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When estimating population density from data collected on non-invasive detector arrays, recently developed spatial capture-recapture (SCR) models present an advance over non-spatial models by accounting for individual movement. While these models should be more robust to changes in trapping designs, they have not been well tested. Here we investigate how the spatial arrangement and size of the trapping array influence parameter estimates for SCR models. We analysed black bear data collected with 123 hair snares with an SCR model accounting for differences in detection and movement between sexes and across the trapping occasions. To see how the size of the trap array and trap dispersion influence parameter estimates, we repeated analysis for data from subsets of traps: 50% chosen at random, 50% in the centre of the array and 20% in the South of the array. Additionally, we simulated and analysed data under a suite of trap designs and home range sizes. In the black bear study, we found that results were similar across trap arrays, except when only 20% of the array was used. Black bear density was approximately 10 individuals per 100 km(2). Our simulation study showed that SCR models performed well as long as the extent of the trap array was similar to or larger than the extent of individual movement during the study period, and movement was at least half the distance between traps. SCR models performed well across a range of spatial trap setups and animal movements. Contrary to non-spatial capture-recapture models, they do not require the trapping grid to cover an area several times the average home range of the studied species. This renders SCR models more appropriate for the study of wide-ranging mammals and more flexible to design studies targeting multiple species.

Large carnivore attacks on humans are a serious form of human-wildlife interaction which has increased globally in recent decades. When attacks occur, both humans and large carnivores suffer, highlighting the need to characterize these conflicts toward mitigation of attacks. We investigated brown bear ( Ursus arctos ) and Persian leopard ( Panthera pardus ) attacks on humans across Iran using reports provided by the Government of Iran during 2012–2020. We characterized temporal and spatial patterns of attacks, as well as species-specific attributes. We identified 83 attacks resulting in 77 human injuries and 6 fatalities. Bears were responsible for more attacks (63%) than leopards (37%). Attacks occurred more frequently during defensive reactions by bears and leopards on adult male people while livestock herding during the day in spring and summer. Bears reportedly attacked people more often in western provinces of Iran, while leopards attacked more frequently in northern provinces. We recommend that the Iran Department of the Environment consider implementing a national reporting system to document bear and leopard attacks on people. We further suggest development of national bear and leopard management plans that emphasize mitigating human risk to improve human attitudes toward these carnivore species to facilitate their conservation.

Species distribution models (SDMs) are widely applied to understand the processes governing spatial and temporal variation in species abundance and distribution but often do not account for measurement errors such as false negatives and false positives. We describe unmarked, a package for the freely available and open‐source R software that provides a complete workflow for modelling species distribution and abundance while explicitly accounting for measurement errors. Here we focus on recent advances in unmarked functionality to support multi‐species, multi‐state, and multi‐season data, as well as support for fitting models with random effects. For illustration, we present an analysis of Acadian Flycatcher Empidonax virescens abundance on Roanoke River National Wildlife Refuge, North Carolina, USA, over 18 years. We found that Acadian Flycatcher abundance was initially greater in hardwood plantation habitat relative to bottomland hardwood forest along river levees but that abundance declined over time in both habitats. We plan for unmarked development to keep pace with advances in hierarchical modelling in ecology, including better handling of continuous‐time data from camera trap and automated recording units and integrated models for multiple data streams.

Human-wildlife interactions occur where human and wildlife coexist and share common resources including food or shelter. Increasing wildlife populations within protected areas also can increase interactions with humans living adjacent to these areas, resulting in conflicts including human casualty, livestock depredation, crop damage, and property loss. We analyzed six years human-wildlife conflict data from 2016–2021 in the buffer zone of Shuklaphanta National Park and conducted questionnaire survey to investigate factors influencing human-wildlife conflicts. Nineteen people were attacked by wildlife, primarily wild boar ( Sus scrofa ). Ninety-two livestock were killed by leopard ( Panthera pardus ), and among these most were sheep or goats killed near ShNP during summer. Crops were most frequently damaged by Asian elephants ( Elephas maximus ), followed by wild boar. Greatest economic losses were from damage to rice, followed by sugarcane and wheat. Asian elephant was the only reported species to cause structural damage to property (e.g., homes). Majority of respondents (83%) considered that the mitigation techniques that are currently in practice are effective to reduce the conflicts. However, the effectiveness of the mitigation techniques are the species specific, we recommend use of more efficacious deterrents (e.g., electric fencing) for large herbivores and mesh wire fencing with partially buried in the ground. Effective collaboration among different tiers of government, non-governmental organizations, civil societies and affected communities are important to share the best practices and continue to apply innovative methods for impactful mitigation of human-wildlife conflicts in the region.

Biotic and abiotic factors influence species habitat selection across space and time. Predator habitat selection is often studied in relation to their primary prey, however, how predators shift their space use in response to secondary prey and the corresponding ecological consequences have received less attention. We used four years (2018, 2020, 2021, 2022) of wolf ( Canis lupus ) GPS data to examine how wolf habitat selection relates to active American beaver ( Castor canadensis ) lodge locations. We hypothesized that wolf selection of beaver lodges would reflect seasonal beaver behavior, intensifying through the ice-free season as beaver vulnerability increases as they spend more time away from their lodges and the vulnerability and availability of moose ( Alces alces ) decreases. Using a generalized linear mixed model and a mixed generalized additive model in a Bayesian framework, we analyzed how wolf habitat selection changed, especially near active beaver lodges. We used 834 unique active beaver lodges in our analysis, 395 [0.74 lodges /km 2 ] in 2018, 386 [0.72 lodges /km 2 ] in 2020, 344 [0.64 lodges /km 2 ] in 2021, and 168 [0.31 lodges /km 2 ] in 2022, a total decline of 57% since wolf restoration. We collected 18,932 wolf GPS locations (N 2018  = 1200, N 2020  = 7224, N 2021  = 3690, N 2021  = 6818) from 23 wolves (10 females and 13 males). Our results suggest that wolves shifted their habitat selection to increase encounters with beavers, supporting previous work demonstrating the importance of beavers to the wolf diet during snow-free periods. This shift supports wolf prey-switching behavior to beavers when their primary prey, moose, are more difficult and riskier to kill.

Large carnivore species frequently predate and consume wild or domestic prey, which is referred to as food-related predation. Large carnivores can also hunt and kill prey exceeding their immediate needs (i.e., they do not consume prey), which is referred to as surplus predation. We used 173 records of livestock predations by gray wolves ( Canis lupus ; n  = 133) and Persian leopards ( Panthera pardus tulliana ; n  = 40) reported by governmental organizations of Iran during 2009–2019 to investigate food-related and surplus predation incidents of livestock. We found that for wolves, the number of reported surplus predation incidents was greater than that of food-related predation incidents during all 4 seasons (spring through winter), whereas for leopards, the number of food-related and surplus predation incidents were similar in all seasons. The number of livestock killed per surplus predation incident was greater for wolves than for leopards and that surplus predations by both species occurred more frequently within corrals than on free-range pastures. As corrals in most villages across Iran are poorly constructed and largely accessible to predators, we recommend that livestock owners enhance corral construction, use well-trained dogs during day and particularly at night, employ people to watch livestock at night, and use fire (e.g., torches) during night to scare carnivores. These strategies can mitigate predation incidents and corresponding economic losses, resulting in fewer losses of livestock, wolves, and leopards, as these two carnivore species are mainly killed by humans due to livestock predations across Iran.

Understanding species distributions and factors influencing them are important for conservation, particularly for species occurring in human-dominated areas. The Indian crested porcupine ( Hystrix indica ; hereafter porcupine) is distributed southeast and central Asia, however, the porcupine occurrence and habitat use is poorly understood in the area. We deployed cameras at 154 sites for 21 days (3234 trap nights) during December 2022–March 2023 in the human-dominated landscape of Parsa-Koshi Complex (PKC), Madesh Province, Nepal. We used single season single species occupancy model to estimate the relationship of selected covariates with porcupine occupancy. We identified moderate occupancy [0.321 ± 0.079 (SD)] and detection probability [0.315 ± 0.076 (SD)] of porcupines. Although porcupine occurrence was greater in protected area than in outside protected areas, occupancy was positively associated with area of farmland (1.531 ± 1.703) and human presence (0.459 ± 0.531), while it declined with increasing forest canopy cover (-0.86 ± 0.363). The positive effects of agricultural areas and human presence demonstrate the adaptability of porcupines to humans and the potential for continued conflicts. Based on these baseline data, policy makers and wildlife managers can gain insight into the pattern of porcupine occurrence and aid targeted conservation strategies to mitigate increasing human-porcupine conflicts in PKC.

Climate change is a significant driver of biodiversity loss impacting an estimated 15–30% of known species by the end of the 21st century. We assessed current suitable habitat and projected future distribution of barking deer ( Muntiacus vaginalis ) across three climate change scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) in northern Pakistan using 99 occurrence records from remote camera during 2021–2023. We obtained bioclimatic data for current (1970–2000) and future (2041–2060, 2061–2080, 2081–2100) periods from the WorldClim database using the Hadley Global Environment Model (HadGEM3-GC31-LL). We used MaxEnt software to predict current and future distributions of barking deer habitat, and changes in suitable habitat across these periods. The model had excellent performance (AUC = 0.936, TSS = 0.823) and jackknife tests showed that precipitation seasonality (Bio15) contributed 32.2% to model predictions, temperature seasonality (Bio4) 28.5%, and annual mean temperature (Bio1) 27.0%. In the current period, highly suitable habitat for barking deer represented 3.7%, moderately suitable habitat 4.4%, less suitable habitat 6.8%, and unsuitable habitat 85.1% of the study area. The gain in suitable habitat was greatest (30.2%) under SSP2-4.5 during 2061–2080. The predicted loss in the suitable habitat of barking deer across all periods was (19.7–23.3%) while the greatest loss (23.3%) was under SSP1-2.6 during 2061–2080. Overall, climate change is projected to result in an overall net gain in suitable habitat for barking deer. Future conservation efforts for barking deer should target currently suitable habitat forecasted to remain suitable.

Climate change is among the greatest drivers of biodiversity loss, threatening up to 15–30% of described species by the end of the twenty-first century. We estimated the current suitable habitat and forecasted future distribution ranges of Indian pangolin ( Manis crassicaudata ) under climate change scenarios. We collected occurrence records of Indian pangolin using burrow counts, remote camera records and previously published literature in Pakistan during 2021–2023. We downloaded bioclimatic data for current (1970–2000) and future (2041–2060, 2061–2080, 2081–2100) climate scenarios from the WorldClim database using the Hadley Global Environment Model (HadGEM3-GC31-LL). We used MaxEnt software to predict current and future distributions of Indian pangolin, then computed the amount of habitat lost, gained, and unchanged across periods. We obtained 560 Indian pangolin occurrences overall, 175 during the study, and 385 from our literature search. Model accuracy was very good (AUC = 0.885, TSS = 0.695), and jackknife tests of variable importance showed that the contribution of annual mean temperature (bio1) was greatest (33.4%), followed by the mean temperature of the coldest quarter (bio-12, 29.3%), temperature seasonality (bio 4, 25.9%), and precipitation seasonality (bio 15, 11.5%). The maxent model predicted that during the current time period (1970–2000) highly suitable habitat for Indian pangolin was (7270 km 2 , 2.2%), followed by moderately suitable (12,418 km 2 , 3.7%), less suitable (49,846 km 2 , 14.8%), and unsuitable habitat (268,355 km 2 , 79.4%). Highly suitable habitat decreased in the western part of the study area under most SSPs and in the central parts it declined under all SSPs and in future time periods. The predicted loss in the suitable habitat of the Indian pangolin was greatest (26.97%) under SSP 585 followed by SSP 126 (23.67%) during the time 2061–2080. The gain in suitable habitat of Indian pangolin was less than that of losses on average which ranged between 1.91 and 13.11% under all SSPs during all time periods. While the stable habitat of the Indian pangolin ranged between 64.60 and 83.85% under all SSPs during all time periods. Our study provides the current and future habitat ranges of Indian pangolin in the face of a changing climate. The findings of our study could be helpful for policymakers to set up conservation strategies for Indian pangolin in Pakistan.

Increasingly, measures of glucocorticoid levels (e.g., cortisol), key components of the neuroendocrine stress axis, are being used to measure past hypothalamic-pituitary-adrenal (HPA) activity to index psychological and physiological stress exhibited by wildlife for assessing individual and population-level well-being. However, many intrinsic and extrinsic factors affect HPA activity in animals. Using American black bears (Ursus americanus; n = 116) as an ecological model and hair cortisol concentration (HCC) as an integrative measure of past HPA activity, we evaluated the influence of diet, sex and the social environment on black bear HCC in a free-ranging population that spanned adjoining ecoregions with differing densities of potential conspecific and heterospecific competitors. HCC varied by sex, with female HCC ranging from 0.6 to 10.7 pg/mg (median = 4.5 ± 1.2 mean absolute deviation [MAD]) and male HCC ranging from 0.5 to 35.1 pg/mg (median = 6.2 ± 2.6 MAD). We also observed a three-way interaction among sex, δ14C and ecoregion, which may indicate that some differences in HCC between female and male black bears results from variability in the nutritional needs of larger-bodied males relative to smaller-bodied females, slight differences in food resources use between ecoregions as well as sex-based differences regarding the social environment. Once we understand what drives sex-specific differences in HCC, HCC may aid our understanding of the physiological responses by bears and other wildlife to diverse environmental challenges.