Humans are responsible for over a quarter of all wildlife mortality events across the globe. The pressure this puts on wildlife populations contributes to the decline of many at-risk species. To ...minimize human-caused mortality and reverse population declines in species across the world, we first need to know where these events are happening or likely to occur since managers and public agencies often have limited resources to devote to a problem. As such, our objective was to develop a modeling approach to delineate human-caused wildlife mortality hotspots in regions with limited data. We used internet search engines and national media to collect data on brown bear (Ursus arctos) mortality events in Iran from 2004 to 2019. We then developed a spatially-explicit Maximum Entropy (MaxEnt) model using anthropogenic and environmental variables to predict the probability of human-caused brown bear mortality. We were able to delineate 7000 km2 as human-caused mortality hotspots, along with the geographical locations of those hotspots. This provides information that can help identify where critical conflict mitigation efforts need to be implemented to reduce the potential for human-caused wildlife mortality. However, more targeted studies such as surveys of local people will be needed inside hotspots identified with this methodology to assess the attitudes of humans toward different wildlife species, informing the specific mitigation actions that will need to be made. Finally, we suggest that media data can be used to identify these hotspots in regions where systematic data is lacking.
Environmental contaminants like arsenic (As), cadmium (Cd), mercury (Hg) or lead (Pb) may disrupt hypothalamic–pituitary–adrenal (HPA) and hypothalamic-pituitary-gonadal (HPG) axes due to their ...endocrine toxicity potential. Resulting long-term physiological stress or adverse effects on wildlife reproduction and ontogeny may cause detrimental effects at the individual and population levels. However, data on environmental metal(loid)sʼ impact on reproductive and stress hormones in wildlife, especially large terrestrial carnivores, are scarce. Hair cortisol, progesterone and testosterone concentrations were quantified and modelled with hair As, Cd, total Hg, Pb, biological, environmental and sampling factors to test for potential effects in free-ranging brown bears (Ursus arctos) from Croatia (N = 46) and Poland (N = 27). Testosterone in males (N = 48) and females (N = 25) showed positive associations with Hg and an interaction between Cd and Pb, but a negative association with interaction between age and Pb. Higher testosterone was found in hair during its growth phase compared to quiescent phase. Body condition index was negatively associated with hair cortisol and positively associated with hair progesterone. Year and conditions of sampling were important for cortisol variation, while maturity stage for progesterone variation (lower concentrations in cubs and yearlings compared to subadult and adult bears). These findings suggest that environmental levels of Cd, Hg and Pb might influence the HPG axis in brown bears. Hair was shown to be a reliable non-invasive sample for investigating hormonal fluctuations in wildlife while addressing individual and sampling specificities.
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•First effect study on hormonal association with metal (loid)s in European brown bear.•Hair testosterone was associated with potentially toxic metal (loid) levels.•Year and conditions of sampling important for cortisol variation in hair.•Maturity stage important for progesterone variation (lowest in cubs & yearlings).
As Earth faces a crisis of biodiversity loss, reintroduction of imperiled species has become an important tool toward mitigating extirpation. Current habitat quality for a reintroduced species may ...change dramatically under future climate scenarios, undermining or supporting species conservation efforts. Models designed to understand such change must consider the niche plasticity of a species to assess the costs and benefits of reintroduction. We integrated spatially-explicit individual-based population models with a dynamic vegetation model, using combinations of global climate models and greenhouse gas scenarios to better understand potential future carrying capacity for grizzly bears in the North Cascades Ecosystem (NCE). We estimated the ecosystem could support a grizzly bear population under several climate change scenarios through the 2080s, with the amount of high quality habitat increasing across all models, scenarios, and time periods, as compared to current conditions. Projected future habitat quality remained consistent or increased slightly along the eastern portion of the ecosystem, and increased along its central and western portions, for a net increase in high quality habitat through time. At the most plausible female home range size of 280 km2, we estimated carrying capacity would increase from a baseline of 139 female bears to 241–289 female bears. Estimated changes in habitat over time could increase grizzly bear density to 20–22 bears/1000 km2 (males and females) from the previous estimate of 17 bears/1000 km2. Species with broad ecological niches (i.e., generalists), such as grizzly bears, may be especially good candidates for reintroduction efforts in some ecosystems. Our integrated model structure provides an innovative tool for advancing reintroduction initiatives while considering some long-term risks for species.
Connectivity, in the sense of the persistence of movements between habitat patches, is key to maintain endangered populations and has to be evaluated in management plans. In practice, connectivity is ...difficult to quantify especially for rare and elusive species. Here, we use spatial capture-recapture (SCR) models with an ecological detection distance to identify barriers to movement. We focused on the transnational critically endangered Pyrenean brown bear (Ursus arctos) population, which is distributed over Spain, France and Andorra and is divided into two main cores areas following translocations. We integrate structured monitoring from camera traps and hair snags with opportunistic data gathered after depredation events. While structured monitoring focuses on areas of regular bear presence, the integration of opportunistic data allows us to obtain information in a wider range of habitat, which is especially important for ecological inference. By estimating a resistance parameter from encounter data, we show that the road network impedes movements, leading to smaller home ranges with increasing road density. Although the quantitative effect of roads is context-dependent (i.e. varying according to landscape configuration), our model predicts that a brown bear with a home range located in an area with relatively high road density (8.29 km/km2) has a home range size reduced by 1.4-fold for males and 1.6-fold for females compared to a brown bear with a home range located in an area with low road density (1.38 km/km2). When assessing connectivity, spatial capture-recapture modeling offers an alternative to the use of experts' opinion when telemetry data are not available.
Until recently, the Bulgarian bear population (
L.) was considered one of the significant ones in Europe and one of the few with more than 500 bears. While the numbers of some neighboring populations ...may be increasing, the Bulgarian population has been on a downward trend since the early 1990s. The probable numbers of the species at the end of the 1980s was about 700-750 individuals. Calculations based on field data from national monitoring and statistical analysis show probable numbers in Bulgaria in 2020 of about 500 individuals (data for the autumn state). This decline is mostly related to poaching due to weaker control activity, the reduction of forest areas and habitat fragmentation. The preservation of the Bulgarian population, which, together with the other Balkan populations and the Apennine bear, has a unique gene pool, is particularly important from the point of view of preserving the biodiversity of the species in Europe.
There is a growing recognition of the role of individual variation in patterns emerging at higher levels of biological organization. Despite the importance of the temporal configuration of ecological ...processes and patterns, intraspecific individual variation in diel activity patterns is almost never accounted for in behavioral studies at the population level. We used individual-based monitoring data from 98 GPS-collared brown bears in Scandinavia to estimate diel activity patterns before the fall hunting season. We extracted 7 activity measures related to timing and regularity of activity from individual activity profiles. We then used multivariate analysis to test for the existence of distinct activity tactics and their environmental determinants, followed by generalized linear regression to estimate the extent of within-individual repeatability of activity tactics. We detected 4 distinct activity tactics, with a high degree of individual fidelity to a given tactic. Demographic factors, availability of key foraging habitat, and human disturbance were important determinants of activity tactics. Younger individuals and those with higher bear and road densities within their home range were more nocturnal and more likely to rest during the day. Good foraging habitat and increasing age led to more diurnal activity patterns and nocturnal resting periods. We did not find evidence of diel activity tactics influencing survival during the subsequent hunting season. We conclude that individual variation in activity deserves greater attention than it currently receives, as it may help account for individual heterogeneity in fitness and could facilitate within-population niche partitioning that can have population- or community-level consequences.
When estimating population density from data collected on non-invasive detector arrays, recently developed spatial capture-recapture (SCR) models present an advance over non-spatial models by ...accounting for individual movement. While these models should be more robust to changes in trapping designs, they have not been well tested. Here we investigate how the spatial arrangement and size of the trapping array influence parameter estimates for SCR models. We analysed black bear data collected with 123 hair snares with an SCR model accounting for differences in detection and movement between sexes and across the trapping occasions. To see how the size of the trap array and trap dispersion influence parameter estimates, we repeated analysis for data from subsets of traps: 50% chosen at random, 50% in the centre of the array and 20% in the South of the array. Additionally, we simulated and analysed data under a suite of trap designs and home range sizes. In the black bear study, we found that results were similar across trap arrays, except when only 20% of the array was used. Black bear density was approximately 10 individuals per 100 km(2). Our simulation study showed that SCR models performed well as long as the extent of the trap array was similar to or larger than the extent of individual movement during the study period, and movement was at least half the distance between traps. SCR models performed well across a range of spatial trap setups and animal movements. Contrary to non-spatial capture-recapture models, they do not require the trapping grid to cover an area several times the average home range of the studied species. This renders SCR models more appropriate for the study of wide-ranging mammals and more flexible to design studies targeting multiple species.
The expansion of large carnivores across Europe is posing a challenge to their conservation. Since success with conservation may depend significantly on human behavior, knowledge of certain ...behaviors’ emergence and all the factors that affect them are crucial. The present study included 534 students who were divided into a comparison group (n = 317) and a treatment group (n = 217) consisting of 309 lower secondary (LS, MAge = 12.2, SD = 0.94) and 225 upper secondary (US, n = 225, MAge = 16.5, SD = 0.99) school students. We assessed their attitudes to and knowledge of brown bears. An indirect effect of the workshops (instructions) is also described. Sociodemographic factors, such as gender and seeing a bear in nature, significantly influenced the students’ attitudes and knowledge. Residence, owning a dog, having a hunter in the family, breeding livestock and visiting a zoo had a smaller effect on the students’ attitudes and knowledge. The results thus show that greater knowledge is correlated with proconservation attitudes, and partly with reduction of fear. Therefore, future conservation and management should employ strong communication, especially education activities based on direct experiences and carefully designed information regarding species and socio-scientific issues.
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