Black bear recolonization patterns in a human-dominated landscape vary based on housing: New insights from spatially explicit density models

Evans, Michael J.; Rittenhouse, Tracy A. G.; Hawley, Jason E.; Rego, Paul W.

doi:10.1016/j.landurbplan.2017.01.009

Cited by 34 publications

(48 citation statements)

References 67 publications

(69 reference statements)

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“…Indeed, areas on the WNC with few bear detections and some of the lowest predicted densities have little or no hunting but a high density of heavily used recreational hiking and mountain biking trails. In areas where human presence is more pronounced and anthropogenic food rewards are high, such as residential or urban areas, bears are commonly attracted to human development (Sollmann et al , Evans et al ); however, such areas can become attractive sinks due to high levels of human‐caused mortality (Beckmann and Lackey , Lamb et al ).…”

Section: Discussionmentioning

confidence: 99%

Factors associated with black bear density and implications for management

2019

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Wildlife density estimates are important to accurately formulate population management objectives and understand the relationship between habitat characteristics and a species’ abundance. Despite advances in density and abundance estimation methods, management of common game species continues to be challenged by a lack of reliable population estimates. In Washington, USA, statewide American black bear (Ursus americanus) abundance estimates are predicated on density estimates derived from research in the 1970s and are hypothesized to be a function of precipitation and vegetation, with higher densities in western Washington. To evaluate current black bear density and landscape relationships in Washington, we conducted a 4‐year capture‐recapture study in 2 areas of the North Cascade Mountains using 2 detection methods, non‐invasive DNA collection and physical capture and deployment of global positioning system (GPS) collars. We integrated GPS telemetry from collared bears with spatial capture‐recapture (SCR) data and created a SCR‐resource selection model to estimate density as a function of spatial covariates and test the hypothesis that density is higher in areas with greater vegetative food resources. We captured and collared 118 bears 132 times and collected 7,863 hair samples at hair traps where we identified 537 bears from 1,237 detections via DNA. The most‐supported model in the western North Cascades depicted a negative relationship between black bear density and an index of human development. We estimated bear density at 20.1 bears/100 km2, but density varied from 13.5/100 km2 to 27.8 bears/100 km2 depending on degree of human development. The model best supported by the data in the eastern North Cascades estimated an average density of 19.2 bears/100 km2, which was positively correlated with primary productivity, with resulting density estimates ranging from 7.1/100 km2 to 33.6 bears/100 km2. The hypothesis that greater precipitation and associated vegetative production in western Washington supports greater bear density compared to eastern Washington was not supported by our data. In western Washington, empirically derived average density estimates (including cubs) were nearly 50% lower than managers expected prior to our research. In eastern Washington average black bear density was predominantly as expected, but localized areas of high primary productivity supported greater than anticipated bear densities. Our findings underscore the importance that black bear density is not likely uniform and management risk may be increased if an average density is applied at too large a scale. Disparities between expected and empirically derived bear density illustrate the need for more rigorous monitoring to understand processes that affect population numbers throughout the jurisdiction, and suggest that management plans may need to be reevaluated to determine if current harvest strategies are achieving population objectives. © 2019 The Wildlife Society.

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Section: Discussionmentioning

confidence: 99%

Factors associated with black bear density and implications for management

2019

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“…We use a black bear population in Connecticut (CT) for which we previously estimated densities across the established range using SCR, to test the performance of SC models estimating density using camera detections of unmarked individuals. SCR analyses using individual genetic identity from hair samples indicated differences in bear densities according to housing density, with peak bear densities occurring in areas with 6–50 houses/km 2 , and a latitudinal decrease in density from North to South (Evans, Hawley, Rego, & Rittenhouse, ). Estimated bear density across the study area ranged from 0 to 21.7 individuals/100 km 2 , providing a spectrum of values to which SC models could be validated.…”

Section: Methodsmentioning

confidence: 99%

Evaluating spatially explicit density estimates of unmarked wildlife detected by remote cameras

Evans

Rittenhouse

2018

Journal of Applied Ecology

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Remote cameras have become a promising, cost‐effective tool for monitoring wildlife populations. Yet, for species where individuals are indistinguishable, remote cameras’ ability to provide robust and precise density estimates has been limited without the use of invasive marking. Using the American black bear as a model species, we evaluated methods for estimating wildlife densities using remote camera detections of unmarked individuals against estimates from spatial capture–recapture (SCR) models using individual detections. We also tested the effect of incorporating varying proportions of marked individuals on model accuracy and precision. Spatial count (SC) models using unmarked individuals produced estimates of bear density within 0.6% of those from SCR. We extended SC models to incorporate variation in density as a function of land use/land cover, and identified identical relationships between variation in bear densities and housing density as obtained using SCR. Incorporating individual detection data from simultaneous non‐invasive genetic sampling lead to more precise, but biased estimates. Synthesis and applications. Our results identify contexts in which camera count data can be used as an alternative to spatial capture–recapture (SCR) when individual identification is prohibitive. Spatial count models provided an accurate, but less precise replication of spatial capture–recapture density estimates and may provide consistent insights into spatial variation in density. Mixed samples of camera counts and auxiliary individual detections are likely to be of limited use, but fitting spatial count models to populations with partial visual markings could improve their precision.

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“…Spatial genetic patterns indicated anthropogenic features changed dispersal processes, potentially affecting population demographics and implicating landscape heterogeneity as a driver of dispersal. Female philopatry was disrupted around increased development, and greater distances between parent–offspring pairs in more developed areas indicate that greater interspersion of unrelated individuals may contribute to elevated bear densities (Evans et al., ). We identified a positive association between intervening housing density and genetic similarity between females, indicating increased gene flow through development in both rural and developed contexts.…”

Section: Discussionmentioning

confidence: 99%

“…For forest cover, V max occurred at 1. For housing density, we set V max at 500 houses/km 2 , a value consistent with our previous research defining the relationship between bear density and development in CT (Evans et al., ) and knowledge of black bear behavior around urban areas (Beckmann & Berger, ; Johnson et al., ; Merkle, Krausman, Decesare, & Jonkel, ). We also considered each variable as potentially facilitating dispersal to account for greater dispersal through unfavorable habitat (i.e., compensatory movement Knowlton & Graham, ; Peterman, Connette, Semlitsch, & Eggert, ).…”

Section: Methodsmentioning

confidence: 99%

“…American black bears ( Ursus americanus ) are a prominent large carnivore occupying developed areas, and elevated bear densities in exurban relative to rural areas have recently been documented (Baruch‐Mordo et al., ; Evans et al., ; Johnson et al., ). However, inhabiting developed landscapes could alter the spatial genetic structure of bear populations in ways not yet understood.…”

Section: Introductionmentioning

confidence: 99%

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Spatial genetic patterns indicate mechanism and consequences of large carnivore cohabitation within development

Evans

Rittenhouse

Hawley

et al. 2018

Ecology and Evolution

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Patterns of human development are shifting from concentrated housing toward sprawled housing intermixed with natural land cover, and wildlife species increasingly persist in close proximity to housing, roads, and other anthropogenic features. These associations can alter population dynamics and evolutionary trajectories. Large carnivores increasingly occupy urban peripheries, yet the ecological consequences for populations established entirely within urban and exurban landscapes are largely unknown. We applied a spatial and landscape genetics approach, using noninvasively collected genetic data, to identify differences in black bear spatial genetic patterns across a rural‐to‐urban gradient and quantify how development affects spatial genetic processes. We quantified differences in black bear dispersal, spatial genetic structure, and migration between differing levels of development within a population primarily occupying areas with >6 houses/km2 in western Connecticut. Increased development disrupted spatial genetic structure, and we found an association between increased housing densities and longer dispersal. We also found evidence that roads limited gene flow among bears in more rural areas, yet had no effect among bears in more developed ones. These results suggest dispersal behavior is condition‐dependent and indicate the potential for landscapes intermixing development and natural land cover to facilitate shifts toward increased dispersal. These changes can affect patterns of range expansion and the phenotypic and genetic composition of surrounding populations. We found evidence that subpopulations occupying more developed landscapes may be sustained by male‐biased immigration, creating potentially detrimental demographic shifts.

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Black bear recolonization patterns in a human-dominated landscape vary based on housing: New insights from spatially explicit density models

Cited by 34 publications

References 67 publications

Factors associated with black bear density and implications for management

Factors associated with black bear density and implications for management

Evaluating spatially explicit density estimates of unmarked wildlife detected by remote cameras

Spatial genetic patterns indicate mechanism and consequences of large carnivore cohabitation within development

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