Integrating vessel monitoring systems (VMS) data with daily catch data from logbooks to explore the spatial distribution of catch and effort at high resolution.

Abstract

Vessel monitoring systems (VMS) automatically collect positional data from fishing vessels. The VMS data can be linked to catch data from logbooks to provide a census of spatially resolved catch-and-effort data. We explore and validate the most appropriate and practical method for integrating Irish VMS and logbook data. A simple speed rule is applied to identify VMS records that correspond to fishing activity. These data are then integrated with the catch data from logbooks using date and vessel identifier. A number of assumptions were investigated, and the resulting distribution maps of catch and effort appear to be unbiased. The method is illustrated with an example of a time-series of spatially explicit catch-per-unit-effort (cpue) estimates. The proposed method is relatively simple and does not require specialist software or computationally intensive methods. It will be possible to generalize this approach to similar datasets that are available within the EU and many other regions. Analysis of integrated VMS and logbook data will allow fisheries data to be analysed on a considerably finer spatial scale than was possible in the past, which opens up a range of potential applications.