Combining fisheries surveys to inform marine species distribution modelling. (20th January 2020)

• Record Type: Journal Article
• Authors: Moriarty, Meadhbh; Sethi, Suresh A; Pedreschi, Debbi; Smeltz, T Scott; McGonigle, Chris; Harris, Bradley P; Wolf, Nathan; Greenstreet, Simon P R
• Editors: Kotwicki, Stan
• Is Part Of: ICES journal of marine science. Volume 77:Number 2(2020)
• Page Start: 539
• Page End: 552
• Publication Date: 2020-01-20
• Subjects: catchability -- fisheries-independent assessment -- gear efficiency -- generalized additive mixed model -- species distribution modelling -- survey standardization; Ocean -- Periodicals; Fisheries -- Periodicals; Fishes -- Periodicals; Marine biology -- Bibliography -- Periodicals; 551.4605
• DOI: 10.1093/icesjms/fsz254
• Languages: English
• ISSNs: 1054-3139

Abstract

Abstract: Ecosystem-scale examination of fish communities typically involves creating spatio-temporally explicit relative abundance distribution maps using data from multiple fishery-independent surveys. However, sampling performance varies by vessel and sampling gear, which may influence estimated species distribution patterns. Using GAMMs, the effect of different gear–vessel combinations on relative abundance estimates at length was investigated using European fisheries-independent groundfish survey data. We constructed a modelling framework for evaluating relative efficiency of multiple gear–vessel combinations. 19 northeast Atlantic surveys for 254 species-length combinations were examined. Space-time variables explained most of the variation in catches for 181/254 species-length cases, indicating that for many species, models successfully characterized distribution patterns when combining data from disparate surveys. Variables controlling for gear efficiency explained substantial variation in catches for 127/254 species-length data sets. Models that fail to control for gear efficiencies across surveys can mask changes in the spatial distribution of species. Estimated relative differences in catch efficiencies grouped strongly by gear type, but did not exhibit a clear pattern across species' functional forms, suggesting difficulty in predicting the potential impact of gear efficiency differences when combining survey data to assess species' distributions and highlighting the importance of modelling approaches that can control for gear differences.