Remotely Sensing the Biophysical Drivers of Sardinella aurita Variability in Ivorian Waters
| Autor: | Marie-Fanny Racault, Brice A. Mobio, Kouadio Affian, Shubha Sathyendranath, Dionysios E. Raitsos, Jean-Baptiste Kassi, Trevor Platt |
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| Rok vydání: | 2018 |
| Předmět: |
0106 biological sciences
education.field_of_study 010504 meteorology & atmospheric sciences Overfishing biology 010604 marine biology & hydrobiology Fishing Population Pelagic zone biology.organism_classification 01 natural sciences Fishery ocean color chlorophyll fisheries management Sardinella aurita phenology predictive model remote sensing phytoplankton ecology interannual variability fish landings trophic interactions General Earth and Planetary Sciences Upwelling Marine ecosystem Fisheries management Sardinella education 0105 earth and related environmental sciences |
| Zdroj: | Remote Sensing; Volume 10; Issue 5; Pages: 785 |
| ISSN: | 2072-4292 |
| Popis: | The coastal regions of the Gulf of Guinea constitute one of the major marine ecosystems, producing essential living marine resources for the populations of Western Africa. In this region, the Ivorian continental shelf is under pressure from various anthropogenic sources, which have put the regional fish stocks, especially Sardinella aurita, the dominant pelagic species in Ivorian industrial fishery landings, under threat from overfishing. Here, we combine in situ observations of Sardinella aurita catch, temperature, and nutrient profiles, with remote-sensing ocean-color observations, and reanalysis data of wind and sea surface temperature, to investigate relationships between Sardinella aurita catch and oceanic primary producers (including biomass and phenology of phytoplankton), and between Sardinella aurita catch and environmental conditions (including upwelling index, and turbulent mixing). We show that variations in Sardinella aurita catch in the following year may be predicted, with a confidence of 78%, based on a bilinear model using only physical variables, and with a confidence of 40% when using only biological variables. However, the physics-based model alone is not sufficient to explain the mechanism driving the year-to-year variations in Sardinella aurita catch. Based on the analysis of the relationships between biological variables, we demonstrate that in the Ivorian continental shelf, during the study period 1998–2014, population dynamics of Sardinella aurita, and oceanic primary producers, may be controlled, mainly by top-down trophic interactions. Finally, based on the predictive models constructed here, we discuss how they can provide powerful tools to support evaluation and monitoring of fishing activity, which may help towards the development of a Fisheries Information and Management System. |
| Databáze: | OpenAIRE |
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