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Estimating stock depletion level from patterns of catch history
[post]
2018
unpublished
The degree to which a stock is depleted is one of the most important quantities in fisheries management because it is used to quantify the success of management and to inform management responses. However, stock depletion is extremely difficult to estimate, particularly with limited data. Using the RAM Legacy database, we developed a boosted regression tree (BRT) model to correlate depletion with a range of predictors calculated from catch data, making the model usable for many fisheries
doi:10.31230/osf.io/5nxt7
fatcat:z5vznm3lvfe7ddz5xdhy44meau