Global Ecology and Conservation

Understanding the spatial patterns of biodiversity and their environmental determinants is fundamental to ecology and conservation, particularly in mountainous transitional zones where species assemblages can shift rapidly. Amphibians, as highly sensitive organisms, are excellent indicators of environmental change, yet quantitative assessments of their diversity in the Huangshan Mountains-a biodiversity hotspot at the junction of the Palaearctic and Oriental realms in southern Anhui, China-remain limited. We conducted systematic line-transect surveys across 200 grids (5 km x 5 km) during the spring and autumn of 2023 and 2024, recording a total of 10,342 individuals belonging to 23 species, 20 genera, 9 families, and 2 orders. Three species (Fejervarya multistriata, Microhyla fissipes, and Bufo gargarizans) were identified as dominant, and two nationally protected species (Hoplobatrachus chinensis and Andrias davidianus) were detected. Inter-annual alpha diversity did not differ significantly, but pronounced seasonal variation was observed, with spring supporting higher Shannon-Wiener and Pielou evenness than autumn in both years. Using generalized additive models and model averaging, we found that annual precipitation and the normalized difference vegetation index (NDVI) were consistently the strongest positive predictors of Shannon-Wiener diversity, Simpson dominance, and species richness, while species richness also declined significantly with increasing human footprint. Total beta diversity (Soerensen dissimilarity) was very high (0.981) and overwhelmingly driven by species turnover (97.86%) rather than nestedness. Partial Mantel tests and distance-based redundancy analysis further revealed that environmental distances-particularly annual precipitation-significantly shaped overall beta diversity and its turnover component after accounting for geographic distance. These results highlight the predominant role of climatic and vegetation gradients in structuring amphibian assemblages in this subtropical mountainous region, providing baseline data to inform local conservation strategies.

AimSpecies in mountain ecosystems often experience upslope distribution shifts in response to climate change. However, elevational range dynamics exhibit substantial complexity around this general trend, with varying magnitude and direction of shifts observed among studies. We tested whether factors other than temperature, such as habitat size and land use, are also responsible for observed elevational shifts in a cold adapted species. LocationHokkaido, Japan MethodsWe resurveyed 61 historical (1963-2007) occurrence sites covering a wide elevational range (60-2,210 m) within the distribution range of the northern pika (Ochotona hyperborea). We assessed the existence of elevational shifts using quantile regression and the relative importance of temperature, habitat size, and land use on the shift using occupancy analysis. ResultsWe detected presence of the northern pika at 41 sites, suggesting extirpations at 20 sites (32.8%) across a wide elevational range of 60-1,550 m. The concentration of extirpation sites at low to mid elevations resulted in a significant upslope shift of the distribution centroid, although the shift was nonsignificant at lower and upper portions of the range. The occupancy analysis revealed a negative effect of long-term mean of summer maximum temperature and a stronger positive effect of habitat size. ConclusionsThis highlights the susceptibility of the northern pika to heat stress and the importance of larger habitats and thus habitat heterogeneity for persistence of local populations. Given the possibility that the observed shift represents a precursor of elevational contraction, continuous monitoring of the local populations is highly needed to evaluate their long-term viability.

Extensive deforestation and disturbance have reshaped forest landscapes in West Africa, including areas surrounding Tai National Park, the largest remaining block of Upper Guinean rainforest. Although many degraded areas are currently undergoing regeneration, the capacity of these secondary forests to recover their biodiversity attributes remains insufficiently assessed within this park. This study quantifies the multidimensional restoration of biodiversity across 125 secondary forest plots and 15 primary forest plots representing 14,731 inventoried individuals in four sectors of the park. Using a Bayesian modelling framework, we estimate recovery trajectories of Shannon diversity, floristic composition, functional traits (wood density, leaf mass per area, seed mass), and conservation-relevant species. The different biodiversity attributes recovered at contrasting rates. Diversity was restored more rapidly ({lambda} = 0.06) than floristic composition ({lambda} = 0.03), and these recovery varied according to environmental variables. Among these, the presence of remnant trees showed the highest median on diversity (0.53 {+/-} 0.61) and floristic composition (0.37 {+/-} 0.17), promoting the rapid recovery of both attributes, followed by prior land use, particularly cocoa farming which also positively influenced the recovery of alpha diversity ({lambda} = 0.03) and floristic composition ({lambda} = 0.02). Regarding functional traits, they displayed contrasting dynamics: specific leaf area and seed mass recovered rapidly along successional gradients, whereas wood density followed a more gradual recovery trajectory. From a conservation perspective, although the proportion of IUCN Red List species remained stable along the successional gradient, old-growth indicator species were significantly more abundant in primary forests. To ensure the long-term conservation of biodiversity, protecting both primary and regenerating forests is essential to preserve the ecological resilience of this park.

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.

Understanding the spatial distribution of species and their patterns of endemism is necessary for establishing effective conservation priorities. Despite the vital pollination services bees provide, Californias native bee distribution patterns remain largely unexplored relative to plants and butterflies. We analyzed bee species richness and endemism across California and their concordance with plant distributions. Richness was high across areas of the California Floristic Province, including the Sierra Nevada, San Francisco Bay Area and Central Coast, South Coast Ranges, and the Transverse and Peninsular ranges. Bee endemism was more localized, concentrated in the San Joaquin Valley, eastern Sierra Nevada and adjacent Great Basin, Sierra Nevada foothills, and California deserts. Because richness and endemism appear to operate at different spatial scales and likely respond to different environmental drivers, effective conservation strategies must address both. Additionally, conservation plans that incorporate both plant and bee diversity are needed to achieve more comprehensive biodiversity protection.

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.

Conserving migratory birds effectively requires full annual cycle strategies that identify where on-the-ground efforts can have the greatest impact. Here, we present a hemispheric spatial framework to identify priority areas for 112 migratory bird species across the Americas. Building on full annual cycle prioritizations, we defined finer-scale spatial planning units that reflect differences in migratory and congregational behaviors between shorebirds and landbirds. We compiled population data for each planning unit and focal species and applied conservation planning tools to design area-efficient portfolios of sites and landscapes that secure 10% of each species population within the Americas flyways. The resulting minimum area portfolios include 175 shorebird sites and 80 landbird landscapes optimized to meet the species-specific 10% representation targets across breeding, non-breeding, and passage seasons. We also identified a broader set of complementary solutions, ranked by an importance score, to provide decision-makers with flexible options for strategic resource allocation. This framework provides the scientific foundation for the Americas Flyways Initiative (AFI), which aims to catalyze investment in nature-based solutions and bird-friendly infrastructure to enhance the conservation of migratory birds and strengthen the resilience of the Americas flyways by 2050.

Understanding how scientific effort is distributed is essential for evaluating the evidence available to guide species conservation. We assessed the temporal, thematic, methodological, and spatial organization of jaguar (Panthera onca) research across the species range. Using 1,028 bibliographic records, we applied a metadata-based scope filter, defining a primary analytical corpus of 857 articles and an inclusive sensitivity corpus of 989. We analyzed publication growth from 1946-2024, author-keyword networks, high-specificity research-domain and methodological indicators, article-based spatial concentration across nine regions, and anthropogenic context using the Human Impact Index. Publication output increased strongly and nonlinearly, with the negative-binomial generalized additive model explaining 96% of deviance. Population and abundance, human-wildlife conflict and coexistence, and movement and connectivity were the most frequent research domains, whereas camera trapping was the most frequent methodological approach. Spatial analyses included 237 georeferenced terrestrial articles. Research was strongly concentrated in the Pantanal, Mesoamerica, and Atlantic Forest, but was underrepresented relative to range area in the Andes and Choco-Darien, Amazon, and Guiana Shield. These patterns were stable to the broader scope definition. Research concentration showed no strong association with region-wide anthropogenic pressure, although studies within several extensive regions tended to occur in more human-influenced portions than the regional average. Jaguar research therefore shows substantial growth and partial alignment with applied conservation challenges but remains geographically uneven. Expanding representative research in underrepresented regions, while maintaining work in threatened landscapes, would strengthen the evidence base for range-wide conservation planning and improve coordination among countries, institutions, and regional research traditions.

High-throughput amplicon sequencing has transformed microsatellite (STR) genotyping by overcoming many of the limitations of fragment-length analysis, enabling more accurate, cost-effective, and standardized genotyping. Yet, protocols specifically designed for high-throughput sequencing (HTS)-based STR genotyping from low-template and degraded DNA remain scarce, despite the prevalence of these challenging sample types in ecological and conservation contexts. We present a methodology for the de novo development of robust STR multiplex panels together with a laboratory protocol for efficient and reliable STR genotyping by sequencing with low quantity and quality DNA samples. The protocol comprises (i) an automated bioinformatic pipeline to design large sets of short tetranucleotide markers optimized for multiplex amplicon sequencing of degraded and low-template DNA; (ii) guidelines for efficient in vitro optimization of multiplex amplification using directly low quantity/quality template DNA; and (iii) a library preparation procedure that improves detection of low-level allele signal while enabling quality assessment of STR amplicon sequencing under limiting DNA conditions. We demonstrate the approach by developing and validating STR panels for non-invasive genotyping of three large carnivore species: a 44-plex for the grey wolf (Canis lupus), a 41-plex for the Eurasian lynx (Lynx lynx), and a 30-plex for the brown bear (Ursus arctos). Multiplex performance was high, with [≥]91% of samples successfully genotyped at [≥]50% of loci (allele size range 28-110 bp across panels) and correctly assigned to known individuals, negligible levels of noise in the controls, and high discriminatory power (PIDsibs [≤]2.4 x 1e-12), also owing to sequence variation among same-length alleles at 15-50% of loci. The approach is broadly applicable to animal and plant species, a wide range of sample types, and large-scale analysis such as genetic monitoring. Our study reinforces the value of STR amplicon sequencing for ecological and conservation applications while highlighting the importance of marker design and laboratory workflows tailored to HTS-based genotyping for accurate and efficient implementation.

The accelerated loss of biodiversity in sub-Saharan Africa threatens the functioning of tropical ecosystems. In Cote dIvoire, the Comoe National Park (PNCOMOE), a Sudano-Guinean savannah, and the Tai National Park (PNTAI), a dense rainforest, both UNESCO World Heritage Sites, are home to fauna assemblages of global importance, whose long-term resilience remains insufficiently quantified. This study assesses and compares, over a decade (2014-2025), the functional stability of vertebrate communities in these two contrasting ecosystems, using nine metrics covering resistance, invariance, persistence, interspecific synchrony, Tilmans stability, Jacobian resilience and a Composite Stability Index (CSI). Abundance data for 107 vertebrate species were collected via foot transects at PNTAI and aerial surveys at PNCOMOE. The stability metrics were calculated using the R package estar, integrated with an alpha diversity analysis (Shannon H', species richness S, Pielous evenness J') and a Jacobian spectral analysis within a multidimensional ecological assessment. PNTAI (0.708) exhibits significantly higher alpha diversity (H' = 2.82; S = 55.7 taxa) and community resilience 4.6 times higher than in the PNCOMOE (0.153). Its interspecific asynchrony index (0.504) reveals a strong portfolio effect, absent in the PNCOMOE (0.232). In contrast, PNCOMOE exhibits higher temporal invariance (0.382 versus 0.116) and Tilman stability (0.276 versus 0.152), reflecting more predictable dynamics. The overall ICS favours the PNTAI (0.484) and (0.370). The Jacobian analysis detects local instability in both parks (Re({lambda}max) = 5.58 at the PNTAI; 3.73 at the PNCOMOE). The two parks exhibit distinct yet complementary stability architectures: PNTAI relies on dynamic stability based on resilience and interspecific compensation, whilst PNCOMOE demonstrates conservative stability through temporal regularity. The absence of calculable resilience at PNCOMOE suggests a potential crossing of a functional degradation threshold, arguing for urgent restoration interventions and differentiated conservation strategies, tailored to the resilience mechanisms specific to each ecosystem.

Protected areas are vital to the recovery of endangered species. Of the 24 remaining endemic passerines in Hawaii, 16 species are endangered or critically endangered. Yet protected areas in the archipelago are changing as a result of climate change and biological invasions. For example, the non-native southern house mosquito (Culex quinquefasciatus), the primary vector of avian malaria (Plasmodium relictum), has been encroaching upward as higher elevations warm. How the ranges of endemic birds have also shifted their range upward in the Ka[u] Rainforest, the largest native forest on the Island of Hawaii, is not well understood. We used hierarchical distance sampling to characterize how population density has changed from 2002 to 2024 for eight endemic bird species in the Ka[u] Rainforest. For five species, the most parsimonious model included an interaction between year and a quadratic elevation effect. Species that were most common at lower elevations in 2002, e.g., Apapane (Himatione sanguinea), tended to be most common at mid-elevations by 2024. Species that were already most common at higher elevations, such as Iiwi (Drepanis coccinea) and Hawaii [A]kepa (Loxops coccineus), tended to decline in density. For example, Iiwi density at 1,530 m declined from 3.31 birds per ha (95% confidence interval [CI]: 2.67-4.11) to 1.34 birds per ha (95% CI: 1.05-1.71), and Hawaii [A]kepa were completely extirpated from elevations below 1,530 m by 2024. Our results demonstrate how the elevational ranges of endemic species have shifted in response to climate change, biological invasions, and habitat degradation. Translating these results into conservation measures may require a more thorough investigation of the causal mechanisms of these range shifts with finer scale habitat data, under the same hierarchical modeling framework.

Spatial overlap of domestic animals and wildlife can have positive effects such as increased biodiversity in some areas and reduction in forest fires but it can also have negative consequences such as pathogen spillover, vector and pathogen propagation into new areas among others. Thus, understanding the interactions between wildlife and domestic animals on shared landscapes is critical for conservation and management purposes. To investigate these cattle-wildlife interactions, we chose Buck Island Ranch (BIR) in southcentral Florida. We studied spatial overlap between Domestic Cattle (Bos Taurus) and multiple wildlife species such as Wild Boar (Sus scrofa), White-tailed Deer (Odocoileus virginianus), Rabbits (Sylvilagus spp) and others in pasture, semi-pasture, and hammock habitats/vegetation types at BIR. Five management blocks were selected that had pasture and hammock habitats and within each block we established matched pairs of 100m transects. Animal dung samples were surveyed and identified in 13 pairs of transects. We used Wilcoxon signed rank test to determine differences in dung counts between the habitats and calculated Simpson diversity index to analyze the differences in diversity between the habitat types. We found that there was greater dung count of white-tailed deer in hammock habitats compared to pastures (p=0.048) and greater diversity of wildlife in hammocks than pastures (p=0.028). Cattle dung was found in high density in both hammocks and pastures. These results indicate that hammocks are areas shared between cattle and wildlife at BIR and depending on the extent of direct and indirect contacts between these animals there can be a risk for pathogen spillover. We recommend further research on local land and cattle management practices that can facilitate the co-existence of livestock and wildlife.

Wildlife monitoring in arid environments is complicated by substantial temporal and spatial variation in animal activity driven by unpredictable environmental conditions. For highly mobile species, movements across the landscape may further influence activity recorded at fixed monitoring locations, raising questions about whether short-term surveys adequately represent patterns of site use. We examined temporal variation in acoustic activity of the threatened Pilbara Leaf-nosed Bat (Rhinonicteris aurantia Pilbara form), a highly mobile, cave-roosting insectivorous bat inhabiting the arid Pilbara region of north-western Australia. Acoustic activity was monitored continuously at two permanent diurnal roosts for up to two years, comprising 1601 detector-nights across three detector locations. We tested relationships between nightly activity and environmental conditions, detector location and anthropogenic disturbance. Activity varied substantially through time and among detector locations. Moon illumination and cumulative rainfall were strongly associated with activity, but their interaction differed between roosts: activity was highest under low moon illumination and low cumulative rainfall at Chateau Cave, whereas activity at Daltons was highest under low moon illumination and higher cumulative rainfall. Activity also differed markedly between detector positions within Chateau Cave, and humidity, temperature and artificial light at night had additional location-specific effects. Other measures of anthropogenic disturbance, including cave entry, blasting and mining activity, had comparatively weak support. The contrasting environmental relationships among locations demonstrate that acoustic activity at permanent roosts is strongly context dependent. For a species capable of extensive movements among roosts, temporal variation in activity may reflect behavioural responses and redistribution of individuals across the landscape rather than rapid demographic change. We suggest that facultative nomadism may provide a useful hypothesis for understanding temporal variation in roost use by Pilbara Leaf-nosed Bat. More broadly, our results demonstrate that short-duration acoustic surveys of highly mobile species in arid environments may provide an incomplete representation of longer-term site use and should incorporate temporal replication and environmental context when used for conservation and impact assessment.

Reliable population estimates are essential for wildlife management, yet monitoring schemes often do not match the administrative scale at which decisions are made. We illustrate this challenge using the Eurasian lynx in the canton of Valais, Switzerland, where official state monitoring is fragmented across three reference areas surveyed in different years. We analyzed three winters (2023-2026) of independent, canton-wide camera trap data, recording 899 independent lynx captures (27, 31 and 34 adults per winter). Lynx distribution and reproduction concentrated in the Northwest and connected to the thriving Pre-alpine populations. Density modelling for 2025/2026 estimated 37 independent lynx (95% CI: 26-52) on the whole cantonal territory, corresponding to a density of 1.09 (0.77-1.56) individuals per 100 km2. These estimates are substantially below the figures improperly extrapolated from a cross-cantonal reference area and conveyed by political authorities. Future lynx management decisions should be rooted in scientifically sound, scale-relevant information.

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.

Assessing breeding phenology using singing intensity can potentially provide insights into a species' responses to climate or habitat change. Although male passerines are known to sing elaborate songs during the breeding season, females of several tropical passerines also sing. The Nilgiri Flycatcher (Eumyias albicaudatus) is an endemic dimorphic songbird found in the southern Western Ghats of India. Despite its limited distribution and its ecological significance as an indicator species of cloud forests, very little is known about its vocal behaviour and breeding ecology. To examine sex-specific differences in vocalisation patterns, we analysed 294 male and 102 female focal songs from two pairs of birds. We then used data from a year-long automated recorder placed near a breeding pair to study the species' singing phenology using the BirdNET Analyser. The two sexes broadly produced similar songs, although males' songs included more notes at a faster pace. The sex-specific detectors failed due to this high similarity among songs of the two sexes, but we were able to automate species-level detection (F1-score = 0.795 at a confidence threshold of 0.1). We found strong seasonality in vocal activity, with peaks in singing during the breeding season, and identified a diurnal peak at dawn. More data are required to parameterise differences in annual vocal activity between the sexes. These detection patterns provide a framework for a landscape-wide examination of Nilgiri Flycatcher phenology and occurrence. This study suggests that automatic detectors can be a reliable tool for assessing singing phenology in birds and provide insights into breeding periods.

The global market concentrates extractive pressure on lands held by Indigenous peoples, including peoples living in isolation, for whom free, prior and informed consent cannot be obtained and protection must therefore rest on territorial instruments. Halmahera, Indonesia, holds some of the worlds largest lateritic nickel reserves beneath a lowland rainforest inhabited by the Hongana Manyawa, yet the trajectory of land use and cover change across the island has not been quantified. We characterised land use and cover change over the 17,437 km2 island between 2014 and 2024 using MapBiomas time series, and projected a business-as-usual scenario to 2054 with a stochastic cellular-automata model implemented in Dinamica EGO, calibrated with weights of evidence on eight variables describing mining and logging concessions, transport infrastructure, settlements and previous clearing. Forest covered 83.0% of the island in 2014 and 82.1% in 2024; under unchanged policy it falls to 73.7% by 2054, a net loss of 162 thousand ha, or 11.2% of the 2014 baseline, at gross rates of 47,000-51,000 ha per decade. Deforestation probability is highest within 500 m of previous clearing and declines with distance from settlements, cities and mining sites, while proximity to national parks carries a negative weight of evidence. The frontier is self-propagating and spatially predictable, and legally designated territory retains forest within it. Protecting the Hongana Manyawa consequently depends on excluding extractive licensing from the interior forest ahead of the frontier rather than behind it.

Gray fox (Urocyon cinereoargenteus) populations in the Midwestern USA have suffered precipitous declines in recent decades, yet they are relatively understudied. However, understanding survival and cause-specific mortality is vital for declining populations and the limited existing survival studies have been performed outside of the Midwest. We equipped 13 gray foxes in southern Illinois with GPS radio collars to investigate their survival and cause-specific mortality. We calculated the Kaplan-Meier 6- and 12-month survival rates to be 0.79 (95% CI: 0.57-1.0) and 0.53 (95% CI: 0.27-1.0), respectively. We recorded 4 mortalities: 1 disease, 1 gunshot, and 2 unknown causes. While our study has a small sample size, it contributes key information on a data-deficient mesocarnivore suffering from a population decline driven by undefined causes. We recommend further research into the survival and mortality of this elusive mesocarnivore.

Predation is a major selective force shaping lemur behaviour and population dynamics, yet direct observations remain rare, particularly for small nocturnal species. Here, we document predation on mouse lemurs (Microcebus spp., Cheirogaleidae) in Andohahela National Park, south-eastern Madagascar, and using complementary evidence from radio-telemetry and owl pellet analyses. Two radio-collared individuals were confirmed as prey of endemic snakes, Ithycyphus oursi and Madagascarophis meridionalis (both Pseudoxyrhophiidae), representing the first documented records of Microcebus predation by these species. Examination of owl pellets and prey remains from three sites and from three owl species revealed a single predation event by Asio madagascariensis (Strigidae), likely involving M. tanosi, no evidence of mouse lemur predation by Tyto alba (Tytonidae) despite high local prey availability, and a single and first predation record from Athene superciliaris (Strigidae). Material from A. superciliaris roosts was otherwise dominated by invertebrates, indicating that primate predation is likely opportunistic. Together, these findings expand the known predator guild of mouse lemurs and suggest that snake predation is rarely detected, and its contribution to mouse lemur mortality and population dynamics is likely underestimated. Our findings demonstrate how combining behavioural field observations with dietary evidence can uncover otherwise undetected predation events and clarify predator prey relationships in nocturnal primates.

Citizen science data are increasingly used to infer biodiversity change, but causal claims based on such data are credible only if sampling effort and its temporal shifts are explicitly modeled. Zhang et al. (1) used citizen science data to conclude that greater photovoltaic policy stringency, measured using the photovoltaic policy stringency index (PSI), reduced county-level bird diversity in China. We reproduced their fixed effects and instrumental variable estimates. However, the observed Shannon diversity derived from pooled citizen science records reflects both bird communities and sampling effort, which the authors' controls do not adequately capture. Accounting for observer count changed the reported statistically significant 2.10% decline in Shannon index to a nonsignificant 0.58% increase (P = 0.288) per one-standard-deviation increase in PSI, and rendered the instrumental variable estimate statistically indistinguishable from zero (P = 0.912). Yet observer count is only one of many sources of sampling bias. PSI was also associated with multiple dimensions of sampling effort, consistent with sampling effort acting as a potential mediator in the PSI-diversity chain. The sampling domain also shifted markedly from 2014 to 2023: recorded county-months increased almost 24-fold, median observer count rose from one to three, and zero-duration records declined from 57.2% to 0.17%. Without adequate adjustment, these shifts confound estimates of temporal change in observed bird diversity. Beyond its inadequate treatment of sampling effort, the original study also misinterpreted its statistical results. Although the reported R{superscript 2} values are high, they are dominated by county and year-month fixed effects, with PSI contributing a partial R{superscript 2} of only 0.048% on observed Shannon index. The PSI-photovoltaic-area correlation is also weak (r = 0.0414) and vanishes after accounting for fixed effects (P = 0.977). Furthermore, the released bird observation data contain many erroneous outliers, raising significant concerns about insufficiently rigorous data preprocessing and quality control. These results show that the released data cannot properly distinguish ecological change from sampling effort change. Robust inference from citizen science data requires checklist-level effort metadata, explicit correction for spatiotemporal sampling shifts, and close collaboration among researchers with complementary methodological and ecological expertise.