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Resident American black bear (Ursus americanus) density (a) and percent projected harvest (b) for bears in Wildlife Management Units (WMUs) in and around Algonquin Provincial Park (APP), Ontario, Canada, 2006-2014. In panel (a), shading indicates resident bear density (bears/100 km 2 ); labels on individual WMUs indicate the population size estimate. In panel (b), shading indicates projected harvest/resident bear population (%); labels indicate number of bears harvested (projected harvest).
Source publication
Protected areas may provide insufficient protection for carnivores such as bears (Ursidae) with large home ranges and extensive seasonal movements. Even in protected areas, harvest can be the main cause of mortality if parks are small or individuals live close to the boundary. At >7,600 km2, Algonquin Provincial Park (APP) is the largest protected...
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Infrequent, long-distance animal movements outside of typical home range areas provide useful insights into resource acquisition, gene flow, and disease transmission within the fields of conservation and wildlife management, yet understanding of these movements is still limited across taxa. To detect these extra-home range movements (EHRMs) in spat...
Citations
... We modified the 300-m cost surface of Pither et al. (2023) by adding a fifth lowest cost, which we assigned to natural areas within protected area boundaries under the assumption that these areas are less costly to move through than natural areas outside park boundaries (Spencer et al., 2010; Table 1). While we do not propose that the natural landscapes themselves would differ within vs outside park boundaries, we reasoned that regulation of various human activities, such as resource extraction, new hydro development, hunting, and recreation, within protected areas as well as traditional land use practices and stewardship within Indigenous Protected and Conserved Areas (IPCAs) can provide benefits through decreased disturbance and mortality, allowing wildlife to move more easily through protected and conserved areas (Fryxell et al., 2020;Hebblewhite & Whittington, 2020;Indigenous Circle of Experts, 2018;Obbard et al., 2017;Schuster et al., 2019). We also note that a similar approach was taken by Spencer et al. (2010) who weighted pixels in protected areas according to their degree of regulation. ...
It has been recognized that well-connected networks of protected areas are needed to halt the continued loss of global biodiversity. The recently signed Kunming-Montreal biodiversity agreement commits countries to protecting 30% of terrestrial lands in well-connected networks of protected areas by 2030. To meet these ambitious targets, land-use planners and conservation practitioners will require tools to identify areas important for connectivity and track future changes. In this study we present methods using circuit theoretic models with a subset of sentinel park nodes to evaluate connectivity for a protected areas network. We assigned a lower cost to natural areas within protected areas, under the assumption that animal movement within parks should be less costly given the regulation of activities. We found that by using mean pairwise effective resistance (MPER) as an indicator of overall network connectivity, we were able to detect changes in a parks network in response to simulated land-use changes. As expected, MPER increased with the addition of high-cost developments and decreased with the addition of new, low-cost protected areas. We tested our sentinel node method by evaluating connectivity for the protected area network in the province of Ontario, Canada. We also calculated a node isolation index, which highlighted differences in protected area connectivity between the north and the south of the province. Our method can help provide protected areas ecologists and planners with baseline estimates of connectivity for a given protected area network and an indicator that can be used to track changes in connectivity in the future.
... areas alone may be insufficient in sustaining viable populations of such species (Obbard et al., 2017;Nayeri et al., 2022;Madadi et al., 2023). ...
Human encroachment in natural habitats and consequent landscape modifications pose significant threats to animal populations, particularly endangered species. Therefore, studying the factors that determine the spatial distribution of large carnivores, including those at risk, holds great significance in developing effective conservation strategies. Among the most endangered bear populations worldwide, the conservation of the brown bear Ursus arctos population in the Central Zagros Mountains (southwestern Iran), which represents the species’ southernmost geographical range, is currently facing serious challenges. However, little is known about the species’ geographical range and the critical factors affecting its distribution in this area. Here, we employed a modelling approach to estimate the geographical distribution of this brown bear population and identify the primary landscape features that contribute to the species’ distribution. Our analysis revealed the following findings: (1) about 45% of the study area comprises suitable habitat for brown bears; (2) main factors influencing bear distribution, along with their respective contributions, are (a) distance to conservation areas and prohibited hunting areas (CAs/PHAs; 33.7%), (b) maximum temperature during the warmest month (21.6%), (c) landscape roughness (14.8%), (d) forest density (11.2%) and (e) mean annul precipitation (10.6%); and (3) roughly 69% the predicted suitable habitats exist outside CAs/PHAs. This highlights the importance of considering areas beyond CAs/PHAs in future conservation strategies, were the connectivity among forest patches is crucial for bear survival. The recent escalation of human activities, such as the harvesting of natural resources (e.g., medicinal and aromatic plants, fruits and honey), orchard and agricultural development, overgrazing of livestock, and the construction of water transfer infrastructures from the mountains to downstream regions, raises significant concerns for bear conservation in the study area. These activities contribute to landscape changes and have the potential to escalate conflicts between local communities and bears. Our findings highlight opportunities for designating new areas for brown bear habitat conservation and for promoting landscape connectivity.
... This is also supported by Mohammadi, Almasieh, Nayeri, et al. (2021) who showed that ~ 80 % of the brown bear distribution range is outside of PAs in Iran. These results clearly show the importance of conservation of bears and other large carnivores in a human-dominated landscape in Iran (Chapron et al., 2014), as many PAs are relatively small to contain viable populations of such species (Obbard et al., 2017;Mohammadi, Almasieh, Nayeri, et al., 2021). ...
Large carnivores’ far ranging habits and their requirements for wide areas often led them to move into unprotected lands, making them especially vulnerable to various human threats. Therefore, it is crucial to better understand their mortality characteristics and potential threats so to help guide conservation efforts. Brown bear is a protected species in Iran, however, knowledge on its population structure and causes of mortality are sparse. The main objective of this study was to understand the causes and spatio-temporal patterns of brown bear mortality in Iran. We carried out a systematic survey of internet media sources to answer (1) the mortality of which age and sex group is reported in the media; (2) what are the most common causes of mortality; (3) what are the temporal and spatial patterns of brown bear mortality?. Overall, we found 135 mortalities of brown bears in Iran from 2004-2019. Our findings showed that 84% of mortalities were related to anthropogenic causes and being shot (59%) was the most common cause followed by vehicle collisions (18.7%). Only 2% of reported mortalities were due to natural causes, and no information on the causes of mortality was available for 14%. We further found no differences in the sex distribution of bears killed, but adults (68%) were more commonly killed than subadults (22%); and age was unknown in 9% of mortalities. Most mortalities (75%) were reported in summer and autumn. We found that the number of bear mortality increased with increasing elevation, road density, proportion of forest cover, and that it was higher in areas with a higher proportion of protected areas (PA). However, most reported mortality cases were found outside of PAs. The main takeaway messages from our study are that the conservation of large carnivores in Iran must occur in co-existence with humans in a human-dominated landscape. It is also essential to obtain reliable data on population structure as well as more data on mortality rates and causes. We propose, among other conservation actions, the establishment of a central database for the systematic collection of data on human-carnivore conflicts as well as a compensation scheme for reimbursement of damages by large carnivores.
... Over much of the northeastern portion of their range, American black bears are only active within stable home ranges for a matter of weeks before and during the breeding season in spring and early summer, after which they make long distance migrations to patchily distributed, seasonally available food crops, returning to their breeding ranges to den (Noyce & Garshelis, 2011;Obbard et al., 2017). In Ontario, Canada, black bears are sampled during the breeding season to meet the SECR assumption that bears occupy home ranges during sampling (Howe et al., 2013;Obbard et al., 2010), but most weight gain (which is critical to successful reproduction) and most harvest mortality occur in late summer and autumn when bears are traveling widely; harvest data are summarized within management units and bears sampled in one unit are likely to be harvested in a different unit (e.g., Obbard et al., 2017). ...
... Over much of the northeastern portion of their range, American black bears are only active within stable home ranges for a matter of weeks before and during the breeding season in spring and early summer, after which they make long distance migrations to patchily distributed, seasonally available food crops, returning to their breeding ranges to den (Noyce & Garshelis, 2011;Obbard et al., 2017). In Ontario, Canada, black bears are sampled during the breeding season to meet the SECR assumption that bears occupy home ranges during sampling (Howe et al., 2013;Obbard et al., 2010), but most weight gain (which is critical to successful reproduction) and most harvest mortality occur in late summer and autumn when bears are traveling widely; harvest data are summarized within management units and bears sampled in one unit are likely to be harvested in a different unit (e.g., Obbard et al., 2017). Therefore, spatial covariates describing habitat productivity and harvest pressure are expected to be poor predictors of local bear densities during sampling. ...
Information about how animal abundance varies across landscapes is needed to inform management action but is costly and time‐consuming to obtain; surveys of a single population distributed over a large area can take years to complete. Surveys employing small, spatially replicated sampling units improve efficiency, but statistical estimators rely on assumptions that constrain survey design or become less reasonable as larger areas are sampled. Efficient methods that avoid assumptions about similarity of detectability or density among replicates are therefore appealing. Using simulations and data from >3500 black bears sampled on 73 independent study areas in Ontario, Canada, we (1) quantified bias induced by unmodeled spatial heterogeneity in detectability and density; (2) evaluated novel, design‐based estimators of average density across replicate study areas; and (3) evaluated two estimators of the variance of average density across study areas: an analytic estimator that assumed an underlying homogeneous spatial Poisson point process for the distribution of animals' activity centers, and an empirical estimator of variance across study areas. In simulations where detectability varied in space, assuming spatially constant detectability yielded density estimates that were negatively biased by 20% to 30%; estimating local detectability and density from local data and treating study areas as independent, equal replicates when estimating average density across study areas using the design‐based estimator yielded unbiased estimates at local and landscape scales. Similarly, detectability of black bears varied among study areas and estimates of bear density at landscape scales were higher when no information was shared across study areas when estimating detectability. This approach also maximized precision (relative SEs of estimates of average black bear density ranged from 7% to 18%) and computational efficiency. In simulations, the analytic variance estimator was robust to threefold variation in local densities but the empirical estimator performed poorly. Conducting multiple, similar SECR surveys and treating them as independent replicates during analyses allowed us to efficiently estimate density at multiple scales and extents while avoiding biases caused by pooling spatially heterogeneous data. This approach enables researchers to address a wide range of ecological or management‐related questions and is applicable with most types of SECR data.
... We attached a single strand of barbed-wire approximately 50 centimeters above the ground. We assumed this height would avoid (or minimize) collecting hair from animals <two years old because morphometric data from live-trapping studies in Ontario showed that very few yearling bears reached 50 cm at shoulder height (Obbard et al., 2017;Obbard & Howe, 2008). Thus, we consider our density estimates specific to bears aged ≥ 2 years. ...
Landscape structure affects animal movement. Differences between landscapes may induce heterogeneity in home range size and movement rates among individuals within a population. These types of heterogeneity can cause bias when estimating population size or density and are seldom considered during analyses. Individual heterogeneity, attributable to unknown or unobserved covariates, is often modelled using latent mixture distributions, but these are demanding of data, and abundance estimates are sensitive to the parameters of the mixture distribution. A recent extension of spatially explicit capture-recapture models allows landscape structure to be modelled explicitly by incorporating landscape connectivity using non-Euclidean least-cost paths, improving inference, especially in highly structured (riparian & mountainous) landscapes. Our objective was to investigate whether these novel models could improve inference about black bear ( Ursus americanus ) density. We fit spatially explicit capture-recapture models with standard and complex structures to black bear data from 51 separate study areas. We found that non-Euclidean models were supported in over half of our study areas. Associated density estimates were higher and less precise than those from simple models and only slightly more precise than those from finite mixture models. Estimates were sensitive to the scale (pixel resolution) at which least-cost paths were calculated, but there was no consistent pattern across covariates or resolutions. Our results indicate that negative bias associated with ignoring heterogeneity is potentially severe. However, the most popular method for dealing with this heterogeneity (finite mixtures) yielded potentially unreliable point estimates of abundance that may not be comparable across surveys, even in data sets with 136–350 total detections, 3–5 detections per individual, 97–283 recaptures, and 80–254 spatial recaptures. In these same study areas with high sample sizes, we expected that landscape features would not severely constrain animal movements and modelling non-Euclidian distance would not consistently improve inference. Our results suggest caution in applying non-Euclidean SCR models when there is no clear landscape covariate that is known to strongly influence the movement of the focal species, and in applying finite mixture models except when abundant data are available.
... The role of harvest regulations on anthropogenic mortality can be especially complex for wide-ranging carnivores inhabiting expansive areas that constitute a matrix of varying hunting regulations (Obbard et al., 2017). ...
Understanding the types and magnitude of human-caused mortality is essential for maintaining viable large carnivore populations. We used a database of cause-specific mortality to examine how hunting regulations and landscape configurations influenced human-caused mortality of North American gray wolves (Canis lupus). Our dataset included 21 studies that monitored the fates of 3564 wolves and reported 1442 mortalities. Human-caused mortality accounted for 61% of mortality overall, with 23% due to illegal harvest, 16% due to legal harvest, and 12% the result of management removal. The overall proportion of anthropogenic wolf mortality was lowest in areas with an open hunting season compared to areas with a closed hunting season or mixed hunting regulations, suggesting that harvest mortality was neither fully additive nor compensatory. Proportion of mortality from management removal was reduced in areas with an open hunting season, suggesting that legal harvest may reduce human-wolf conflicts or alternatively that areas with legal harvest have less potential for management removals (e.g., less livestock depredation). Proportion of natural habitat was negatively correlated with the proportion of anthropogenic and illegal harvest mortality. Additionally, the proportion of mortality due to illegal harvest increased with greater natural habitat fragmentation. The observed association between large patches of natural habitat and reductions in several sources of anthro-pogenic wolf mortality reiterate the importance of habitat preservation to maintain wolf populations. Furthermore, effective management of wolf populations via implementation of harvest may reduce conflict with humans. Effective wolf conservation will depend on holistic strategies that integrate ecological and socioeconomic factors to facilitate their long-term coexistence with humans. K E Y W O R D S Canis lupus, carnivore, cause-specific mortality, meta-analysis, telemetry
... In large carnivores, such as the American black bear (Ursus americanus Pallas, 1780), the dispersal process is mostly male biased while in females there is marked philopatry, based on residence and site fidelity (Costello 2010). This results in young females tending to overlap in their home ranges with their mother or their offspring, whereas young males have higher rates of dispersal and are more susceptible to mortality by natural or anthropogenic factors (Rogers 1987;Costello 2010;Obbard et al. 2017). ...
Context
Black bear connectivity studies are scarce in the southern distribution where the species is endangered. The identification of corridors is a strategy to promote conservation in human-modified landscapes.
Objectives
Assess and validate long-distance corridors in the southern black bear distribution using resistance models, occurrence records, and radio-telemetry of an individual that dispersed between the Sierras Madres of Mexico.
Methods
We acquired black bear occurrence records from several sources and telemetry records from one dispersal individual in northern Mexico. We generated ensemble habitat suitability models and resistance landscape surfaces to generate cumulative resistant kernel and least-cost paths to identify connectivity core areas and corridors of importance through Natural Protected Areas. Finally, we assessed long-distance corridors.
Results
We developed three habitat suitability models for black bears southern range; one matches the current distribution of the species. When including radio-tracking records, the landscape resistance is reduced to arid sites with low habitat suitability. We used least resistance connectivity surfaces to merge subpopulations within each Sierra Madre. The long-distance corridor models indicate narrow routes that require individuals with plastic behavioral dispersal capacity. Almost 20% of the connectivity core areas are within Natural Protected Areas. These are the first large-scale corridors using resistance layers in the southern black bear distribution.
Conclusions
Corridors can be functional for a range of temperate and dry habitat species. Landscape connectivity models should include the monitoring of dispersal individuals to identify the plasticity of organisms and the tangible barriers for them.
... The meta-analysis revealed that harvest is a large source of anthropogenic black bear mortality, even for bears collared in areas where there is no legal harvest. Larger-bodied species such as black bears are particularly prone to this occurrence due to their wide-ranging movement, which often take them outside non-harvest areas 54 . Selective hunting has the potential to affect population dynamics 9 , and evolutionary processes; though strong evidence of artificial selection has only been found in mountain ungulates 55 . ...
With efforts to restore large mammal populations following extirpations, it is vital to quantify how they are impacted by human activities and gain insights into population dynamics in relation to conservation goals. Our objective was to characterize cause-specific mortality of black bears (Ursus americanus) throughout their range. We first quantified cause-specific mortality for 247 black bears in one harvested and two non-harvested populations. We then simulated a small recolonizing population with and without anthropogenic mortality. Lastly, we conducted a meta-analysis of all published black bear mortality studies throughout North America (31 studies of 2630 bears). We found anthropogenic mortality was greater than natural mortality, non-harvest anthropogenic mortality (e.g. poaching, defense of property, etc.) was greater in non-harvested populations, and harvesting was one of the major causes of mortality for bears throughout their range. Our simulation indicated that removing anthropogenic mortality increased population size by an average of 23% in 15 years. We demonstrated that bears are exposed to high levels of anthropogenic mortality, and the potential for human activities to slow population growth in expanding populations. Management and conservation of wide-ranging mammals will depend on holistic strategies that integrate ecological factors with socio-economic issues to achieve successful conservation and coexistence.
... Harvest and mortality rates from long term studies are available for some locations in Ontario: North Bay (1969-1981, Chapleau (1989Chapleau ( -2000, Bruce Peninsula (1998)(1999)(2000)(2001)(2002)(2003), and Algonquin Park (2004-2014) (Kolenosky 1986(Kolenosky , 1990Howe et al. 2007;Obbard and Howe 2008;Obbard et al. 2017). However, data for hunted populations in the Great Lakes-St. ...
Monitoring abundance of black bears (Ursus americanus) is critical, as this information is required to inform sustainable management of a harvested black bear population. In Ontario, black bears have been monitored using a combination of direct and indirect measures, including determining if harvest is sustainable by examining annual harvest statistics; estimating survival, mortality, and abundance through telemetry studies; modelling population viability using the RISKMAN program; and estimating abundance and density through genetic capture-recapture methods.
Many jurisdictions in the United States reconstruct the hunted population of black bears using harvest and age-at-harvest data to estimate population size and trend. Our objectives were to: 1) Determine whether population reconstruction models could be used as an alternative to direct measures of population size, such as capture-recapture methods 2) Summarize the main data requirements and assumptions common to many population reconstruction models 3) Determine the extent to which those requirements can be met by data available in Ontario
We also provide recommendations to improve the reliability of black bear harvest and age-at-harvest data, which would be required to implement population reconstruction as a viable management tool in Ontario.
Population reconstruction is based on an estimate of the number and age distribution of harvested animals, as well as other auxiliary data, such as hunter effort, to determine the original size, age distribution, and recruitment rate of the harvested population of a wildlife species. To calculate total population size, annual mortality due to other causes must also be known or estimated. We present and discuss six methods of population reconstruction, and describe the data and assumptions required to run the models. We conclude that no population reconstruction model can replace direct estimates of abundance, but such models can provide managers with accurate, important population trend information between years of other surveys.
For accurate and precise population estimates via population reconstruction, harvest and effort data must be complete, accurate, and unbiased. Age-at-harvest data from annual tooth submissions must be accurate and representative of the harvested population. Independently collected auxiliary data, such as mortality or abundance, should be available at regular intervals and be representative of the bear population. Finally, immigration and emigration should be negligible, and harvest mortality should be the main cause of death. If other causes of death are common, the rate of that mortality should either be constant and known, or measured annually for each region.
Ontario harvest and age-at-harvest data for 1985 to 2014 violated the main assumptions of population reconstruction.
* Harvest and effort surveys for non-residents were completed by most non-resident hunters; therefore, they can be considered to be accurate. However, corresponding data for resident hunters were likely more biased through time and across space. Resident hunters may hunt in any wildlife management unit (WMU) with an open season, so if spatial biases in the data exist, we could not account for them because we did not know where non-replying hunters hunted. Harvest and effort data were biased to hunters who replied voluntarily and likely to those who were successful.
* Survey methods changed through time, making reported success rates and projected annual bear harvests inconsistent through time.
*Total bear harvest was estimated using a provincial correction factor instead of a local factor, potentially biasing WMU-specific harvest estimates.
* Non-resident hunters submitted an adequate sample of bear teeth for ageing, but resident hunters did not. As a result, it is unlikely that the sample of age-at-harvest data from residents was representative of the harvested population.
* In some WMUs, especially those surrounding protected areas, seasonal immigration may significantly outweigh seasonal emigration during the hunting season in Ontario (Obbard et al. 2017), which introduces differential biases in the population estimate.
* Harvest mortality is the main cause of death for black bears in Ontario, but many bears die from other natural and human-induced causes. We have poor estimates of these mortalities. Therefore, estimated population size can be viewed only as an indicator of total population size. Trends in the proportion of mortality due to factors other than hunting, which may occur over time, could bias population estimates.
* Independent bear abundance estimates from regularly conducted telemetry or capture-recapture studies (every 5 to 10 years) are necessary to calibrate estimates from population reconstruction. Currently, vital rate information for bears in Ontario is dated and may not be available at appropriate spatial scales.
If population reconstruction is to be considered a viable method for estimating population size and population trends in Ontario in the future, consistent survey methods, greater compliance with mandatory reporting, and higher rates of tooth submission are needed. Population reconstruction should not be used in isolation to obtain accurate abundance estimates. Other jurisdictions conduct independent abundance estimates using alternate methods every 5 to 10 years to confirm and correct population reconstruction trends and estimates. Therefore, Ontario requires upto-date vital rate information from capture-recapture programs, such as collaring (physical capture-recapture) or barbed-wire hair-trap (genetic capture-recapture). Without these auxiliary data, population reconstruction models may produce trends or estimates that are unrealistic or incorrect. Ontario manages bear populations at the WMU scale; therefore, accurate and precise data are required at that scale to provide meaningful estimates. We present specific recommendations to improve data collection and meet the assumptions of the model. When assumptions and data requirements are met, population reconstruction could be a valuable tool for local bear managers, especially as population estimates are available each year, allowing managers to respond immediately to local problems or socioeconomic opportunities.
Reliable estimates of population density are fundamental for managing and conserving wildlife. Spatially explicit capture–recapture (SECR) models in combination with information‐theoretic model selection criteria are frequently used to estimate population density. Variation in density and detectability is inevitable and, when unmodeled, can lead to erroneous estimates. Despite this knowledge, the performance of SECR models and information‐theoretic criteria remain relatively untested for populations with realistic levels of variation in density and detectability. We addressed this issue using simulations of American black bear ( Ursus americanus ) populations with variable density and detectability between sexes and across study areas. We first assessed the reliability of Akaike information criterion adjusted for small sample sizes (AIC c ) to correctly identify the true data generating model or a good approximating model. We then assessed the bias, accuracy, and precision of density estimates when such a model was selected or not. We demonstrated that unmodeled heterogeneity in detection and, more importantly, density can lead to pronounced bias. However, when a good approximating model is included in the candidate set, models with lower AIC c included important forms of variation and yielded accurate estimates. We encourage researchers and practitioners to consider the impact of unmodeled variation in SECR models when making inferences and to strive to include covariates likely to be the most influential based on the species biology and ecology in candidate model sets. Doing so can improve the robustness of wildlife density estimation methods that can be leveraged to make more sound conservation and management decisions.
