A novel approach to assess distribution trends from fisheries survey data
2019
Abstract Climate change and fishery impacts modify the spatial distribution of marine species. Understanding and predicting changes in distribution is important for adaptation by fishers and the management of fishery resources and biodiversity. However, identifying such trends is challenging given the variability inherent in trawl survey data. We apply a novel two-step approach to identify fish distribution trends from trawl surveys. First, species-specific average locations (mean latitude and longitude centre of gravity) and extent (effective area occupied) were estimated within a spatio-temporal delta modelling framework. The resulting time series and associated variance estimates were then passed to a multivariate Bayesian state-space model to estimate average trends over the study period. We applied this two-stage approach to three decades (1986–2016) of demersal trawl research survey data from the Agulhas Bank of South Africa to quantify distributional changes in 44 commonly caught fishes (chondrichthyans and teleosts). Across the entire assemblage, average trends showed a westward (alongshore) shift in location and a reduction in the extent of populations. At the species level, six taxa showed a location trend towards the west or south-west, and three shifted towards the east or north-east. The area occupied by species showed two taxa that had a decreasing trend in spatial extent and one species that was expanding. The mean westward and contracting trends of the assemblage were interpreted as likely signals of climate forcing, whereas the eastward shift of three species may be linked to fishing impacts. A lack of knowledge of subsurface oceanographic changes in the region challenges interpretation of the distribution changes and is identified as a research priority. We recommend additional research regarding causal drivers of distribution shifts, specifically to attribute observed changes to climate, fishing, and inter-annual environmental variability.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
80
References
7
Citations
NaN
KQI