Limnology and Oceanography: Methods

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

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.

Oligotrophic subtropical waters are some of the ocean's largest continuous ecosystems, yet their protist diversity and community succession remain poorly understood. We examined the protist community in the surface waters of the Gulf of Aqaba at near-daily resolution from March 2024 to July 2025 using an Imaging FlowCytobot. The record revealed a clear seasonal succession. Total cell density increased nearly threefold during winter mixing, driven mainly by an increase in cells smaller than 5 microns. Cells were generally larger during summer, making total biovolume similar in summer and winter. Biovolume reached its highest sustained values during the spring bloom. Despite its low cell density, the summer community was dynamic, with sudden appearances of euglenophytes, flagellates and dinoflagellates at high densities. Coccolithophores and cryptophytes increased during winter, followed by diatoms and ciliates in spring. We also provide a dataset of 31,700 annotated IFCB images.

The decline in fishery yields in Japan's enclosed coastal seas has been accompanied by a reduction in phytoplankton biomass, suggesting a widespread decrease in ecosystem productivity. Oligotrophication in Mikawa Bay has caused substantial declines in phytoplankton biomass and Manila clam (Ruditapes philippinarum) production. To assess whether external nutrient enhancement could stimulate phytoplankton growth, a controlled demonstration experiment using treated effluent from two sewage treatment plants (WWTPs) was conducted (spanning fiscal years 2022 to 2024) based on analysis using a three-dimensional non-hydrostatic model. Although effluent DIP and nitrogen concentrations were increased, model results showed that WWTP-derived nutrients represent only a minor portion of the total nutrient budget. Field observations revealed limited increases in surface water phosphorus, strong seasonal variability, and only temporary rises in chlorophyll-a and clam harvests. Monthly TP data demonstrated that seasonal DIP pulses, especially spring phosphorus bursts, dominate nutrient dynamics and overshadow external loading effects. Laboratory experiments further showed that phosphate is efficiently fixed by Fe(III) under oxidizing conditions and rapidly released during reductive dissolution of [FeOOH-HPO4]2- complexes, confirming iron as the principal regulator of internal P cycling. Because current numerical models omit iron-driven internal cycling, they cannot accurately predict bioavailable P or ecosystem responses. Overall, the study indicates that localized nutrient enhancement is insufficient to counter long-term oligotrophication, and effective management must integrate nitrogen limitation, internal Fe and P cycling, oceanic exchange, and seasonal variability in Ise and Mikawa Bays.

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.

The Retaria are an abundant planktonic protist lineage that play a substantial role in biogeochemical cycling, primary production, and food web dynamics in open ocean ecosystems. Their impact is, in large part, due to their capacity to host photosynthetic endosymbionts. Despite the importance of these relationships in the global oceans, our knowledge about the diversity of photosymbionts associated with the planktonic Retaria is still limited due to the difficulty of collecting and analyzing these cells. Here we apply a new protocol to assess retarian photosymbiont diversity: Fluorescence Lifetime Imaging Microscopy (FLIM) is an easy-to-use method to distinguish between different sources of fluorescence during confocal microscopy. We applied FISH probes that hybridize with the most commonly reported retarian photosymbiont lineages to environmental plankton samples and used FLIM to confirm the presence or absence of our FISH probes in retarian cells. By analyzing the fluorescence lifetime of 92 photosymbionts, we found that the retarian photosymbiosis is far more complex than originally described, where Retaria commonly host multiple algal lineages per cell, and regularly host algal lineages outside of the two most common lineages. These efforts demonstrate that FLIM is an overlooked tool in the study of host-microbe associations, with significant potential to be used across diverse host lineages and environmental samples.

Understanding the consequences of global change for our ecosystems requires reliable, accurate, and scalable tools for detecting ecological change. To this end, recent efforts have focused on scaling up the quantification of demographic processes from individual organisms (the fundamental ecological unit) to the larger spatial scales they inhabit to yield more precise and informative estimations of ecological change, especially in response to disturbance. Here, we describe a transferable workflow that combines robust underwater photogrammetry techniques with machine-learning-assisted image analysis to quantify demographic changes in coral colonies (growth, stasis, partial mortality, and complete mortality) through time on the reef landscape. We then demonstrate several analytical applications of this workflow that can be broadly applied to sessile and/or clonal organisms in other ecosystems. First, we tracked the fates of 3,162 coral colonies through a marine heatwave that caused substantial mortality. Second, our approach enabled detection of size- and taxon-dependent patterns in demographic changes from before to after the heatwave. Finally, for a subset (425) of these colonies, we further demonstrated how our method can be used to track fates across multiple years, including a year of change before and after the heatwave took place, revealing nuanced patterns of survival and mortality, as well as changes in size structure that occurred before and after the disturbance. Our workflow offers an important advance for increasing the accuracy of change detection on coral reefs and other ecosystems by linking demographic changes in individual organisms with spatially extensive image-based surveys through time.

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.

The picocyanobacterium Prochlorococcus is a fundamental contributor to ocean primary productivity. While its free-living population has been extensively studied, primarily using flow cytometric analyses, the size and distribution of its particle-associated population is not well understood. Using filter fractionated samples from cruises in the Pacific Ocean, Atlantic Ocean, and Mediterranean Sea, we generated metagenomic data using internal standards, yielding absolute genome equivalent counts of Prochlorococcus cells in different size fractions. We used these data to model a relationship between relative and absolute genome equivalent counts, yielding a correction factor that we validated using published datasets. We then applied the correction factor to size-fractionated global metagenomic data from the TARA Oceans Project, which has widespread Prochlorococcus cells in size fractions >1.6 m throughout the transects, to calculate the fraction of the total Prochlorococcus population in large size fractions. The ''particle-associated'' population fraction increased with net primary productivity. Dissolved inorganic carbon was also directly correlated with increased particle association, which, combined with other evidence, could indicate an association with upwelling. We also examined the relationship between particle-associated population and carbon export at 150 m by incorporating published estimates of carbon flux based on TARA optical scattering data. This study highlights the potential importance of particle-associated Prochlorococcus to carbon flux in marine ecosystems and offers a way to convert relative to absolute genome equivalents of microorganisms in archival metagenomic datasets.

Plankton plays a fundamental role in aquatic ecosystems, influencing biogeochemical cycles and serving as a key food source for many organisms. Recent high-throughput imaging technologies enable the rapid acquisition of large volumes of microscopic images, creating new opportunities for monitoring planktonic ecosystems. However, the manual processing and annotation of the vast amounts of data generated by these devices remain time-consuming tasks. In this context, machine learning-based classification models offer a promising solution. In this data paper, we introduce a new labeled freshwater plankton dataset comprising approximately 88,000 images distributed across 43 taxa. We also present the labeling assistance method we used to facilitate dataset annotation. Finally, we present a baseline based on a convolutional neural network (CNN), which achieves a classification accuracy of 93% on our dataset.

(1) Kelp forests support ecologically, commercially, and culturally important species, yet their benthic communities remain difficult to monitor consistently across space and time. Scientific SCUBA surveys provide valuable observations but can be constrained by safety, bottom time, depth, and the spatial extent that divers can efficiently cover, motivating complementary approaches for collecting standardized benthic imagery. (2) We developed and field-tested a standardized, open-source framework for benthic visual-imaging surveys using a small, modular remotely operated vehicle (ROV). Across four cost-scalable hardware configurations, we integrated navigation sensors, custom BlueOS Extensions, and our surftrak contribution to ArduSub, which enables fixed-altitude flight above the seafloor, and developed two open-source desktop applications that streamline field operations (rov_flight_ops) and imagery processing (rov_imagery_processing). We also evaluated power supplies, benthic lighting, camera settings, field protocols, and telemetry-processing workflows over 303 transects conducted on 64 survey days from 2022 to 2026. (3) The ROV operated across soft-sediment and rocky habitats, currents of 0-3 kt, and underwater visibility of 0-10 m. surftrak held the ROV within 0.2 m of its target altitude for 96% of 21 h of survey transects, producing an approximately 1 m^2 standardized image footprint. Sufficient illumination and optimized camera settings yielded high-resolution imagery in visibility below 2 m, while topside power increased endurance and operational flexibility. Combining Doppler velocity log and underwater acoustic positioning data through the vehicle's extended Kalman filter improved navigation and post hoc transect reconstruction. During 2026 surveys, rov_flight_ops and rov_imagery_processing automated flight logging, log retrieval, fault diagnosis, and the sorting, development, and telemetry annotation of survey imagery. Dense kelp canopies nevertheless constrained vehicle operation, and downward-facing imagery provided limited observations of cryptic or obscured organisms. (4) We provide configuration-specific bills of materials, hardware and wiring documentation, software and firmware inventories, camera settings, open-source field and imagery-processing software, step-by-step field protocols, and pre- and post-dive checklists to support replication and adaptation of the framework. Together, these resources provide a field-tested starting point for expanding standardized benthic imaging while complementing diver surveys across kelp forests and other shallow coastal ecosystems.

Environmental DNA (eDNA) metabarcoding enables sensitive, non-invasive assessment of fish communities, but highly multiplexed analyses using Oxford Nanopore Technologies (ONT) platforms require stringent control of sample-index misassignment and sequencing errors. We developed a MiFish experimental workflow combining unique dual indexes, a library protocol that omitted end preparation and used 5'-phosphorylated primers, BLAST-based demultiplexing, quality-dependent clustering, consensus generation, and haplotype partitioning by SNP/INDEL patterns. Omitting pooled end-prep reduced the mean index-chimera rate from 0.0674% to 0.000420%, a 160-fold reduction. We applied the workflow to an archive of seawater samples collected weekly off Monbetsu, Hokkaido, Japan, from 2012 to 2022. Relative read abundance (RRA) data were obtained for 274 samples, and eight taxa showed significant seasonality. For six of these taxa, the three-year mean RRA peaks coincided with reported spawning periods in Hokkaido. The workflow substantially reduced index misassignment and enabled cost-efficient, highly multiplexed analysis of a decadal fish eDNA time series.

Tidal flats cover less than 1% of the surface of our planet, but they provide important ecosystem functions and services, like carbon sequestration and nutrient (re-)mineralization, primary, sec-ondary, and food production, and habitats for a variety of species. Despite their importance, they are threatened by environmental stressors and anthropogenic impacts. Hence, a better under-standing of the interaction between macrozoobenthos, their metabolic activity, and their contri-bution to carbon and nitrogen cycling is important. Therefore, we conducted in-situ pulse-chase tracer experiments at a Pacific oyster (Magallana gigas) reef in the Eastern Scheldt (Southwest Dutch Delta, Netherlands) in summer and autumn 2020. During these experiments, we provided the submerged benthic community with 13C and 15N-enriched bacterioplankton and incubated it in seawater enriched in 1% deuterium oxide (2H2O) for one tidal cycle (~9 h), before the benthic community was kept at in situ conditions for another 14 d. Our aim was (1) to assess seasonal variations in 13C and 15N processing by macrozoobenthos, (2) to evaluate potential life-stage de-pendent differences in 2H uptake - a proxy for metabolic activity, and (3) to identify the macro-zoobenthos taxon which had the highest metabolic turnover rate (MTR). In summer, most bacte-rioplankton-derived 13C- and 15N was taken up by sponges (Halichondria panicea), limpets (Crepidula fornicata), and clams (Ruditapes philippinarum), whereas in autumn, H. panicea, C. fornicata and the sponge Hymeniacidon perlevis dominated 13C and 15N incorporation. Statisti-cally significant differences in 2H uptake between life stages (juvenile/ small vs. adult) was de-tected in Malacostraca (i.e., Rhithropanopeus harrisii), but not in Polychaeta or Bivalvia. There-fore, this difference between taxonomic classes might be linked to mold-intermolt periods. Sea-sonal differences in MTR of H. panicea and M. gigas (i.e., the species with the highest MTRs in summer and autumn) might be linked to seasonal environmental variability, such as temperature and food availability.

Deep-sea abyssal plains harbour extensive biodiversity, much of which remains undocumented. Polymetallic nodules in the abyssal plains of the Clarion-Clipperton Zone (CCZ), Central Pacific, harbour diverse meiofaunal communities within their crevices, representing an understudied habitat. Given their high concentrations of nickel, copper, and cobalt, nodules are currently one of the primary targets for the extraction of deep-sea mineral resources. Here, we characterise the physical properties of polymetallic nodules, quantify their meiofaunal crevice communities, and compare them to those from the nearby sediments. We show that nodules contain internal cracks and microfossils, that their crevices harbour meiofaunal communities dominated by nematodes and copepods, and that faunal abundance increases significantly with nodule volume. Nodule-crevice nematode and copepod abundances were equivalent to approximately 10% and 25%, respectively, of those recorded in nearby sediments across the two exploration contract areas in the eastern CCZ. Based on 18S rRNA data, nematode and copepod assemblages recovered from nodule crevices differed from those recovered from nearby sediments collected during the same expedition and within the same exploration contract areas. Our findings, therefore, point to the possibility of nodule-associated crevice meiofauna communities and the consequent risk of biodiversity loss associated with nodule removal through potential future commercial mining.

Studying algae requires specialized equipment to characterize culture growth and physiological performance and non-invasive monitoring of these cultures typically relies on optical density (OD) measurements. Currently, OD is often measured using standard spectrometers that suffer from detector saturation at high cell densities, which requires time consuming sample dilutions and lacks compatibility with flat-walled cell culture flasks like Roux bottles. Here we describe a 3D-printable device to measure optically dense algal cultures directly within these cultivation vessels. This instrument combines light attenuation and scattering, resulting in a dual-sensor system that utilizes near-infrared light (950 nm) to precisely quantify biomass without interference from changing photosynthetic pigments. Cultures that reach high cell densities can be assumed to be accurately quantified in situ using the scattered signal, preserving the integrity of the culture and eliminating the need for subsampling. This method is adaptable to the most common geometries of Roux bottles (T-25, T-75, and T-175) and could be used to monitor small-scale batch cultures without contamination risks. A cyanobacteria algal species (Limnospira platensis) and three flask sizes were analysed on light attenuation linearity and scattering detection limits at different cell concentration, demonstrating that the light attenuation module can reliably measure biomass up to an OD of 3.1 (equivalent to >1.5 g/L) without requiring dilution.

Diatoms are major contributors to marine primary production, yet current approaches for monitoring their abundance and function rely on coarse satellite chlorophyll estimates or sparse cell count and carbon fixation measurements. Molecular markers are a promising approach for high-resolution measurement of both abundance and metabolic activity through analysis of environmental DNA (eDNA) and RNA (eRNA). We present an isothermal quantitative recombinase polymerase amplification (qRPA) assay targeting rbcL gene copies and transcripts of marine diatoms, operating at low temperature and producing results in less than 15 min. We demonstrate specificity and calibration across diverse diatom taxa, then apply the assay to eDNA and eRNA samples from the Mare Chiara Long-Term Ecological Research site in the Bay of Naples, Italy, alongside microscopy, chlorophyll, physicochemical, and carbon-fixation data. Diatom rbcL DNA tracked abundance across five orders of magnitude despite seasonal shifts in community composition. Combining molecular and optical data revealed increased cellular rbcL copies and chlorophyll in low-light winter populations, suggesting enhanced photosynthetic capacity despite lower abundance. Furthermore, rbcL RNA reflected total carbon fixation rates and identified populations with differing carbon fixation activity. These results support rapid, RPA-based rbcL quantification as a robust approach for biomolecular ocean observing.

1. Context. Capturing and identifying airborne biological matter (bioaerosols) enables detailed characterisation of ecological communities, but the cost and weight of existing commercially available active air samplers limits the deployment of multiple devices needed to realise this potential. 2. Method. We present the AberTrap, a lightweight (~50g), open-source (CC-BY-SA), programmable rotating-arm bioaerosol sampler that can be self-built from common laboratory components and makerspace equipment at low cost (ca {pound}20 per unit, exc. power supply). To characterise the device's performance, we first explored the influence of rotational speed and paddle design on aerosol capture under controlled conditions, using fluorescein and a range of biological aerosols (4.5-33 m). To demonstrate its utility for ecological applications, we then validated field performance in a species-rich broadleaf woodland (England, UK), deploying eight samplers over five days and identifying captured fungal aerosols by ITS2 metabarcoding. 3. Key results. Modifying paddle design allowed us to influence particle selection and capture efficiency. Slotted paddles captured significantly more aerosols than plain paddles despite sampling less air, which we traced to the concentration of aerosols at the paddle leading edges. This effect was most pronounced for the smallest particles and outweighs the influence of rotational speed. In the field, 20 daily samples (four samplers over five days) detected 2,431 fungal taxa, 78.9% of the Chao2-estimated total fungal richness. A single sampler captured only 59% of this richness. Continuous 5-day sampling recovered 78% of the taxa detected by daily sampling, indicating only modest paddle saturation over this period. Our time segregated design allowed us to infer dispersal dynamics; 35% of taxa were recorded only on one day, and 19% recorded across all five days. Overall, replicate AberTraps provided high sampling completeness. 4. Implications. The AberTrap provides a low-cost, lightweight and programmable alternative to commercial rotating-arm samplers, enabling levels of spatial and temporal replication impractical with existing devices. Low cost and portability facilitate deployment in remote or resource-limited contexts. Its open-source, adaptable design allows the device to be tailored for applications in biodiversity assessment, pathogen surveillance and ecological monitoring.

Individual encounter histories are central to capture-recapture models, but fisheries monitoring is often reduced to counts that do not account for variation in detection probability. This study presents a machine-vision workflow for converting long-term video surveillance of Atlantic salmon (Salmo salar) and sea trout (Salmo trutta) spawning runs into individual-level data for capture-recapture analysis. The workflow detects fish-positive frames, saves video clips, extracts fish-head regions of interest, and organizes cropped images for re-identification. A binary EfficientNetB0 fish detector achieved validation accuracy of 0.9918 and PR AUC of 0.9992; at a conservative threshold of 0.98, validation false positives were eliminated while retaining 94.3% recall. A YOLOv8n model localized fish-head regions, and an EfficientNetB0 ArcFace model trained on head images from 700 identities achieved 99.80% accuracy among accepted known matches and an image-weighted false-accept rate of 0.81% when non-training identities were treated as unknown. Zero-shot closed-set retrieval achieved 99.17% top-1 accuracy across 1,416 identities excluded from model training, demonstrating strong generalization to previously unseen identities.