The global decline of marine fish stocks calls for sustainable fisheries anagement based on reliable quantitative estimates. Dynamic spatial distributions of fish populationsrespond to biological, environmental and anthropogenic drivers. Species distribution models involving data from those areas enable projection of fish presence and abundance. They rely on an international fisheries independent survey effort across large spatial scales by multiple agencies with different equipment. Typically,surveysfocus on individual geographical or jurisdictional regions, which are not reflective of natural species ranges. This generates the challenge, how to best combine heterogeneous fisheriessurvey data for marine species distribution research. Therefore, a standardisation protocol which generated a Quality Assurance–Quality Audited dataset of groundfish surveys was developed. Its public availability constitutes an important contribution to the European fisheries research community and has led to applicationsin inferential studies outside the scope of this dissertation. Amodelling framework for combining fisheries surveys to examine species distribution on a multi-regional scale for the North East Atlantic Ocean was devised. It allowed evaluation ofrelative efficiency of gear-vessel combinations on 19 surveys for 254 species-length combinations. Estimated relative differences in catch efficiencies grouped strongly by gear type, but there were no clear patterns across the species’ functional forms. A critical evaluation of species distribution modelling approaches evaluated the potential for, and limitations of,tracking current and future spatial distribution of marine taxa and characterizing habitat niches. The application of generalised additive models to presenceabsence data provided the most consistent resultsfor four test species (Raja microocellata, Leucoraja naevus, Eutrigla gurnardus and Sebastes viviparous), which were categorised as “local”/“widespread” and “common”/“rare” to capture distribution patterns within the survey data. Among tested environmental variables mean seafloor temperature was most influential and thus appears fundamental to understanding the drivers of change in species distributions, particularly in changing climates.
|Date of Award||Jun 2021|
|Sponsors||Department of Education and Learning|
|Supervisor||Paul Dunlop (Supervisor) & Rory Quinn (Supervisor)|
- Climate change
- Species distribution modelling,
- North East Atlantic