Proxy For Biomass Research Articles

Carbon-centric dynamics of Earth’s marine phytoplankton

Marine phytoplankton are fundamental to Earth's ecology and biogeochemistry. Our understanding of the large-scale dynamics of phytoplankton biomass has greatly benefited from, and is largely based on, satellite ocean color observations from which chlorophyll-a (Chla), a commonly used proxy for carbon biomass, can be estimated. However, ocean color satellites only measure a small portion of the surface ocean, meaning that subsurface phytoplankton biomass is not directly monitored. Chla is also an imperfect proxy for carbon biomass because cellular physiology drives large variations in their ratio. The global network of Biogeochemical (BGC)-Argo floats now makes it possible to complement satellite observations by addressing both these issues at once. In our study, we use ~100,000 water-column profiles from BGC-Argo to describe Earth's phytoplankton carbon biomass and its spatiotemporal variability. We estimate the global stock of open ocean phytoplankton biomass at ~314 Tg C, half of which is present at depths not accessible through satellite detection. We also compare the seasonal cycles of carbon biomass stocks and surface Chla visible from space and find that surface Chla does not accurately identify the timing of the peak annual biomass in two-thirds of the ocean. Our study is a demonstration of global-scale, depth-resolved monitoring of Earth's phytoplankton, which will be crucial for understanding future climate-related changes and the effects of geoengineering interventions if implemented.

Soil moisture and water redistribution patterns in white oak (Quercus alba) saplings and trees in fragmented urban woodlands

In the midwestern United States, models predict extended summer heatwaves and increasingly frequent and prolonged drought conditions. In the Chicago region, the potential for large-scale mortality of white oak trees (Quercus alba) coupled with the ongoing decline of white oak sapling recruitment are major concerns for researchers and practitioners. In this study, we determined the sources of water used by mature white oak trees and saplings in three qualitatively different sites within a remnant oak forest in Chicago during the 2021 drought. We investigated soil moisture dynamics (volumetric water content, VWC) and water isotope composition of leaf tissues (δD, δ18O), rainwater, and groundwater. These data were linked to sapling height (proxy for biomass) and ectomycorrhizal (ECM) functional types. We predicted that: (i) mature oak trees use deeper water sources and conducted hydraulic redistribution (HR), and (ii) mature trees shared water with saplings during dry periods via long-distance ECM functional types. Soil moisture decreased progressively from June to October (spring to fall), with August and September having the lowest moisture (<20 % VWC). Following rainfall recharge, temporal patterns of soil moisture showed gravity drainage and then ongoing stair-stepwise drawdown consistent with plant evapotranspiration. Leaf δD and δ18O values in mature trees and saplings were consistent with water uptake from rainfall and subsequent enrichment via evapotranspiration. In two sites, mature trees and saplings demonstrated distinct δD: δ18O slopes, with mature trees more enriched than saplings. In the third site, mature trees and saplings δD: δ18O slopes overlapped but here, the ECM community was dominated by contact-type ECM and sapling height increased with distance from the mature oak. Our findings indicate that HR was not a component of site ecohydrology, and future climate conditions may present increasing challenges for white oak recruitment as both mature trees and saplings compete for limited rainfall-derived soil moisture.

Defining algal bloom phenology in Lake Erie

Elucidating the impact of global climate change on aquatic ecosystems, particularly through phenological shifts in primary producers, is critical for understanding ecological resilience. Here, we focus on the phenological shifts in chlorophyll as a proxy for algae biomass and primary production in aquatic ecosystems, specifically in Lake Erie as well as concentrations of the toxin microcystin. By tracking temporal changes in each, we identified key phenological phases important to estimate duration, magnitude, and intensity of harmful algal blooms (HABs). Determining which influential biotic and abiotic factors such as temperature, wind speed, nutrient availability, and climate change is most important, is a long-term management need for Lake Erie, which can be explored using our methodology. Our novel statistical framework employing Bayesian generalized additive mixed models described seasonal chlorophyll and particulate microcystin concentration from Lake Erie and our simple geometric method identified the start, peak, and end of algal blooms. This research enhances our understanding of the ecological effects of nutrient pollution on aquatic ecosystems and provides a repeatable method for determining phenological events without the need for user defined cutoffs which aids in the management and mitigation of HABs, safeguarding water quality in regions dependent on lakes for drinking water.

In situ imaging of a kleptoplastidic ciliate thin layer indicates traditional sampling underestimates oceanic mixotroph biomass

Planktonic mixotrophs, including ciliates, are abundant, yet understudied, mediators of primary and secondary production in aquatic food webs. Here, we report high-resolution in situ observations of a thin layer—a vertically limited patch of high organism abundance—of the ciliate, Laboea strobila. Within the thin layer, peak L. strobila abundances were as high as 62,000 cells/L, six times higher than previously reported, and were strongly positively correlated with co-measured chlorophyll a concentrations, indicating that the organism indulged in kleptoplasty, retaining plastids from ingested algae. Estimates indicated L. strobila contributed to ~63–78% of chlorophyll a within the layer, in sharp contrast to conventional expectations that phytoplankton dominate this signature, suggesting that mixotroph biomass, and consequently, their contribution to marine ecosystems is widely underestimated. These observations also highlight the importance of pairing traditional approaches such as chlorophyll a measurements with high-resolution imaging for proper attribution of biomass proxies.

Remote Sensing of Chlorophyll-a in Clear vs. Turbid Waters in Lakes

Chlorophyll-a (Chl-a), a proxy for phytoplankton biomass, is one of the few biological water quality indices detectable using satellite observations. However, models for estimating Chl-a from satellite signals are currently unavailable for many lakes. The application of Chl-a prediction algorithms may be affected by the variance in optical complexity within lakes. Using Lake Winnipeg in Canada as a case study, we demonstrated that separating models by the lake’s basins [north basin (NB) and south basin (SB)] can improve Chl-a predictions. By calibrating more than 40 commonly used Chl-a estimation models using Landsat data for Lake Winnipeg, we achieved higher correlations between in situ and predicted Chl-a when building models with separate Landsat-to-in situ matchups from NB and SB (R2 = 0.85 and 0.76, respectively; p &lt; 0.05), compared to using matchups from the entire lake (R2 = 0.38, p &lt; 0.05). In the deeper, more transparent waters of the NB, a green-to-blue band ratio provided better Chl-a predictions, while in the shallower, highly turbid SB, a red-to-green band ratio was more effective. Our approach can be used for rapid Chl-a modeling in large lakes using cloud-based platforms like Google Earth Engine with any available satellite or time series length.

Multiple remotely sensed datasets and machine learning models to predict chlorophyll-a concentration in the Nakdong River, South Korea.

The Nakdong River is a crucial water resource in South Korea, supplying water for various purposes such as potable water, irrigation, and recreation. However, the river is vulnerable to algal blooms due to the inflow of pollutants from multiple points and non-point sources. Monitoring chlorophyll-a (Chl-a) concentrations, a proxy for algal biomass is essential for assessing the trophic status of the river and managing its ecological health. This study aimed to improve the accuracy and reliability of Chl-a estimation in the Nakdong River using machine learning models (MLMs) and simultaneous use of multiple remotely sensed datasets. This study compared the performances of four MLMs: multi-layer perceptron (MLP), support vector machine (SVM), random forest (RF), and eXetreme Gradient Boosting (XGB) using three different input datasets: (1) two remotely sensed datasets (Sentinel-2 and Landsat-8), (2) standalone Sentinel-2, and (3) standalone Landsat-8. The results showed that the MLP model with multiple remotely sensed datasets outperformed other MLMs with 0.43 - 0.86 greater in R2 and 0.36 - 5.88 lower in RMSE. The MLP model demonstrated the highest performance across the range of Chl-a concentrations and predicted peaks above 20 mg/m3 relatively well compared to other models. This was likely due to the capacity of MLP to handle imbalanced datasets. The predictive map of the spatial distribution of Chl-a generated by MLP well captured the areas with high and low Chl-a concentrations. This study pointed out the impacts of imbalanced Chl-a concentration observations (dominated by low Chl-a concentrations) on the performance of MLMs. The data imbalance likely led to MLMs poorly trained for high Chl-a values, producing low prediction accuracy. In conclusion, this study demonstrated the value of multiple remotely sensed datasets in enhancing the accuracy and reliability of Chl-a estimation, mainly when using the MLP model. These findings would provide valuable insights into utilizing MLMs effectively for Chl-a monitoring.

The interaction between vegetation patchiness and tidal flows in a shortleaf seagrass meadow

AbstractSeagrasses are critical coastal habitats that provide numerous ecosystem services. The inherent patchiness within meadows exerts a significant influence on the flow‐vegetation interaction, which, in turn, affects the array of services provided by these environments. We present field observations of vegetation distribution and hydrodynamic measurements within and surrounding an approximately 2 m diameter gap (bare sediment) in a fragmented seagrass meadow. We show that variability in mean flows and turbulence is correlated with meadow structure at small (O (100 m)) and large (O (102 m)) spatial scales. Our observations reveal that bare gaps within seagrass meadows lead to faster flows and lower bed elevations. Despite slower flow speeds above the dense seagrass adjacent to the gap, the rates of dissipation of turbulent energy above the vegetation are typically around an order of magnitude larger than above the bare bed. Associated with this enhanced dissipation of turbulent energy, we observed a dominance of down‐deceleration events promoting fluid exchange and mixing and driving mass flux into the canopy. Analysis of directional variograms demonstrates that the major continuity axis within NDVI (normalized difference vegetation index) imagery (used as a proxy for vegetation biomass) coincides with the major axis of flow on both gap and meadow scales. Conversely, along the axis of minor flow variance, vegetation remains dense and exhibits greater uniformity. These findings indicate a feedback mechanism between seagrass meadow patchiness and spatial structure through flow modification, which may be beneficial for plant development.

Effects of Tree Leaves, Tannins, and Water Color on Chlorophyll Concentrations in Ponds

Leaf litter is an important input to freshwater systems. Leaves provide carbon, nutrients, and secondary compounds. We examined the effects of tree leaf species on chlorophyll a concentration—a proxy for phytoplankton biomass. We found that an input of Chinese tallow (Triadica sebiferum, invasive in the southeastern USA) and red maple (Acer rubrum) leaves resulted in lower chlorophyll concentrations than controls and other native species. These leaf species also leached tannins, resulting in a darker water color, and either may have caused the patterns observed. To separate these potential mechanisms (darker water leading to light limitation and tannin toxicity), we conducted a second experiment with a fully factorial design manipulating tannins and water color. We found that darker water resulted in the lowest chlorophyll concentration, suggesting light limitation. In the clear-water treatment, the addition of tannic acid lowered chlorophyll concentrations but also resulted in moderately darker water by the end of the experiment. The tannic acid may have been toxic to the algae, or there may have been some light limitation. Our results suggest that tannins that darken water color may substantially suppress phytoplankton and that tree species composition may influence both phytoplankton and the brownification of freshwater.

Causal feedback loops modify lake chlorophyll a–nutrient relationships over two decades of nutrient reductions and climate warming

AbstractUnderstanding how the causal feedback between phytoplankton and environmental drivers controlling the chlorophyll a (Chl a, as a proxy of phytoplankton biomass)–nutrient relationships are modulated under different ecosystem conditions is a major challenge in aquatic ecology. Using an empirical dynamic model (convergent cross mapping) on a 20‐yr dataset on 20 Danish lakes, we quantified hypothesized causal feedback networks for each lake and related them to lake system properties (e.g., mean water depth, nutrient concentrations and extent of reduction, climate warming) vs. the Chl a–nutrient relationship (estimated from generalized least square models). The results showed prevalent causal feedback across the studied lakes, which demonstrated clear patterns for the tested ecosystem variations. Weaker causal feedbacks were found in deeper lakes and lakes with larger warming trends, while stronger causal feedbacks appeared in lakes experiencing greater reductions of TP (total phosphorus) and TN (total nitrogen). Moreover, these causal feedbacks showed a strong and positive coupled pattern. Most of the causal feedbacks worked as enhancement loops, which promote the sensitivity of phytoplankton to TP, not least in shallow lakes with a high TP reduction, and as regulatory loops, which force a shift in the Chl a–TN relationship from a more negative slope in lakes experiencing a high nutrient reduction and weak warming to a positive slope in lakes with low nutrient reduction and stronger warming. Our findings suggest a mechanistic explanation of how internal feedbacks regulate the Chl a–nutrient relationships across a broad gradient of nutrient reductions, climate warming, and lake morphologies.

Normalized difference vegetation index analysis reveals increase of biomass production and stability during the conversion from conventional to organic farming.

Monitoring agriculture by remote sensing enables large-scale evaluation of biomass production across space and time. The normalized difference vegetation index (NDVI) is used as a proxy for green biomass. Here, we used satellite-derived NDVI of arable farms in the Netherlands to evaluate changes in biomass following conversion from conventional to organic farming. We compared NDVI and the stability of NDVI across 72 fields on sand and marine clay soils. Thirty-six of these fields had been converted into organic agriculture between 0 and 50 years ago (with 2017 as reference year), while the other 36 were paired control fields where conventional farming continued. We used high-resolution images from the Sentinel-2 satellite to obtain NDVI estimates across 5 years (January 2016-October 2020). Overall, NDVI did not differ between conventional and organic management during the time series, but NDVI stability was significantly higher under organic management. NDVI was lower under organic management in sandy, but not in clay, soils. Organic farms that had been converted less than ~19 years ago had lower NDVI than conventional farms. However, the difference diminished over time and eventually turned positive after ~19 years since the conversion. NDVI, averaged across the 5 years of study, was positively correlated to soil Olsen-P measured from soil samples collected in 2017. We conclude that NDVI in organic fields was more stable than in conventional fields, and that the lower biomass in the early years since the transition to organic agriculture can be overcome with time. Our study also indicates the role of soil P bioavailability for plant biomass production across the examined fields, and the benefit of combining remote sensing with on-site soil measurements to develop a more mechanistic understanding that may help us navigate the transition to a more sustainable type of agriculture.

Contrasted Trends in Chlorophyll‐a Satellite Products

AbstractPhytoplankton sustains marine ecosystems and influences the global carbon cycle. This study analyzes trends in surface chlorophyll‐a concentration (Schl), a proxy for phytoplankton biomass, using six of the most widely used merged satellite products. Significant regional variations are observed, with contrasting trends observed among different products. To assess if these trends can be related to changes in the environment or to bias in radiometric products, a convolutional neural network is used to examine the relationship between physical ocean variables versus Schl. The results suggest that the merging algorithm of Globcolour‐GSM is not reliable for trend detection and that observed changes in Schl after 2012/2016 are not supported by changes of the physical ocean. These results emphasize the need for careful interpretation of satellite‐derived Schl trends and highlight the potential of machine learning in understanding the complex interactions in marine ecosystems.

Seasonal patterns of microbial diversity across the world oceans

AbstractUnderstanding the patterns of marine microbial diversity (Bacteria + Archaea) is essential, as variations in their alpha‐ and beta‐diversities can affect ecological processes. Investigations of microbial diversity from global oceanographic expeditions and basin‐wide transects show positive correlations between microbial diversity and either temperature or productivity, but these studies rarely captured seasonality, especially in polar regions. Here, using multiannual alpha‐diversity data from eight time series in the northern and southern hemispheres, we show that marine microbial community richness and evenness generally correlate more strongly with daylength than with temperature or chlorophyll a (a proxy for photosynthetic biomass). This pattern is observable across time series found in the northern and southern hemispheres regardless of collection method, DNA extraction protocols, targeted 16S rRNA hypervariable region, sequencing technology, or bioinformatics pipeline.

Estimation of net accumulation and removal of fluorescent dissolved organic matter in different Baltic Sea water masses

This study aimed to detect non-conservative processes that affect the distribution of fluorescent dissolved organic matter (FDOM) in the Baltic Sea. An extensive data set comprised of 408 FDOM data, optical and physical profiles, and the development of a water masses balance model allowed us to ascertain the sources of mixing anomalies. These were seen as second-order deviations in the FDOM distribution as a function of salinity in three layers: surface water, Baltic Sea Winter Water, and deep water. The difference between modeled and measured FDOM values at three different excitation/emission wavelengths allowed to show the strength of non-conservative processes, such as photochemical and microbial decomposition (negative residual values) or extracellular release of dissolved organic matter from phytoplankton, heterotrophic uptake and release from anoxic sediments (positive residual values). Humic-like FDOM fractions displayed positive residuals in all seasons for intermediate and deep layers and negative residuals in surface waters. Largest accumulation rates of humic-like fractions were reached in the Gulf of Gdańsk during summer in intermediate and deep layers, while the greatest removal in surface waters was observed during spring in the Bornholm and Gotland Basins and during summer in the Gulf of Gdańsk, probably due to photodegradation. Positive residuals of the protein-like fraction were observed at the surface in summer and autumn in the Gulf of Gdańsk, probably linked to the abundance of phytoplankton and also due to the low molecular weight by-products of photodegradation of humic-like components. Spatial transects revealed an increase in humic-like residuals with depth and a strong correlation with apparent oxygen utilization, increasing with higher fluorescence and exhibiting an asymptotic trend. A relationship was found between the protein-like fractions and phytoplankton biomass proxies. A generalized concept for FDOM cycling in the Baltic Sea was proposed, highlighting photobleaching as the dominant non-linear process determining the efficiency of humic-like FDOM removal. The protein-like component was found to be more efficiently taken up by aerobic prokaryotes at the surface. Microbial utilization and reworking of organic matter, release from sediments, and a decade-long stagnation of bottom water masses, all contribute to the observed accumulation of FDOM in mesohaline deep waters below the permanent pycnocline in the Baltic Sea.

Different climate conditions drive variations in gross primary productivity and woody biomass accumulation in a temperate and a boreal conifer forest in Canada

Understanding the complex relationships between climate, forest carbon (C) uptake and biomass growth has become a research priority, crucial for assessing the climate change impacts on forest C sequestration. Such associations are expected to vary across biomes, due to different climate constraints on tree physiology. However, our understanding of the seasonal dynamics of long-term C sequestration and how climate influences them in different forest biomes is still limited.We investigated a boreal Pinus banksiana forest (Old Jack Pine, OJP) and a temperate Pinus strobus plantation (Turkey Point, TP39) in Canada. We aimed to assess the link between C uptake and above-ground woody biomass growth, and the effects of climate inter-annual variability on them. We used daily records of climate and gross primary productivity (GPP, period 1999–2019 at OJP and 2003–2018 at TP39), and investigated xylem biomass proxies at cell (cell wall area) and tree-ring level (ring wall area) from 1970 to 2019 at OJP, and from 1970 to 2018 at TP39.In both forests, the direct link between C sink and C source was revealed by the common inter-annual variability of GPP and xylem biomass. GPP and xylem biomass were mostly influenced by spring and late summer temperature at OJP. However, at both sites, summer drought negatively influenced GPP, and biomass growth especially in recent decades. Analysis of dry and cold years evidenced short-term negative effects of low temperature on GPP and xylem biomass in OJP, and of drought in TP39.Long-term intra-annual analyses are crucial to assess the variable effects of climate on forest C cycle. Warm spring and autumn can benefit both GPP and biomass growth, but even in the boreal forest, summer drought has negative impacts. Increasing dry spells, especially in the temperate site, could reduce future forest capacity to uptake C and fix it in wood biomass.

Response of hyporheic biofilms to temperature changes and dissolved organic carbon enrichment: a mesocosm study

PurposeHyporheic biofilms are the central site for biogeochemical cycling in streams and rivers. In view of global warming and increasing human pressures, this study aimed to compare the response of hyporheic biofilm biomass and activities from an unpolluted reference stream reach surrounded by forest with those from a stream reach exposed to agricultural and urban land use using a mesocosm experiment in which the water temperature and dissolved organic carbon (DOC) contents were manipulated.MethodsHyporheic sediments collected in the field from the two study reaches (i.e. reference and impacted) were incubated in the laboratory at two different temperatures (10 °C, 14 °C) and wetted with three types of synthetic water (control [C] – 0 mg L−1; low DOC – 5 mg L−1; high DOC – 30 mg L−1) for four weeks. The responses of the hyporheic biofilms were measured weekly using structural (total protein content [TPC] as a proxy for biofilm biomass) and functional measures (electron transport system activity [ETSA] and community-level physiological profiling [CLPP]).ResultsThe response of hyporheic biofilms to temperature changes and DOC enrichment was site-specific for all studied measures (TPC, ETSA and CLPP, including measured average well colour development [AWCD]). The addition of DOC to biofilms from the pristine stream reach significantly heightened the responses at 10 °C, a temperature within the normal environmental temperature ranges of the reference location, but not at 14 °C, which was here, a temperature outside normal environmental range. On the other hand, biofilms from the impacted stream reach exhibited increased responses following DOC enrichment under both temperature regimes, with a particularly pronounced response at 14 ºC, in this case, both experimental temperatures were within the normal environmental temperature ranges of the study locations.ConclusionHyporheic biofilms were shown to be, like benthic biofilms, sensitive to temperature changes and organic enrichment, but their response to temperature changes and enrichment caused by climate change and/or other anthropogenic pressures (i.e. point and non-point pollution, removal of the riparian zone, hydromorphological modifications, etc.) was not simply linear but site-specific. The intensity of the response, characterized by increased activity and biomass production, appears to be constrained within the temperature ranges prevalent in the environment from which the biofilms originate. These findings emphasize the importance of site-specific considerations in predicting the impacts of climate change and anthropogenic pressures on these critical components of river and stream ecosystems.

Using bioluminescence as a tool for studying diversity in marine zooplankton and dinoflagellates: an initial assessment.

Bioluminescence is light chemically produced by an organism. It is widespread across all major marine phyla and has evolved multiple times, resulting in a high diversity of spectral properties and first flash kinetic parameters (FFKP). The bioluminescence of a system is often a good proxy for planktonic biomass. The species-specific parameters of bioluminescent displays can be measured to identify species in situ and describe planktonic biodiversity. Most bioluminescent organisms will flash when mechanically stimulated i.e., when subjected to supra-threshold levels of shear stress. Here we compare first flash kinetic parameters such as flash duration, peak intensity, rise time, decay time, first-flash mechanically stimulated light and e-folding time obtained with the commercially available Underwater Bioluminescence Assessment Tool (UBAT). We provide descriptions of the first flash kinetic parameters of several species of dinoflagellates Pyrocystis fusiformis, Pyrocystis noctiluca, Pyrodinium bahamense, Lingulodinium polyedra, Alexandrium monilatum and two zooplankton (the ctenophore Mnemiopsis leidyi and the larvacean Oikopleura sp.). FFKPs are then compared and discussed using non-parametric analyses of variance (ANOVAs), hierarchical clustering and a linear discriminant analysis to assess the ability to use bioluminescence signatures for identification. Once the first flash kinetic parameters of a bioluminescent species have been described, it is possible to detect its presence using emissions collected by in situ bathyphotometers. Assessing abundance and diversity of bioluminescent species may therefore be possible.

Stream Algal Biomass Associations with Environmental Variables in a Temperate Rainforest

Benthic algae and autotrophic seston are important bases of stream food webs, and several different environmental factors may influence their biomass. We explored how benthic algae and autotrophic seston biomass (using chlorophyll-a as a proxy for algal biomass) were associated with stream temperature, channel width, canopy cover, stream cardinal orientation, benthic macroinvertebrate functional feeding group abundance, salmonid biomass, and water velocity in 16 small, fish-bearing streams in the temperate rainforest of the Olympic Peninsula in Washington State, USA, in the summer of 2020. We performed a mixed-effects regression analysis of extracted chlorophyll-a (chl-a) and then used model averaging to determine significant (α = 0.05) algal–environmental associations for benthic algae and autotrophic seston separately. We found that benthic algae chl-a concentration increased significantly with stream temperature (p = 0.0085) and decreased significantly with water velocity (p = 0.0053). For autotrophic seston, we found that chl-a concentration increased significantly with benthic macroinvertebrate predator abundance (p = 0.0007) and stream temperature (p = 0.0160). This study underscores the need to consider a broad range of environmental variables when making research and management decisions concerning stream ecology.

Evaluation of Ocean Color Algorithms to Retrieve Chlorophyll-a Concentration in the Mexican Pacific Ocean off the Baja California Peninsula, Mexico

Mathematical algorithms relate satellite data of ocean color with the surface Chlorophyll-a concentration (Chl-a), a proxy of phytoplankton biomass. These mathematical tools work best when they are adapted to the unique bio-optical properties of a particular oceanic province. Ocean color algorithms should also consider that there are significant differences between datasets derived from different sensors. Common solutions are to provide different parameters for each sensor or use merged satellite data. In this paper, we use satellite data from the Copernicus merged product suite and in situ data from the southernmost part of the California Current System to test two widely used global algorithms, OCx and CI, and a regional algorithm, CalCOFI2. The OCx algorithm yielded the most favorable results. Consequently, we regionalized it and conducted further testing, leading to significant improvements, especially in eutrophic and oligotrophic waters. The database was then separated according to (a) dynamic boundaries in the area, (b) bio-optical properties, and (c) climatic conditions (El Niño/La Niña). Regional algorithms were obtained and tested for each partition. The Chl-a retrievals for each model were tested and compared. The best fit for the data was for the regional algorithms that considered the climatic conditions (El Niño/La Niña). These results will allow for the construction of consistent regionally adapted time series and, therefore, will demonstrate the importance of El Niño/La Niña events on the bio-optical properties of the area.

Atlas of phytoplankton phenology indices in selected Eastern Mediterranean marine ecosystems.

Phytoplankton is a fundamental component of marine food webs and play a crucial role in marine ecosystem functioning. The phenology (timing of growth) of these microscopic algae is an important ecological indicator that can be utilized to observe its seasonal dynamics, and assess its response to environmental perturbations. Ocean colour remote sensing is currently the only means of obtaining synoptic estimates of chlorophyll-a (a proxy of phytoplankton biomass) at high temporal and spatial resolution, enabling the calculation of phenology metrics. However, ocean colour observations have acknowledged weaknesses compromising its reliability, while the scarcity of long-term in situ data has impeded the validation of satellite-derived phenology estimates. To address this issue, we compared one of the longest available in situ time series (20 years) of chlorophyll-a concentrations in the Eastern Mediterranean Sea (EMS), along with concurrent remotely-sensed observations. The comparison revealed a marked coherence between the two datasets, indicating the capability of satellite-based measurements in accurately capturing the phytoplankton seasonality and phenology metrics (i.e., timing of initiation, duration, peak and termination) in the studied area. Furthermore, by studying and validating these metrics we constructed a satellite-derived phytoplankton phenology atlas, reporting in detail the seasonal patterns in several sub-regions in coastal and open seas over the EMS. The open waters host higher concentrations from late October to April, with maximum levels recorded during February and lowest during the summer period. The phytoplankton growth over the Northern Aegean Sea appeared to initiate at least a month later than the rest of the EMS (initiating in late November and terminating in late May). The coastal waters and enclosed gulfs (such as Amvrakikos and Maliakos), exhibit a distinct seasonal pattern with consistently higher levels of chlorophyll-a and prolonged growth period compared to the open seas. The proposed phenology atlas represents a useful resource for monitoring phytoplankton growth periods in the EMS, supporting water quality management practices, while enhancing our current comprehension on the relationships between phytoplankton biomass and higher trophic levels (as a food source).

Evaluation of metrics and thresholds for use in national-scale river harmful algal bloom assessments

The spatiotemporal distribution of harmful algal blooms (HABs) in rivers remains poorly understood, and there is an urgent need to develop a consistent set of metrics to better document HAB occurrences and forecast future events. Using data from seven sites in the Illinois River Basin, we computed metrics focused on HAB conditions related to excess algal growth and hypoxia. Daily mean chlorophyll and dissolved oxygen (DO) concentrations, gross primary productivity (GPP), and net ecosystem productivity (NEP) rates, focused on water quality status, identifying the timing of the transition from a clear-water to an algal dominated state. Early warning indicators (EWIs), the first-order autoregressive process (Ar1) and standard deviation (SD) of chlorophyll concentrations, focused on future events, forecasting blooms. Metrics were compared to either literature-derived or statistical-based thresholds and were normalized by total number of daily samples for an exceedance rate. Exceedances of a daily mean chlorophyll concentration averaged 50 % across all sites using a 10 µg L−1 threshold but increasing the threshold to 50 μg L−1 reduced the average exceedance rate to 5 %. The average exceedance rate for GPP (∼8 g O2 m2d−1 threshold) was 15 %, similar to the daily amplitude DO concentration (∼3 mg L−1 threshold), but the average for NEP (0 g O2 m2 d−1 threshold) was higher, at 28 %. The number of days with at least 1 continuous DO concentration below the threshold of 5, 3, or 2 mg L−1, had basin wide exceedance rates of 9 %, 3 %, and 2 %, respectively. Thresholds for EWIs, Ar1 and SD, were exceeded at 5 of the 7 sites with high chlorophyll concentrations and GPP rates. The correlation between proxies for algal biomass (chlorophyll concentration) and productivity (GPP) was strongest for sites in the middle region of the basin, with R2 values between 0.54 and 0.74. Although, cyanotoxin concentrations are the most commonly used metrics by states to define an inland water HAB, there is a paucity of publicly available data. The wider availability of chlorophyll and oxygen data combined with the results from this study suggest that biomass and productivity state and event-based metrics may be a promising way to assess and predict the vulnerability of rivers to some of the deleterious effects of HABs at broad spatial scales.