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Combining multiple data sets to unravel the spatiotemporal dynamics of a data-limited fish stock ArchiMer
Pinto, Cecilia; Travers-trolet, Morgane; Macdonald, Jed; Rivot, Etienne; Vermard, Youen.
The biological status of many commercially-exploited fishes remains unknown, mostly due to a lack of data necessary for their assessment. Investigating the spatio-temporal dynamics of such species can lead to new insights into population processes, and foster a path towards improved spatial management decisions. Here, we focused on striped red mullet (Mullus surmuletus), a widespread, yet data-limited species of high commercial importance. Aiming to quantify range dynamics in this data-poor scenario, we combined fishery-dependent and -independent datasets through a series of Bayesian mixed-effects models designed to capture monthly and seasonal occurrence patterns near the species’ northern range limit across 20 years. Combining multiple datasets allowed...
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Ano: 2019 URL: https://archimer.ifremer.fr/doc/00460/57187/59150.pdf
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