A multidisciplinary approach to estimating wolf population size for long-term conservation

The wolf (Canis lupus) is among the most controversial of wildlife species. Abundance estimates are required to inform public debate and policy decisions, but obtaining them at biologically relevant scales is challenging. We developed a system for comprehensive population estimation across the Italian alpine region (100,000 km2 ), involving 1513 trained operators representing 160 institutions. This extensive network allowed for coordinated genetic sample collection and landscape-level spatial capture-recapture analyses that transcended administrative boundaries to produce the first estimates of key parameters for wolf population status assessment. Wolf abundance was estimated at 952 individuals (95% credible interval 816-1120) and 135 reproductive units (i.e., packs) (95% credible interval 112-165). We also estimated that mature individuals accounted for 33-45% of the entire population. The monitoring effort was spatially estimated thereby overcoming an important limitation of citizen science data. This is an important approach for promoting wolf-human coexistence based on wolf abundance monitoring and an endorsement of large-scale harmonized conservation practices.

Transboundary Monitoring of the Wolf Alpine Population over 21 Years and Seven Countries

Wolves have large spatial requirements and their expansion in Europe is occurring over national boundaries, hence the need to develop monitoring programs at the population level. Wolves in the Alps are defined as a functional population and management unit. The range of this wolf Alpine population now covers seven countries: Italy, France, Austria, Switzerland, Slovenia, Liechtenstein and Germany, making the development of a joint and coordinated monitoring program particularly challenging. In the framework of the Wolf Alpine Group (WAG), researchers developed uniform criteria for the assessment and interpretation of field data collected in the frame of different national monitoring programs. This standardization allowed for data comparability across borders and the joint evaluation of distribution and consistency at the population level. We documented the increase in the number of wolf reproductive units (packs and pairs) over 21 years, from 1 in 1993-1994 up to 243 units in 2020-2021, and examined the pattern of expansion over the Alps. This long-term and large-scale approach is a successful example of transboundary monitoring of a large carnivore population that, despite administrative fragmentation, provides robust indexes of population size and distribution that are of relevance for wolf conservation and management at the transnational Alpine scale.

Density-habitat relationships of white-tailed deer (Odocoileus virginianus) in Finland

In heterogeneous landscapes, resource selection constitutes a crucial link between landscape and population-level processes such as density. We conducted a non-invasive genetic study of white-tailed deer in southern Finland in 2016 and 2017 using fecal DNA samples to understand factors influencing white-tailed deer density and space use in late summer prior to the hunting season. We estimated deer density as a function of landcover types using a spatial capture-recapture (SCR) model with individual identities established using microsatellite markers. The study revealed second-order habitat selection with highest deer densities in fields and mixed forest, and third-order habitat selection (detection probability) for transitional woodlands (clear-cuts) and closeness to fields. Including landscape heterogeneity improved model fit and increased inferred total density compared with models assuming a homogenous landscape. Our findings underline the importance of including habitat covariates when estimating density and exemplifies that resource selection can be studied using non-invasive methods.

A flexible and efficient Bayesian implementation of point process models for spatial capture-recapture data

Spatial capture-recapture (SCR) is now routinely used for estimating abundance and density of wildlife populations. A standard SCR model includes sub-models for the distribution of individual activity centers (ACs) and for individual detections conditional on the locations of these ACs. Both sub-models can be expressed as point processes taking place in continuous space, but there is a lack of accessible and efficient tools to fit such models in a Bayesian paradigm. Here, we describe a set of custom functions and distributions to achieve this. Our work allows for more efficient model fitting with spatial covariates on population density, offers the option to fit SCR models using the semi-complete data likelihood (SCDL) approach instead of data augmentation, and better reflects the spatially continuous detection process in SCR studies that use area searches. In addition, the SCDL approach is more efficient than data augmentation for simple SCR models while losing its advantages for more complicated models that account for spatial variation in either population density or detection. We present the model formulation, test it with simulations, quantify computational efficiency gains, and conclude with a real-life example using non-invasive genetic sampling data for an elusive large carnivore, the wolverine (Gulo gulo) in Norway.

Evaluating the summer landscapes of predation risk and forage quality for elk (Cervus canadensis)

The recovery of carnivore populations in North American has consequences for trophic interactions and population dynamics of prey. In addition to direct effects on prey populations through killing, predators can influence prey behavior by imposing the risk of predation. The mechanisms through which patterns of space use by predators are linked to behavioral response by prey and nonconsumptive effects on prey population dynamics are poorly understood. Our goal was to characterize population‐ and individual‐level patterns of resource selection by elk (Cervus canadensis) in response to risk of wolves (Canis lupus) and mountain lions (Puma concolor) and evaluate potential nonconsumptive effects of these behavioral patterns. We tested the hypothesis that individual elk risk‐avoidance behavior during summer would result in exposure to lower‐quality forage and reduced body fat and pregnancy rates. First, we evaluated individuals' second‐order and third‐order resource selection with a used‐available sampling design. At the population level, we found evidence for a positive relationship between second‐ and third‐order selection and forage, and an interaction between forage quality and mountain lion risk such that the relative probability of use at low mountain lion risk increased with forage quality but decreased at high risk at both orders of selection. We found no evidence of a population‐level trade‐off between forage quality and wolf risk. However, we found substantial among‐individual heterogeneity in resource selection patterns such that population‐level patterns were potentially misleading. We found no evidence that the diversity of individual resource selection patterns varied predictably with available resources, or that patterns of individual risk‐related resource selection translated into biologically meaningful changes in body fat or pregnancy rates. Our work highlights the importance of evaluating individual responses to predation risk and predator hunting technique when assessing responses to predators and suggests nonconsumptive effects are not operating at a population scale in this system.

Assumptions about fence permeability influence density estimates for brown hyaenas across South Africa

Wildlife population density estimates provide information on the number of individuals in an area and influence conservation management decisions. Thus, accuracy is vital. A dominant feature in many landscapes globally is fencing, yet the implications of fence permeability on density estimation using spatial capture-recapture modelling are seldom considered. We used camera trap data from 15 fenced reserves across South Africa to examine the density of brown hyaenas (Parahyaena brunnea). We estimated density and modelled its relationship with a suite of covariates when fenced reserve boundaries were assumed to be permeable or impermeable to hyaena movements. The best performing models were those that included only the influence of study site on both hyaena density and detection probability, regardless of assumptions of fence permeability. When fences were considered impermeable, densities ranged from 2.55 to 15.06 animals per 100 km², but when fences were considered permeable, density estimates were on average 9.52 times lower (from 0.17 to 1.59 animals per 100 km²). Fence permeability should therefore be an essential consideration when estimating density, especially since density results can considerably influence wildlife management decisions. In the absence of strong evidence to the contrary, future studies in fenced areas should assume some degree of permeability in order to avoid overestimating population density.

Minimum habitat thresholds required for conserving mountain lion genetic diversity

Jointly considering the ecology (e.g., habitat use) and genetics (e.g., population genetic structure and diversity) of a species can increase understanding of current conservation status and inform future management practices. Previous analyses indicate that mountain lion (Puma concolor) populations in California are genetically structured and exhibit extreme variation in population genetic diversity. Although human development may have fragmented gene flow, we hypothesized the quantity and quality of remaining habitat available would affect the genetic viability of each population. Our results indicate that area of suitable habitat, determined via a resource selection function derived using 843,500 location fixes from 263 radio‐collared mountain lions, is strongly and positively associated with population genetic diversity and viability metrics, particularly with effective population size. Our results suggested that contiguous habitat of ≥10,000 km² may be sufficient to alleviate the negative effects of genetic drift and inbreeding, allowing mountain lion populations to maintain suitable effective population sizes. Areas occupied by five of the nine geographic–genetic mountain lion populations in California fell below this habitat threshold, and two (Santa Monica Area and Santa Ana) of those five populations lack connectivity to nearby populations. Enhancing ecological conditions by protection of greater areas of suitable habitat and facilitating positive evolutionary processes by increasing connectivity (e.g., road‐crossing structures) might promote persistence of small or isolated populations. The conservation status of suitable habitat also appeared to influence genetic diversity of populations. Thus, our results demonstrate that both the area and status (i.e., protected or unprotected) of suitable habitat influence the genetic viability of mountain lion populations.

Simulation-based validation of spatial capture-recapture models: A case study using mountain lions

Spatial capture-recapture (SCR) models have improved the ability to estimate densities of rare and elusive animals. However, SCR models have seldom been validated even as model formulations diversify and expand to incorporate new sampling methods and/or additional sources of information on model parameters. Information on the relationship between encounter probabilities, sources of additional information, and the reliability of density estimates, is rare but crucial to assessing reliability of SCR-based estimates. We used a simulation-based approach that incorporated prior empirical work to assess the accuracy and precision of density estimates from SCR models using spatially unstructured sampling. To assess the consequences of sparse data and potential sources of bias, we simulated data under six scenarios corresponding to three different levels of search effort and two levels of correlation between search effort and animal density. We then estimated density for each scenario using four models that included increasing amounts of information from harvested individuals and telemetry to evaluate the impact of additional sources of information. Model results were sensitive to the quantity of available information: density estimates based on low search effort were biased high and imprecise, whereas estimates based on high search effort were unbiased and precise. A correlation between search effort and animal density resulted in a positive bias in density estimates, though the bias decreased with increasingly informative datasets. Adding information from harvested individuals and telemetered individuals improved density estimates based on low and moderate effort but had negligible impact for datasets resulting from high effort. We demonstrated that density estimates from SCR models using spatially unstructured sampling are reliable when sufficient information is provided. Accurate density estimates can result if empirical-based simulations such as those presented here are used to develop study designs with appropriate amounts of effort and information sources.

Improving estimation of puma (Puma concolor) population density: clustered camera-trapping, telemetry data, and generalized spatial mark-resight models

Obtaining reliable population density estimates for pumas (Puma concolor) and other cryptic, wide-ranging large carnivores is challenging. Recent advancements in spatially explicit capture-recapture models have facilitated development of novel survey approaches, such as clustered sampling designs, which can provide reliable density estimation for expansive areas with reduced effort. We applied clustered sampling to camera-traps to detect marked (collared) and unmarked pumas, and used generalized spatial mark-resight (SMR) models to estimate puma population density across 15,314 km² in the southwestern USA. Generalized SMR models outperformed conventional SMR models. Integrating telemetry data from collars on marked pumas with detection data from camera-traps substantially improved density estimates by informing cryptic activity (home range) center transiency and improving estimation of the SMR home range parameter. Modeling sex of unmarked pumas as a partially identifying categorical covariate further improved estimates. Our density estimates (0.84–1.65 puma/100 km²) were generally more precise (CV = 0.24–0.31) than spatially explicit estimates produced from other puma sampling methods, including biopsy darting, scat detection dogs, and regular camera-trapping. This study provides an illustrative example of the effectiveness and flexibility of our combined sampling and analytical approach for reliably estimating density of pumas and other wildlife across geographically expansive areas.

Lions and leopards coexist without spatial, temporal or demographic effects of interspecific competition

Although interspecific competition plays a principal role in shaping species behaviour and demography, little is known about the population-level outcomes of competition between large carnivores, and the mechanisms that facilitate coexistence. We conducted a multilandscape analysis of two widely distributed, threatened large carnivore competitors to offer insight into coexistence strategies and assist with species-level conservation. We evaluated how interference competition affects occupancy, temporal activity and population density of a dominant competitor, the lion (Panthera leo), and its subordinate competitor, the leopard (Panthera pardus). We collected camera-trap data over 3 years in 10 study sites covering 5,070 km² . We used multispecies occupancy modelling to assess spatial responses in varying environmental and prey conditions and competitor presence, and examined temporal overlap and the relationship between lion and leopard densities across sites and years. Results showed that both lion and leopard occupancy was independent of-rather than conditional on-their competitor's presence across all environmental covariates. Marginal occupancy probability for leopard was higher in areas with more bushy, "hideable" habitat, human (tourist) activity and topographic ruggedness, whereas lion occupancy decreased with increasing hideable habitat and increased with higher abundance of very large prey. Temporal overlap was high between carnivores, and there was no detectable relationship between species densities. Lions pose a threat to the survival of individual leopards, but they exerted no tractable influence on leopard spatial or temporal dynamics. Furthermore, lions did not appear to suppress leopard populations, suggesting that intraguild competitors can coexist in the same areas without population decline. Aligned conservation strategies that promote functioning ecosystems, rather than target individual species, are therefore advised to achieve cost- and space-effective conservation.

Using spatial mark-recapture for conservation monitoring of grizzly bear populations in Alberta

One of the challenges in conservation is determining patterns and responses in population density and distribution as it relates to habitat and changes in anthropogenic activities. We applied spatially explicit capture recapture (SECR) methods, combined with density surface modelling from five grizzly bear (Ursus arctos) management areas (BMAs) in Alberta, Canada, to assess SECR methods and to explore factors influencing bear distribution. Here we used models of grizzly bear habitat and mortality risk to test local density associations using density surface modelling. Results demonstrated BMA-specific factors influenced density, as well as the effects of habitat and topography on detections and movements of bears. Estimates from SECR were similar to those from closed population models and telemetry data, but with similar or higher levels of precision. Habitat was most associated with areas of higher bear density in the north, whereas mortality risk was most associated (negatively) with density of bears in the south. Comparisons of the distribution of mortality risk and habitat revealed differences by BMA that in turn influenced local abundance of bears. Combining SECR methods with density surface modelling increases the resolution of mark-recapture methods by directly inferring the effect of spatial factors on regulating local densities of animals.

Estimating abundance and density of Amur tigers along the Sino-Russian border

As an apex predator the Amur tiger (Panthera tigris altaica) could play a pivotal role in maintaining the integrity of forest ecosystems in Northeast Asia. Due to habitat loss and harvest over the past century, tigers rapidly declined in China and are now restricted to the Russian Far East and bordering habitat in nearby China. To facilitate restoration of the tiger in its historical range, reliable estimates of population size are essential to assess effectiveness of conservation interventions. Here we used camera trap data collected in Hunchun National Nature Reserve from April to June 2013 and 2014 to estimate tiger density and abundance using both maximum likelihood and Bayesian spatially explicit capture-recapture (SECR) methods. A minimum of 8 individuals were detected in both sample periods and the documentation of marking behavior and reproduction suggests the presence of a resident population. Using Bayesian SECR modeling within the 11 400 km(2) state space, density estimates were 0.33 and 0.40 individuals/100 km(2) in 2013 and 2014, respectively, corresponding to an estimated abundance of 38 and 45 animals for this transboundary Sino-Russian population. In a maximum likelihood framework, we estimated densities of 0.30 and 0.24 individuals/100 km(2) corresponding to abundances of 34 and 27, in 2013 and 2014, respectively. These density estimates are comparable to other published estimates for resident Amur tiger populations in the Russian Far East. This study reveals promising signs of tiger recovery in Northeast China, and demonstrates the importance of connectivity between the Russian and Chinese populations for recovering tigers in Northeast China.

Linking landscape-scale differences in forage to ungulate nutritional ecology

Understanding how habitat and nutritional condition affect ungulate populations is necessary for informing management, particularly in areas experiencing carnivore recovery and declining ungulate population trends. Variations in forage species availability, plant phenological stage, and the abundance of forage make it challenging to understand landscape-level effects of nutrition on ungulates. We developed an integrated spatial modeling approach to estimate landscape-level elk (Cervus elaphus) nutritional resources in two adjacent study areas that differed in coarse measures of habitat quality and related the consequences of differences in nutritional resources to elk body condition and pregnancy rates. We found no support for differences in dry matter digestibility between plant samples or in phenological stage based on ground sampling plots in the two study areas. Our index of nutritional resources, measured as digestible forage biomass, varied among land cover types and between study areas. We found that altered plant composition following fires was the biggest driver of differences in nutritional resources, suggesting that maintaining a mosaic of fire history and distribution will likely benefit ungulate populations. Study area, lactation status, and year affected fall body fat of adult female elk. Elk in the study area exposed to lower summer range nutritional resources had lower nutritional condition entering winter. These differences in nutritional condition resulted in differences in pregnancy rate, with average pregnancy rates of 89% for elk exposed to higher nutritional resources and 72% for elk exposed to lower nutritional resources. Summer range nutritional resources have the potential to limit elk pregnancy rate and calf production, and these nutritional limitations may predispose elk to be more sensitive to the effects of harvest or predation. Wildlife managers should identify ungulate populations that are nutritionally limited and recognize that these populations may be more impacted by recovering carnivores or harvest than populations inhabiting more productive summer habitats.