ICES Journal of Marine Science

Bottom trawls have been used for centuries, yet studies of their impact on marine ecosystems have largely been restricted to recent decades. Here, we reconstruct fishing effort for the international trawler fleets in the North Sea from the age of sail to early steam trawling, by synthesising historical data describing vessel numbers and specifications, gear dimensions, fishing grounds, and operational characteristics. The trawler fleet increased from ca 800 sailing vessels in the 1820s to ca 3500 at the peak in sail trawling in the 1880s. Subsequently, steam trawling fleets emerged, increasing to almost 2000 vessels in the 1910s, while sailing fleets declined. Trawling grounds, covering ca 7% of the North Sea in 1820s, expanded from coastal to offshore grounds, reaching ca 25% in the 1880s, and 46% in the 1910s after the transition to steam trawling. Using a hydro- and aerodynamic approach to model the wind conditions required for sail trawling, we show that about 55% to 80% of the time at sea was suitable for trawling, providing a new quantitative basis for estimating historical fishing effort. The surface area swept by the trawl per year increased from 35,000 km2 in 1820s to 225,000 km2 in 1880s and 500,000 km2 in 1910s, corresponding to ca 60% of present levels. The trawling intensity (swept area ratio) varied between 0.9-1.7 year-1 in the era of sail, increasing to ca 2.0 in the 1910s. The trawling footprint (unique area trawled) increased to 160,000 km2, about half the present level.

As anthropogenic threats have intensified over the past 500 years, we find ourselves in the midst of a sixth mass extinction, with continued losses of biodiversity threatening ecosystem stability. This biodiversity loss has caused species extinctions across taxa, and placed several others at high risk of functional extinction. These disturbance-driven impacts represent one of the most acute biodiversity crises facing global marine systems. Species exhibiting slow life histories characteristically have low resilience to disturbance. Here, we assess the risk of functional extinction and identify policy pathways for population recovery of the slow-living, Critically Endangered elasmobranch, the spinetail devil ray (Mobula mobular). We develop a stochastic, state-structured Integral Projection Model (IPM) parameterised with demographic data collected from fishery landings data in India, the world's largest mobulid fishery, and supplemented with data on vital rates from published literature. Using the IPM, we estimate that the population is declining at approximately 12% annually, experiencing substantial limiting pressure from fisheries overexploitation and failing to approach its biological maximum growth potential. Our results indicate that populations of M. mobular will be at high risk of functional extinction if 'business as usual' harvest scenario persists for another decade. We further show that long-term population recovery is only possible if survival increases significantly across all size classes, especially among large reproductive females, alongside a concurrent increase in fecundity. We conclude that no single policy measure is sufficient to recover population of M. mobular along the southeastern coast of India. Instead, combined protection through maximum bycatch mitigation and protection of nursery areas in no-take zones will be required for population recovery. This research demonstrates that recovery of overexploited populations often requires integrated resource management across life stages, and that the Critically Endangered M. mobular warrants urgent conservation action to avoid functional extinction.

Offshore wind farms are rapidly expanding to meet growing demands for renewable energy, with development expected to extend further offshore into deeper waters. This expansion requires a robust understanding of the long-term ecological consequences of offshore wind farms (OWFs) and how these may interact with ongoing climate change. We used the coupled hydrodynamic-ecosystem-biogeochemical water-column model (GOTM-ERSEM-BFM) to investigate ecosystem-wide responses to environmental changes associated with OWFs and climate warming. Specifically, we examined OWF-related scenarios of reduced benthic suspension-feeding activity, representing potential effects of contaminant emissions from OWFs, and reduced wind forcing, together with increased sea surface temperature. The scenarios were simulated individually and in combination to explore potential interactive effects. These scenarios were simulated at two contrasting locations in the North Sea, representing a well-mixed coastal site and a seasonally stratified offshore site. The coastal site exhibited comparatively modest ecosystem responses across the scenarios, whereas responses were generally stronger at the deeper offshore site. At the offshore site, changes in stratification altered vertical nutrient dynamics and contributed to pronounced differences in ecosystem responses between the surface and bottom layers. Our results demonstrate that ecosystem responses to OWF-related and climate-driven environmental changes are strongly dependent on local environmental conditions, suggesting that ecological consequences may differ substantially as wind farm development expands into deeper offshore environments.

Populations are exposed to multiple anthropogenic stressors simultaneously; however, the combined effects are poorly understood. Climate change is starkly impacting marine ecosystems and consequently fishes, with warming temperatures and increases in frequencies and durations of extreme climate events. Concurrently, plastics, such as nylon used in fishing industries, are contaminating marine waters at unprecedented levels, with detrimental effects on fishes. Here we studied the cumulative effects of warming and nylon microplastic fibres on the behavior and physiology of threespine stickleback (Gasterosteus aculeatus) by exposing fish to conditions of 15{degrees}C and 20{degrees}C and nylon concentrations of 0, 1, 10, and 100 mg/g (mg nylon/g food) for 4 weeks. Feeding rates responded complexly to multiple stressors, as increasing concentrations of plastic reduced feeding rates, with warming having an antagonistic effect. Furthermore, we observed "coughing" behaviors in response to ingestion of microfibres and a unique reselection tendency of food items previously selected by conspecifics. Under warming conditions, critical thermal maximum (CTmax) increased; however, exposure to plastics led to reductions in CTmax and thermal safety margins. Given these results, we anticipate reduced acclimation capacities, greater anxiety, and reductions in foraging efficiencies with increasing concentrations of plastic. Cumulatively, these stressors will yield greater energetic trade-offs and decreased accuracy in food selection with stark implications for marine ecosystem dynamics.

After introduction, many non-native marine species are dispersed planktonically. Secondary spread within the non-native range has been shown to prevent the establishment of the introduced species if the advection of larvae prevents sufficient return of larvae to maintain the population in the face of competition with native species. However, those studies have largely neglected the effects of spatial variation in alongshore larval transport. We examine the introduction of a novel species with planktonic dispersal into a more realistic coastal environment which includes spatial variation in larval transport estimated from the Mercator Ocean 1/12th degree global circulation model. The introduction may either be from a distant habitat, or through range expansion. We find that there are locations in the global coastal ocean where introduced species are more likely to persist because of spatial variation of coastal currents. These include regions where alongshore larval transport diverges, such as estuaries. The location where a non-native species is introduced may not be where it flourishes - it cannot be assumed that the region where invading species are first noticed to be abundant is the region where it was introduced. We extend closed-population theory to open coastal systems to estimate persistence as a function of local circulation, habitat extent, and the competitive advantage of the introduced species. Software is provided which allows the estimations of regions where introduced species are more likely to persist and flourish as a function of larval depth behavior, planktonic duration and release timing.

Many Sockeye salmon (Oncorhynchus nerka) populations have declined over recent decades, and climate change is likely to exacerbate these declines through direct and indirect ecological effects. The response to the associated environmental changes is likely to vary among life stages, populations, and regions. Quantitative estimates of climate change driven impacts that account for this variability could fill a critical gap and provide forward-looking insights into how sockeye are expected to respond to future climate-driven change across their lifecycle. To address this need we developed a hierarchical population dynamics model parameterized with juvenile, adult return and spawner abundance data from 13 sockeye salmon populations from Washington State to northern British Columbia. We used a formal causal inference framework that paired salmon abundance data with a suite of environmental covariates hypothesized to represent ecological conditions across the lifecycle. We used the model to estimate population-specific responses to each environmental driver, then combined parameter estimates with projections from down-scaled climate change models to estimate productivity responses to anticipated environmental change. We found that historical sockeye productivity was strongly associated with environmental covariates, which explained more interannual variability in return abundance than spawner abundance in most populations. However, the life stages and specific environmental covariates with the largest impacts differed among populations and regions, often displaying a latitudinal gradient. Increases in coastal ocean temperatures and mixed layer depth generally had negative effects though they varied among regions. Increased freshwater summer rearing and return migration temperatures had weaker but consistently negative effects. Under future climate conditions, projected changes in these environmental covariates are expected to result in substantial declines in productivity across most populations. Sockeye salmon display varying degrees of sensitivity to climate change across life stages, populations, and regions. Effective future management will require explicitly accounting for these life stage and population-specific responses.

The ability to model the complex and uncertain population dynamics of endangered species has improved dramatically in recent decades. However, approaches to identify optimal decisions often require a simplified representation of population dynamics. This leads to a conundrum where managers may be unsure about the output of dynamic decision models because they rely on simplified assumptions of the underlying population dynamics. Here, by pairing integrated population models (IPM) that synthesize diverse ecological data with deep reinforcement learning (DRL) capable of optimizing decisions with high-dimensional uncertainty, we introduce a framework that delivers data-driven and ecologically detailed adaptive management strategies. We demonstrate its utility through application to the supplementation program for the endangered Rio Grande silvery minnow. Using our IPM-DRL framework, we developed an adaptive decision model that selects production and distribution decisions of the supplementation program in response to the observed demographic, hydrological, and genetic environment. The decision model outperformed all heuristic approaches in the simulation across management objectives that weighed persistence and effective population size-related genetic impact differently. For example, the currently deployed supplementation strategy performed 5.3% worse than the decision model under the persistence-focused objective scoring and 185% worse under the genetics-focused one. Analysis of the models decisions in relation to demographic and environmental covariates revealed that minimum sub-population size and total population size were primary drivers of the models decisions. The results demonstrate that the IPM-DRL framework offers a high-performing and interpretable decision-support tool for managing endangered species. SignificanceConservation problems, like imperiled species management, are often challenging because the system dynamics are complex and uncertain. We demonstrate how combining an integrated population model that infers key demographic processes from noisy ecological data with a deep reinforcement learning framework that optimizes management actions addresses these challenges by generating high-performing supplementation strategies for a conservation-dependent species. Our approach embeds two decades of monitoring data within a multi-objective decision-making environment that accounts for ecological uncertainty. The result is a generalizable framework that links ecological inference directly to actionable policy outcomes, enabling scientists and managers to move beyond describing system states and processes toward identifying optimal management actions.

Coral reef monitoring needs scalable, non-invasive tools to complement resource-intensive traditional survey methods. Passive Acoustic Monitoring (PAM) offers a promising supplement, but its effectiveness is limited by the difficulty of attributing recorded sounds to species outside of previously well-characterized taxa. Using Omnidirectional Underwater Passive Acoustic Cameras (UPAC-360), we identified sounds from 31 reef fish species across 14 families on the Kona coast of Hawaii Island, including 13 not previously documented as soniferous. By releasing video and audio specimens, we have created the largest open-access collection of in-situ reef fish sounds to date for the Pacific. A subset of acoustically distinctive taxa--such as Hawaiian Dascyllus (Dascyllus albisella), Lei Triggerfish (Sufflamen bursa), soldierfishes (Myripristis spp.), wrasses, and herbivorous grazers--were identifiable in PAM recordings through manual acoustic and spectrogram review. Through identifying particular sounds linked to species with different ecological roles, these sounds have the potential to serve as indicators of reef function to increase the information and value coming from PAM surveys of Hawaiian and Pacific coral reefs.

Biological invasions are a major driver of global change, reshaping ecosystems and threatening biodiversity worldwide. Anticipating where invaders will establish and where they will exert the strongest ecological impacts are key challenges for early detection and targeted management. Although Species Distribution Models (SDMs) are widely used to forecast biological invasions, they often provide uncertain estimates of establishment ranges and limited insight into invader performance, making it difficult to anticipate ecological impacts. Here, we address these limitations by integrating physiological information on invader performance with SDMs to identify regions of high invasion risk. Using the brown alga Rugulopteryx okamurae, one of the most prominent marine invaders in Europe, we first test alternative hypotheses of northern establishment limits: (i) a cold-survival constraint driven by winter temperatures and (ii) a growth constraint derived from the species' thermal performance. To identify the more likely scenario, we combine cold-tolerance experiments with seasonal growth comparisons between the invader and a native macroalga Dictyota dichotoma, whose established distribution allows physiological performance to be directly related to realised presence. Finally, we project seasonal growth of the invader across the predicted establishment range as a proxy for biomass accumulation and potential ecological impacts. Our results indicate that northern limit in Europe will be more likely constrained by winter survival rather than growth, extending the potential establishment range of Rugulopteryx to mid-Norway. In contrast, the highest impacts are likely to remain concentrated in southern Europe, where thermal conditions sustain high year-round growth. Overall, our approach illustrates how understanding the physiological response of invaders to their environment can improve the interpretation of SDM outputs and help identify areas at greatest risk of impact within their potential establishment range.

Blue Economy models position aquaculture as a key pathway to securing global food security. Species selected for aquaculture typically show rapid growth, high stress tolerance and fast biomass accumulation, but these same traits may increase their potential to become invasive when introduced beyond their native range. We investigated the invasion history and current status of the commercially important red seaweed Kappaphycus alvarezii in the Palk Bay-Gulf of Mannar region of India. This is one of the worlds largest cultivation hubs, a climatically vulnerable marine biodiversity hotspot, and one of the three regions to report invasion. We combined in-water surveys, interviews with wild seaweed collectors, and a review of published literature to reconstruct the history of invasion and assess current status. Invasion has declined substantially, with interviews indicating that the disappearance of invasive populations began around 2014. We discuss several non-mutually exclusive explanations for this decline, including climate change, loss of coral substrate, herbivory, and reduced vitality of the seaweed. Although the decline in invasion is encouraging for coral reefs, our findings raise questions about the ecological and socioeconomic consequences of introducing non-native aquaculture species under Blue Economy initiatives, particularly in ecologically sensitive regions vulnerable to climate change.

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.

Coastal forests are increasingly threatened by saturated soil and elevated salinity levels resulting from sea level rise, saltwater intrusion, and storm surges. In response to rising salinization and flooding, healthy coastal forests that rely on freshwater (both wetland forests and low-elevation upland forests) are transitioning into landscapes dominated by dead or dying trees, known as ghost forests. Situated among salt-tolerant shrubs and grasses, ghost forests eventually become marshes or open water. Here, our main objective was to quantify the dynamics and pathways of these forest landscape conversions, as well as the factors contributing to the changes, which is vital for understanding the progression of coastal ecosystem degradation and forecasting future changes. We focused first on identifying the best method to track forest landscape change by exploring the role of multiple remote sensing indices (i.e., multispectral, bi-seasonal, topographical, and phenological metrics) in enhancing the performance of deep learning models (convolutional neural networks, CNNs) for land cover classification in the coastal plain of North Carolina using surface reflectance of Landsat 8 and Sentinel-2 images. Then, we used the best available data (Landsat 8) to understand long-term change and identify patterns of land cover change from 1985 to 2021. Our study reveals that incorporating phenology and topographical indices enhances the separability of the ghost forests class from all other vegetation classes. In our assessment, the higher-resolution Sentinel-2 data (F1 Score = 96.3) outperformed Landsat images (F1 score = 93.4) for the 2021 co-available year. However, Landsat remains an important tool used due to its long-term data record. Therefore, we used Landsat to determine that 21% of forests were lost between 1985 and 2021, and that the rate of loss is increasing. Between 2010 and 2021, 23,876 ha of forest were converted to marsh, ghost forest, and shrub, which is 1.5 times higher than the 16,968 ha lost between 1985 and 2010. These conversions from forest to ghost forest and marshes were driven primarily by proximity to the channel, salinity, and the increasing rate of relative sea level rise (RSLR), which are the key environmental drivers of observed changes. By quantifying these changes, we highlight regions most vulnerable to environmental stressors, providing a basis for targeted conservation strategies.

This brief communication presents two solutions for calculating absolute measures of error from time-difference-of-arrival (TDOA) positioning in underwater acoustic telemetry arrays. First, a Monte Carlo estimation of TDOA positioning error is derived. Next, a computationally inexpensive, approximate solution to the Monte Carlo method is presented. This approximate solution is achieved by solving the Jacobian of a closed-form TDOA positioning model. The positioning error covariance matrix returned from either method can then be used to report the accuracy of TDOA positions or utilized in state-space positioning models. Finally, calculations of the expected radial error are shown which serves as a simple summary statistic for reporting positioning error in real units.

The impact of invasive species on marine ecosystems is rapidly increasing, where they often outcompete native species in the absence of natural enemies. The parasite release hypothesis states that the success of invasive species relates partly to the loss of natural parasites during introduction and lower susceptibility to native parasites. Barnacles are highly successful invaders due to broad environmental tolerance and dispersal via shipping, but whether parasite release also participates in this success remains unknown. In this study, we analyse parasite infection patterns in native and invasive barnacles in the Wadden Sea by surveying communities across tidal zones. Additionally, year-round molecular monitoring of larval stages and a literature review were used to track the distribution of the invasive Pacific barnacle Balanus glandula in Europe and document its appearance in the Wadden Sea. The long-established invasive Austrominius modestus dominated the high and middle intertidal zone, whereas native species (Balanus crenatus and Amphibalanus improvisus) prevailed in lower zones. Native and invasive barnacles differed in parasite infection frequency (mostly cestodes and trematodes). The native Semibalanus balanoides had the highest prevalence (27%), followed by the invasive A. modestus (11%), and no infections were found in B. glandula. Lower parasite prevalence in invasive barnacles is consistent with the hypothesis that parasite release supports invasion success. In the absence of competent parasites, B. glandula could impact native barnacles through competition. Continued monitoring of B. glandula is recommended to track its distribution, interactions with native species, and parasite acquisition, providing further insight into the parasite release hypothesis.

PurposeDiscussions surrounding the biomedical faculty job market often focus on applicant competitiveness and external metrics such as number of publications and funding records. Consequently, there is typically less discussion about applicant readiness, the point at which applicants perceive themselves as prepared to enter the market. Since 2018 our group, the Faculty Job Market Collaboration (FJMC), has conducted annual end-of-cycle surveys of biomedical faculty job applicants, producing the largest longitudinal dataset on this process to date. MethodsWe employed a mixed-methods design examining faculty applicants in biological science fields in North America. Regression analyses were conducted on a longitudinal dataset of 729 respondents across multiple hiring cycles. To determine how applicants evaluated their own preparation, qualitative interviews were conducted with a separate cohort of biomedical postdoctoral applicants during the 2024-2026 job cycles. ResultsOur findings demonstrate that rather than depending on a single quantitative threshold, readiness is a multifaceted construct shaped by actionable and interpersonal drivers. Key factors influencing an applicants perceived readiness include taking agency to submit applications, receiving explicit support from a mentor, incorporating strategic use of artificial intelligence tools into application preparation, and their career stage. ConclusionBy distinguishing individual readiness from systemic assumptions of market competitiveness, this study highlights a blind spot in academic workforce development. Our results suggest that applicants can achieve readiness and successful outcomes through different combinations of support, strategy, and timing rather than a uniform metric profile. By integrating quantitative and qualitative data, our study provides an evidence-based framework for understanding applicant readiness and offers practical guidance to help trainees navigate the increasingly competitive academic job market. Teaser TextOur mixed-model analysis of the biomedical faculty job market is designed to help prospective faculty candidates assess their readiness to enter the job market. By integrating multiple indicators of academic productivity, funding success, and professional experience, our study provides evidence-based benchmarks that can guide applicants in evaluating their competitiveness and identifying areas for further development before pursuing faculty positions.

Coral reef fish assemblages are widely used as indicators of ecosystem condition, yet manual annotation of underwater video remains a major bottleneck for scalable biodiversity monitoring. Despite rapid progress in automated detection, ecologically realistic and publicly available datasets remain scarce, particularly for the Western Indian Ocean. Here, we present WIO-ReefFish, a reef fish detection dataset derived from diver-operated line-intercept transects and designed for ecological monitoring under natural survey conditions. WIO-ReefFish comprises 1,000 ultra-high-definition images (3840 $\times$ 2160 pixels) and 6,768 exhaustive bounding-box annotations spanning 24 taxonomic categories, thereby preserving full-frame assemblage structure in complex reef scenes. We also establish a standardized benchmark across nine object detection models under two complementary protocols: class-aware detection and class-agnostic fish localization. Detection performance was consistently higher under the class-agnostic protocol. The best-performing model (RT-DETR) improved from 0.48 mAP50 in the class-aware setting to 0.70 mAP50 when taxonomic constraints were removed, indicating that taxonomic discrimination remains substantially more challenging than fish localisation in reef imagery. Spatially independent evaluation revealed a pronounced generalisation gap, particularly for taxonomic detection, whereas class-agnostic fish localisation remained substantially more robust across transects and countries. Together, these results establish WIO-ReefFish as a realistic benchmark for automated reef fish detection and provide a foundation for more robust computer-vision tools in coral reef biodiversity monitoring. The WIO-ReefFish dataset and associated benchmarking resources are publicly available.

Sexual coral propagation is an emerging technique capable of producing large numbers of corals for coral transplantation and reef rehabilitation. In contrast to asexual coral propagation, sexual propagation increases genotypic diversity and can be used for selective breeding to enhance coral heat tolerance or other desirable traits. However, implementation at meaningful ecological scales is hindered by high mortality during early life stages, high costs associated with nursery rearing facilities, and labour-intensive outplanting methods. To overcome these issues, we developed the CoralAssist Plug (CAP), a ceramic device designed for the rapid and cost-effective outplanting of sexually propagated corals in large numbers that maximises post-outplant survivorship. CAPs combine three important functional features: 1) built-in microrefugia to protect juvenile corals from grazing, 2) a relatively small size, 3 by 1 cm, that is easy to handle and stack efficiently without compromising the survivorship of corals, and 3) a hole in the middle that facilitates handling and attachment. CAPs were settled with Acropora aff. digitifera and outplanted to a reef crest after 1 to 6 months of ex situ nursery rearing. A 3-person dive team was able to outplant ~120 CAPs in one 90-minute shallow dive (just over 2 minutes per CAP per person). With longer nursery durations of 6 months, it was possible to achieve 36 % yield (i.e., the proportion of devices with a surviving coral) 4-years post-outplant. With nursery durations shortened to 1 month, we were able to attain 24 % yield 3-years post-outplant. Microrefugia significantly enhanced post-outplant survivorship leading to an 11 % increase in yield 4 years post outplant compared to devices without microrefugia. Outplanted corals that had reached adult size, were self-attached and were reproductively mature after 4 years. Our results suggest that CAPs can play a meaningful role in reef rehabilitation by efficiently introducing sexually propagated corals into natural populations with clear applications to assisted evolution techniques, such as selective breeding.

BackgroundThe relationship between aesthetic appreciation and environmental values remains a critical yet under-researched area in environmental psychology. Although the Two-Major Environmental Values (2-MEV) model--encompassing preservation and utilization dimensions--serves as a standard framework for assessing environmental attitudes, the integration of aesthetic perception within this structure has largely remained unexplored. This study investigates the conceptual linkages across a diverse international sample to determine whether aesthetic appreciation functions independently of a traditional environmental value framework. Methods and FindingsWe conducted a large-scale, cross-sectional survey involving 11,800 pre- and in-service teachers across 34 countries. Participants environmental values were evaluated using the 2-MEV scale, while their aesthetic appreciation of nature and the built environment was assessed using Osgoods semantic differential technique. Employing principal component analysis, hierarchical exploratory factor analysis (EFA), analysis of variance (ANOVA), and within-class analysis (WCA), we accounted for cross-national variations and evaluated response consistency. The results demonstrate that aesthetic appreciation comprises two distinct dimensions-- focusing separately on nature and the built environment--that operate independently of traditional preservation and utilization values, showing only weak correlations. Furthermore, while the overarching psychological structure remains consistent globally, our findings reveal significant cross-national variations in respondent scores, particularly concerning utilization-related values. ConclusionsThese findings establish that aesthetic appreciation constitutes a distinct psychological construct separate from conventional environmental value frameworks. The observed cross-cultural variability underscores the necessity of accounting for national and cultural contexts when designing environmental education programs. By leveraging a robust, comprehensive global dataset, this study provides a vital empirical foundation for integrating aesthetic and value-based dimensions into future environmental research and educational policy.

The tidal wetlands of Louisiana comprise about 25% of those found throughout the conterminous United States yet estimates of wetland loss rates in the region between 1932 and 2016 have exceeded 60 km2 yr-1. To mitigate further degradation and wetland loss in the region, a globally unprecedented $50B, 50-year plan for coastal Louisiana is driving restoration efforts, and demand exists from multiple stakeholders for regularly updated, regional-scale, accurate land cover information. We used machine learning (random forests; RF) and cloud computing to develop a new Landsat-based, marsh vegetation community geospatial dataset. The dataset depicts wetland vegetation community types defined in a previous study at annual (1985-2025) time steps at 30-m resolution. An RF algorithm was used to integrate training samples with feature variables derived from Landsat imagery, and the resulting geospatial data product achieved an overall correct classification rate of 78%. The approach for development of the land cover dataset presented here has potential for application in other coastal wetland habitats throughout the world.

For organisms with biparental care, successful reproduction hinges on coordination between partners. Seabirds face an extreme coordination challenge because parents must schedule nest attendance on land with long-distance foraging trips at sea. We present a computational model of incubation schedules for a vulnerable seabird, the Leachs Storm-Petrel (Hydrobates leucorhous). Using only simple energetic rules and parameters, the model recapitulates natural incubation rhythms, exposes a tradeoff between parent energy and egg attendance, and predicts severe reproductive failure in harsh environments. Incubation primarily fails through "schedule breakdown" -- a single point in the season when both parents spend too long foraging and the egg dies from cold. The resilience of the developing offspring to neglect is thus a fundamental adaptation to the uncertainties of biparental care. These results raise new alarms about the indirect causes of reproductive failure in sensitive marine species and provide theoretical foundations for the evolutionary ecology of scheduling behaviors.