REVIEW: Wildlife camera trapping: a review and recommendations for linking surveys to ecological processes

The Activity Patterns and Grouping Characteristics of the Remaining Goitered Gazelle (Gazella subgutturosa) in an Isolated Habitat of Western China

Wildlife activity patterns, which reveal the daily allocation of time and energy, are crucial for understanding survival pressures, adaptive strategies, and behavioral characteristics in different environments. Among ungulates, grouping behavior is a prevalent adaptive trait that reflects the population structure, mating systems, and life history strategies formed over long-term evolutionary processes. This study aimed to elucidate the daily activity patterns and grouping characteristics of the rare goitered gazelle (Gazella subgutturosa) in the Helan Mountains of western China from 2022 to 2023 using camera trap monitoring. With a total of 3869 camera days of effective trapping, we recorded 442 independent detections of goitered gazelles. The results revealed the following: (1) Goitered gazelle is primarily active during the day, showing an activity pattern similar to crepuscular animals, with two activity peaks occurring after dawn and before dusk. (2) Daily activity patterns showed both seasonal and sex differences. In the warm season, morning activity peaks occurred earlier, and afternoon peaks occurred later compared to the cold season. The overlap in daily activity patterns between females and males in the warm season was lower than that in the cold season, and this trend persisted throughout the year. (3) The number of times different types of groups were observed varied significantly, with single males and single females accounting for a larger proportion of all observed groups. There was no significant difference in group size across seasons, with groups typically consisting of 1-2 individuals. Our study provides detailed insights into the temporal ecology and population structure of goitered gazelles in arid and semi-arid ecosystems. This information will guide the identification of future conservation priorities and the development of management plans for the reserve.

Unveiling the Biodiversity and Conservation Significance of Medog: A Camera-Trapping Survey on Mammals in the Southeastern Tibetan Mountains

The Medog in southeastern Tibet is home to a diverse range of wild animals. However, research on these mammals' species directories, distribution, and conservation status remains insufficient, despite their crucial role in maintaining ecological balance. The study carried out a camera-trapping survey to assess mammal biodiversity and the significance of mammal protection in their natural habitats in Gedang, Medog. Future directions and application prospects of the study for wildlife conservation in the southeastern Tibetan mountains were also discussed. The survey, spanning from April 2023 to May 2024, with 19,754 camera trap days, revealed 25 mammalian species across five orders and 14 families. Among these, four classified as Endangered, five as Vulnerable, two as Near Threatened on the IUCN Red List, nine were categorized as Critically Endangered or Endangered on the Red List of China's Vertebrates, and seven were China's national first-class key protected wildlife. The order Carnivora exhibited the highest diversity, comprising 12 species. Furthermore, the study filled the knowledge gap regarding the underrepresentation of Gongshan muntjac Muntiacus gongshanensis in IUCN and provided new insights into the recorded coexistence of the Himalayan red panda Ailurus fulgens and Chinese red panda Ailurus styani along the Yarlung Zangbo River for the first time, and also documented new upper elevation limits for four large to medium-sized species. Regarding the relative abundance indices (RAI) captured by camera traps, the most prevalent species identified was the White-cheeked macaque Macaca leucogenys, followed by the Gongshan muntjac and Himalayan serow Capricornis thar. The monitoring also captured a number of domestic dogs and livestock, as well as human disturbances. These findings underscore the importance of conserving these mammals and emphasize the need for conservation efforts to protect their habitats and reduce human activities that threaten their survival, thereby maintaining the ecological balance of the region. Additionally, the research highlighted Gedang's significance to global conservation efforts for mammalian diversity, providing essential data for effective wildlife conservation strategies.

Mammal responses to human recreation depend on landscape context

Rapid growth in outdoor recreation may have important and varied effects on terrestrial mammal communities. Few studies have investigated factors influencing variation in observed responses of multiple mammal species to recreation. We used data from 155 camera traps, in western Alberta (Canada), and a hierarchical Bayesian community modelling framework to document 15 mammal species responses to recreation, test for differential responses between predators and prey, and evaluate the influence of local context. Factors characterizing context were trail designation (i.e., use by motorized vs non-motorized), management type, forest cover, landscape disturbance, and season. We used three measures to characterize variation in recreation pressure: distance to trail, trail density, and an index of recreation intensity derived from the platform Strava. We found limited evidence for strong or consistent effects of recreation on mammal space use. However, mammal space use was better explained by an interaction between recreation and the influencing factors than by either on their own. The strongest interaction was between trail density and management type; mammals were more likely to avoid sites near a higher density of trails in areas with more restrictive management. We found that responses to recreation varied with the trail designation, although there were not clear or consistent differences between responses to trails designated for motorized vs. non-motorized use. Overall, we found that responses were species- and context-dependent. Limiting the density of trails may be important for reducing negative impacts to mammals within conservation areas. We show that using multiple measures of recreation yields more insight into the varied effects of human disturbances on wildlife. We recommend investigating how different characteristics of recreation (noise, speed, and visibility) influence animal behaviors. Multispecies monitoring and modelling across multiple landscapes that vary in recreation pressure can lead to an adaptive management approach to ensuring outdoor recreation coexistence with wildlife.

Assessing the role of habitat, climate, and anthropization gradients on terrestrial mammal diversity in the western Mediterranean basin

Mammal species globally exhibit distribution patterns conditioned by environmental conditions and human impact. The Mediterranean basin provides an ideal system to study these effects due to its diverse climate, and habitat conditions. In this work, we aim to assess the impact of landscape heterogeneity and anthropization degree on terrestrial mammal diversity in this region. Accordingly, we deployed over 300 camera traps across 28 sites for 3 months. Detected mammal species (weighing more than 1kg) were classified as domestic carnivores, domestic ungulates, wild carnivores, wild ungulates, lagomorphs, and large rodents. Alpha and beta diversity were calculated for each group and all wild mammals. Simple linear regressions and multimodal analysis were conducted between mammal diversities and climate, environmental conditions, landscape heterogeneity, and anthropization degree variables. Redundancy analyses were performed to identify variables and species determining the mammalian community composition. Indexes measuring landscape heterogeneity, anthropization degree, and its 30-year change did not correlate with mammal diversity. However, the difference in elevation within sites and domestic carnivore abundance showed a significant positive correlation with some of the diversity indexes. Nonetheless, rainfall and mean elevation factors generally showed the highest correlation with mammal diversity. Instead, a few influential species, including generalists and open-habitat specialists, highlighted the importance of conserving open areas, as well as the importance of the Pyrenees region as a key habitat for certain species. Therefore, climatic variables emerged as the key determinants of mammal diversity, highlighting climate change as a potential threat to mammal diversity in this area.

Exploring temporal activity of dholes, their prey, and competitors in East Java, Indonesia

Dholes (Cuon alpinus) are endangered large carnivores found in scattered populations in Asia. One of the main threats to dholes is the decreasing prey availability throughout their distribution range. In the present study, we used camera trap data collected over 6 years to investigate the temporal activity patterns of dholes and their putative prey species in Baluran National Park in Java, Indonesia. We also explored the overlap in activity between dholes and the park's other remaining large carnivore the Javan leopard (Panthera pardus melas), as well as humans. Furthermore, we investigated potential differences in activity patterns between dholes in packs and dholes roaming in pairs or alone. We found a high temporal overlap between dholes and their wild ungulate prey species (ranging from Δ = 0.66-0.90), with the lowest overlap observed between dholes and bantengs (Bos javanicus) (Δ = 0.66), and the highest between dholes and muntjacs (Muntiacus muntjak) (Δ = 0.90). A very low overlap was found between dholes and domestic cattle (Bos indicus) (Δ = 0.27) whereas a moderately high overlap was found between dholes and leopards (Δ = 0.70) and dholes and humans (Δ = 0.62). We found a significant difference in activity patterns between dholes in packs and dholes roaming alone or in pairs (Δ = 0.78, p = .01). Single/pairs of dholes were more active both during the day and at night, whereas packs were predominantly active around sunrise and sunset. The high overlap with humans potentially has a negative effect on dhole activity, particularly for dispersing individuals, and the low overlap with domestic species questions the extent to which dholes are considered to predate on them.

Comparison of soil eDNA to camera traps for assessing mammal and bird community composition and site use

Species detections often vary depending on the survey methods employed. Some species may go undetected when using only one approach in community-level inventory and monitoring programs, which has management and conservation implications. We conducted a comparative study of terrestrial mammal and bird detections in the spring and summer of 2021 by placing camera traps at 30 locations across a large military installation in northern Michigan, USA and testing replicate soil samples from these sites for environmental DNA (eDNA) using an established vertebrate metabarcoding assay. We detected a total of 48 taxa from both survey methods: 26 mammalian taxa (excluding humans, 24 to species and two to genus) and 22 avian taxa (21 to species and one to genus). We detected a relatively even distribution of mammalian taxa on cameras (17) and via eDNA analysis (15), with seven taxa detected from both methods. Most medium-to-large carnivores were detected only on cameras, whereas semi-fossorial small mammals were detected only via eDNA analysis. We detected higher bird diversity with camera traps (18 taxa) compared to eDNA analysis (eight taxa; four taxa were detected with both methods), but cameras alone were most effective at detecting smaller birds that frequently occupy arboreal environments. We also used Bayesian spatial occupancy models for two widely distributed game species (white-tailed deer, Odocoileus virginianus, and ruffed grouse, Bonasa umbellus) that were moderately detected with both survey methods and found species-specific site use (occupancy) estimates were similar between cameras and eDNA analysis. Concordant with similar studies, our findings suggest that a combination of camera trap and eDNA surveys could be most useful for assessing the composition of terrestrial mammal communities. Camera traps may be most efficient for assessing bird diversity but can be complemented with eDNA analysis, particularly for species that spend considerable time on the ground.

Man versus machine: cost and carbon emission savings of 4G-connected Artificial Intelligence technology for classifying species in camera trap images

Timely and accurate detection and identification of species are crucial for monitoring wildlife for conservation and management. Technological advances, including connectivity of camera traps to mobile phone networks and artificial intelligence (AI) algorithms for automated species identification, can potentially improve the timeliness and accuracy of species detection and identification. Adoption of this new technology, however, is often seen as cost-prohibitive as it has been difficult to calculate the cost savings or qualitative benefits over the life of the program. We developed a decision tool to quantify potential cost savings associated with incorporating the use of mobile phone network connectivity and AI technologies into monitoring programs. Using a feral cat eradication program as a case study, we used our decision tool to quantify technology-related savings in costs and carbon emissions, and compared the accuracy of AI species identification to that of experienced human observers. Over the life of the program, AI technology yielded cost savings of $0.27 M and when coupled with mobile phone network connectivity, AI saved $2.15 M and 115,838 kg in carbon emissions, with AI algorithms outperforming human observers in both speed and accuracy. Our case study demonstrates how advanced technologies can improve accuracy and cost-effectiveness and improve monitoring program efficiencies.

Combining camera trap surveys and IUCN range maps to improve knowledge of species distributions

Reliable maps of species distributions are fundamental for biodiversity research and conservation. The International Union for Conservation of Nature (IUCN) range maps are widely recognized as authoritative representations of species' geographic limits, yet they might not always align with actual occurrence data. In recent area of habitat (AOH) maps, areas that are not habitat have been removed from IUCN ranges to reduce commission errors, but their concordance with actual species occurrence also remains untested. We tested concordance between occurrences recorded in camera trap surveys and predicted occurrences from the IUCN and AOH maps for 510 medium- to large-bodied mammalian species in 80 camera trap sampling areas. Across all areas, cameras detected only 39% of species expected to occur based on IUCN ranges and AOH maps; 85% of the IUCN only mismatches occurred within 200 km of range edges. Only 4% of species occurrences were detected by cameras outside IUCN ranges. The probability of mismatches between cameras and the IUCN range was significantly higher for smaller-bodied mammals and habitat specialists in the Neotropics and Indomalaya and in areas with shorter canopy forests. Our findings suggest that range and AOH maps rarely underrepresent areas where species occur, but they may more often overrepresent ranges by including areas where a species may be absent, particularly at range edges. We suggest that combining range maps with data from ground-based biodiversity sensors, such as camera traps, provides a richer knowledge base for conservation mapping and planning.

A century of statistical Ecology

As data and computing power have surged in recent decades, statistical modeling has become an important tool for understanding ecological patterns and processes. Statistical modeling in ecology faces two major challenges. First, ecological data may not conform to traditional methods, and second, professional ecologists often do not receive extensive statistical training. In response to these challenges, the journal Ecology has published many innovative statistical ecology papers that introduced novel modeling methods and provided accessible guides to statistical best practices. In this paper, we reflect on Ecology's history and its role in the emergence of the subdiscipline of statistical ecology, which we define as the study of ecological systems using mathematical equations, probability, and empirical data. We showcase 36 influential statistical ecology papers that have been published in Ecology over the last century and, in so doing, comment on the evolution of the field. As data and computing power continue to increase, we anticipate continued growth in statistical ecology to tackle complex analyses and an expanding role for Ecology to publish innovative and influential papers, advancing the discipline and guiding practicing ecologists.

Mammal responses to global changes in human activity vary by trophic group and landscape

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human-wildlife interactions along gradients of human influence.

Home security cameras as a tool for behavior observations and science affordability

Reliably capturing transient animal behavior in the field and laboratory remains a logistical and financial challenge, especially for small ectotherms. Here, we present a camera system that is affordable, accessible, and suitable to monitor small, cold-blooded animals historically overlooked by commercial camera traps, such as small amphibians. The system is weather-resistant, can operate offline or online, and allows collection of time-sensitive behavioral data in laboratory and field conditions with continuous data storage for up to four weeks. The lightweight camera can also utilize phone notifications over Wi-Fi so that observers can be alerted when animals enter a space of interest, enabling sample collection at proper time periods. We present our findings, both technological and scientific, in an effort to elevate tools that enable researchers to maximize use of their research budgets. We discuss the relative affordability of our system for researchers in South America, home to the largest ectotherm diversity.

Automated Observations of Dogs' Resting Behaviour Patterns Using Artificial Intelligence and Their Similarity to Behavioural Observations

Although direct behavioural observations are widely used, they are time-consuming, prone to error, require knowledge of the observed species, and depend on intra/inter-observer consistency. As a result, they pose challenges to the reliability and repeatability of studies. Automated video analysis is becoming popular for behavioural observations. Sleep is a biological metric that has the potential to become a reliable broad-spectrum metric that can indicate the quality of life and understanding sleep patterns can contribute to identifying and addressing potential welfare concerns, such as stress, discomfort, or health issues, thus promoting the overall welfare of animals; however, due to the laborious process of quantifying sleep patterns, it has been overlooked in animal welfare research. This study presents a system comparing convolutional neural networks (CNNs) with direct behavioural observation methods for the same data to detect and quantify dogs' sleeping patterns. A total of 13,688 videos were used to develop and train the model to quantify sleep duration and sleep fragmentation in dogs. To evaluate its similarity to the direct behavioural observations made by a single human observer, 6000 previously unseen frames were used. The system successfully classified 5430 frames, scoring a similarity rate of 89% when compared to the manually recorded observations. There was no significant difference in the percentage of time observed between the system and the human observer (p > 0.05). However, a significant difference was found in total sleep time recorded, where the automated system captured more hours than the observer (p < 0.05). This highlights the potential of using a CNN-based system to study animal welfare and behaviour research.

Native prey, not landscape change or novel prey, drive cougar (Puma concolor) distribution at a boreal forest range edge

Many large carnivores, despite widespread habitat alteration, are rebounding in parts of their former ranges after decades of persecution and exploitation. Cougars (Puma concolor) are apex predator with their remaining northern core range constricted to mountain landscapes and areas of western North America; however, cougar populations have recently started rebounding in several locations across North America, including northward in boreal forest landscapes. A camera-trap survey of multiple landscapes across Alberta, Canada, delineated a range edge; within this region, we deployed an array of 47 camera traps in a random stratified design across a landscape spanning a gradient of anthropogenic development relative to the predicted expansion front. We completed multiple hypotheses in an information-theoretic framework to determine if cougar occurrence is best explained by natural land cover features, anthropogenic development features, or competitor and prey activity. We predicted that anthropogenic development features from resource extraction and invading white-tailed deer (Odocoileus virgianius) explain cougar distribution at this boreal range edge. Counter to our predictions, the relative activity of native prey, predominantly snowshoe hare (Lepus americanus), was the best predictor of cougar occurrence at this range edge. Small-bodied prey items are particularly important for female and sub-adult cougars and may support breeding individuals in the northeast boreal forest. Also, counter to our predictions, there was not a strong relationship detected between cougar occurrence and gray wolf (Canis lupus) activity at this range edge. However, further investigation is recommended as the possibility of cougar expansion into areas of the multi-prey boreal system, where wolves have recently been controlled, could have negative consequences for conservation goals in this region (e.g. the recovery of woodland caribou [Rangifer tarandus caribou]). Our study highlights the need to monitor contemporary distributions to inform conservation management objectives as large carnivores recover across North America.

Mesocarnivores vary in their spatiotemporal avoidance strategies at communications hubs of an apex carnivore

Mesocarnivores face interspecific competition and risk intraguild predation when sharing resources with apex carnivores. Within a landscape, carnivores across trophic levels may use the same communication hubs, which provide a mix of risks (injury/death) and rewards (gaining information) for subordinate species. We predicted that mesocarnivores would employ different strategies to avoid apex carnivores at shared communication hubs, depending on their trophic position. To test our prediction, we examined how different subordinate carnivore species in the Santa Cruz Mountains of California, USA, manage spatial overlap with pumas (Puma concolor), both at communication hubs and across a landscape-level camera trap array. We estimated species-specific occurrence, visitation rates, temporal overlap, and Avoidance-Attraction Ratios from camera traps and tested for differences between the two types of sites. We found that mesocarnivores generally avoided pumas at communication hubs, and this became more pronounced when pumas scent-marked during their most recent visit. Coyotes (Canis latrans), the pumas' closest subordinate competitor in our system, exhibited the strongest avoidance at communication hubs. Gray foxes (Urocyon cinereoargenteus) avoided pumas the least, which may suggest possible benefits from pumas suppressing coyotes. Overall, mesocarnivores exhibited various spatiotemporal avoidance strategies at communication hubs rather than outright avoidance, likely because they benefit from information gained while 'eavesdropping' on puma activity. Variability in avoidance strategies may be due to differential predation risks, as apex carnivores often interact more aggressively with their closest competitors. Combined, our results show how apex carnivores trigger complex species interactions across the entire carnivore guild and how trophic position determines behavioral responses and subsequent space use of subordinate mesocarnivores across the landscape.

Using the multivariate Hawkes process to study interactions between multiple species from camera trap data

Interspecific interactions can influence species' activity and movement patterns. In particular, species may avoid or attract each other through reactive responses in space and/or time. However, data and methods to study such reactive interactions have remained scarce and were generally limited to two interacting species. At this time, the deployment of camera traps opens new opportunities but adapted statistical techniques are still required to analyze interaction patterns with such data. We present the multivariate Hawkes process (MHP) and show how it can be used to analyze interactions between several species using camera trap data. Hawkes processes use flexible pairwise interaction functions, allowing us to consider asymmetries and variations over time when depicting reactive temporal interactions. After describing the theoretical foundations of the MHP, we outline how its framework can be used to study interspecific interactions with camera trap data. We design a simulation study to evaluate the performance of the MHP and of another existing method to infer interactions from camera trap-like data. We also use the MHP to infer reactive interactions from real camera trap data for five species from South African savannas (impala Aepyceros melampus, greater kudu Tragelaphus strepsiceros, lion Panthera leo, blue wildebeest Connochaetes taurinus and Burchell's zebra Equus quagga burchelli). The simulation study shows that the MHP can be used as a tool to benchmark other methods of interspecific interaction inference and that this model can reliably infer interactions when enough data are considered. The analysis of real data highlights evidence of predator avoidance by prey and herbivore-herbivore attraction. Lastly, we present the advantages and limits of the MHP and discuss how it can be improved to infer attraction/avoidance patterns more reliably. As camera traps are increasingly used, the multivariate Hawkes process provides a promising framework to decipher the complexity of interactions structuring ecological communities.

Analysing the effects of distance, taxon and biomass on vertebrate detections using bulk-collected carrion fly iDNA

Invertebrate-derived DNA (iDNA) metabarcoding from carrion flies is a powerful, non-invasive tool that has value for assessing vertebrate diversity. However, unknowns exist around the factors that influence vertebrate detections, such as spatial limits to iDNA signals or if detections are influenced by taxonomic class or estimated biomass of the vertebrates of interest. Using a bulk-collection method, we captured flies from within a zoo and along transects extending 4 km away from this location. From 920 flies, we detected 28 vertebrate species. Of the 28 detected species, we identified 9 species kept at the zoo, 8 mammals and 1 bird, but no reptiles. iDNA detections were highly geographically localized, and only a few zoo animals were detected outside the zoo setting. However, due to the low number of detections in our dataset, we found no influence of the taxonomic group or the estimated biomass of animals on their detectability. Our data suggest that iDNA detections from bulk-collected carrion flies, at least in urban settings in Australia, are predominantly determined by geographic proximity to the sampling location. This study presents an important step in understanding how iDNA techniques can be used in biodiversity monitoring.

Using global remote camera data of a solitary species complex to evaluate the drivers of group formation

The social system of animals involves a complex interplay between physiology, natural history, and the environment. Long relied upon discrete categorizations of "social" and "solitary" inhibit our capacity to understand species and their interactions with the world around them. Here, we use a globally distributed camera trapping dataset to test the drivers of aggregating into groups in a species complex (martens and relatives, family Mustelidae, Order Carnivora) assumed to be obligately solitary. We use a simple quantification, the probability of being detected in a group, that was applied across our globally derived camera trap dataset. Using a series of binomial generalized mixed-effects models applied to a dataset of 16,483 independent detections across 17 countries on four continents we test explicit hypotheses about potential drivers of group formation. We observe a wide range of probabilities of being detected in groups within the solitary model system, with the probability of aggregating in groups varying by more than an order of magnitude. We demonstrate that a species' context-dependent proclivity toward aggregating in groups is underpinned by a range of resource-related factors, primarily the distribution of resources, with increasing patchiness of resources facilitating group formation, as well as interactions between environmental conditions (resource constancy/winter severity) and physiology (energy storage capabilities). The wide variation in propensities to aggregate with conspecifics observed here highlights how continued failure to recognize complexities in the social behaviors of apparently solitary species limits our understanding not only of the individual species but also the causes and consequences of group formation.

How landscape traits affect boreal mammal responses to anthropogenic disturbance

Understanding mammalian responses to anthropogenic disturbance is challenging, as ecological processes and the patterns arising therefrom notoriously change across spatial and temporal scales, and among different landscape contexts. Responses to local scale disturbances are likely influenced by landscape context (e.g., overall landscape-level disturbance, landscape-level productivity). Hierarchical approaches considering small-scale sampling sites as nested holons within larger-scale landscapes, which constrain processes in lower-level holons, can potentially explain differences in ecological processes between multiple locations. We tested hypotheses about mammal responses to disturbance and interactions among holons using collected images from 957 camera sites across 9 landscapes in Alberta from 2007 to 2020 and examined occurrence for 11 mammal species using generalized linear mixed models. White-tailed deer occurred more in higher disturbed sites within lower disturbed landscapes (β = -0.30 [-0.4 to -0.15]), whereas occurrence was greater in highly disturbed sites within highly disturbed landscapes for moose (β = 0.20 [0.09-0.31]), coyote (β = 0.20 [0.08-0.26]), and lynx (β = 0.20 [0.07-0.26]). High disturbance sites in high productivity landscapes had higher occurrence of black bears (β = -0.20 [-0.46 to -0.01]), lynx (β = -0.70 [-0.97 to -0.34]), and wolves (β = -0.50 [-0.73 to -0.21]). Conversely, we found higher probability of occurrence in low productivity landscapes with increasing site disturbance for mule deer (β = 0.80 [0.39-1.14]), and white-tailed deer (β = 0.20 [0.01-0.47]). We found the ecological context created by aggregate sums (high overall landscape disturbance), and by subcontinental hydrogeological processes in which that landscape is embedded (high landscape productivity), alter mammalian responses to anthropogenic disturbance at local scales. These responses also vary by species, which has implications for large-scale conservation planning. Management interventions must consider large-scale geoclimatic processes and geographic location of a landscape when assessing wildlife responses to disturbance.

The method matters. A comparative study of biologging and camera traps as data sources with which to describe wildlife habitat selection

Habitat use is a virtually universal activity among animals and is highly relevant as regards designing wildlife management and conservation actions. This has led to the development of a great variety of methods to study it, of which resource selection functions combined with biologging-derived data (RSF) is the most widely used for this purpose. However this approach has some constraints, such as its invasiveness and high costs. Analytical approaches taking into consideration imperfect detection coupled with camera trap data (IDM) have, therefore, emerged as a non-invasive cost-effective alternative. However, despite the fact that both approaches (RSF and IDM) have been used in habitat selection studies, they should also be comparatively assessed. The objective of this work is consequently to assess them from two perspectives: explanatory and predictive. This has been done by analyzing data obtained from camera traps (60 sampling sites) and biologging (17 animals monitored: 7 red deer Cervus elaphus, 6 fallow deer Dama dama and 4 wild boar Sus scrofa) in the same periods using IDM and RSF, respectively, in Doñana National Park (southern Spain) in order to explain and predict habitat use patterns for three studied species. Our results showed discrepancies between the two approaches, as they identified different predictors as being the most relevant to determine species intensity of use, and they predicted spatial patterns of habitat use with a contrasted level of concordance, depending on species and scale. Given these results and the characteristics of each approach, we suggested that although partly comparable interpretations can be obtained with both approaches, they are not equivalent but rather complementary. The combination of data from biologging and camera traps would, therefore, appear to be suitable for the development of an analytical framework with which to describe and characterise the habitat use processes of wildlife.

Forensic experiments on animal scavenging: A systematic literature review on what we have and what we need

Vertebrate scavengers frequently affect forensic casework by feeding on human remains or by scattering body parts and bones. Therefore, animal activity can influence complete recovery of bodies, trauma analysis, and the estimation of the postmortem interval (PMI), potentially hampering identification of the deceased and elucidation of the perimortem circumstances. Experimental research is well suited to investigate scavengers and their impact on carcasses over time, generating knowledge on the forensic relevance of certain scavenger species or communities. However, there are currently no systematised standards to conduct these investigations with a forensic focus, impeding comparison and synthesis of the studies. In our work, we performed a systematic literature review and found 79 publications featuring terrestrial experiments on vertebrate scavenging and/or scattering within a forensic context. We extracted 21 variables describing the study environment, experimental design and the specimens. The results show that there is considerable inconsistency in the study designs and that some of the variables are insufficiently reported. We point out research questions and areas that require attention in future studies, stressing the importance of infrequently mentioned or applied variables. Furthermore, we recommend guidelines to include and report a list of variables in forensic scavenging and scattering experiments. These guidelines will help standardising future research in the field, facilitating inter-study consolidation of results and conclusions, and consequently, inform forensic casework.

Co-circulation of Hepatitis E Virus (HEV) Genotype 3 and Moose-HEV-Like Strains in Free-Ranging-Spotted Deer (Axis axis) in Uruguay

Hepatitis E caused by hepatitis E virus (HEV) is considered an emerging foodborne zoonosis in industrialized, non-endemic countries. Domestic pigs and wild boars are considered the main reservoir of HEV. However, HEV can also infect an ever-expanding host range of animals, but they exact role in transmitting the virus to other species or humans is mostly unknown. In this work, we investigated the spread of HEV in free-living and captive spotted deer (Axis axis) from Uruguay in a 2-year period (2020-2022) and examined the role of this invasive species as a new potential reservoir of the virus. In addition, with the aim to gain new insights into viral ecology in the context of One Health, by using camera trapping, we identified and quantified temporal and spatial coexistence of spotted deer, wild boars, and cattle. In free-living animals, we detected an anti-HEV seropositivity of 11.1% (6/54). HEV infection and viral excretion in feces were assessed by RT-PCR. Thirteen of 19 samples (68.4%) had HEV RNA. Six samples were amplified using a broadly reactive RT-PCR and sequenced. No captive animal showed evidence of HEV infection. Additionally, HEV RNA was detected in a freshwater pond shared by these species. Phylogenetic and p-distance analysis revealed that zoonotic HEV genotype 3 strains circulate together with unclassified variants related to moose HEV whose potential risk of transmission to humans and other domestic and wild animals is unknown. The data presented here suggest that spotted deer (A. axis) may be a novel host for zoonotic HEV strains.

Occupancy of the Ethiopian endemic Moorland Francolin in pristine and degraded Afroalpine biome using a camera trap approach

Occupancy modeling is an essential tool for understanding species-habitat associations, thereby helping to plan the conservation of rare and threatened wildlife species. The conservation status and ecology of several avian species, particularly ground-dwelling birds, are poorly known in Ethiopia. We used camera trap-based occupancy modeling to investigate habitat covariate influence on occupancy (Ψ) and detection probability (ρ) estimates of Moorland Francolins Scleroptila psilolaema from spatially replicated surveys across both relatively pristine and disturbed landscapes in the Afroalpine biome of Ethiopia. Model-averaged estimate of ψ ^ across all sites was 0.76 (SD = 0.28) and ρ ^ was 0.77 (SD = 0.13) in the pristine landscape. The ψ ^ of the species in the disturbed landscape was 0.56 (SD = 0.19) and ρ ^ was 0.48 (SD = 0.06). As hypothesized, based on our model-averaged beta coefficient estimates (βmean ± SE), predators significantly negatively influenced the occupancy of Moorland Francolins in pristine habitat. We also found a significant positive association of occupancy with herb species richness. Contrary to our prediction, distance to road significantly negatively influence the occupancy of the species, suggesting that occupancy probability was highest in proximity to roadsides and trails in the pristine habitat. There was no significant influence of habitat covariates on the occupancy of the species in the disturbed habitat. The most important covariates that significantly influence the detectability of the species in pristine habitat included sampling occasion and precipitation. The greater occupancy and detectability of this endemic species in the pristine habitat could be linked with the particular conservation status and management of this biodiversity hotspot in the central highlands of Ethiopia. Our results suggest that strict legal enforcement is required to sustainably preserve Moorland Francolins and the ecological integrity of the entire Afroalpine biome. We recommend using camera traps in order to develop realistic and effective conservation and management strategies for rare, sensitive, cryptic, and ground-dwelling animals in the region.

A simple framework for maximizing camera trap detections using experimental trials

Camera trap data are biased when an animal passes through a camera's field of view but is not recorded. Cameras that operate using passive infrared sensors rely on their ability to detect thermal energy from the surface of an object. Optimal camera deployment consequently depends on the relationship between a sensor array and an animal. Here, we describe a general, experimental approach to evaluate detection errors that arise from the interaction between cameras and animals. We adapted distance sampling models and estimated the combined effects of distance, camera model, lens height, and vertical angle on the probability of detecting three different body sizes representing mammals that inhabit temperate, boreal, and arctic ecosystems. Detection probabilities were best explained by a half-normal-logistic mixture and were influenced by all experimental covariates. Detection monotonically declined when proxies were ≥6 m from the camera; however, models show that body size and camera model mediated the effect of distance on detection. Although not a focus of our study, we found that unmodeled heterogeneity arising from solar position has the potential to bias inferences where animal movements vary over time. Understanding heterogeneous detection probabilities is valuable when designing and analyzing camera trap studies. We provide a general experimental and analytical framework that ecologists, citizen scientists, and others can use and adapt to optimize camera protocols for various wildlife species and communities. Applying our framework can help ecologists assess trade-offs that arise from interactions among distance, cameras, and body sizes before committing resources to field data collection.

Rural selection drives the evolution of an urban-rural cline in coat color in gray squirrels

Phenotypic differences between urban and rural populations are well-documented, but the evolutionary processes driving trait variation along urbanization gradients are often unclear. We combined spatial data on abundance, trait variation, and measurements of fitness to understand cline structure and test for natural selection on heritable coat color morphs (melanic, gray) of eastern gray squirrels (Sciurus carolinensis) along an urbanization gradient. Population surveys using remote cameras and visual counts at 76 sites along the urbanization gradient revealed a significant cline in melanism, decreasing from 48% in the city center to <5% in rural woodlands. Among 76 squirrels translocated to test for phenotypic selection, survival was lower for the melanic than gray morph in rural woodlands, whereas there was no difference in survival between color morphs in the city. These results suggest the urban-rural cline in melanism is explained by natural selection favoring the gray morph in rural woodlands combined with relaxed selection in the city. Our study illustrates how trait variation between urban and rural populations can emerge from selection primarily in rural populations rather than adaptation to novel features of the urban environment.

Capturing red squirrels (Sciurus vulgaris) on camera: A cost-effective approach for monitoring relative abundance and habitat preference

Effective methods for monitoring animal populations are crucial for species conservation and habitat management. Motion-activated cameras provide an affordable method for passively surveying animal presence across the landscape but have mainly been used for studying large-bodied mammals. This paper explores the relative abundance and habitat preferences of red squirrels (Sciurus vulgaris) in coniferous forests using cameras and live trapping. The study was conducted in two forests (Newborough and Pentraeth) on Anglesey, North Wales, with a total of 50 sampling locations across four habitat categories. Detailed woodland structure and composition data were gathered around each sampling location. We found a strong positive correlation between the number of individual red squirrels live trapped over 10 days with the number of camera images of squirrels recorded during a previous 5-day period. The time interval between camera deployment and the first recorded image of a red squirrel showed a significant negative correlation with the number of individuals live trapped. Red squirrel relative abundance was negatively related to forest canopy openness, while the presence of Scots pine and increased tree species diversity were positively associated with the relative abundance of squirrels. There was also a strong site difference with lower relative abundance at Newborough compared with Pentraeth, which likely reflects the heavy thinning of mature forest at Newborough reducing tree crown connectivity. The results show that remotely activated cameras are an effective method for monitoring red squirrel populations across varying animal densities. The cameras also provided crucial information on red squirrel habitat preferences that can aid in woodland management and conservation efforts. Cameras have great potential to collect data on the population status of other small mammals, but it is essential that these methods are validated on a species-by-species basis.

Assessing mammal population densities in response to urbanization using camera trap distance sampling

Environmental filtering is deemed to play a predominant role in regulating the abundance and distribution of animals during the urbanization process. However, the current knowledge about the effects of urbanization on the population densities of terrestrial mammals is limited. In this study, we compared two invasive mammals (dogs Canis lupus familiaris and cats Felis silvestris) and three indigenous mammals (Siberian weasels Mustela sibirica, Amur hedgehogs Erinaceus amurensis, and Tolai hares Lepus tolai) in response to urbanization using camera trap distance sampling (CTDS) in the rural-urban landscape of Tianjin, China. We used generalized additive mixed models (GAMMs) to test the specific responses of their densities to levels of urbanization. Invasive dogs (2.63 individuals/km2, 95% CI: 0.91-7.62) exhibited similar density estimations to cats (2.15 individuals/km2, 95% CI: 1.31-3.50). Amur hedgehogs were the most abundant species (6.73 individuals/km2, 95% CI: 3.15-14.38), followed by Tolai hares (2.22 individuals/km2, 95% CI: 0.87-5.68) and Siberian weasels (2.15 individuals/km2, 95% CI: 1.06-4.36). The densities of cats, Siberian weasels, and Amur hedgehogs increased with the level of urbanization. The population densities of dogs and cats were only influenced by urban-related variables, while the densities of Siberian weasels and Amur hedgehogs were influenced by both urban-related variables and nature-related variables. Our findings highlight that the CTDS is a suitable and promising method for wildlife surveys in rural-urban landscapes, and urban wildlife management needs to consider the integrated repercussions of urban- and nature-related factors, especially the critical impacts of green space habitats at finer scales.

Estimating effective survey duration in camera trap distance sampling surveys

Among other approaches, camera trap distance sampling (CTDS) is used to estimate animal abundance from unmarked populations. It was formulated for videos and observation distances are measured at predetermined 'snapshot moments'. Surveys recording still images with passive infrared motion sensors suffer from frequent periods where animals are not photographed, either because of technical delays before the camera can be triggered again (i.e. 'camera recovery time') or because they remain stationary and do not immediately retrigger the camera following camera recovery time (i.e. 'retrigger delays'). These effects need to be considered when calculating temporal survey effort to avoid downwardly biased abundance estimates. Here, we extend the CTDS model for passive infrared motion sensor recording of single images or short photo series. We propose estimating 'mean time intervals between triggers' as combined mean camera recovery time and mean retrigger delays from the time interval distribution of pairs of consecutive pictures, using a Gamma and Exponential function, respectively. We apply the approach to survey data on red deer, roe deer and wild boar. Mean time intervals between triggers were very similar when estimated empirically and when derived from the model-based approach. Depending on truncation times (i.e. the time interval between consecutive pictures beyond which data are discarded) and species, we estimated mean time intervals between retriggers between 8.28 and 15.05 s. Using a predefined snapshot interval, not accounting for these intervals, would lead to underestimated density by up to 96% due to overestimated temporal survey effort. The proposed approach is applicable to any taxa surveyed with camera traps. As programming of cameras to record still images is often preferred over video recording due to reduced consumption of energy and memory, we expect this approach to find broad application, also for other camera trap methods than CTDS.

Simulation-based assessment of the performance of hierarchical abundance estimators for camera trap surveys of unmarked species

Knowledge on animal abundances is essential in ecology, but is complicated by low detectability of many species. This has led to a widespread use of hierarchical models (HMs) for species abundance, which are also commonly applied in the context of nature areas studied by camera traps (CTs). However, the best choice among these models is unclear, particularly based on how they perform in the face of complicating features of realistic populations, including: movements relative to sites, multiple detections of unmarked individuals within a single survey, and low detectability. We conducted a simulation-based comparison of three HMs (Royle-Nichols, binomial N-mixture and Poisson N-mixture model) by generating groups of unmarked individuals moving according to a bivariate Ornstein-Uhlenbeck process, monitored by CTs. Under a range of simulated scenarios, none of the HMs consistently yielded accurate abundances. Yet, the Poisson N-mixture model performed well when animals did move across sites, despite accidental double counting of individuals. Absolute abundances were better captured by Royle-Nichols and Poisson N-mixture models, while a binomial N-mixture model better estimated the actual number of individuals that used a site. The best performance of all HMs was observed when estimating relative trends in abundance, which were captured with similar accuracy across these models.

Mammalian predator and prey responses to recreation and land use across multiple scales provide limited support for the human shield hypothesis

Outdoor recreation is widespread, with uncertain effects on wildlife. The human shield hypothesis (HSH) suggests that recreation could have differential effects on predators and prey, with predator avoidance of humans creating a spatial refuge 'shielding' prey from people. The generality of the HSH remains to be tested across larger scales, wherein human shielding may prove generalizable, or diminish with variability in ecological contexts. We combined data from 446 camera traps and 79,279 sampling days across 10 landscapes spanning 15,840 km2 in western Canada. We used hierarchical models to quantify the influence of recreation and landscape disturbance (roads, logging) on ungulate prey (moose, mule deer and elk) and carnivore (wolf, grizzly bear, cougar and black bear) site use. We found limited support for the HSH and strong responses to recreation at local but not larger spatial scales. Only mule deer showed positive but weak landscape-level responses to recreation. Elk were positively associated with local recreation while moose and mule deer responses were negative, contrary to HSH predictions. Mule deer showed a more complex interaction between recreation and land-use disturbance, with more negative responses to recreation at lower road density or higher logged areas. Contrary to HSH predictions, carnivores did not avoid recreation and grizzly bear site use was positively associated. We also tested the effects of roads and logging on temporal activity overlap between mule deer and recreation, expecting deer to minimize interaction with humans by partitioning time in areas subject to more habitat disturbance. However, temporal overlap between people and deer increased with road density. Our findings highlight the complex ecological patterns that emerge at macroecological scales. There is a need for expanded monitoring of human and wildlife use of recreation areas, particularly multi-scale and -species approaches to studying the interacting effects of recreation and land-use change on wildlife.

Wolf contact in horses at permanent pasture in Germany

Wolves returned to Germany in 2000, leading to fear in German horse owners that their horses could be in danger of wolf attacks or panic-like escapes from pastures when sighting wolves. However, reports from southern European countries indicate that wolf predation on horses diminishes with increasing presence of wildlife. Therefore, we conducted a long-term, filed observation between January 2015 and July 2022 on 13 non breeding riding horses, mares and geldings, kept permanently on two pastures within the range of wildlife and a stable wolf pack with annual offspring. Wildlife cameras at the fences of the pastures made 984 times recordings of wolves and 3151 times recordings of wildlife in and around the pastures. Between 1 January 2022 and 23 March 2022 we observed two stable horse groups. Pasture 1 was grazed by five horses of mixed breed, four mares and one gelding, with the median age of 8 years (min. = 6y, max. = 29y). Pasture 2 was grazed by eight heavy warmbloods and draught horses, three mares and five geldings, with the median age of 16 years (min. = 13y, max. = 22y). During this period no wolf was recorded at pasture 2, but wild boar several times, whereas at pasture 1, wolves were recorded 89 times, and for the wildlife mostly hare. Wolves may have avoided pasture 2 because of the presence of wild boar or because the large group of older, heavy breed horses may have formed a stable, protective group. The latter needs to be confirmed in a follow-up field observation, which records anti-predator behavior and welfare indicators in horses. In conclusion, wolves did not attack the mature horses on pastures with plenty of wildlife and the horses did not respond to the presence of wolves with visible signs of reduced welfare or panic. This indicates that wolves may prefer to prey on easily accessible wildlife around and at horse pastures and that Central European horses become accustom to the presence of non-hunting wolves.

Camera trapping expands the view into global biodiversity and its change

Growing threats to biodiversity demand timely, detailed information on species occurrence, diversity and abundance at large scales. Camera traps (CTs), combined with computer vision models, provide an efficient method to survey species of certain taxa with high spatio-temporal resolution. We test the potential of CTs to close biodiversity knowledge gaps by comparing CT records of terrestrial mammals and birds from the recently released Wildlife Insights platform to publicly available occurrences from many observation types in the Global Biodiversity Information Facility. In locations with CTs, we found they sampled a greater number of days (mean = 133 versus 57 days) and documented additional species (mean increase of 1% of expected mammals). For species with CT data, we found CTs provided novel documentation of their ranges (93% of mammals and 48% of birds). Countries with the largest boost in data coverage were in the historically underrepresented southern hemisphere. Although embargoes increase data providers' willingness to share data, they cause a lag in data availability. Our work shows that the continued collection and mobilization of CT data, especially when combined with data sharing that supports attribution and privacy, has the potential to offer a critical lens into biodiversity. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Influence of heterospecifics on mesocarnivore behaviour at shared scavenging opportunities in the Canadian Rocky Mountains

In seasonal environments, the ability of mustelid species to acquire carrion-a dietary resource heavily depended upon-is driven by a collection local habitat characteristics and competition dynamics. In resource-scarce winter, sympatric mesocarnivores must balance energetic rewards of carrion with avoiding antagonistic interactions with conspecifics. We examined scavenging interactions among three mustelid species in the northern Canadian Rocky Mountains. Camera traps (n = 59) were baited with carrion during winter between 2006 to 2008. Spatial and temporal dimensions of scavenger behaviour (i.e., carcass use) were evaluated using a multi-model approach, which enabled us to recognize potentially adaptive behavioural mechanisms for mitigating competition at carcass sites. Best performing models indicated that carrion site use is governed by a combination of competition threats and environmental factors. A decrease in scavenging with increasing snow depth was observed across all species. Mustelids adopted a host of adaptive behavioural strategies to access shared scavenging opportunities. We found evidence that wolverine (Gulo gulo) and American marten (Martes americana) segregate in space but temporally tracked one another. Short-tailed weasel (Mustela erminea) scavenging decreased with greater site use by marten. Carcass availability across a spatially complex environment, as well as spatial-temporal avoidance strategies, can facilitate carrion resource partitioning.

Impacts of large herbivores on terrestrial ecosystems

Large herbivores play unique ecological roles and are disproportionately imperiled by human activity. As many wild populations dwindle towards extinction, and as interest grows in restoring lost biodiversity, research on large herbivores and their ecological impacts has intensified. Yet, results are often conflicting or contingent on local conditions, and new findings have challenged conventional wisdom, making it hard to discern general principles. Here, we review what is known about the ecosystem impacts of large herbivores globally, identify key uncertainties, and suggest priorities to guide research. Many findings are generalizable across ecosystems: large herbivores consistently exert top-down control of plant demography, species composition, and biomass, thereby suppressing fires and the abundance of smaller animals. Other general patterns do not have clearly defined impacts: large herbivores respond to predation risk but the strength of trophic cascades is variable; large herbivores move vast quantities of seeds and nutrients but with poorly understood effects on vegetation and biogeochemistry. Questions of the greatest relevance for conservation and management are among the least certain, including effects on carbon storage and other ecosystem functions and the ability to predict outcomes of extinctions and reintroductions. A unifying theme is the role of body size in regulating ecological impact. Small herbivores cannot fully substitute for large ones, and large-herbivore species are not functionally redundant - losing any, especially the largest, will alter net impact, helping to explain why livestock are poor surrogates for wild species. We advocate leveraging a broad spectrum of techniques to mechanistically explain how large-herbivore traits and environmental context interactively govern the ecological impacts of these animals.

Camera Trap Methods and Drone Thermal Surveillance Provide Reliable, Comparable Density Estimates of Large, Free-Ranging Ungulates

Camera traps and drone surveys both leverage advancing technologies to study dynamic wildlife populations with little disturbance. Both techniques entail strengths and weaknesses, and common camera trap methods can be confounded by unrealistic assumptions and prerequisite conditions. We compared three methods to estimate the population density of white-tailed deer (Odocoileus virgnianus) in a section of Pilot Mountain State Park, NC, USA: (1) camera trapping using mark-resight ratios or (2) N-mixture modeling and (3) aerial thermal videography from a drone platform. All three methods yielded similar density estimates, suggesting that they converged on an accurate estimate. We also included environmental covariates in the N-mixture modeling to explore spatial habitat use, and we fit models for each season to understand temporal changes in population density. Deer occurred in greater densities on warmer, south-facing slopes in the autumn and winter and on cooler north-facing slopes and in areas with flatter terrain in the summer. Seasonal density estimates over two years suggested an annual cycle of higher densities in autumn and winter than in summer, indicating that the region may function as a refuge during the hunting season.

Combining multiple data sources with different biases in state-space models for population dynamics

The resolution at which animal populations can be modeled can be increased when multiple datasets corresponding to different life stages are available, allowing, for example, seasonal instead of annual descriptions of dynamics. However, the abundance estimates used for model fitting can have multiple sources of error, both random and systematic, namely bias. We focus here on the consequences of, and how to address, differing and unknown observation biases when fitting models.State-space models (SSMs) separate process variation and observation error, thus providing a framework to account for different and unknown estimate biases across multiple datasets. Here we study the effects on the inference of including or excluding bias parameters for a sequential life stage population dynamics SSM using a combination of theory, simulation experiments, and an empirical example.When the data, that is, abundance estimates, are unbiased, including bias parameters leads to increased imprecision compared to a model that correctly excludes bias parameters. But when observations are biased and no bias parameters are estimated, recruitment and survival processes are inaccurately estimated and estimates of process variance become biased high. These problems are substantially reduced by including bias parameters and fixing one of them at even an incorrect value. The primary inferential challenge is that models with bias parameters can show properties of being parameter redundant even when they are not in theory.Combining multiple datasets into a single analysis by using bias parameters to rescale data can offer significant improvements to inference and model diagnostics. Because their estimability in practice is dataset specific and will likely require more precise estimates than might be expected from ecological datasets, we outline some strategies for characterizing process uncertainty when it is confounded by bias parameters.

Human presence and infrastructure impact wildlife nocturnality differently across an assemblage of mammalian species

Wildlife species may shift towards more nocturnal behavior in areas of higher human influence, but it is unclear how consistent this shift might be. We investigated how humans impact large mammal diel activities in a heavily recreated protected area and an adjacent university-managed forest in southwest British Columbia, Canada. We used camera trap detections of humans and wildlife, along with data on land-use infrastructure (e.g., recreation trails and restricted-access roads), in Bayesian regression models to investigate impacts of human disturbance on wildlife nocturnality. We found moderate evidence that black bears (Ursus americanus) were more nocturnal in response to human detections (mean posterior estimate = 0.35, 90% credible interval = 0.04 to 0.65), but no other clear relationships between wildlife nocturnality and human detections. However, we found evidence that coyotes (Canis latrans) (estimates = 0.81, 95% CI = 0.46 to 1.17) were more nocturnal and snowshoe hares (Lepus americanus) (estimate = -0.87, 95% CI = -1.29 to -0.46) were less nocturnal in areas of higher trail density. We also found that coyotes (estimate = -0.87, 95% CI = -1.29 to -0.46) and cougars (Puma concolor) (estimate = -1.14, 90% CI = -2.16 to -0.12) were less nocturnal in areas of greater road density. Furthermore, coyotes, black-tailed deer (Odocoileus hemionus), and snowshoe hares were moderately more nocturnal in areas near urban-wildland boundaries (estimates and 90% CIs: coyote = -0.29, -0.55 to -0.04, black-tailed deer = -0.25, -0.45 to -0.04, snowshoe hare = -0.24, -0.46 to -0.01). Our findings imply anthropogenic landscape features may influence medium to large-sized mammal diel activities more than direct human presence. While increased nocturnality may be a promising mechanism for human-wildlife coexistence, shifts in temporal activity can also have negative repercussions for wildlife, warranting further research into the causes and consequences of wildlife responses to increasingly human-dominated landscapes.

Daily and Seasonal Activity Patterns of Plateau Pikas (Ochotona curzoniae) on the Qinghai-Tibet Plateau, China, and Their Relationship with Weather Condition

Exploring the activity patterns of small mammals is important for understanding the survival strategies of these animals, such as foraging and mating. The purpose of the present study was to determine the activity of free-living plateau pikas (Ochotona curzoniae) in different months and seasons (cold and warm seasons), with a particular emphasis on the effects of weather condition. Based on a camera-trapping survey conducted from October 2017 to September 2018, we evaluated the activity patterns and activity levels of plateau pikas inhabiting the eastern Qinghai-Tibet Plateau in China. The effects of environmental factors on the activity of plateau pikas were examined using the generalized additive mixed model (GAMM). The results showed that: (1) The plateau pikas exhibited unimodal patterns of activity during the cold season (October-April). During the warm season (May-September), the activity patterns of the plateau pikas were bimodal. Their activity levels were highest in June. (2) During the cold season, their activity levels rose gradually over the course of the day to a peak near noon, and they were not significantly higher after sunrise than they were before sunset. During the warm season, their activity peaks were in the morning and afternoon, and their activity levels were substantially lower after sunrise than they were before sunset. (3) The plateau pikas were more active under conditions with lower ambient temperatures and precipitation during the cold and warm seasons. While relative air humidity was positively correlated with the activity of the plateau pikas during the warm season, wind speed was negatively correlated with the pikas' activity during the cold season. Overall, these results collectively indicate that plateau pikas occupy habitats with cool and less windy microclimates during the cold season, and with cool and moist microclimates during the warm season. Information on the time allocation of pikas' activity levels during different seasons should provide a baseline for understanding their potential for adaptation to climate change.

Animal Species Recognition with Deep Convolutional Neural Networks from Ecological Camera Trap Images

Accurate identification of animal species is necessary to understand biodiversity richness, monitor endangered species, and study the impact of climate change on species distribution within a specific region. Camera traps represent a passive monitoring technique that generates millions of ecological images. The vast numbers of images drive automated ecological analysis as essential, given that manual assessment of large datasets is laborious, time-consuming, and expensive. Deep learning networks have been advanced in the last few years to solve object and species identification tasks in the computer vision domain, providing state-of-the-art results. In our work, we trained and tested machine learning models to classify three animal groups (snakes, lizards, and toads) from camera trap images. We experimented with two pretrained models, VGG16 and ResNet50, and a self-trained convolutional neural network (CNN-1) with varying CNN layers and augmentation parameters. For multiclassification, CNN-1 achieved 72% accuracy, whereas VGG16 reached 87%, and ResNet50 attained 86% accuracy. These results demonstrate that the transfer learning approach outperforms the self-trained model performance. The models showed promising results in identifying species, especially those with challenging body sizes and vegetation.

Understanding carnivore interactions in a cold arid trans-Himalayan landscape: What drives co-existence patterns within predator guild along varying resource gradients?

Predators compete for resources aggressively, forming trophic hierarchies that shape the structure of an ecosystem. Competitive interactions between species are modified in the human-altered environment and become particularly important where an introduced predator can have negative effects on native predator and prey species. The trans-Himalayan region of northern India has seen significant development in tourism and associated infrastructure over the last two decades, resulting in many changes to the natural setting of the landscape. While tourism, combined with unmanaged garbage can facilitate red fox (Vulpes vulpes), it also allows free-ranging dogs (Canis lupus familiaris), an introduced mesopredator to thrive, possibly more than the native red fox. We look at the little-known competitive dynamics of these two meso-carnivores, as well as their intra-guild interactions with the region's top carnivores, the snow leopard (Panthera uncia) and the Himalayan wolf (Canis lupus chanco). To study interactions between these four carnivores, we performed multispecies occupancy modeling and analyzed spatiotemporal interactions between these predators using camera trap data. We also collected scat samples to calculate dietary niche overlaps and determine the extent of competition for food resources between these carnivores. The study found that, after controlling for habitat and prey covariates, red fox site use was related positively to snow leopard site use, but negatively to dog and wolf site use. In addition, site use of the dog was associated negatively with top predators, that is, snow leopard and Himalayan wolf, while top predators themselves related negatively in their site use. As anthropogenic impacts increase, we find that these predators coexist in this resource-scarce landscape through dietary or spatiotemporal segregation, implying competition for limited resources. Our research adds to the scant ecological knowledge of the predators in the region and improves our understanding of community dynamics in human-altered ecosystems.

Long-term monitoring of mammal communities in the Peneda-Gerês National Park using camera-trap data

Background

In the past decades, agricultural land abandonment and declining land-use intensity became common, especially in the Mediterranean countries of southern Europe. In some areas, this development opened up possibilities for rewilding and the recolonisation or expansion of large mammal populations. Yet, in some instances, co-occurrence of wild mammals and free-ranging domestic herbivores might lead to potential conflicts. It is, therefore, necessary to study the ecological interactions between wild and domestic mammal species to understand the effects of land abandonment and rewilding on biodiversity and ecosystem services. Camera traps are an effective tool for studying species interactions and occupancy dynamics as they allow for long-term monitoring with minimal interference. We conducted a long-term monitoring programme with camera traps in the Peneda-Gerês National Park in northern Portugal. The area has undergone substantial land-use changes following the abandonment of agricultural areas in the past 60 years. While agro-pastoral activities, especially the breeding of free-ranging horses and cattle, are still common in the area, the intensity of these activities has decreased significantly, promoting natural succession and an increase or return of several large mammal species in recent years. Overall, our project aims at: (1) assessing the population trends of the medium and large sized mammals in the area over time; (2) analysing the effects of passive rewilding on occurrence, abundance and behaviour; and (3) understanding potential interactions or conflicts between wild and domestic herbivores. In this publication, we present results of a primary occupancy analysis between 2015 and 2020, as well as a comparison between occupancy and density estimates for 2019.

New information

Our publication provides a dataset from long-term camera-trap monitoring in the Peneda-Gerês National Park between 2015 and 2021. We established a 16 km² grid of 64 cameras deployed yearly during the summer months. Together with this publication, we publish the data and images collected between 2015 and 2021, using both the Camtrap DP standard and the GBIF Darwin Event Core. We obtained a total of 934,810 pictures on 41,234 trap nights. The pictures were automatically grouped into sequences with each sequence representing a distinct occurrence event, resulting in 80,191 occurrences. Out of those, 14,442 contained observations of a species, while the remaining were either blank or the species was not identifiable. We only obtained the information whether a species was present or absent on a picture, disregarding the number of individuals. Most observations were of domestic cattle (Bostaurus) and horses (Equuscaballus), followed by European roe deer (Capreoluscapreolus) and wild boar (Susscrofa). Further observations include red fox (Vulpesvulpes), gray wolf (Canislupus), Eurasian badger (Melesmeles), stone marten (Martesfoina), common genet (Genettagenetta), Iberian ibex (Caprapyrenaica) and red deer (Cervuselaphus). We estimated occupancy and densities for the most common species. The project is on-going and additional data will be included in the future. The dataset is freely available for ecological analysis, but also for training machine-learning systems in automated image classification as all pictures have been manually classified.

A Camera-Trap Survey of Mammals in Thung Yai Naresuan (East) Wildlife Sanctuary in Western Thailand

The Thung Yai Naresuan (East) Wildlife Sanctuary (TYNE), in the core area of the Western Forest Complex of Thailand, harbors a diverse assemblage of wildlife, and the region has become globally significant for mammal conservation. From April 2010 to January 2012, 106 camera traps were set, and, in 1817 trap-nights, registered 1821 independent records of 32 mammal species. Of the 17 IUCN-listed (from Near Threatened to Critically Endangered) mammal species recorded, 5 species listed as endangered or critically endangered included the Asiatic elephant (Elephas maximus), tiger (Panthera tigris), Malayan tapir (Tapirus indicus), dhole (Cuon alpinus), and Sunda pangolin (Manis javanica). The northern red muntjac (Muntiacus vaginalis), large Indian civet (Viverra zibetha), Malayan porcupine (Hystrix brachyuran), and sambar deer (Cervus unicolor) were the most frequently recorded species (10-22 photos/100 trap-nights), representing 62% of all independent records, while the golden jackal (Canis aureus), clouded leopard (Neofelis nebulosa), marbled cat (Pardofelis marmorata), and Sunda pangolin were the least photographed (<0.1/100 trap-nights). Species accumulation curves indicated that the number of camera trap locations needed to record 90% of taxa recorded varied from 26 sites for herbivores to 67 sites for all mammals. TYNE holds a rich community of mammals, but some differences in photo-rates from an adjacent sanctuary and comparisons with other research on local mammals suggest that some species are rare and some are missed because of the limitations of our technique. We also conclude that the management and conservation plan, which involves the exclusion of human activities from some protected areas and strict protection efforts in the sanctuaries, is still suitable for providing key habitats for endangered wildlife populations, and that augmented and regular survey efforts will help in this endeavor.

Daily activity timing in the Anthropocene

Animals are facing novel 'timescapes' in which the stimuli entraining their daily activity patterns no longer match historical conditions due to anthropogenic disturbance. However, the ecological effects (e.g., altered physiology, species interactions) of novel activity timing are virtually unknown. We reviewed 1328 studies and found relatively few focusing on anthropogenic effects on activity timing. We suggest three hypotheses to stimulate future research: (i) activity-timing mismatches determine ecological effects, (ii) duration and timing of timescape modification influence effects, and (iii) consequences of altered activity timing vary biogeographically due to broad-scale variation in factors compressing timescapes. The continued growth of sampling technologies promises to facilitate the study of the consequences of altered activity timing, with emerging applications for biodiversity conservation.

The Factors Influencing Wildlife to Use Existing Bridges and Culverts in Giant Panda National Park

Roads, acting as barriers, hamper wildlife movements and disrupt habitat connectivity. Bridges and culverts are common structures on roads, and some of them can function to allow wildlife passage. This study investigated the effects of traffic, the surrounding landscape, human disturbance, and bridge and culvert structures on the utilization of bridges and culverts as dedicated passages by wildlife, using motion-activated infrared camera traps along a 64 km road in Giant Panda National Park, Sichuan, China. The results show that both species richness and counts of wildlife recorded at the bridge and culvert were significantly lower than those observed at sites distant from roads. No large-sized wildlife was recorded at the bridges and culverts. Human activities and traffic volume significantly and negatively affect medium-sized wildlife utilization of bridges and culverts. We conclude that bridges and culverts serve as wildlife crossings, but their efficacy is weak. This emphasizes the necessity of retrofitting bridges and culverts via mitigation facilities such as noise and light barriers, and vegetation restoration on both sides of the roads in Giant Panda National Park.

Prediction of the visit and occupy of the sika deer (Cervus nippon) during the summer season using a virtual ecological approach

Prediction of the spaces used by animals is an important component of wildlife management, but requires detailed information such as animal visit and occupy in a short span of the target species. Computational simulation is often employed as an effective and economical approach. In this study, the visit and occupy of sika deer (Cervus nippon) during the plant growing season were predicted using a virtual ecological approach. A virtual ecological model was established to predict the visit and occupy of sika deer based on the indices of their food resources. The simulation results were validated against data collected from a camera trapping system. The study was conducted from May to November in 2018 in the northern Kanto region of Japan. The predictive performance of the model using the kernel normalized difference vegetation index (kNDVI) was relatively high in the earlier season, whereas that of the model using landscape structure was relatively low. The predictive performance of the model using combination of the kNDVI and landscape structure was relatively high in the later season. Unfortunately, visit and occupy of sika deer could not predict in November. The use of both models, depending on the month, achieved the best performance to predict the movements of sika deer.

The Open-source Camera Trap for Organism Presence and Underwater Surveillance (OCTOPUS)

This Open-source Camera Trap for Organism Presence and Underwater Surveillance (OCTOPUS) was designed to operate as a motion activated camera trap, deployable at depths of up to 800 ft for ∼72 h deployments. The core components of the OCTOPUS are built off a Raspberry Pi 3B+ with a custom PCB hat which operates a strobe lighting system and a high definition Arducam camera. When an appropriate threshold of motion is detected, the OCTOPUS captures a high-definition image of the subject. Field trials for this system demonstrated its use for cryptic benthic organisms, specifically small octopus (Octopus rubescens). The OCTOPUS collected data on several species allowing the observation and quantification of interspecific and conspecific interactions. This system unlocks the potential of autonomous underwater data collection for a wide range of applications, from species specific observations to large scale ecological assessments.