SummaryA Bayesian hierarchical approach is presented for the estimation of length-weight relationships (LWR) in fishes. In particular, estimates are provided for the LWR parameters a and b in general as well as by body shape. These priors and existing LWR studies were used to derive species-specific LWR parameters. In the case of data-poor species, the analysis includes LWR studies of closely related species with the same body shape. This approach yielded LWR parameter estimates with measures of uncertainty for practically all known 32 000 species of fishes. Provided is a large LWR data set extracted from www.fishbase.org, the source code of the respective analyses, and ready-to-use tools for practitioners. This is presented as an example of a self-learning online database where the addition of new studies improves the species-specific parameter estimates, and where these parameter estimates inform the analysis of new data.

Climate change is altering habitats for marine fishes and invertebrates, but the net effect of these changes on potential food production is unknown. We used temperature-dependent population models to measure the influence of warming on the productivity of 235 populations of 124 species in 38 ecoregions. Some populations responded significantly positively (n = 9 populations) and others responded significantly negatively (n = 19 populations) to warming, with the direction and magnitude of the response explained by ecoregion, taxonomy, life history, and exploitation history. Hindcasts indicate that the maximum sustainable yield of the evaluated populations decreased by 4.1% from 1930 to 2010, with five ecoregions experiencing losses of 15 to 35%. Outcomes of fisheries management—including long-term food provisioning—will be improved by accounting for changing productivity in a warmer ocean.