Relating sardine recruitment in the Northern Benguela to satellite-derived sea surface height using a neural network pattern recognition approach

Processes of enrichment, concentration and retention are thought to be important for the successful recruitment of small pelagic fish in upwelling areas, but are difficult to measure. In this study, a novel approach is used to examine the role of spatio-temporal oceanographic variability on recruitment success of the Northern Benguela sardine Sardinops sagax. This approach applies a neural network pattern recognition technique, called a self-organising map (SOM), to a seven-year time series of satellite-derived sea level data. The Northern Benguela is characterised by quasi-perennial upwelling of cold, nutrient-rich water and is influenced by intrusions of warm, nutrient-poor Angola Current water from the north. In this paper, these processes are categorised in terms of their influence on recruitment success through the key ocean triad mechanisms of enrichment, concentration and retention. Moderate upwelling is seen as favourable for recruitment, whereas strong upwelling, weak upwelling and Angola Current intrusion appear detrimental to recruitment success. The SOM was used to identify characteristic patterns from sea level difference data and these were interpreted with the aid of sea surface temperature data. We found that the major oceanographic processes of upwelling and Angola Current intrusion dominated these patterns, allowing them to be partitioned into those representing recruitment favourable conditions and those representing adverse conditions for recruitment. A marginally significant relationship was found between the index of sardine recruitment and the frequency of recruitment favourable conditions (r super(2) = 0.61, p = 0.068, n = 6). Because larvae are vulnerable to environmental influences for a period of at least 50 days after spawning, the SOM was then used to identify windows of persistent favourable conditions lasting longer than 50 days, termed recruitment favourable periods (RFPs). The occurrence of RFPs was compared with back-calculated spawning dates for each cohort. Finally, a comparison of RFPs with the time of spawning and the index of recruitment showed that in years where there were 50 or more days of favourable conditions following spawning, good recruitment followed (Mann-Whitney U-test: p = 0.064, n = 6). These results show the value of the SOM technique for describing spatio-temporal variability in oceanographic processes. Variability in these processes appears to be an important factor influencing recruitment in the Northern Benguela sardine, although the available data time series is currently too short to be conclusive. Nonetheless, the analysis of satellite data, using a neural network pattern-recognition approach, provides a useful framework for investigating fisheries recruitment problems.

Nitrogen uptake of phytoplankton assemblages under contrasting upwelling and downwelling conditions: The Ría de Vigo, NW Iberia

Regenerated production (including organic nitrogen) is shown here to be important in the Ria de Vigo (Galicia, NW Iberia) in supporting both harmful algal bloom communities during the downwelling season, but also (to a lesser extent) diatom communities during stratified periods of weak to moderate upwelling. The Galician Rias, situated in the Iberian upwelling system, are regularly affected by blooms of toxic dinoflagellates, which pose serious threats to the local mussel farming industry. These tend to occur towards the end of summer, during the transition from upwelling to downwelling favourable seasons, when cold bottom shelf waters in the rias are replaced by warm surface shelf waters. Nitrate, ammonium and urea uptake rates were measured in the Ria de Vigo during a downwelling event in September 2006 and during an upwelling event in June 2007. In September the ria was well mixed, with a downwelling front observed towards the middle of the ria and relatively high nutrient concentrations (1.0-2.6 mu mol L-1 nitrate; 1.0-5.6 mu mol L-1 ammonium; 0.1-0.8 mu mol L-1 phosphate; 2.0-9.0 mu mol L-1 silicic acid) were present throughout the water column. Ammonium represented more than 80% of the nitrogenous nutrients, and the phytoplankton assemblage was dominated by dinoflagellates and small flagellates. In June the water column was stratified, with nutrient-rich, upwelled water below the thermocline and warm, nutrient-depleted water in the surface. At this time, nitrate represented more than 80% of the nitrogenous nutrients, and a mixed diatom assemblage was present. Primary phytoplankton production during both events was mainly sustained by regenerated nitrogen, with ammonium uptake rates of 0.035-0.063 mu mol N L-1 h(-1) in September and 0.078-0.188 mu mol N L-1 h(-1) in June. Although f-ratios were generally low (<0.2) in both June and September, a maximum of 0.61 was reached in June due to higher nitrate uptake (0.225 mu mol N L-1 h(-1)). Total nitrogen uptake was also higher during the upwelling event (0.153-0.366 in June and 0.053-0.096 mu mol N L-1 h(-1) in September). Nitrogen uptake kinetics demonstrated a strong preference for ammonium and urea over nitrate in June.

Isolation of microplastics in biota-rich seawater samples and marine organisms

Microplastic litter is a pervasive pollutant present in aquatic systems across the globe. A range of marine organisms have the capacity to ingest microplastics, resulting in adverse health effects. Developing methods to accurately quantify microplastics in productive marine waters, and those internalized by marine organisms, is of growing importance. Here we investigate the efficacy of using acid, alkaline and enzymatic digestion techniques in mineralizing biological material from marine surface trawls to reveal any microplastics present. Our optimized enzymatic protocol can digest >97% (by weight) of the material present in plankton-rich seawater samples without destroying any microplastic debris present. In applying the method to replicate marine samples from the western English Channel, we identified 0.27 microplastics m−3. The protocol was further used to extract microplastics ingested by marine zooplankton under laboratory conditions. Our findings illustrate that enzymatic digestion can aid the detection of microplastic debris within seawater samples and marine biota.

Modelling the Stoichiometric Regulation of C-Rich Toxins in Marine Dinoflagellates

Toxin production in marine microalgae was previously shown to be tightly coupled with cellular stoichiometry. The highest values of cellular toxin are in fact mainly associated with a high carbon to nutrient cellular ratio. In particular, the cellular accumulation of C-rich toxins (i.e., with C:N > 6.6) can be stimulated by both N and P deficiency. Dinoflagellates are the main producers of C-rich toxins and may represent a serious threat for human health and the marine ecosystem. As such, the development of a numerical model able to predict how toxin production is stimulated by nutrient supply/deficiency is of primary utility for both scientific and management purposes. In this work we have developed a mechanistic model describing the stoichiometric regulation of C-rich toxins in marine dinoflagellates. To this purpose, a new formulation describing toxin production and fate was embedded in the European Regional Seas Ecosystem Model (ERSEM), here simplified to describe a monospecific batch culture. Toxin production was assumed to be composed by two distinct additive terms; the first is a constant fraction of algal production and is assumed to take place at any physiological conditions. The second term is assumed to be dependent on algal biomass and to be stimulated by internal nutrient deficiency. By using these assumptions, the model reproduced the concentrations and temporal evolution of toxins observed in cultures of Ostreopsis cf. ovata, a benthic/epiphytic dinoflagellate producing C-rich toxins named ovatoxins. The analysis of simulations and their comparison with experimental data provided a conceptual model linking toxin production and nutritional status in this species. The model was also qualitatively validated by using independent literature data, and the results indicate that our formulation can be also used to simulate toxin dynamics in other dinoflagellates. Our model represents an important step towards the simulation and prediction of marine algal toxicity.