Planning for carnivore recolonization by mapping sex-specific landscape connectivity

Energy-based corridor identification for mammals between protected areas in Iran

Body mass plays a crucial role in determining the mass-specific energy expenditure during terrestrial locomotion across diverse animal taxa, affecting locomotion patterns. The energy landscape concept offers a framework to explore the relationship between landscape characteristics and energy expenditure, enhancing our understanding of animal movement. Although the energy landscape approach solely considers the topographic obstacles faced by animals, its suitability compared to previous methods for constructing resistance maps and delineating corridors has not been comprehensively examined. In this study, we utilized the enerscape R package to generate resistance maps in kilocalories (kcal) by incorporating digital elevation models (DEMs) and body size data (kg). We assigned body sizes ranging from 0.5 to 100 kg to encompass a wide range of small and large mammals in Iran, adjusting maximum dispersal distances accordingly from 50 to 200 km. By analyzing these scenarios, we produced four resistance maps for each body size. Next, we identified potential corridors between terrestrial protected areas in Iran using the Linkage Mapper toolkit and examined barriers and pinch-points along these paths. Our study revealed significant findings regarding the shared corridors between small and large mammals in Iran's landscape. Despite their differing body sizes and energy requirements, many corridors were found to be utilized by both small and large mammal species. For example, we identified 206 corridors for mammals weighing 500 g, which were also recognized as the least-cost paths for 100 kg mammals. Thus, embracing a comprehensive method in resistance map creation, one that incorporates species-specific traits and human infrastructure becomes imperative for accurately identifying least-cost paths and consequently pinpointing pinch points and barriers.

Distribution model transferability for a wide-ranging species, the Gray Wolf

Using existing data can be a reliable and cost-effective way to predict species distributions, and particularly useful for recovering or expanding species. We developed a current gray wolf (Canis lupus) distribution model for the western Great Lakes region, USA, and evaluated the spatial transferability of single-state models to the region. This study is the first assessment of transferability in a wide-ranging carnivore, as well as one of few developed for large spatial extents. We collected 3500 wolf locations from winter surveys in Minnesota (2017–2019), Wisconsin (2019–2020), and Michigan (2017–2020). We included 10 variables: proportion of natural cover, pastures, and crops; distance to natural cover, agriculture, developed land, and water; major and minor road density; and snowfall (1-km res.). We created a regional ensemble distribution by weight-averaging eight models based on their performance. We also developed single-state models, and estimated spatial transferability using two approaches: state cross-validation and extrapolation. We assessed performance by quantifying correlations, receiver operating characteristic curves (ROC), sensitivities, and two niche similarity indices. The regional area estimated to be most suitable for wolves during winter (threshold = maximum sensitivity/specificity) was 106,465 km² (MN = 48,083 km², WI = 27,757 km², MI = 30,625 km²) and correctly predicted 88% of wolf locations analyzed. Increasing natural cover and distance to crops were consistently important for determining regional and single-state wolf distribution. Extrapolation (vs. cross-validation) produced results with the greatest performance metrics, and were most similar to the regional model, yet good internal performance was unrelated to greater extrapolation performance. Factors influencing species distributions are scale-dependent and can vary across areas due to behavioral plasticity. When extending inferences beyond the current occurrence of individuals, assessing variation in ecology such as habitat selection, as well as methodological factors including model performance, will be critical to avoid poor scientific interpretations and develop effective conservation applications. In particular, accurate distribution models for recovering or recovered carnivores can be used to develop plans for habitat management, quantify potential of unoccupied habitat, assess connectivity modeling, and mitigate conflict, facilitating long-term species persistence.

Sex Differences Dictate the Movement Patterns of Striped Hyenas, Hyaena hyaena, in a Human-Dominated Landscape

Large-carnivore populations have experienced significant declines in the past centuries in extended parts of the world. Habitat loss, fragmentation, and depletion of natural resources are some of the main causes of this decline. Consequently, behavioral flexibility, enabling the exploitation of anthropogenic food resources in highly disturbed human-dominated landscapes, is becoming critical for the survival of large carnivores. These behavioral changes increase the potential for human-large carnivore conflict and can further intensify carnivore persecution. Here, we examine how land cover types (representing a gradient of anthropogenic disturbance) alter the behavior of striped hyenas (Hyaena hyaena) in a human-dominated landscape in Israel, and whether differences in life history between males and females affect their reaction to such disturbances and consequently their level of exposure to humans. We used a Hidden Markov Model on GPS-tracking data for seven striped hyenas to segment individual-night trajectories into behavioral states (resting, searching, and traveling). We then used multinomial logistic regression to model hyenas’ behavioral state as a function of the interaction between land cover and sex. Females traveled less than males both in terms of average distance traveled per hour, per night, and nightly net displacement. Most steps were classified as “searching” for females and as “traveling” for males. Female hyenas spent a higher proportion of time in human-dominated areas and a lower proportion in natural areas compared to males, and they were also more likely to be found close to settlements than males. Females changed their time allocation between natural and human-dominated areas, spending more time resting than traveling in natural areas but not in human-dominated ones; males spent more time searching than resting in human-dominated areas but were equally likely to rest or search in natural ones. The differences in life history between male and female hyenas may reflect different motivations for space use as a means to optimize fitness, which affects their exposure to humans and therefore their potential involvement in human-hyenas conflict. Understanding the mechanisms that lead to behavioral change in response to human disturbance is important for adaptive management and promoting human large-carnivores co-existence in general.

Towns and trails drive carnivore movement behaviour, resource selection, and connectivity

BACKGROUND

Global increases in human activity threaten connectivity of animal habitat and populations. Protection and restoration of wildlife habitat and movement corridors require robust models to forecast the effects of human activity on movement behaviour, resource selection, and connectivity. Recent research suggests that animal resource selection and responses to human activity depend on their behavioural movement state, with increased tolerance for human activity in fast states of movement. Yet, few studies have incorporated state-dependent movement behaviour into analyses of Merriam connectivity, that is individual-based metrics of connectivity that incorporate landscape structure and movement behaviour.

METHODS

We assessed the cumulative effects of anthropogenic development on multiple movement processes including movement behaviour, resource selection, and Merriam connectivity. We simulated movement paths using hidden Markov movement models and step selection functions to estimate habitat use and connectivity for three landscape scenarios: reference conditions with no anthropogenic development, current conditions, and future conditions with a simulated expansion of towns and recreational trails. Our analysis used 20 years of grizzly bear (Ursus arctos) and gray wolf (Canis lupus) movement data collected in and around Banff National Park, Canada.

RESULTS

Carnivores increased their speed of travel near towns and areas of high trail and road density, presumably to avoid encounters with people. They exhibited stronger avoidance of anthropogenic development when foraging and resting compared to travelling and during the day compared to night. Wolves exhibited stronger avoidance of anthropogenic development than grizzly bears. Current development reduced the amount of high-quality habitat between two mountain towns by more than 35%. Habitat degradation constrained movement routes around towns and was most pronounced for foraging and resting behaviour. Current anthropogenic development reduced connectivity from reference conditions an average of 85%. Habitat quality and connectivity further declined under a future development scenario.

CONCLUSIONS

Our results highlight the cumulative effects of anthropogenic development on carnivore movement behaviour, habitat use, and connectivity. Our strong behaviour-specific responses to human activity suggest that conservation initiatives should consider how proposed developments and restoration actions would affect where animals travel and how they use the landscape.

Delineating Functional Corridors Linking Leopard Habitat in the Eastern and Western Cape, South Africa

Natural landscapes are increasingly fragmented due to human activity. This contributes to isolation and inadequate gene flow among wildlife populations. These threats intensify where populations are already low, and gene flow is compromised. Ensuring habitat connectivity despite transformed landscapes can mitigate these risks. Leopards are associated with high levels of biodiversity and are the last widely occurring, free-roaming apex predator in South Africa. Although highly adaptable, leopard survival is reduced by human-caused mortality and habitat destruction. We aimed to assess the connectivity of leopard habitat in the Eastern Cape and Western Cape, South Africa. We predicted leopard habitat by correlating GPS data from 31 leopards to environmental features that included human-associated and natural landscapes. We used circuit theory to delineate corridors linking known leopard populations. Finally, using camera traps, we tested whether five predicted corridors were used by leopards. Leopard habitat was strongly correlated to moderate slopes and areas of natural land-cover and plantations, highlighting mountainous areas as important habitat with high connectivity probability. While most habitat patches showed some level of connectivity, leopards avoided highly transformed landscapes, potentially isolating some populations. Where corridors are not functional, active conservation measures for species connectivity becomes important.

Coupling urban 3-D information and circuit theory to advance the development of urban ecological networks

Ongoing, rapid urban growth accompanied by habitat fragmentation and loss challenges biodiversity conservation and leads to decreases in ecosystem services. Application of the concept of ecological networks in the preservation and restoration of connections among isolated patches of natural areas is a powerful conservation strategy. However, previous approaches often failed to objectively consider the impacts of complex 3-D city environments on ecological niches. We used airborne lidar-derived information on the 3-D structure of the built environment and vegetation and detailed land use and cover data to characterize habitat quality, niche diversity, and human disturbance and to predict habitat connectivity among 38 identified habitat core areas (HCAs) in Nanjing, China. We used circuit theory and Linkage Mapper to create a landscape resistance layer, simulate habitat connectivity, and identify and prioritize important corridors. We mapped 64 links by using current flow centrality to evaluate each HCA's contribution and the links that facilitate intact connectivity. Values were highest for HCA links located in the west, south, and northeast of the study area, where natural forests with complex 3-D structures predominate. Two smaller HCA areas had high centrality scores relative to their extents, which means they could act as important stepping stones in connectivity planning. The mapped pinch-point regions had narrow and fragile links among the HCAs, suggesting they require special protection. The barriers with the highest impact scores were mainly located at the HCA connections to Purple Mountain and, based on these high scores, are more likely to indicate important locations that can be restored to improve potential connections. Our novel framework allowed us to sufficiently convey spatially explicit information to identify targets for habitat restoration and potential pathways for species movement and dispersal. Such information is critical for assessing existing or potential habitats and corridors and developing strategic plans to balance habitat conservation and other land uses based on scientifically informed connectivity planning and implementation.