The objective of this study is to analyse at fine scale the annual, seasonal and spatial distributions of several species in the Eastern English Channel (EEC). On the one hand, data obtained from scientific surveys are not available all year through, but are considered to provide consistent yearly and spatially resolved abundance indices. On the other hand, on-board commercial data do cover the whole year, but generally provide a biased perception of stock abundance. The combination of scientific and commercial catches per unit of effort (CPUEs), standardized using a delta-generalized linear model, allowed to infer spatial and monthly dynamics of fish distributions in the EEC, which could be compared with previous knowledge on their life cycles. Considering the scientific survey as a repository, the degree of reliability of commercial CPUEs was assessed with survey-based distribution using the Local Index of Collocation. Large scale information was in agreement with literature, especially for cuttlefish. Fine scale consistency between survey and commercial data was significant for half of the 19 tested species (e.g. whiting, cod). For the other species (e.g. plaice, thornback ray), the results were inconclusive, mainly owing to poor commercial data coverage and/or to particular aspects of the species biology.Ecosystem-Based Fisheries Management (EBFM) requires enhancing knowledge of 32 ecosystem functioning, therefore allowing forecasting the impact of fisheries on salient 33 ecosystem components (Long et al., 2015) and to design future management plans and tools 34 including Marine Protected Areas (Meyer et al., 2007) or fishing closures (Hunter et al., 35 2006). This necessitates a stepwise approach, the first tier of which, and one of the most 36 important, is to gain fine scale knowledge on the seasonal and geographic distribution of 37 marine organisms, in general, and fish stocks in particular (Booth, 2000). 38 Scientific surveys have been implemented for decades to derive spatially-and yearly-resolved 39 abundance indices of commercial fish and shellfish species (e.g. van Keeken et al., 2007).
40Surveys provide abundance indices, derived from standardized and controlled protocols, 41 which allow for a wide spatial coverage associated with a weak selectivity (Verdoit et al., 42 2003). Survey data, however, are costly to obtain and therefore rarely provide for adequate 43 seasonal coverage of the resource distribution. In contrast, information derived from 44 commercial fisheries are generally available all year through. Consequently, the catch per unit 45 of effort (CPUE), the most common and easily collected fishery-dependent index of 46 abundance (Maunder and Punt, 2004), has the potential to reflect fish distributions. However, 47 commercial CPUEs can generally not be used directly as abundance indicators. This is 48 because fishers target rather than sample fish densities, and continuously adapt their activities 49 to prevailing conditions, through technological development and tactical ...
