Limnology and Oceanography: Methods

The advancement in deep learning techniques has made Convolutional Neural Networks (CNNs) a powerful tool for the fully automated classification of zooplankton images. In this study, we systematically investigate how network selection, colour information and differences in imaging instruments affect the classification of zooplankton images by comparing multiple state-of-the-art CNNs on images of zooplankton and marine snow from the in situ Continuous Particle Imaging and Classification Sensor (CPICS), Video Plankton Recorder (VPR), In Situ Ichtyoplankton Imaging System (ISIIS), and the on-board Plankton Imager (Pi-10). With differences between models of 7.8 to 19% in F1-score, we find that model selection strongly affects the classification performance, with EfficientNetV2S showing the most reliable overall performance. Moreover, differences between model architectures are largest for the least abundant classes (<100 labeled images), which implies that when these are present, careful model selection is most beneficial. The high image quality of the Pi-10 strongly increases the performance for the least abundant classes compared to the other instruments. In addition, we find a significant correlation (r = 0.597) between ImageNet the performance and F1-score on zooplankton images, which implies that more generally, a model that performs well on ImageNet will perform well for zooplankton classification. Colour information increases the F1-score of the best performing classifier with 2.8%, but provides a stronger benefit (25% F1-score) for classes with <100 images. The overall performance increase of colour information is less than expected and questions the advantage of recording colour information for zooplankton.

Here, oyster larval developmental abnormalities within a New England hatchery were linked to a common UV sterilization technique that has been used for over 20 years. Because of the known link between phytoplankton oxylipins and egg mortality in copepods, we hypothesized that UV pretreatment of seawater results in the production of oxylipins that inhibit larval digestion of microalgae. We used lipidomics to observe changes in the organic compounds dissolved in estuarine seawater when filtered and when filtered and pretreated with UV. UV treatment resulted in an increase in the relative abundance of oxylipins associated with cyanobacteria, fungi, and macroalgae in 2020, whereas oxylipins typically produced by diatoms were more abundant in the UV treatments from 2021. Oxylipin concentrations were higher in 2020, when the hatchery reported the most severe problems with larval development. Removing the UV step allowed continued larval production in both years. However, the lack of UV sterilization led to an unidentified bacterial pathogen in 2021, which nearly decimated the overall seasonal production of oyster seed. To follow up in a more controlled environment, the larvae were exposed to exogenous oxidized lipids, which resulted in the same digestive syndrome and histological symptoms as the endogenous suite of compounds produced by UV. Further investigation of the lipidomes revealed that oxylipins were only one class of potentially harmful compounds linked to UV sterilization, and the dissolved concentrations of secondary metabolites associated with higher plants, a wide range of pharmaceuticals, and anthropogenic organic pollutants also increased under UV light. Future efforts will explore the sources of these compounds, the mechanisms by which they inhibit oysters, and whether this is an emerging environmental problem for other ecosystems and shellfish hatcheries. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=137 SRC="FIGDIR/small/738347v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@43d06corg.highwire.dtl.DTLVardef@2894daorg.highwire.dtl.DTLVardef@449e59org.highwire.dtl.DTLVardef@f81983_HPS_FORMAT_FIGEXP M_FIG C_FIG

Sinking marine particles is a key process regulating carbon export through the biological carbon pump, yet direct measurements of sinking dynamics remain limited in many coastal environments. One barrier is that most existing approaches require expensive instrumentation and large research platforms. Here, we present a low-cost, modular method for concentrating fast-sinking particles and measuring their individual sinking velocities under controlled conditions. This combines large settling tanks (110 L) for field-based particle fractionation with a video-based tracking system that quantifies the sinking behavior of natural marine particles. The particle sinking speed chamber is surrounded on three sides by a temperature-controlled water chamber, minimizing the problem of advection during measurements. The post-processing Python script delivers sinking velocity, particle size, circularity, and RGB-based properties for large numbers of particles. The method accuracy was validated using reference beads with known theoretical sinking velocities derived from Stokes law. Field deployments in the Baltic Sea demonstrated successful enrichment of fast-sinking particles and stable operation from both a research vessel and a small boat. Compared to existing methods, the approach substantially reduces logistical and financial barriers while maintaining particle-resolved measurements and compatibility with complementary biogeochemical analyses. This enables a broader observational coverage of sinking particle processes across environments that are currently underrepresented in carbon export studies.

The morphology of cyanobacterial colonies plays a key role in harmful cyanobacterial blooms, with implications for their vertical migration, resistance against grazing, and light availability. In this study, we introduce the use of Optical Coherence Tomography (OCT) to investigate the three-dimensional morphology of cyanobacterial colonies. The technique enables non-invasive 3D imaging of colonies up to several millimeters in size, providing access to detailed mesoscale morphological features. Gas vesicles inside cells were shown to strongly improve image quality. We describe the sample preparation and image acquisition protocol, as well as an image processing pipeline that extracts mesoscale morphological features and provides a volumetric visualization of colonies. The method was tested for representative colonies of different cyanobacterial species while a dataset of volumetric images and measured mesoscale features was acquired for natural colonies of Microcystis. We demonstrate the utility of 3D imaging by quantifying the effects of irregular colony morphologies on their flotation velocity and the light availability within colonies. We anticipate OCT to become a key imaging technique to monitor populations of cyanobacterial colonies and investigate colony formation, with potential extensions to other colonial and aggregated organisms in freshwater and marine environments.

Artificial intelligence (AI)-based image analysis can efficiently estimate fish length, but differences in devices, imaging conditions, operators, and AI models limit comparability among surveys. We propose a standardization framework that estimates a bin-specific error matrix from paired reference measurements and AI-derived lengths and applies it to standardize (correct) AI-derived length-frequency distributions. The Richardson-Lucy expectation-maximization algorithm was used, with the number of iterations selected via cross-validation. Simulations based on empirical length-frequency data from 110 species showed that standardization reduced relative bias and distributional discrepancy; median relative-bias and root mean square error ratios were below 1, and the performance was more affected by the amount of paired data than by the number of cross-validation folds. In real data from 957 Japanese jack mackerel, standardized AI-derived distributions approached human-observer histograms, although discrepancies remained in the range of 160-230 mm. The proposed framework provides a practical approach for improving the comparability of image-derived length-frequency data using paired calibration data, without retraining the underlying AI model.

Offshore industry still largely relies on traditional approaches for regulatory compliance to environmental impact on the water column. Implementing environmental DNA (eDNA) workflow can offer several advantages, but early stages such as sampling and conservation of the samples require standardization and simplification before they can be routinely applied in offshore monitoring programs. In this study, we assessed the effect of several filter types (Durapore disc, Sterivex capsule and Wattera high-capacity capsule; all with 0.22 {micro}m pore size) allowing for different volume of filtration used for sampling eDNA. We also evaluated the effect of 25 days conservation of unfiltered water samples with different preservative solutions (Benzalkonium chloride -BAC, Longmires solution LONGI and a modified Longmires solution without SDS, LNoSDS) as a viable option when immediate filtration and cold storage are not possible. For downstream eDNA evaluation of filter types and preservation, we used quantitative digital PCR on selected target DNA and metabarcoding for qualitative assessment of marine prokaryotic and eukaryotic communities. Overall, filter choice had relatively less effects on quantitative and qualitative information from eDNA compared with water preservation. Sterivex and Durapore were better filter choices for biodiversity assessment. While the Wattera filter allowed processing of larger water volumes and improved quantification of metazoan DNA, handling and processing were more challenging. For water conservation, LNoSDS was the best option. Chemical agents of LONGI and BAC may provide favourable substrates for some tolerant bacterial strains, altering the microbial community composition, with consequences for the overall qualitative evaluation of conserved eDNA. For targeted metazoan eDNA, however, chemical preservation showed clear benefits. This research highlights key considerations and viable options for eDNA sampling and simple preservation workflows without cold storage for implementation in offshore water column monitoring. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/733101v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@22a175org.highwire.dtl.DTLVardef@1960864org.highwire.dtl.DTLVardef@1010f49org.highwire.dtl.DTLVardef@92a2f6_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LINeed for standardization of eDNA workflow for offshore water column monitoring C_LIO_LIImportance of eDNA sampling (filters) and eDNA conservation (preservatives) C_LIO_LIFilter choice does not affect drastically the dominant eDNA communities C_LIO_LIConservation outside cold storage challenging for eDNA-based biodiversity evaluation C_LIO_LIViable options: Sterivex filter for sampling; Longmires (no SDS) for conservation C_LI

Over the past decades, metabarcoding and automated cell-counting approaches have greatly advanced our understanding of marine microbial communities. Metabarcoding provides high taxonomic resolution and comprehensive community characterization, typically as relative gene abundances, whereas flow cytometry provides absolute cell abundances but lower taxonomic coverage. Here, we assess whether concurrent flow-cytometry observations can calibrate metabarcoding data to derive absolute gene abundances across four basin-scale Atlantic and Pacific Ocean transects. We first show that flow-cytometry-anchored calibration reproduces absolute abundances of Prochlorococcus and Synechococcus with performance comparable (R2 = 0.87) to internal DNA standard-based quantification. For datasets lacking internal standards, the choice of cytometric "anchor" species introduces systematic offsets in absolute abundance estimates, although spatial patterns remain robust. These offsets may reflect underestimation of cytometric counts or variation in rRNA gene copy numbers among actively dividing cells. We therefore recommend the use of multiple anchors where possible to diagnose systematic uncertainty. Applying this framework, we derive absolute gene concentrations for diverse plankton taxa from compositional metabarcoding data. For taxa with known rRNA gene copy numbers, calibration further enables estimation of absolute cell concentrations. We also resolve ecotype-level absolute abundances of Prochlorococcus along a longitudinal temperature gradient, revealing ecological patterns not apparent from compositional or cytometric data alone. Our results demonstrate that calibrated metabarcoding provides a practical quantitative bridge between molecular and cytometric observations, yielding high taxonomic resolution together with absolute gene concentrations and quantified uncertainties.

Passive sampling is the deployment of a collection material in the environment to continuously capture environmental DNA (eDNA) over time, offering the potential to integrate biodiversity signals while reducing the need for repeated active water collection. However, the mechanisms governing eDNA capture and retention on passive samplers remain poorly understood, limiting the interpretation of passive eDNA signals and their broader application. Here, we investigated the mechanistic performance of glass fibre passive samplers using controlled mesocosm experiments with three invasive freshwater bivalves: zebra mussels (Dreissena polymorpha), quagga mussels (Dreissena bugensis), and Asian clams (Corbicula fluminea). Specifically, we quantified eDNA accumulation dynamics, evaluated the contribution of different eDNA states, tested the persistence of captured eDNA, and compared passive sampler signals with conventional active sampling. Passive samplers rapidly accumulated target eDNA within hours of deployment, after which concentrations either plateaued or continued to increase depending on species. Sequential transfer of passive samplers between mesocosms containing different species showed that previously captured eDNA declined while new target eDNA accumulated to concentrations comparable to freshly deployed samplers, demonstrating continual turnover rather than permanent retention. Dissolved eDNA showed little evidence of accumulation beyond the concentration retained in the pore water within the membrane, suggesting that it is unlikely to be the dominant contributor to long-term passive sampler signals. Instead, the observed variability among replicate samplers, together with the physical properties of glass fibre membranes, suggests that membrane-bound and particulate eDNA are the primary contributors to passive eDNA capture. Collectively, these findings support a model in which glass fibre passive sampler signals reflect a dynamic equilibrium between ongoing eDNA capture and concurrent loss processes rather than cumulative accumulation over time. This mechanistic framework provides a foundation for interpreting passive eDNA data and informs the future development of passive sampling materials, deployment strategies, and biodiversity monitoring applications.

Knowledge regarding variation in habitat use among individuals is crucial for understanding population dynamics and for management and conservation measures. This is especially important for diadromous fishes that shift between habitats, being affected by external pressures and environmental change in different habitats over ontogeny. Herer, we assessed individual variation in habitat use of European eel along a salinity gradient, ranging from fully marine to freshwater in northern Europe, using otolith microchemistry data from >3600 eel together with established time-series segmentation and clustering methods. We show that eel display high degree of individual variation in habitat use. Assigned life-histories included coastal resident, freshwater resident, and coastal and freshwater habitat shifting individuals. Coastal resident eels were observed in a large range of salinities. Given the widespread occurrence of migration barriers in freshwater, it is unknown whether the coastal resident eel preferred that habitat, or if it was the only available habitat for them. Our findings nonetheless highlight the need to include coastal habitats when assessing population development and silver eel production of the critically endangered European eel.

Many dinoflagellates are mixotrophic and regulate their vertical position to navigate dynamic gradients in light, nutrients, and prey. Here, it is shown that the obligate kleptoplastidic mixotroph, Dinophysis acuminata, transitions from diel vertical migration to formation of a stationary, sub-surface thin layer in response to prolonged prey deprivation. An inshore bloom within a salt marsh kettle pond was recorded through continuous in-situ imaging, automated oxygen and fluorescence depth profiling, and targeted water chemistry measurements. During the blooms initial development, D. acuminata cells were photosynthetically active and divided vegetatively while vertically migrating. As photosynthesis and growth slowed, vertical migration ceased and cells formed a stable thin layer that promoted conditions for local acidification and nitrogen remineralization. Surface avoidance by the thin layer drove selective retention of cells within the relatively deep kettle hole. Together, these findings illustrate linkage of metabolic state and swimming behavior in D. acuminata and show how swimming behavior can drive development of toxic blooms within inshore systems. They also illustrate how D. acuminata and other eurytolerant bloom-forming species can exploit and shape physicochemical gradients associated with coastal eutrophication.

Inland waters in the Northern Hemisphere are experiencing increased annual runoff due to higher overall precipitation as well as intensified short-term events such as heavy rainfall, floods and storms. These events affect the total loading and variability of inputs of allochthonous, coloured dissolved organic matter (cDOM) and inorganic nutrients into lakes. Previous studies have shown that increased total cDOM and inorganic nutrient loads affect phytoplankton biomass and metabolic rates, but it is unknown how the effects of different cDOM and nutrient pulse scenarios are modified by spatial and seasonal differences in lake characteristics. Here, we conducted a coordinated, standardized mesocosm experiment across three lakes with different ambient cDOM and nutrient concentrations. In two of these lakes, the experiment was implemented in two seasons. The same total amounts of cDOM, nitrate and phosphate were added to all mesocosms, but in pulses that differed in intensity and frequency. We found that pulse intensity and frequency affected chlorophyll a and phycocyanin concentrations and metabolic rates, i.e. gross primary production and respiration, differently. Specifically, more pronounced effects were found in response to the extreme pulse scenario compared to those with more frequent, smaller pulse additions. Furthermore, the effects were mainly temporary and varied more among lakes than between seasons. The clearest differences between the extreme and more gradual runoff scenarios were found in the lake with the lowest background cDOM and nitrate concentrations, likely because lower light limitation and possibly stronger initial N-limitation caused a faster response to the nutrient addition. Our results highlight that both antecedent lake conditions and characteristics of runoff events can affect phytoplankton biomass and metabolic rates and that comparative experimental approaches are needed to reveal the complexity of the responses.

John Raven pioneered the field of algae ecophysiology, advancing our understanding of cellular resource economics, carbon acquisition, and energy allocation. His work laid the foundation for investigating integrative physiology, linking growth-survival trade-offs across diverse environments. The sea ice habitat provides an excellent framework to continue the research John championed. With steep temperature-salinity gradients, algae survival requires a shift in physiology that we are only beginning to understand. We developed two small scale, reproducible icecosms to investigate physiological changes associated with incorporation into sea ice and survival potential post-melt. Fragilariopsis cylindrus and Nitzschia frigida, known for their association with the ice environment, and Porosira glacialis, known for its association with the ice edge, were used to mechanistically link physical properties with algal physiology and post-melt survival. We observe incorporation into the ice of F. cylindrus and N. frigida alongside vertical photophysiological profiles of F. cylindrus revealing inhospitable conditions in the top compared to the bottom layers of ice. N. frigida and P. glacialis remain viable within the ice and retain the capacity to seed populations following melt. Our results establish icecosms as experimental framework to investigate ecophysiological responses of sea ice algae and provide a foundation toward ecological and evolutionary questions.

Floating debris in the ocean recruits microbes and marine invertebrates to its surface, resulting in rafting communities. As biodegradable plastics increase in prevalence as alternatives to petroleum-based plastics, their properties may impact the dynamics of rafting communities by influencing the composition of bacterial biofilms and attached invertebrates. We compared attached biofouling communities of bacteria and marine invertebrates on biodegradable surfaces and nonbiodegradable petroleum-based plastics and naturally occurring substrata. Six surface types: polypropylene plastic (PP), polystyrene (PS), polylactic acid plastic (PLA), polyhydroxyalkanoates plastic (PHA), maple wood veneer, and propagules of the mangrove Rhizophora mangle, were examined to determine if plastic type affected biofilm composition on the surfaces and their degradation patterns. Biofilm analyses were conducted at twelve weeks, and degradation analyses were conducted at twenty-two weeks of immersion. Using digital image analysis, 16S rRNA sequencing, and metagenomic analyses, we found that microbial biofilms, marine invertebrate inhabitants, and degradation patterns differed across the various substrate types tested. Microbial communities on PLA were more similar to those on the two non-biodegradable plastics, while communities on PLA were more like those on the natural substrata. The biodegradable PLA showed signs of degradation within 22 weeks of immersion, suggesting that biodegradable plastics behave variably in the natural environment. Results of this study bring forth the importance of designing biodegradable plastics with careful consideration of the environmental conditions in which they are likely to persist.

Environmental DNA (eDNA) has the potential to be a powerful tool in blue carbon science for characterizing and quantifying the contribution of marine macrophytes; but its complex, dynamic relationship with bulk biomass is poorly understood. Here, we used eDNA to examine the degradation dynamics of sugar kelp (Saccharina latissima) in muddy, anaerobic marine sediment. This involved three 16-week incubations; with additions of lyophilized sugar kelp alone, a mix of lyophilized marine macrophytes including sugar kelp, and sugar kelp holdfasts buried in sediment. We used species-specific digital polymerase chain reaction assays for mitochondrial, chloroplast and nuclear markers, and metabarcoding for the 16S and 18S ribosomal RNA genes. In the former two incubations, all sugar kelp eDNA markers showed rapid log exponential declines (up to 98-99%) to asymptotes greater than the unamended controls, even as part of a more complex mix of macrophytes. In contrast, for the buried kelp holdfasts, sugar kelp eDNA increased to an asymptote (by up to [~]15X), which may be reflective of the different nature of added biomass. Overall, we demonstrate substantial preservation of environmental DNA and total organic carbon under anaerobic conditions, and the potential to use environmental DNA to quantify biomass in a blue carbon context.

Flow imaging microscopy (FIM) is an important technology for high-throughput characterization of microscopic particles and microorganisms. However, conventional FIM relies on single-plane imaging (SPI), resulting in out-of-focus particles, reduced measurement precision, and incomplete characterization of irregularly shaped objects extending along the z-axis. To address these limitations, a volumetric flow imaging (VFI) framework was developed and implemented on the portable ARTiMiS platform. This approach captures multiple frames along the z-axis and extracts the highest fidelity image for each particle, which can also be used for single image generation with all particles in focus (i.e., all in focus image) and for three-dimensional reconstruction of irregularly shaped objects. Benchmarking VFI with microspheres, live cells (Chlorella vulgaris), and filamentous cyanobacteria demonstrated increased fraction of particles in focus, reduced variability in particle size measurement, and increased resolvability of elongated particles in comparison to conventional SPI on commercially available FIM technologies. For C. vulgaris, VFI-derived size distributions closely matched curated FlowCam measurements without requiring post-processing to exclude out-of-focus particles. All-in-focus image reconstruction enabled simultaneous visualization of particles distributed across multiple depths and consistently resolved a greater proportion of filamentous structures as compared to SPI. For Aphanizomenon sp., Dolichospermum sp., and Planktothrix agardhii, the SPI approach captured only 84%, 61%, and 58%, respectively, of the total filament length resolved by AIF reconstruction. Beyond image-based characterization, VFI enabled estimation of dynamic particle properties such as sinking velocity and mass density. Application of this framework to C. vulgaris cultures revealed distinct mass-density trajectories under nitrogen-replete and nitrogen-deplete conditions, with cell mass density increasing over time under nitrogen-replete conditions and decreasing under nitrogen deprivation. Collectively, these results establish VFI as a next-generation framework for FIM that expands its analytical capabilities beyond conventional morphometric characterization and provides new opportunities for single-cell-enabled environmental monitoring and biomanufacturing.

Quantitative stable isotope probing (qSIP) allows researchers to calculate taxon-specific carbon incorporation from sequencing of natural microbial communities, which can be used as a proxy for metabolic activity rates and subsequently as an input for biogeochemical modeling. While qSIP is widely utilized in soils to investigate the identity and metabolic activity of largely unculturable microbes, the application of qSIP in marine and aquatic ecosystems is more recent. Here, we investigated how bioreactor type (batch vs. chemostat) and carbon substrate complexity (single vs. multiple substrates) affect the incorporation of {superscript 1}3C-labeled glucose into rRNA after 24 hours using excess atomic fraction (EAF) as a proxy for metabolic activity rate. We found that the growth dynamics and community composition of the {superscript 1}3C-incorporating bacteria differed significantly for each treatment. EAF was positively correlated with both 16S gene copy number and a genomic index of copiotrophy in both batch treatments, but not in the chemostat, suggesting that chemostats dampen the competitive advantage of fast-growing copiotrophic taxa. Our results demonstrate that both substrate complexity and experimental regime influence qSIP-derived metabolic activity estimates and provide guidance for future applications of qSIP in aquatic environments.

Health monitoring is essential to ensure laboratory animal welfare and the reliability of experimental data in zebrafish research facilities. Conventional surveillance strategies based on resident or sentinel fish have limitations in terms of sensitivity and animal use, highlighting the need for alternative approaches consistent with the 3Rs principles. In this perspective, the present study evaluated the use of sludge collected from recirculating aquaculture systems as an environmental matrix for molecular health monitoring. Because sludge accumulates microorganisms and organic material from the entire system, it represents a promising sample for pathogen detection. Following an initial environmental surveillance phase to detect pathogens present in the system, the study aimed to optimise a molecular protocol for sludge analysis. To this end, four commercial DNA extraction kits were evaluated to assess their effectiveness in recovering bacterial DNA from sludge. Their performance was analysed by quantitative PCR in terms of extraction efficiency, repeatability, and limit of detection. The results highlighted the strengths and limitations of each DNA extraction protocol and confirmed the suitability of sludge as a non-lethal matrix for pathogen detection. These findings support the implementation of environmental monitoring as a practical and cost-effective alternative to sentinel-based surveillance, improving pathogen detection while reducing animal use in accordance with the 3Rs principles and Directive 2010/63/EU.

Cold stress is a recurring risk in tropical and subtropical aquaculture nursery ponds, yet warning tools remain limited where continuous automated sensors are impractical. This study developed a low-resource cold-stress early warning framework using four years (2022-2025) of 6-hourly manual air and pond-water temperature readings from a Nile tilapia (Oreochromis niloticus) nursery pond in Cumilla, Bangladesh. Models were fitted on 2022-2023, validated on 2024 for threshold selection, and tested on 2025 as an independent year. Cold stress (daily mean water temperature <20{degrees}C) occurred on 133 days; heat stress (>35{degrees}C) on only 4 days. Air-water coupling was strong overall (r = 0.976) but weakened in winter (r = 0.776) and further within the 18-22{degrees}C boundary zone where cold-stress classification is most sensitive. Solar radiation only marginally increased boundary-zone classification AUC from 0.782 to 0.789. In 6-hour regression, the same-hour-yesterday baseline (MAE = 1.117{degrees}C) nearly matched Extreme Gradient Boosting (XGBoost) with MAE of 1.116{degrees}C, cold-zone bias +0.36{degrees}C, and train-test gap 0.02{degrees}C; Random Forest (RF) and Long Short-Term Memory (LSTM) had MAEs of 1.195{degrees}C and 1.244{degrees}C, respectively. For cold-stress classification, Multiple Linear Regression (MLR) gave the highest F1 (0.755), while XGBoost provided the more protective operating point, detecting 95 of 108 cold-stress readings at 6-hour lead time (sensitivity = 0.880, F1 = 0.739). XGBoost warning skill extended to 12, 18, and 24-hour lead times, with F1 scores of 0.722, 0.646, and 0.704, respectively. The framework converts routine manual thermometer readings into short-lead cold-stress alerts for nursery management decisions. Multi-pond validation is needed before deployment.

Thiamine Deficiency Complex (TDC) is a reproductive disorder that affects recruitment of diverse salmonine populations globally. Typical symptoms include behavioral and neurological abnormalities and high offspring mortality. TDC is common in hatcheries that rear salmonines obtained from wild populations, and symptoms are mitigated by thiamine treatment. However, no studies have quantified thiamine concentrations in wild embryos. Here, we evaluated whether fertilized eggs and/or embryos may acquire thiamine from natural sources (e.g., biotic breakdown products and diet) during development. Lake trout (Salvelinus namaycush) gametes were obtained from feral adults in Lake Champlain and fertilized eggs were grouped by family with paired rearing under natural (Lake Champlain) and artificial (controlled laboratory) conditions. Average thiamine concentrations were similar between lake-reared and laboratory-reared fish prior to hatch; however, lake-reared fish experienced significant increases in thiamine concentrations at and after hatching compared to previous stages and compared to laboratory-reared fish; laboratory-reared fish experienced no increases in thiamine concentrations. Water samples revealed an abundance of thiamine precursors and byproducts in the natural environment, which may serve as sources of thiamine for developing embryos. These results demonstrate that salmonine embryos can acquire thiamine from natural sources during development, which may mitigate effects of TDC.

The US NEXRAD radar network has monitored the aerosphere over the US and its territories continuously since the 1990s and archived nearly 300 million radar volume scans. These data contain a wealth of information about the movements of birds, bats, and insects. Historically, this biological information was difficult to access due to the amount of data and challenges in analyzing it. In the last 15 years, fueled by computational and methodological advances, large-scale aeroecology research has blossomed. However, comprehensive analyses of the NEXRAD archive remain very costly. We collected measurements of biological activity from every volume scan in the NEXRAD archive--nearly 300 million data files total--to assemble a dataset of aerial biomass over the US from 1995 to 2025. The core data are vertical profiles, which summarize biological activity at different heights above the radar station for each volume scan. We also provide time series data products that aggregate vertical profiles to point measurements at radar stations across time. These data products can support a range of aeroecology analyses at significantly reduced effort.