Ecography

The ocean tides influence key Earth system processes at a range of spatial and temporal scales. It is known that the geometry of ocean basins is the leading controller of tidal energetics, so well-constrained palaeogeographic reconstructions and tidal properties for Earths past are imperative when investigating other Earth system processes. Here, we present a novel way to constrain both deep-time tidal model results and reconstructions, by combining palaeoecology with sedimentology. We compare new palaeo-tidal model simulations for the Cambrian period, significant for the early origin and radiation of major animal fauna, to tidal proxies. One of the most abundant soft-bodied organisms preserved during this time are cnidarian medusae (jellyfish). A total of 17 cnidarian medusae localities were obtained through the literature, which had an adequate global distribution and occurred at regular intervals throughout the period of study. In some locations there were also estimates of palaeo-tidal range. Our results show a good agreement between the simulations and proxy data. In the few locations where there is disagreement, it is proposed that the palaeogeographic reconstructions are missing details, e.g., island chains, and our results allow for the palaeogeographic reconstructions to be improved. The proxy method presented is promising and can be applied to other time-periods with different marine fossils, particularly at evolutionary and extinction periods where the marginal marine environment is of importance.

Urbanization is reshaping freshwater ecosystems, with well-documented effects across gradients of land-use change, hydrologic alteration, and habitat degradation. However, how biodiversity is organized among neighboring urban aquatic habitats that differ in hydrologic connectivity, disturbance transmission, residence time, management history, and opportunities for species movement is often less clear. This creates a challenge for interpreting urban fish communities at local scales as species occurrence may reflect both contemporary habitat filtering and historical contingencies including native persistence, interbasin transfer, stocking, and nonindigenous introductions. Here we use eDNA detections, historical records, phylogenetic information, and species trait data to investigate the fish assemblages of the Charlotte metropolitan region. We detect a highly mixed fauna that also depicts a strong signature of structured biodiversity profiles across taxonomic, phylogenetic, functional, and life-history dimensions between habitat types. In particular, bounded habitats contained assemblages with larger-bodied species that are fecund and faster to reproduce relative to free-flowing habitats. Species-level occurrence models did not support a simple trait-by-habitat rule. Instead our results demonstrate that urban aquatic habitats can sort historically mixed regional species pools into predictable assemblage-level life-history profiles while simultaneously retaining signatures of evolutionary and historical biogeographic contingency.

Ecologists remotely track movement steps of animals (e.g., via global positioning systems) and use step selection functions to study the effect of environmental factors upon their movement decisions. Constructing such functions requires pairing each observed step with some number of unobserved but feasible comparison steps. Larger numbers of comparison steps generally yield better estimates but also incur potentially challenging computational demands. Thus, it is important to determine an appropriate number of comparison steps. No established guidance exists for this decision. Here, we use simulated tracks to assess how many comparison steps are needed, fitting each set of steps to a conditional logistic regression model. We monitor errors in estimated effects for several classes of tracks, identifying the number of comparison steps for which mean relative absolute error in estimated effects is consistently low. By this criterion, 32 comparison steps per observed step are needed for our primary class of simulated tracks. Tracks in more homogeneous landscapes, tracks with shorter mean step lengths, or shorter tracks generally require more comparison steps (ranging from 64 to 128 per observed step) to achieve the same level of accuracy. Longer tracks generally require fewer comparison steps (16 per observed step). These results clearly demonstrate that the number of comparison steps influences how well step selection functions estimate covariate effects and provides initial direction in a research area that currently lacks quantitative guidance. Movement ecologists should take care when selecting the number of comparison steps paired with each observed step because those decisions matter.

Citizen science observations are abundant, but conservation requires turning uneven records into reliable predictions and directing new surveys to where information is missing. We developed a biodiversity platform for Japan that is updated monthly and integrates 2.32 million records to predict 8,297 species across seven taxonomic groups. Shared representation models outperformed species-specific models in four groups and extended predictions to species with few records. Five independent datasets, including structured monitoring, environmental DNA and complete forest inventories, confirmed that the models ranked observed species and occupied sites above alternatives, with median AUCs of 0.724 to 0.894 across sites and 0.650 to 0.841 across species. For any user-selected area, the platform returns candidate species, distribution predictions, a biodiversity map corrected for uneven observation effort, a conservation priority map for native species and a map recommending where to survey next. This map highlights places where species with few records are predicted to occur despite limited sampling. Independent observations showed that areas ranked highly by this predicted potential contained many such species, indicating that model predictions can help direct surveys toward knowledge gaps. New observations are incorporated into monthly updates, creating a national feedback system connecting citizen science, local conservation decisions and future surveys.

Squid abundance has been reported to increase globally between 1970 and 2010. This increase has been hypothesized to result from two primary factors: the loss of top predators due to overfishing and rising ocean temperatures. The decline in apex predators may lead to the expansion of squid populations either through reduced predation pressure or diminished competition with juvenile predators. Concurrently, increased temperatures could enhance the somatic growth rates of squid, thereby accelerating their population growth. However, empirically disentangling the impacts of predator loss and temperature on squid biomass remains challenging, especially in a food-web context. In this study, we used a size- and trait-based model of upper trophic levels that resolves the ecosystem structure -- biomass and trophic interactions of fish and squid -- for varying depth, temperature, and secondary production, to investigate two hypotheses of the historical expansion of squid, i.e., the effects of predator depletion from fishing and rising temperatures on squid biomass. Our model reveals that intensified fishing of squid predators -- specifically large demersal fish in shelf systems and large pelagic fish in open oceans -- leads to a slight increase in squid biomass. Conversely, elevated temperatures are associated with a decline in squid biomass. This temperature-driven reduction in biomass is attributed to an increased metabolism of squids beyond the available food supply. If historic overfishing on large marine predators continues to be curtailed, we expect a corresponding reduction in global squid biomass and fisheries potential, which could be further exacerbated by rising temperatures.

Marine diatoms contribute to about 20% of global primary production. We present the first basin-scale, multiyear assessment of diatom communities in the North Pacific, combining taxonomically high-resolution RuBisCO large subunit gene (rbcL) metabarcoding with concurrent environmental measurements. Using a nine-year time series of daily samples resolved at the species level via ~500 bp rbcL fragments, we performed multivariate analyses across biogeographic provinces, identifying significant correlations between community structure and environmental drivers such as temperature and macronutrient availability. We report the prevalence of a previously overlooked centric diatom species in the North Pacific, Eunotogramma lunatum, which appears to be near-dominant even in subarctic high-nitrate, low-chlorophyll waters where pennate diatoms are typically favored. These results demonstrate the power of rbcL for large-scale ocean monitoring and provide a critical baseline for future studies of diatom population dynamics, climate change impacts, and ecosystem resilience in a key marine region.

Context Pumping stations pose a threat to fish globally through land use change, habitat fragmentation and entrainment risk, with the catadromous and critically endangered European eel particularly impacted. Objectives/methods Establish, model, assess and understand the present-day distribution of European eel and resident fishes in 152 pumping station catchments in a once extensive wetland (The Fens) using eDNA metabarcoding (855 samples over two and half years), with specific focus on anthropogenic influences on hydrological connectivity and habitat quality. A removal survey design maximised confidence in negative results while minimising time and consumable costs. Results Eel occurrence upstream of pumping stations was low (occupancy = 28.3%) and positively associated with catchment area, fish species richness and natural hydrological connectivity (gravity drainage or flooding) and negatively associated with distance from the tidal limit. Fish species richness replaced catchment area and improved model performance, potentially acting as a biotic indicator of habitat quality and connectivity. Pumped catchments with manually operated upstream water transfers had reduced eel presence, potentially linked to the direction of water flow or the timing of operation. By contrast, fish species richness increased in these catchments during summer, suggesting displacement into unsuitable long-term habitats. Physical habitat maintenance had no detectable effect on eel occurrence or fish species richness. Conclusions This study provides the first landscape-scale assessment of European eel distribution and drivers of occurrence in pumped river catchments. The highly novel and comprehensive insights have implications for European eel conservation as well as infrastructure and catchment management, including compliance with legislation (EC Regulation No. 1100/2007).

Most evidence of the consequences of climate change in natural systems has focussed on shifts in mean temperature (1,2), but the effects of extreme climatic events (ECEs) remain far less understood. This is particularly true for very severe ECEs that may occur only once every few decades. Understanding the consequences of these severe events for natural populations is nonetheless critical, since their frequency is predicted to rise under current climate change (3). Here we combine a unique long-term dataset spanning almost five decades of breeding (>20,000 events) and morphological data (>120,000 observations) in adult and nestling great tits (Parus major) and blue tits (Cyanistes caeruleus) with fine-scale temperature records to examine the effects of an unprecedented heatwave in May 2026 on breeding success and morphology. Average temperature during the heatwave (22-29 May 2026) was 7.85 C above the historical record, reaching +10.5 C (+4.32 SD) at its peak (25-26 May). These record-breaking temperatures significantly reduced adult breeding success and nestling bmass relative to expectation in the absence of a heat-wave. Given the heatwave was widespread (Fig. 1A), our findings from a single, exceptionally well-studied population are likely to generalise to other species exposed to the same event, providing key evidence that severe ECEs can substantially harm wild populations.

1. Forest canopies harbour strong microclimatic gradients that shape plant performance, species interactions and ecosystem processes. Yet, despite renewed interest sparked by global change, forest canopies remain difficult-to-access experimental spaces. 2. With the goal to expand access to tree canopies as experimental arenas, we designed, built, and tested TreeTOP, a standardized experimental platform that opens canopy space for manipulative ecological experiments, specifically with potted plants. TreeTOP features lightweight aluminum frames placed in mature tree canopies non-invasively, allowing potted plants to be placed in three different heights, ground level, shade canopy, and sun canopy. 3. We implemented TreeTOP using two contrasting infrastructure concepts to demonstrate its applicability in both highly equipped canopy research facilities and forests without permanent canopy infrastructure. One installation relied on a canopy crane, grid power and fully automated irrigation, whereas the second was built by certified tree climbers and was equipped with an autonomous solar-powered, battery-operated irrigation system. At both sites, environmental sensor networks monitor the experiment. 4. TreeTOP successfully reproduced characteristic canopy microclimatic gradients, including increasing light availability, daytime air temperatures and thermal extremes with canopy height. Despite differing infrastructures, both implementations generated comparable microclimatic patterns, demonstrating that standardized canopy experiments are feasible in forests with or without permanent canopy access. By opening canopy space for manipulative experiments, TreeTOP provides a transferable framework for investigating plant performance, phenology, species interactions and microbiome assembly under realistic forest conditions.

The shape of density-dependence governs species persistence, and ecosystem stability. Yet, whether per-capita growth declines sublinearily, or superlinearily with density remains hotly debated. Growth rates across the tree of life have been shown to decline sublinearly with density, whereas theory founded on resource competition predicts the opposite. Here, we resolve this discrepancy and show that sublinearity can readily emerge from geometric constraints on consumer interactions. By linking inter individual spacing, movement and interference rates, we derive two limiting-interference regimes, one of which the well-mixed limit recovers the form of classic Beddington DeAngelis interference response. We then developed an individual-based model from first principles which reproduces the derived sublinearity response, and further use empirical data from published consumer-resource experiments that also bears the signature of sublinear density-dependence. Further, embedding the interference mechanisms underlying the emergence of sublinear density-dependence in coexistence theory opens a new regime for species coexistence where classical theory fails to predict. Our framework indicates that non-consumptive interactions are not merely a correction to resource competition but might be a distinct axis along which diverse communities may potentially coexist.

Heritable bacterial symbionts are pervasive in terrestrial arthropods, often imposing reproductive manipulations to promote their own spread within host populations. Co-infections are common, potentially allowing symbiont co-infectors to hitchhike through a host population. However, adverse thermal conditions can disrupt these communities, particularly when co-infectors vary in their thermal sensitivity. We used a multi-generation experiment to test whether warm (29 {degrees}C) conditions disrupted spread of heritable symbionts through uninfected populations of the spider, Mermessus fradeorum. We tested two common infection combinations: a single infection with a cytoplasmic incompatibility (CI) inducing Rickettsiella or a feminizing co-infection that included a feminizing Wolbachia, the same Rickettsiella, and up to three apparent hitchhikers (two additional Wolbachia strains and Tisiphia). We initiated replicate populations with 1/3 of one infection type and 2/3 uninfected spiders, evaluating population infection rate over 5 spider generations under different temperature regimes. Under cool (21{degrees}C) conditions, Wolbachia feminization drove co-infection to 88% and Rickettsiella CI drove single infection to 83% of host populations. Vertical transmission for all symbionts was high (97-99%) and hitchhiking symbionts also spread effectively. Under warm conditions, feminization and CI efficacy were reduced, and symbionts suffered variably reduced vertical transmission. Warm conditions ultimately destroyed the co-infecting symbiont consortium and impeded symbiont spread. On its own, though, Rickettsiella was still able to increase, despite reduced strength of CI. We hypothesize that contrasting tensions between feminizing spread of the symbiont consortium versus environmentally driven loss of function and transmission may explain observed patterns of mixed infections in field populations of this spider.

Background: Reproducible taxonomic collapsing and geological-timescale annotation of time-calibrated phylogenetic trees in R often require coordination among several packages and repeated code for label parsing, clade validation, plotting, and export. Workflow-managed analyses additionally benefit from non-interactive configuration, predictable diagnostics, and machine-readable exit status. Results: We present Rclade, an R package that consolidates the multi-package coordination required for taxonomic collapsing into a streamlined, single-function interface. Rclade provides (1) custom ggproto objects (GeomPolygonStraight/GeomSegmentStraight) that bypass coord_munch() interpolation to achieve straight-edge rendering of collapsed triangles in circular layouts; (2) automatic detection and parsing of four taxonomic-label formats (GTDB, Silva, NCBI, embedded) plus user-supplied custom regex, with explicit input-validation contracts and parsing-accuracy evaluation on real and derived test sets; and (3) workflow embeddability through YAML configuration, library-mode APIs, and standard Unix exit codes. Benchmarks on synthetic and real datasets (200-10,000 synthetic tips and real reference trees up to 10,122 tips; 5 replicates at every scale under a unified fully rendered measurement protocol) show that the full-pipeline overhead is modest for interactive use (median {approx}0.87 s in-session rendering and {approx}8.4 s process-level wall-clock at 10,000 tips). Conclusions: Rclade is a convenience layer over the ggtree/deeptime ecosystem that reduces boilerplate while adding targeted technical improvements for circular-layout rendering and format heterogeneity management.

Human deep-space missions face bone-kidney risks that cannot be extrapolated from six-month ISS data. We built a 12-state Ca-bone-urine-stone mechanistic ODE model and jointly calibrated its 11 physiological parameters on eight ISS targets by Bayesian identification (M0 base = 19-D; M1 extension adds a GCR-bone coupling term for parsimony testing only), then propagated the M0 posterior to four environments (ISS, Lunar subsurface, Lunar surface, Mars). Lumbar-lower BMD loss increases with mission duration and partial-gravity unloading (ISS 180 d -4.83% -> Mars 730 d -12.15%; 2^3 factorial: duration 82.9%, gravity 12.5%, GCR main effect ~ 0), whereas stone rate follows the opposite gradient (ISS 16.1 vs Mars 13.1 per 1000 person-years), reflecting weakened partial-gravity bone resorption alongside residual urinary chemistry changes. The dominant pathway thus shifts from bone-centric on the ISS to kidney-centric on Mars, where residual urinary-chemistry changes-not bone resorption-drive stone risk. The direct GCR-bone coupling term is unidentifiable at current ISS doses (DeltaWAIC = +0.0076 +/- 0.126 SE), so M0 is retained as the main inference model. Bisphosphonates provide >=84% BMD protection but leave a urinary-chemistry residual, so bisphosphonate monotherapy would underestimate Mars stone risk; potassium-magnesium-citrate combinations (RRR_RSS 51%) should therefore be added to deep-space countermeasures. A Lunar-surface 365-day mission is the earliest environment on the NASA roadmap to cross a composite RED threshold. That profile differs from the regolith-shielded 180-day case in both cumulative GCR (~69x) and duration (2x), so a shielding-specific effect cannot be isolated here; forcing the GCR coupling terms to zero leaves all four composite tiers unchanged (0/4, Supp S24), and the shielded 180-day profile is YELLOW rather than GREEN. Independent hold-out validation (Culliton 2025 60-day HDT-bedrest RCT, n=8 control arm of n=24 total) supports the M0 posterior predictive distribution on the lumbar-BMD sub-scope.

Background In adults, cold-attributable mortality exceeds heat-attributable mortality roughly 17-fold. Child-specific evidence has begun to emerge only recently - a nationwide Brazilian case-crossover study located the minimum mortality temperature (MMT) for under-five deaths, and a 56-country survey-based analysis linked monthly temperature anomalies to under-five mortality - but no multi-country, climate-zone-resolved estimate of the childhood respiratory-infection MMT exists, and whether temperature variability is independently associated with childhood respiratory mortality at the global scale is unknown. We quantified both. Methods We combined Global Burden of Disease 2023 mortality estimates, lower respiratory infection (LRI) deaths at ages 0-19 years and asthma deaths at ages 0-24 years, 171 countries, 1990-2023 - with 0.5 deg monthly land temperature and diurnal temperature range (DTR) fields from C-LSAT/C-LDTR (1901-2023). Four exposure dimensions (annual mean, DTR, seasonal amplitude, interannual variability) entered two-way fixed-effects models with Driscoll-Kraay standard errors. A quadratic term in mean temperature located the MMT, with percentile confidence intervals from a 300-replication country-cluster bootstrap. Future-exposure leads, country-level detrending, and permutation tests assessed contemporaneous causality, applied to both the linear coefficients and the quadratic term generating the MMT; national pneumococcal conjugate vaccine (PCV3) coverage and ambient PM2.5 exposure series were added as time-varying mechanistic covariates. Results The childhood LRI MMT was 17.1 C (95% CI 14.7-19.8), the 36th percentile of the annual-temperature distribution; zone estimates were 24.7 C in tropical and 15.8 C in subtropical countries, with weak temperate and no subarctic identification. The quadratic term underpinning the MMT, however, failed both falsification checks - future temperatures reproduced the U-shape and country-level detrending erased it - so these MMT values describe a trend-level geographic pattern of the annual construct rather than a contemporaneous dose-response. Interannual temperature variability was positively associated with LRI (+0.278, 95% CI 0.102-0.454; p = 0.002) and asthma mortality (+0.836, 95% CI 0.447-1.226; p = 2.6 x 10^-5) per 1 C, but future-exposure models returned nearly identical significant coefficients and detrending erased significance, supporting only a trend-level association; adjustment for national PCV3 coverage and PM2.5 exposure left these estimates essentially unchanged. Annual mean temperature was likewise inversely associated with both outcomes at the trend level; DTR and seasonal amplitude showed no independent within-country effects. Conclusions This study provides the first multi-country, climate-zone-resolved geography of the optimal temperature for childhood respiratory survival, spanning 171 countries; because the underlying quadratic association is trend-level, the estimates are directional. The observed variability-mortality associations are trend-level signals rather than contemporaneous causal evidence; daily-scale, child-specific designs are required to determine whether short-term thermal variability affects paediatric respiratory mortality.

Motivation: With the scaling frequency and intensity of extreme heat events across the globe, it is critical for public institutions to develop early detection systems and continuous monitoring of these events and their impacts. In Brazil, Rio de Janeiro was the first city to publish its heat protocol, with the Rio Heat Dashboard as a central component of this system. Implementation: The dashboard was implemented using R/Shiny and integrates climatic and health data from multiple sources. General features: The application comprises real-time heat exposure monitoring and automatic alert level classification, which is monitored daily by multiple municipal actors and supports activation of actions specified in the heat protocol. It also features a health impact module, which lists each heat event and its impact on mortality, and primary care and emergency visits. Availability: The source for full reproducibility is available through https://github.com/joaohmorais/RioHeatDashboard.

Wildlife re-identification (re-ID) is a widely used and powerful tool with diverse applications in animal ecology and conservation. Current automated methods typically operate on single images of a single body part of the animal. However, a single encounter may contain multiple images capturing different body regions, each providing complementary individual-specific information. In contrast to automated approaches, researchers often manually select the most suitable images and regions for identification based on factors like visibility, occlusion and image quality. This creates a mismatch between automated methods and field practice, limiting the practical adoption of current automated re-ID pipelines. Here, we address this by introducing an encounter-based, multi-body-part re-ID framework, using sea turtles as a model taxon. Our framework combines three elements: (1) An orientation-aware deep learning model, TurtleDetector, that in addition to the full bodies, it also automatically segments key body regions, i.e. heads, front and hind flippers, from images within an encounter; (2) a hybrid body-part-specific retrieval method, that sequentially combines a fast global-feature model (MiewID or DINOv3) with a more accurate but costlier local-feature model (ALIKED with LightGlue); and (3) a merged identity-prediction strategy that selects the highest calibrated similarity score across all available body parts and images of an encounter. We evaluate the framework on three long-term re-ID datasets spanning three species, loggerheads, greens, and hawksbill turtles, under an evaluation protocol that mirrors real-world, time-aware re-ID workflows. Across datasets, combining multiple body regions consistently improved identification performance over the best-performing single body region, resulting to an increase of 4-6% in top-1 accuracy. Interestingly, body regions traditionally underused in sea turtle re-ID, such as the hind flippers and carapaces, provided complementary identifying information that improved encounter-level re-ID when integrated through the hybrid retrieval method. Our findings demonstrate that automated wildlife re-ID can benefit from moving beyond single-image, single-body-part identification towards encounter-level integration of all available visual evidence. Our work further suggests that, where feasible, field photo-acquisition protocols should aim to capture multiple informative views of an individual during each encounter. Importantly, many species and taxa, including elephants, primates, cetaceans, and other large vertebrates, possess such individual-specific features across multiple body regions, highlighting the broad potential applicability of our framework.

A subset of untreated primary prostate cancer (PCa) contain substantial focal T-cell infiltrates, but whether these reflect antitumor responses that could potentially be enhanced by immune checkpoint blockade (ICB) remains unclear. We used immunohistochemistry, immunofluorescence, whole-slide spatial analysis, bulk RNA sequencing, and immune-cell deconvolution to characterize immune infiltrates in untreated primary PCa. Absolute CD8 T-cell density generally increased with total CD3 T-cell density, but the CD8/CD3 ratio decreased as overall T-cell density increased, indicating a preferential increase in CD4 T cells. Highly infiltrated tumors also had lower GZMB abundance relative to CD8 T-cell abundance. Multiplex analysis showed trends toward greater TIM3 and LAG3 expression among PD1CD8 T cells and increased regulatory T-cell features in highly infiltrated tumors. TIGIT cell density and the TIGIT/CD3 ratio increased with T-cell infiltration, whereas PD1/CD3 was not associated with overall CD3 T-cell density. Both TIGIT/CD3 and PD1/CD3 ratios were enriched within lymphoid aggregates compared with matched tumor and benign regions, consistent with these structures being checkpoint-rich immune niches. Transcriptomic analyses supported a shift in relative immune composition toward CD4 T cells and selective increases in immune checkpoints. Together these findings suggest that effective immune responses in a subset of primary PCa with increased T-cell infiltration are being repressed by several mechanisms and may respond to therapies targeting specific immunosuppressive mechanisms.

The southern sea otter (Enhydra lutris nereis) population at San Nicolas Island, California, has been monitored annually since the translocation of 140 sea otters to the island was completed in 1990. Monitoring efforts have varied in frequency and method across years. In 2017, in accordance with the National Defense Authorization Act for Fiscal Year 2016, the U.S. Navy and the U.S. Fish and Wildlife Service formally initiated a sea otter monitoring and research plan to determine the effects of military readiness activities on the growth or decline of the southern sea otter population at San Nicolas Island. The monitoring program, at its basic level, includes quarterly seasonal surveys of population abundance, distribution, and foraging activity. This report presents data from the program with a focus on the recent three years from winter 2023 through winter (February) 2026. From 2023 to 2026, we measured an 8.1-percent per annum decrease in population abundance (95-percent confidence interval =1.1-14.6 percent), with 106 total individuals counted as of February 2026. Historically, sea otter habitat usage at San Nicolas Island was concentrated on the west end of the island. Between 2017 and 2019, we observed increased seasonal usage of the north and south sides of the island, and in 2020-2022, a large (approximately 30-40 individuals) group of sea otters (raft) took up residence off the east end. During 2023-2026 the east end raft disappeared, and sea otters returned to their historical habitat usage patterns at the west end of the island. Foraging data were collected from summer 2023 to winter 2026 on a total of 461 foraging dives in 32 foraging bouts, and the majority of identified prey on successful dives (n=325) were sea urchins (124) followed by snails (48), bivalves (41) and crabs (23). One lobster and one octopus were also identified among the sea otter prey items. We combined these data with data from 2020-2022 to estimate overall energy intake rates that averaged 7.7 kilocalories per minute (95-percent credible interval =6.6-9.1 kilocalories per minute). These results can be useful to the planning of future monitoring and research of sea otters at San Nicolas Island.

Importance: Evidence on GLP-1/GIP therapies is largely derived from trials enrolling selected populations or medical records that miss utilization outside healthcare channels. No nationally representative cohort has characterized real-world uptake, indications, and access. Objective: To characterize GLP-1/GIP prevalence, indication, clinical profile, and access. Design: Prospective cohort study with three GLP-1/GIP surveillance waves (March 2024, December 2024, October 2025). Setting: The Understanding America Study, an address-based, nationally representative panel of approximately 15,000 US adults aged 18+ years initiated in 2014. Participants: UAS participants responding to at least one surveillance wave (n=9150). Exposures: GLP-1/GIP use status (never vs any use, comprising current and former use), self-reported primary indication (diabetes, weight loss, or other), and access pathway (traditional vs non-traditional). Main Outcomes and Measures: Survey-weighted prevalence of GLP-1/GIP use, overall and by indication and access pathway; sociodemographic, cardiometabolic, treatment, and access characteristics; and smartwatch-derived resting heart rate, heart rate variability, maximum activity heart rate, step count, and sleep duration and variability. Results: Among n=9150 adults (1274 with any use; 60.9% female; median age 53 years), weighted prevalence increased 46%, from 8.2% (March 2024) to 12.0% (October 2025) representing 32 million. Weight-loss indications grew, reaching nearly half of use (4.1% to 5.6%); diabetes-indicated use was stable (5.3% to 5.4%). Users carried high cardiometabolic burden (obesity, 68.2%; diabetes, 53.6%) but diverged by indication: diabetes-indicated users were older (median, 59 vs 49 years), whereas weight-loss-indicated users were more often female (69.9% vs 51.3%) and healthier. One in three users (~9 million) had non-traditional access, especially in weight-loss-indicated users, of whom 33% had no conventional prescription; 41% used compounding, online, or foreign pharmacies; and, 43% lacked coverage. Non-traditional users were five times as likely to report an unlisted, likely compounded formulation (19.8% vs 4.1%). All p<0.05. Conclusions and Relevance: Real-world GLP-1/GIP use has grown rapidly and diversified substantially in indication, access, and population profile. One in 3 users obtained treatment through nontraditional channels largely invisible to claims data, raising long-term safety, efficacy, and coverage questions. GLIMMER provides a public, nationally representative longitudinal evidence base for future payer and provider decisions.

Objectives To evaluate whether access to a certified large language model (LLM)-based clinical decision support system improves physician diagnostic performance in rheumatology compared with conventional diagnostic resources alone. Methods In this multicentre, open-label, randomised controlled trial, 82 physicians from seven hospitals in two countries were randomised 1:1 to conventional diagnostic resources plus Prof. Valmed or conventional resources alone. Participants assessed three rheumatology vignettes before and after assistance. The primary outcome was top-1 diagnostic accuracy. Secondary outcomes included top-3 accuracy, diagnostic reasoning, confidence, case-processing time and perceived support quality. Results Top-1 accuracy increased from 22.2% to 33.3% in the intervention group and from 23.3% to 35.0% in the control group, with no between-group difference in improvement (adjusted OR 0.99, 95% CI 0.45 to 2.19; p=0.979). Differences in top-3 accuracy, diagnostic reasoning and confidence were also not significant. Assisted case-processing time was substantially shorter with LLM support (94 vs 206 s; adjusted mean difference -112 s, 95% CI -141 to -83; p<0.001). Information timeliness and perceived diagnostic support quality were rated significantly higher in the intervention group. Exploratory analyses showed persistent overconfidence and substantial AI over-reliance. Conclusions Certified LLM-based diagnostic support did not improve diagnostic accuracy compared with conventional resources, but substantially reduced case-processing time and improved perceived support quality. These findings suggest potential workflow benefits while highlighting overconfidence and over-reliance as important safety considerations.