The development of spatio-temporal models of fishery catch-per-unit-effort data to derive indices of relative abundance

Spatio-temporal models are increasingly used to develop indices of population abundance from fishery-dependent and -independent data. Developments in spatio-temporal index standardization were discussed at a workshop hosted by The Center for the Advancement of Population Assessment Methodology (CAPAM) titled Development and application of spatio-temporal models to derive indices of relative abundance (La Jolla, CA, USA; Feb. 26-March 2, 2018). This special issue includes ten submissions that highlight potential benefits arising from spatio-temporal index standardization including: (1) improved prediction for areas with little-to-no data; (2) capacity to weight densities by area to account for sampling rates that vary spatially; (3) calculation of the composition (e.g. age or length) of the indices and to weight predictions by catch to inform the composition of fishery removals, (4) estimation of distribution shifts and range expansion/contraction; and (5) capacity to combine data sources. The articles in this Special Issue highlight the need for continued development and testing for spatio-temporal index standardization methods, so that the relative strengths and weaknesses of different approaches are fully understood. The articles also identify topics that warrant further research including improved model diagnostics, accounting for biased rates of sampling (preferential sampling), and improvements in computational efficiency.