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| Walker, Emily; Rivoirard, Jacques; Gaspar, Philippe; Bez, Nicolas. |
| In the open ocean, movements of migratory fish populations are typically surveyed using tagging methods that are subject to low sample sizes for archive tags, except for a few notable examples, and poor temporal resolution for conventional tags. Alternatively, one can infer patterns of movement of migratory fish by tracking movements of their predators, i.e., fishing vessels, whose navigational systems (e.g., GPS) provide accurate and frequent VMS (vessel monitoring system) records of movement in pursuit of prey. In this paper, we develop a state-space model that infers the foraging activities of fishing vessels from their tracks. Second, we link foraging activities to probabilities of tuna presence. Finally, using multivariate geostatistical interpolation... |
| Tipo: Text |
Palavras-chave: GPS; Multivariate geostatistics; Presence index; Spatiotemporal distribution; Trajectometry; Tropical tuna; Vessel monitoring system (VMS). |
| Ano: 2015 |
URL: https://archimer.ifremer.fr/doc/00610/72249/71048.pdf |
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| Aronés, Katia; Grados, Daniel; Ayón, Patricia; Bertrand, Arnaud. |
| Anchovy (Engraulis ringens) is the most important exploited fish species in the Northern Humboldt Current System (NHCS) off Peru. This species, as well as most other pelagic resources, mainly forage on zooplankton. The NHCS is bottom-up controlled at a variety of scales. Therefore, fish biomass is driven by the abundance of their prey. In this context, we studied the spatiotemporal patterns of zooplankton biomass in the NHCS from 1961-2012. Data were collected with Hensen net all along the Peruvian coast. To transform zooplankton biovolume into biomass we used a regression that was calibrated from 145 zooplankton samples collected during four surveys and, for which, precise information was available on both biovolume and wet weight. The regression model... |
| Tipo: Text |
Palavras-chave: Secondary production; Mesozooplankton; Macrozooplankton; Regime-shift; Spatiotemporal distribution; Decadal trends. |
| Ano: 2019 |
URL: https://archimer.ifremer.fr/doc/00588/70042/67972.pdf |
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