++ model noted that its results better correspond with what is, in reality, the highest catch that a fish stock can support in the long-term, given that environmental conditions do not change much.
Now powered by an artificial neural network that has been trained with catch and biomass data of 400 stocks to identify plausible ranges of the initial and final state of the stocks being assessed, CMSY++ allows managers and scientists to input only catch data to estimate how much fish is left in a given stock and how much fishing pressure can be applied.
