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Lookup NU author(s): Dr Fabrice StephensonORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© The Author(s) 2024.Effective ecosystem-based management of bottom-contacting fisheries requires understanding of how disturbances from fishing affect seafloor fauna over a wide range of spatial and temporal scales. Spatial predictions of abundance for 67 taxa were developed, using an extensive dataset of faunal abundances collected using a towed camera system and spatially explicit predictor variables including bottom-trawl fishing effort, using a Joint Species Distribution Model (JSDM). The model fit metrics varied by taxon: the mean tenfold cross-validated AUC score was 0.70 ± 0.1 (standard deviation) for presence–absence and an R2 of 0.11 ± 0.1 (standard deviation) for abundance models. Spatial predictions of probability of occurrence and abundance (individuals per km2) varied by taxon, but there were key areas of overlap, with highest predicted taxon richness in areas of the continental shelf break and slope. The resulting joint predictions represent significant advances on previous predictions because they are of abundance, allow the exploration of co-occurrence patterns and provide credible estimates of taxon richness (including for rare species that are often not included in more commonly used single-species distribution modelling). Habitat-forming taxa considered to be Vulnerable Marine Ecosystem (VME) indicators (those taxa that are physically or functionally fragile to anthropogenic impacts) were identified in the dataset. Spatial estimates of likely VME distribution (as well as associated estimates of uncertainty) were predicted for the study area. Identifying areas most likely to represent a VME (rather than simply VME indicator taxa) provides much needed quantitative estimates of vulnerable habitats, and facilitates an evidence-based approach to managing potential impacts of bottom-trawling.
Author(s): Stephenson F, Bowden DA, Rowden AA, Anderson OF, Clark MR, Bennion M, Finucci B, Pinkerton MH, Goode S, Chin C, Davey N, Hart A, Stewart R
Publication type: Article
Publication status: Published
Journal: Biodiversity and Conservation
Year: 2024
Volume: 33
Pages: 3103-3127
Online publication date: 30/07/2024
Acceptance date: 02/07/2024
Date deposited: 16/08/2024
ISSN (print): 0960-3115
ISSN (electronic): 1572-9710
Publisher: Springer Science and Business Media B.V.
URL: https://doi.org/10.1007/s10531-024-02904-y
DOI: 10.1007/s10531-024-02904-y
Data Access Statement: The data generated in this research will be shared on reasonable request to the corresponding author. The R code used in this research is available in the GitHub open repository https://github.com/ Fabrice-Stephenson/Using_JSDM_to_predict_VME.
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