Modeling freshwater plankton community dynamics with static and dynamic interactions using graph convolution embedded long short-term memory

Given the frequent association between freshwater plankton and water quality degradation, several predictive models have been devised to understand and estimate their dynamics. However, the significance of biotic and abiotic interactions has been overlooked. In this study, we aimed to address the importance of the interaction term in predicting plankton community dynamics by applying graph convolution embedded long short-term memory networks (GC-LSTM) models, which can incorporate interaction terms as graph signals. Temporal graph series comprising plankton genera or environmental drivers as node features and their relationships for edge features from two distinct water bodies, a reservoir and a river, were utilized to develop these models. To assess the predictability, the performances of the GC-LSTM models on community dynamics were compared those of LSTM and GCN models at various lead times. Moreover, GNNExplainer was used to examine the global and local importance of the nodes and edges for all predictions and specific predictions, respectively. The GC-LSTM models outperformed the LSTM models, consistently showing higher prediction accuracy. Although all the models exhibited performance degradation at longer lead times, the GC-LSTM models consistently demonstrated better performance regarding each graph signal and plankton genus. GNNExplainer yielded interpretable explanations for important genera and interaction pairs among communities, revealing consistent importance patterns across different lead times at both global and local scales. These findings underscore the potential of the proposed modeling approach for forecasting community dynamics and emphasize the critical role of graph signals with interaction terms in plankton communities.

Phytoplankton assemblage responses to nitrogen following COVID-19 stay-in-place orders in western Long Island Sound (New York/Connecticut)

This study evaluated water quality, nitrogen (N), and phytoplankton assemblage linkages along the western Long Island Sound (USA) shoreline (Nov. 2020-Dec. 2021) following COVID-19 stay-in-place (SIP) orders through monthly surveys and N-addition bioassays. Ammonia-N (AmN; NH3+NH4+) negatively correlated with total chlorophyll-a (chl-a) at all sites; this was significant at Alley Creek, adjacent to urban wastewater inputs, and at Calf Pasture, by the Norwalk River (Spearman rank correlation, p < 0.01 and 0.02). Diatoms were abundant throughout the study, though dinoflagellates (Heterocapsa, Prorocentrum), euglenoids/cryptophytes, and both nano- and picoplankton biomass increased during summer. In field and experimental assessments, high nitrite + nitrate (N + N) and low AmN increased diatom abundances while AmN was positively linked to cryptophyte concentrations. Likely N + N decreases with presumably minimal changes in AmN and organic N during COVID-19 SIP resulted in phytoplankton assemblage shifts (decreased diatoms, increased euglenoids/cryptophytes), highlighting the ecological impacts of N-form delivered by wastewater to urban estuaries.

Interspecific competition between the bloom-causing dinoflagellates Hetrocapsa bohaiensis and the local species Chlorella pyrenoidosa

Harmful algal blooms caused by Heterocapsa bohaiensis have broken out in aquaculture areas near Liaodong Bay, China, since 2012, resulting in mass mortality of Eriocheir sinensis larvae and substantial economic loss. Chlorella pyrenoidosa is a local phytoplankton species that is found in aquaculture ponds. However, the reason why H. bohaiensis dominated and proliferated in the phytoplankton community remains unknown. Previous studies have revealed the toxicity and hemolytic activity of H. bohaiensis. It is suspected that the out-competition of H. bohaiensis to C. pyrenoidosa was associated with toxicity. Filtrate and bi-algal cultures were investigated to determine the interspecific competition between H. bohaiensis and C. pyrenoidosa in this study. Filtrate experiments revealed that H. bohaiensis showed no toxin allelopathy in C. pyrenoidosa. However, the C. pyrenoidosa filtrates had significant allelopathic effects on the growth of H. bohaiensis. The bi-algal culture experiments and the simulation showed that the dominant species were dependent on the initial cell density ratios of the species and nutrient ratios. Therefore, H. bohaiensis achieved competitive advantage through exploitation competition but not allelopathy. The results contribute to the reasons for the occurrence of H. bohaiensis blooms in a further study.

Phytoplankton Morpho-Functional Trait Variability along Coastal Environmental Gradients

We utilized the trait-based approach in a novel way to examine how specific phytoplankton traits are related to physical features connected to global change, water quality features connected to catchment change, and nutrient availability connected to nutrient loading. For the analyses, we used summertime monitoring data originating from the coastal northern Baltic Sea and generalized additive mixed modeling (GAMM). Of the physical features connected to global climate change, temperature was the most important affecting several studied traits. Nitrogen-fixing, buoyant, non-motile, and autotrophic phytoplankton, as well as harmful cyanobacteria, benefited from a higher temperature. Salinity and stratification did not have clear effects on the traits. Water transparency, which in the Baltic Sea is connected to catchment change, had a mostly negative relation to the studied traits. Harmfulness was negatively correlated with transparency, while the share of non-harmful and large-sized phytoplankton was positively related to it. We used nutrient loading source type and total phosphorus (TP) as proxies for nutrient availability connected to anthropogenic eutrophication. The nutrient loading source type did not relate to any of the traits. Our result showing that N-fixing was not related to TP is discussed. The regionality analysis demonstrated that traits should be calculated in both absolute terms (biomass) and proportions (share of total biomass) to get a better view of community changes and to potentially supplement the environmental status assessments.

Responses of phytoplankton community structure and association to variability in environmental drivers in a tropical coastal lagoon

Spatial and seasonal heterogeneity in phytoplankton communities are governed by many biotic and abiotic drivers. However, the identification of long-term spatial and temporal trends in abiotic drivers, and their interdependencies with the phytoplankton communities' structure is understudied in tropical brackish coastal lagoons. We examined phytoplankton communities' spatiotemporal dynamics from a 5-year dataset (n = 780) collected from 13 sampling stations in Chilika Lagoon, India, where the salinity gradient defined the spatial patterns in environmental variables. Generalized additive models showed a declining trend in phytoplankton biomass, pH, and dissolved PO₄ in the lagoon. Hierarchical modelling of species communities revealed that salinity (44.48 ± 28.19%), water temperature (4.37 ± 5.65%), and season (4.27 ± 0.96%) accounted for maximum variation in the phytoplankton composition. Bacillariophyta (Indicator Value (IV): 0.74) and Dinophyta (IV: 0.72) emerged as top indicators for polyhaline regime whereas, Cyanophyta (IV: 0.81), Euglenophyta (IV: 0.79), and Chlorophyta (IV: 0.75) were strong indicators for oligohaline regime. The responses of Dinophyta and Chrysophyta to environmental drivers were much more complex as random effects accounted for ~70-75% variation in their abundances. Prorocentrum minimum (IV: 0.52), Gonyaulax sp. (IV: 0.52), and Alexandrium sp. (IV: 0.51) were potential indicators of P-limitation. Diploneis weissflogii (IV: 0.43), a marine diatom, emerged as a potential indicator of N-limitation. Hierarchical modelling revealed the positive association between Cyanophyta, Chlorophyta, and Euglenophyta whereas, Dinophyta and Chrysophyta showed a negative association with Cyanophyta, Chlorophyta, and Euglenophyta. Landsat 8-Operational Land Imager satellite models predicted the highest and lowest Cyanophyta abundances in northern and southern sectors, respectively, which were in accordance with the near-coincident field-based measurements from the lagoon. This study highlighted the dynamics of phytoplankton communities and their relationships with environmental drivers by separating the signals of habitat filtering and biotic interactions in a monsoon-regulated tropical coastal lagoon.

Identifying biotic drivers of population dynamics in a benthic-pelagic community

Benthic species and communities are linked to pelagic zooplankton through life-stages encompassing both benthic and pelagic habitats and through a mutual dependency on primary producers as a food source. Many zooplankton taxa contribute to the sedimentary system as benthic eggs. Our main aim was to investigate the nature of the population level biotic interactions between and within these two seemingly independent communities, both dependent on the pelagic primary production, while simultaneously accounting for environmental drivers (salinity, temperature, and oxygen conditions). To this end, we applied multivariate autoregressive state-space models to long (1966-2007) time series of annual abundance data, comparing models with and without interspecific interactions, and models with and without environmental variables included. We were not able to detect any direct coupling between sediment-dwelling benthic taxa and pelagic copepods and cladocerans on the annual scale, but the most parsimonious model indicated that interactions within the benthic community are important. There were also positive residual correlations between the copepods and cladocerans potentially reflecting the availability of a shared resource or similar seasonal dependence, whereas both groups tended to correlate negatively with the zoobenthic taxa. The most notable single interaction within the benthic community was a tendency for a negative effect of Limecola balthica on the amphipods Monoporeia affinis and Pontoporeia femorata which can help explain the observed decrease in amphipods due to increased competitive interference.

Drivers shaping episodic and gradual changes in phytoplankton community succession: Taxonomic versus functional groups

Describing temporal changes in phytoplankton communities is complicated owing to (i) multivariate environmental drivers, (ii) inter-specific relationships, and (iii) various species. With long-term research data from the lower Nakdong River from 1993 to 2016, we examined the temporal changes at two scales-episodic (from weekly to monthly) and long-term (yearly)-and screened the potential environmental drivers. Phytoplankton community component patterns were modeled with the drivers as covariates, using multivariate autoregressive state-space (MARSS) models, to assess their response to environmental drivers and biotic interactions. We assumed that compared to taxonomic classification, functional classification would obtain a better identification of community response to temporal variability. Over 24 years, the succession patterns of the dominant taxonomic and functional groups decreased in diversity, with the greatest decreases in biomass of Bacillariophyceae and group D (mainly the diatom Stephanodiscus hantzschii), and coincided with the introduction of group H1 (dinitrogen-fixing nostocaleans). The potential drivers for these changes were precipitation, water level, and total nitrogen (TN) for taxonomic groups and TN, total phosphorus, and euphotic zone depth for functional groups. The results of the MARSS model and temporal trends for each driver indicated that the increases in the water level and light availability were mostly related with the taxonomic and functional groups, respectively. The model for functional groups proposed a total of 24 significant inter-group relationships, where five relationships supported the succession patterns of dominant groups in the Nakdong River. Combined with the effects of increased light availability, a positive relationship between groups H1 and M (mainly Cyanobacteria and Microcystis aeruginosa) appears to induce cyanobacterial bloom development over a long period. These results can be fundamental information for river system management concerning the resulting cascading effects of changes in environmental drivers and inter-group relationships on the phytoplankton community composition.

Shifts in Diatom Dominance Associated with Seasonal Changes in an Estuarine-Mangrove Phytoplankton Community

A study on seasonal phytoplankton abundance and composition in a mangrove estuary, Matang Mangrove Forest Reserve (MMFR), Malaysia, was carried out to determine the phytoplankton structure in this ecosystem, and to identify potential indicators of environmental changes. Phytoplankton samples were collected bimonthly from June 2010 to April 2011, to cover both dry (June to October) and wet (November to April) seasons, at four selected sampling sites along the river. Diatoms showed the highest number of species (50 species) from a total of 85 phytoplankton species from 76 genera. Diatoms contributed more than 90% of the total phytoplankton abundance during the dry season (southwest monsoon) and less than 70% during the wet season (northeast monsoon) as dinoflagellates became more abundant during the rainy season. Two diatoms were recorded as dominant species throughout the sampling period; Cyclotella sp. and Skeletonema costatum. Cyclotella sp. formed the most abundant species (62% of total phytoplankton) during the dry period characterized by low nutrients and relatively low turbidity. Skeletonema costatum contributed 93% of the total phytoplankton in October, which marked the end of the dry season and the beginning of the wet season, characterized by strong winds and high waves leading to the upwelling of the water column. Massive blooms of Skeletonema costatum occurred during the upwelling when total nitrogen (TN) and total phosphorus (TP) concentrations were highest (p < 0.05) throughout the year. The abundance of diatom species during the wet season was more evenly distributed, with most diatom species contributing less than 12% of the total phytoplankton. Autotrophic producers such as diatoms were limited by high turbidity during the northeast monsoon when the rainfall was high. During the wet season, Cyclotella and Skeletonema costatum only contributed 9% and 5% of the total phytoplankton, respectively, as dinoflagellates had more competitive advantage in turbid waters. This study illustrates that some diatom species such as Cyclotella sp. and Skeletonema costatum could be used as indicators of the environmental changes in marine waters.

Environmental variables driving species and genus level changes in annual plankton biomass

Abiotic variables subject to global change are known to affect plankton biomasses, and these effects can be species-specific. Here, we investigate the environmental drivers of annual biomass using plankton data from the Gulf of Finland in the northern Baltic Sea, spanning years 1993-2016. We estimated annual biomass time-series of 31 nanoplankton and microplankton species and genera from day-level data, accounting for the average phenology and wind. We found wind effects on day-level biomass in 16 taxa. We subsequently used state-space models to connect the annual biomass changes with potential environmental drivers (temperature, salinity, stratification, ice cover and inorganic nutrients), simultaneously accounting for temporal trends. We found clear environmental effects influencing the annual biomasses of Dinobryon faculiferum, Eutreptiella spp., Protoperidinium bipes, Pseudopedinella spp., Snowella spp. and Thalassiosira baltica and indicative effects in 10 additional taxa. These effects mostly concerned temperature, salinity or stratification. Together, these 16 taxa represent two-thirds of the summer biomass in the sampled community. The inter-annual variability observed in salinity and temperature is relatively low compared to scenarios of predicted change in these variables. Therefore, the potential impacts of the presented effects on plankton biomasses are considerable.