Recent trends in plankton and upwelling intensity off Galicia (NW Spain)

The mean intensity of the NE Atlantic upwelling system at its northern limit (Galicia, NW Spain) decreased during the last 40 years. At the same time, warming of surface waters was detected. Plankton biomass and composition are expected to reflect such changes when integrated over large time and space scales. In this study, biomass, abundance and species composition of phyto- and zooplankton were analysed to search for significant patterns of annual change and relations with upwelling intensity. Regionally integrated, mostly offshore, data were obtained from the Continuous Plankton Recorder (since 1958) whereas coastal data from Vigo and A Coruña came from the Radiales program (since 1987). No significant trends were found in phytoplankton biomass at either regional or local scales. However, there was a significant decrease in diatom abundance at regional scales and also of large species at local scales. Zooplankton abundance (mainly copepods) significantly decreased offshore but increased near the coast. Biomass of zooplankton also increased near the coast, with the fastest rates in the south. Warm-water species, like Temora stylifera, were increasingly abundant at both regional and local scales. Significant correlations between upwelling intensity and plankton suggest that climatic effects were delayed for several years. Our results indicate that the effects of large scale climatic trends on plankton communities are being effectively modulated within the pelagic ecosystem in this upwelling region.

Modelling a light-driven phytoplankton succession

We used a numerical model to investigate if and to what extent cellular photoprotective capacity accounts for succession and vertical distribution of marine phytoplankton species/groups. A model describing xanthophyll photoprotective activity in phytoplankton has been implemented in the European Regional Sea Ecosystem Model and applied at the station L4 in the Western English Channel. Primary producers were subdivided into three phytoplankton functional types defined in terms of their capacity to acclimate to different light-specific environments: low light (LL-type), high light (HL-type) and variable light (VL-type) adapted species. The LL-type is assumed to have low cellular level of xanthophyll-cycling pigments (PX) relative to the modelled photosynthetically active pigments (chlorophyll and fucoxanthin (FUCO) = PSP). The HL-type has high PX content relative to PSP while VL-type presents an intermediate PX to PSP ratio. Furthermore, the VL-type is capable of reversibly converting FUCO to PX and synthesizing new PX under high-light stress. In order to reproduce phytoplankton community succession with each of the three groups being dominant in different periods of the year, we had also to assume reduced grazing pressure on HL-adapted species. Model simulations realistically reproduce the observed seasonal patterns of pigments and nutrients highlighting the reasonability of the underpinning assumptions. Our model suggests that pigment-mediated photophysiology plays a primary role in determining the evolution of marine phytoplankton communities in the winter-spring period corresponding to the shoaling of the mixed layer and the increase of light intensity. Grazing selectivity however contributes to the phytoplankton community composition in summer.

Evaluating the SEVIRI Fire Thermal Anomaly Detection Algorithm across the Central African Republic Using the MODIS Active Fire Product

Satellite-based remote sensing of active fires is the only practical way to consistently and continuously monitor diurnal fluctuations in biomass burning from regional, to continental, to global scales. Failure to understand, quantify, and communicate the performance of an active fire detection algorithm, however, can lead to improper interpretations of the spatiotemporal distribution of biomass burning, and flawed estimates of fuel consumption and trace gas and aerosol emissions. This work evaluates the performance of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Fire Thermal Anomaly (FTA) detection algorithm using seven months of active fire pixels detected by the Moderate Resolution Imaging Spectroradiometer (MODIS) across the Central African Republic (CAR). Results indicate that the omission rate of the SEVIRI FTA detection algorithm relative to MODIS varies spatially across the CAR, ranging from 25% in the south to 74% in the east. In the absence of confounding artifacts such as sunglint, uncertainties in the background thermal characterization, and cloud cover, the regional variation in SEVIRI's omission rate can be attributed to a coupling between SEVIRI's low spatial resolution detection bias (i.e., the inability to detect fires below a certain size and intensity) and a strong geographic gradient in active fire characteristics across the CAR. SEVIRI's commission rate relative to MODIS increases from 9% when evaluated near MODIS nadir to 53% near the MODIS scene edges, indicating that SEVIRI errors of commission at the MODIS scene edges may not be false alarms but rather true fires that MODIS failed to detect as a result of larger pixel sizes at extreme MODIS scan angles. Results from this work are expected to facilitate (i) future improvements to the SEVIRI FTA detection algorithm; (ii) the assimilation of the SEVIRI and MODIS active fire products; and (iii) the potential inclusion of SEVIRI into a network of geostationary sensors designed to achieve global diurnal active fire monitoring.