Benthic food web structures as an explanation for prolonged ecological half-life of 137Cs in flatfish species in the Fukushima coastal area.

After the accident at the Fukushima Daiichi Nuclear Power Plant (FDNPP), Japan, in March 2011, 137Cs in demersal fish had, between 2011 and 2015, a prolonged ecological half-life when compared to pelagic fish. Using stable isotope mixing models combined with gut content analysis and 137Cs activity concentrations, this study investigated the hypothesis that an unexplored food web structure could be a contributing factor explaining the ecological half-life of 137Cs in benthic flatfish. Benthic invertebrates and demersal fish species sampled in 2015 still showed 137Cs activity concentrations higher than pre-accident. The mixing models of stable N and C isotopes and gut content analysis identified deposit, suspension and filter feeders to be the main flatfish food items in the benthos. There was a significant correlation between 137Cs activity concentrations in specific flatfish species and benthos, and between 137Cs activity concentrations in benthos and surface sediment. The results of this study partially explained the 137Cs activity concentrations found in the analysed demersal fish, suggesting that the benthos can be a continuous source of 137Cs for the demersal fish during this period of time. Extending monitoring programmes to include invertebrates that are not food species for humans would greatly improve our ability to understand the role of trophic transfer pathways and take appropriate management actions.

Variability in spring phytoplankton blooms associated with ice retreat timing in the Pacific Arctic from 2003-2019.

The Arctic is experiencing rapid changes in sea-ice seasonality and extent, with significant consequences for primary production. With the importance of accurate monitoring of spring phytoplankton dynamics in a changing Arctic, this study further examines the previously established critical relationship between spring phytoplankton bloom types and timing of the sea-ice retreat for broader temporal and spatial coverages, with a particular focus on the Pacific Arctic for 2003-2019. To this end, time-series of satellite-retrieved phytoplankton biomass were modeled using a parametric Gaussian function, as an effective approach to capture the development and decay of phytoplankton blooms. Our sensitivity analysis demonstrated accurate estimates of timing and presence/absence of peaks in phytoplankton biomass even with some missing values, suggesting the parametric Gaussian function is a powerful tool for capturing the development and decay of phytoplankton blooms. Based on the timing and presence/absence of a peak in phytoplankton biomass and following the classification developed by the previous exploratory work, spring bloom types are classified into three groups (under-ice blooms, probable under-ice blooms, and marginal ice zone blooms). Our results showed that the proportion of under-ice blooms was higher in the Chukchi Sea than in the Bering Sea. The probable under-ice blooms registered as the dominant bloom types in a wide area of the Pacific Arctic, whereas the marginal ice zone bloom was a relatively minor bloom type across the Pacific Arctic. Associated with a shift of sea-ice retreat timing toward earlier dates, we confirmed previous findings from the Chukchi Sea of recent shifts in phytoplankton bloom types from under-ice blooms to marginal ice zone blooms and demonstrated that this pattern holds for the broader Pacific Arctic sector for the time period 2003-2019. Overall, the present study provided additional evidence of the changing sea-ice retreat timing that can drive variations in phytoplankton bloom dynamics, which contributes to addressing the detection and consistent monitoring of the biophysical responses to the changing environments in the Pacific Arctic.

Marine biodiversity refugia in a climate-sensitive subarctic shelf.

The subarctic shelf of the Eastern Bering Sea (EBS) is one of the world's most productive marine environments, exposed to drastic climate changes characterized by extreme fluctuations in temperature, sea ice concentration, timing, and duration. These climatic changes elicit profound responses in species distribution, abundance, and community composition. Here, we examined the patterns of alpha and temporal beta diversity of 159 marine taxa (66 vertebrates and 93 invertebrate species) from 29 years (1990-2018) of species observations from the NOAA bottom trawl surveys in the EBS. Based on these data, we identified geographically distinct refugial zones in the northern and southern regions of the middle shelf, defined by high species richness and similarity in community species composition over time. These refugial zones harbor higher frequencies of occurrence for representative taxa relative to the regions outside of refugia. We also explored the primary environmental factors structuring marine biodiversity distributions, which underpinned the importance of the winter sea ice concentration to alpha and temporal beta diversity. The spatial biodiversity distributions between high and low winter sea ice regimes highlighted contrasting signals. In particular, the latter showed elevated species richness compared to the former. Further, the temporal beta diversity between the high and low winter sea ice periods underpinned an overall increase in the compositional similarity of marine communities in the EBS. Despite these spatiotemporal differences in biodiversity distributions, the identified refugia represent safe havens of marine biodiversity in the EBS. Distinguishing these areas can help facilitate conservation and management efforts under accelerated and ongoing climatic changes.

Multiple facets of marine biodiversity in the Pacific Arctic under future climate.

Climate change is triggering a global reorganization of marine life. Biogeographical transition zones, diversity-rich regions straddling biogeographical units where many species live at, or close to, their physiological tolerance limits (i.e., range distribution edges), are redistribution hotspots that offer a unique opportunity to understand the mechanisms and consequences of climate-driven thermophilization processes in natural communities. In this context, we examined the impacts of climate change projections in the 21st century (2026-2100) on marine biodiversity in the Eastern Bering and Chukchi seas within the Pacific Arctic, a climatically exposed and sensitive boreal-to-Arctic transition zone. Overall, projected changes in species distributions, modeled using species distribution models, resulted in poleward increases in species richness and functional redundancy, along with pronounced reductions in phylogenetic distances by century's end (2076-2100). Future poleward shifts of boreal species in response to warming and sea ice changes are projected to alter the taxonomic and functional biogeography of contemporary Arctic communities as larger, longer-lived and more predatory taxa expand their leading distributional margins. Drawing from the existing evidence from other Arctic regions, these changes are anticipated to increase the susceptibility and vulnerability of the Arctic ecosystems, as trophic connectance between biological components increases, thus decreasing the modularity of Arctic food webs. Our results demonstrate how integrating multiple diversity facets can provide key insights into the relationships between climate change, species composition and ecosystem functioning across marine biogeographic regions.

Evidence of increased toxic Alexandrium tamarense dinoflagellate blooms in the eastern Bering Sea in the summers of 2004 and 2005.

The eastern Bering Sea has a vast continental shelf, which contains various endangered marine mammals and large fishery resources. Recently, high numbers of toxic A. tamarense resting cysts were found in the bottom sediment surface of the eastern Bering Sea shelf, suggesting that the blooms have recently occurred. However, little is known about the presence of A. tamarense vegetative cells in the eastern Bering Sea. This study's goals were to detect the occurrence of A. tamarense vegetative cells on the eastern Bering Sea shelf and to find a relationship between environmental factors and their presence. Inter-annual field surveys were conducted to detect A. tamarense cells and environmental factors, such as nutrients, salinity, chlorophyll a, and water temperature, along a transect line on the eastern Bering Sea shelf during the summers of 2004, 2005, 2006, 2009, 2012, and 2013. A. tamarense vegetative cells were detected during every sampling year, and their quantities varied greatly from year to year. The maximum cell densities of A. tamarense observed during the summers of 2004 and 2005 were much higher than the Paralytic shellfish poisoning warning levels, which are greater than 100-1,000 cells L-1, in other subarctic areas. Lower quantities of the species occurred during the summers of 2009, 2012, and 2013. A significant positive correlation between A. tamarense quantity and water temperature and significant negative correlations between A. tamarense quantity and nutrient concentrations (of phosphate, silicate, and nitrite and nitrate) were detected in every sampling period. The surface- and bottom-water temperatures varied significantly from year to year, suggesting that water temperatures, which have been known to affect the cell growth and cyst germination of A. tamarense, might have affected the cells' quantities in the eastern Bering Sea each summer. Thus, an increase in the Bering Sea shelf's water temperature during the summer will increase the frequency and scale of toxic blooms and the toxin contamination of plankton feeders. This poses serious threats to humans and the marine ecosystem.

The conservative behavior of dissolved organic carbon in surface waters of the southern Chukchi Sea, Arctic Ocean, during early summer.

The spatial distribution of dissolved organic carbon (DOC) concentrations and the optical properties of dissolved organic matter (DOM) determined by ultraviolet-visible absorbance and fluorescence spectroscopy were measured in surface waters of the southern Chukchi Sea, western Arctic Ocean, during the early summer of 2013. Neither the DOC concentration nor the optical parameters of the DOM correlated with salinity. Principal component analysis using the DOM optical parameters clearly separated the DOM sources. A significant linear relationship was evident between the DOC and the principal component score for specific water masses, indicating that a high DOC level was related to a terrigenous source, whereas a low DOC level was related to a marine source. Relationships between the DOC and the principal component scores of the surface waters of the southern Chukchi Sea implied that the major factor controlling the distribution of DOC concentrations was the mixing of plural water masses rather than local production and degradation.

Remote estimation of phytoplankton size fractions using the spectral shape of light absorption.

Phytoplankton size structure plays an important role in ocean biogeochemical processes. The light absorption spectra of phytoplankton provide a great potential for retrieving phytoplankton size structure because of the strong dependence on the packaging effect caused by phytoplankton cell size and on different pigment compositions related to phytoplankton taxonomy. In this study, we investigated the variability in light absorption spectra of phytoplankton in relation to the size structure. Based on this, a new approach was proposed for estimating phytoplankton size fractions. Our approach use the spectral shape of the normalized phytoplankton absorption coefficient (a(ph)(λ)) through principal component analysis (PCA). Values of a(ph)(λ) were normalized to remove biomass effects, and PCA was conducted to separate the spectral variance of normalized a(ph)(λ) into uncorrelated principal components (PCs). Spectral variations captured by the first four PC modes were used to build relationships with phytoplankton size fractions. The results showed that PCA had powerful ability to capture spectral variations in normalized a(ph)(λ), which were significantly related to phytoplankton size fractions. For both hyperspectral a(ph)(λ) and multiband a(ph)(λ), our approach is applicable. We evaluated our approach using wide in situ data collected from coastal waters and the global ocean, and the results demonstrated a good and robust performance in estimating phytoplankton size fractions in various regions. The model performance was further evaluated by a(ph)(λ) derived from in situ remote sensing reflectance (R(rs)(λ)) with a quasi-analytical algorithm. Using R(rs)(λ) only at six bands, accurate estimations of phytoplankton size fractions were obtained, with R(2) values of 0.85, 0.61, and 0.76, and root mean-square errors of 0.130, 0.126, and 0.112 for micro-, nano-, and picophytoplankton, respectively. Our approach provides practical basis for remote estimation of phytoplankton size structure using a(ph)(λ) derived from satellite observations or rapid field instrument measurements in the future.

An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models.

We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters.