Camera Sites Research Articles

Human activities reshape the spatial overlap between North Chinese leopard and its wild ungulate prey

BackgroundRapidly expanding human activities have profoundly changed the habitat use of both large carnivores and their prey, but whether and how human activities affect the interactions between them has received relatively less attention. In this study, we conducted a systematically designed camera-trapping survey on an endangered large carnivore (North Chinese leopard Panthera pardus japonensis) and its wild ungulate prey (Siberian roe deer Capreolus pygargus and wild boar Sus scrofa) in the Taihang Mountains of central North China. Using conditional two-species occupancy model based on data derived from the extensive sampling effort (15,654 camera-days at 102 camera sites), we examined the relationship of spatial use between leopards and each prey species under the effects of human presence, free-ranging cattle, roads and settlements.ResultsHumans and cattle had contrasting effects on the relationship of spatial use between leopard and roe deer, with higher and lower spatial segregation between them at human and cattle-frequented sites, respectively. Roads might create a shelter for wild boar from leopard predation, with less spatial segregation between them at sites close to the roads.ConclusionsOur findings demonstrate that human activities are reshaping the spatial overlap between large carnivores and their prey, and have non-equivalent effects among different types of human activity. Such effects may further alter the strength of interspecific interactions between predator and prey, with far-reaching influences on the community and ecosystem that require more research.

Impacts of coyote colonization on coastal mammalian predators

Extreme ecosystem modification by humans has caused drastic reductions in populations and ranges of top mammalian predators, while simultaneously allowing synanthropic mesopredator species to expand. These conditions often result in inflated local densities of highly adaptable mesopredators that disrupt trophic dynamics and place unsustainable predation pressure on native prey populations. Colonization of a dominant predator may lead to top-down control of mesopredators and restore trophic balance. Coyotes are a novel colonizer of some coastal barrier islands of eastern North America, offering an opportunity to test how the addition of an apex predator impacts an established guild of mesopredators. To assess their trophic impact, we conducted 75,576 camera trapping hours over an 18-month study period, capturing > 1.5 million images across 108 coastal camera sites. Using two-species occupancy and habitat use models, we found sizeable effects of coyote habitat use on that of red foxes and free-ranging domestic cats, suggesting that coyotes function as apex predators in barrier island ecosystems. In fact, the only factor that determined the spatial pattern of highly ubiquitous red foxes was the sympatric habitat use of the largest carnivore in the food web—coyotes. That ‘novel’ apex predators can become established in coastal food webs illustrates the highly dynamic nature of conservation challenges for habitats and species at the edge of the sea.

Patterns of breeding in the long-nosed potoroo revealed by camera trapping in northern New South Wales

The breeding pattern of the long-nosed potoroo (Potorous tridactylus) has not been described in the north of its geographic range. Long-nosed potoroos were continuously monitored at eight camera sites on the New England Tableland in northern New South Wales over a 17-month period. Evidence of breeding relied on detecting females with pouch bulges and young-at-foot. Breeding occurred throughout the year but pouch bulges were more commonly seen in May and October than in other months. Females produced two to four young per site, equating to 2.1 per year. This study has demonstrated the great potential of using camera trapping to describe aspects of the breeding pattern in a cryptic marsupial.

Implementation Mapping of the Collaborative University of California Teleophthalmology Initiative (CUTI): A Qualitative Study Using the Exploration, Preparation, Implementation, and Sustainment (EPIS) Framework.

Background This study aimed to investigate the rationale, barriers, and facilitators of teleretinal camera implementation in primary care and endocrinology clinics for diabetic retinopathy (DR) screening across University of California (UC) health systems utilizing the Exploration, Preparation, Implementation, and Sustainment (EPIS) framework. Methodology Institutional representatives from UC Los Angeles, San Diego, San Francisco, and Davis participated in a series of focus group meetings to elicit implementation facilitators and barriers for teleophthalmology programs within their campuses. Site representatives also completed a survey regarding their program's performance over the calendar year 2022 in the following areas: DR screening camera sites, payment sources and coding, screening workflows including clinical, information technology (IT), reading, results, pathologic findings, and follow-up, including patient outreach for abnormal results. Focus group and survey results were mapped to the EPIS framework to gain insights into the implementation process of these programs and identify areas for optimization. Results Four UC campuses with 20 active camera sites screened 7,450 patients in the calendar year 2022. The average DR screening rate across the four campuses was 55%. Variations between sources of payment, turn-around time, image-grading structure, image-report characteristics, IT infrastructure, and patient outreach strategies were identified between sites. Closing gaps in IT integration between data systems, ensuring the financial sustainability of the program, and optimizing patient outreach remain primary challenges across sites and serve as good opportunities for cross-institutional learning. Conclusions Despite the potential for long-term cost savings and improving access to care, numerous obstacles continue to hinder the widespread implementation of teleretinal DR screening. Implementation science approaches can identify strategies for addressing these challenges and optimizing implementation.

Invasion in cold: weather effects on winter activity of an alien mesopredator at its northern range

Whether an invasive species thrives in cold ecosystems depends on its response to winter weather. A potential threat to these ecosystems in Europe is the invasive raccoon dog (Nyctereutes procyonoides). The survival of this mesopredator is supported in cold weather, because it can periodically use winter sleep, but its winter activity levels compared to native mesopredators remain unclear. We investigated the winter behaviour of raccoon dogs in Finland, near the edge of their invasion front, and compared their activity to native red foxes and badgers. Using wildlife cameras, we found that raccoon dogs do reduce activity during the coldest months, but camera observations did not strongly correlate with temperature perhaps due to feeding at camera sites. That is, artificial food sources may have increased raccoon dogs’ winter activity. Nevertheless, they responded more clearly to temperature drops than red foxes, but were more active than badgers that were mostly dormant and thus absent from our data. GPS-tracked raccoon dogs remained at some level active through winter, even near subarctic regions, but the cold and snowy weather clearly decreased activity and individuals stayed close to their nests during the coldest periods. Overall, these findings suggest that raccoon dogs can maintain some winter activity even in extremely cold environments, and they readily exploit human-provided resources. This potential ability to thrive in cold regions highlights the invasive potential of raccoon dogs. As winters become milder due to climate change, their numbers could increase significantly within cold-adapted ecosystems, impacting native species and posing conservation challenges.

SNAPSHOT USA 2021: A third coordinated national camera trap survey of the United States.

SNAPSHOT USA is a multicontributor, long-term camera trap survey designed to survey mammals across the United States. Participants are recruited through community networks and directly through a website application (https://www.snapshot-usa.org/). The growing Snapshot dataset is useful, for example, for tracking wildlife population responses to land use, land cover, and climate changes across spatial and temporal scales. Here we present the SNAPSHOT USA 2021 dataset, the third national camera trap survey across the US. Data were collected across 109 camera trap arrays and included 1711 camera sites. The total effort equaled 71,519 camera trap nights and resulted in 172,507 sequences of animal observations. Sampling effort varied among camera trap arrays, with a minimum of 126 camera trap nights, a maximum of 3355 nights, a median 546 nights, and a mean 656 ± 431 nights. This third dataset comprises 51 camera trap arrays that were surveyed during 2019, 2020, and 2021, along with 71 camera trap arrays that were surveyed in 2020 and 2021. All raw data and accompanying metadata are stored on Wildlife Insights (https://www.wildlifeinsights.org/), and are publicly available upon acceptance of the data papers. SNAPSHOT USA aims to sample multiple ecoregions in the United States with adequate representation of each ecoregion according to its relative size. Currently, the relative density of camera trap arrays varies by an order of magnitude for the various ecoregions (0.22-5.9 arrays per 100,000 km2), emphasizing the need to increase sampling effort by further recruiting and retaining contributors. There are no copyright restrictions on these data. We request that authors cite this paper when using these data, or a subset of these data, for publication. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government.

Monitoring fast‐moving animals—Building a customized camera system and evaluation toolset

Abstract Automated cameras (including camera traps) are an established observation tool, allowing, for example the identification of behaviours and monitoring without harming organisms. However, limitations including imperfect detection, insufficient data storage and power supply restrict the use of camera traps, making inexpensive and customizable solutions desirable. We describe a camera system and evaluation toolset based on Raspberry Pi computers and YOLOv5 that can overcome those shortcomings with its modular properties. We facilitate the set‐up and modification for researchers via detailed step‐by‐step guides. A customized camera system prototype was constructed to monitor fast‐moving organisms on a continuous schedule. For testing and benchmarking, we recorded mason bees (Osmia cornuta) approaching nesting aids on 20 sites. To efficiently process the extensive video material, we developed an evaluation toolset utilizing the convolutional neural network YOLOv5 to detect bees in the videos. In the field test, the camera system performed reliably for more than a week (2 h per day) under varying weather conditions. YOLOv5 detected and classified bees with only 775 original training images. Overall detection reliability varied depending on camera perspective, site and weather conditions, but a high average detection precision (78%) was achieved, which was confirmed by a human observer (80% of algorithm‐based detections confirmed). The customized camera system mitigates several disadvantages of commercial camera traps by using interchangeable components and incorporates all major requirements a researcher has for working in the field including moderate costs, easy assembly and an external energy source. We provide detailed user guides to bridge the gap between ecology, computer science and engineering.

Delay in Adélie penguin nest occupation restricts parental investment in nest construction and reduces reproductive output.

Reproductive success is an important demographic parameter that can be driven by environmental and behavioural factors operating on various spatio-temporal scales. As seabirds breed on land and forage in the ocean, processes occurring in both environments can influence their reproductive success. At various locations around East Antarctica, Adélie penguins' (Pygoscelis adeliae) reproductive success has been negatively linked to extensive sea-ice. In contrast, our study site in the Windmill Islands has limited fast ice present during the breeding season, allowing us to examine drivers of reproductive success under vastly different marine environmental conditions. Here, we examined the reproductive success of 450 Adélie penguin nests over a 10-year period using images obtained from remotely operated cameras. We analysed nest survival in relation to marine and climatic factors, environmental conditions at the camera site and immediately around the nest, and behavioural attributes reflecting parental investment and phenological timing. Our key result was a strong positive association between nest structure and chick survival, particularly when ground moisture and snow cover around the nest were high. Earlier nesting birds were more likely to build bigger nests, although it is unclear whether this is due to more time available to build nests or whether early arrival and high-quality nests are complementary traits. This intrinsic activity is likely to become more important if future predictions of increased snowfall in this region manifest.

Impact of Speed Limit Enforcement Cameras on Speed Behavior: Naturalistic Evidence from Brazil

Speeding is widely recognized as a key contributor to the occurrence and severity of road crashes, making studies on speed reduction devices particularly relevant given poor road safety outcomes worldwide. This study investigates the impact of fixed speed cameras on driver behavior and speed reduction in urban arterials using a naturalistic driving study methodology. Data from 13 drivers and 116 trips in Curitiba, Brazil, were analyzed, with a focus on speed cameras placed on arterial roads. Speed data were grouped and analyzed by various categories, including topographic profile, day and week periods, and rain conditions. Mean comparisons were used to compare data sets, revealing an overall speed reduction effect of 0.69 km/h (−1.33%) around the speed camera. The study identified a pattern of punctual speed reduction, known as a “kangaroo jump,” a speed reduction followed by an increase in speed, referred to as the “compensation effect,” and a new pattern characterized by a non-significant speed reduction at the speed camera site followed by an increase in speed, referred to as the “cobra strike effect” because of its curve pattern. The largest speed reductions were observed for flat topographic profiles (−2.98%), daytime travel (−1.58%), and travel on working days (−1.75%) with rain (−1.80%). Conversely, the speed camera had little impact on vehicle speed for uphill topographic profiles, no rain conditions, and travels during weekend.

Efficient data collection for camera trap‐based density estimation: A preliminary assessment

Abstract Camera traps have great potential for generating wildlife insights by providing high resolution site‐specific data. Methods of data collection and analysis reliant on these tools for population density estimation can be relatively resource intensive, hindering their mainstream adoption. Here, we explore the potential of population density estimates derived from a distance sampling method based on optics theory, which greatly simplifies the process of setting up camera sites and analysing data. Specifically, we (1) tested the method on human subjects in an artificial environment, (2) compared it to another method relying on virtual grids on images using wild populations of black‐backed jackal (Canis mesomelas) and African civet (Civettictis civetta) in South Africa and (3) deployed it to estimate wild boar (Sus scrofa) population densities in Hungary. The initial human trials resulted in an estimate that was extremely close to true population density. When compared to the virtual grid method, results suggest that our distance sampling method can deliver accurate estimates with increased convenience and robustness against disruptions of the camera sites. The wild boar study resulted in a realistic density estimate, which can be used as a baseline when assessing future fluctuations in population density. As this new approach does not have special requirements for setting up camera sites, it is efficient and widely applicable across other density estimation methods requiring an estimate for effective detection distance. Additionally, the method can be applied in the retrospective analysis of existing datasets.

Conducting community-led research using trail cameras to develop baseline wandering domestic cat local abundance estimates

Assessing cat local abundance provides information on where wandering cat numbers are highest and what habitats or factors are associated with wandering cats. A variety of stakeholders can lead this research and then use the findings to make scientifically informed decisions to guide the physical locations of cat management actions. Here, we document a framework that engages community members, uses minimal equipment (six trail cameras), and provides scientifically derived information for interested parties to inform, direct, or test the effectiveness of cat management practices. Using these methods in Gatineau, Quebec, Canada, we demonstrate how we estimated cat population size and cat local abundances across a variety of co-variates while accounting for non-perfect detection by using 55 trail camera sites and N-mixture models. Urban areas had three-fold higher local wandering cat abundances than parkland areas, and neighbourhoods below the median income had the highest local abundances of wandering cats. We estimated there are between 8905 and 48,419 (mean 21,298) wandering cats in Gatineau, with 18%–73% of those cats being unowned. These findings can be used to identify locations for future cat management. If estimates of cat abundance are repeated, they can assess the effectiveness of management actions.

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.

Differential habitat use between demographic states of black bears in managed timber forests

AbstractThe long‐term effects of intensive forest harvest on sensitive demographic stages of the American black bear (Ursus americanus) have been often overlooked. Much of Maine, USA, is covered in forests that are hospitable to bears and commercial timber harvest. To investigate the potential effects of differing intensities of disturbance on black bears, and on females with cubs particularly, we designed a large‐scale natural experiment with 197 motion‐sensitive camera sites dispersed over representative forest stands in northern and central Maine. Using multi‐state occupancy models, we distinguished the overall trends in space use by females with young versus adult bears without young. Forest disturbance at large spatial scales was positively associated with the probability of use for both demographic groups and the availability of hardwood trees was an additional important factor for habitat use by females with young. Our study illustrates the use of motion‐sensitive cameras to monitor and understand habitat use by distinct life‐history stages of animals living in human‐modified landscapes, and results indicate that managers can maintain black bear habitat in areas of active forest harvest by ensuring the availability of hardwood species.

Trucks versus treks: The relative influence of motorized versus nonmotorized recreation on a mammal community.

Outdoor recreation is increasing rapidly on public lands, with potential consequences for wildlife communities. Recreation can induce shifts in wildlife activity and habitat use, but responses vary widely even within the same species, suggesting mitigating factors that remain poorly understood. Both the type of recreation-motorized or nonmotorized-and the distance of wildlife from human disturbance may be important in developing a general understanding of recreation impacts on wildlife and making more informed management decisions. We conducted a camera-trapping survey in the Colville National Forest (CNF) of northeastern Washington in the summers of 2019 and 2020. We collected ~11,000 trap nights of spatially extensive data on nine mid-large mammalian species, simultaneously recording the presence and activity patterns of motorized (primarily vehicles on roads) and nonmotorized (primarily hikers on trails) recreation and wildlife both along trails and roads and off trails and off roads (away from most recreation). We used diel overlap analysis, time lag analysis, and single-season single-species occupancy modeling to examine the impact of recreation on the focal species. Species temporally avoided recreationists either by shifting to more nocturnal hours or delaying return to recently used recreation sites. Most species also responded spatially by altering the use or the intensity of use of camera sites due to recreation, although both positive and negative associations with recreation were documented. Species responded to nonmotorized recreation (e.g., hikers on trails) more often than motorized recreation (e.g., vehicles on roads). Most effects of recreation extended off the trail or road, although in three instances the spatiotemporal response of species to recreation along trails/roads disappeared a short distance away from those features. Our work suggests that a better understanding of landscape-scale impacts of recreation, including fitness consequences, will require additional work to disentangle the effects of different types of recreation and estimate the effective distance at which wildlife responds. Moreover, these results suggest that quiet, nonconsumptive recreation may warrant increased attention from land managers given its potential to influence the spatiotemporal ecology of numerous species.

Virtual snow stakes: a new method for snow depth measurement at remote camera stations

AbstractRemote cameras are used to study demographics, ecological processes, and behavior of wildlife populations. Cameras have also been used to measure snow depth with physical snow stakes. However, concerns that physical instruments at camera sites may influence animal behavior limit installation of instruments to facilitate collecting such data. Given that snow depth data are inherently contained within images, potential insights that could be made using these data are lost. To facilitate camera‐based snow depth observations without additional equipment installation, we developed a method implemented in an R package called edger to superimpose virtual measurement devices onto images. The virtual snow stakes can be used to derive snow depth measurements. We validated the method for snow depth estimation using camera data from Latah County, Idaho, USA in winter 2020–2021. Mean bias error between the virtual snow stake and a physical snow stake was 5.8 cm; the mean absolute bias error was 8.8 cm. The mean Nash Sutcliffe Efficiency score comparing the fit of the 2 sets of measurements within each camera was 0.748, indicating good agreement. The edger package provides researchers with a means to take critical measurements for ecological studies without the use of physical objects that could alter animal behavior, and snow data at finer scales can complement other snow data sources that have coarser spatial and temporal resolution.

The Distribution and Activity of the Invasive Raccoon Dog in Lithuania as Found with Country-Wide Camera Trapping

The raccoon dog (Nyctereutes procyonoides Gray, 1834) is an invasive mammal widespread in northern, eastern, and central Europe, where it damages biodiversity and carries a wide range of pathogens. Surveys of this species in Lithuania ceased before 2000, so there is a lack of scientific information on its distribution and relative abundance. In 2019–2022, we carried out a nationwide recording of raccoon dogs using camera traps (101 sites, sampling effort of 15,563 trapping days). The species was found at 64 sites (63.4% of the sites surveyed), with an average relative shooting frequency of 4.30 photographs per 100 days. The frequency of raccoon dogs was higher at camera sites where lynx (Lynx lynx Linnaeus, 1758) or wolves (Canis lupus Linnaeus, 1758) were recorded compared to sites where predators were absent (7.95 vs. 3.21 photos/100 days, p < 0.05). The highest raccoon dog activity (69.5% of records) was observed at night and at temperatures between −3 and +5 °C. Below −15 °C, animals were not active, while above 25 °C, there was very little activity. Diurnal activity (36.1% of daytime records in April–June) increased during estrus, gestation, and rearing of pups. We conclude that wide-scale camera trapping is a suitable method for raccoon dog surveys.

Industrial development alters wolf spatial distribution mediated by prey availability.

Increasing resource extraction and human activity are reshaping species' spatial distributions in human-altered landscape and consequently shaping the dynamics of interspecific interactions, such as between predators and prey. To evaluate the effects of industrial features and human activity on the occurrence of wolves (Canis lupus), we used wildlife detection data collected in 2014 from an array of 122 remote wildlife camera traps in Alberta's Rocky Mountains and foothills near Hinton, Canada. Using generalized linear models, we compared the occurrence frequency of wolves at camera sites to natural land cover, industrial disturbance (forestry and oil/gas exploration), human activity (motorized and non-motorized), and prey availability (moose, Alces alces; elk, Cervus elaphus; mule deer, Odocoileus hemionus; and white-tailed deer, Odocoileus virginianus). Industrial block features (well sites and cutblocks) and prey (elk or mule deer) availability interacted to influence wolf occurrence, but models including motorized and non-motorized human activity were not strongly supported. Wolves occurred infrequently at sites with high densities of well sites and cutblocks, except when elk or mule deer were frequently detected. Our results suggest that wolves risk using industrial block features when prey occur frequently to increase predation opportunities, but otherwise avoid them due to risk of human encounters. Effective management of wolves in anthropogenically altered landscapes thus requires the simultaneous consideration of industrial block features and populations of elk and mule deer.

Relative Abundance of Mammals and Estimation of Minimum Trapping Effort Using Camera Traps in Jangsudae, Seoraksan National Park

In Jangsudae of Seoraksan National Park, South Korea, 14 mammal species have been listed, including ten medium- and large-sized species; additionally, this region is an important habitat for the endangered long-tailed goral (Naemorhedus caudatus). In this study, a camera trap survey was conducted over 103 monitoring days at 18 sites in Jangsudae to evaluate the minimum trapping effort (MTE) needed to detect the ten listed mammal species. The most photographed species were the long-tailed goral, wild boar (Sus scrofa), and Asian badger (Meles leucurus), accounting for 77.1% (n = 366) of the total independent photographs. Long-tailed goral, the most frequently captured mammal species (44.8%), was captured at 17 camera sites (relative abundance index = 206.8). According to the rarefaction analysis, 1840 camera days (102.2 monitoring days at 18 camera sites) were required to photograph all ten resident species. Moreover, at least 1010 and 664 camera days were required to detect 95% and 90% of the ten residential species, respectively. MTE was evaluated in summer when wild species were highly detectable owing to their high activity. Future studies should evaluate MTE through one-year long-term monitoring that includes all four seasons, and compare the results with those of this study.

Niche partitioning by sympatric civets in the Himalayan foothills of Pakistan.

Niche overlap between sympatric species can indicate the extent of interspecific competition. Sympatric competing species can exhibit spatial, temporal, and dietary adjustments to reduce competition. We investigated spatial, temporal, and dietary niche overlap of sympatric Asian palm civet (Paradoxurus hermaphroditus) and small Indian civet ( Viverricula indica), in and around Pir Lasura National Park, Pakistan. We used remote cameras to determine the frequency and timing of detections to estimate spatial and temporal overlap, and prey remains from scats to estimate dietary overlap. We collected scat samples of Asian palm civet (n = 108) and small Indian civet (n = 44) for dietary analysis. We found low spatial (Oij = 0.32) and temporal (Δ = 0.39) overlap, but high dietary niche overlap (0.9) between these two civet species. Both civet species were detected at only 11 camera sites and small Indian civets were detected most frequently during 2:00-5:00 h and 8:00-10:00 h, whereas Asian palm civets detections were greatest during 20:00-2:00 h. The overall niche breadth of Asian palm civet was slightly narrower (L = 9.69, Lst = 0.31) than that of the small Indian civet (L = 10, Lst = 0.52). We identified 27 dietary items (15 plant, 12 animal) from scats of Asian palm civet including Himalayan pear (Pyrus pashia; 27%), Indian gerbil (Tatera indica; 10%), Rhesus monkey (Macaca mulatta; 4%), and insects (5%). Scat analysis of small Indian civets revealed 17 prey items (eight plant, nine animal) including Himalayan pear (24%), domestic poultry (15%), Indian gerbil (11%), and house mouse (Mus musculus; 5%). Both civet species consumed fruits of cultivated orchard species. Spatial and temporal partitioning of landscapes containing diverse foods appears to facilitate coexistence between Asian palm civets and small Indian civets.

Testing umbrella species and food-web properties of large carnivores in the Rocky Mountains

Despite criticisms, the umbrella species concept remains a fundamental conservation tool for protecting biodiversity in the face of global change, yet it is rarely tested. Food web theory provides a tool to test both umbrella-species' suitability and their ecological function, which we investigate in a large-mammal food web. Using data from 698 camera trap locations in the Canadian Rockies, we develop hierarchical occupancy models to predict the co-occurrence of 16 large mammal species. We draw upon previous diet studies in the Canadian Rockies to describe the meta food-web (meta-web) for these species. Next, we filtered the meta-web using predicted occupancy to estimate realized food webs at each camera location. We tested the umbrella species concept using predicted occupancy across all 698 camera sites. We then tested for carnivore effects using realized food webs on 5 food-web properties: species richness, links, connectance, nestedness and modularity using generalized linear models while accounting for landscape covariates known to affect food web dynamics. Our multispecies occupancy models reflected factors previously demonstrated to affect large mammal occurrence. Our results also demonstrated that grizzly bear (Ursus horribilis), a generalist carnivore, was the best umbrella carivore species, and explained species richness the best. When considering food web properties, however, wolves (Canis lupus) and cougars (Felis concolor) served as better umbrellas that also captured food web properties such as connectance, links and nestedness that better reflect ecological interactions. Our results support the role of large carnivores as umbrella and ecologically interactive species in conservation planning.