Combining resource selection functions and home-range data to identify habitat conservation priorities for brown bears

Linking landscape structure and vegetation productivity with nut consumption by the Cantabrian brown bear during hyperphagia

In bears, reproduction is dependent on the body reserves accumulated during hyperphagia. The Cantabrian brown bear mainly feeds on nuts during the hyperphagia period. Understanding how landscape heterogeneity and vegetation productivity in human-dominated landscapes influence the feeding habits of bears may therefore be important for disentangling species-habitat relationships of conservation interest. We determined the spatial patterns of nut consumption by brown bears during the hyperphagia period in relation to landscape structure, characteristics of fruit-producing patches and vegetation productivity. For this purpose, we constructed foraging models based on nut consumption data (obtained by scat analysis), by combining vegetation productivity data, topographical variables and landscape metrics to identify nut foraging patterns during this critical period for bears. The average wooded area of patches where scats were collected and where the nuts that the bears had consumed were produced was larger than that of the corresponding patches where nuts were not produced. For scats collected outside of nut-producing patches, the distance between the scats and the patches was greatest for chestnut-producing patches. Elevation, Gross Primary Production (GPP) and the Aggregation Index (AI) were good predictors of acorn consumption in the models. Good model fits were not obtained for data on chestnut consumption in bears. The findings confirm that brown bears feeding on nuts show a preference for relatively large, highly aggregated patches with a high degree of diversity in the landscape pattern, which may help the bears to remain undetected. The nut prediction model highlights areas of particular importance for brown bears during hyperphagia. The human presence associated with sweet chestnut forest stands or orchards may make bears feel more vulnerable when feeding.

Spring phenology drives range shifts in a migratory Arctic ungulate with key implications for the future

Annual variation in phenology can have profound effects on the behavior of animals. As climate change advances spring phenology in ecosystems around the globe, it is becoming increasingly important to understand how animals respond to variation in the timing of seasonal events and how their responses may shift in the future. We investigated the influence of spring phenology on the behavior of migratory, barren-ground caribou (Rangifer tarandus), a species that has evolved to cope with short Arctic summers. Specifically, we examined the effect of spring snow melt and vegetation growth on the current and potential future space-use patterns of the Porcupine Caribou Herd (PCH), which exhibits large, inter-annual shifts in their calving and post-calving distributions across the U.S.-Canadian border. We quantified PCH selection for snow melt and vegetation phenology using machine learning models, determined how selection resulted in annual shifts in space-use, and then projected future distributions based on climate-driven phenology models. Caribou exhibited strong, scale-dependent selection for both snow melt and vegetation growth. During the calving season, caribou selected areas at finer scales where the snow had melted and vegetation was greening, but within broader landscapes that were still brown or snow covered. During the post-calving season, they selected vegetation with intermediate biomass expected to have high forage quality. Annual variation in spring phenology predicted major shifts in PCH space-use. In years with early spring phenology, PCH predominately used habitat in Alaska, while in years with late phenology, they spent more time in Yukon. Future climate conditions were projected to advance spring phenology, shifting PCH calving and post-calving distributions further west into Alaska. Our results demonstrate that caribou selection for habitat in specific phenological stages drive dramatic shifts in annual space-use patterns, and will likely affect future distributions, underscoring the importance of maintaining sufficient suitable habitat to allow for behavioral plasticity.

Spatial ecology of conflicts: unravelling patterns of wildlife damage at multiple scales

Human encroachment into natural habitats is typically followed by conflicts derived from wildlife damage to agriculture and livestock. Spatial risk modelling is a useful tool to gain the understanding of wildlife damage and mitigate conflicts. Although resource selection is a hierarchical process operating at multiple scales, risk models usually fail to address more than one scale, which can result in the misidentification of the underlying processes. Here, we addressed the multi-scale nature of wildlife damage occurrence by considering ecological and management correlates interacting from household to landscape scales. We studied brown bear (Ursus arctos) damage to apiaries in the North-eastern Carpathians as our model system. Using generalized additive models, we found that brown bear tendency to avoid humans and the habitat preferences of bears and beekeepers determine the risk of bear damage at multiple scales. Damage risk at fine scales increased when the broad landscape context also favoured damage. Furthermore, integrated-scale risk maps resulted in more accurate predictions than single-scale models. Our results suggest that principles of resource selection by animals can be used to understand the occurrence of damage and help mitigate conflicts in a proactive and preventive manner.

Landscape condition influences energetics, reproduction, and stress biomarkers in grizzly bears

Environmental change has been shown to influence mammalian distribution, habitat use, and behavior; however, few studies have investigated the impact on physiological function. This study aimed to determine the influence of landscape condition on the expression of target proteins related to energetics, reproduction, and stress in grizzly bears. We hypothesized that changes in landscape condition explains protein expression. Skin biopsies were collected from free-ranging grizzly bears in Alberta, Canada from 2013-2019 (n = 86 individuals). We used an information theoretic approach to develop 11 a priori candidate generalized linear mixed models to explain protein expression. We compared models using Akaike Information Criteria (AICc) weights and averaged models with ΔAICc < 2 for each protein. Food resources, represented by increased distance to coal mines and decreased crown closure, positively influenced energetic proteins (adiponectin and alpha-1-acid glycoprotein). Proteins related to reproduction (ceruloplasmin and serpin B5) were positively associated with increased wetland and upland food resources in addition to movement, but negatively associated with increased distance to roads. One stress related protein, complement C3, was positively influenced by increased percent conifer. Given the need to detect emerging threats to wildlife, we suggest the assessment of physiological function will lead to improved monitoring of species in rapidly changing landscapes.

Habitat use and selection patterns inform habitat conservation priorities of an endangered large carnivore in southern Europe

Understanding the habitat use and selection patterns of endangered species is essential in developing management measures that will protect critical habitat and mitigate human-wildlife conflicts. This understanding is particularly important in areas with high anthropogenic pressures. To understand the ecological role of various habitat types in the conservation of an endangered large carnivore in southern Europe, with its distinct environmental conditions and predominantly anthropogenic landscapes, we studied 18 GPS-collared brown bears Ursus arctos in Greece. We examined the use and selection of habitats according to age and sex categories and behavioral status during 5 ecologically defined seasons. Areas with rough terrain were identified as important refuge areas and were used by all bears in late hyperphagia and emergence. All bears used areas closer to human-related habitat features during the night. Habitat selection was positive for areas with rough terrain and naturalized (i.e. abandoned or not intensive) crops and areas close to water courses, while high-altitude areas and roads were avoided. The selection or avoidance of other habitats varied across bear categories and between stationary and moving behavior. We recommend that the results of the study be used to develop guidelines for species conservation and allow for prioritizing management actions that will promote the conservation of bears in Greece. In particular, the habitat use patterns provide information on how to limit interactions between humans and bears in space and/or time, while the habitat selection patterns indicate suitable habitats that should be protected/improved based on their importance and ecological role for the species.

Brown bear den characteristics and selection in eastern Transylvania, Romania

Dens are important for species that need to survive and reproduce during harsh winters. Brown bears (Ursus arctos) in Romania, listed by the European Union as a population of concern, use dens for several months each year. To date, few quantitative assessments of denning habitat have been carried out for this population or others in Europe. In 2008–2013 and 2015–2017, we used local knowledge and telemetry data from brown bears fitted with GPS collars to identify 115 winter dens and eight open ground nests used by bears in eastern Transylvania, Romania. We located most dens in mountainous areas (64%) and fewer in foothills (36%). Den entrances in mountainous areas were significantly narrower than entrances in foothills, likely due to the need for reduced thermal loss during more severe winters at higher elevations. We selected seven habitat characteristics (abiotic and biotic) and human-related covariates associated with known locations of dens and open nests to identify potential brown bear denning habitat using maximum entropy modeling. We found that terrain ruggedness was the single most important factor when predicting bear denning habitat. The habitat map derived from this study can be used in the future to safeguard bear denning areas from potential human disturbances.

Inferring fine-scale spatial structure of the brown bear (Ursus arctos) population in the Carpathians prior to infrastructure development

Landscape genetics is increasingly being used in landscape planning for biodiversity conservation by assessing habitat connectivity and identifying landscape barriers, using intraspecific genetic data and quantification of landscape heterogeneity to statistically test the link between genetic variation and landscape variability. In this study we used genetic data to understand how landscape features and environmental factors influence demographic connectedness in Europe’s largest brown bear population and to assist in mitigating planned infrastructure development in Romania. Model-based clustering inferred one large and continuous bear population across the Carpathians suggesting that suitable bear habitat has not become sufficiently fragmented to restrict movement of individuals. However, at a finer scale, large rivers, often located alongside large roads with heavy traffic, were found to restrict gene flow significantly, while eastern facing slopes promoted genetic exchange. Since the proposed highway infrastructure development threatens to fragment regions of the Carpathians where brown bears occur, we develop a decision support tool based on models that assess the landscape configuration needed for brown bear conservation using wildlife corridor parameters. Critical brown bear corridors were identified through spatial mapping and connectivity models, which may be negatively influenced by infrastructure development and which therefore require mitigation. We recommend that current and proposed infrastructure developments incorporate these findings into their design and where possible avoid construction measures that may further fragment Romania’s brown bear population or include mitigation measures where alternative routes are not feasible.

Large carnivore habitat suitability modelling for Romania and associated predictions for protected areas

Habitat characteristics associated with species occurrences represent important baseline information for wildlife management and conservation, but have rarely been assessed for countries recently joining the EU. We used footprint tracking data and landscape characteristics in Romania to investigate the occurrence of brown bear (Ursus arctos), gray wolf (Canis lupus) and Eurasian lynx (Lynx lynx) and to compare model predictions between Natura 2000 and national-level protected areas (gap analysis). Wolves were more likely to occur where rugged terrain was present. Increasing proportion of forest was positively associated with occurrence of all large carnivores, but forest type (broadleaf, mixed, or conifer) generally varied with carnivore species. Areas where cultivated lands were extensive had little suitable habitat for lynx, whereas bear occurrence probability decreased with increasing proportion of built areas. Pastures were positively associated with wolf and lynx occurrence. Brown bears occurred primarily where national roads with high traffic volumes were at low density, while bears and lynx occurred at medium-high densities of communal roads that had lower traffic volumes. Based on predictions of carnivore distributions, natural areas protected in national parks were most suitable for carnivores, nature parks were less suitable, whereas EU-legislated Natura 2000 sites had the lowest probability of carnivore presence. Our spatially explicit carnivore habitat suitability predictions can be used by managers to amend borders of existing sites, delineate new protected areas, and establish corridors for ecological connectivity. To assist recovery and recolonization, management could also focus on habitat predicted to be suitable but where carnivores were not tracked.

Movement ecology of brown bears (Ursus arctos) in the Romanian Eastern Carpathians

Brown bear movement patterns are driven by their opportunistic feeding behaviour, with their complex life history and seasonality playing an important role in habitat selection. Within a large unfragmented forest habitats persisting over decades in the Romanian Carpathians and a prohibitive hunting management during 40 years of communist centralised game management, information about brown bear movements and spatial ecology is lacking. Using data obtained from 13 brown bears fitted with GPS telemetry collars, we estimated home ranges and core activity areas and we investigated the daily, seasonal and altitudinal movements of brown bears in the Eastern Romanian Carpathians and surrounding high hills. The median MCP95% home ranges of brown bears was 629.92 km2 and the median size of core activity areas (estimated as 50% kernel density) was 36.37 km2, with no significant differences between males and females. The mean daily distance travelled, measured as daily displacement length, was 1818 m and an analysis of seasonal movements indicated significant differences between seasons (greatest movements during the Hyperphagia season). The GPS-collared brown bears travelled between a minimum altitude measured at ~234 m and a maximum at ~1634 m. Analysing the spatial overlap between the estimated home range and the game management units (GMU) limits, we obtained a median number of 8 GMUs overlapping totally or partially with estimated home range polygons. Our study, using GPS telemetry, highlights the complex spatial ecology of the brown bear in the Romanian Carpathians, with larger home range size than those estimated in other European brown bear populations and with daily movements that vary by season and within a large altitude range. Our study supports the implementation of brown bear monitoring at a regional scale, rather than focusing on county level GMUs as the monitoring unit.