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AbstractDNA-based biodiversity surveys, which involve collecting physical samples from survey sites and assaying them in the laboratory to detect species via their diagnostic DNA sequences, are increasingly being adopted for biodiversity monitoring and decision-making. The most commonly employed method, metabarcoding, combines PCR with high-throughput DNA sequencing to amplify and read ‘DNA barcode’ sequences, generating count data indicating the number of times each DNA barcode was read. However, DNA-based data are noisy and error-prone, with several sources of variation, and cannot alone estimate the species-specific amount of DNA present at a surveyed site (DNA biomass). In this paper, we present a unifying modelling framework for DNA-based survey data that allows estimation of changes in DNA biomass within species, across sites and their links to environmental covariates, whilst for the first time simultaneously accounting for key sources of variation, error and noise in the data-generating process, and for between-species and between-sites correlation. Bayesian inference is performed using MCMC with Laplace approximations. We describe a re-parameterisation scheme for crossed-effects models designed to improve mixing, and an adaptive approach for updating latent variables, which reduces computation time. Theoretical and simulation results are used to guide study design, including the level of replication at different survey stages and the use of quality control methods. Finally, we demonstrate our new framework on a dataset of Malaise-trap samples, quantifying the effects of elevation and distance-to-road on each species, and produce maps identifying areas of high biodiversity and species DNA biomass. [ABSTRACT FROM AUTHOR]

Roads can impact population abundance due to mortality from collisions with vehicles, habitat degradation and loss of connectivity. Some species, however, can be unaffected or even positively affected by roads and roadside environments. Despite this, there is scarce information on population‐level responses to roads. To fill this knowledge gap, we sampled medium and large mammals with camera traps near two paved roads with low and high traffic volumes in agricultural landscapes in the Brazilian Cerrado. We used Royle‐Nichols' occupancy models to investigate the effects of road proximity on the local abundance of 12 mammal species with varying susceptibility to roadkill. We found that road proximity affected only three species, all of which had high roadkill rates. While two of these species exhibited lower abundance near roads, the third showed the opposite response. For most species, irrespective of their roadkill rates, variations in local abundance were strongly correlated with habitat quality and connectivity. Species' life‐history traits, individual behaviour and the impact of roads and traffic on populations over time may explain these idiosyncratic responses. [ABSTRACT FROM AUTHOR]

Aim: Planning conservation action requires accurate estimates of abundance and distribution of the target species. For many mammals, particularly those inhabiting tropical forests, there are insufficient data to assess their conservation status. We present a framework for predicting species distribution using jaguarundi (Herpailurus yagouaroundi), a poorly known felid for which basic information on abundance and distribution is lacking. Location: Mesoamerica and South America. Time Period: From 2003 to 2021. Taxa: Herpailurus yagouaroundi. Methods: We combined camera‐trap data from multiple sites and used an occupancy modelling framework accounting for imperfect detection to identify habitat associations and predict the range‐wide distribution of jaguarundis. Results: Our model predicted that the probability of jaguarundi occupancy is positively associated with rugged terrain, herbaceous cover, and human night‐time light intensity. Jaguarundi occupancy was predicted to be higher where precipitation was less seasonal, and at intermediate levels of diurnal temperature range. Our camera data also revealed additional detections of jaguarundis beyond the current International Union for Conservation of Nature (IUCN) range distribution, including the Andean foothills of Colombia and Bolivia. Main Conclusion: Occupancy was predicted to be low throughout much of Amazonian lowlands, a vast area at the centre of jaguarundi known range. Further work is required to investigate whether this area represents sub‐optimal conditions for the species. Overall, we estimate a crude global jaguarundi population of 35,000 to 230,000 individuals, covering 4,453,406 km2 of Meso‐ and South America at the 0.5 probability level of occupancy. Our current framework allows for an initially detailed, well‐informed species distribution that should be challenged and refined with improved habitat layers and additional records of jaguarundi detection. We encourage similar studies of lesser‐known mammals, pooling existing by‐catch data from the growing bank of camera‐trap surveys around the world. [ABSTRACT FROM AUTHOR]

Understanding the distribution, abundance and detectability of species is pivotal for effective conservation and management strategies. This study investigated the populations of Chelonoidis denticulatus and Chelonoidis carbonarius within one of the largest remnants of the Atlantic Forest in Brazil (Vale Natural Reserve). The aim was to evaluate species abundance, factors influencing occupancy and detectability, and implications for conservation. Sampling occurred from 2015 to 2018 across 24 line transects. We measured climate and landscape variables potentially associated with species occurrence in each transect. We used the Royle–Nichols model to estimate abundance, while occupancy modelling assessed occupancy, detectability, and the effects of variables. The estimated population size of both species (C. denticulatus: 153 individuals, C. carbonarius: 105 individuals) was notably lower than in Amazonian areas. Detectability surged after rainfall, exceeding 70% with at least 55 mm of rain on the prior day. Occupancy of C. denticulatus correlated positively with forest cover, while both species were negatively affected by distance from water. The study's findings signal potential critical conditions for Chelonoidis species in the Atlantic Forest. The small estimated populations, coupled with their reliance on water availability and forest cover for occupancy and detectability, pose significant conservation challenges. As climate change threatens the planet, these factors assume heightened significance. Given the alarming scenario of potentially critical population status within the Atlantic Forest, urgent attention is needed for robust conservation strategies. Strengthening ecological knowledge specific to this biome is essential to developing effective measures that counter the impacts of habitat loss, climate change and other threats. This study underscores the importance of preserving water resources and forest cover within the Atlantic Forest to secure the future of Chelonoidis species and highlights the need for comprehensive, targeted conservation efforts. [ABSTRACT FROM AUTHOR]

The Asian tapir Tapirus indicus is the only tapir species in Southeast Asia. It is declining across its range and is categorized as Endangered on the IUCN Red List. The forests of Sumatra are critical to Asian tapir conservation as they contain some of the last remaining populations of the species, yet conservation efforts are hindered by a lack of information on habitat suitability. We collated camera-trap data from nine landscapes across 69,500 km2 of Sumatran rainforest to help predict suitable habitat for Asian tapirs on the island. Predictions from Bayesian occupancy models demonstrated that tapir occupancy was greatest in forests below 600 m elevation and exclusively in forests with high aboveground biomass. Forests around the Barisan Mountains on the west of Sumatra provide the most suitable habitat for the species. Only 36% of the most critical habitat (i.e. 80th percentile of predicted occupancy values, or above) for tapirs is formally protected for conservation, with much of the remainder found in forests allocated to watershed protection (35%) or logging (23%). We highlight several key areas in Sumatra where tapir conservation could be bolstered, such as by leveraging existing conservation efforts for other charismatic flagships species on the island.

The Asian tapir Tapirus indicus is the only tapir species in Southeast Asia. It is declining across its range and is categorized as Endangered on the IUCN Red List. The forests of Sumatra are critical to Asian tapir conservation as they contain some of the last remaining populations of the species, yet conservation efforts are hindered by a lack of information on habitat suitability. We collated camera-trap data from nine landscapes across 69,500 km2 of Sumatran rainforest to help predict suitable habitat for Asian tapirs on the island. Predictions from Bayesian occupancy models demonstrated that tapir occupancy was greatest in forests below 600 m elevation and exclusively in forests with high aboveground biomass. Forests around the Barisan Mountains on the west of Sumatra provide the most suitable habitat for the species. Only 36% of the most critical habitat (i.e. 80th percentile of predicted occupancy values, or above) for tapirs is formally protected for conservation, with much of the remainder found in forests allocated to watershed protection (35%) or logging (23%). We highlight several key areas in Sumatra where tapir conservation could be bolstered, such as by leveraging existing conservation efforts for other charismatic flagships species on the island. [ABSTRACT FROM AUTHOR]

Abstract Biodiversity monitoring is undergoing a revolution, with fauna observation data being increasingly gathered continuously over extended periods, through sensors like camera traps and acoustic recorders, or via opportunistic observations. These data are often analysed with discrete‐time ecological models, requiring the transformation of continuously collected data into arbitrarily chosen, non‐independent discrete‐time intervals. To overcome this issue, ecologists are increasingly turning to the existing continuous‐time models in the literature. Closer to the real detection process, they are lesser known than discrete‐time models, not always easily accessible and can be more complex. Focusing on occupancy models, a type of species distribution models, we asked ourselves: Should we dedicate time and effort to learning and using these continuous‐time models, or can we go on using discrete‐time models? We conducted a comparative simulation study using data generated within a continuous‐time framework. We assessed the performance of five static occupancy models with varying detection processes: discrete detection/non‐detection process, discrete count process, continuous‐time Poisson process and two types of modulated Poisson processes. Our goal was to assess their abilities to estimate occupancy probability with continuously collected data. We applied all models to empirical lynx data as an illustrative example. In scenarios with easily detectable animals, we found that all models accurately estimated occupancy. All models reached their limits with highly elusive animals. Variation in discretisation intervals had minimal impact on the discrete models' capacity to estimate occupancy accurately. Our study underscores that opting for continuous‐time models with an increased number of parameters, aiming to get closer to the sensor detection process, may not offer substantial advantages over simpler models when the sole aim is to accurately estimate occupancy. Model choice can thus be driven by practical considerations such as data availability or implementation time. However, occupancy models can encompass goals beyond estimating occupancy probability. Continuous‐time models, particularly those considering temporal variations in detection, can offer valuable insights into specific species behaviour and broader ecological inquiries. We hope that our findings offer valuable guidance for researchers and practitioners working with continuously collected data in wildlife monitoring and modelling.

Summary: Medium- and large-sized mammals play important roles in maintaining forest ecosystem functions, and these functions often diminish when mammal species are depleted by human activities. Understanding the sensitivity or tolerance of mammal species to human pressure and detecting species changes through monitoring programmes can inform appropriate management decisions. The objective of our study was to identify medium- and large-sized mammal species that can be included in a monitoring programme in the Southern Yungas of Argentina. We used occupancy modelling to estimate the probability of habitat use (ψ) of 13 of 25 mammal species detected by 165 camera traps placed in forests across a range of human footprint index (HFI) values. As defined by the HFI, 54% of the study area is wilderness. The probabilities of habitat use of two mammal species were significantly associated with the HFI: the lowland tapir (Tapirus terrestris ; ψ = 0.33, range = 0.22–0.50) was inversely associated with HFI values, whereas the grey brocket deer (Mazama gouazoubira ; ψ = 0.79, range = 0.67–0.87) was positively associated with the HFI. Monitoring the probability of habitat use of the sensitive species (lowland tapir) could help us to detect changes in areas experiencing anthropogenic impacts before they cause extirpation, whereas the high probability of the habitat use values of the tolerant species (grey brocket deer) might indicate that anthropogenic impacts are strongly influencing habitat, signalling that mitigation strategies might be warranted. The Southern Yungas retains an intact mammal fauna, and we showed that the HFI is useful for monitoring anthropogenic impacts on these mammals. There are still opportunities to develop conservation strategies to minimize threats to mammal species in the region by implementing a monitoring programme with the proposed species. [ABSTRACT FROM AUTHOR]

Context: Ecological surveillance monitoring typically targets multiple taxonomic groups by using standardised sampling across large spatial scales. Although surveillance monitoring confers advantages over hypothesis-driven monitoring in its broad taxonomic and spatial scope, the approach has been criticised for its disconnect from ecological management and failure to provide insights on the drivers of ecological change Aims: To assess the adequacy of a plot-based general fauna-monitoring program for sampling reptiles as indicators of ecosystem health in a semi-arid upland region of the Northern Territory, Australia. Methods: We surveyed reptiles at 90 sites, stratified between major landform and vegetation types, and using standard fauna-sampling methods, across the 2568 km2 Tjoritja National Park in the MacDonnell Ranges. We compiled a full inventory of the reptile fauna of the study area and identified species with potential utility as ecological indicators. We then used single-season occupancy models and power analyses to evaluate the adequacy of sampling for detecting potential future changes in occupancy. Key results: We detected 57 of the 68 reptile species known from the protected area, 17 of which are potentially useful indicators of ecological health, mostly related to fire management. There was insufficient power to detect moderate (50%) future changes in reptile occupancy for all but the single most detected species. For the two ecological indicator species with sufficient detections for occupancy modelling, a positive association with a keystone structure (dense spinifex grass) was confirmed. However, increasing detection probability or the number of surveys would result in only minor improvements in power to detect occupancy change in these species. Conclusions: Although reptiles are potentially useful indicators of ecological health, particularly in relation to fire regimes, the number of sites required to detect future changes in reptile occupancy by using standardised plot-based monitoring in this protected area is prohibitively high. Implications: Our results suggest that once ecological associations are understood, monitoring ecological health remotely by using techniques such as fire-scar mapping to track proportions of long-unburnt vegetation should be considered over labour-intensive surveillance monitoring for reptiles. Targeted monitoring of threatened and other reptile species of conservation or cultural concern may also be warranted. Ecological surveillance monitoring targets multiple taxonomic groups using standardised sampling across large spatial scales. We assessed the adequacy of a general fauna-monitoring program for sampling reptiles as indicators of ecosystem health in the semi-arid Northern Territory and found insufficient power to detect potential future changes in reptile occupancy. Once ecological associations are understood, monitoring ecological health remotely using techniques such fire-scar mapping to track proportions of long-unburnt vegetation, should be considered over labour-intensive surveillance monitoring for reptiles. Photograph by Peter J. McDonald. [ABSTRACT FROM AUTHOR]

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AbstractThe occupancy modelling framework offers tremendous flexibility in estimating species abundance and distribution patterns while accounting for imperfect detection, and has seen rapid growth and adoption since its introduction at the beginning of the century.At the same time, in an era of big data, there are increasing demands on developing quantitative skills and proficiency in young ecologists, many of whom lack the quantitative training needed to conduct research professionally.We introduce occupancyTuts, an R package that features 28 learnr tutorials that teach the statistical underpinnings of several occupancy models. The tutorials include written content, instructional videos, R exercises, and quiz elements, covering a range of topics including statistical underpinnings, single‐ and dynamic‐occupancy models, study design and several of the ‘spin‐off’ models that extend the basic framework.We plan for development of new tutorials that use RPresence as the analysis engine, and welcome new tutorial contributions that use other R packages as the analysis engine as well.

The persistence of seed-dispersing animals in degraded habitats could be critical for ensuring the long-term conservation value and restoration of forests. This is particularly important in Southeast Asia, where > 70% of the remaining forest areas are within 1 km of a forest edge, and many are degraded (e.g. logged). We synthesized information on the habitat associations of the binturong Arctictis binturong, a large, semi-arboreal, frugivorous civet and one of the most important seed dispersers in the region, especially for figs (Ficus spp). We adopted a multiscale approach by employing ensemble species distribution modelling from presence-only records, assessing landscape-scale variation in detection rates in published camera-trap studies and using hierarchical occupancy modelling to assess local (i.e. within-landscape) patterns observed from 20 new camera-trap surveys. Contrary to prior reports that binturongs are strongly associated with intact forests, the species was equally present in degraded forests and near forest edges where sufficient forest cover was maintained (> 40% forest cover within a 20-km radius). The species also tolerates moderate incursions of oil palm plantations (< 20% of the area within a 20-km radius covered by oil palm plantations). The relative resilience of binturongs to habitat degradation could be in part because of behavioural adaptations towards increased nocturnal activity. These results support the notion that key seed dispersers can persist and maintain their ecological function in degraded forests.

Loss of natural habitat due to increases in agricultural extent raises the question of whether human‐dominated landscape types can support biodiversity, particularly for declining insect pollinators. Compared to more rural agricultural landscapes, urban areas may confer benefits for bumble bee populations by providing stable and diverse floral resources. However, disentangling the effects of local‐ and landscape‐scale characteristics on bumble bee populations in human‐modified landscapes is challenging.Here, we assessed bumble bee occupancy using a repeated transect sampling design conducted during the summers of 2019 and 2020 within the metropolitan area of Madison, WI, and the surrounding agricultural landscape. We fit hierarchical occupancy models to estimate the detection (p) and occupancy (ψ) probabilities relative to local habitat quality (floral abundance and floral richness) and landscape (agricultural‐urban gradient) features for eight bumble bee species. We hypothesised that bumble bees were more likely to occupy urban areas, serving as refugia, relative to agricultural sites.We found that the detection probability of all bumble bee species was seasonal and influenced by maximum floral abundance at survey sites, independent of the surrounding land cover type. After accounting for species‐specific detection probabilities, the effect of urbanisation on bee occupancy was weak, and no species were less likely to occupy urban than rural agricultural areas.Our findings suggest that bumble bee occupancy is associated with a 'honeypot effect' where local resource availability, in the form of higher floral abundance, is most important in limiting the occupancy of bumble bees across urban and agricultural landscapes. [ABSTRACT FROM AUTHOR]

The persistence of seed-dispersing animals in degraded habitats could be critical for ensuring the long-term conservation value and restoration of forests. This is particularly important in Southeast Asia, where > 70% of the remaining forest areas are within 1 km of a forest edge, and many are degraded (e.g. logged). We synthesized information on the habitat associations of the binturong Arctictis binturong , a large, semi-arboreal, frugivorous civet and one of the most important seed dispersers in the region, especially for figs (Ficus spp). We adopted a multiscale approach by employing ensemble species distribution modelling from presence-only records, assessing landscape-scale variation in detection rates in published camera-trap studies and using hierarchical occupancy modelling to assess local (i.e. within-landscape) patterns observed from 20 new camera-trap surveys. Contrary to prior reports that binturongs are strongly associated with intact forests, the species was equally present in degraded forests and near forest edges where sufficient forest cover was maintained (> 40% forest cover within a 20-km radius). The species also tolerates moderate incursions of oil palm plantations (< 20% of the area within a 20-km radius covered by oil palm plantations). The relative resilience of binturongs to habitat degradation could be in part because of behavioural adaptations towards increased nocturnal activity. These results support the notion that key seed dispersers can persist and maintain their ecological function in degraded forests. [ABSTRACT FROM AUTHOR]

The occupancy modelling framework offers tremendous flexibility in estimating species abundance and distribution patterns while accounting for imperfect detection, and has seen rapid growth and adoption since its introduction at the beginning of the century.At the same time, in an era of big data, there are increasing demands on developing quantitative skills and proficiency in young ecologists, many of whom lack the quantitative training needed to conduct research professionally.We introduce occupancyTuts, an R package that features 28 learnr tutorials that teach the statistical underpinnings of several occupancy models. The tutorials include written content, instructional videos, R exercises, and quiz elements, covering a range of topics including statistical underpinnings, single‐ and dynamic‐occupancy models, study design and several of the 'spin‐off' models that extend the basic framework.We plan for development of new tutorials that use RPresence as the analysis engine, and welcome new tutorial contributions that use other R packages as the analysis engine as well. [ABSTRACT FROM AUTHOR]

Large transboundary protected areas such as the Kavango-Zambezi Transfrontier Conservation Area (KAZA-TFCA), improve mammal conservation by addressing biodiversity threats on regional and international levels, but an adequate understanding of mammal space use and richness within protected areas is critical for effective management planning. This information has however been missing from the Angolan component of the KAZA-TFCA, such as areas of Luengue-Luiana National Park (LLNP), especially compared with neighbouring countries. We used camera trap data from 2021 to 2023 to investigate species richness of medium- and large-sized mammals in two hotspot areas of LLNP, as well as assess the space use patterns of 9 carnivore and 16 herbivore species. A total of 48 species were recorded over 10,781 camera trapping nights, with African elephant (Loxodonta africana) and small antelope (e.g. common duiker Sylvicapra grimmia and steenbok Raphicerus campestris) being the most common. Species composition differed significantly between sites, with 21 species more relatively abundant at Ndunjuru, including cheetah (Acinonyxjubatus) and African wild dog (Lycaon pictus), and eight species more relatively abundant at Bico, including lion (Panthera leo) and hippopotamus (Hippopotamus amphibius). The detection probability of 22 species were affected by one or more ecological (e.g. proximity to rivers) or anthropogenic (e.g. human settlement) covariate. These results are intended to act as a baseline to monitor conservation effort and aid habitat management in LLNP, as well as similar protected areas within the KAZA-TFCA and elsewhere. [ABSTRACT FROM AUTHOR]

The Asian small-clawed otter (Aonyx cinereus) is a globally vulnerable mesopredator endemic to South and Southeast Asia. This species is one of the least studied and smallest of all 13 otter species. The species is tolerant of least-aquatic conditions and reported across a wide range of habitats. Its ecology is not fully and methodically deciphered. Recently, new populations were discovered in eastern Bangladesh, the north-western border of the Indo-Burma Biodiversity Hotspot. Based on camera trapping carried out between January and July 2021, we investigated otter occupancy and spatiotemporal coexistence within an anthropized riparian mixed-evergreen forest. We assessed the influence of stream density, the distance between the camera-trap station and the nearest built-up area, and slope on otter habitat use; cumulated precipitation and Julian day on detection probability. Our results revealed a mammalian mesopredator release effect and heavy anthropogenic activities; however, otters and humans exhibited very low spatiotemporal overlap. Detections showed high temporal convergence with the nocturnal-crepuscular carnivore guild. Otter occupancy did not show any pattern when modelled with altitude or human density; detection neither decreased with the progression of the monsoon. Our findings suggest that otters can adapt their habitat use to human pressure in forests dominated by human activities, especially with dense stream networks. We encourage further research to gain a better understanding of the factors that could impact otter habitat preference, such as food abundance, undergrowth vegetation, human-induced forest fires, and fishing or poaching pressure. Understanding otters is a potential tool to step up research investment in anthropized forests. [ABSTRACT FROM AUTHOR]

Abstract The negative impact of large carnivore presence in human‐dominated landscapes manifests as livestock depredation and in extreme cases as attacks on humans. In the case of conflict with leopards in Nepal, attacks resulting in human fatality have become more frequent over time, thus creating an urgent socio‐ecological and management issue. We estimated the occurrence of leopard attacks in Nepal from human‐leopard conflict cases reported in the media. We used occupancy models to analyse data collected from online news reports on incidents of leopard attacks on humans to explore drivers of leopard attacks on a landscape scale. Our results suggest that the probability of occurrence of leopard attack is associated with human population density, terrain ruggedness and livestock density. The human population density effect may be indicative of a density‐dependent relationship, where attacks are more likely in areas where an increased abundance of humans increases encounter rates with leopards. The positive effect of livestock density suggests that livestock may be drawing leopards into human settlements, and consequently increasing the likelihood of attacks on humans. Terrain ruggedness might be offering ideal conditions to facilitate attacks on humans, for example remoteness and high amounts of cover to launch ambush attacks. We provide inference and insights into key determinants of leopard attacks on humans on a landscape scale. These insights can be used to guide future research, inform mitigation measures to reduce leopard attacks and foster a better understanding of the interaction between people and leopards. This study demonstrates the applicability and novelty of using a hierarchical modelling framework applied to freely and publicly available media reports to inform the applied management of human‐wildlife conflict at a national scale. Read the free Plain Language Summary for this article on the Journal blog.

Medium to large rainforest mammals are key conservation flagship groups that offer non‐redundant ecosystem functions, but anthropic pressures, such as illegal hunting, may strongly affect their occupancy in Amazonia. We combined camera traps and occupancy models to assess the influence of distance from human settlements, the number of families per settlement and the synergetic effect of the average weight of 27 species on the occupancy probability of mammals. Specifically, we classified mammal species according to the game preferences of hunters (i.e. a group of species depleted for bushmeat, a group of species hunted for retaliation and a group of non‐hunted species). We also accounted for the influence on the detection probability of each group of both the number of days each camera operated and the body weight of mammals. The occupancy probability of the bushmeat group (i.e. deer, peccaries, agoutis, pacas and armadillos) was lower at locations closer to human settlements. Still, the number of families correlated positively with occupancy, with the occupancy probability of the group being slightly higher at sites with more families. This difference was probably due to larger and more abundant crops and fruiting trees attracting wildlife at such sites. Conversely, the occupancy probability of the retaliation group (i.e. carnivores) and the non‐hunted group (i.e. opossums, spiny rats, squirrels and anteaters) were indifferent to anthropogenic stressors. The detection probability of the non‐hunted and particularly the most depleted species correlated negatively with body weight. This may suggest that larger species, especially those from the bushmeat group, are rarer or less abundant in the system, possibly because they are the preferable target of hunters. In the long term, locals will likely need to travel long distances to find harvest meat. Poaching also threatens food security since game bushmeat is an essential source of protein for isolated rural Amazonians. [ABSTRACT FROM AUTHOR]

The negative impact of large carnivore presence in human‐dominated landscapes manifests as livestock depredation and in extreme cases as attacks on humans. In the case of conflict with leopards in Nepal, attacks resulting in human fatality have become more frequent over time, thus creating an urgent socio‐ecological and management issue.We estimated the occurrence of leopard attacks in Nepal from human‐leopard conflict cases reported in the media. We used occupancy models to analyse data collected from online news reports on incidents of leopard attacks on humans to explore drivers of leopard attacks on a landscape scale. Our results suggest that the probability of occurrence of leopard attack is associated with human population density, terrain ruggedness and livestock density.The human population density effect may be indicative of a density‐dependent relationship, where attacks are more likely in areas where an increased abundance of humans increases encounter rates with leopards. The positive effect of livestock density suggests that livestock may be drawing leopards into human settlements, and consequently increasing the likelihood of attacks on humans. Terrain ruggedness might be offering ideal conditions to facilitate attacks on humans, for example remoteness and high amounts of cover to launch ambush attacks.We provide inference and insights into key determinants of leopard attacks on humans on a landscape scale. These insights can be used to guide future research, inform mitigation measures to reduce leopard attacks and foster a better understanding of the interaction between people and leopards.This study demonstrates the applicability and novelty of using a hierarchical modelling framework applied to freely and publicly available media reports to inform the applied management of human‐wildlife conflict at a national scale. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

The Endangered giant pangolin Smutsia gigantea is rare and elusive across its Central African range. Because of its solitary and nocturnal nature, the species is difficult to study and so its ecology is little known. Pangolins are considered the most trafficked mammals in the world. Therefore, confirming presence accurately and monitoring trends in distribution and abundance are essential to inform and prioritize conservation efforts. Camera traps are popular tools for surveying rare and cryptic species. However, non-targeted camera-trap surveys yield low camera-trapping rates for pangolins. Here we use camera-trap data from surveys conducted within three protected areas in Uganda to test whether targeted placement of cameras improves giant pangolin detection probability in occupancy models. The results indicate that giant pangolin detection probability is highest when camera traps are targeted on burrows. The median number of days from camera deployment to first giant pangolin detection event was 12, with the majority of events captured within 32 days from deployment. The median interval between giant pangolin events at a camera-trap site was 33 days. We demonstrate that camera-trap surveys can be designed to improve the detection of giant pangolins and we outline a set of recommendations to maximize the effectiveness of efforts to survey and monitor the species. [ABSTRACT FROM AUTHOR]

Abstract Medium to large rainforest mammals are key conservation flagship groups that offer non‐redundant ecosystem functions, but anthropic pressures, such as illegal hunting, may strongly affect their occupancy in Amazonia. We combined camera traps and occupancy models to assess the influence of distance from human settlements, the number of families per settlement and the synergetic effect of the average weight of 27 species on the occupancy probability of mammals. Specifically, we classified mammal species according to the game preferences of hunters (i.e. a group of species depleted for bushmeat, a group of species hunted for retaliation and a group of non‐hunted species). We also accounted for the influence on the detection probability of each group of both the number of days each camera operated and the body weight of mammals. The occupancy probability of the bushmeat group (i.e. deer, peccaries, agoutis, pacas and armadillos) was lower at locations closer to human settlements. Still, the number of families correlated positively with occupancy, with the occupancy probability of the group being slightly higher at sites with more families. This difference was probably due to larger and more abundant crops and fruiting trees attracting wildlife at such sites. Conversely, the occupancy probability of the retaliation group (i.e. carnivores) and the non‐hunted group (i.e. opossums, spiny rats, squirrels and anteaters) were indifferent to anthropogenic stressors. The detection probability of the non‐hunted and particularly the most depleted species correlated negatively with body weight. This may suggest that larger species, especially those from the bushmeat group, are rarer or less abundant in the system, possibly because they are the preferable target of hunters. In the long term, locals will likely need to travel long distances to find harvest meat. Poaching also threatens food security since game bushmeat is an essential source of protein for isolated rural Amazonians.

Anthropogenic activities can profoundly affect ecological communities. This is true of the most ubiquitous type of anthropogenic land-use, livestock grazing. While livestock grazing is known to impact vegetation structure, soil, and hydrological features, the effects of livestock occurrence on animal communities are often more complex. Herein, we estimated the relative effects of cattle occurrence and vegetation structure on the occupancy of a carnivore guild in northern California and southern Oregon, USA. We used remote cameras to non-invasively collect detection and non-detection data of cattle and nine carnivore species. We incorporated detection data into a Bayesian hierarchical occupancy model to estimate the effects of livestock occurrence and vegetation structure on carnivore occupancy. We found varied effects of cattle occurrence on carnivore occupancy, with most species showing no clear response to cattle occurrence. Vegetation structure, including structural diversity and vegetation productivity, had stronger effects on carnivore occupancy than cattle occurrence. This work provides an exploration of the effects of cattle occurrence and forest structure on carnivore space-use in a grazed forest system, and suggests vegetation structure may have stronger effects than cattle occurrence on carnivore occupancy in grazed forest systems. Future work to clarify the direct and indirect effects of livestock occurrence can inform conservation and management strategies in forested ecosystems.

African wild dogs utilise a den for ~10–12 weeks after birthing, during which home ranges are contracted and usually in areas away from roads and water sources, with low prey and predator abundances, high terrain ruggedness and vegetation cover. Our study in Savé Valley Conservancy (SVC) investigated which ecological and environmental factors determine the selection of denning areas and behaviours. Camera trap data collected from four den grids and three random den grids were analysed using binomial generalised linear and occupancy models. Denning wild dogs preferred areas with higher kudu and impala presence and areas closer to roads and water sources. Wild dogs may den in areas we perceive as riskier in an attempt to reduce energy expenditure when hunting. The detection of wild dogs strongly decreased with higher lion presence, while increasing with steeper slopes, higher vegetation cover and leopard presence. Given lion habitat preferences, SVC wild dogs could be using areas which reduce their exposure to lions, while solitary leopards do not necessarily pose a risk to wild dog packs. Our study highlights that the denning behaviours of wild dogs may be inconsistent both within and among populations, and that comprehensive research approaches be taken to understand their denning behaviours, assisting the development of appropriate management/conservation strategies. [ABSTRACT FROM AUTHOR]

Understanding ecological‐ and management‐related predictors of mammal space use within protected areas is critical for management planning. This is particularly true in small, fenced and isolated reserves where we hypothesised that management‐related activities will influence large herbivore space use more than ecological characteristics. We used camera trap data to assess the space use patterns for 18 ungulate species in the small and isolated Majete Wildlife Reserve (Majete) in the understudied Miombo woodland ecoregion of southern Malawi. In the 2018 dry season, the 691 km2 reserve was systematically surveyed for ungulate presence at 140 camera trap locations. Over a period of 5456 camera days, the survey yielded 11 078 independent detections of 18 ungulate species and three predators. Using a single‐species occupancy modelling framework, the probability of space use of ungulates was assessed in relation to five management (fire exposure, fire frequency, water availability, distance from fence and road) and five ecological (visibility, grass biomass, vegetation type, terrain ruggedness and predator abundance) space use covariates, while accounting for imperfect detection. Top‐ranked models contained multiple covariates for 15 of the 16 species modelled, with only nyala's (Tragelaphus angasii) space use best predicted by vegetation type only. Distance to water, vegetation type, visibility and fire frequency were predictors having strong influences on six or more species each. More management‐related covariates reflected in top models, but ecological covariates had more meaningful effect sizes making us reject the hypothesis. Importantly though, distance from the roads and fence were also identified as prominent predictors. Notably, black rhinoceros' (Diceros bicornis) probability of space use increased with distance from the reserve boundary. Beyond informing habitat management for ungulates in Majete, these results can form the basis for understanding species‐specific space use patterns in other small reserves with similar characteristics and threats. [ABSTRACT FROM AUTHOR]

Non-native fish have been shown to have deleterious impacts on freshwater ecosystems in New Zealand. Early detection is critical for their effective management. Traditional capture-based techniques may not detect newly introduced fish, especially if they are present in low abundance. Molecular techniques that target environmental DNA (eDNA) have been shown, in many instances, to be more sensitive, cost-effective and require lower sampling effort. However, appropriate sampling strategies are needed to ensure robust and interpretable data are obtained. In this study we used droplet digital PCR assays to investigate the presence of two non-native fish in New Zealand, the European perch (Perca fluviatilis) and rudd (Scardinius erythrophthalmus) in three small lakes. Samples were collected from water and surface sediment at near-shore and mid-lake sites. Probabilistic modelling was used to assess the occupancy of fish eDNA and develop guidance on sampling strategies. Based on the detection probability measures from the present study, at least six sites and five replicates per site are needed to reliably detect fish eDNA in sediment samples, and twelve sites with eight replicates per site for water samples. The results highlight the potential of developing monitoring and surveillance programs adapted to lakes, that include the use of assays targeting eDNA. This study focused on small shallow lakes, and it is likely that these recommendations may vary in larger, deeper, and more geomorphologically complex lakes, and this requires further research. [ABSTRACT FROM AUTHOR]

Non-native fish have been shown to have deleterious impacts on freshwater ecosystems in New Zealand. Early detection is critical for their effective management. Traditional capture-based techniques may not detect newly introduced fish, especially if they are present in low abundance. Molecular techniques that target environmental DNA (eDNA) have been shown, in many instances, to be more sensitive, cost-effective and require lower sampling effort. However, appropriate sampling strategies are needed to ensure robust and interpretable data are obtained. In this study we used droplet digital PCR assays to investigate the presence of two non-native fish in New Zealand, the European perch (Perca fluviatilis) and rudd (Scardinius erythrophthalmus) in three small lakes. Samples were collected from water and surface sediment at near-shore and mid-lake sites. Probabilistic modelling was used to assess the occupancy of fish eDNA and develop guidance on sampling strategies. Based on the detection probability measures from the present study, at least six sites and five replicates per site are needed to reliably detect fish eDNA in sediment samples, and twelve sites with eight replicates per site for water samples. The results highlight the potential of developing monitoring and surveillance programs adapted to lakes, that include the use of assays targeting eDNA. This study focused on small shallow lakes, and it is likely that these recommendations may vary in larger, deeper, and more geomorphologically complex lakes, and this requires further research.

Long‐term land‐use change impacts tropical bird communities through population‐level and functional diversity effects from habitat loss, degradation and fragmentation, leading to land management and conservation challenges.Assessing the temporal impacts of land‐use change on occupancy patterns, population change and functional traits of bird species in tropical areas is limited by the treatment of nondetections as true absences or artefacts of low sampling effort during and throughout years.With this in mind, we developed a novel Bayesian species occupancy framework to account for species absences to evaluate bird community changes in Palenque, Chiapas, Mexico, where there is opportunity for study given exceptional records of change across habitats from rainforest to urban centres. We created a novel dataset of population trends for 244 bird species over the years 1900 to 2020 from published short‐term field studies, expert field notes and community science pages.Our results show that open area species had higher population increases than forest specialists over time, represented most evidently by the turnover of rainforest specialists for urban species. Modelled influence of functional traits displayed the importance of main habitat types, body mass and habitat and dietary breadth as factors that associated with bird population trends. On average, species with body masses <6.6 and > 948.4 g showed decreasing trends, while all other species showed increasing or stable trends.Our findings illuminate the value of accounting for species absences from several data sources to discover long‐term species population trends and affiliated functional traits whose preservation requires conservation and land management action to protect bird ecosystem services. Primary forest conservation is key to maintaining populations of habitat and dietary specialists, such as small understorey insectivorous and large frugivorous species. Protecting rare natural savanna patches from conversion to cattle pasture is vital to prevent further extirpation of native granivores and to slow colonization by exotic and invasive species. [ABSTRACT FROM AUTHOR]

As an important factor in the investigation of building energy consumption, occupant behavior (OB) has been widely studied on the building level. However so far, studies of OB modelling on the district scale remain limited. Indeed, district-scale OB modelling has been facing the challenges from the scarcity of district-scale data, modelling methods, as well as simulation application. This study initiates the extrapolation of occupancy modelling methodology from building level to district scale through proposing modelling methods of inter-building movements. The proposed modelling methods utilize multiple distribution fittings and Bayesian network to upscale the event description methods from inter-zone movement events at the building level to inter-building movement events at the district level. This study provides a framework on the application of the proposed modelling methods for a university campus in the suburbs of Shanghai, taking advantages of data sensing, monitoring and survey techniques. With the collected campus-scale occupancy data, this paper defines five patterns of inter-building movement. One pattern represents the dominated inter-building movement events for one kind of students in their daily campus life. Based on the quantitative descriptions for various inter-building movement events, this study performs the stochastic simulation for the campus district, using Markov chain models. The simulation results are then validated with the campus-scale occupancy measurement data. Furthermore, the impact of inter-building movement modelling methods on building energy demand is evaluated for the library building, taking the deterministic occupancy schedules suggested by current building design standard as a baseline. [ABSTRACT FROM AUTHOR]

Context: Camera trapping is an effective tool for cost-efficient monitoring of species over large temporal and spatial scales and it is becoming an increasingly popular method for investigating wildlife communities and trophic interactions. However, camera trapping targeting rare and elusive species can be hampered by low detection rates, which can decrease the accuracy and precision of results from common analytical approaches (e.g., occupancy modeling, capture-recapture). Consequently, researchers often employ attractants to increase detection without accounting for how attractants influence detection of species among trophic levels. Aims: We aimed to evaluate the influences of a commonly used non-species-specific olfactory lure (i.e. sardines) and sampling design on detection of four species (i.e. bobcat [ Lynx rufus ], coyote [ Canis latrans ], raccoon [ Procyon lotor ], and eastern cottontail [ Sylvilagus floridanus ]) that represented a range of foraging guilds in an agricultural landscape. Methods: We set 180 camera stations, each for ∼28 days, during the summer of 2019. We set cameras with one of three lure treatments: (1) olfactory lure, (2) no olfactory lure, or (3) olfactory lure only during the latter half of the survey. We evaluated the influence of the lure at three temporal scales of detection (i.e. daily probability of detection, independent sequences per daily detection, and triggers per independent sequence). Key results: The lure tended to positively influence detection of coyotes and raccoons but negatively influenced detection of bobcats and eastern cottontails. The influence of the lure varied among temporal scales of detection. Conclusions: Scent lures can differentially influence detection of species within or among tropic levels, and the influence of a scent lure may vary among temporal scales. Implications: Our results demonstrate the importance of evaluating the influence of an attractant for each focal species when using camera data to conduct multi-species or community analyses, accounting for variation in sampling strategies across cameras, and identifying the appropriate species-specific temporal resolution for assessing variation in detection data. Furthermore, we highlight that care should be taken when using camera data as an index of relative abundance (e.g. as is commonly done with prey species) when there is variation in the use of lures across cameras. Camera trapping is a popular method for studying wildlife communities and scent lures are often used to improve detection of carnivores without considering the influence on other species. This study evaluated how a scent lure influenced detection of four species across foraging guilds and demonstrated disparate effects on species. We recommend that researchers avoid using scent lures or account for potential variation in their influence on detection for each species when assessing wildlife communities with cameras. Photograph by Marlin M. Dart. [ABSTRACT FROM AUTHOR]

The Sunda Clouded Leopard Neofelis diardi on Borneo is threatened principally by deforestation for oil palm plantations and the indiscriminate use of illegal trapping. Sunda Clouded Leopard populations are decreasing across their range, and the species has been categorised as Vulnerable on the IUCN Red List. Despite the persistence of threats and numerous surveys in recent years, information on its ecology is still limited. Most studies to date have relied on the use of camera traps as their primary sampling tool, as it is challenging otherwise to gather data on Sunda Clouded Leopards. This study aimed to test the feasibility of estimating the Sunda Clouded Leopard occupancy using a different approach. We conducted vehicle spotlight transect surveys in a mixed-use forest reserve and logging concession in Sabah. We drove a cumulative total of 8,433 km of transects at night and documented the occurrence of Sunda Clouded Leopards in eight out of 31 predetermined long-distance transects, yielding a relatively low na􀅢ve occupancy rate (nO 􀑁 0.26). When accounting for imperfect detection (􀊌 􀑁 0.15), null occupancy of Sunda Clouded Leopards appeared much higher (􀢱 􀑁 0.55), though our parameter estimates lacked relative precision. Despite this, our results suggest there may be potential to further refine and adapt a basic, cost-effective monitoring approach in a local mixed-use reserve with the help of concession managers and additional improvements to study design. We caution, however, that not all study sites may be suited for this type of approach and strongly advise the development of pilot studies to evaluate their overall feasibility. [ABSTRACT FROM AUTHOR]

African elephants (Loxodonta africana) are increasingly exposed to high levels of human disturbance and are threatened by poaching and human–elephant conflict. As anthropogenic pressures continue to increase, both inside and outside protected areas, understanding elephant behavioural responses to human activity is required for future conservation management. Here, we use bycatch data from camera trap surveys to provide inferences on elephant habitat use and temporal activity in Kasungu National Park (KNP), Malawi. The KNP elephant population has declined by ~ 95% since the late 1970s, primarily because of intensive poaching, and information on elephant ecology and behaviour can assist in the species' recovery. Using occupancy modelling, we show that proximity to water is the primary driver of elephant habitat use in KNP, with sites closer to water having a positive effect on elephant site use. Our occupancy results suggest that elephants do not avoid sites of higher human activity, while results from temporal activity models show that elephants avoid peak times of human activity and exhibit primarily nocturnal behaviour when using the KNP road network. As key park infrastructure is located near permanent water sources, elephant spatiotemporal behaviour may represent a trade-off between resource utilisation and anthropogenic-risk factors, with temporal partitioning used to reduce encounter rates. Increased law enforcement activity around permanent water sources could help to protect the KNP elephant population during the dry season. Our findings highlight that camera trap bycatch data can be a useful tool for the conservation management of threatened species beyond the initial scope of research. [ABSTRACT FROM AUTHOR]

Southeast Asia is experiencing a biodiversity crisis driven by the synergistic forces of deforestation and poaching. The mainland serow (Capricornis sumatraensis) is a large rainforest goat threatened by habitat loss, hunting for bushmeat, and poaching for traditional medicine. Serow have been considered to be montane forest specialists and preferring limestone karsts, but this has never been rigorously evaluated. If the species is restricted to high elevations, climate change and the upward expansion of deforestation and agriculture would threaten the species, but less so if serows are more closely associated with landscape roughness (i.e., rough topography including at low elevations such as in karst landscapes). We collated and synthesised new and existing camera-trap data from 29 landscapes across Southeast Asia to determine the serow's habitat associations at regional, landscape, and local scales. Serow occurrence was negatively associated with oil palm plantation cover and positively associated with landscape roughness across all scales; elevation was not a top-performing variable in model selection. With just 16% of their forested range under some form of declared protection, climate change and expansion of oil palm plantations into higher elevations will further reduce habitat and facilitate poaching into the species' core habitat. However, the serow's preference for rough landscapes, where mechanised agriculture is infeasible, may be its saving grace. An improved understanding of megafauna habitat associations provides conservationists, enforcement agencies, and policymakers with practical and applicable guidance to ensure their persistence in Asia. [ABSTRACT FROM AUTHOR]

Apex predators ideally require vast intact spaces that support sufficient prey abundances to sustain them. In a developing world, however, it is becoming extremely difficult to maintain large enough areas to facilitate apex predators outside of protected regions. Free-roaming leopards (Panthera pardus) are the last remaining apex predator in the Greater Cape Floristic Region, South Africa, and face a multitude of threats attributable to competition for space and resources with humans. Using camera-trap data, we investigated the influence of anthropogenic land modification on leopards and the availability of their natural prey species in two contrasting communities--primarily protected (Cederberg) and agriculturally transformed (Piketberg). Potential prey species composition and diversity were determined, to indicate prey availability in each region. Factors influencing spatial utilisation by leopards and their main prey species were also assessed. Estimated potential prey species richness (Cederberg = 27, Piketberg = 26) and diversity indices (Cederberg--H' = 2.64, Ds = 0.90; Piketberg--H' = 2.46, Ds = 0.89), supported by both the Jaccard's Index (J = 0.73) and Sørensen's Coefficient (CC = 0.85), suggested high levels of similarity across the two regions. Main leopard prey species were present in both regions, but their relative abundances differed. Grey rhebok, klipspringer, and rock hyrax were more abundant in the Cederberg, while Cape grysbok, Cape porcupine, chacma baboon, and common duiker were more abundant in Piketberg. Leopards persisted across the agriculturally transformed landscape despite these differences. Occupancy modelling revealed that the spatial dynamics of leopards differed between the two regions, except for both populations preferring areas further away from human habitation. Overall, anthropogenic factors played a greater role in affecting spatial utilisation by leopards and their main prey species in the transformed region, whereas environmental factors had a stronger influence in the protected region. We argue that greater utilisation of alternative main prey species to those preferred in the protected region, including livestock, likely facilitates the persistence of leopards in the transformed region, and believe that this has further implications for human-wildlife conflict. Our study provides a baseline understanding of the potential direct and indirect impacts of agricultural landscape transformation on the behaviour of leopards and shows that heavily modified lands have the potential to facilitate mammalian diversity, including apex predators. We iterate that conservation measures for apex predators should be prioritised where they are present on working lands, and encourage the collaborative development of customised, cost-effective, multi-species conflict management approaches that facilitate coexistence. [ABSTRACT FROM AUTHOR]

This systematic literature review examines Occupant Behaviour (OB) modelling in residential buildings, focusing on its role in narrowing the energy performance gap and enhancing occupant comfort. It provides an overview of methodologies from simple statistical models to advanced machine learning algorithms. We conducted a chronological literature review on OB modelling in residential buildings, identifying the algorithms and the main remarks and limitations of each study. We also present sample populations for each study, offering a comprehensive view of OB modelling's evolution. Our study shows a trend towards incorporating intelligent technologies like IoT and Artificial Intelligence, highlighting an evolution towards more advanced and precise techniques. The review evaluates studies utilizing monitoring, diary, or survey data to improve behavioural model accuracy, covering aspects such as occupant presence, window manipulation, lighting and shading regulation, thermostat adjustment, and usage patterns of domestic hot water and appliances. The review underscores the importance of standardized data collection and integrating OB into building standards. It advocates for adaptive OB models leveraging IoT data with privacy considerations and calls for comparative analysis of modelling techniques. Future research should develop adaptable occupancy profile repositories and integrated modelling frameworks to address OB complexities. • Explores comprehensive occupant behaviour modelling methods in residential settings. • Urges integration of realistic occupant behaviour models into building standards. • Highlights IoT's crucial role in enhancing occupant behaviour model accuracy. • Proposes extensive future research directions in occupant behaviour modelling. [ABSTRACT FROM AUTHOR]

Wildfires are predicted to increase in frequency and severity with climate change but detailed understanding of their influence on forest wildlife is lacking for many species. Wildfires vary in their extent and severity among landscapes, limiting generalisations about impacts from a single wildfire. We investigated post-wildfire persistence in the threatened exudivorous yellow-bellied glider (Petaurus australis) in south-eastern Australia. The widespread occurrence of wildfires in the 'Black Summer' of 2019–20 enabled populations in three landscapes (90–160 km apart) to be studied. This species has a slow life history (one young per year and >1 year to mature) so post-fire recovery is predicted to be slow. We conducted repeat surveys over 3 years post-fire in each landscape at 25–29 sites that were occupied pre-wildfire. All survey sites were burnt in two landscapes but only 40 % were burnt in the third. We estimated declines in occupancy of 13 %, 40 % and 66 % in burnt forest. The factors driving the variation in decline appear to be a combination of fire severity and the abundance of very large (≥80 cm) hollow (i.e. cavity) -bearing trees that serve as den sites. The implications of this study are that the impacts of wildfires on populations of tree-hollow dependent species can be expected to vary in different landscapes as a consequence of fire severity, rainfall deficit and logging history. Our study suggests the importance of ensuring populations are conserved across a wide geographic gradient, and the value of very large hollow-bearing trees rather than simply the number of any hollow-bearing trees. • Knowledge of the response of wildlife to wildfires is a global deficiency. • The Australian Black Summer fires allowed unique landscape replication of wildfires. • We investigated post-fire persistence in an iconic arboreal mammal. • We estimated declines in occupancy in burnt forest landscapes of 13 %, 40 % and 66 %. • Very large hollow-bearing trees appear to influence survival through wildfire. [ABSTRACT FROM AUTHOR]

Small rodents are a key indicator to understand the effect of rapidly changing winter climate on Arctic tundra ecosystems. However, monitoring rodent populations through the long Arctic winter by means of conventional traps has, until now, been hampered by snow cover and harsh ambient conditions. Here, we conduct the first extensive assessment of the utility of a newly developed camera trap to study the winter dynamics of small mammals in the Low Arctic tundra of northern Norway. Forty functional cameras were motion-triggered 20 172 times between September 2014 and July 2015, mainly by grey-sided voles (Myodes rufocanus (Sundevall, 1846)), tundra voles (Microtus oeconomus (Pallas, 1776)), Norwegian lemmings (Lemmus lemmus (Linnaeus, 1758)) and shrews (Sorex spp.). These data proved to be suitable for dynamical modelling of species-specific site occupancy rates. The occupancy rates of all recorded species declined sharply and synchronously at the onset of the winter. This decline happened concurrently with changes in the ambient conditions recorded by time-lapse images of snow and water. Our study demonstrates the potential of subnivean camera traps for elucidating novel aspects of year-round dynamics of Arctic small mammal communities.

Aim: Climate change is an increasingly important driver of biodiversity loss. The ectothermic nature of amphibians may make them particularly sensitive to changes in temperature and precipitation regimes, adding to declines from other threats. While active season environmental conditions can influence growth and survival, effects of variation in winter conditions on population dynamics are less well‐studied. Given that extreme winter temperatures can influence amphibian survival and fitness, we expected that increased winter severity—as measured by variability in winter temperatures and snow cover—would be associated with decreased occupancy, and that populations that experience more severe winters would have the largest sensitivities and show the greatest declines. Location: Eastern United States. Time period: 2001–2015. Major taxa studied: Anurans. Methods: We used large‐scale citizen science data from the eastern half of the United States, a diverse biogeographic and climatic region, to assess how variation in winter severity influenced occupancy dynamics (i.e. presence or absence of species across sites and years) of 11 spring and summer breeding anuran species. Results: Most species had increased occupancy in years with greater than average snow cover and warmer than average mean winter temperatures. Surprisingly, climatic conditions in winter affected occupancy dynamics of species with varying life history characteristics, including both spring and summer breeding species, those that overwinter under the soil, and those that overwinter in ponds and stream beds. For two wide‐ranging species (Lithobates catesbeianus and Lithobates clamitans), colder winter temperatures reduced occupancy more at northern latitudes, while the association between days of snow cover and latitude was equivocal. Main conclusions As the climate continues to change, expected reductions in snowpack may reduce occupancy of already declining anuran populations, while milder winters may improve overwinter survival for some species. The contradictory impacts of temperature and snow cover illustrate the importance of considering multi‐dimensional impacts of climate change on anuran populations. [ABSTRACT FROM AUTHOR]

Occupancy modelling is an increasingly common framework for analysing acoustic data to study the variation in populations through space and time, but different survey designs endow survey locations with varying degrees of biological meaning. Recording units may be preferentially deployed in areas known to be important to a species, which implies an 'area of occupancy' conception of a species range, or recording units may be randomly deployed without knowledge of focal species space‐use (e.g. a survey grid), which implies an 'extent of occurrence' conception of a species range. Preferential sampling requires substantial pre‐survey information (e.g. the location of focal species territories) but leads to intuitive parameter interpretation and greater precision; vastly greater survey coverage is attainable with random sampling, but the resulting data merit careful post‐processing to achieve precise, ecologically meaningful results. Importantly, occupancy, detection, extinction and colonization estimates are incomparable between study designs. However, an understanding of focal species movement and vocal behaviour can inform the development of creative definitions of acoustic detections – and thus site occupancy – which may help bring the ecological realism of preferential sampling to the data yielded by the more scalable random sampling approach. Understanding the implications of study design choices on parameter interpretation is a fundamental aspect of basic ecological inference and endangered species monitoring. [ABSTRACT FROM AUTHOR]

The oomycete Aphanomyces astaci causes crayfish plague, a disease threatening native European crayfish. It is carried and transmitted by American crayfish species, which are the original hosts of A. astaci. In recent years, environmental DNA (eDNA) methods have been successfully implemented to monitor the spread of both A. astaci and its hosts. However, still little is known about how population density and other environmental factors influence the detectability of this host-pathogen complex. In a mesocosm experiment, we tested the influence of crayfish density, temperature and food availability on the detectability of eDNA for A. astaci and its host, signal crayfish Pacifastacus leniusculus. We also compared eDNA results with crayfish population density measured by catch per unit effort (CPUE) from two lakes with varying cray-fish density and A. astaci prevalence. The mesocosm experiment revealed that a limited set of controlled factors can substantially change the detectable amount of eDNA, even though the physical presence of the target organisms remains the same. In cold, clear water, eDNA quantities of both targets increased far more than in a linear fashion with increased crayfish density. However, the presence of food decreased the detectability of crayfish eDNA, presumably through increased microbial-induced eDNA degradation. For A. astaci, where eDNA typically represents living spores, food did not affect the detectability. However, high water temperature strongly reduced it. The increased complexity and variability of factors influencing eDNA concentration under natural conditions, compared to a controlled experimental environment, suggests that establishing a reliable relationship between eDNA quantities and crayfish density is difficult to achieve. This was also supported by field data, where we found minimal correspondence between eDNA quantity and CPUE data. A comparison between quantitative real-time PCR (qPCR) analysis and droplet-digital PCR (ddPCR) analysis revealed higher detection success of the targets in field samples when using qPCR. Overall, our results support eDNA as an effective tool for presence-absence monitoring, but it seems less suited for biomass quantification and population density estimates. Detection of A. astaci and P. leniusculus is not influenced uniformly by respective environmental factors. Consequently, we recommend a strategy of monitoring both targets, where the detection of one may point towards the presence of the other. [ABSTRACT FROM AUTHOR]

Silviculture is among the human activities that contribute most to fragmentation and habitat loss. The comprehension of the effects of such activity on the environment is crucial for conservation. Here, we assessed the effects of silviculture on the local distribution of Contomastix vacariensis, an endemic lizard from southern Brazil. We used a single‐season occupancy model in a Bayesian framework to estimate the occupancy probability of the species in 69 sites with different distances from silviculture areas. Our data showed a low probability of occupancy of C. vacariensis within a distance smaller than 1000 m from silviculture areas, while detection probability was negatively influenced by wind speed. This is the first work to demonstrate a gradual negative effect of exotic silviculture in lizards, which may be more intense inside planted areas and decrease as the distance from the exotic plantation increases. Such results may help delimit the size of conservation areas and management of exotic silviculture species within these areas. Studies with similar methods, considering the distance from the effects of environmental impacts, can be a helpful tool to make predictions based on the projected growth of silviculture in natural areas supporting threatened species. [ABSTRACT FROM AUTHOR]

Summary: Knowledge of where a threatened species occurs in a landscape is crucial for determining its habitat requirements and informing its conservation planning and management. We conducted the first broad-scale survey of the Endangered Alligator Rivers Yellow Chat Epthianura crocea tunneyi across much of its known range on drying coastal floodplains in northern Australia. Presence-absence records from 257 sites surveyed in the late dry season (August–December) of 2018 and 2019 were modelled using occupancy/detectability models. Occupancy was estimated to be 0.10 ± 0.04 with a high detection probability (0.89 ± 0.07). Modelling of 13 site-level environmental covariates found that chats were more likely to be detected at sites where the native shrub Sesbania sesban was present, were close to hydrogeological features such as depressions or channels, were long unburnt (5+ years) and/or with topsoil damage caused by feral pigs. Our estimates of chat occupancy, detectability, and the covariates that influence their occupancy, have improved our understanding of the role that fire and feral animals have on chat distribution and habitat selection, and can be used as a baseline for future monitoring. We also provide recommendations on how to design and implement future monitoring of this subspecies. [ABSTRACT FROM AUTHOR]

In 2012, a new volunteer-based recording scheme for vascular plants was launched in the Netherlands. Its purpose is to track the changes in the number of occupied 1-km grid cells for as many native plant species as possible between survey rounds of 8 years. We did not prescribe a strict field protocol to minimize variation in observer effort, but instead chose to statistically correct for this variation with occupancy models. These models require replicated visits to a grid cell per season, which was implemented by having two independent observers survey grid cells and record all plant species observed. Now that a first survey round has ended (2012–2019), we evaluate our approach, i.e. we tested whether the scheme has the potential to produce proper trend estimates. The number of occupied grid cells in the first round was estimated per species, using an occupancy model with day of year, visit duration and observer experience as covariates for detection. The detection probability, which was 0.43 on average, strongly depended on visit duration and day of year. It was possible to estimate the number of occupied grid cells quite precisely for several hundreds of species, such that the statistical power is expected to be high enough to detect changes of 10% between survey rounds. For rare species, however, the power to detect changes is expected to be quite low. We conclude that the approach works well, but further improvements are suggested. [ABSTRACT FROM AUTHOR]

Ecologists often study biodiversity by evaluating species occupancy and the relationship between occupancy and other covariates. Occupancy models are now widely used to account for false absences in field surveys and to reduce bias in estimates of covariate relationships. Existing occupancy models take as inputs binary detection/non‐detection observations of species at each visit to each site. However, autonomous sensing devices and machine learning models are increasingly used to survey biodiversity, generating a new type of observation record (i.e. continuous‐score data) that reflects the model's confidence a species is present in each autonomously sensed file, instead of binary detection/non‐detection data. These data are not directly compatible with traditional binary occupancy modelling methods.Here, we develop a new occupancy model that models continuous scores on a visit level as a Gaussian mixture, combining a distribution of scores for files that do contain the species of interest and a distribution of scores for files that do not. The model takes as input continuous scores for each autonomously sensed and classified file, along with an optional small number of binary, manually verified detection and non‐detection annotations.We present a simulation study that shows that over a range of empirically realistic parameters, our model outperforms traditional occupancy models that are based on binary annotation alone. We also apply this new model to an empirical case study using data generated from five machine learning classifiers applied to autonomous acoustic recordings gathered in the eastern United States.Because our occupancy model generalizes allowable input data beyond binary observations, it is particularly well‐suited to the increasing volume of machine learning classified data in ecology and conservation. [ABSTRACT FROM AUTHOR]

Abstract Camera traps (CTs) have been increasingly used for wildlife monitoring worldwide. In the tropics, most CT inventories target wildlife‐friendly sites, and CTs are commonly placed towards wildlife trails. However, it has been argued that this placement strategy potentially provides biased results in comparison to more systematic or randomized approaches. Here, we investigated the impact of CT placement on the remotely sensed mammal diversity in a tropical forest in Gabon by comparing pairs of systematically placed and wildlife‐trail‐oriented CTs. Our survey protocol consisted of 15–17 sampling points arranged on a 2 km2 grid and left for one month in the field. This protocol was replicated sequentially in four areas. Each sampling point comprised a CT pair: the ‘systematic CT’, installed at the theoretical point and systematically oriented towards the most uncluttered view; and the ‘trail CT’, placed within a 20‐m radius and facing a wildlife trail. For the vast majority of species, the detection probabilities were comparable between placements. Species average capture rates were slightly higher for trail‐based CTs, though this trend was not significant for any species. Therefore, the species richness and composition of the overall community, such as the spatial distribution patterns (from evenly spread to site‐restricted) of individual species, were similarly depicted by both placements. Opting for a systematic orientation ensures that pathways used preferentially by some species—and avoided by others—will be sampled proportionally to their density in the forest undergrowth. However, trail‐based placement is routinely used, already producing standardised data within large‐scale monitoring programmes. Here, both placements provided a comparable picture of the mammal community, though it might not be necessarily true in depauperate areas. Both types of CT data can nevertheless be combined in multi‐site analyses, since methods now allow accounting for differences in study design and detection bias in original CT data.

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The increasing complexity and pace of ecological change requires natural resource managers to consider entire species assemblages. Acoustic recording units (ARUs) require minimal cost and effort to deploy and inform relative activity, or encounter rates, for multiple species simultaneously. ARU‐based surveys require post‐processing of the recordings via software algorithms that assign a species label to each recording. The automated classification process can result in cross‐species misidentifications that should be accounted for when employing statistical modelling for conservation decision‐making.Using simulation and ARU‐based detection counts from 17 bat species in British Columbia, Canada, we investigate three strategies for adjusting statistical inference for species misclassification: (a) 'coupling' ambiguous and unambiguous detections by validating a subset of survey events post‐hoc, (b) using a calibration dataset on the software algorithm's (in)accuracy for species identification or (c) specifying informative Bayesian priors on classification probabilities. We explore the impact of different Bayesian prior specifications for the classification probabilities on posterior estimation. We then consider how the quantity of data validated post‐hoc impacts model convergence and resulting inferences for bat species relative activity as related to nightly conditions and yearly site occupancy after accounting for site‐level environmental variables.Coupled methods resulted in less bias and uncertainty when estimating relative activity and species classification probabilities relative to calibration approaches. We found that species that were difficult‐to‐detect and those that were often inaccurately identified by the software required more validation effort than more easily detected and/or identified species.Our results suggest that, when possible, acoustic surveys should rely on coupled validated detection information to account for false‐positive detections, rather than uncoupled calibration datasets. However, if the assemblage of interest contains a large number of rarely detected or less prevalent species, an intractable amount of effort may be required, suggesting there are benefits to curating a calibration dataset that is representative of the observation process. Our findings provide insights into the practical challenges associated with statistical analyses of ARU data and possible analytical solutions to support reliable and cost‐effective decision‐making for wildlife conservation/management in the face of known sources of observation errors. [ABSTRACT FROM AUTHOR]