Methods to get more information from sparse vessel monitoring systems data

Vessel Monitoring Systems (VMS) and other vessel tracking data have been used for many years to map the distribution of fishing activities. Mapping areas with low levels of fishing activity can be of particular interest; for example to avoid conflicts between fishing and other ocean uses like offshore renewable energy or to protect relatively pristine ecosystems from increasing fishing pressure. A particular problem when trying to delineate areas that are lightly fished, is the relative sparsity of vessel monitoring data in these areas. This paper explores three novel methods for estimating the distribution of fishing activity from VMS data, with particular focus on lightly impacted areas. The first new method divides the area of interest into a nested grid with varying cell sizes (depending on the density of data at each location); the second new method uses Voronoi diagrams to define polygons around observations and the third method applies a local regression to generate a smooth map of fishing intensity. The new methods are compared with two established methods: applying spatial grids and interpolating fishing tracks. The track interpolation method generally performs better than any of the new methods, however it is not always possible or appropriate to apply track interpolation; in those cases the local regression method is the best alternative

Spatial Heterogeneity in Fishing Creates de facto Refugia for Endangered Celtic Sea Elasmobranchs

The life history characteristics of some elasmobranchs make them particularly vulnerable to fishing mortality; about a third of all species are listed by the IUCN as Threatened or Near Threatened. Marine Protected Areas (MPAs) have been suggested as a tool for conservation of elasmobranchs, but they are likely to be effective only if such populations respond to fishing impacts at spatial-scales corresponding to MPA size. Using the example of the Celtic Sea, we modelled elasmobranch biomass (kg h(−1)) in fisheries-independent survey hauls as a function of environmental variables and ‘local’ (within 20 km radius) fishing effort (h y(−1)) recorded from Vessel Monitoring Systems data. Model selection using AIC suggested strongest support for linear mixed effects models in which the variables (i) fishing effort, (ii) geographic location and (iii) demersal fish assemblage had approximately equal importance in explaining elasmobranch biomass. In the eastern Celtic Sea, sampling sites that occurred in the lowest 10% of the observed fishing effort range recorded 10 species of elasmobranch including the critically endangered Dipturus spp. The most intensely fished 10% of sites had only three elasmobranch species, with two IUCN listed as Least Concern. Our results suggest that stable spatial heterogeneity in fishing effort creates de facto refugia for elasmobranchs in the Celtic Sea. However, changes in the present fisheries management regime could impair the refuge effect by changing fisher's behaviour and displacing effort into these areas

Monitoring the recovery of exploited deep-water species

Commercial fisheries for deep-water species off the Irish coast developed in the late 1990s and declined in the early 2000s. Many of the exploited stocks were depleted a result of commercial exploitation and ICES has advised a zero catch for Orange Roughy since 2004, and for Portuguese Dogfish and Leafscale Gulper shark since 2005. Since 2016, the deep water access regulation has effectively banned trawling in waters deeper than 800 m (EC, 2016) and fishing for deep-water sharks with static netting >600 m is also banned by the technical measures regulation (EC, 2019). However, some of these species continue to be caught, either by gears not covered by this regulation or in water <800 m deep. The Marine Institute carried out a survey programme to assess the distribution and abundance of these species between 1992 and 1999 and again between 2006 and 2009. Since 2019, 3 days of the Irish Anglerfish and Megrim Survey have been allocated to monitoring the recovery of commercial deep-water species. This work was funded under the European Maritime and Fisheries Fund (EMFF) from 2019 to 2021 and European Maritime, Fisheries and Aquaculture Fund (EMFAF) since 2022. The main objective of the current project is to assess the recovery of exploited deep-water species in Irish waters by comparing the results from 2019 to 2022 surveys with those from the previous period in 2006 to 2009 (methods used in the earlier period 1992 to 1999 were different, therefore a direct comparison with that period is not possible).EMFF, EMFAF, the project is co-funded by the Government of Ireland and the European Unio

Precision estimates and suggested sample sizes for length-frequency data

For most fisheries applications, the shape of a length-frequency distribution is much more important than its mean length or variance. This makes it difficult to evaluate at which point a sample size is adequate. By estimating the coefficient of variation of the counts in each length class and taking a weighted mean of these, a measure of precision was obtained that takes the precision in all length classes into account. The precision estimates were closely associated with the ratio of the sample size to the number of size classes in each sample. As a rule-of-thumb, a minimum sample size of 10 times the number of length classes in the sample is suggested because the precision deteriorates rapidly for smaller sample sizes. In absence of such a rule-of-thumb, samplers have previously under-estimated the required sample size for samples with large fish, while over-sampling small fish of the same species