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Benazzouz, A., Mordane, S., Orbi, A., Chagdali, M., Hilmi, K., Atillah, A., et al. (2014). An improved coastal upwelling index from sea surface temperature using satellite-based approach : the case of the Canary Current upwelling system. Continental Shelf Research, 81, 38–54.
Résumé: A new methodology to derive an SST-based upwelling index was based on a rigorous spatial analysis of satellite SST fields and their variability, by referring to previous works, from Wooster et al. (1976) to Santos et al. (2011). The data was precautiously processed by considering data quality aspects (including cloud cover) and the best way to derive accurate coastal SST and its offshore reference. The relevance of the developed index was evaluated by comparing its spatial and seasonal consistency against two wind-based indices as well as with the previous SST-based indices, largely superseding these later ones in term of overall quality and spatio-temporal dynamic. Our index adequately describes the spatio-temporal variability of the coastal upwelling intensity in the Canary Current upwelling system and has the advantage of describing complementary aspects of the coastal dynamics of the region that were not covered by Ekman-based indices. The proposed methodology is generic and can be easily applicable to various coastal upwelling systems, especially the four major eastern boundary upwelling ecosystems.
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Carlier, A., Chauvaud, L., van der Geest, M., Le Loc’h, F., Le Duff, M., Vernet, M., et al. (2015). Trophic connectivity between offshore upwelling and the inshore food web of Banc d’Arguin (Mauritania): new insights from isotopic analysis. Estuarine, Coastal and Shelf Science, 165, 149–158.
Résumé: Banc d’Arguin (BA), Mauritania, is a nationally protected shallow gulf > 10,000 km2 between the Sahara desert and the upwelling system off the Mauritanian coast. In the southeast, BA consists of a 500 km2 tidal flat, the most important wintering site for shorebirds using the East Atlantic Flyway. The Mauritanian upwelling-driven phytoplankton production supports the most productive fisheries worldwide, but little is known about its trophic role in the functioning of the inshore BA food web. Using stable isotopes as trophic tracers to distinguish between upwelling-driven phytoplankton, open ocean phytoplankton, and benthic primary producers, we assessed the spatial extent to which the inshore BA food web is fuelled by upwelling-driven phytoplankton production. The δ13C and δ15N signals were characterized in dominant primary producers, benthic invertebrate taxa, and various fish species along an offshore–inshore (northwest–southeast) gradient. We also monitored the spatial and temporal extent of upwelling entering BA during 2008 with remote sensing of sea surface temperature and chlorophyll a data. The results suggest that benthic invertebrates and fishes living in the northwestern part of BA depend on the nearby upwelling phytoplankton production, but this food source does not support the intertidal benthic community in southeast BA. Furthermore, the isotopic signatures of fishes suggest weak trophic connectivity between the northern subtidal and southeastern intertidal BA. Our results support the hypothesis that the southeastern tidal flat region functions as a distinct ecosystem with a food web supported mainly by local benthic primary production, which is crucial knowledge for effective management of the pristine BA national park.
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Demarcq, H., Reygondeau, G., Alvain, S., & Vantrepotte, V. (2012). Monitoring marine phytoplankton seasonality from space. Remote Sensing of Environment, 117, 211–222.
Résumé: Remote sensing techniques are used to study the large scale patterns related to the seasonal modes of variability of the marine phytoplankton. Ten years of monthly composite maps of sea surface chlorophyll-a concentration and the PHYSAT database of four Phytoplanktonic Functional Types (PFTs), both from SeaWiFS, are used to investigate characteristics of phytoplankton seasonality in the trades and westerlies wind oceanic biomes, where data density is adequate. We use a combination of wavelet transform and statistical techniques that allow us to quantify both intensity and duration of the seasonal oscillation of chlorophyll-a concentration and PFTs relative occurrence, and to map these relationships. Next, the seasonal oscillations detected are related to four PFTs revealing six major global phytoplanktonic associations. Our results elucidate the intensity and duration of the seasonal dynamic of the chlorophyll-a concentration and of the relative occurrence of four PFTs at a global scale. Thus, the typology of the different types of seasonality is investigated. Finally, an overall agreement between the results and the biogeochemical provinces partition proposed by Longhurst is found, revealing a strong environmental control on the seasonal oscillation of primary producers and a clear latitudinal organization in the succession of the phytoplankton types. Results provided in this study quantify the seasonal oscillation of key structural parameters of the global ocean, and their potential implications for our understanding of ecosystem dynamics.
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DRUON, J. - N., FROMENTIN, J. - M., AULANIER, F., & HEIKKONEN, J. (2011). Potential feeding and spawning habitats of Atlantic bluefin tuna in the Mediterranean Sea. Marine Ecology-progress Series, 439, 223–240.
Résumé: Atlantic bluefin tuna Thunnus thynnus (ABFT) is a fish of high market value which has recently become strongly overexploited, notably in the Mediterranean Sea. This area is an essential habitat for ABFT reproduction and growth. We present here an approach for deriving the daily mapping of potential ABFT feeding and spawning habitats based on satellite-derived sea surface temperature (SST) and chl a concentration. The feeding habitat was mainly derived from the simultaneous occurrence of oceanic fronts of temperature and chl a content while the spawning habitat was mostly inferred from the heating of surface waters. Generally, higher chl a contents were found to be preferred for the feeding habitat and a minimum SST value was found for the spawning habitat. Both habitats were defined by the presence of relevant oceanographic features and are therefore potential and functionally-linked habitats. This approach provides, for the first time, a synoptic view of the potential ABFT habitats in the Mediterranean Sea. The model performs well in areas where both satellite data and ABFT observations are available, as 80% of presence data are in the vicinity of potential habitats. The computed monthly, seasonal and annual maps of potential feeding and spawning habitat of ABFT from 2003 to 2009 are in good agreement with current knowledge on ABFT. Overall, the habitat size of ABFT is about 6% of the Mediterranean Sea surface. The results displayed a strong seasonality in habitat size and locations as well as high year-to-year variations (30 to 60%), particularly for the potential spawning habitat, which is key information for evaluating the utility of ABFT Marine Protected Areas in the Mediterranean Sea.
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Ewald, M., Aerts, R., Lenoir, J., Fassnacht, F. E., Nicolas, M., Skowronek, S., et al. (2018). LiDAR derived forest structure data improves predictions of canopy N and P concentrations from imaging spectroscopy. Remote Sensing of Environment, 211, 13–25.
Résumé: Imaging spectroscopy is a powerful tool for mapping chemical leaf traits at the canopy level. However, covariance with structural canopy properties is hampering the ability to predict leaf biochemical traits in structurally heterogeneous forests. Here, we used imaging spectroscopy data to map canopy level leaf nitrogen (Nmass) and phosphorus concentrations (Pmass) of a temperate mixed forest. By integrating predictor variables derived from airborne laser scanning (LiDAR), capturing the biophysical complexity of the canopy, we aimed at improving predictions of Nmass and Pmass. We used partial least squares regression (PLSR) models to link community weighted means of both leaf constituents with 245 hyperspectral bands (426–2425 nm) and 38 LiDAR-derived variables. LiDAR-derived variables improved the model's explained variances for Nmass (R2cv 0.31 vs. 0.41, % RSMEcv 3.3 vs. 3.0) and Pmass (R2cv 0.45 vs. 0.63, % RSMEcv 15.3 vs. 12.5). The predictive performances of Nmass models using hyperspectral bands only, decreased with increasing structural heterogeneity included in the calibration dataset. To test the independent contribution of canopy structure we additionally fit the models using only LiDAR-derived variables as predictors. Resulting R2cv values ranged from 0.26 for Nmass to 0.54 for Pmass indicating considerable covariation between biochemical traits and forest structural properties. Nmass was negatively related to the spatial heterogeneity of canopy density, whereas Pmass was negatively related to stand height and to the total cover of tree canopies. In the specific setting of this study, the importance of structural variables can be attributed to the presence of two tree species, featuring structural and biochemical properties different from co-occurring species. Still, existing functional linkages between structure and biochemistry at the leaf and canopy level suggest that canopy structure, used as proxy, can in general support the mapping of leaf biochemistry over broad spatial extents.
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