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The 'presentist bias' in time-series data: Implications for fisheries science and policy

by Daniel Pauly; Dirk Zeller

Feb 3, 2018

The bias in catch time series data that occurs when improvements in fisheries catch reporting systems (e.g.,consideration of a previously unmonitored fishery, or region) lead to an increase in current catches without thecorresponding past catches being corrected retroactively, here called 'presentist bias' is described, and twoexamples, pertaining to Mozambique and Tanzania are given. This bias has the effect of generating catch timeseries at the aggregate that appear 'stable' or increasing when in fact catches are declining over time, withpotentially serious consequences for the assessment of the status of national fisheries, or in interpreting theglobal landings data disseminated by the FAO. The presentist bias can be compensated for by retroactive nationaldata corrections as done, e.g., through catch reconstructions.