Probability ogives for trends in stock biomass and fishing mortality from landings time series

Abstract

Most fisheries are conducted without any scientific knowledge about the size and productivity of the stocks that support them. This navigation in the dark in most fisheries is a major obstacle in making them sustainable sources of nutrition for people in general and income for fishers and other economic actors along supply chains. Fisheries that have not been assessed generally are data-intermediate and data-poor, the latter usually having annual time series of landings as the single piece of data available. A major effort in the last two decades has been directed toward developing ‘catch-only’ stock assessment methods, although some of these methods have been tested and found deficient. Here we provide a novel approach to using annual landing time series as the single source of data to qualitatively judge the condition of un-assessed stocks using frequentist cumulative probability ogives, both in terms of stock biomass and fishing mortality. A meta-analysis of the FishSource database allowed us to infer statistical patterns from hundreds of assessed fisheries and thousands of annual landings, biomass, and fishing mortality observations. Four stock-management types were considered separately in the analysis: short-lived and others (mid- to long-lived) stocks, controlled or not controlled by catch limits. Obtained cumulative probability ogives provide clear evaluations of stock biomass and fishing mortality trends in all four stock-management types, leading to actionable information on probable current status and future trends. Using these probability ogives, we developed decision trees that lead to qualitative scores on the exploitation status of un-assessed stocks.