Nutrient consumption by diatoms in the dark subsurface layer of Funka Bay, Hokkaido, Japan

We conducted time-series observations in Funka Bay, Hokkaido, Japan, from 15 February to 14 April 2019. The diatom spring bloom peaked on 4 March and started declining on 15 March. Funka Bay winter water remained below 30-m depth, which was below the surface mixed-layer and dark-zone depths on both dates. At depths of 30–50 m, concentrations of NO3–, PO43–, and Si(OH)4 decreased by half between these dates even in darkness. Incubation experiments using the diatom Thalassiosira nordenskioeldii showed that this diatom could consume nutrients in darkness at substantial rates. We conclude that the nutrient reduction in the subsurface layer (30–50 m) could be explained by dark consumption by diatoms that had been growing in the surface waters and then sank to the subsurface layer. We believe that this is the first study to present observational evidence for the consumption of the main nutrients by diatoms in the dark subsurface layer during the spring bloom. Nutrient consumption in this layer might have a substantial influence on the primary production during and after the spring bloom.

The onset of the spring phytoplankton bloom in the coastal North Sea supports the Disturbance Recovery Hypothesis

The spring phytoplankton bloom is a key event in temperate and polar seas, yet the mechanisms that trigger it remain under debate. Some hypotheses claim that the spring bloom onset occurs when light is no longer limiting, allowing phytoplankton division rates to surpass a critical threshold. In contrast, the Disturbance Recovery Hypothesis (DRH) proposes that the onset responds to an imbalance between phytoplankton growth and loss processes, allowing phytoplankton biomass to start accumulating, and this can occur even when light is still limiting. Although many studies have shown that the DRH explains the spring bloom onset in oceanic waters, it is less certain whether and how it also applies to coastal areas. To address this question at a coastal location in the Scottish North Sea, we combined 21 years (1997–2017) of weekly in situ data with meteorological information. The onset of phytoplankton biomass accumulation occurred around the same date each year, 16 ± 11 days (mean ± SD) after the winter solstice, when light limitation for growth was strongest. Also, negative and positive biomass accumulation rates (r) occurred respectively before and after the winter solstice at similar light levels. The seasonal change from negative to positive r was mainly driven by the rate of change in light availability rather than light itself. Our results support the validity of the DRH for the studied coastal region and suggest its applicability to other coastal areas.

ECOSMO II(CHL): a marine biogeochemical model for the North Atlantic and the Arctic

ECOSMO II is a fully coupled bio-physical model of 3d-hydrodynamics with an intermediate complexity N(utrient) P(hytoplankton) Z(ooplankton) D(etritus) type biology including sediment-water column exchange processes originally formulated for the North Sea and Baltic Sea. Here we present an updated version of the model incorporating chlorophyll a as a prognostic state variable: ECOSMO II(CHL). The version presented here is online coupled to the HYCOM ocean model. The model is intended to be used for regional configurations for the North Atlantic and the Arctic incorporating coarse to high spatial resolutions for hind-casting and operational purposes. We provide the full descriptions of the changes in ECOSMO II(CHL) from ECOSMO II and provide the evaluation for the inorganic nutrients and chlorophyll variables, present the modeled biogeochemistry of the Nordic Seas and the Artic and experiments on various parameterization sets as use cases targeting chlorophyll a dynamics. The model evaluations demonstrated that the simulations are consistent with the large-scale climatological nutrient settings, and are capable of representing regional and seasonal changes. The Norwegian and Barents Seas primary production show distinct seasonal patterns with a pronounced spring bloom dominated by diatoms and low biomass during winter months. The Norwegian Sea annual primary production is around double that of the Barents Sea while also having an earlier spring bloom. The parameterization experiments showed that the representation of open ocean chlorophyll a benefits from using higher phytoplankton growth and zooplankton grazing rates with less photosynthesis efficiency compared to the original implementation of ECOSMO II, which was valid for the North Sea and the Baltic Sea representing coastal domains. Thus, for open ocean modeling studies, we suggest the use of the parameterization sets presented in this study.

Differential response of distinct copepod life history types to spring environmental forcing in Rivers Inlet, British Columbia, Canada

The temporal dynamics of five copepod species common to coastal waters of the Pacific Northwest were examined in relation to variability in spring temperature and phytoplankton dynamics in 2008, 2009, and 2010 in Rivers Inlet, British Columbia, Canada. The five species were differentiated by life history strategies. Acartia longiremis, Metridia pacifica, and Paraeuchaeta elongata remained active over most of the year. By contrast, the reproductive effort of Eucalanus bungii and Calanus marshallae was concentrated over the spring period and they spent most of the year in diapause as C5 copepodites. A delay in the timing of the spring bloom was associated with a shift in the phenology of all species. However, following the delay in spring bloom timing, recruitment to the G1 cohort was reduced only for E. bungii and C. marshallae. Recruitment successes of E. bungii and C. marshallae was also drastically reduced in 2010, an El Niño year, when spring temperatures were highest. Reasons for the observed differential response to spring environmental forcing, and its effect on upper trophic levels, are discussed.

Transition from a Mixotroph/Heterotroph Protist Community During the Dark Winter to a Photoautotrophic Spring Community in Arctic Surface Waters

Unicellular plankton communities (protists) are the basis of the marine food web. The spring bloom is especially important, because of its high biomass. However, it is poorly described how the protist community structure in Arctic surface waters develops from winter to spring. We show that mixotrophy and parasitism are the prominent trophic modes in the dark winter period. The transition period was characterized by a high relative abundance of mixotrophic dinoflagellates, while centric diatoms and the haptophyte Phaeocystis pouchetii dominated the successive phototrophic spring bloom event. Our observations indicate the presence of a characteristic winter community and a community shift from winter to spring, and not just a dormant spring community waiting for better circumstances. The spring bloom initiation commenced while sea ice was still obstructing the light penetration into the water column. The initiation coincided with a change in day length and spectral composition of the light, rather than with an increased light intensity. The initial increase in fluorescence, and therefore photosynthetic activity, was detected relatively deep in the water column, at ~55 m depth. This suggests that water column stratification and a complex interplay of abiotic factors eventually promote the spring bloom initiation.

Analysis of 23 Years of Daily Cloud-Free Chlorophyll and Suspended Particulate Matter in the Greater North Sea

Satellite-derived estimates of ocean color variables are available for several decades now and allow performing studies of the long-term changes occurred in an ecosystem. A daily, gap-free analysis of chlorophyll (CHL) and suspended particulate matter (SPM, indicative of light availability in the subsurface) at 1 km resolution over the Greater North Sea during the period 1998–2020 is presented. Interannual changes are described, with maximum average CHL values increasing during the period 1998–2008, a slightly decreasing trend in 2009–2017 and an stagnation in recent years. The typical spring bloom is observed to happen earlier each year, with about 1 month difference between 1998 and 2020. The duration of the bloom (time between onset and offset) appears also to be increasing with time, but the average CHL value during the spring bloom does not show a clear trend. The causes for earlier spring blooms are still unclear, although a rising water temperature can partially explain them through enhanced phytoplankton cell division rates or through increased water column stratification. SPM values during winter months (prior to the development of the spring bloom) do not exhibit a clear trend over the same period, although slightly higher SPM values are observed in recent years. The influence of sea surface temperature in the spring bloom timing appears to be dominant over the influence of SPM concentration, according to our results. The number of satellites available over the years for producing CHL and SPM in this work has an influence in the total amount of available data before interpolation. The amount of missing data has an influence in the total variability that is retained in the final dataset, and our results suggest that at least three satellites would be needed for a good representation of ocean color variability.

Bioavailability of Various Phosphorus Fractions and Their Seasonality in a Eutrophic Estuary in the Southern Baltic Sea – A Laboratory Approach

Phosphorus (P) is a major driver of eutrophication, especially in anthropogenically impacted coastal waters, and determining its bioavailability is important for providing a good estimation of the eutrophication potential in aquatic systems. Therefore, we observed the bioavailability of P in four laboratory experiments on water samples collected in March, June, September, and December 2018. In the experiments, all P fractions of the sampled water were investigated in three treatments (“unfiltered” and “10 μm”- and “1.2 μm”-filtered). The bioavailability (utilization by organisms within several days) ranged from 9 to 100% for dissolved P, and 34 to 100% for particulate P. However, one of the particulate P fractions was bound in biomass and therefore was not directly bioavailable. The conditions in the March experiment represented a natural spring bloom with a residual potential for planktonic growth. In June and September, the nutrients needed for growth were depleted in the different treatments. In December, a spring bloom was simulated by the laboratory conditions. Preferential P uptake by a specific group of organisms could not be observed directly, although a trend of higher utilization of dissolved P by heterotrophic bacteria was observed. In conclusion, the bioavailable P (sum of dissolved P fractions and one particulate P fraction) accounted for between 20 and 94% of the total P. Consequently, our experiments demonstrated that the commonly monitored P fractions lead to an underestimation of the bioavailable P and thus of potential for eutrophication in aquatic systems, too.

North Sea spring bloom-associated Gammaproteobacteria fill diverse heterotrophic niches

Background The planktonic bacterial community associated with spring phytoplankton blooms in the North Sea is responsible for a large amount of carbon turnover in an environment characterised by high primary productivity. Individual clades belonging to the Gammaproteobacteria have shown similar population dynamics to Bacteroidetes species, and are thus assumed to fill competing ecological niches. Previous studies have generated large numbers of metagenome assembled genomes and metaproteomes from these environments, which can be readily mined to identify populations performing potentially important ecosystem functions. In this study we attempt to catalogue these spring bloom-associated Gammaproteobacteria, which have thus far attracted less attention than sympatric Alphaproteobacteria and Bacteroidetes. Methods We annotated 120 non-redundant species-representative gammaproteobacterial metagenome assembled genomes from spring bloom sampling campaigns covering the four years 2010–2012 and 2016 using a combination of Prokka and PfamScan, with further confirmation via BLAST against NCBI-NR. We also matched these gene annotations to 20 previously published metaproteomes covering those sampling periods plus the spring of 2009. Results Metagenome assembled genomes with clear capacity for polysaccharide degradation via dedicated clusters of carbohydrate active enzymes were among the most abundant during blooms. Many genomes lacked gene clusters with clearly identifiable predicted polysaccharide substrates, although abundantly expressed loci for the uptake of large molecules were identified in metaproteomes. While the larger biopolymers, which are the most abundant sources of reduced carbon following algal blooms, are likely the main energy source, some gammaproteobacterial clades were clearly specialised for smaller organic compounds. Their substrates range from amino acids, monosaccharides, and DMSP, to the less expected, such as terpenoids, and aromatics and biphenyls, as well as many ‘unknowns’. In particular we uncover a much greater breadth of apparent methylotrophic capability than heretofore identified, present in several order level clades without cultivated representatives. Conclusions Large numbers of metagenome assembled genomes are today publicly available, containing a wealth of readily accessible information. Here we identified a variety of predicted metabolisms of interest, which include diverse potential heterotrophic niches of spring bloom-associated Gammaproteobacteria. Features such as those identified here could well be fertile ground for future experimental studies.

Climate Change Induced Trends and Uncertainties in Phytoplankton Spring Bloom Dynamics

Spring phytoplankton blooms in the southern North Sea substantially contribute to annual primary production and largely influence food web dynamics. Studying long-term changes in spring bloom dynamics is therefore crucial for understanding future climate responses and predicting implications on the marine ecosystem. This paper aims to study long term changes in spring bloom dynamics in the Dutch coastal waters, using historical coastal in-situ data and satellite observations as well as projected future solar radiation and air temperature trajectories from regional climate models as driving forces covering the twenty-first century. The main objective is to derive long-term trends and quantify climate induced uncertainties in future coastal phytoplankton phenology. The three main methodological steps to achieve this goal include (1) developing a data fusion model to interlace coastal in-situ measurements and satellite chlorophyll-a observations into a single multi-decadal signal; (2) applying a Bayesian structural time series model to produce long-term projections of chlorophyll-a concentrations over the twenty-first century; and (3) developing a feature extraction method to derive the cardinal dates (beginning, peak, end) of the spring bloom to track the historical and the projected changes in its dynamics. The data fusion model produced an enhanced chlorophyll-a time series with improved accuracy by correcting the satellite observed signal with in-situ observations. The applied structural time series model proved to have sufficient goodness-of-fit to produce long term chlorophyll-a projections, and the feature extraction method was found to be robust in detecting cardinal dates when spring blooms were present. The main research findings indicate that at the study site location the spring bloom characteristics are impacted by the changing climatic conditions. Our results suggest that toward the end of the twenty-first century spring blooms will steadily shift earlier, resulting in longer spring bloom duration. Spring bloom magnitudes are also projected to increase with a 0.4% year−1 trend. Based on the ensemble simulation the largest uncertainty lies in the timing of the spring bloom beginning and -end timing, while the peak timing has less variation. Further studies would be required to link the findings of this paper and ecosystem behavior to better understand possible consequences to the ecosystem.