Proxy For Biomass Research Articles

Marine protected areas provide unfished reference information to empirically assess fishery status

Fisheries stock assessments typically determine stock-status using estimates of unfished biomass generated from fisheries dependent data. Due to limitations and biases in these data, modelled unfished estimates are reliant on assumptions regarding stock ecology. This can lead to a high degree of uncertainty in estimates of unfished biomass and can compromise sustainable management. We propose using the biomass of exploited species in no-take marine protected areas (marine reserves) as a proxy for unfished biomass to empirically assess stock status. Marine reserves provide contemporary examples of exploited populations in the absence of fishing under current conditions. Using lobster (Jasus edwardsii) potting and diver-based survey data from 2018 and 2019 we calculated fisheries relevant metrics from inside and outside two north-eastern New Zealand marine reserves. Based on marine reserve reference points, we found spawning stock catch rates and biomass of lobster in adjacent fished areas were 3 % and 2 % of unfished levels. Comparability of potting and dive survey estimates validates using dive survey data to estimate stock status, while differences in population information between survey methods highlights the limited ability of catch data to accurately inform on sub-legal abundances. Overall, our fisheries-independent approach suggests the fished population is at lower levels than latest estimates for the wider fishery and demonstrates how marine reserves can provide information on key parameters which can be incorporated into traditional stock assessments. Planning for future marine reserves should consider the value of such areas as tools to help manage fisheries in addition to protecting exploited species.

Assessing the effectiveness of management measures in the Ria Formosa coastal lagoon, Portugal

The Ria Formosa is an important transitional and coastal lagoon on the south coast of Portugal that provides valuable ecosystem services. The lagoon is a protected area under national and international conventions. There is a great potential for Blue Growth sectors, such as aquaculture and coastal tourism, but these rely on good water quality. European environmental legislation, such as the Water Framework Directive, requires member states, such as Portugal to implement management measures if a surface water body is not of good ecological status. This work addresses the effectiveness of management measures, such as wastewater treatment plant implementation and dredging, on the water quality of the Ria Formosa coastal lagoon system. This is an important social-ecological issue, since management measures can be very expensive. The ecological status of Ria Formosa was evaluated, according to the physico-chemical and biological quality elements of the Water Framework Directive. The main indicators were the physico-chemical quality elements of nutrient and oxygen condition, and the biological quality element chlorophyll a, as a proxy for phytoplankton biomass, under the Water Framework Directive. The data for these quality elements from the Ria Formosa were analyzed for consistency with the classification for the Water Framework Directive water bodies. The data after the implementation of management measures was compared with historical data to evaluate if these measures had been effective. The relation between nutrient pressures, meteorological and hydrological conditions was addressed, especially rainfall and runoff. Results showed a decrease in nutrient concentration after the management interventions, despite the increase of population and intensifying agriculture in the catchment. The Ecological Status is spatially variable with an overall moderate status, indicating the need for further management measures. There is a significant reduction in nutrient pressure on the lagoon during drought years. This indicates that climate change may alter the structure and function of the lagoon in the future.

The Importance of Spatial and Temporal Scales in Understanding Chlorophyll Variability in the Southern Ocean

Polar regions are undergoing dramatic, rapid, and possibly irreversible changes. Substantial shifts in patterns of sea ice extent and thickness have cascading effects on polar ecosystems (including phytoplankton), with implications for carbon cycling and global climate. Phytoplankton growth is closely tied to environmental variables such as light and nutrient availability, which are sensitive to climate-induced changes in upper ocean circulation, stratification, and sea ice cover. Recently, Prend et al. (2022, https://doi.org/10.1029/2022GB007329) investigated temporal and spatial scales of chlorophyll (a proxy for phytoplankton biomass) variability in the Southern Ocean. They demonstrated that the dominant temporal scale of variability is sub-seasonal (∼0.5–3 months). The implications of this are two-fold: first, climate oscillations (such as the Southern Annular Mode) are not major drivers of year-to-year variation in chlorophyll; second, intermittent bursts of chlorophyll, generated by small-scale processes such as storms and eddies, dictate the annual mean chlorophyll concentration. Additionally, spatial autocorrelation for chlorophyll concentration varied by time scale: seasonal chlorophyll variability was correlated over much larger areas than were variations in year-to-year chlorophyll concentration. Based on Prend et al. (2022, https://doi.org/10.1029/2022GB007329), future work should be cognizant of (a) the spatio-temporal scales over which chlorophyll is averaged and (b) the need to focus on small-scale, sub-seasonal events (rather than large-scale climate oscillations) to mechanistically explain chlorophyll variability.

Comparative assessment of satellite- and drone-based vegetation indices to predict arthropod biomass in shrub-steppes.

Arthropod biomass is a key element in ecosystem functionality and a basic food item for many species. It must be estimated through traditional costly field sampling, normally at just a few sampling points. Arthropod biomass and plant productivity should be narrowly related because a large majority of arthropods are herbivorous, and others depend on these. Quantifying plant productivity with satellite or aerial vehicle imagery is an easy and fast procedure already tested and implemented in agriculture and field ecology. However, the capability of satellite or aerial vehicle imagery for quantifying arthropod biomass and its relationship with plant productivity has been scarcely addressed. Here, we used unmanned aerial vehicle (UAV) and satellite Sentinel-2 (S2) imagery to establish a relationship between plant productivity and arthropod biomass estimated through ground-truth field sampling in shrub steppes. We UAV-sampled seven plots of 47.6-72.3ha at a 4-cm pixel resolution, subsequently downscaling spatial resolution to 50 cm resolution. In parallel, we used S2 imagery from the same and other dates and locations at 10-m spatial resolution. We related several vegetation indices (VIs) with arthropod biomass (epigeous, coprophagous, and four functional consumer groups: predatory, detritivore, phytophagous, and diverse) estimated at 41-48 sampling stations for UAV flying plots and in 67-79 sampling stations for S2. VIs derived from UAV were consistently and positively related to all arthropod biomass groups. Three out of seven and six out of seven S2-derived VIs were positively related to epigeous and coprophagous arthropod biomass, respectively. The blue normalized difference VI (BNDVI) and enhanced normalized difference VI(ENDVI) showed consistent and positive relationships with arthropod biomass, regardless of the arthropod group or spatial resolution. Our results showed that UAV and S2-VI imagery data may be viable and cost-efficient alternatives for quantifying arthropod biomass at large scales in shrub steppes. The relationship between VI and arthropod biomass is probably habitat-dependent, so future research should address this relationship and include several habitats to validate VIs as proxies of arthropod biomass.

Bioregionalization of the coastal and open oceans of British Columbia and Southeast Alaska based on Sentinel-3A satellite-derived phytoplankton seasonality

Classifying the ocean into regions with distinct biogeochemical or physical properties may enhance our interpretation of ocean processes. High-resolution satellite-derived products provide valuable data to address this task. Notwithstanding, no regionalization at a regional scale has been attempted for the coastal and open oceans of British Columbia (BC) and Southeast Alaska (SEA), which host essential habitats for several ecologically, culturally, and commercially important species. Across this heterogeneous marine domain, phytoplankton are subject to dynamic ocean circulation patterns and atmosphere-ocean-land interactions, and their variability, in turn, influences marine food web structure and function. Regionalization based on phytoplankton biomass patterns along BC and SEA’s coastal and open oceans can be valuable in identifying pelagic habitats and representing a baseline for assessing future changes. We developed a two-step classification procedure, i.e., a Self-Organizing Maps (SOM) analysis followed by the affinity propagation clustering method, to define ten bioregions based on the seasonal climatology of high-resolution (300 m) Sentinel-3 surface chlorophyll-a data (a proxy for phytoplankton biomass), for the period 2016-2020. The classification procedure allowed high precision delineation of the ten bioregions, revealing separation between off-shelf bioregions and those in neritic waters. Consistent with the high-nutrient, low-chlorophyll regime, relatively low values of phytoplankton biomass (< 1 mg/m3) distinguished off-shelf bioregions, which also displayed, on average, more prominent autumn biomass peaks. In sharp contrast, neritic bioregions were highly productive (>> 1 mg/m3) and characterized by different phytoplankton dynamics. The spring phytoplankton bloom onset varied spatially and inter-annually, with substantial differences among bioregions. The proposed high-spatial-resolution regionalization constitutes a reference point for practical and more extensive implementation in understanding the spatial dynamics of the regional ecology, data-driven ocean observing systems, and objective regional management.

Methods for robust estimates of tree biomass from pollen accumulation rates: Quantifying paleoecological reconstruction uncertainty

Pollen accumulation rates (PAR, grains cm–2 year–1) have been shown to be a reliable but methodologically complex bioproxy for quantitative reconstruction of past tree abundance. In a prior study, we found that the PARs of major tree taxa – Pseudotsuga, Pinus, Notholithocarpus, and the pollen group TC (Taxaceae and Cupressaceae families) – were robust and precise estimators of contemporary tree biomass. This paper expands our earlier work. Here, we more fully evaluate the errors associated with biomass reconstructions to identify weaknesses and recommend improvements in PAR-based reconstructions of forest biomass. We account for uncertainty in our biomass proxy in a formal, coherent fashion. The greatest error was introduced by the age models, underscoring the need for improved statistical approaches to age-depth modeling. Documenting the uncertainty in pollen vegetation models should be standard practice in paleoecology. We also share insights gained from the delineation of the relevant source area of pollen, advances in Bayesian 210Pb modeling, the importance of site selection, and the use of independent data to corroborate biomass estimates. Lastly, we demonstrate our workflow with a new dataset of reconstructed tree biomass between 1850 and 2018 AD from lakes in the Klamath Mountains, California. Our biomass records followed a broad trend of low mean biomass in the ∼1850s followed by large contemporary increases, consistent with expectations of forest densification due to twentieth century fire suppression policies in the American West. More recent reconstructed tree biomass estimates also corresponded with silviculture treatments occurring within the relevant source area of pollen of our lake sites.

Linking eutrophication to carbon dioxide and methane emissions from exposed mangrove soils along an urban gradient

Mangroves are one of the most important but threatened blue carbon ecosystems globally. Rapid urban growth has resulted in nutrient inputs and subsequent coastal eutrophication, associated with an enrichment in organic matter (OM) from algal and sewage sources and substantial changes in greenhouse gas (GHG) emissions. However, the effects of nitrogen (N) and phosphorus (P) enrichment on mangrove soil OM composition and GHG emissions, such as methane (CH4) and carbon dioxide (CO2), are still poorly understood. Here, we aim to evaluate the relationships between CO2 and CH4 efflux with OM composition in exposed soils from three mangrove areas along watersheds with different urbanization levels (Rio de Janeiro State, Brazil). To assess spatial (lower vs. upper intertidal zones) and seasonal (summer vs. winter) variability, we measured soil-air CO2 and CH4 fluxes at low spring tide, analyzing elementary (C, N, and P), isotopic (δ13C and δ15N), and the molecular (n-alkanes and sterols) composition of surface soil OM. A general trend of OM composition was found with increasing urban influence, with higher δ15N (proxy of anthropogenic N enrichment), less negative δ13C, more short-chain n-alkanes, lower C:N ratio (proxies of algal biomass), and higher epicoprostanol content (proxies of sewage-derived OM). The CO2 efflux from exposed soils increased greatly in median (25/75 % interquartile range) from 4.6 (2.9/8.3) to 24.0 (21.5/32.7) mmol m−2 h−1 from more pristine to more urbanized watersheds, independent of intertidal zone and seasonality. The CO2 fluxes at the most eutrophicated site were among the highest reported worldwide for mangrove soils. Conversely, CH4 emissions were relatively low (three orders of magnitude lower than CO2 fluxes), with high peaks in the lower intertidal zone during the rainy summer. Thus, our findings demonstrate the influence of coastal eutrophication on global warming potentials related to enhanced heterotrophic remineralization of blue carbon within mangrove soils.

A suggested climate service for cyanobacteria blooms in the Baltic Sea – Comparing three monitoring methods

Dense blooms of filamentous cyanobacteria are recurrent phenomena in the Baltic Sea, with occasional negative effects on the surrounding ecosystem, as well as on tourism, human health, aquaculture, and fisheries. Establishing a climate service is therefore suggested; including multi-method observations of cyanobacteria biomass, biodiversity, and biogeography, in correspondence to biotic and abiotic factors. Three different approaches were compared for determination of spatial and temporal variability and trends of the blooms; 1) microscopy-based long-term data, 2) satellite remote sensing, and 3) phycocyanin fluorescence mounted on a merchant vessel. Firstly, microscopy-based data on cyanobacteria biomass from the period 2000–2020 showed that the toxin producing genus Nodularia and non-toxic Aphanizomenon both had summer means of 15 µg C L−1, while Dolichospermum was less dominant with a mean of 8 µg C L−1. Some years also the Kattegat was affected by cyanobacteria blooms, likely transported here by ocean currents. Secondly, the satellite remote sensing time series for the period 2002–2020 indicated that near surface blooms were most frequent in the Northern Baltic Proper and that near surface blooms have increased in the Bothnian Sea, starting later in the season than in the Baltic Proper. The largest extents (i.e., total area covered) were observed in 2005, 2008, and 2018. Thirdly, phycocyanin fluorescence from a flow through sensor mounted on a merchant vessel was used as a proxy for cyanobacteria biomass and correlated to cyanobacteria biomass estimated by microscopy. However, the satellite remote sensing data on surface accumulations showed little resemblance to the data on cyanobacteria biomass based on water sampling and microscopy, interpreted as an effect of methods. Sensors on satellites mainly detect surface accumulations of cyanobacteria while the microscopy data was based on samples 0–10 m, thereby comprising a larger community. Data from satellite remote sensing of cyanobacteria was correlated to the phycocyanin fluorescence indicating that similar bio-optical properties are observed. Finally, results from a downscaled ocean climate model (NEMONordic) were used to produce future scenarios for temperature and salinity, which directly affects cyanobacteria blooms in the Baltic Sea, supposedly by increasing in abundance and change in species composition. Short-term forecasts can be used together with observations for early warning of cyanobacteria blooms, and we suggest an internationally coordinated cyanobacteria observation and warning system for the Baltic Sea area.

Vegetation canopy height estimation in dynamic tropical landscapes with TanDEM‐X supported by GEDI data

Abstract Vegetation canopy height is a relevant proxy for aboveground biomass, carbon stock, and biodiversity. Wall‐to‐wall information of canopy height with high spatial resolution and accuracy is not yet available on large scales. For the globally consistent TanDEM‐X data, simplifications are necessary to estimate canopy height with semi‐empirical models based on polarimetric synthetic aperture radar interferometry (PolInSAR). We trained the semi‐empirical models with sampled GEDI data, because the assumptions behind the application of such simplifications are not always valid for TanDEM‐X. General linear as well as sinc models and empirical parameterizations of these models were applied to estimate the canopy height in tropical landscapes of Sumatra, Indonesia. Airborne laser scanning (ALS) data were consistently used as an independent reference. The general simplified models were compared with the trained empirical versions to assess the potential improvement of the empirical parameterization of the models. The residuals of the different canopy height models were further evaluated in relation to land use and structural information of the vegetation. Our results indicated that the empirical parameters substantially improved the estimation from a root‐mean‐square‐error (RMSE) of 10.3 m (55.8%) to 8.8 m (47.7%), when using the linear model. In contrast, the improvement of the sinc model with empirical parameters was not substantial compared to the general sinc model (7.4 m [40.4%] vs. 6.9 m [37.5%]). A consistent improvement was observed in the linear model, whereas the improvement of the sinc model was dependent on the land‐use type. Structural attributes like the canopy height itself and vegetation cover had a significant effect on the accuracies, with higher and denser vegetation generally resulting in higher residuals. We demonstrate the potential of the combined exploitation of the TanDEM‐X and GEDI missions for a wall‐to‐wall canopy height estimation in a tropical region. This study provides relevant findings for a consistent mapping of vegetation canopy height in tropical landscapes and on large scales with spaceborne laser and SAR data.

Sub‐Seasonal Forcing Drives Year‐To‐Year Variations of Southern Ocean Primary Productivity

AbstractPrimary productivity in the Southern Ocean plays a key role in global biogeochemical cycles. While much focus has been placed on phytoplankton production seasonality, non‐seasonal fluctuations exceed the amplitude of the seasonal cycle across large swaths of the Antarctic Circumpolar Current. This non‐seasonal variability comprises a broad range of timescales from sub‐seasonal (<3 months) to multi‐annual (>1 year), all of which can project onto the annual mean value. However, year‐to‐year variations of surface chlorophyll (SChl), a proxy for phytoplankton biomass, are typically attributed to ocean circulation changes associated with the Southern Annular Mode (SAM), which implicitly assumes that sub‐seasonal variability averages to near‐zero over long timescales. Here, we test this assumption by applying a timeseries decomposition method to satellite‐derived SChl in order to separate the low‐frequency and high‐frequency contributions to the non‐seasonal variability. We find that throughout most of the Southern Ocean, year‐to‐year SChl variations are dominated by the sub‐seasonal component, which is not strongly correlated with the SAM. The multi‐annual component, while correlated with the SAM, only accounts for about 10% of the total SChl variance. This suggests that changes in annual mean SChl are related to intermittent forcing at small scales, rather than low‐frequency climate variability, and thus do not remain correlated over large regions.

Data reconstruction of daily MODIS chlorophyll-a concentration and spatio-temporal variations in the Northwestern Pacific

Sea surface chlorophyll-a concentration (Chl-a) is a key proxy for phytoplankton biomass. Spatio-temporal continuous Chl-a data are important to understand the mechanisms of chlorophyll occurrence and development and track phytoplankton changes. However, the greatest challenge in utilizing daily Chl-a data is massive missing pixels due to orbital position and cloud coverage. This study proposes the application of a spatial filling method using the machine learning-based Extreme Gradient Boosting (BST) to reconstruct missing pixels of daily MODIS Chl-a data from 2007 to 2018. The approach is applied to different trophic biogeographical subregions of the Northwestern Pacific where it has complex phytoplankton dynamics and frequent data missing. Various environmental variables are taken into consideration, including meteorological forcing, geographic and topographic features, and oceanic physical components. The BST-reconstructed Chl-a (BST Chl-a) is validated using in-situ Chl-a measurements, VIIRS and Himawari-8 Chl-a products. The results show that the BST model is highly adaptive in reconstructing Chl-a data, and it performs well in pelagic, offshore and coastal with the best performance in pelagic. BST Chl-a improves coverage without significant quality degradation compared to the original MODIS Chl-a. BST Chl-a agrees better with in-situ data than that of MODIS, with CC of 0.742, RMSE of 0.247, MAE of 0.202 and Bias of 0.089. Cross-satellite validation using VIIRS and Himawari-8 Chl-a also shows promising results with the CC of 0.861 and 0.765, respectively, suggesting the high accuracy of BST Chl-a. The inter-annual trend of BST Chl-a decreases in coastal and increases in offshore and pelagic. BST Chl-a images present similar spatial patterns to MODIS Chl-a under different missing rates, with gradual decreases from coastal to pelagic. It indicates that phytoplankton bloom patterns can be identified by daily BST Chl-a images.

Mapping algal bloom dynamics in small reservoirs using Sentinel-2 imagery in Google Earth Engine

Freshwater algal blooms have caused ecological damage and public health concerns throughout the world. Monitoring such blooms via in situ sampling is both costly and time-consuming, and satellite imagery provides a rapid and relatively inexpensive way to supplement these techniques. Sentinel-2 MultiSpectral Imager data have effectively detected chlorophyll-a, a proxy for algal biomass, in large bodies of water, but few studies have shown the applicability in small (<10 km2) reservoirs, which are critically important for aquatic species, drinking water, irrigation, cultural activities, and recreation. This study provides a test of the use of Sentinel-2 imagery in Google Earth Engine for algal bloom detection in two small freshwater reservoirs in northern California, USA, from October 2015 to December 2020. Google Earth Engine’s cloud computing allows for the analysis of extensive datasets and time series, expanding the capacity to analyze the spatial and temporal heterogeneity of floating algal blooms. Here we analyzed four spectral indices - Normalized Difference Vegetation Index (NDVI), Normalized Difference Chlorophyll Index (NDCI), B8AB4, and B3B2 - to retrieve chlorophyll-a data for algal bloom identification in two highly dynamic freshwater systems. We assessed the relationship between spectral indices and monthly in situ water samples that were collected at three sites within the reservoirs using cubic polynomial regression equations. NDCI, which leverages the red-edge wavelength, most accurately identified chlorophyll-a across all study sites (highest adjusted R2 = 0.84, lowest RMSE = 0.02 µg/l), followed by NDVI. We demonstrate that Sentinel-2 imagery can capture greater spatial and temporal heterogeneity of algal blooms than typical in situ sampling. This suggests that remote sensing may be an increasingly important tool in monitoring algal bloom dynamics in small reservoirs and other aquatic environments.

Mapping the long‐term influence of river discharge on coastal ocean chlorophyll‐a

AbstractAlthough the potential of river discharge to support ocean productivity and marine ecosystems is known, the specifics of this relationship are poorly understood in many regions of the world. Global estimates of river flow indicate that river discharge is decreasing due to the increasing fragmentation, extraction and regulation of rivers. This likely means that the contribution of river flow to coastal productivity and water quality is changing, potentially leading to fewer and smaller magnitude ocean fertilisation events. We developed a simple analysis method, based on Earth observation data, to investigate where coastal ocean chlorophyll‐a is most strongly influenced by river discharge. The per‐pixel spatiotemporal correlation technique (implemented using Python) correlates chlorophyll‐a concentration (a proxy for phytoplankton biomass and indicator of primary productivity) from MODIS ocean colour data with river discharge data. The method was tested globally on 11 different rivers discharging into coastal ocean regions. Our findings suggest some of the world's largest river systems, such as the Amazon River, have zones of elevated coastal chl‐a that extend hundreds to thousands of km from the river mouth. These findings suggest the influence of river discharge may have been underestimated in many coastal regions of the world. The method appears more effective for larger river systems discharging to ocean waters with less complex nutrient dynamics and weaker seasonal productivity patterns, most notably in temperate regions. Increasing our understanding of the specific areas influenced by river discharge, and the degree of influence over space and time, is an important step towards the improved river and coastal management. This method will increase the capacity of researchers to monitor how, when and where coastal waters are affected as river discharge continues to change into the future.

Biogeographical Classification of the Global Ocean From BGC-Argo Floats.

Biogeographical classifications of the global ocean generalize spatiotemporal trends in species or biomass distributions across discrete ocean biomes or provinces. These classifications are generally based on a combination of remote‐sensed proxies of phytoplankton biomass and global climatologies of biogeochemical or physical parameters. However, these approaches are limited in their capacity to account for subsurface variability in these parameters. The deployment of autonomous profiling floats in the Biogeochemical Argo network over the last decade has greatly increased global coverage of subsurface measurements of bio‐optical proxies for phytoplankton biomass and physiology. In this study, we used empirical orthogonal function analysis to identify the main components of variability in a global data set of 422 annual time series of Chlorophyll a fluorescence and optical backscatter profiles. Applying cluster analysis to these results, we identified six biomes within the global ocean: two high‐latitude biomes capturing summer bloom dynamics in the North Atlantic and Southern Ocean and four mid‐ and low‐latitude biomes characterized by variability in the depth and frequency of deep chlorophyll maximum formation. We report the distribution of these biomes along with associated trends in biogeochemical and physicochemical environmental parameters. Our results demonstrate light and nutrients to explain most variability in phytoplankton distributions for all biomes, while highlighting a global inverse relationship between particle stocks in the euphotic zone and transfer efficiency into the mesopelagic zone. In addition to partitioning seasonal variability in vertical phytoplankton distributions at the global scale, our results provide a potentially novel biogeographical classification of the global ocean.

Basin-scale biogeochemical and ecological impacts of islands in the tropical Pacific Ocean

In the relatively unproductive waters of the tropical ocean, islands can enhance phytoplankton biomass and create hotspots of productivity and biodiversity that sustain upper trophic levels, including fish that are crucial to the survival of islands’ inhabitants. This phenomenon, termed the island mass effect 66 years ago, has been widely described. However, most studies focused on individual islands, and very few documented phytoplankton community composition. Consequently, basin-scale impacts on phytoplankton biomass, primary production and biodiversity remain largely unknown. Here we systematically identify enriched waters near islands from satellite chlorophyll concentrations (a proxy for phytoplankton biomass) to analyse the island mass effect for all tropical Pacific islands on a climatological basis. We find enrichments near 99% of islands, impacting 3% of the tropical Pacific Ocean. We quantify local and basin-scale increases in chlorophyll and primary production by contrasting island-enriched waters with nearby waters. We also reveal a significant impact on phytoplankton community structure and biodiversity that is identifiable in anomalies in the ocean colour signal. Our results suggest that, in addition to strong local biogeochemical impacts, islands may have even stronger and farther-reaching ecological impacts.

Quantifying Per-Cell Chlorophyll a in Natural Picophytoplankton Populations Using Fluorescence-Activated Cell Sorting

Marine phytoplankton play a central role in global biogeochemical cycling, carbon export, and the overall functioning of marine ecosystems. While chlorophyll a (Chl a) is widely used as a proxy for phytoplankton biomass, identifying the proportion of Chl a attributable to different phytoplankton groups remains a major challenge in oceanography, especially for the picophytoplankton groups that often represent the majority of phytoplankton biomass in the open ocean. We describe a method for measuring picophytoplankton per-cell Chl a in field samples using fluorescence-activated cell sorting followed by solvent-based Chl a extraction and fluorescence quantification. Applying this method to surface samples from the Gulf of Mexico, we determined per-cell Chl a to be 0.24 ± 0.07, 0.6 ± 0.33, and 26.36 ± 20.9 fg Chl a cell-1 for Prochlorococcus, Synechococcus, and PPE, respectively (mean ± SD). Measurements of per-cell Chl a using this method are precise to within 1.7, 2.1, and 3.1% for Prochlorococcus, Synechococcus, and PPE, respectively. We demonstrate that this approach can be used to obtain estimates of group-specific Chl a for Prochlorococcus, Synechococcus, and picophytoeukaryotes, the latter two of which cannot be captured by existing methods. We also demonstrate that measurements of per-cell Chl a made using this method in field samples are sufficiently precise to capture relationships between per-cell Chl a and cytometer red fluorescence, providing a bridge between biomass estimates from cell counts and bulk measurements of total Chl a.

Hydrodynamic Drivers of Nutrient and Phytoplankton Dynamics in a Subtropical Reservoir

Chlorophyll-a (chla) is an important parameter to assess water quality in lakes and reservoirs, since it is a proxy for phytoplankton biomass and primary production. The increasing availability of data with high spatial and temporal resolution allows assessing short-term dynamics and small-scale variations of chla within larger water bodies. In freshwater reservoirs, the nutrient concentrations and the physical conditions that control phytoplankton growth vary along their longitudinal extend. Here, we analyze how the flow paths of the inflowing river water into density-stratified reservoirs affect the vertical and longitudinal distribution of nutrients and chla. We combine spatially resolved and high-frequency measurements of chla from satellite remote sensing and in-situ sensors, with numerical simulations using a three-dimensional hydrodynamic model to assess the influence of density currents on chla dynamics along a subtropical drinking water reservoir in the south of Brazil. Chla did not have pronounced seasonal dynamics (4.9 ± 1.2 µg L−1, at the continuous measurement station); instead, spatial variability along the reservoir was more pronounced (4.4 ± 2.1 µg L−1, all monitored points within the euphotic zone). Most of the nutrients from the inflowing river were consumed in the upstream region, and phytoplankton in the lacustrine zone depended on internal loading. Temporal variability was observed only in the upstream region, and phytoplankton produced in that area was transported downstream by density currents, resulting in large concentrations of chla below the euphotic zone. The results of a hydrodynamic model that simulates the present state are in good agreement with the observations. Two simulated scenarios, where the density current patterns were altered, resulted only in slight variations in density currents, indicating that the influence of the main inflow was of minor relevance in chla concentrations in downstream regions of the reservoir. Our results highlight the importance of two-dimensional hydrodynamic processes in regulating phytoplankton dynamics in reservoirs.

Phytoplankton Distributions in the Kuroshio-Oyashio Region of the Northwest Pacific Ocean: Implications for Marine Ecology and Carbon Cycle

The Northwest Pacific Ocean (NWPO) is a significant sink for atmospheric CO2 but a paucity of large-scale phytoplankton surveys in the upper and lower euphotic zone results in uncertainties in estimates of the efficiency of the biological carbon pump there. Here, we report the spatial distribution of lipid biomarkers from diatoms (brassicasterol/epi-brassicasterol), dinoflagellates (dinosterol), and haptophytes (C37 alkenones) as proxies of phytoplankton biomass and community structure in suspended particles from the surface and deep chlorophyll maximum (DCM) layers across low- and mid-latitude regions of the NWPO. Our observations suggest that these lipid biomarkers can be used as indicators of the vertical distributions of phytoplankton biomass, which was comparable between the surface and DCM layers. Water masses with different nutrient concentrations strongly controlled the variations of lipid biomarkers, showing high biomass and the dominance of diatoms in the eutrophic Oyashio region, whereas low biomass and high proportions of dinoflagellates and haptophytes occurred in the oligotrophic Kuroshio region. Diatoms predominated in the DCM, likely enhancing carbon sequestration in the deep ocean and in sediments. Our results quantitatively demonstrate the horizontal and vertical variations of phytoplankton biomass and community structure, leading to an improved understanding of ecosystem function and biogeochemical cycles in this important region of the NWPO.

Satellite observations estimating the effects of river discharge and wind-driven upwelling on phytoplankton dynamics in the Chesapeake Bay.

Phytoplankton growth in estuaries is regulated by a complex combination of physical factors with freshwater discharge usually playing a dominating role controlling nutrient and light availability. The role of other factors, including upwelling-generating winds, is still unclear because most estuaries are too small for upwelling to emerge. In this study, we used remotely sensed proxies of phytoplankton biomass and concentration of suspended mineral particles to compare the effect of river discharge with the effect of upwelling events associated with persistent along-channel southerly winds in the Chesapeake Bay, a large estuary where upwelling and its effects on biogeochemical dynamics have been previously reported. The surface chlorophyll-a concentrations (Chl-a) were estimated from Visible Infrared Imaging Radiometer Suite (VIIRS) satellite data using the Generalized Stacked-Constraints Model (GSCM) corrected for seasonal effects by comparing remotely sensed and field-measured data. Light limitation of phytoplankton growth was assessed from the concentration of suspended mineral particles estimated from the remotely sensed backscattering at blue (443 nm) wavelength bbp (443). The nine-year time series (2012-2020) of Chl-a and bbp (443) confirmed that a primary factor regulating phytoplankton growth in this nearshore eutrophic area is discharge from the Susquehanna River, and presumably the nutrients it delivers, with a time lag up to four months. Persistent southerly wind events (2-3 days with wind speed >4 m/s) affected the water column stratification in the central part of the bay but did not result in significant increases in remotely sensed Chl-a. Analysis of model simulations of selected upwelling-favorable wind events revealed that strong southerly winds resulted in well-defined lateral (East-West) responses but were insufficient to deliver high-nutrient water to the surface layer to support phytoplankton bloom. We conclude that, in the Chesapeake Bay, which is a large, eutrophic estuary, wind-driven upwelling of deep water plays a limited role in driving phytoplankton growth under most conditions compared with river discharge. Integr Environ Assess Manag 2022;18:921-938. © 2022 SETAC.

Portfolio effects and functional redundancy contribute to the maintenance of octocoral forests on Caribbean reefs

Declines in abundance of scleractinian corals on shallow Caribbean reefs have left many reefs dominated by forests of arborescent octocorals. The ecological mechanisms favoring their persistence require exploration. We quantified octocoral communities from 2014 to 2019 at two sites in St. John, US Virgin Islands, and evaluated their dynamics to assess whether portfolio effects might contribute to their resilience. Octocorals were identified to species, or species complexes, and their abundances and heights were measured, with height2 serving as a biomass proxy. Annual variation in abundance was asynchronous among species, except when they responded in similar ways to hurricanes in September 2017. Multivariate changes in octocoral communities, viewed in 2-dimensional ordinations, were similar between sites, but analyses based on density differed from those based on the biomass proxy. On the density scale, variation in the community composed of all octocoral species was indistinguishable from that quantified with subsets of 6–10 of the octocoral species at one of the two sites, identifying structural redundancy in the response of the community. Conservation of the relative colony size-frequency structure, combined with temporal changes in the species represented by the tallest colonies, suggests that portfolio effects and functional redundancy stabilize the vertical structure and canopy in these tropical octocoral forests.