Camera trap placement and the potential for bias due to trails and other features

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.

Assessing the impacts of recreation on the spatial and temporal activity of mammals in an isolated alpine protected area

The management objectives of many protected areas must meet the dual mandates of protecting biodiversity while providing recreational opportunities. It is difficult to balance these mandates because it takes considerable effort to monitor both the status of biodiversity and impacts of recreation. Using detections from 45 camera traps deployed between July 2019 and September 2021, we assessed the potential impacts of recreation on spatial and temporal activity for 8 medium- and large-bodied terrestrial mammals in an isolated alpine protected area: Cathedral Provincial Park, British Columbia, Canada. We hypothesised that some wildlife perceive a level of threat from people, such that they avoid 'risky times' or 'risky places' associated with human activity. Other species may benefit from associating with people, be it through access to anthropogenic resource subsidies or filtering of competitors/predators that are more human-averse (i.e., human shield hypothesis). Specifically, we predicted that large carnivores would show the greatest segregation from people while mesocarnivores and ungulates would associate spatially with people. We found spatial co-occurrence between ungulates and recreation, consistent with the human shield hypothesis, but did not see the predicted negative relationship between larger carnivores and humans, except for coyotes (Canis latrans). Temporally, all species other than cougars (Puma concolor) had diel activity patterns significantly different from that of recreationists, suggesting potential displacement in the temporal niche. Wolves (Canis lupus) and mountain goats (Oreamnos americanus) showed shifts in temporal activity away from people on recreation trails relative to off-trail areas, providing further evidence of potential displacement. Our results highlight the importance of monitoring spatial and temporal interactions between recreation activities and wildlife communities, in order to ensure the effectiveness of protected areas in an era of increasing human impacts.

The Preferred Habitat of Reintroduced Banteng (Bos javanicus) at the Core and the Edge of Salakphra Wildlife Sanctuary, Thailand

Monitoring of banteng (Bos javanicus) after reintroduction is important for their management. This study aimed to monitor the preferred habitat and area of use of reintroduced banteng at the core (13 banteng) and the edge (three banteng) of Salakphra Wildlife Sanctuary between 2019 and 2021 and compared the finding with previous studies conducted from 2014 to 2019. The Binary Logistic Regression (BLR) showed the most preferred, moderately preferred, and least preferred areas were 44.7 km², 1.2 km², and 54.1 km² in the dry season, and 25.9 km², 1.0 km², and 9.3 km² in the wet season, respectively. Maximum Entropy (MaxEnt) showed the most preferred, moderately preferred, and least preferred areas as 12.1 km², 17.3 km², and 65.9 km², respectively. Banteng have previously been found close to ponds and salt licks. The area of use size, as determined by Minimum Convex Polygon (MCP) and Kernel Density Estimation (KDE), was 20.3 km² and 6.5 km², respectively. Three banteng were reintroduced to the edge area in 2020. The edge area was temporarily utilized by these individuals. In the core area, the area of use in this study decreased compared to the previous studies from 2014 to 2019, indicating they were able to find their preferred habitat. This study suggested that, if the area is managed appropriately, banteng will be able to live in a smaller habitat, and we will be able to restore the banteng population in the future.

Adapting camera-trap placement based on animal behavior for rapid detection: A focus on the Endangered, white-bellied pangolin (Phataginus tricuspis)

Pangolin species are notoriously difficult to detect and monitor in the wild and, as a result, commonly used survey techniques fall short in gathering sufficient data to draw confident conclusions on pangolin populations, conservation status, and natural history. The white-bellied pangolin is a semiarboreal species that may be poorly detected in general mammal surveys even with modern techniques such as camera-trapping. As a result, population status information is often derived from hunting, market, and trafficking data. There is therefore a crucial need to improve camera-trap survey methods to reliably detect this species in its natural environment. Here, we test the influence of camera-trap placement strategy on the detectability of the white-bellied pangolin by comparing estimates from targeted ground-viewing camera-trapping and a novel log-viewing placement strategy adapted from local hunters' knowledge. Our results suggest that (1) deploying camera-traps to detect animals walking along logs is an effective strategy for recording several forest species, including the white-bellied pangolin, and (2) that camera-traps targeting logs are more efficient at detecting white-bellied pangolins than camera-traps viewing the ground (>100% increase in detection probability). We also found moderate evidence that there is a relationship between the white-bellied pangolin occurrence at our locality and elevation and weak evidence of an association with distance to the nearest river. Our results suggest an effective new monitoring approach allowing consistent detection of the white-bellied pangolin with moderate survey effort. This highlights the importance of harnessing local knowledge to guide the design of monitoring protocols for cryptic species.

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.

Targeting burrows improves detection in giant pangolin Smutsia gigantea camera-trap surveys

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

Are we telling the same story? Comparing inferences made from camera trap and telemetry data for wildlife monitoring

Estimating habitat and spatial associations for wildlife is common across ecological studies and it is well known that individual traits can drive population dynamics and vice versa. Thus, it is commonly assumed that individual- and population-level data should represent the same underlying processes, but few studies have directly compared contemporaneous data representing these different perspectives. We evaluated the circumstances under which data collected from Lagrangian (individual-level) and Eulerian (population-level) perspectives could yield comparable inference to understand how scalable information is from the individual to the population. We used Global Positioning System (GPS) collar (Lagrangian) and camera trap (Eulerian) data for seven species collected simultaneously in eastern Washington (2018-2020) to compare inferences made from different survey perspectives. We fit the respective data streams to resource selection functions (RSFs) and occupancy models and compared estimated habitat- and space-use patterns for each species. Although previous studies have considered whether individual- and population-level data generated comparable information, ours is the first to make this comparison for multiple species simultaneously and to specifically ask whether inferences from the two perspectives differed depending on the focal species. We found general agreement between the predicted spatial distributions for most paired analyses, although specific habitat relationships differed. We hypothesize the discrepancies arose due to differences in statistical power associated with camera and GPS-collar sampling, as well as spatial mismatches in the data. Our research suggests data collected from individual-based sampling methods can capture coarse population-wide patterns for a diversity of species, but results differ when interpreting specific wildlife-habitat relationships.

National parks and conservation concessions: a comparison between mammal populations in two types of tropical protected areas in Ucayali, Peru

Peru contains the second largest surface area of the Amazon biome. The Peruvian Amazon is threatened by logging, illegal crops, mining, and agricultural expansion. While a number of national parks exist in the Amazon region, privately managed areas like Conservation Concessions can be an attractive complement to existing parks. We compare medium and large mammal communities in a Conservation Concession in Ucayali with the nearby Parque Nacional Sierra del Divisor National Park and describe species relative abundance and richness of both protected areas. Results suggest that Conservation Concessions can harbour an important diversity of mammal species and could provide connections to larger protected areas. However, they are no substitutes for large protected areas, especially for sensitive and threatened species. Further research is needed to demonstrate their complementarity and improve landscape-level connectivity between conservation models.

Spatially associated or composite life traces from Holocene paleosols and dune sands provide evidence for past biotic interactions

Biotic interactions (e.g., predation, competition, commensalism) where organisms directly or indirectly influenced one another are of great interest to those studying the history of life but have been difficult to ascertain from fossils. Considering the usual caveats about the temporal resolution of paleontological data, traces and trace fossils in the sedimentary record can record co-occurrences of organisms or their behaviours with relatively high spatial fidelity in a location. Neoichnological studies and studies on recently buried traces, where direct trophic links or other connections between tracemakers are well-known, may help interpret when and where overlapping traces represented true biotic interactions. Examples from Holocene paleosols and other buried continental sediments in Poland include the tight association between mole and earthworm burrows, forming an ichnofabric representing a predator-prey relationship, and that of intersecting insect and root traces demonstrating the impact of trees as both ecosystem engineers and the basis for food chains. Trampling by ungulates, which leaves hoofprints and other sedimentary disturbances, may result in amensal or commensal effects on some biota in the short term and create heterogeneity that later trace-making organisms, such as invertebrate burrowers, can also respond to in turn, though such modified or composite traces may be challenging to interpret.

Leopard density and interspecific spatiotemporal interactions in a hyena-dominated landscape

Scavenging is widespread in the carnivore guild and can greatly impact food web structures and population dynamics by either facilitation or suppression of sympatric carnivores. Due to habitat loss and fragmentation, carnivores are increasingly forced into close sympatry, possibly resulting in more interactions such as kleptoparasitism and competition. In this paper, we investigate the potential for these interactions when carnivore densities are high. A camera trap survey was conducted in central Tuli, Botswana, to examine leopard Panthera pardus densities and spatiotemporal activity patterns of leopard and its most important competitors' brown hyena Parahyaena brunnea and spotted hyena Crocuta crocuta. Spatial capture-recapture models estimated leopard population density to be 12.7 ± 3.2 leopard/100 km², which is one of the highest leopard densities in Africa. Time-to-event analyses showed both brown hyena and spotted hyena were observed more frequently before and after a leopard observation than expected by chance. The high spatiotemporal overlap of both hyena species with leopard is possibly explained by leopard providing scavenging opportunities for brown hyena and spotted hyena. Our results suggest that central Tuli is a high-density leopard area, despite possible intense kleptoparasitism and competition.

Estimating animal abundance at multiple scales by spatially explicit capture-recapture

Information about how animal abundance varies across landscapes is needed to inform management action but is costly and time-consuming to obtain; surveys of a single population distributed over a large area can take years to complete. Surveys employing small, spatially replicated sampling units improve efficiency, but statistical estimators rely on assumptions that constrain survey design or become less reasonable as larger areas are sampled. Efficient methods that avoid assumptions about similarity of detectability or density among replicates are therefore appealing. Using simulations and data from >3500 black bears sampled on 73 independent study areas in Ontario, Canada, we (1) quantified bias induced by unmodeled spatial heterogeneity in detectability and density; (2) evaluated novel, design-based estimators of average density across replicate study areas; and (3) evaluated two estimators of the variance of average density across study areas: an analytic estimator that assumed an underlying homogeneous spatial Poisson point process for the distribution of animals' activity centers, and an empirical estimator of variance across study areas. In simulations where detectability varied in space, assuming spatially constant detectability yielded density estimates that were negatively biased by 20% to 30%; estimating local detectability and density from local data and treating study areas as independent, equal replicates when estimating average density across study areas using the design-based estimator yielded unbiased estimates at local and landscape scales. Similarly, detectability of black bears varied among study areas and estimates of bear density at landscape scales were higher when no information was shared across study areas when estimating detectability. This approach also maximized precision (relative SEs of estimates of average black bear density ranged from 7% to 18%) and computational efficiency. In simulations, the analytic variance estimator was robust to threefold variation in local densities but the empirical estimator performed poorly. Conducting multiple, similar SECR surveys and treating them as independent replicates during analyses allowed us to efficiently estimate density at multiple scales and extents while avoiding biases caused by pooling spatially heterogeneous data. This approach enables researchers to address a wide range of ecological or management-related questions and is applicable with most types of SECR data.

Estimating density of ocelots in the Atlantic Forest using spatial and closed capture–recapture models

Monitoring variation in population features such as abundance and density is essential for evaluating and implementing conservation actions. Camera trapping can be important for assessing population status and trends and is increasingly used to generate density estimates through capture–recapture models. Moreover, success in using this technique can vary seasonally given shifting animal distributions and camera encounter rates. Notwithstanding these potential advantages, a gap still exists in our understanding of the performance of such models for estimating density of cryptic Neotropical terrestrial carnivores with low encounter rate probability with cameras. In addition, scanty information is available on how sampling design can affect the accuracy and precision of density estimates for Neotropical carnivores. We evaluate the performance of spatially explicit versus nonspatial capture–mark–recapture models for estimating densities and population size of ocelots (Leopardus pardalis) within an Atlantic Forest fragment in Brazil. We conducted two spatially concurrent surveys, a random camera-trap deployment covering the entire study area and a systematic camera-trap deployment in a small portion of the study area, where trails and unpaved roads were located. We obtained 244 photographs of ocelots in the Rio Doce State Park from April 2016 to November 2017, using 54-double camera stations spaced approximately 1.5 km apart (random placement) totaling 4,320 trap-nights and 15-double camera stations spaced from 0.3–10 km apart (systematic placement) totaling 1,200 trap-nights. Using the random placement design, ocelot density estimates were similar during the dry season, 14.0 individuals/km2 (± 5.6 SE, 6.6–30.0, 95% CI) and 13.78 individuals/km2 (± 4.25 SE, 5.4–22.1, 95% CI) from spatially explicit capture–recapture and nonspatial models, respectively. Using the systematic placement design spatially explicit models had smaller and less precise ocelot density estimates than nonspatial models during the dry season. Ocelot density was 12.4 individuals/100 km2 (± 5.0 SE, 5.8–26.7, 95% CI) and 19.9 individuals/km2 (± 5.2 SE, 9.7–30.1, 95% CI) from spatially explicit and nonspatial models, respectively. During the rainy season, we found the opposite pattern. Using the systematic placement design, spatial-explicit models had higher and less precise estimates than nonspatial models. Ocelot density was 24.6 individuals/100 km2 (± 13.9 SE, 8.7–69.4, 95% CI) and 11.89 individuals/km2 (± 3.93 SE, 4.19–19.59, 95% CI) from spatially explicit and nonspatial models, respectively. During the rainy season, we could not compare models using the random placement design due to limited number of recaptures to run nonspatial models. In addition, a single recapture yielded an imprecise population density estimate using spatial models (high SE and large 95% CIs), thus precluding any comparison between nonspatial and spatially explicit models. We demonstrate relative differences and similarities between the performance of spatially explicit and nonspatial capture–mark–recapture models for estimating density and population size of ocelots and highlight that both types of capture–recapture models differ in their estimation depending on the sampling design. We highlight that performance of camera surveys is contingent on placement design and that researchers need to be strategic in camera distribution according to study objectives and logistics. This point is especially relevant for cryptic or endangered species occurring at low densities and having low detection probability using traditional sampling methods.

Dogs suppress a pivotal function in the food webs of sandy beaches

Domestic dogs are the most abundant carnivore globally and have demonstrable negative impacts to wildlife; yet, little evidence regarding their functional roles in natural food webs exists. Adding dogs to food webs may result in a net loss (via suppression of naturally occurring species), net gain (via mesopredator release), or no change (via functional replacement) to ecosystem function. Scavenging is a pivotal function in ecosystems, particularly those that are energetically supported by carrion. Dogs also scavenge on animal carcasses, but whether scavenging by dogs influences the structural and functional properties of food webs remains unclear. Here we used camera traps baited with carrion to test the effect of dogs on the composition and diversity of the vertebrate scavenger guild, as well as carrion detection and consumption rates. We conducted this work in sandy beach ecosystems, which rely on the import of marine organic matter (i.e. stranding of dead marine animals). Diversity of the scavenger community was similar on beaches without dogs. Dogs increased the time it took for carcasses to be detected and decreased the proportion of carrion consumed. This ‘dog suppression effect’ on scavenging was stronger for nocturnal mammalian scavengers, presumably being driven by indirect trait-mediated effects, which raises further questions about the broader ecological consequences of domestic dogs in natural systems.

Data-integration of opportunistic species observations into hierarchical modeling frameworks improves spatial predictions for urban red squirrels

The prevailing trend of increasing urbanization and habitat fragmentation makes knowledge of species’ habitat requirements and distribution a crucial factor in conservation and urban planning. Species distribution models (SDMs) offer powerful toolboxes for discriminating the underlying environmental factors driving habitat suitability. Nevertheless, challenges in SDMs emerge if multiple data sets - often sampled with different intention and therefore sampling scheme – can complement each other and increase predictive accuracy. Here, we investigate the potential of using recent data integration techniques to model potential habitat and movement corridors for Eurasian red squirrels (Sciurus vulgaris), in an urban area. We constructed hierarchical models integrating data sets of different quality stemming from unstructured on one side and semi-structured wildlife observation campaigns on the other side in a combined likelihood approach and compared the results to modeling techniques based on only one data source - wherein all models were fit with the same selection of environmental variables. Our study highlights the increasing importance of considering multiple data sets for SDMs to enhance their predictive performance. We finally used Circuitscape (version 4.0.5) on the most robust SDM to delineate suitable movement corridors for red squirrels as a basis for planning road mortality mitigation measures. Our results indicate that even though red squirrels are common, urban habitats are rather small and partially lack connectivity along natural connectivity corridors in Berlin. Thus, additional fragmentation could bring the species closer to its limit to persist in urban environments, where our results can act as a template for conservation and management implications.

Spatio-Temporal Patterns and Source-Dispersion Modeling Towards Sloth Bear–Human Conflict Management in Central India

The impact of humans on biodiversity, in the form of the spatially extensive occurrence of humans and subsequent habitat degradation, leads to negative interactions between humans and native wildlife. However, knowledge of the spatial and temporal interface between humans and wildlife is necessary to understand the root cause of such negative interactions, yet considerably understudied in the context of human-dominated landscapes in south and south-eastern Asia. We took this opportunity, gaining insights on seasonal spatial interaction and spatio-temporal overlap between sloth bears (Melursus ursinus) and humans, and subsequently predicted the conflict source sites and dispersion (i.e., hotspots) based on the robust geographic profiling (GP) method in the Sanjay Tiger Reserve (STR), a human-dominated landscape of central India. Detection data of sloth bear and human were obtained from camera trap survey conducted for two years (2017–2018) and records of conflict incidents (2009–2019) were collected from forest department. We found that sloth bears can co-occur with humans independently of seasons, based on occupancy models. However, during summer, higher temporal overlap (Δ4 = 0.46) and lower spatial overlap (0.31) were observed between sloth bears and humans. Contrastingly, lower temporal overlap (Δ4 = 0.29) and higher spatial overlap (0.44) were observed between the same two during winter. The activity patterns of sloth bears and humans differed significantly across seasons and within the same species in different seasons. Our findings indicated that significant changes in human activity, especially during summer, increased the likelihood of sloth bear-human interaction and subsequent conflict incidents. The mapping of conflict source and dispersion (with high accuracy) also predicted a greater probability of conflict during summer, compared to winter, and thus showed the successful application of GP models in this field. Also, camera trap data alone were able to predict the occurrence of hotspots, demonstrating the use of camera trap records in the successful prediction of source-dispersion of conflict. This study would be useful for decision-makers to alleviate sloth bear–human conflict based on insights on seasonal variation of spatio-temporal overlap between the two and direct conservation efforts accordingly.

Short duration overnight cattle kraaling in natural rangelands: Does time after kraal use affect their utilization by wildlife and above ground grass parameters?

In east and southern Africa some private ranch owners are corralling (hereafter kraaling) cattle overnight for short periods (for example, seven days) in natural rangelands to create nutrient enriched hotspots which are attractive to large herbivores. However, the effect of season and time after kraal use (alt. age of nutrient enriched hotspots) on large herbivore use of these sites has not been examined. We collated the number of large herbivore sightings per day from camera traps during wet, early and late dry season in nutrient enriched hotspots of varying ages (1, 2, 3 and 4 years) and surrounding vegetation. In addition, above ground grass biomass and height in nutrient enriched hotspots was compared to that of the surrounding vegetation. Furthermore, we tested if repeated grazing in nutrient enriched hotspots stimulated grass compensatory growth. Large herbivore use of nutrient enriched hotspots was similar during wet, early and late dry season. Time after kraal use had a significant effect on mixed feeders (impala and African savanna elephant) utilization of nutrient enriched hotspots but not grazers (zebra and warthog) and browsers (giraffe and greater kudu). Both impala and African savanna elephants mostly used nutrient enriched hotspots one year after kraal use. Aboveground grass biomass and height were higher in surrounding vegetation than in nutrient enriched hotspots. Repeated clipping (proxy for grazing) resulted in compensatory aboveground grass biomass in nutrient enriched hotspots, which declined with time after kraal use. We concluded that nutrient enriched hotspots created through short duration overnight kraaling were important foraging sites for large herbivores.

Camera traps and guard observations as an alternative to researcher observation for studying anthropogenic foraging

Foraging by wildlife on anthropogenic foods can have negative impacts on both humans and wildlife. Addressing this issue requires reliable data on the patterns of anthropogenic foraging by wild animals, but while direct observation by researchers can be highly accurate, this method is also costly and labor‐intensive, making it impractical in the long‐term or over large spatial areas. Camera traps and observations by guards employed to deter animals from fields could be efficient alternative methods of data collection for understanding patterns of foraging by wildlife in crop fields. Here, we investigated how data on crop‐foraging by chacma baboons and vervet monkeys collected by camera traps and crop guards predicted data collected by researchers, on a commercial farm in South Africa. We found that data from camera traps and field guard observations predicted crop loss and the frequency of crop‐foraging events from researcher observations for crop‐foraging by baboons and to a lesser extent for vervets. The effectiveness of cameras at capturing crop‐foraging events was dependent on their position on the field edge. We believe that these alternatives to direct observation by researchers represent an efficient and low‐cost method for long‐term and large‐scale monitoring of foraging by wildlife on crops.

A synthetic review of terrestrial biological research from the Alberta oil sands region: 10 years of published literature

In the past decade, a large volume of peer-reviewed papers has examined the potential impacts of oil and gas resource extraction in the Canadian oil sands (OS). A large proportion focuses on terrestrial biology: wildlife, birds, and vegetation. We provide a qualitative synthesis of the condition of the environment in the oil sands region (OSR) from 2009 to 2020 to identify gaps and progress cumulative effects assessments. Our objectives were to (1) qualitatively synthesize and critically review knowledge from the OSR; (2) identify consistent trends and generalizable conclusions; and (3) pinpoint gaps in need of greater monitoring or research effort. We visualize knowledge and terrestrial monitoring foci by allocating papers to a conceptual model for the OS. Despite a recent increase in publications, focus has remained concentrated on a few key stressors, especially landscape disturbance, and a few taxa of interest. Stressor and response monitoring is well represented, but direct monitoring of pathways (linkages between stressors and responses) is limited. Important knowledge gaps include understanding effects at multiple spatial scales, mammal health effects monitoring, focused monitoring of local resources important to Indigenous communities, and geospatial coverage and availability, including higher attribute resolution in human footprint, comprehensive land cover mapping, and up-to-date LiDAR coverage. Causal attribution based on spatial proximity to operations or spatial orientation of monitoring in the region is common but may be limited in the strength of inference that it provides. Integr Environ Assess Manag 2022;18:388-406. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Comparing the efficiency of monofilament and regular nets for capturing bats

Regular nylon or polyester mist nets used for capturing bats have several drawbacks, particularly that they are inefficient at sampling insectivorous species. One possible alternative is to use monofilament nets, whose netting is made of single strands of yarn instead of several as regular nets, making them less detectable. To date, only one study has quantified the differences in capture rates between monofilament and regular mist nets for the study of bats, yet surprisingly, its findings suggest that the latter are more efficient than the former. Here, we provide further evidence of the differences in sampling efficiency between these two nets. We captured 90 individuals and 14 species in regular nets and 125 individuals and 20 species in monofilament nets. The use of monofilament nets increased overall capture rates, particularly for insectivorous species. Species accumulation curves indicate that samples based on regular nets are significantly underestimating species diversity, most notably as these nets fail at sampling rare species. We show that incorporating monofilament nets into bat studies offers an opportunity to expand records of different guilds and rare bat species and to improve our understanding of poorly known bat assemblages while using a popular, relatively cheap and portable sampling method.

Camera trap placement for evaluating species richness, abundance, and activity

Information from camera traps is used for inferences on species presence, richness, abundance, demography, and activity. Camera trap placement design is likely to influence these parameter estimates. Herein we simultaneously generate and compare estimates obtained from camera traps (a) placed to optimize large carnivore captures and (b) random placement, to infer accuracy and biases for parameter estimates. Both setups recorded 25 species when same number of trail and random cameras (n = 31) were compared. However, species accumulation rate was faster with trail cameras. Relative abundance indices (RAI) from random cameras surrogated abundance estimated from capture-mark-recapture and distance sampling, while RAI were biased higher for carnivores from trail cameras. Group size of wild-ungulates obtained from both camera setups were comparable. Random cameras detected nocturnal activities of wild ungulates in contrast to mostly diurnal activities observed from trail cameras. Our results show that trail and random camera setup give similar estimates of species richness and group size, but differ for estimates of relative abundance and activity patterns. Therefore, inferences made from each of these camera trap designs on the above parameters need to be viewed within this context.

Limited influence of hunting on the activity patterns and habitat use of Pampas fox (Lycalopex gymnocercus) in agroecosystems of central Argentina

The Pampas fox (Lycalopex gymnocercus) has suffered from hunting and human persecution for decades, both for fur trade or due to conflicts with livestock. However, studies assessing the effects of hunting pressure on this canid population ecology are lacking. In this work, we assessed the influence of several hunting-related variables on the daily activity patterns and habitat use of the Pampas fox. In private farms of central Argentina, we performed two camera-trapping surveys: one during the non-hunting season and other during the hunting season, distinguishing between sites with or without access by hunters. The habitat use of Pampas foxes did not vary between seasons, but their detectability was lower during the hunting season in habitats that allow humans to see foxes easily (i.e., habitats with high visibility). Pampas foxes selected dusk and night-time, increasing their activity at dusk hours on sites with hunting and showed differences in activity patterns related with the level of visibility of the habitat and to season. Hunting pressure may interact with anthropogenic habitat modifications and create ecological traps for the Pampas fox in agroecosystems.

Modelos de ocupación para datos de cámaras trampa

El uso de las cámaras trampa (CT) en la investigación de fauna silvestre puede generar conclusiones sesgadas cuando la detectabilidad imperfecta de especies no es considerada. Herramientas analíticas como los modelos de ocupación permiten estimar simultáneamente parámetros ecológicos corregidos por la probabilidad de detección. Sin embargo, es necesario implementar e interpretar de manera correcta los parámetros estimados por estos modelos para obtener inferencias con sentido biológico. Este trabajo presenta un marco conceptual base para diseñar de manera apropiada un análisis de ocupación por medio de datos de CT. Se discuten y se señalan recomendaciones generales para la definición de los elementos del modelo, el diseño del muestreo, así como estrategias de modelamiento estadísticos apropiadas dependiendo de los objetivos del estudio, las características de la especie y el tipo de datos obtenidos. Las decisiones tomadas por el investigador para definir cada uno de los componentes del modelo deben considerar la escala adecuada para que el fenómeno de estudio tenga sentido biológico. De esta manera, es posible generar inferencias y conclusiones robustas a partir de información de CT, lo que permite avanzar en el entendimiento de los mecanismos que subyacen a la ecología espacial de fauna silvestre y por lo tanto en su conservación.

How do habitat amount and habitat fragmentation drive time-delayed responses of biodiversity to land-use change?

Land-use change is a root cause of the extinction crisis, but links between habitat change and biodiversity loss are not fully understood. While there is evidence that habitat loss is an important extinction driver, the relevance of habitat fragmentation remains debated. Moreover, while time delays of biodiversity responses to habitat transformation are well-documented, time-delayed effects have been ignored in the habitat loss versus fragmentation debate. Here, using a hierarchical Bayesian multi-species occupancy framework, we systematically tested for time-delayed responses of bird and mammal communities to habitat loss and to habitat fragmentation. We focused on the Argentine Chaco, where deforestation has been widespread recently. We used an extensive field dataset on birds and mammals, along with a time series of annual woodland maps from 1985 to 2016 covering recent and historical habitat transformations. Contemporary habitat amount explained bird and mammal occupancy better than past habitat amount. However, occupancy was affected more by the past rather than recent fragmentation, indicating a time-delayed response to fragmentation. Considering past landscape patterns is therefore crucial for understanding current biodiversity patterns. Not accounting for land-use history ignores the possibility of extinction debt and can thus obscure impacts of fragmentation, potentially explaining contrasting findings of habitat loss versus fragmentation studies.

Baiting/Luring Improves Detection Probability and Species Identification-A Case Study of Mustelids with Camera Traps

Simple Summary

Camera traps are now widely used in animal research because they can monitor animals continuously. Nocturnal mammals are particularly difficult to monitor, and identification without cameras would be difficult. However, camera traps can be improved. We here compared two experimental settings to increase detection and images taken of mustelids, mostly martens. Both tuna bait and glandular scents improved the detection and the number of images taken. Both methods were more successful than a control group setting without any attractants.

Abstract

Motion-triggered trail cameras (hereafter camera traps) are powerful tools which are increasingly used in biological research, especially for species inventories or the estimation of species activity. However, camera traps do not always reliably detect animal visits, as a target species might be too fast, too small, or too far away to trigger an image. Therefore, researchers often apply attractants, such as food or glandular scents, to increase the likelihood of capturing animals. Moreover, with attractants, individuals might remain in front of a camera trap for longer periods leading to a higher number of images and enhanced image quality, which in turn might aid in species identification. The current study compared how two commonly used attractants, bait (tuna) and glandular scent (mustelid mix), affected the detection and the number of images taken by camera traps compared to control camera sites with conventional camera traps. We used a before–after control group design, including a baseline. Attractants increased the probability of detecting the target species and number of images. Tuna experiments produced on average 7.25 times as many images per visit than control camera traps, and scent lures produced on average 18.7 times as many images per visit than the control traps.

The Mostela: an adjusted camera trapping device as a promising non-invasive tool to study and monitor small mustelids

In spite of their potential important role in shaping small mammal population dynamics, weasel (Mustela nivalis) and stoat (Mustela erminea) are understudied due to the difficulty of detecting these species. Furthermore, their conservation status in many countries is unknown due to lack of monitoring techniques. There is thus an important need for a method to detect these small mustelids. In this study, we tested the efficiency of a recently developed camera trapping device, the Mostela, as a new technique to detect mustelids in a study area near Dieren, the Netherlands. We placed Mostelas in linear landscape features, and other microhabitats thought to be frequently visited by weasels, from March to October 2017 and February to October 2018. We tested for yearly and monthly differences in site use and detectability, as well as the effect of entrance tube size, using an occupancy modelling framework. We found large seasonal differences in site use and detectability of weasels with the highest site use in June to October and highest detection probability in August and September. Detection probability was approximately two times higher for Mostelas with a 10-cm entrance tube compared with 8-cm. Furthermore, we were able to estimate activity patterns based on the time of detection, identify the sex in most detections (69.5%), and distinguish several individuals. Concluding, the Mostela seems promising as a non-invasive monitoring tool to study the occurrence and ecology of small mustelids. Further development of individual recognition from images would enable using the Mostela for density estimates applying capture-recapture models.