Predicting kill sites of an apex predator from GPS data in different multiprey systems

Kill rates are a central parameter to assess the impact of predation on prey species. An accurate estimation of kill rates requires a correct identification of kill sites, often achieved by field-checking GPS location clusters (GLCs). However, there are potential sources of error included in kill-site identification, such as failing to detect GLCs that are kill sites, and misclassifying the generated GLCs (e.g., kill for nonkill) that were not field checked. Here, we address these two sources of error using a large GPS dataset of collared Eurasian lynx (Lynx lynx), an apex predator of conservation concern in Europe, in three multiprey systems, with different combinations of wild, semidomestic, and domestic prey. We first used a subsampling approach to investigate how different GPS-fix schedules affected the detection of GLC-indicated kill sites. Then, we evaluated the potential of the random forest algorithm to classify GLCs as nonkills, small prey kills, and ungulate kills. We show that the number of fixes can be reduced from seven to three fixes per night without missing more than 5% of the ungulate kills, in a system composed of wild prey. Reducing the number of fixes per 24 h decreased the probability of detecting GLCs connected with kill sites, particularly those of semidomestic or domestic prey, and small prey. Random forest successfully predicted between 73%-90% of ungulate kills, but failed to classify most small prey in all systems, with sensitivity (true positive rate) lower than 65%. Additionally, removing domestic prey improved the algorithm's overall accuracy. We provide a set of recommendations for studies focusing on kill-site detection that can be considered for other large carnivore species in addition to the Eurasian lynx. We recommend caution when working in systems including domestic prey, as the odds of underestimating kill rates are higher.

Temporal variation in translocated Isle Royale wolf diet

Wolves (Canis lupus) can exert top-down pressure and shape ecological communities through the predation of ungulates and beavers (Castor spp.). Therefore, understanding wolf foraging is critical to estimating their ecosystem-level effects. Specifically, if wolves are consumers that optimize tradeoffs between the cost and benefits of prey acquisition, changes in these factors may lead to prey-switching or negative-density dependent selection with potential consequences for community stability. For wolves, factors affecting cost and benefits include prey vulnerability, risk, reward, and availability, which can vary temporally. We described the wolf diet by the frequency of occurrence and percent biomass and characterized the diet using prey remains found in wolf scats on Isle Royale National Park, Michigan, USA, during May-October 2019 and 2020. We used logistic regression to estimate prey consumption over time. We predicted prey with temporal variation in cost (availability and/or vulnerability) such as adult moose (Alces alces), calf moose, and beaver (Castor canadensis) to vary in wolf diets. We analyzed 206 scats and identified 62% of remains as beaver, 26% as moose, and 12% as other species (birds, smaller mammals, and wolves). Adult moose were more likely to occur in wolf scats in May when moose are in poor condition following winter. The occurrence of moose calves peaked during June-mid-July following birth but before calf vulnerability declined as they matured. By contrast, beaver occurrence in wolf scat did not change over time, reflecting the importance of low-handling cost prey items for recently introduced lone or paired wolves. Our results demonstrate that the wolf diet is responsive to temporal changes in prey costs. Temporal fluctuation in diet may influence wolves' ecological role if prey respond to increased predation risk by altering foraging or breeding behavior.

Diverging ecological traits between the Balkan lynx and neighbouring populations as a basis for planning its genetic rescue

Selecting appropriate candidates for genetic rescue mostly relies on previous genetic research and monitoring, while ecological and behavioural traits of the remnant and source populations are rarely considered for such conservation measures. Because of their slow recovery, Eurasian lynx Lynx lynx populations in Central and Western Europe have been a repeated target of genetic reinforcements and reintroductions in the past 50 years. Once inhabiting much of south-eastern Europe, the Balkan lynx L. l. balcanicus is now critically endangered and confined to a small population. Long-term isolation has caused loss of genetic diversity and has possibly led to inbreeding depression. Immediate actions need to consider genetic reinforcement to increase the genetic diversity and secure population viability. Here, we compared the Balkan lynx with two neighbouring populations: Dinaric population originating from the Carpathian subspecies (L.l. carpathicus) and Anatolian population of Caucasian subspecies (L.l. dinniki) to determine is better suited source from an ecological standpoint. Main findings suggest that the L.l. carpathicus is ecologically more similar to the L.l. balcanicus and therefore likely better suited for the environment of south-western Balkans on the basis of prey preference (roe deer being the main prey), local prey availability (lower lagomorph and higher ungulate availability) and habitat use (predominant use of the mixed and broadleaved forests). We discuss the contrasting results of genetic and ecological analyses from both the evolutionary and conservation perspective and provide potential solutions that would take into account both aspects to pave the road towards potential genetic rescue of the Balkan lynx.

Variable effects of wolves on niche breadth and density of intraguild competitors

The parallel niche release hypothesis (PNR) indicates that reduced competition with dominant competitors results in greater density and niche breadth of subordinate competitors and which may support an adaptive advantage.We assessed support for the PNR by evaluating relationships between variation in niche breadth and intra- and interspecific density (an index of competition) of wolves (Canis lupus) coyotes (C. latrans), and bobcats (Lynx rufus).We estimated population density (wolf track surveys, coyote howl surveys, and bobcat hair snare surveys) and variability in space use (50% core autocorrelated kernel density home range estimators), temporal activity (hourly and overnight speed), and dietary (isotopic δ13C and δ15N) niche breadth of each species across three areas of varying wolf density in the Upper Peninsula of Michigan, USA, 2010-2019.Densities of wolves and coyotes were inversely related, and increased variability in space use, temporal activity, and dietary niche breadth of coyotes was associated with increased coyote density and decreased wolf density supporting the PNR. Variability in space use and temporal activity of wolves and dietary niche breadth of bobcats also increased with increased intraspecific density supporting the PNR.Through demonstrating decreased competition between wolves and coyotes and increased coyote niche breadth and density, our study provides multidimensional support for the PNR. Knowledge of the relationship between niche breadth and population density can inform our understanding of the role of competition in shaping the realized niche of species.

Spatial segregation and habitat partitioning of bobcat and Canada lynx

Harvest records suggest that the abundance of bobcats ( Lynx rufus) has increased and the leading edge of their distribution has spread northward, while the trailing edge of the Canada lynx ( Lynx canadensis) range has contracted in Ontario, Canada. There has been a debate about whether these closely related felids might compete in areas of sympatry, but there is little research on sympatric populations of bobcat and lynx. Both species are found on the north shore of Lake Huron in Ontario, Canada, which provided an opportunity to investigate their spatial patterns and habitat use. We surveyed snowmobile routes for snow tracks over three winters and estimated probability of occupancy for the two felid species while accounting for detectability. Bobcat and lynx tracks were never found on the same survey route. Bobcat occupancy increased with habitat heterogeneity, whereas lynx occupancy increased with homogeneity. Our results fit with the common assumption of the generalist and specialist natures of bobcat and lynx, respectively. Our findings suggest that bobcats invaded former lynx territory after these areas became vacant. The story of the bobcat and the lynx is one of the loss of a unique, boreal specialist due to anthropogenic change, and eventual replacement by an adaptable generalist.

Subsidies from anthropogenic resources alter diet, activity, and ranging behavior of an apex predator (Canis lupus)

Acquisition of resources can be costly and individuals are predicted to optimize foraging strategies to maximize net energy gain. Wolves (Canis lupus) would be expected to scavenge on subsidies from anthropogenic resources when these resources provide an energetic benefit over the capture of wild prey. We examined the effects of subsidies from anthropogenic resources in the form of livestock carcass dumps (LCDs) on wolf space use, activity, tortuosity, and diet in portions of North America’s northern hardwood/boreal ecosystem. We fitted 19 wolves with global positioning system collars during May–August of 2009–2011 and 2013–2015. Wolves with LCDs within their home ranges used areas adjacent to LCDs greater than non-LCD sites and had decreased home ranges and activity as compared to wolves without LCDs in their home ranges. Additionally, cattle comprised at least 22% of wolf diet from scavenging in areas with LCDs present as compared to no cattle in the diet of wolves without access to LCDs. Subsidies from anthropogenic resources in the form of LCDs can serve as attractants for wolves and alter wolf diet, activity, and ranging behavior. Apex predators may alter their behavior where subsidies from anthropogenic resources occur and management of these subsidies should be considered when attempting to reduce the impacts of humans on wolf behavior.

Habitat suitability does not capture the essence of animal-defined corridors

BACKGROUND

Increases in landscape connectivity can improve a species' ability to cope with habitat fragmentation and degradation. Wildlife corridors increase landscape connectivity and it is therefore important to identify and maintain them. Currently, corridors are mostly identified using methods that rely on generic habitat suitability measures. One important and widely held assumption is that corridors represent swaths of suitable habitat connecting larger patches of suitable habitat in an otherwise unsuitable environment. Using high-resolution GPS data of four large carnivore species, we identified corridors based on animal movement behavior within each individual's home range and quantified the spatial overlap of these corridors. We thus tested whether corridors were in fact spatial bottle necks in habitat suitability surrounded by unsuitable habitat, and if they could be characterized by their coarse-scale environmental composition.

RESULTS

We found that most individuals used corridors within their home ranges and that several corridors were used simultaneously by individuals of the same species, but also by individuals of different species. When we compared the predicted habitat suitability of corridors and their immediate surrounding area we found, however, no differences.

CONCLUSIONS

We could not find a direct correspondence between corridors chosen and used by wildlife on the one hand, and a priori habitat suitability measurements on the other hand. This leads us to speculate that identifying corridors relying on typically-used habitat suitability methods alone may misplace corridors at the level of space use within an individual's home range. We suggest future studies to rely more on movement data to directly identify wildlife corridors based on the observed behavior of the animals.

Space-time clusters for early detection of grizzly bear predation

Accurate detection and classification of predation events is important to determine predation and consumption rates by predators. However, obtaining this information for large predators is constrained by the speed at which carcasses disappear and the cost of field data collection. To accurately detect predation events, researchers have used GPS collar technology combined with targeted site visits. However, kill sites are often investigated well after the predation event due to limited data retrieval options on GPS collars (VHF or UHF downloading) and to ensure crew safety when working with large predators. This can lead to missing information from small-prey (including young ungulates) kill sites due to scavenging and general site deterioration (e.g., vegetation growth). We used a space-time permutation scan statistic (STPSS) clustering method (SaTScan) to detect predation events of grizzly bears (Ursus arctos) fitted with satellite transmitting GPS collars. We used generalized linear mixed models to verify predation events and the size of carcasses using spatiotemporal characteristics as predictors. STPSS uses a probability model to compare expected cluster size (space and time) with the observed size. We applied this method retrospectively to data from 2006 to 2007 to compare our method to random GPS site selection. In 2013-2014, we applied our detection method to visit sites one week after their occupation. Both datasets were collected in the same study area. Our approach detected 23 of 27 predation sites verified by visiting 464 random grizzly bear locations in 2006-2007, 187 of which were within space-time clusters and 277 outside. Predation site detection increased by 2.75 times (54 predation events of 335 visited clusters) using 2013-2014 data. Our GLMMs showed that cluster size and duration predicted predation events and carcass size with high sensitivity (0.72 and 0.94, respectively). Coupling GPS satellite technology with clusters using a program based on space-time probability models allows for prompt visits to predation sites. This enables accurate identification of the carcass size and increases fieldwork efficiency in predation studies.

Identification of kill sites from GPS clusters for jaguars (Panthera onca) in the southern Pantanal, Brazil

Context Understanding predator–prey relationships is important for making informed management decisions. Knowledge of jaguar (Panthera onca) predation on livestock and native prey is imperative for future conservation of jaguars in Central and South America. Aim As part of an investigation to determine predation patterns of jaguars in the southern Pantanal, Brazil, we examined spatial, temporal and habitat variables, which are useful in categorising location clusters as kill sites and non-kill sites. Methods Using GPS-collars on 10 jaguars we obtained a total of 11 784 locations, from which 877 clusters were identified, visited and examined for prey remains. Of the 877 clusters, 421 were associated with a kill and 456 clusters were not associated with a kill. We used univariate and multivariate models to examine the influence of spatial (distance to nearest: water, dense cover, road; dispersion of points), temporal (season, time, number of nights, duration) and habitat (percentage of seven habitat classes, dominant habitat class) variables on categorising clusters as kill or non-kill sites. Key results We found the time a jaguar spent at a cluster (duration), the dispersion of points around the centre of the cluster (dispersion) and the number of nights spent at the cluster were all reliable predictors of whether a cluster was a kill or non-kill site. The best model predicting the likelihood a cluster was a jaguar kill site was a combination of duration and dispersion. Habitat variables were not important in discriminating kills from non-kill sites. Conclusion We identified factors useful for discriminating between kills and non-kill sites for jaguars. We found that as a jaguar spent more time at a cluster and as the dispersion of points around the centre of the cluster increased, the higher likelihood the cluster was a jaguar kill. Similarly, as the number of nights spent at the cluster increased, the greater the probability the cluster was a kill. Implications Our results will increase the efficiency of field investigations of location clusters in determining predation patterns of jaguars in Central and South America. Being able to prioritise which location clusters should be investigated will assist researchers with limited time and resources.

Improvements on GPS Location Cluster Analysis for the Prediction of Large Carnivore Feeding Activities: Ground-Truth Detection Probability and Inclusion of Activity Sensor Measures

Animal space use studies using GPS collar technology are increasingly incorporating behavior based analysis of spatio-temporal data in order to expand inferences of resource use. GPS location cluster analysis is one such technique applied to large carnivores to identify the timing and location of feeding events. For logistical and financial reasons, researchers often implement predictive models for identifying these events. We present two separate improvements for predictive models that future practitioners can implement. Thus far, feeding prediction models have incorporated a small range of covariates, usually limited to spatio-temporal characteristics of the GPS data. Using GPS collared cougar (Puma concolor) we include activity sensor data as an additional covariate to increase prediction performance of feeding presence/absence. Integral to the predictive modeling of feeding events is a ground-truthing component, in which GPS location clusters are visited by human observers to confirm the presence or absence of feeding remains. Failing to account for sources of ground-truthing false-absences can bias the number of predicted feeding events to be low. Thus we account for some ground-truthing error sources directly in the model with covariates and when applying model predictions. Accounting for these errors resulted in a 10% increase in the number of clusters predicted to be feeding events. Using a double-observer design, we show that the ground-truthing false-absence rate is relatively low (4%) using a search delay of 2–60 days. Overall, we provide two separate improvements to the GPS cluster analysis techniques that can be expanded upon and implemented in future studies interested in identifying feeding behaviors of large carnivores.