Methodological considerations when using local knowledge to infer spatial patterns of resource exploitation in an Irish Sea fishery

Despite the potential of local knowledge (LK) to provide reliable, quick, and low cost data, its use has been limited due to the lack of understanding of the accuracy and biases. We compared fishers' spatial LK data and fishery independent data from vessel monitoring systems (VMS) to analyse the concurrence between fisher derived and independently derived information. We examined the effect of sample size and scale on the match, to indicate the most appropriate approaches for future studies. Whilst LK provided a reasonable estimate of fishing extent, the estimated intensity of fishing was less well correlated with the VMS data. The agreement between LK and VMS data was significantly affected by the sample size from which LK knowledge was derived. There can be considerable variation in the accuracy of individual LK samples, therefore the sample size must be maximised to buffer for unreliable LK samples. A finer grid provided a more accurate representation of fishing extent; however, fishing intensity was more accurate when a coarser grid resolution was used. The use of a larger grid could also buffer some of the inaccuracy of a small sample size when determining intensity. Local knowledge can provide data of a similar accuracy to conventional scientific data, which is of particular use in data poor situations, e.g. in developing countries and for inshore fisheries that have no current mandatory VMS recording systems. However, the proportion of the community sampled should be maximised to minimise inaccuracy between individual fishers.