Bycatch of Myliobatid Rays in the Central Mediterranean Sea: the Influence of Spatiotemporal, Environmental, and Operational Factors as Determined by Generalized Additive Modeling

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Abstract

Identification of the factors influencing the distribution of vulnerable species can be useful for predicting their occurrence at a local to regional scale and for identifying the most suitable measures of management and conservation. We used generalized additive models to assess the effects of spatiotemporal, environmental, and operational factors on the catches of two myliobatids: the Common Eagle Ray Myliobatis aquila and the Bull Ray Pteromylaeus bovinus. Fishing data were collected from commercial midwater trawlers operating in the north-central Adriatic Sea during 2006–2013. Presence/absence and abundance (CPUE) data were modeled separately, and eachmodel was then validated by using a test data set. The presence/absence and abundance of Common Eagle Rays and Bull Rays were mostly influenced by spatial (haul location) and temporal predictors. The major occurrences of Common Eagle Rays and Bull Rays were observed in the upper Adriatic Sea between late spring and early autumn. During winter, a southward shift in the catch was recorded for both species. In accordance with a significant effect of depth, Common Eagle Rays were more likely to be caught in hauls conducted between 10- and 60-m depths. The CPUEs of Common Eagle Rays and Bull Rays declined significantly with haul duration and net vertical opening. The validation procedure indicated that the predictive accuracy of the models was rather good. Giving new insight into the ecological requirements of Common Eagle Rays and Bull Rays, the results of this studymay contribute to the development of conservation strategies and can be used to direct future monitoring and research programs.

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Mesa, G. L., Annunziatellis, A., Filidei, E., & Fortuna, C. M. (2016). Bycatch of Myliobatid Rays in the Central Mediterranean Sea: the Influence of Spatiotemporal, Environmental, and Operational Factors as Determined by Generalized Additive Modeling. Marine and Coastal Fisheries, 8, 382–394. https://doi.org/10.1080/19425120.2016.1167795

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