Identifying priority areas for spatial management of mixed fisheries using ensemble of multi‐species distribution models

Author:

Panzeri Diego12ORCID,Russo Tommaso345,Arneri Enrico5,Carlucci Roberto46,Cossarini Gianpiero1,Isajlović Igor7,Krstulović Šifner Svjetlana8,Manfredi Chiara4,Masnadi Francesco5,Reale Marco1,Scarcella Giuseppe5,Solidoro Cosimo1,Spedicato Maria Teresa9,Vrgoč Nedo7,Zupa Walter9,Libralato Simone1ORCID

Affiliation:

1. National Institute of Oceanography and Applied Geophysics – OGS Trieste Italy

2. University of Trieste Trieste Italy

3. Laboratory of Experimental Ecology and Aquaculture, Department of Biology University of Rome Tor Vergata Rome Italy

4. CoNISMa, National Inter‐University Consortium for Marine Sciences Rome Italy

5. National Research Council, Institute for Marine Biological Resources and Biotechnology Ancona Italy

6. Department of Biology University of Bari Bari Italy

7. Institute of Oceanography and Fisheries Split Croatia

8. Department of Marine Studies University of Split Split Croatia

9. COISPA‐ Technology and Research Bari Italy

Abstract

AbstractSpatial fisheries management is widely used to reduce overfishing, rebuild stocks, and protect biodiversity. However, the effectiveness and optimization of spatial measures depend on accurately identifying ecologically meaningful areas, which can be difficult in mixed fisheries. To apply a method generally to a range of target species, we developed an ensemble of species distribution models (e‐SDM) that combines general additive models, generalized linear mixed models, random forest, and gradient‐boosting machine methods in a training and testing protocol. The e‐SDM was used to integrate density indices from two scientific bottom trawl surveys with the geopositional data, relevant oceanographic variables from the three‐dimensional physical‐biogeochemical operational model, and fishing effort from the vessel monitoring system. The determined best distributions for juveniles and adults are used to determine hot spots of aggregation based on single or multiple target species. We applied e‐SDM to juvenile and adult stages of 10 marine demersal species representing 60% of the total demersal landings in the central areas of the Mediterranean Sea. Using the e‐SDM results, hot spots of aggregation and grounds potentially more selective were identified for each species and for the target species group of otter trawl and beam trawl fisheries. The results confirm the ecological appropriateness of existing fishery restriction areas and support the identification of locations for new spatial management measures.

Funder

European Regional Development Fund

Publisher

Wiley

Subject

Management, Monitoring, Policy and Law,Aquatic Science,Ecology, Evolution, Behavior and Systematics,Oceanography

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