Mining a sea of data: deducing the environmental controls of ocean chlorophyll

Simulation Experiment of Environmental Impact of Deep-Sea Mining: Response of Phytoplankton Community to Polymetallic Nodules and Sediment Enrichment in Surface Water

In this paper, simulation experiments were conducted to study the response of phytoplankton biomass and community composition to the influence of polymetallic nodules and sediment at four stations in the western Pacific in 2021. Chlorophyll a, pico-phytoplankton cell abundance, and metal concentration were measured before and after 24 h of deck incubation. The results show that there were three different patterns of response, namely, restrained, stimulated, and unaffected patterns. The restrained pattern appeared in the filtered treatments at station Incub.01, and the stimulated pattern appeared in the unfiltered treatments at station Incub.02. The response of the phytoplankton was not detectable at stations Incub.03 and 04. Regardless, positive and negative responses were found in the dominant pico-phytoplankton group-Prochlorococcus-and with slight variation in Synechococcus. The concentration of manganese varied among the treatments compared to that of iron and other metals. The factors affecting the growth of the phytoplankton in this study were metal concentrations and turbidity. The phytoplankton biomass baseline may also have played an important role: the lower the biomass, the higher the growth rate. This study proved that deep-sea polymetallic nodule mining will have a specific impact on surface phytoplankton biomass, but turbidity and particle retention time could be important factors in mitigating the extent of the impact.

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.

Evaluation of Machine Learning Predictions of a Highly Resolved Time Series of Chlorophyll-a Concentration

Pelagic chlorophyll-a concentrations are key for evaluation of the environmental status and productivity of marine systems, and data can be provided by in situ measurements, remote sensing and modelling. However, modelling chlorophyll-a is not trivial due to its nonlinear dynamics and complexity. In this study, chlorophyll-a concentrations for the Helgoland Roads time series were modeled using a number of measured water and environmental parameters. We chose three common machine learning algorithms from the literature: the support vector machine regressor, neural networks multi-layer perceptron regressor and random forest regressor. Results showed that the support vector machine regressor slightly outperformed other models. The evaluation with a test dataset and verification with an independent validation dataset for chlorophyll-a concentrations showed a good generalization capacity, evaluated by the root mean squared errors of less than 1 µg L−1. Feature selection and engineering are important and improved the models significantly, as measured in performance, improving the adjusted R2 by a minimum of 48%. We tested SARIMA in comparison and found that the univariate nature of SARIMA does not allow for better results than the machine learning models. Additionally, the computer processing time needed was much higher (prohibitive) for SARIMA.

Phytoplankton nutrient dynamics and flow cytometry based population study of a eutrophic wetland habitat in eastern India, a Ramsar site

Phytoplankton diversity, their abundance based on flow cytometric (FCM) analysis and seasonal nutrient dynamics were investigated from a waste water fed wetland of Eastern India (88° 24.641'E and 22° 33.115'N). The primary objective of the study was to correlate the seasonal fluctuations in phytoplankton abundance to the environmental variables. Total chlorophyll content and FCM based cell counts were used to characterize and quantify the phytoplankton population. Multivariate statistical methods were employed in predicting the possible relationships between biotic and abiotic variables. Distinct seasonal variations characterized by high abundance during the pre-summer period compared to other seasons were detected. The results indicated that environmental factors like water temperature and nutrients, such as various forms of nitrogen and phosphate, influenced the seasonal phytoplankton accumulation. Cluster analysis and non-metric multidimensional scaling helped analyze the seasonal distribution of phytoplankton based on their composition. The dominant genera among the entire phytoplankton community were Scenedesmus spp. of Chlorophyta, followed by Merismopedia spp. of Cyanoprokaryota. Around 3.7 × 105 phytoplankton mL-1 were recorded during the study period. Due to the very high count of individual species in the community, FCM based counting was applied for determination of Species Diversity Index. The entire population was divided into 13 subpopulations based on the cell sorting method and the seasonal abundance in each sub-population was illustrated.

Long-term changes in nutrients, chlorophyll a and their relationships in a semi-enclosed eutrophic ecosystem, Bohai Bay, China

As the representative semi-enclosed bay of China, Bohai Bay has experienced severe eutrophication in recent decades. Monitoring data from 1995 to 2013 were analysed by generalized additive models (GAMs) to explore the temporal variations in nutrients concentrations, nutrient ratios, chlorophyll a (Chl a) concentrations and the responses of Chl a to the changes in nutrients in the spring and summer. The results showed that dissolved inorganic nitrogen (DIN) decreased from 1995 to 2000 but increased after 2000 in both the spring and summer, and soluble reactive phosphorus (SRP) decreased while the molar nitrogen/phosphorus (N/P) ratios (DIN to SRP) increased over the last two decades. Generally, P-limited phytoplankton growth was observed in the spring and summer and DIN was identified as the main pollutant constituent in Bohai Bay. Furthermore, negative correlations were found between DIN and Chl a in summer in Bohai Bay.

Relative contribution of persistent organic pollutants to marine phytoplankton biomass dynamics in the North Sea and the Kattegat

In this paper, we use concentrations of persistent organic pollutants (POPs) and of chlorophyll a to infer POP-induced effects on marine primary production in the Kattegat and the North Sea between the 1990s and the 2000s. To do so, we modelled phytoplankton dynamics using four classical drivers (light and nutrient availability, temperature and zooplankton grazing) and tested whether extending this model with a POP-induced phytoplankton growth limitation term improved model fit to observed chlorophyll a concentrations. Including monitored concentrations of PCBs and pesticides did not lead to a better model fit, suggesting that POP-induced growth limitation of marine phytoplankton in the North Sea and the Kattegat is small compared to the limitations caused by the classical drivers. In an attempt to more fully represent the multitude of POPs in the marine environment, the monitored concentrations were multiplied with a factor 10 and 100. Under these two configurations, region-specific contributions of POPs in the phytoplankton growth limitation were found. The inferred contribution of POPs to phytoplankton growth limitation was ca. 1% in Belgian marine waters, but in the Kattegat POPs explained ca. 10% of the phytoplankton growth limitation. These results suggest that there are regional differences in the contribution of POPs to the phytoplankton growth limitation.

Slow science: the value of long ocean biogeochemistry records

Sustained observations (SOs) have provided invaluable information on the ocean's biology and biogeochemistry for over 50 years. They continue to play a vital role in elucidating the functioning of the marine ecosystem, particularly in the light of ongoing climate change. Repeated, consistent observations have provided the opportunity to resolve temporal and/or spatial variability in ocean biogeochemistry, which has driven exploration of the factors controlling biological parameters and processes. Here, I highlight some of the key breakthroughs in biological oceanography that have been enabled by SOs, which include areas such as trophic dynamics, understanding variability, improved biogeochemical models and the role of ocean biology in the global carbon cycle. In the near future, SOs are poised to make progress on several fronts, including detecting climate change effects on ocean biogeochemistry, high-resolution observations of physical-biological interactions and greater observational capability in both the mesopelagic zone and harsh environments, such as the Arctic. We are now entering a new era for biological SOs, one in which our motivations have evolved from the need to acquire basic understanding of the ocean's state and variability, to a need to understand ocean biogeochemistry in the context of increasing pressure in the form of climate change, overfishing and eutrophication.

In situ measurements of phytoplankton fluorescence using low cost electronics

Chlorophyll a fluorometry has long been used as a method to study phytoplankton in the ocean. In situ fluorometry is used frequently in oceanography to provide depth-resolved estimates of phytoplankton biomass. However, the high price of commercially manufactured in situ fluorometers has made them unavailable to some individuals and institutions. Presented here is an investigation into building an in situ fluorometer using low cost electronics. The goal was to construct an easily reproducible in situ fluorometer from simple and widely available electronic components. The simplicity and modest cost of the sensor makes it valuable to students and professionals alike. Open source sharing of architecture and software will allow students to reconstruct and customize the sensor on a small budget. Research applications that require numerous in situ fluorometers or expendable fluorometers can also benefit from this study. The sensor costs US$150.00 and can be constructed with little to no previous experience. The sensor uses a blue LED to excite chlorophyll a and measures fluorescence using a silicon photodiode. The sensor is controlled by an Arduino microcontroller that also serves as a data logger.