POSTER Session 1

Ocean color remote sensing for Species Distribution Modeling in fisheries management

Species Distribution Modeling (SDM) encompasses various approaches used to predict the probabilistic distribution of a species across a geographic space and time. It can be used to indirectly infer information concerning populations densities and to evaluate the responses to changes in environmental forcings. SDM uses environmental data and various methodologies, such as multivariable regressions or environmental envelopes. Out study is focused on building habitat suitability indices for fisheries management. Several input variables are used, ranging from temperature and salinity to chlorophyll-a and suspended particulate matter concentrations. The main objective of the present work was to assess how the uncertainties associated with the ocean color products propagate through the model towards the final predictive maps. We also draw conclusions regarding the relative importance of each independent variable that contributes to the estimation of habitat suitability. We show that the biogeochemical variables retrieved from ocean color remote sensing have a relatively high influence on the outcomes of the SDM. However, these are species-dependent, so their importance can vary significantly, depending on the targeted fish. In terms of required accuracy level, the individual uncertainties associated with each parameter can accumulate and propagate to the final products, changing drastically the distribution of suitable areas and their dynamics over time.

Sorin Constantin, Terrasigna, Romania, https://orcid.org/0000-0003-2124-4728

Ioan-Daniel Șerban, Terrasigna, Romania

Marius Budileanu, Terrasigna, Romania

Georgiana Anghelin, Terrasigna, Romania

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