Conservation Science and Practice

This study examined the spatial distribution of potential human encounters with dangerous large mammals in and adjacent to the Ifakara-Lupiro-Mang'ula Wildlife Management Area (ILUMA WMA) and Nyerere National Park (NNP) in southern Tanzania. Using published survey data collected over one year, this secondary analysis focused on four potentially dangerous large mammals: elephant (Loxodonta africana), buffalo (Syncerus caffer), hippopotamus (Hippopotamus amphibius) and hyena (Crocuta crocuta). Potential encounter risk was estimated using overlap indices based on co-occurrence of signs of wildlife and human activities. Potential encounter risk was found to be concentrated around readily identifiable foci within the study area and differed between species and distinguishable human livelihood activities. Potential for encountering the two most apparently important dangerous animals, elephant and buffalo, was closely associated with authorized fishing camps within the ILUMA WMA and the ecotone between substantially disturbed and largely intact natural land cover. The greatest potential for encountering hippopotamus occurred largely around two river beds, while hyena encounter potential was more closely associated with established villages and converted lands close to the western boundary of the ILUMA WMA. These new maps of hazard and risk suggest that effective human-wildlife conflict (HWC) mitigation in this WMA is unlikely to arise from any stand-alone intervention, but from targeted actions that reduce spatiotemporal overlap between people and wildlife by keeping them apart and/or protecting them against each other. Overall, this study demonstrates that mapping potential encounter risk based on spatiotemporal overlap of indirect activity indicators like tracks, spoor and signs provides a proactive and statistically powerful way to identify where hazardous encounters are most likely to occur, offering considerable advantages over retrospective assessments of much sparser observations of actual realised conflict events after they have already occurred. This new spatial risk mapping approach provides a framework for shifting management from reactive responses after conflict occurs towards proactive prevention.

Information on Western bongo (Tragelaphus eurycerus eurycerus) across its range remains scarce and fragmented, leaving the status of populations poorly understood, limiting effective conservation planning. We conducted three camera-trap surveys across Semuliki National Park, Uganda, between October 2019 and August 2020 (90 camera locations; 11,640 camera days), during which we detected the only currently known population of Western bongo in East Africa. We assessed the status of this population using data from the final survey (March-August 2020), when bongos were detected, applying an individual identification system adapted from Eastern bongo (Tragelaphus eurycerus isaaci) and spatially explicit capture-recapture (SECR) modelling to estimate density and abundance. To reflect known aspects of bongo ecology, we incorporated sex and habitat covariates derived from remotely sensed data as predictors of density. Bongos were detected on 17 occasions, and we identified 18 individuals (11 females and 7 males), of which seven immature individuals (5 females and 2 males). The top-ranking SECR model included the tasseled cap greenness index and sex as predictors of density. The model estimated a population size of 56.49 individuals (SE = 7.69; 95% CI = 41.43-71.56), with an estimated density of 0.58 individuals km-2 (SE = 0.171; 95% CI = 0.32-1.09) within Semuliki National Park. These results provide the first quantitative baseline for this population and suggest the presence of an established breeding population, highlighting the need for structured monitoring to support its long-term conservation.

Over the past two decades, significant population recoveries of tigers and leopards have driven a substantial rise in human-carnivore conflict across South Asia. Sustaining the long-term conservation of both species demands effective, adaptive conflict management. However, existing research is largely confined to isolated landscapes or protected areas, hindering the identification of spatial conflict drivers across broader, heterogeneous regions. To address this gap, this study compiled 4,457 human leopard conflict (HLC) and 2,563 human tiger conflict (HTC) records spanning 2000 to 2024 across Bangladesh, Bhutan, India, and Nepal. We evaluated conflict locations against 33 landscape, anthropogenic, climatic, topographic, and hydrological predictors across three spatial scales using binomial generalized linear regression models and three alternative background sampling methods. Model performance peaked at the largest spatial scale for both species and remained consistent across sampling strategies. HTC correlated positively with forest fragmentation and proximity to human settlements, but decreased with higher overall anthropogenic disturbance. Conversely, HLC concentrated in highly productive, high-precipitation, human-modified landscapes. These contrasting spatial patterns highlight distinct ecological responses to habitat modification and carry unique conservation implications. Ultimately, this study underscores the need to integrate carnivore abundance, wild prey densities, and socioeconomic factors to achieve a holistic understanding of conflict dynamics.

1. Assessing the conservation value of secondary forests and reforestation is important for conservation planning. Butterflies are widely used as indicators, and fruit-feeding butterflies are often used in biodiversity assessments in tropical landscapes. 2. We examined fruit-feeding butterfly diversity, abundance, and community composition across a primary forest, a secondary forest, and a plantation forest in northern Vietnam. We sampled butterflies nearly monthly during one year using baited traps. 3. Primary and secondary forest supported higher species richness than plantation forest. Moreover, while secondary forest had mainly a subset of species found in primary forest, the plantation forest had a distinct butterfly fauna. 4. Butterfly abundance and community composition varied across months, without showing a clear seasonal pattern. 5. Our results suggest that secondary and plantation forests do not fully replace primary forests, but they contribute meaningfully to butterfly conservation in human-modified tropical landscapes.

1. Occurrence records underpin biodiversity analyses, but their coordinates are often erroneous or missing. Misplaced coordinates distort environmental predictors and range estimates used in conservation assessment. Existing tools flag suspect records or georeference locality text, but rarely correct coordinates, provide calibrated uncertainty, or quantify downstream consequences. 2. We present GeoMend, a deterministic, rule-based method that flags and corrects suspect coordinates and georeferences records lacking coordinates from locality text, assigning each a precision tier or uncertainty radius. It uses no machine learning or artificial intelligence. We evaluate it against expert coordinates for 16,913 records and 736 species on Hispaniola, compare georeferencers using 5,000 localities from 72 countries, and measure changes in environmental predictors and the extent of occurrence. 3. On held-out Hispaniola records, GeoMend flags 92% of coordinates more than 5 km from expert truth, versus 27% for CoordinateCleaner. Among the accepted corrections with paired coordinates, the median error falls from 2.19 to 0.82 km, and 68% of the complete held-out pairs improve. On records placed by both GeoMend and GEOLocate that also have original coordinates, the median error is 0.67 km for GeoMend versus 10.69 km for GEOLocate. For records lacking coordinates, evaluated uncertainty radii contain expert truth about 92% of the time in well-supported gazetteer classes. Correction reduces the mean standardized environmental distance from expert truth by 38% and moves the extent of occurrence toward expert truth by a median of 8% (mean of 79%). Corrections and newly georeferenced records give 17 Hispaniola species their first range estimate. 4. On the global benchmark, GeoMend is more accurate than GPT-4o for two-thirds of the records placed by all four comparators, with median errors of 4.4 and 10.8 km, respectively. Applied to Global Biodiversity Information Facility (GBIF) records lacking coordinates, it places records from 82,180 previously unmapped species across 233 countries, ranging from precise locality interpretations to administrative centroids. Automated placement makes the global backlog more approachable, while explicit tiers distinguish uses supported by precise and coarse coordinates. Further georeferencing requires regional expertise to combine automated placement with local knowledge.

Information on the long-term dynamics of species distributions is essential for assessing global biodiversity change and its causes, and for informed conservation decisions. A valuable source of such historical information are atlases. They provide spatial standardisation, extensive geographic coverage, temporal replication, documented sampling protocols, and span multiple species. Here we present model-based occupancy probabilities for 1,055 bird and 58 butterfly species, derived from nine gridded atlas datasets spanning several editions over the past 50 years. These are: Japan, New Zealand, New York state (US), the states of Alberta, Quebec, and The Maritimes (Canada), Czech Republic, United Kingdom, and Europe. Despite standardisation and coordination during data collection, the raw atlas data still contain some variation in sampling effort. We accounted for this using a two-step process: (1) we estimated a proxy for sampling effort in each grid cell within each atlas period using the Frescalo Algorithm, and (2) we ran a Bayesian spatial occupancy model for each species and atlas period, using the estimated sampling effort as the single predictor of detection in the observation process of the model. As the main product, we provide occupancy probabilities for species across grid cells and atlas periods. We also report uncertainty around each probability estimate and flag ~21% (rare) species per atlas for which the model did not fit well. The probability distributions are fit for purpose and served in a user-friendly database with standardised geographic projection, metadata, and taxonomy.

Reliable estimates of population size are fundamental to understanding wildlife population status and informing conservation. Obtaining such estimates remains challenging for unmarked species, particularly in tropical countries where logistical and financial constraints limit intensive monitoring. The endangered dhole (Cuon alpinus), a highly social canid without natural markings, is one such species for which robust population estimates remain scarce. We estimated dhole density in the Valparai plateau, a human-dominated agroforest-forest mosaic in India's Western Ghats. We compared Spatially Explicit Capture-Recapture (SECR) models based on individual identification from fecal DNA and Space-to-Event (STE) models based on camera-trap detections. We additionally applied both approaches to individually identifiable leopards (Panthera pardus) to cross-validate STE versus SECR estimates. SECR estimated dhole density at 22 individuals per 100 sq.km, with STE estimates varying substantially depending on how the camera viewshed area was defined. STE estimates based on post hoc viewshed measurements, particularly after reducing the viewshed by 10%, were comparable to SECR estimates. In contrast, STE underestimated leopard density relative to SECR (7 versus 12 per 100 sq.km), although uncertainty intervals overlapped. Ecologically, our results indicate that human-use agroforest mosaics can support dhole densities comparable to, or exceeding, those reported from several Protected Areas, highlighting their potential importance for dhole conservation. More broadly, we argue that STE models may offer a practical and relatively inexpensive approach for baseline monitoring of dholes from camera-trap surveys, but their reliability depends strongly on accurate characterization of the effective viewshed and may vary across species and landscapes.

Urban protected areas (PAs) have become important habitats for wildlife in rapidly expanding human-dominated landscapes. These PAs may provide refuge and continuously abundant resources, which may enable some adaptable carnivores to persist and attain high abundances. However, little is known about the population ecology and interactions between carnivores sharing such spatially restricted and disturbed urban habitats. We evaluated the densities and spatio-temporal interactions of leopards (Panthera pardus) and striped hyenas (Hyaena hyaena) in Jhalana-Amagarh Conservation Reserve, a protected area (PA) embedded within the metropolis of Jaipur, India. During May-July 2025, we deployed 30 paired camera-traps and used spatially explicit capture-recapture models to estimate density and individual activity centres. We further quantified their diel activity and temporal overlap using kernel density estimation. Leopard density was estimated at 7.03 {+/-} 1.31 individuals/10 km sq and striped hyena density at 4.06 {+/-} 0.96 individuals/10 km sq, with activity centres of both species occurring in close proximity and frequently towards the reserve periphery. Both species were predominantly nocturnal and showed high temporal overlap ({Delta}4 = 0.801, CI=0.73-0.86). Our results report exceptionally high leopard and striped hyena densities in an urban PA and exemplify the importance of small PAs within rapidly expanding cities, stressing the need for finer-scale studies more broadly to understand the mechanisms shaping interactions between the two species. However, such systems require careful management of food subsidies, habitat quality and connectivity along with long-term monitoring of population viability, disease dynamics and human-wildlife conflict.

Climate change will alter habitat suitability for plant communities in mountain ecosystems of the Western Himalaya. There will be contrasting magnitudes and spatial configurations of these changes for different plant species, and it is an important question how to translate these contrasts into effective climate-proof multi-species conservation planning. This study assessed current habitat associations and projected changes in suitable habitat for two contrasting species, Meconopsis aculeata and Rhododendron campanulatum, in Himachal Pradesh, India. Field surveys and spatially filtered occurrence records were combined with MaxEnt modelling using 10 non-collinear environmental predictors. Habitat suitability was projected to 2050 and 2070 under Shared Socioeconomic Pathways; SSP1-2.6, SSP2-4.5 and SSP5-8.5 using HadGEM3-GC31-LL. Field observations showed contrasting habitat associations, with M. aculeata occurring mainly in open alpine herbaceous communities and R. campanulatum in subalpine woody communities. Elevation was an important predictor for both species while climatic predictors contributed differently to their relative importance and response patterns. Future projections indicated reductions in suitable habitat of approximately 25% for M. aculeata and 27-28% for R. campanulatum. Habitat-change maps showed heterogeneous patterns of loss, gain and persistence rather than uniform contraction, and centroid displacement remained small (7.7-8.5 km). We performed proximity analyses to show which currently suitable areas are most close to areas of future gain, in order to support the design of climate-proof protected areas. We discuss how interspecific differences in response are relevant to multi-species conservation planning that considers the spatial relationship between current high-suitability areas and the gain, loss and redistribution of future suitable habitat.

BACKGROUND: The Argentine ant (Linepithema humile) is among the world's worst invasive species. In the Donana Biological Reserve (Spain), it is associated with human structures that provide the mild, moist conditions it needs within the hot, dry scrubland. We evaluated a habitat-modification treatment, predicting that removing this suitable habitat would eradicate the invader locally. Over an 18-year period, we monitored ant communities at a treated and an untreated site, at different distances from the human structures, before and after treatment, and analysed how temperature and worker numbers affected encounters at baits between the Argentine ant and native ants. RESULTS: Distance to the human structures shaped ant communities at both sites, but only the treated site changed after treatment. There, the Argentine ant decreased close to the human structure and almost disappeared farther from it, whereas the endemic Cataglyphis tartessica and C. floricola recovered, especially close to the structure. At baits, the outcome of encounters depended mainly on how temperature changes favoured each species relative to its maximum activity temperature: Cataglyphis spp. displaced the Argentine ant in the morning, as temperature increased, and the Argentine ant recovered the baits in the late afternoon. Numerical advantage favoured only the Argentine ant. CONCLUSION: Habitat modification reduced the Argentine ant and allowed endemic ants to recover, but did not eradicate the invader, which persisted at low abundance 13 years after treatment. In protected areas, habitat management should be combined with eradication, monitoring and prevention of spread.

Management of marine protected areas (MPAs) require long-term monitoring and evaluation that is often limited by the cost and effort of conventional visual based surveys. We evaluated a community science-based eDNA approach to MPA monitoring over two years in the Point Dume State Marine Reserve, the Point Dume State Marine Conservation Area, and two paired unprotected reference sites. Across the sampling period, we detected 119 species of fish and marine mammals, including 19 of the 22 regional management-priority species for Southern CA MPAs. Protected and unprotected comparison sites were broadly similar in overall assemblage with 93 species shared across all sites. Multivariate analyses revealed site-level differences, although season and year explained more variation than protection status. Species presence also shifted during a La-Nina transition, highlighting the importance of long-term monitoring under different climatological contexts. Community scientists greatly expanded the temporal and spatial scope of eDNA sampling and generated high-quality data. Subsampling analysis showed that quarterly sampling, with three sample replicates and sequencing depths between 700k-990k, recovered 95% of observed biodiversity of the full time series. These results demonstrate that a community science-based eDNA program could provide a standardized, scalable, low-cost, and management-relevant approach for long-term monitoring across California's MPA network.

Climate change poses a major threat to marine mammal populations, many of which remain vulnerable after years of overexploitation during the 17th to 20th centuries. Extreme climate events have grown in both frequency and severity in recent decades, and this trend is projected to accelerate under continued greenhouse gas emissions. Here, we assess how this intensification affects a top marine predator at the epicentre of extreme El Nino events - the Peruvian population of Otaria byronia (South American sea lion). We first apply a Bayesian population model that best predicts observed population dynamics to reconstruct female O. byronia population trends, estimate vital rates, and evaluate the effects of environmental drivers on survival and reproduction. We then use the same model to project extirpation risk under multiple future climate scenarios reflecting anticipated increases in both the intensity and frequency of extreme El Nino events. Our reconstruction reveals that the Peruvian O. byronia population has shown considerable resilience to episodic El Nino events over the past quarter-century, likely sustained by high female survival during normal and favourable years. However, under a scenario of moderate increases in El Nino frequency and intensity, the probability of extirpation over the next 50 years is 83.4% higher than under current conditions. As disturbance regimes intensify globally, we suggest that resilience-oriented management frameworks, grounded in species-specific demographic data and environmental context, as demonstrated here, will be essential for safeguarding marine mammal populations against an increasingly volatile climate.

Soil is one of the most biodiverse habitats on the planet, yet the extent of soil biodiversity knowledge in Canada is unknown. To better understand our knowledge, we systematically mapped soil invertebrate biodiversity knowledge from peer-reviewed literature to identify spatial and taxonomic gaps and to assess whether areas projected to experience different magnitudes of climate change are adequately sampled. A total of 1,176 Canadian sampling locations were identified from 427 articles. We found biases in sampling coverage spatially and in relation to current and projected climatic conditions. The geographic region above 60 degrees North is sparsely sampled. Colder regions (< -0.12 C) and regions receiving the least (< 646.47 mm), moderately high (2268.67 to 2809.40 mm), and high (2809.40 to 3350.14 mm) amounts of precipitation were under sampled. Regions projected to have the smallest (< 0.86 C) and greatest (> 1.59 C) magnitudes in temperature change and regions projected to have moderate (-2.06 to +2.69 mm) to large changes (+2.69 to +7.44 mm) in precipitation were underrepresented. The sampled locations also suffer from taxonomic biases which were skewed toward Nematoda (19%), Annelida (18%), Acari (15%), and Collembola (14%). Our results suggest that methods such as stratified sampling is essential to capture underrepresented regions, taxonomic groups, and an array of current and projected climatic conditions. Additionally, shifting to a multispecies sampling approach is essential for broader soil ecosystem knowledge. Importantly, data from well-sampled areas should be examined to determine how it can be leveraged to advance conservation management of soil invertebrates.

Trail cameras have become ubiquitous tools for ecological data collection over recent decades. Despite progress in the development of automated algorithms and artificial intelligence for image classification, our ability to process large volumes of data remain limited by the need for trained human observers to make refined judgements. We provide guidance on placement of trail cameras for observing Asian elephants (Elephas maximus) and outline a protocol for training and testing naive human observers in performing image classifications (age/sex class and group composition) that cannot yet be automated. This process can be used to develop a high-throughput workflow capable of extracting useful data from large volumes of images. Our training material consisted of 14,007 images collected from 6 trail cameras around Udawalawe National Park in Sri Lanka from 2017-2019. In the first stage, expert observers (n=3) trained a group of inexperienced participants (n=4), who engaged in an iterative process to develop a protocol document. The document was then tested on a second set of subjects (n=6) each of whom classified 350 test images in four separate sequential batches using quantitative measures of precision and accuracy. The test set was sampled from 54,435 images from an additional 25 cameras. When compared to expert observers, they achieved a fair level of precision (Fleiss' kappa = 0.247) and 82.6% accuracy. Our approach can usefully be extended to other species and contexts.

1. As city populations expand globally, understanding how urbanization shapes ecosystem services is increasingly important. Urban agriculture plays a key role in food access, particularly in low-income areas with limited access to fresh produce. Arthropods play important roles in these systems through pollination, herbivory, pest control, and nutrient cycling. Urban development of natural areas often reduces biodiversity, including that of arthropods. Additionally, urban biodiversity frequently correlates positively with socioeconomic conditions, a pattern known as the luxury effect. 2. In this study, we examined how gradients in urbanization and socioeconomic context relate to local and landscape habitat quality, arthropod abundance, and pollination services across 21 community gardens in the Denver, CO Metro Area. To quantify ecosystem services, we employed a sentinel plant, Cucumis sativus (cucumber), and collected arthropods (insects, myriapods, arachnids, isopods), assigning them to functional groups based on their known feeding behavior. We evaluated direct and indirect pathways linking urban matrix characteristics to arthropod-mediated ecosystem services. 3. The abundance of all arthropod groups (including pollinators, herbivores, and natural enemies) declined steeply with increasing impervious surface. Neighborhood wealth was associated only with bee species richness and Shannon diversity and displayed a hump-shaped pattern that peaked at wealth levels 35-46% above the national average, then declined. Multivariate GLMs revealed that Western honeybees (Apis mellifera) were the only species driving differences in bee community composition, with their abundance positively related to neighborhood wealth. 4. We also observed pollen limitation in our cucumber plants, and as bee Shannon diversity increased, cucumber production increased. Environmental covariates alone showed no direct relationship with cucumber production, indicating that insect pollination mediated this effect. This work identifies the biophysical and social-ecological drivers of urban arthropod biodiversity and ecosystem services, revealing where crop production may be most vulnerable to decline in cities.

Palm oil is the worlds leading vegetable oil, with production continuing to expand, particularly across Southeast Asia. Within established plantations, conserving and restoring riparian margins can reduce erosion, improve connectivity, and support biodiversity. Simultaneously, climate change is increasing thermal stress within tropical agricultural landscapes, raising the potential importance of riparian buffers as microclimatic refugia, although this has not previously been evaluated. The Riparian Ecosystem Restoration in Tropical Agriculture (RERTA) Project is a long-term Before-After Control-Impact experiment established within oil palm plantations in Riau, Indonesia, to evaluate alternative riparian restoration strategies following plantation replanting. Treatments included passive restoration (retaining mature oil palms and allowing natural regeneration), active restoration (enrichment planting with six native tree species), and a control (replanting immature oil palms to the river edge). Six years after restoration, we assessed vegetation structure using terrestrial laser scanning and thermal stability using temperature loggers and thermal imaging. We also evaluated the long-term temperature buffering capacity of each treatment under current and projected climates using CHELSA climate data and downscaled outputs from multiple General Circulation Models under Shared Socioeconomic Pathway scenarios for 2045 and 2085. Active restoration produced greater structural complexity, a more closed canopy, and cooler, more thermally stable conditions than passive restoration and control treatments. Restored margins also contained significantly more cool surface microhabitats, reducing thermal extremes under both current and future climate scenarios. Our findings demonstrate that active restoration of riparian margins can enhance thermal buffering and create microclimatic refugia for biodiversity within tropical oil palm landscapes. As agricultural intensification and climate change continue to reshape tropical ecosystems, restoring structurally complex riparian vegetation will be critical for sustaining biodiversity and the ecosystem services upon which agricultural production depends.

Agricultural intensification is a major cause of population declines in farmland birds and insects worldwide. While these declines are expected to disrupt trophic interactions through density-dependent cascading effects, examples outside of crop pest control or involving more than two trophic levels remain poorly documented. Here we quantify such cascading effects across three trophic levels involving a declining aerial insectivore, the Tree Swallow (Tachycineta bicolor), which breeding success decreases with agricultural intensity, Protocalliphora bird blowflies (Diptera: Calliphoridae) that parasitize its nestlings, and Nasonia parasitoid jewel wasps (Hymenoptera: Pteromalidae) that feed upon blowfly pupae within swallow nests. Agriculture intensity may affect each of these actors either directly via, for instance, toxicological effects from pesticide use, or indirectly through density-dependent trophic interactions, which can exacerbate or mitigate one another. Using Bayesian models within a causal inference framework, we quantified how nestling host density, meteorological conditions, and agricultural landscape context affect Nasonia parasitoid infestation of Protocalliphora pupae, and estimated Protocalliphora emergence success. Analyses were based on 3,340 Protocalliphora puparia collected from 248 Tree Swallow nests over a 16-year period (2004-2019) across a 10,200-km2 agricultural intensity gradient in Southern Quebec, Canada. Model predictions indicated that Protocalliphora emergence probability increased steeply with nestling host availability (i.e., nestling-days). Whereas Nasonia parasitoid infestation occurrence at the nest level increased with Protocalliphora host availability, the proportion of infested Protocalliphora pupae within nest decreased and led to a dilution effect at the individual level. Although Protocalliphora abundance within nests decreased with agricultural intensity, their emergence probability peaked in agrointensive landscapes. This increase was associated with reduced Nasonia infestation rates, suggesting that agricultural intensity indirectly mitigated parasitoid pressure on Protocalliphora host populations. Our results highlight how agricultural intensification can shape multitrophic interactions and life-history traits (emergence success and infestation rates) by simultaneously reducing host availability and weakening top-down control by parasitoids.

Ground-nesting wild bees require suitable soil conditions for their below-ground development and overwintering life stages. Understanding how soil translocation and disturbance affect individuals and the following generations of bees is important for identifying conservation measures for ground-nesting wild bees. We investigated the effects of soil translocation and disturbance on the ground-nesting solitary spring mining bee Colletes cunicularius. In a replicated controlled design, we compared the effects of soil translocation with different degrees of disturbance on the number of surviving bees and the emergence time. We found that soil translocation and disturbance reduced bee survival but did not result in complete mortality, with some individuals surviving even under severe soil disturbance. There was no evidence that soil disturbance affected the timing of spring emergence, suggesting that disturbance is unlikely to alter the timing of nest construction and, consequently, the production of the next generation. Our results indicate that translocating soil containing overwintering bees could be a promising conservation measure to compensate for habitat loss caused by land conversion.

Aim: To test whether individual movement mechanisms inferred from animal tracking data can be scaled up to explain landscape-scale patterns of population density and improve predictions of population redistribution under future environmental change. Location: Texas Gulf Coast, USA Time Period: 2009-2018 Major Taxa Studied: Whooping Crane (Grus americana) Methods: We parameterized individual-level step-selection functions using 14,898 GPS locations from 22 Whooping Cranes and propagated the resulting movement and habitat-selection mechanisms across the landscape to derive steady-state distributions of space use. We compared these movement-informed predictions with correlative species distribution models fitted to the same data. Predictions were evaluated using withheld tracking observations and fully independent population-level aerial-survey data. We then projected both approaches under sea-level-rise scenarios to assess how future habitat loss and fragmentation alter crane space use. Results: Movement mechanisms derived from individual-level tracking data captured the mechanistic dependence of population density on habitat quality and spatial configuration. When projected across the landscape, these mechanisms reproduced fully independently observed density patterns and outperformed conventional species distribution models. Because predictions arose from movement mechanisms rather than occurrence-environment correlations, movement-informed models also captured the effects of habitat reconfiguration under sea-level rise. They projected pronounced population redistribution and an expansion of core space-use areas of up to 80% which conventional models missed. Main Conclusions: Individual movement mechanisms derived from biologging data can scale up to explain current population structure and predict future redistribution under environmental change. By mechanistically accounting for how habitat configuration constrains accessibility, movement-informed models reveal severe impacts of fragmentation that are missed by conventional distribution models. Rapidly expanding biologging datasets therefore offer a scalable basis for connecting individual behavior to macroecological patterns and improving biodiversity forecasts in changing landscapes.

Translocations are commonly used to reduce the risk of extinction of threatened species, and often to reintroduce animals to their former habitats. If extirpation occurred a long time ago, individuals may be placed into novel environments outside of conditions they have previously experienced, which can affect translocation success. To measure success of translocations, particularly those to novel habitats, it is important to monitor post-release spatial behaviour. In 2023, ten critically endangered k[a]k[a]p[o] (Strigops habroptilus) were released to form a new population at the fenced mainland island of Sanctuary Mountain Maungatautari (hereafter Maungatautari) in the North Island of New Zealand, an area from which they were extirpated approximately a century earlier. The spatial behaviour and habitat selection of these k[a]k[a]p[o] was analysed using dynamic space use and step selection functions with temporally dynamic responses applied to GPS logger data recorded over a seven month period. These showed three unexpected results: k[a]k[a]p[o] were highly mobile and used larger areas compared to other sites; there was synchronicity of movement, with most individuals simultaneously moving toward the perimeter fence in spring; and when near the fence k[a]k[a]p[o] selected for areas of pasture and exotic vegetation more than anticipated. While direct comparisons are difficult due to varying data availability, this unexpected spatial behaviour and habitat selection suggests that k[a]k[a]p[o] behavioural responses were different at Maungatautari compared to other sites. This may indicate that k[a]k[a]p[o] released at Maungatautari had a longer exploratory stage than elsewhere; that there were behavioural effects influenced by conspecific density or the availability of novel and exotic vegetation; or that there were specific breeding habitat requirements not met at the site during the study period. These results highlight the importance of high-resolution spatial monitoring to evaluate the success of translocations, particularly those to novel environments.