A. Cole Burton

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

Summary Reliable assessment of animal populations is a long-standing challenge in wildlife ecology. Technological advances have led to widespread adoption of camera traps (CTs) to survey wildlife distribution, abundance and behaviour. As for any wildlife survey method, camera trapping must contend with sources of sampling error such as imperfect detection. Early applications focused on density estimation of naturally marked species, but there is growing interest in broad-scale CT surveys of unmarked populations and communities. Nevertheless, inferences based on detection indices are controversial, and the suitability of alternatives such as occupancy estimation is debatable. We reviewed 266 CT studies published between 2008 and 2013. We recorded study objectives and methodologies, evaluating the consistency of CT protocols and sampling designs, the extent to which CT surveys considered sampling error, and the linkages between analytical assumptions and species ecology. Nearly two-thirds of studies surveyed more than one species, and a majority used response variables that ignored imperfect detection (e.g. presence–absence, relative abundance). Many studies used opportunistic sampling and did not explicitly report details of sampling design and camera deployment that could affect conclusions. Most studies estimating density used capture–recapture methods on marked species, with spatially explicit methods becoming more prominent. Few studies estimated density for unmarked species, focusing instead on occupancy modelling or measures of relative abundance. While occupancy studies estimated detectability, most did not explicitly define key components of the modelling framework (e.g. a site) or discuss potential violations of model assumptions (e.g. site closure). Studies using relative abundance relied on assumptions of equal detectability, and most did not explicitly define expected relationships between measured responses and underlying ecological processes (e.g. animal abundance and movement). Synthesis and applications. The rapid adoption of camera traps represents an exciting transition in wildlife survey methodology. We remain optimistic about the technologys promise, but call for more explicit consideration of underlying processes of animal abundance, movement and detection by cameras, including more thorough reporting of methodological details and assumptions. Such transparency will facilitate efforts to evaluate and improve the reliability of camera trap surveys, ultimately leading to stronger inferences and helping to meet modern needs for effective ecological inquiry and biodiversity monitoring.

Hierarchical Multi-Species Modeling of Carnivore Responses to Hunting, Habitat and Prey in a West African Protected Area

Protected areas (PAs) are a cornerstone of global efforts to shield wildlife from anthropogenic impacts, yet their effectiveness at protecting wide-ranging species prone to human conflict – notably mammalian carnivores – is increasingly in question. An understanding of carnivore responses to human-induced and natural changes in and around PAs is critical not only to the conservation of threatened carnivore populations, but also to the effective protection of ecosystems in which they play key functional roles. However, an important challenge to assessing carnivore communities is the often infrequent and imperfect nature of survey detections. We applied a novel hierarchical multi-species occupancy model that accounted for detectability and spatial autocorrelation to data from 224 camera trap stations (sampled between October 2006 and January 2009) in order to test hypotheses about extrinsic influences on carnivore community dynamics in a West African protected area (Mole National Park, Ghana). We developed spatially explicit indices of illegal hunting activity, law enforcement patrol effort, prey biomass, and habitat productivity across the park, and used a Bayesian model selection framework to identify predictors of site occurrence for individual species and the entire carnivore community. Contrary to our expectation, hunting pressure and edge proximity did not have consistent, negative effects on occurrence across the nine carnivore species detected. Occurrence patterns for most species were positively associated with small prey biomass, and several species had either positive or negative associations with riverine forest (but not with other habitat descriptors). Influences of sampling design on carnivore detectability were also identified and addressed within our modeling framework (e.g., road and observer effects), and the multi-species approach facilitated inference on even the rarest carnivore species in the park. Our study provides insight for the conservation of these regionally significant carnivore populations, and our approach is broadly applicable to the robust assessment of communities of rare and elusive species subject to environmental change.

Critical evaluation of a long-term, locally-based wildlife monitoring program in West Africa

Effective monitoring programs are required to understand and mitigate biodiversity declines, particularly in tropical ecosystems where conservation conflicts are severe yet ecological data are scarce. “Locally-based” monitoring has been advanced as an approach to improve biodiversity monitoring in developing countries, but the accuracy of data from many such programs has not been adequately assessed. I evaluated a long-term, patrol-based wildlife monitoring system in Mole National Park, Ghana, through comparison with camera trapping and an assessment of sampling error. I found that patrol observations underrepresented the park’s mammal community, recording only two-thirds as many species as camera traps over a common sampling period (2006–2008). Agreement between methods was reasonable for larger, diurnal and social species (e.g., larger ungulates and primates), but camera traps were more effective at detecting smaller, solitary and nocturnal species (particularly carnivores). Data from patrols and cameras corresponded for some spatial patterns of management interest (e.g., community turnover, edge effect on abundance) but differed for others (e.g., richness, edge effect on diversity). Long-term patrol observations were influenced by uneven sampling effort and considerable variation in replicate counts. Despite potential benefits of locally-based monitoring, these results suggest that data from this and similar programs may be subject to biases that complicate interpretation of wildlife population and community dynamics. Careful attention to monitoring objectives, methodological design and robust analysis is required if locally-based approaches are to satisfy an aim of reliable biodiversity monitoring, and there is a need for greater international support in the creation and maintenance of local monitoring capacity.

A framework for adaptive monitoring of the cumulative effects of human footprint on biodiversity

Effective ecological monitoring is imperative in a human-dominated world, as our ability to manage functioning ecosystems will depend on understanding biodiversity responses to anthropogenic impacts. Yet, most monitoring efforts have either been narrowly focused on particular sites, species and stressors — thus inadequately considering the cumulative effects of multiple, interacting impacts at scales of management relevance — or too unfocused to provide specific guidance. We propose a cumulative effects monitoring framework that integrates multi-scaled surveillance of trends in biodiversity and land cover with targeted evaluation of hypothesized drivers of change. The framework is grounded in a flexible conceptual model and uses monitoring to generate and test empirical models that relate the status of diverse taxonomic groups to the nature and extent of human “footprint” and other landscape attributes. An adaptive cycle of standardized sampling, model development, and model evaluation provides a means to learn about the system and guide management. Additional benefits of the framework include standardized data on status and trend for a wide variety of biodiversity elements, spatially explicit models for regional planning and scenario evaluation, and identification of knowledge gaps for complementary research. We describe efforts to implement the framework in Alberta, Canada, through the Alberta Biodiversity Monitoring Institute, and identify key challenges to be addressed.

The role of digital data entry in participatory environmental monitoring

Many argue that monitoring conducted exclusively by scientists is insufficient to address ongoing environmental challenges. One solution entails the use of mobile digital devices in participatory monitoring (PM) programs. But how digital data entry affects programs with varying levels of stakeholder participation, from nonscientists collecting field data to nonscientists administering every step of a monitoring program, remains unclear. We reviewed the successes, in terms of management interventions and sustainability, of 107 monitoring programs described in the literature (hereafter programs) and compared these with case studies from our PM experiences in Australia, Canada, Ethiopia, Ghana, Greenland, and Vietnam (hereafter cases). Our literature review showed that participatory programs were less likely to use digital devices, and 2 of our 3 more participatory cases were also slow to adopt digital data entry. Programs that were participatory and used digital devices were more likely to report management actions, which was consistent with cases in Ethiopia, Greenland, and Australia. Programs engaging volunteers were more frequently reported as ongoing, but those involving digital data entry were less often sustained when data collectors were volunteers. For the Vietnamese and Canadian cases, sustainability was undermined by a mismatch in stakeholder objectives. In the Ghanaian case, complex field protocols diminished monitoring sustainability. Innovative technologies attract interest, but the foundation of effective participatory adaptive monitoring depends more on collaboratively defined questions, objectives, conceptual models, and monitoring approaches. When this foundation is built through effective partnerships, digital data entry can enable the collection of more data of higher quality. Without this foundation, or when implemented ineffectively or unnecessarily, digital data entry can be an additional expense that distracts from core monitoring objectives and undermines project sustainability. The appropriate role of digital data entry in PM likely depends more on the context in which it is used and less on the technology itself.

Density and distribution of a brown bear (Ursus arctos) population within the Caucasus biodiversity hotspot

Population declines and extirpations of large mammalian carnivores are major concerns for global biodiversity conservation. Many large carnivores are vulnerable to conflict with humans and attract conservation attention for their flagship appeal and ecological importance. Coexisting with carnivores requires an understanding of carnivore distribution and abundance relative to human activities and disturbances. Such knowledge is often hindered by the rare and elusive nature of carnivores and the lack of systematic ecological surveys in biodiverse regions facing high levels of threat. The Caucasus Ecoregion is one such biodiversity hotspot harboring several threatened mammal species for which there is a paucity of reliable data, including brown bears (Ursus arctos). Caucasus brown bear populations have declined significantly from historical times and may be isolated and vulnerable to disturbance from development activities such as mining, as well as increasing hunting pressure. To inform land-use planning and bear conservation in the Caucasus Ecoregion, we conducted systematic surveys in May–October 2015 in the foothills of the Caucasus Mountains within the Vayots Dzor region of Armenia. We used noninvasive genetic sampling, camera trapping, and statistical models that account for imperfect detection to estimate density and distribution of the bear population in the 1,000-km2 study area. Across 34 sampling sites, we obtained 3,163 camera-trap photos of brown bears and genotyped 28 individual bears (7 males and 21 females). Spatially explicit capture-recapture models revealed an unexpectedly high density of bears (59.4/1,000 km2; females = 44.6, 95% confidence interval, CI = 25.4–78.4; males = 14.8, 95% CI = 6.6–34.0), and multi-method occupancy models indicated that bears were distributed across most of the study area (ψ = 0.85; SE = 0.07). These results provide robust evidence that a significant population of brown bears persists in Armenias Vayots Dzor region, despite a history of hunting and habitat loss that have driven declines in brown bear populations throughout much of the Caucasus Ecoregion. Continued persistence of this flagship species may be threatened by mining, poaching, and other anthropogenic pressures in the region, underscoring the urgent need for strategic conservation planning, impact mitigation, and expanded ecological monitoring within this biodiversity hotspot.

Mammal responses to the human footprint vary across species and stressors

A rapidly expanding human footprint - comprised of anthropogenic land-use change and infrastructure - is profoundly affecting wildlife distributions worldwide. Cumulative effects management (CEM) is a regional approach that seeks to manage combined effects of the human footprint on biodiversity across large spatial scales. Challenges to implementing this approach include a lack of ecological data at large spatial scales, the high cost of monitoring multiple indicators, and the need to manage multiple footprints across industries. To inform development of effective CEM, we used large mammals as indicators to address the following questions: a) do species respond more strongly to individual footprint features or to cumulative effects (combined area of all footprint types, measured as total footprint), b) which features elicit the strongest responses across species, and c) are the direction of responses to footprint consistent? We used data from 12 years of snowtrack surveys (2001-2013) in the boreal forest of Alberta, coupled with regional footprint and landcover data, to develop generalized linear mixed-effects models relating the relative abundance of five boreal mammals [gray wolf (Canis lupus), Canada lynx (Lynx canadensis), coyote (Canis latrans), white-tailed deer (Odocoileus virginianus) and moose (Alces alces)] to individual and cumulative effects of the human footprint. We found that across species the strongest responses were to agriculture, roads, and young cutblocks (<10 years), suggesting these as potential priority stressors to address within CEM. Most species also responded to total footprint, indicating that in the absence of detailed information on individual features, this coarse measure can serve as an index of cumulative effects. There was high variability in direction and magnitude of responses across species, indicating that community-level responses are likely and should be considered within CEM planning.

Effects of law enforcement and community outreach on mammal diversity in a biodiversity hotspot

Management activities such as law enforcement and community outreach are thought to affect conservation outcomes in protected areas, but their importance relative to intrinsic environmental characteristics of the parks and extrinsic human pressures surrounding the parks have not been explored. Furthermore, it is not clear which is more related to conservation outcomes-the management itself or local peoples perceptions of the management. We measured objective (reports by park staff) and subjective (reports by local people) levels of community outreach and law enforcement based on responses to 374 questionnaires. We estimated mammal abundance and diversity of 6 protected areas based on data from 115 camera traps in Xishuangbanna, southwest China, a biodiversity hotspot with high hunting and land-conversion pressures. We then examined correlations among them and found that local peoples perception of law enforcement was positively related to the local abundance of 2 large, hunted species, wild boar (Sus scrofa) (β = 15.22) and muntjac (Muntiacus vaginalis) (β = 14.82), but not related to the abundance of smaller mammals or to objective levels of enforcement. The subjective frequency of outreach by park staff to local communities (β = 3.42) and park size (β = 3.28) were significantly and positively related to mammal species richness, whereas elevation, human population density, and subjective frequency of law enforcement were not. We could not conclude that community outreach and law enforcement were directly causing increased mammal abundance and diversity. Nevertheless, the patterns we detected are some of the first empirical evidence consistent with the idea that biodiversity in protected areas may be more positively and strongly related to local perceptions of the intensity of park management than to either intrinsic (e.g., elevation, park size) or extrinsic (e.g., human population density) environmental factors.

Biodiversity: past, present and future.

On 12–15 May 2011, a diverse group of students, researchers and practitioners from across Canada and around the world met in Banff, Alberta, to discuss the many facets of biodiversity science at the 6th Annual Meeting of the Canadian Society for Ecology and Evolution.