Ecological Indicators

Passive acoustic monitoring (PAM) is increasingly applied in biodiversity research, yet its reliability as a proxy for biodiversity remains insufficiently evaluated. In particular, the spatiotemporal autocorrelation inherent in acoustic indices of PAM is rarely quantified, despite its importance for the standardized application of acoustic monitoring. We conducted an integrated study to investigate these issues using a complete grid-based monitoring system covering the entire region (100 grids of 1 km x 1 km) in southern subtropical climatic zones. Acoustic data from 58 valid sites were combined with camera-trapping and vegetation surveys to evaluate six commonly used acoustic indices in PAM. We found that these indices were more strongly associated with relative abundance and community diversity metrics of bird and mammal than with species richness. Spatially, autocorrelation ranges of some acoustic indices extended to approximately 4 km (i.e., the Bioacoustic Index (BIO) and Normalized difference soundscape index (NDSI)). Temporally, all indices exhibited significant autocorrelation over 2-5 days, exceeding the typical short-term turnover of bird and mammal activity (1-2 days). Our results indicate that acoustic indices are not direct proxies for species richness but provide complementary information on soundscape dynamics. By explicitly quantifying spatiotemporal autocorrelation, this study offers practical guidance for sampling design and statistical analysis in passive acoustic monitoring, supporting more reliable and efficient biodiversity assessment.

Field-based monitoring of tree species in forests is often sparse due to logistical constraints. Remote sensing enables repeated, spatially contiguous collection of reflectance data across large areas. Tree species classification accuracy using such data is variable, likely because most studies use observational datasets where species occurrence correlates with environmental variation. We used two sites of a tree biodiversity experiment in Germany (BIOTREE: Kaltenborn and Bechstedt), where different species have been planted with high replication under controlled diversity levels, to assess how well tree species could be classified using reflectance data from airborne imaging spectroscopy and different classification methods (linear discriminant analysis, LDA, and a non-linear support vector machine, SVM). Reflectance data for 589 wavelengths between 400-2400 nm were acquired at 1 m spatial resolution during peak growing season. Reflectance spectra showed large and significant variation between taxonomic classes, orders, and species, and weak, but still significant, interactions between classes or orders and diversity levels. Classification accuracy reached 100% in training datasets, 77%-83% for the four species in Kaltenborn prediction datasets, and 31%-49% for the 16 species in Bechstedt prediction datasets. LDA provided more accurate predictions than SVM; and using similarly-spaced original wavelengths with LDA was as efficient as using principal components derived from the original data. While airborne imaging spectroscopy effectively distinguished up to four tree species in our datasets, classification accuracy was lower in more species-rich plots. In these cases, the methodology may be more useful for functional diversity monitoring than for tree species classification.

Coral restoration is recognised as a critical tool to mitigate pantropical degradation of reef ecosystems. Robust monitoring of restoration progress is crucial for projects to evaluate their success, improve practice, and share knowledge. However, traditional visual surveys often fail to capture the full impact of coral restoration on reef function. Therefore, we employed Passive Acoustic Monitoring (PAM) to assess whether the soundscape of a coral restoration site in the Seychelles differs from adjacent healthy and degraded reference reefs. We applied two methods of soundscape analysis: manual detection of unidentified fish sounds; and machine learning-based Uniform Manifold Approximation and Projection analysis. Results were approach-specific: the manual approach highlighted similarities in fish calls between the restoration site and the healthy reference reef, while the machine learning approach extracted broader soundscape patterns, clustering the restoration site alongside the degraded reference reef. Although this is a single-site study, these findings suggest that a) coral restoration alters reef soundscapes, though recovery time may be taxon-specific, and b) multiple metrics are needed to bridge single-taxon and broad soundscape scales. This study contributes to the evolving field of soundscape ecology in coral reef ecosystems, highlighting the utility of PAM in monitoring changes to reef function through coral restoration.

Passive acoustic monitoring (PAM) enables non-invasive sampling of wildlife across broad spatial, temporal and taxonomic scales. Its ongoing and widespread use has generated unprecedented volumes of acoustic data, shifting the primary bottleneck from data collection to the storage, processing, integration, and interpretation of PAM outputs. Although many software tools exist to address these challenges, differences in their design, scope, and usability often create fragmented and complex analytical workflows. To identify the key barriers and opportunities shaping the implementation of PAM surveys, we conducted a structured expert solicitation involving 30 international practitioners working across terrestrial and aquatic ecosystems. Experts identified and ranked their most critical pain points in current PAM workflows, spanning data storage, processing, and interpretation. The top challenge identified related to accurate species identification using deep learning and artificial intelligence (AI) models, especially in noisy soundscapes or for underrepresented taxa. Eight additional priority challenges included workflow fragmentation, limited availability of user-friendly analytical and visualisation tools, uneven access to software, manual validation bottlenecks, computational constraints, and difficulties in data handling, standardisation, and sharing. Participants also proposed practical mitigation strategies for these priority challenges, supported by step-by-step guidance to help overcome key barriers. Together, these insights provide a roadmap toward more scalable, open-access, and collaborative software systems, which are increasingly essential to realise the full potential of PAM in global biodiversity monitoring.

Agriculture has modified the soil structure due to the influence of external factors and processes that affect microbial biodiversity. Metagenomics is a fundamental tool for the study of soil microbial diversity because it provides information about the ecosystem diversity, including both the microorganisms that cannot be isolated in culture media and those that are no longer viable in the analyzed sample. In this work, six soil samples obtained from agroecosystems of central and northern Argentina were subjected to a preliminary 16S metagenomic analysis. Copiotrophic bacteria (Proteobacteria and Actinobacteria) were dominant and one of the samples had a dominance of an oligotrophic Phylum (Acidobacteria). Our findings support previous evidence from traditionally managed agroecosystems and provide new insights into the diversity of soil microbiomes in Argentine regions outside the Pampas. Finally, we analyzed the most common genera with relevant species to agronomy, both beneficial and pathogenic, and their abundance and diversity in the sequenced samples.

Global biodiversity is declining at an unprecedented rate due to rapid environmental change and increasing human pressures. Ongoing urban expansion fragments natural systems, while urban design increasingly seeks to mitigate these impacts through the integration of blue-green infrastructure. Effective biodiversity monitoring is therefore essential to evaluate ecological conditions within these novel socio-ecological systems. Although urban biodiversity monitoring is challenged by its high landscape heterogeneity, dense human populations provide opportunities for large-scale data collection through public participation in citizen science. Using data from 25 City Nature Challenge (CNC) projects across the United Kingdom (2020-2025), we assessed the effects of the four-day bioblitz on species inventories, participation in biological recording, and spatial patterns of recording effort. CNC events doubled public participation in iNaturalist recording relative to baseline activity, leading to the documentation of numerous previously unrecorded species through increased observer effort and broader use of urban blue-green spaces. These results show that CNC events enhance urban biodiversity datasets by increasing the number of observers and reducing spatial and observer biases, providing a cost-effective tool for enriching urban biodiversity data. In addition to generating ecological data, CNC events could have public health benefits through increased exposure to urban blue-green spaces.

Artificial pond construction is widely used in wetland restoration, yet biodiversity outcomes depend strongly on design and subsequent management. We tested how different regimes (grazing, mowing, and no management) influence habitat structure, water conditions, and aquatic macroinvertebrate diversity in newly excavated experimental ponds within an eutrophic wetland in South Moravia (Czechia). Across four focal groups (Mollusca, Odonata, Coleoptera, Heteroptera), we observed rapid colonisation of the newly built ponds. Species richness and densities rose during early development, dropped after drying events, and then partially recovered, indicating repeated "resetting" of communities under fluctuating hydrology. Periodic drying also prevented fish stock establishment. Management significantly affected species composition and both grazed and mowed ponds displayed higher densities (abundances) than controls, but differed only slightly in terms of species richness. The grazed ponds were characterised by high sunlight exposure, reduced reed dominance, and trampling-generated high littoral heterogeneity. These ponds showed highest numbers of taxa adapted to shallow and warm waterbodies, muddy substrate, semiaquatic microhabitats, or newly emerged and disturbed habitats. The mowed ponds promoted dense submergent vegetation, supporting Odonata representation and other taxa requiring aquatic vegetation. The control ponds remained highly shaded by high-grown reed, organic-matter rich, hosting a set of taxa tolerant of low-light, low-oxygen conditions. At the wetland scale, multiple small ponds increased overall diversity through high between-pond heterogeneity. Our results highlight that pond construction alone is insufficient for wetland restoration: follow-up long-term management regimes, especially extensive grazing, can rapidly generate structural heterogeneity and sustain diverse aquatic invertebrate assemblages in eutrophic wetlands.

Astyanax Baird & Girard, 1854 is a widely distributed and species-rich genus of Acestrorhamphidae, whose abundant populations in Neotropical basins play a crucial ecological role at the trophic level. Taxonomic uncertainties persist within the genus, as seen in Astyanax sp. (formerly designated as A. fasciatus) from the Magdalena basin in Colombia. Concerns about its genetic status are heightened due to ecological threats posed by hydroelectric dams, from habitat loss to river connectivity. We isolated and characterized 17 microsatellite loci to assess the population genetics of this species in a broad sample from the middle and lower sections of the Cauca River, now interrupted by the Ituango dam. Furthermore, a multidisciplinary approach integrating phylogenetic analyses of mitochondrial (COI) and nuclear (rag2) markers with geometric morphometric analyses was employed to evaluate potential cryptic diversity within Astyanax sp. Microsatellites revealed two genetic groups in the studied area, strongly supported as distinct lineages by phylogenetic analyses. Unexpectedly, one of these lineages of Astyanax sp. was recovered in an unresolved clade with samples of A. microlepis and allopatric samples of A. viejita from the Maracaibo Lake basin. Each genetic group showed high genetic diversity, but also evidence of recent bottleneck events and significant-high values of inbreeding. Morphometric analyses provided evidence of significant phenotypic differentiation among A. microlepis, Astyanax sp. 1 (Asp1), and Astyanax sp. 2 (Asp2). Morphological patterns ranged from the robust profile of A. microlepis to the streamlined shape of Astyanax sp. 2 (Asp2), with Astyanax sp. 1 (Asp1) displaying intermediate traits and localized differences in head length and fin placement. Statistical support from permutation tests and a high overall classification accuracy (95.65%) underscore the existence of distinct morphospecies, suggesting that phenotypic differentiation is well-established, despite the complex evolutionary history of the group. This study suggests the presence of cryptic diversity within Astyanax sp. and provides valuable genetic information for the conservation and management of their populations in the Magdalena basin.

AimFreshwater species face significant challenges from direct and indirect anthropogenic impacts, leading to a global decline in freshwater biodiversity. Protected areas are a key tool for conservation, but their effectiveness in covering freshwater biodiversity remains uncertain. This study assesses the protection coverage of freshwater macroinvertebrates, vertebrates, and macrophytes in Cuba against the 17% and 30% conservation targets set by the Convention on Biological Diversity. LocationCaribbean biodiversity hotspot, including freshwater ecosystems across the Cuban archipelago. MethodsWe analyzed the distribution of 182 freshwater macroinvertebrates, 26 vertebrates, and 19 macrophyte species using an ensemble of four species distribution modeling techniques: Maxent, Boosted Regression Trees (BRT), Random Forest (RF), and Spatial Stream Network (SSN). We evaluated species overlap with Cubas current protected areas and conducted spatial conservation prioritization exercises that (i) included (lock-in) and (ii) excluded (free-choice) existing protected areas. ResultsOur analysis revealed that 41% (90 species) and 71% (161 species) failed to meet the 17% and 30% conservation targets, respectively. Many of the insufficiently protected species are globally threatened or endemic to the Cuban archipelago, heightening their extinction risk. Conservation planning that includes current protected areas requires significantly larger areas to meet the 30% representation target due to redundancy in existing protections. Conversely, excluding current protected areas achieves conservation goals more efficiently with fewer resources. Both approaches highlight the need to improve connectivity, particularly in upstream regions that are often neglected under the current protected area configuration. Main conclusionsFreshwater biodiversity in Cuba is poorly represented within existing protected areas. Meeting the 30% conservation target would require protecting an additional 30-70% of area, with a focus on headwaters and underrepresented taxa. Expanding Cubas National System of Protected Areas (SNAP) to prioritize fresh-water species, particularly endemics, is essential. A spatial conservation planning approach that integrates both lock-in and free-choice strategies can optimize resource use while enhancing connectivity across key rivers and tributaries.

Tropical coral reef ecosystems worldwide are being impacted by combined pressures of climate change and human activities that introduce large quantities of nutrients and sediments into coastal areas. In this context, phytoplankton represent a critical link between dissolved inorganic nutrients and coral reef food webs, yet their role in these ecosystems remains understudied. We investigated ecological responses of the summer phytoplankton community of Shiraho Reef (Ishigaki Island, Okinawa, Japan) to nutrient enrichment using field-based microcosm experiments under natural light and temperature conditions in September 2022 and 2023. Treatments included single and combined additions of nitrogen, phosphorus, and silicon. Chlorophyll a (Chl a) concentrations increased after three days under combined nutrient conditions, whereas single-nutrient additions produced limited responses, indicating a strong co-limitation by nitrogen and phosphorus in the reef. Analysis of size-fractionated Chl a revealed shifts from picophytoplankton that typically dominate tropical oligotrophic ecosystems toward larger groups supported by enhanced nutrient availability. Our results show short-term impacts of nutrient enrichment events on phytoplankton size structure and biogeochemical cycling in coral reefs, and highlight the importance of pelagic processes in coral reef carbon dynamics under nutrient-enrichment.

The rising demand for outdoor recreation worldwide may be undermining the conservation objectives of protected areas (PAs). We leveraged a natural experiment, in which two adjacent PAs were closed to the public for different durations during the COVID-19 pandemic. Using detections from 39 camera traps in Joffre Lakes and Garibaldi Parks, Canada, from 2020-2022, we examined how recreation influenced mammal habitat use and diversity. Bayesian regression showed weak evidence that, when recreation was higher, detections declined for black bear, mule deer, and marten, while detections of bobcat and hoary marmot shifted closer to trails. Accumulation curves revealed that species richness and diversity were higher in the closed vs. open PA in 2020 (mean differences of -5.04 for richness and -0.33 for Shannon diversity). However, diversity did not decline consistently despite increases in recreation in 2021 and 2022. Notably, several rare species were only detected in the lower-recreation PA, suggesting they may be filtered out of the higher-recreation PA. This emphasizes the need for long-term monitoring to detect delayed and cumulative effects of recreation on mammal communities. Given growing global pressures on biodiversity, we urge PA managers to prioritize adaptive management to assess and balance outdoor recreation with conservation goals.

Mountain ecosystems face unprecedented pressures from anthropogenic activities and climate change, challenging the productivity of these vital habitats. In the Tien Shan mountains, understanding localized responses to these pressures is often hindered by the coarse spatiotemporal resolutions of available data. To address this, we combined high-resolution satellite imagery (1997-2021) to map land-cover dynamics in the Naryn oblast, Kyrgyzstan across a gradient of grazing intensities. We classified and quantified land-cover distribution over 24 years, investigating the roles of topography, elevation, and anthropogenic disturbances as drivers of change. Our results identify intermediate elevations, high degrees of disturbance, and the interaction between the two as the primary contributors to recent transitions in grassland, forest, and barren habitats. By integrating Landsat analysis-ready data, European Space Agency WorldCover dataset and digital elevation models at fine spatial scales, we provide valuable contemporary and historical landscape and habitat-level insights and a high-resolution framework for disentangling climate-driven shifts from land-use impacts. These findings highlight the urgency of localized management in remote, data-poor regions where rapid environmental change threatens both biodiversity and pastoral livelihoods. Our work serves as a critical baseline for characterizing the adaptability of semi-arid mountain rangelands under escalating global and regional pressures.

Mesic resources, the late-season herbaceous vegetation found in riparian areas and wet meadows, provide disproportionately important forage and habitat across western U.S. rangelands, yet their response to climatic variability and anthropogenic influences remains poorly understood. Using a 40-year Landsat time series (1984-2024), we quantified trends in late-season productivity (NDVI) across 4.5 million hectares of the sagebrush biome and applied random forest models to distinguish between temporal and spatial predictors of mesic resource productivity. We identified a fundamental shift in how mesic resources respond to drought: from 1984 to 2004, mesic productivity was strongly correlated with drought severity (Palmer Drought Severity Index, R{superscript 2} = 0.92), but this relationship weakened substantially in the next two decades (2005-2024; R{superscript 2} = 0.28), during which time productivity increased despite persistent aridity. Temporal modeling identified rising atmospheric CO2 concentrations as the strongest predictor of this shift, consistent with enhanced plant water-use efficiency under CO2 fertilization. Spatially, large agricultural valley floodplains act as anthropogenic refugia, sustaining productive mesic resources through flood irrigation and subsequent groundwater recharge into late summer. These findings suggest that human water management and physiological shifts in vegetation are currently buffering mesic systems against meteorological drought throughout U.S. rangelands. However, this apparent buffering is spatially heterogeneous and may mask vulnerability to groundwater depletion, shifts in precipitation regimes, and woody encroachment. Sustaining these vital ecosystems will require conservation approaches that go beyond climate monitoring to include balanced management considering both agricultural and ecological water needs and constraints.

Vessel-whale collisions are a growing global concern and remain challenging to quantify. Therefore, the use of proxies, such as Close Encounters (CEs) that comprise Surprise Encounters (SEs) and Near-Miss Events (NMEs), has been proposed and widely employed to assess collision risk. To better understand this risk in the Eastern North Atlantic, where maritime traffic is intensive, this study aimed to redefine and quantify CEs, and to assess detectability-related variables that may affect CE identification. CEs were assessed using a cetacean occurrence dataset collected between 2012 and 2024 on board cargo ships and oceanographic vessels. CEs thresholds were redefined based on Time to Potential Collision (TPC), rather than distance alone (as described in literature), to allow a more dynamic, risk-based, and speed-sensitive approach. In total, 1226 sightings of whales (baleen, sperm, and beaked whales) were recorded, of which 37.4% were classified as SEs and 2.0% as NMEs. The sperm whale, Physeter macrocephalus, was the species most frequently involved in CEs (13.9% of all CEs), followed by the Cuviers beaked whale, Ziphius cavirostris (11.8%). A Generalized Additive Model was used to assess the influence of detectability-related variables (i.e., meteorological conditions, whale taxa, vessel characteristics, and Marine Mammals Observers (MMOs) experience) on TPC. Significantly lower TPC values were observed with beaked whales, cargo ships, poor visibility conditions, and less experienced MMOs. The results of this study provide an CEs assessment in this region and contribute to the ongoing efforts to standardize CE quantification, by using TPC as a metric. This work also highlights the importance of decreased speeds and the presence of experienced MMOs on board to increase detection probability and TPC, thereby potentially minimizing collision risk.

The invasiveness risk of 15 non-native freshwater fish species established in the lower Tigris Basin (south-west Iran) was evaluated for Shadegan International Wetland and associated catchments of the Jarrahi and Karun rivers by integrating risk screening with species distribution modelling. Risk identification under both current and projected climate conditions indicated that most taxa pose elevated invasion risk, with 13 species ranked as high risk and two as medium risk under the Basic Risk Assessment, and 11 as high risk, three as medium risk, and one as low risk after incorporating climate change effects. The highest scoring species were redbelly tilapia Coptodon zillii, blue tilapia Oreochromis aureus, and Nile tilapia O. niloticus, each with outcome scores exceeding 40 under both screening components. Species distribution models for these taxa showed good predictive performance and indicated broad climatic suitability across the lower basin, with projections based on non-native occurrences suggesting a substantially wider potential distribution than projections based on native range data. Collectively, these findings indicate a high likelihood of continued spread and ecological impact within this internationally important wetland system and support the need for coordinated transboundary management to strengthen monitoring, early detection, rapid response, and strategic control of potentially invasive species.

Fuel availability and fuel dryness are consistently shown to be the primary drivers of wildfire intensity and burnt area. Here we hypothesise that differences in the timing of fuel build up and drying determine the optimal time for wildfire occurrence. We use gross primary production (GPP) as a measure of biomass production and hence fuel availability, and vapour pressure deficit (VPD) as a measure of fuel drying. We use the phase difference in the seasonal time course and magnitude of GPP and VPD to cluster regions that should therefore have distinct wildfire behaviour. We then show that each of the resultant clusters is distinctive in terms of one or more fire properties, specifically number of ignitions, burnt area, size, speed, duration, intensity, and length of the wildfire season. The emergence of distinct regimes as a function of two biophysical drivers reflects the fact that both vegetation and wildfire properties are a consequence of eco-evolutionary adaptions to environmental conditions. We then examine the degree to which human activities or vegetation properties modify these fire regimes within each of these clusters. Variability in GPP and VPD largely explains the within-cluster variation in fire properties. The type of vegetation cover has an influence on burnt area and carbon emissions in particular, while human activities are more important for fire properties such as size, rate of spread and duration largely through their influence of landscape fragmentation. Although both human activities and vegetation properties modify wildfire regimes, the ability to distinguish wildfire regimes using GPP and VPD alone emphasizes that land management, fire use and fire suppression are constrained by environmental conditions. This eco-evolutionary optimality approach to characterising wildfire regimes provides a basis for designing a simple fire model for Earth System modelling.

The north coast of mainland Portugal supports a strong dolphin presence and extensive fishing activity, increasing the likelihood of interactions, such as bycatch. This study provides an initial assessment of potential conflict areas, using automatic identification system (AIS) data from Global Fishing Watch. To this end, sighting data from the ATLANTIDA project (2021-2024) on the common dolphin (Delphinus delphis) were used to describe spatiotemporal patterns of occurrence and encounter rates, and to predict their association with fishing effort to identify and map areas of potential overlap. A generalised additive model (GAM) was then applied, integrating environmental, spatial, temporal, and fisheries-related variables to identify the main predictors of species occurrence. Common dolphins were frequently observed during the summer, with an average encounter rate of 3.662 sightings/km. This high encounter rate may be associated with factors such as sea surface temperature, diet, and purse seine fishing activity. The maps showed a spatial overlap between fishing grounds and areas of common dolphin occurrence. Fishing effort was nearly identical between locations with sightings (2.00 h/km{superscript 2}) and those without (1.62 h/km{superscript 2}), suggesting that dolphins are not actively avoiding fishing areas but may instead frequent them due to shared habitat preferences. The best-fitted GAM indicated that encounters were related to year, latitude, fishing effort, depth, sea surface temperature, and season. There was an increase in occurrence over the years and a decrease with increasing fishing effort and sea surface temperature, possibly linked to changes in prey availability, although broad confidence intervals warrant cautious interpretation. Despite some limitations encountered in this study, we believe our findings provide valuable insights into the relationship between dolphin occurrence, environmental conditions, and fishing activities in the area, establishing an important baseline for future conservation and fisheries management efforts.

The effects of the selection of livestock type (e.g., sheep or cattle) and grazing intensity on the soil seed bank of sand grasslands of conservation interest were studied. 25 grazed grassland sites classified into four grazing intensity categories were studied. The soil seed bank was analysed by seedling emergence; germinated seedlings were classified into morpho-functional, social behaviour type (SBT) and CSR strategy groups. The following hypotheses were tested: i) Diversity and density of soil seed banks are lower in sheep-grazed sites than in cattle-grazed ones. ii) The species composition, diversity, and density of the soil seed banks are more strongly affected by grazing intensity than by the livestock type. iii) Leaf traits, SBT and CSR strategy composition are highly affected both by livestock type and grazing intensity. The main effect of livestock type only affected seed bank density, while that of grazing intensity had a significant effect on most of the variables. Most of the studied variables were affected by the interaction of grazing intensity and livestock type. Total seed bank density was lower at all grazing intensity levels in sheep-grazed sites than in cattle-grazed ones, especially close to frequently visited places. We found that sheep grazing sustained a much lower total seed bank density and lower density of species of natural and semi-natural habitats regardless to the grazing intensity. Thus, livestock type must be carefully selected and high-intensity sheep grazing should be avoided in the long-run when managing sand grasslands. HighlightsO_LIThe soil seed banks of sheep and cattle grazed sand grassland were studied C_LIO_LIEffect of grazing intensity found the most important driver of seed bank diversity and density C_LIO_LIThe total soil seed bank density was higher in cattle than sheep grazed sites C_LIO_LIBoth intensity and livestock type must be considered in the grassland management planning C_LIO_LIHigh intensity sheep grazing should be avoided in sand grassland management C_LI

Wind has a strong influence on the flight characteristics, movements, energetics, demography, life-history traits and biogeography of flying animals. With climate change affecting atmospheric circulation patterns at different time scales, understanding the links between wind and animal movements is crucial for predicting its impact on flying biodiversity. Most studies on the relationship between wind and seabird movements have, however, focused on local scales, exploring birds perceptive sensitivity to local wind. In this study, we examine low-level wind pattern oscillations in the Southern Indian Ocean at multiple time scales to explain the local- to large-scale movements of the Amsterdam albatross. Adult individuals exhibited smooth trajectories, strongly correlated with seasonal, intra-seasonal or interannual wind oscillations. Conversely, younger individuals displayed more erratic and exploratory movements, often being swept away by eastward moving low-pressure systems at a synoptic time scale. Our results suggest that Amsterdam albatrosses can learn and adapt to the annual and monthly low-level wind climatology and interannual variability of the Southern Indian Ocean. This also highlights the importance of investigating seabird movements in relation to broader-scale wind patterns to support their conservation in a changing climate due to human activities. A robust assessment of regional circulation response to climate change for upcoming decades could help project the impact of climate change on seabird movements and mitigate its effects.

Reliable freshwater access drives terrestrial wildlife movements and habitat use globally. The small, rain-fed seasonal pools critical for dryland wildlife persistence are vulnerable to rising temperatures and unstable precipitation regimes projected under climate change. In southern Africa, which is expected to warm rapidly by 2100, the drying and disappearance of surface water may cause a breakdown in seasonal migrations of large, area-sensitive, and water-dependent wildlife species. Furthermore, the disappearance of ephemeral water may concentrate wildlife around remaining surface water, increasing resource competition and human-wildlife conflict. An accurate understanding of the dynamics and drivers of seasonal surface water will therefore be critical to wildlife and human health as climate change intensifies. Here, we present a framework and empirical analysis of fine-scale surface water mapping in the 520,000km2 Kavango Zambezi Transfrontier Conservation Area (KAZA), the worlds largest terrestrial conservation area. From 2019-2025, we implemented Otsu thresholding on median Automated Water Extraction Index imagery from 10m Sentinel-2 MSI, leveraging high wet season contrast between vegetation and water as a dry season positive mask. We created >35 quasi-monthly KAZA-wide Ephemeral Surface Water (ESW) rasters (mean classification accuracy 87%, compared to 50% accuracy for existing water products), and found wet season precipitation drivers of non-riparian water fill levels did not extend into the dry season. Then, using GPS data from 27 African savanna elephants (Loxodonta africana), which typically visit water every 48 hours, we compared elephant water visitation rates based on ESW to existing 30m Global Surface Water (GSW) maps. Models using ESW estimated 99% of elephant data came within a 48-hour window, compared to 42% for GSW, suggesting that ESW is a better proxy for actual wildlife water use in animal movement modeling. As aridification threatens to diminish surface water resources, we must model the drivers of wildlife movements at the scale of wildlife needs. With ESW, we provide fine scale accessible surface water data and a straightforward coding architecture for applications beyond KAZA.