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Bajjouk, Touria; Jauzein, Cecile; Drumetz, Lucas; Dalla Mura, Mauro; Duval, Audrey; Dubois, Stanislas. |
Sabellaria alveolata is a sedentary gregarious tube-building species widely distributed from southwest Scotland to Morocco. This species builds what are currently considered the largest European biogenic reefs in the bay of Mont-Saint-Michel (France). As an ecosystem engineer, S. alveolata generates small to large scale topographic complexity, creating numerous spatial and trophic niches for other species to colonize. Sabellaria reefs are also under anthropogenic pressures, leading locally to massive degradation. However, stakeholders lack spatially explicit measures of reef ecological status, at adapted spatial resolution to provide key management information for this protected habitat. Traditional field surveys are extremely time-consuming and rely on... |
Tipo: Text |
Palavras-chave: Benthic habitats; Biogenic reefs; Ecological status; Hyperspectral; Intertidal; Lidar; Mapping. |
Ano: 2020 |
URL: https://archimer.ifremer.fr/doc/00654/76574/77710.pdf |
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Martinez, Elodie; Brini, Anouar; Gorgues, Thomas; Drumetz, Lucas; Roussillon, Joana; Tandeo, Pierre; Maze, Guillaume; Fablet, Ronan. |
Phytoplankton plays a key role in the carbon cycle and supports the oceanic food web. While its seasonal and interannual cycles are rather well characterized owing to the modern satellite ocean color era, its longer time variability remains largely unknown due to the short time-period covered by observations on a global scale. With the aim of reconstructing this longer-term phytoplankton variability, a support vector regression (SVR) approach was recently considered to derive surface Chlorophyll-a concentration (Chl, a proxy of phytoplankton biomass) from physical oceanic model outputs and atmospheric reanalysis. However, those early efforts relied on one particular algorithm, putting aside the question of whether different algorithms may have specific... |
Tipo: Text |
Palavras-chave: Phytoplankton time-series reconstruction; Ocean color; Neural networks; Support vector regression; Multi-layer perceptron; Physical predictors. |
Ano: 2020 |
URL: https://archimer.ifremer.fr/doc/00667/77871/80017.pdf |
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