Environmental Impact on Harmful Species Pseudo-nitzschia spp. and Phaeocystis globosa Phenology and Niche

On the conditions promoting Pseudo-nitzschia spp. blooms in the eastern English Channel and southern North Sea

This study investigated the drivers of the blooms of Pseudo-nitzschia seriata and Pseudo-nitzschia delicatissima complexes in the eastern English Channel and southern North Sea. Phytoplankton data series acquired from 1992 to 2020 were analyzed with a multivariate statistical approach based on Hutchinson's niche concept. P. seriata and P. delicatissima complexes were found to be typically present year round, but they bloomed at different periods because they occupied different realized ecological niches. P. delicatissima complex occupied a more marginal niche and was less tolerant than P. seriata complex. P. delicatissima complex typically bloomed in April-May at the same time as Phaeocystis globosa while P. seriata complex blooms were more frequently observed in June during the decline of low intensity P. globosa blooms. P. delicatissima and P. seriata complexes were both favored by low-silicate environments and relatively low turbulence but they responded differently to water temperature, light, ammonium, phosphate and nitrite + nitrate conditions. Niche shifts and biotic interactions played important roles in the control of the blooms of P. delicatissima and P. seriata complexes. The two complexes occupied different sub-niches during their respective low abundance and bloom periods. The phytoplankton community structure and the number of other taxa presenting a niche overlapping the niches of P. delicatissima and P. seriata complexes also differed between these periods. P. globosa was the taxa contributing the most to the dissimilarity in community structure. P. globosa interacted positively with P. delicatissima complex and negatively with P. seriata complex.

Seasonal change and subniche dynamics of three Alexandrium species in the Korea Strait

Some members of the dinoflagellate genus Alexandrium produce toxins responsible for paralytic shellfish poisoning, which causes environmental impacts and large economic losses worldwide. The Outlying Mean Index (OMI) and the Within Outlying Mean Index (WitOMI) were used to examine the ecological niches of three Alexandrium species identifying factors affecting their population dynamics in the Korea Strait (KS). Species niches were divided into seasonal subniches based on species' temporal and spatial patterns, with A. catenella being highest in the spring, A. pacificum in the summer, and A. affine in the autumn. These shifts in abundance are likely due to changes in their habitat preferences and resource availability, as well as the effects of biological constraints. A subniche-based approach, which considers the interactions between the environment and the biological characteristics of a species, was useful in understanding the factors shaping the population dynamics of the individual species. Additionally, a species distribution model was used to predict the phenology and biogeography of the three Alexandrium species in the KS and their thermal niches on a larger scale. The model predicted that, in the KS, A. catenella exists on the warm side of the thermal niche, while A. pacificum and A. affine exist on the cold side, indicating that these species may respond differently to increases in water temperature. However, the predicted phenology was incongruent with the abundance of the species as measured by droplet digital PCR. Overall, the WitOMI analysis and species distribution model can provide valuable insights into how population dynamics are influenced by the integrated interplay of biotic and abiotic processes.

Variability patterns and phenology of harmful phytoplankton blooms off southern Portugal: Looking for region-specific environmental drivers and predictors

Harmful algal blooms (HABs) negatively impact coastal ecosystems, fisheries, and human health, and their prediction has become imperative for effective coastal management. This study aimed to evaluate spatial-temporal variability patterns and phenology for key toxigenic phytoplankton species off southern Portugal, during a 6-year period, and identify region-specific environmental drivers and predictors. Total abundance of species responsible for amnesic shellfish poisoning (Pseudo-nitzschia spp.), diarrhetic shellfish poisoning (Dinophysis spp.), and paralytic shellfish poisoning (G. catenatum) were retrieved, from the National Bivalve Mollusk Monitoring System public database. Contemporaneous environmental variables were acquired from satellite remote sensing, model-derived data, and in situ observations, and generalized additive models (GAMs) were used to explore the functional relationships between HABs and environmental variables and identify region-specific predictors. Pseudo-nitzschia spp. showed a bimodal annual cycle for most coastal production areas, with spring and summer maxima, reflecting the increase in light intensity during the mixed layer shoaling stage, and the later stimulatory effects of upwelling events, with a higher bloom frequency over coastal areas subjected to stronger upwelling intensity. Dinophysis spp. exhibited a unimodal annual cycle, with spring/summer maxima associated with stratified conditions, that typically promote dinoflagellates. Dinophysis spp. blooms were delayed with respect to Pseudo-nitzschia spp. spring blooms, and followed by Pseudo-nitzschia spp. summer blooms, probably reflecting upwelling-relaxation cycles. G. catenatum occurred occasionally, namely in areas more influenced by river discharges, under weaker upwelling. Statistical-empirical models (GAMs) explained 7-8%, and 21-54% of the variability in Pseudo-nitzschia spp. and Dinophysis spp., respectively. Overall, a set of four easily accessible environmental variables, surface photosynthetically available radiation, mixed layer depth, sea surface temperature, and chlorophyll-a concentration, emerged as the most influential predictors. Additionally, over the coastal production areas along the south coast, river discharges exerted minor negative effects on both HAB groups. Despite evidence supporting the role of upwelling intensity as an environmental driver of Pseudo-nitzschia spp., it was not identified as a relevant model predictor. Future model developments, such as the inclusion of additional environmental variables, and the implementation of species- and period-specific, and hybrid modelling approaches, may further support HAB operational forecasting and managing over complex coastal domains.