Limnology and Oceanography: Methods

Quagga mussels (Dreissena rostriformis bugensis) are among the most impactful invaders in freshwaters of the Northern Hemisphere. As filter-feeders, they can reduce harmful algal blooms (HABs), but their effects are expected to be dependent on cyanobacteria species and water temperature. However, conclusive studies on these traits and their combination are lacking. Here, we combined laboratory experiments with an analysis of long-term data from a temperate shallow lake 10 years before and after quagga mussel invasion, respectively. We tested the hypotheses that quagga mussel filtration rates in the laboratory would 1) vary among common cyanobacteria species and 2) decrease above a critical temperature. Regarding the field data, we expected that 3) quagga mussels can reduce the summer biovolume of palatable cyanobacteria, but that 4) this effect disappears above a critical temperature. Our results support all four hypotheses. In laboratory experiments, Dolichospermum flos-aquae was classified as palatable to quagga mussels, while Aphanizomenon flos-aquae, Anabaenopsis elenkinii and Microcystis aeruginosa were less-palatable cyanobacteria. Filtration rates decreased above 28.9{degrees}C (CI: 27.6-30.2{degrees}C) with mussels dying at 32{degrees}C. Our long-term lake data show that cyanobacteria biovolumes were lower after quagga mussel invasion, but only below 27.7{degrees}C (CI: 26.9-28.4{degrees}C), confirming a critical thermal window for quagga mussel filtration. Global warming will therefore facilitate HABs by increasing the growth rates of cyanobacteria and reducing the filtration rates of quagga mussels above critical summer water temperatures, which are increasingly being reached in invaded lakes. This critical thermal window must be considered when making HAB predictions. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC="FIGDIR/small/707163v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@175851eorg.highwire.dtl.DTLVardef@76a481org.highwire.dtl.DTLVardef@12a3965org.highwire.dtl.DTLVardef@11e3e7d_HPS_FORMAT_FIGEXP M_FIG C_FIG

More diverse ecosystems on land and in the ocean are thought to be more productive, stable, and resistant to change, but these relationships are highly variable across systems and scales. Although the productivity-diversity relationship (PDR) has been extensively explored on land, there are limited in-water observations of the PDR in marine ecosystems. In this work, the relationship between phytoplankton diversity and carbon biomass (as a proxy for productivity) was examined using a global in situ dataset. The shape of this relationship was evaluated for three metrics of phytoplankton diversity: pigment concentrations modeled from hyperspectral remote sensing reflectance (Rrs({lambda})), pigment concentrations measured by high performance liquid chromatography (HPLC), and 18S rRNA gene sequences. While gene sequencing methods provide higher resolution taxonomic information about phytoplankton communities, remote sensing methods collect higher resolution spatiotemporal information on global scales. By comparing these methods (Rrs({lambda})-modeled pigments vs. measured HPLC pigments vs. 18S rRNA gene sequences), this work demonstrates the variability in the relationship between phytoplankton diversity and carbon biomass based on the method of assessing these parameters, and establishes a baseline for in situ observations that has the potential to be extended to global observations from NASAs Plankton Aerosol Cloud ocean Ecosystem (PACE) satellite.

1Diatoms are microscopic marine algae that are critical for global primary production, carbon sequestration, and fisheries productivity. However, select diatoms may form harmful algal blooms, which threaten marine ecosystems and the fisheries they sustain. Rapidly identifying harmful blooms is necessary to effectively manage marine resources, yet current identification methods are limited by expensive and labor-intensive in situ point sampling. Hyperspectral remote sensing enables scalable monitoring, but its ability to resolve taxonomic shifts within phytoplankton groups (e.g. diatoms) is largely unknown. To investigate this uncertainty, we cultured four dominant diatom genera from the California Current upwelling system, including this systems most abundant harmful algae, Pseudo-nitzschia. The hyperspectral absorption and backscatter of these taxa were measured and used to model spectral reflectances that remote sensing platforms (satellites/drones) might detect. Differences between fingerprints of these taxa were quantified using vector-based and statistical analyses. Mean spectral differences of 48% were observed between the most dominant diatom, Thalassiosira, and the most toxic diatom, Pseudo-nitzschia. Differences of approximately 30% were found between Pseudo-nitzschia and the second and third most abundant diatoms, Chaetoceros and Asterionellopsis. Successful identification of Pseudo-nitzschias reflectance fingerprint was driven by the presence of a unique feature around 560 nm. The distinct spectral fingerprint of Pseudo-nitzschia indicates that it can be distinguished from benign diatom blooms using hyperspectral remote sensing platforms.

Ocean Alkalinity Enhancement (OAE) is a marine carbon dioxide removal (mCDR) strategy that involves adding alkaline substances to surface waters to enhance CO2 uptake and storage. The dispersal of alkaline materials such as sodium hydroxide (NaOH) into seawater can cause rapid increases in pH and total alkalinity (TA) that substantially exceeds natural variability in marine environments. Such fluctuations may negatively affect marine life, especially small animals like copepods who cannot avoid OAE plumes and whose physiological processes could be disrupted by large and rapid shifts in seawater pH. To address knowledge gaps regarding potential biological impacts of OAE, we studied these effects in Calanus finmarchicus, a keystone copepod species in the Northwest Atlantic Ocean. We exposed C. finmarchicus from the late juvenile copepodite stages and adult females to NaOH-dosed seawater at pH 10.5 ([~]5,000 {micro}mol kg-1 TA) and pH 9.0 ([~]3,150 {micro}mol kg-1 TA) for durations that reflect expected short-term exposure times during field OAE deployments (pH 10.5: 1, 5, 10 minutes; pH 9.0: 1, 15, 30 minutes). None of the treatment combinations resulted in mortality immediately after the initial exposure. Individuals were monitored for survival for 72 hours post-exposure (hpe), and only one treatment group (juveniles exposed to pH 10.5 for 10 minutes) showed a significant reduction in final survival; no other pH-duration combination showed increased mortality. Effects on the ability to initiate an escape response were more substantial. Adult females treated with pH 10.5 for 5 or 10 minutes showed a significant reduction in escape response immediately after exposure. In contrast, juveniles showed no immediate change in escape response following exposure to pH 10.5 or pH 9.0, although juveniles exposed to pH 10.5 for 10 minutes exhibited reduced escape response at 24 hpe. Using microrespirometry, we measured oxygen consumption following a 10-minute exposure to pH 10.5 and detected no effect on routine metabolic rate immediately post-exposure or at 12 hpe. Overall, our results suggest that C. finmarchicus is relatively tolerant to short-term exposures to very high pH and alkalinity. Future work should prioritize longer-term exposure under more moderate ocean OAE conditions.

The Mississippi River (MR) is the largest source of freshwater and nutrients to the Gulf of Mexico (GoM), strongly influencing stratification, primary production, and plankton organization. The interaction between buoyant plume waters and denser shelf waters in the northern Gulf of Mexico (nGoM) generates sharp density gradients that can promote fine-scale biological aggregation. We investigated how hydrographic structure associated with the MR plume controls the vertical distribution of plankton during May 2017 using an integrated instrumentation suite that included an in situ digital holographic imaging system (HOLOCAM) coupled with CTD and optical sensors. Phytoplankton thin layers were repeatedly detected at plume-edge stations within or immediately above a compressed pycnocline formed by bottom-trapped saline wedges. These layers were 1.2-3.5 m thick and exhibited chlorophyll-a concentrations up to threefold higher than background levels. The assemblage was dominated by chain-forming diatoms, particularly Chaetoceros debilis and C. socialis, whose local abundance maxima coincided with chlorophyll peaks. In contrast, copepods, appendicularians, and other zooplankton were broadly distributed throughout the upper water column and rarely aggregated within the layers. Redundancy analysis indicated that chlorophyll concentration and stratification intensity were primary drivers of community structure across stations. Satellite imagery revealed rapid short-term variability in plume extent, helping explain differences in stratification and thin layer development among sampling days. Our results demonstrate that salt-wedge dynamics at the plume-shelf interface constitute a key physical mechanism governing transient phytoplankton thin layer formation in the nGoM, while zooplankton responses remain weakly coupled at the temporal scales resolved here.

Autonomous video-acoustic monitoring at the sea-floor can improve our understanding of poorly documented ecosystems and help interpret active or passive acoustic data, but it has been rarely carried out, particularly in the Arctic. This study deployed a video camera synchronized with a hydrophone, combined with red lights and other oceanographic instrumentation, on the bottom of a glacial fjord in Inglefield Bredning, northwest Greenland (to 260 m water depth). Through manual review and automatic analysis of high-frequency images (30 fps) and audios (96 kHz), the conditions and biodiversity near the sea-floor were quantified. The data revealed a highly turbulent environment with abundant suspended particles and fibers, with 88% of 478 detected organisms being Amphipoda, Copepoda, Hydrozoa, and Chaetognatha. Amongst the other observed animals were Decapoda, Liparidae, Pterotracheoidea, Ctenophora, and curious narwhals (Monodon monoceros). The number of marine snow particles was highly variable through time and could change up to twofold within several hours. The tide modulated the particle flow direction and speed. Overall, the results show that portable moorings with video recorders are an important tool for exploration of the Arctic seafloor.

O_LIPhytoplankton are the major primary producers in the Southern Ocean, participate in the global carbon cycle, nutrient cycles, and are at the base of the food-web. These polar ecosystems are unique in their extended periods of darkness in the winter. C_LIO_LIProlonged darkness has the potential to exert selection that affects the composition of diatom communities if there is differential survival of diatoms in the dark, variation in population growth rates in subsequent light periods, or both. C_LIO_LIWe tested whether prolonged darkness has the potential to exert within-species selection on a model polar diatom species by exposing 5 strains of the polar diatom Porosira glacialis to prolonged darkness at two different temperatures in the laboratory. We measured population survival in the dark, growth rate upon re-illumination, and between strain variability in these traits. C_LIO_LIWe found a pronounced decline in survival and growth rate with time spent in the dark, as well as important intraspecific variation in these. C_LIO_LIHigher temperature exacerbated declines in growth and survival. C_LIO_LIOur results show that the darkness of polar night can exert selection within diatom species, with implications for phytoplankton community composition and subsequent impacts on Southern Ocean biogeochemical cycles. C_LI

Using linear inverse ecosystem modeling as a data assimilation tool, we compare spawning grounds of Atlantic and Southern Bluefin Tuna (ABT and SBT, respectively) based on results from field campaigns in the Gulf of Mexico (GoM) and eastern Indian Ocean off northwest Australia (Argo Basin). Both regions are warm, stratified, low-nutrient waters dominated by cyanobacteria (Prochlorococcus). Despite these similarities, the Argo Basin is more productive, with [~]1.5X higher net primary production and nearly 2X higher production of top trophic levels in the model (tuna larvae, planktivorous fish, and predatory gelatinous zooplankton). Higher primary production in the Argo Basin is mainly driven by higher N2 fixation and storm mixing of new nutrients in the upper and lower euphotic zone, respectively. Increased ecosystem efficiency (secondary production of top trophic levels / primary production) results from differences in plankton food web organization. In the GoM, protistan zooplankton are the direct consumers of nearly all phytoplankton production. In contrast, higher rates of herbivory by crustaceans feeding on nanophytoplankton combines with a higher impact of appendicularians on cyanobacteria to convert plankton production into larval tuna prey more efficiently in the Argo Basin. Despite similarities in the proportions of phytoplankton production mediated by cyanobacteria and other picoplankton in both systems, food web pathways to larval tuna and other planktivorous fish are substantially shorter in the Argo Basin. Our results highlight the impact of distinct zooplankton ecological niches on ecosystem efficiency and suggest a need for better inclusion of plankton food-web structure in models simulating climate impacts on fisheries production. HIGHLIGHTSO_LIDeveloped food web models of tuna spawning habitat (Indian Ocean & Gulf of Mexico) C_LIO_LISpawning habitats in the Argo Basin and Gulf of Mexico (GoM) are both oligotrophic C_LIO_LIArgo Basin had higher net primary production in part as a result of nitrogen fixation C_LIO_LIArgo Basin had higher rates of direct herbivory by metazoan zooplankton C_LIO_LIThis resulted in greater ecosystem efficiency in the Argo Basin. C_LI

Since 1995, European fisheries of Pecten maximus have faced the presence of Pseudo-nitzschia species, which are able to produce the neurotoxin domoic acid responsible for Amnesic Shellfish Poisoning (ASP). As filter-feeders, scallops can accumulate and retain domoic acid much longer than most other bivalves, from months to years. When concentrations exceed the regulatory threshold, fisheries are closed leading to economic concern. Inter-individual variability increases the difficulty to predict the depuration dynamics. Quantifying the correlations between domoic acid depuration in P. maximus and individual physiological traits, particularly body size, could improve the understanding of contamination and depuration. We analysed toxin dynamics in organs and assessed the effects of body size and growth. This analysis was based on two datasets from an experimental and an in situ depuration monitoring of P. maximus exposed to a natural bloom of toxic P. australis. Results showed that the distribution of domoic acid shifted among organs between contamination and two months of depuration. Toxin concentrations correlated negatively with body size during contamination and after two months of depuration, but shifted to a positive correlation after 7 months of depuration. This suggested that smaller scallops both accumulate more domoic acid and depurate it more rapidly. Dilution by growth appeared to explain the inversion of the correlation between domoic acid and body size throughout depuration. These results yield useful information for modelling these mechanisms, thus providing valuable tools for scallop fishery management facing ASP. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=60 SRC="FIGDIR/small/708139v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@1fd317org.highwire.dtl.DTLVardef@15b9032org.highwire.dtl.DTLVardef@57dae8org.highwire.dtl.DTLVardef@1e4c7fc_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIExperimental and in situ datasets allowed to quantify DA proportion dynamics in organs in P. maximus C_LIO_LIDA concentration and body size are negatively correlated during contamination phase, but positively after a 7-month depuration C_LIO_LIConsidering dilution by growth is important for young scallops to assess DA depuration dynamics C_LIO_LIBoth depuration rate and dilution by growth need to be considered to model DA depuration over the whole scallop size range C_LI

We developed a model to predict surface water temperature across U.S. lakes using satellite remote sensing and in situ observations to enhance cyanobacterial harmful algal bloom (cyanoHAB) forecasting. The study focused on Sentinel-3 Ocean and Land Colour Instrument (OLCI) sensor resolved lakes. We developed random forest models using both Landsat-derived and in-situ-measured surface water temperature. Landsat models offered broad spatial and temporal coverage of all OLCI resolved lakes, but they were sensitive to cloud cover and required filtering to minimize error. In contrast, the in situ model represented fewer OLCI resolved lakes, but yielded lower mean absolute error and bias. The models predicted lake surface temperature across the entire calendar year, with best performance (RMSEapplied=1.11; biasapplied=0.01; MAEapplied=0.77) from the in situ model. This approach allowed for the continuous prediction of lake surface temperatures from 1.1 to 31.6 {degrees}C for unfrozen, open-water conditions critical for improving the accuracy of cyanoHAB forecasting. A key strength of this study was the use of an extensive dataset and model validation against in situ observations, which improved predictive accuracy throughout the year across all seasons. The predictive model offers a water resource tool for management, ecosystem protection, and public health.

Environmental DNA (eDNA) metabarcoding is a key tool in biodiversity monitoring due to its high-throughput, non-destructive nature. While short-read (SR) sequencing platforms such as Illumina Miseq have been routinely used in environmental monitoring, their limited read lengths (less than 600 bp) constrain the depth of taxonomic assignment, particularly for complex microbial eukaryotes like protists. Conversely, long-read (LR) sequencing technologies like Oxford Nanopore Technologies (ONT) offer promising alternatives but remain underutilized for studying protist communities. We conducted a comparative study of SR versus LR metabarcoding of protist communities along a coastal-offshore gradient in the Belgian part of the North Sea. Using amplicons targeting the V4 region (SR; 577 bp) and the V4-V5 region (LR; 745 bp) of the 18S rRNA gene, we compared diversity patterns, taxonomic assignment, and community composition between approaches. We observed general congruence in community composition at higher taxonomic levels, but under the applied workflows, LR metabarcoding yielded a greater depth of taxonomic annotation at lower taxonomic ranks. Notably, dinoflagellates were less overrepresented in LR data, and a unique detection of potential nuisance taxa (e.g., Bellerochea), and ecologically important genera such as haptophytes (e.g., Gephyrocapsa) was achieved. These results highlight the potential of LR metabarcoding to complement SR approaches by providing increased taxonomic annotation depth and ecological insights. Although both methods targeted only partial regions of the 18S rRNA gene, LR metabarcoding yielded a greater depth of taxonomic assignment under the applied workflows. As next-generation sequencing technologies continue to evolve, our research provides valuable insights for selecting optimal strategies in routine plankton monitoring and biodiversity assessment programs.

European tidal flats that host non-native Magallana gigas reefs contribute to several ecosystem functions. Among others, they provide a habitat for a large variety of associated fauna. However, we often lack detailed information about any trophic interactions of the associated macrozoobenthos species with the oysters, and about their role in the carbon and nutrient cycle. Therefore, we performed ex-situ pulse-chase tracer experiments in the Eastern Scheldt (Southwest Dutch Delta, Netherlands) in summer and autumn 2020, where we fed M. gigas and their associated fauna 13C- and 15N-enriched bacterioplankton while the macrozoobenthos was incubated in water containing deuterium oxide (2H2O; enrichment: 1 - 2.5%). The aim was (1) to assess differences in short-term (<12h) processing of bacterioplankton in summer and autumn, and (2) to study differences in 2H incorporation - a proxy for metabolic activity - of M. gigas and its associated fauna in summer and autumn. In summer, all macrozoobenthos species combined consumed significantly less bacterioplankton-derived 13C and 15N than in autumn, while all macrozoobenthos species combined incorporated comparable amounts of 2H into their tissue in both seasons. Most bacterioplankton-derived 13C and 15N was taken up by sponges (Halichondria panicea, Hymeniacidon perlevis), crabs (Carcinus maenas, Eriocheir sinensis, Rhithropanopeus harrisii), and limpets (Crepidula fornicata). Most 2H was taken up by crabs (C. maenas, E. sinensis), sponges (H. perlevis), and snails (Littorina littorea), implying that these species were the most metabolically active ones. Overall, the metabolic activity was linked to feeding activity in summer 2020, whereas in autumn 2020, the link was weaker and the most metabolically active species were not necessarily the species that had incorporated most 13C and/or 15N.

Cyanobacterial colonies often exploit their buoyancy and large size to float upwards rapidly and form dense surface blooms, which can degrade water quality, threaten ecosystems and public health, and impose substantial economic costs. Yet, how the morphology of cyanobacterial colonies controls their vertical velocity remains poorly understood. We conducted detailed three-dimensional morphological characterization of colonies of the cyanobacterium Microcystis in lake samples at the single-colony level and performed controlled flotation experiments in stratified flows. Using particle tracking in a vertical density gradient, we separately quantified the contributions of colony shape and buoyant density at the level of individual colonies. Our results show that the shape factor in Stokes law varies systematically with colony size. Consequently, the vertical velocity of colonies does not scale with the square of colony size but only with a power of 1.13, as larger colonies have a more irregular shape and therefore experience enhanced drag. We therefore correct the commonly used Stokes law to account for the size-dependent change in the shape factor. Interestingly, implementation of this power law relationship in a vertical migration model shows widespread chaotic dynamics in the migration trajectories of Microcystis colonies. These results highlight the importance of morphological plasticity in cyanobacterial colonies and can inform predictive models and hydrodynamic control strategies for toxic blooms. Our methodology to simultaneously determine the density, shape factor and velocity is broadly applicable to suspended aggregates with complex shapes in freshwater and marine systems.

Biologists aim to predict where species will survive and thrive as the planet warms. To do so, we often rely on data-hungry species distribution models (SDMs) that use associations between species occurrences and environmental predictors to capture the realised niche. An alternative basis for predictions is to experimentally quantify the effect of environmental drivers on performance, which captures the fundamental niche. We presently do not know which of these approaches represents a better path towards accurate forecasts. SDMs may depend too strongly on present-day environmental covariation, which will change in the future. In contrast, a major shortcoming of experiments is that they ignore most environmental drivers to focus on one or two. Quantifying how well fundamental and realised niches agree today would help establish how useful both SDMs and experiments are likely to be. We therefore compared both niches in 39 relatively common marine phytoplankton species. The temperature-dependence of population growth rate was characterised with a thermal performance curve model applied to lab experimental data, and the temperature-dependence of species occurrence probability estimated with SDMs applied to a global compilation of marine presence records. We found a fairly strong, near 1:1 relationship between measures of thermal niche centre: the median growth temperature in the lab and the median occurrence temperature in the field (R2 = 0.49). We also found a modest positive relationship between measures of thermal niche width, the growth niche width and the occurrence niche width (R2 = 0.24). This agreement should increase our confidence in environmental preferences inferred with SDMs. It also suggests that simple experiments can reliably constrain species ranges and help forecast range shifts. This has important implications for forecasting community composition and ecosystem processes, as we ought to be able to predict range shifts in biogeochemically-important taxa such as diatoms and nitrogen-fixing cyanobacteria.

Seamounts are prominent deep-ocean features that strongly influence geological processes, ocean circulation, and benthic biodiversity. Despite their importance, most seamounts remain unmapped and poorly characterized, particularly in the southeast Pacific Ocean, a region recognized for high marine endemism and ecological isolation. In this study, we present a quantitative habitat characterization of a previously undocumented seamount, informally named Solito Seamount, located between the Nazca-Desventuradas Marine Park and the Juan Fernandez Archipelago. High-resolution multibeam bathymetry and backscatter intensity data were integrated with in situ observations from two remotely operated vehicle (ROV) dives (SO643 and SO645) to investigate how geomorphology and substrate distribution influence benthic community patterns. An automated and hierarchical quantitative mapping framework incorporating objective terrain analysis and multivariate statistical techniques, including principal component analysis and clustering, was applied to delineate five distinct megahabitat types: flat, basal slope, valley, ridge slope, and ridge crest. ROV video transects traversing these megahabitats revealed five associated substrate type forming macrohabitats: bedrock, bedrock with sediment veneer, sediment-rock transition, sediment, and coral rubble. Outputs were used to investigate how environmental heterogeneity structures megafaunal assemblages of Solito Seamount. Multivariate analysis revealed a combined effect of megahabitat type and substrate type on benthic megafaunal assemblages across the depth gradient. These compositional dissimilarities were primarily driven by habitat-forming taxa. In the deeper dive (SO643), a broad suite of taxa contributed to dissimilarities, and assemblages were primarily organised by megahabitat. The ridge crest hosted a distinct reef-building scleractinian community, whereas the ridge slope hosted mixed antipatharian, gorgonian and actiniarian assemblages. In contrast, the shallower dive exhibited simpler patterns with few taxa driving dissimilarities. Substrate effects were most pronounced with coral rubble forming a distinct habitat characterised by sponges (Stelletta sp.). Pronounced biological differences between dives may also represent depth-dependent structuring resulting from differences in oxygen regimes associated with water masses, underscoring the role of oceanographic forcing. This study provides the first quantitative habitat map of this previously undocumented seamount, delivering essential baseline information for this largely unexplored region of the southeast Pacific. The integrated multi-scale geophysical and biological approach presented here offers a robust framework for advancing seamount ecosystem understanding and supporting future biodiversity assessments and conservation planning.

For sustainable algal biomass cultivation, we need substantial improvement in annualized productivity by reducing the frequency of crop failure and improved growth in open raceway pond systems. In this study, high-performing strains were identified and optimized for biomass productivity. We utilized next-generation sequencing methods to quantify the ecological features of open raceway systems cultivated at in Arizona. We utilized data from several months of cultivation runs to construct a rich time-series of the ecology dynamics using amplicon sequencing and used custom anomaly detection, "PondSentry", for the early prediction of pond crashes. PondSentry uses tensor decomposition of higher-order joint moments to detect incipient anomalies in multivariate data and displays significant improvements from standard knowledge-based anomaly detection methods. The PondSentry strategy identifies signs of deteriorating pond health at an average of three days before an actual crash event, with rank order of the ecological features plausible for crop failures driven by organisms such as Amoeboaphelidium occidentale FD01. These findings are independently confirmed with PCR and microscopy studies at an Arizona cultivation site. PondSentrys time-series-based anomaly detection of crashes provides a suitable monitoring strategy for eukaryotic crash agents in unialgal culture. The early warnings can be used to time interventions or harvests to prevent biomass loss. The PondSentry strategy strengthens the role of data science and data-driven methods in algal cultivation and can increase the feasibility of algal-biomass based products.

Marine non-cyanobacterial diazotrophs (NCDs) are recognized as globally distributed, however, few representatives have been isolated in pure cultures. As a result, understanding the physiology, growth rate, substrate preference and dinitrogen (N2) fixation capabilities proves difficult. Thalassolituus haligoni. sp. nov., BB40 was isolated from a fjord-like inlet within Kjipuktuk (Halifax), Nova Scotia. The fully sequenced genome displayed all necessary genes required for N2 fixation, and various carbon uptake pathways. The gram-negative flagellated rod shape bacterium displayed significantly higher growth rates in medium amended with nitrate (NO3-) or ammonia (NH3), compared to dissolved N2, as the sole nitrogen source. Biological N2 fixation rates were detectable across all conditions, measuring a range from 9.34 x 10-6 to 1.4 x 10-1 fmol N cell-1 day-1. Growth of the isolate was successful between 4 {degrees}C up to 35 {degrees}C, with a Topt of 20 {degrees}C for N2, and between 27 - 30 {degrees}C for fixed nitrogen (NO3- and NH3). The closest relatives to T. haligoni, were found to be the uncultured Arc-gamma-03 (99% average nucleotide identity (ANI)) and Oceanobacter antarcticus (81% ANI). T. haligoni also displays versatile capabilities for growth on various carbon, and nitrogen sources, and antibiotics. Collectively this study provides an in-depth physiological assessment of an Oceanospirillales diazotrophic species which we presently have limited knowledge of.

Marine subseafloor sediments host extensive microbial communities that drive global biogeochemical processes. Despite its proximity to one of the most densely populated and economically important coastal regions in the world, the sub benthic ecology of the San Pedro Channel, the waterway separating Los Angeles County from Santa Catalina Island, remains largely uncharacterized. To establish the foundational knowledge required for future impact assessment studies, we initiated a sediment coring survey that generated a water and sediment depth standardized transect across the sloping flanks of the San Pedro Basin. Here, we describe the early development of an integrated subseafloor microbiological catalogue for this region of intense maritime activity incorporating molecular ecology, microbial isolation and cultivation, and physiological assays. This initial effort is designed not as a direct comparison between basin flanks, but as a baseline assessment that captures ecological and microbiological variation across paired sides matched in water column depth and sediment depth beneath seafloor. Accordingly, we provide a cross channel coordinated dataset of subseafloor microbial communities and cultivated representatives from San Pedro Basin sediment, offering a critical starting point for understanding natural variability and for detecting potential signatures of environmental or anthropogenic disturbance. Ultimately, this baseline will support long{square}term monitoring efforts and supply a curated collection of isolates for future experimental microbiology and comparative genomics research.

AbstractThe ability to accurately assess ecosystem C budgets across scales from individual sites to continents is essential for C accounting, management, and ultimately mitigating climate change. State data assimilation (SDA) provides a framework for harmonizing observations with models, while robustly accounting for and reducing multiple sources of uncertainty. In this study, we employed a hybrid SDA framework that combines process-based terrestrial biosphere modeling, hierarchical Bayesian inference, and machine learning to harmonize bottom-up and remotely-sensed data streams for 8,000 pre-selected 1km2 locations across North America within a hybrid structure. Combining bottom-up soils data (SoilGrids) with spectral (MODIS and Landsat) and microwave (SMAP) remote sensing helps constrain the major C and water stocks through space and time. Machine learning is used both to identify and correct systematic errors in the process model (SIPNET) and to interpolate the pre-selected locations onto a 1km grid, making it computationally feasible to generate annual ensemble maps of the North American carbon budget. Furthermore, the uncertainties for each variable were reduced compared to those from observations or models alone. Spatiotemporal analysis showed a slight decrease in aboveground biomass (AGB) across the western US, a loss of leaf area across the boreal, and a slight greening of the Alaskan tundra. The uncertainty trends suggest a significant reduction in the uncertainty about soil organic carbon (SOC), the largest C reservoir. Validation results show that we accurately estimate C pools, compared to the assimilated data streams and held-out observations of AGB from GEDI, ICESat-2, and the US FIA, and SOC from the ISCN network. Our ML-debiasing algorithm further improved the accuracy of major C pools (AGB, SOC). In general, our continental SDA framework will facilitate global C MRV (monitoring, reporting, and verification) by providing accurate and precise C-cycle estimates, along with their corresponding spatiotemporal uncertainties.

Environmental DNA (eDNA) provides a powerful non-invasive tool for monitoring freshwater mussel assemblages, yet detection probabilities can be influenced by reproductive behaviors, seasonal vertical migration, and hydrological conditions. This study assessed eDNA detection from April through October across two diverse mussel beds in Ohio, encompassing species with both tachytictic (short-term brooders) and bradytictic (long-term brooders) reproductive strategies. Mussel DNA was consistently detected across seasons, with detection patterns generally aligning with species observed through a visual tactile survey. Overall, the eDNA sequence abundance was positively correlated with tactile mussel counts, however congruence between the two surveys was strongest during low discharge and when the surveys occurred in close temporal proximity to one another. This study finds that eDNA sampling for freshwater mussels performs adequately within the currently prescribed survey window for visual surveys. However, seasonal factors such as endobenthic burial behavior and high discharge events may have reduced detection efficiency, particularly in Killbuck Creek, where species richness was lowest during periods of high flow in early spring. Therefore, decisions made regarding the timing of eDNA surveys should consider local environmental conditions (e.g., temperature and flow) to achieve optimal results.