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Bader, M. and Sieracki, P. (2022). Grizzly Bear Denning Habitat and Demographic Connectivity in Northern Idaho and Western Montana. Northwestern Naturalist, 103(3), 209 – 225.

This study focuses on mapping potential denning habitat in areas key to grizzly bear population connectivity. A key model for grizzlies is the demographic model, which focuses on assessing protected habitat where there are resident female grizzlies. Identifying potential grizzly bear habitat involves looking for areas with year-round habitat, including denning areas. Using den site location data from USFWS in ArcGIS and LANDFIRE EVT, ranges and means of slope, elevation, and aspect of denning sites as well as vegetative cover were calculated. Distance to roads, ski areas, and water were also evaluated for denning sites. Based on findings of prevalence of adequate denning habitat and year-round habitat, the study suggests expanding the Bitterroot Recovery Area northward in western Montana and eastern Idaho. In addition to determining potential areas for expansion, this study also highlights areas that pose the largest threats to connectivity, such as the I-90 corridor which cuts across Montana as well as US Highway 93 from Whitefish to Darby, Montana. Additional studies on key crossing areas would be useful for determining wildlife crossings.

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Bjornlie, D., Thompson, D., Haroldson, M., Schwartz, C., Gunther, K., Cain, S., Tyers, D., Frey, K., and Aber, B. (2014). Methods to Estimate Distribution and Range Extent of Grizzly Bears in the Greater Yellowstone Ecosystem. Wildlife Society Bulletin, 38(1), 182 – 187. https://doi.org/10.1002/wsb.368

Provides an updated method of determining grizzly bear distribution. Previous methodologies relied on fixed-kernel density estimators. This study provided an easier technique to include all verified grizzly observations. The analysis begins by mapping grizzly locations from verified sources from 1990 to 2004 and 1990 to 2010 onto a 3 x 3 kilometer grid and then using kriging in ArcGIS to determine a predicted population distribution. Population distribution increased 38% from 2004 to 2010, primarily to the north and south of the previously measured range. Much of this expansion is from improved habitat connectivity in previously unoccupied areas as the grizzly population has grown. Prior analysis only utilized radiotelemetry via collared bears, but the new methodology includes radiotelemetry, conflicts, mortalities, DNA samples, and locations of observations or tracks by professionals. Providing up-to-date species distribution is key for grizzlies, which continue to face delisting and determination of distinct population segments. The study determined expansion northward and southward, but posits that northward expansion, and thus connectivity with the Northern Continental Divide Ecosystem is unlikely due to I-90. However, grizzlies are more frequently sighted in the northern areas of the Wind River Range in Wyoming, indicating the potential for the bears to continue southern expansion.

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Bjornlie, D., Van Manen, F., Ebinger, M., Haroldson, M., Thompson, D., and Costello, C. (2014). Whitebark Pine, Population Density, and Home-Range Size of Grizzly Bears in the Greater Yellowstone Ecosystem. PLoS ONE, 9(2), e88160. https://doi.org/10.1371/journal.pone.0088160

Evaluates the impact of declining Whitebark Pine trees in the Greater Yellowstone Ecosystem on grizzly bear population density and food sources. Declines in Whitebark Pines, which is a key food source for grizzlies in the fall, has yielded a slower population growth rate. Determined that during Whitebark Pine declines, individual grizzly bear home range sizes did not increase as was initially suspected as bears would try to find additional food sources. Mapped Whitebark Pine in the Greater Yellowstone Ecosystem and tracked grizzlies using flights to evaluate home ranges using various mapping models. Created population density map using a combination of flight sightings with GPS locations of tagged bears. It was determined that female grizzly bear home range is constrained by population density, i.e., with a dense population, female grizzly bears will have smaller home ranges, regardless of Whitebark Pine abundance or lack thereof. This is relevant information for grizzly bear connectivity mapping as growing grizzly populations in constrained spaces will yield denser populations and thus smaller home ranges unless the grizzly bears are able to disperse to new areas.

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Craighead, L. and Olenicki, T. (2005). Modeling Highway Impacts Related to Grizzly Bear Core, Living, and Connectivity Habitat in Idaho, Montana, and Wyoming Using a Two-Scale Approach. UC Davis: Road Ecology Center. Wildlife Impacts and Conservation Solutions. https://search.library.oregonstate.edu/permalink/01ALLIANCE_OSU/1ffs2e1/cdi_cdl_escholarship_oai_escholarship_org_ark_13030_qt88d4r0t8

Identifies roads that bisect grizzly habitat, categorizing the area through which the road travels as core (sufficient for a population), connectivity (sufficient for movement between core areas), or living (sufficient for an individual) habitat using GIS.  Provides distance measurements for the length of each road and its habitat type. This study provides a repeatable methodology of performing coarse-scale analysis of habitat type and road impact, and then determining which roads warrant finer scale analysis. In fine-scale analysis, curvature and slope of the road, highway features, buildings, etc. are evaluated to determine high risk areas for wildlife. Wildlife-vehicle collision data is useful for determining areas where wildlife is most likely to attempt to cross a road. This data can be used to determine where wildlife crossings may be most impactful.

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Cushman, S., McKelvey, K., and Schwartz, M. (2008). Use of Empirically Derived Source-Destination Models to Map Regional Conservation Corridors. Conservation Biology, 23(2), 368-376. https://doi.org/10.1111/j.1523-1739.2008.01111.x

Criticizes mainstream focus on narrow connectivity corridors and instead offers an alternative to focus on resistance maps and least-cost path analysis. Determines key corridors and impediments to black bear habitat connectivity from Canada to Yellowstone National Park. Argues resistance should be defined as areas with cumulative and continuous low resistance that connect to high population density areas. Prior connectivity modeling relied on expert opinion to determine resistance, but this is unvalidated by on-the-ground analysis. Using largely artificial resistance data does not produce accurate models to determine habitat usage and connectivity. Combines species-specific resistance data with least-cost paths to determine potential corridors. Most corridors largely used public lands. The study also determined various types of impediments to wildlife movement, including gaps in public lands, highways, and development.

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Dilkina, B., Houtman, R., Gomes, C., Montgomery, C., McKelvey, K., et al. (2017). Trade-offs and Efficiencies in Optimal Budget-Constrained Multispecies Corridor Networks. Conservation Biology, 31(1), 192-202. https://doi.org/10.1111/cobi.12814

Highlights the importance of wildlife corridors in effective conservation and some of the challenges associated with determining corridors. Outlines the typical use of GIS leveraging resistant surfaces and recent focus on areas with overlapping resistance for various species. This study worked to design a way to optimize corridors that are budget-constrained and can function for multiple species, allowing for weighing of different species based on priorities. By analyzing the cumulative resistance of each potential pathway connecting two protected areas, in conjunction with a cost analysis, the authors could determine which corridor was financially feasible and ecologically impactful. This study determined a potential corridor design that would work for both grizzlies and wolverines in western Montana, focusing on potential connectivity between the GYE and NCDE. Core habitat for grizzlies were the two aforementioned ecosystems and resistance was evaluated using factors such as vegetation, development, and roads. Wolverines rely on late season snow and 6 areas in between the GYE and NCDE were determined as habitat areas. To determine corridors, each potential area was evaluated in terms of resistance and price of connectivity to the core protected areas (GYE and NCDE). This study determined various potential corridors depending on the weighing of each of the species. This is a useful study in its explicitness in the trade-offs of evaluating corridors based solely on ecological impact for a single species versus considering ecological and biological impacts for multiple species.

[grizzlyhabitatconnectivity]

Ebinger, M., Haroldson, M., Van Manen, F., Costello, C., Bjornlie, D., Thompson, D., Gunter, K., et al. (2016). Oecologia, 181, 695 – 708. https://doi.org/10.1007/s00442-016-3594-5

Created predictive model to determine carcass visitation by grizzly bears in the Greater Yellowstone Ecosystem. Using cluster data from GPS-collared bears, the location of grizzly bears and carcasses was analyzed to determine if bears were feeding on carcasses more regularly given the decline of Whitebark Pine seeds. Based on cluster data of grizzly visitation, each cluster was categorized as i) large-biomass carcass visitation, ii) small-biomass carcass visitation, iii) old carcass visitation, iv) resting, or v) non-carcass activity. Analyzing grizzly cluster data during a period of Whitebark pine declines in the GYE, the study analyzed grizzly bear activity during the fall, when Whitebark pine seeds typically constitute a large portion of grizzly bears’ diets. The accuracy of the predictive model was highest for large-biomass carcasses. This type of model may be useful in understanding potential grizzly bear response to changes in food availability in the face of climate change. This will be useful for mapping habitat connectivity as food availability plays a key role in determining habitat selection by grizzly bears.

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Ford, A., Barrueto, M., and Clevenger, A. (2017). Road Mitigation Is a Demographic Filter for Grizzly Bears. Wildlife Society Bulletin, 41(4), 712 – 719. https://www.jstor.org/stable/10.2307/90016791

Evaluates use and cost-effectiveness of different types of wildlife crossings in Banff National Park. Analyzes use type by single grizzlies (male or female) versus families (female with cubs). All grizzlies preferred large and open structures (i.e., overpasses), but families were more selective in which type of crossing they would use, strongly preferring overpasses. Wildlife crossings are key pieces of infrastructure that help promote population connectivity, and thus genetic diversity and continued survival of grizzlies and other species. Grizzly population viability relies on female grizzlies’ ability to cross highways and disperse. Grizzly use of different types of wildlife crossings including overpasses, open-span bridges, large metal culverts, small concrete culverts, and small metal culverts, was recorded using remote cameras. The majority of crossings occurred at open-span bridges and overpasses, though when accounting for availability, overpasses were highly favored. Solo bears were more likely to use smaller, less open crossings versus families. Given the importance of maintaining distribution of family groups, open-span bridges and overpasses, both with fencing along the roads to direct animals to the crossings, should be prioritized. Grizzly populations containing a highway that has a crossing structure have better genetic diversity than populations without a crossing structure. This is extremely useful information given I-90’s position across Montana and highlights the importance of providing a wildlife crossing across the interstate.

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Natural Resources Defense Council. (2019). Connectivity and Conservation: Grizzly Bears in the Lower 48. https://www.nrdc.org/resources/connectivity-and-conservation-grizzly-bears-lower-48

Story map showing grizzly bear populations in the lower-48. Provides an overview of grizzly bear significance in ecosystems, including seed dispersal, prey management, nitrogen provision, etc. Explains grizzly bear recovery zones in the U.S. and the importance of reconnecting the isolated Greater Yellowstone Ecosystem grizzly bear population with the Northern Continental Divide Ecosystem population. A lack of genetic diversity in the population can weaken the overall population. Uses interactive maps throughout the story maps to demonstrate and highlight areas where the bears currently reside versus potential future recovery zones. Explains that grizzly bear dispersion is usually driven by males that are looking to establish a home range and demonstrates on maps the gaps between current grizzly range and potential connectivity corridors. Overlays roads and the large interstates that prevent movement between populations as well as areas with wildlife overpasses.

[grizzlyhabitatconnectivity]

Parson, B.M., Coops, N.C., Kearney, S.P., Burton, A.C., Nelson, T.A., and Stenhouse, G.B. (2021). Road Visibility Influences Habitat Selection By Grizzly Bears (Ursus arctos horribilis). Canadian Journal of Zoology, 99(3), 161 – 171. https://doi.org/10.1139/cjz-2020-0125

Analyzes topography and vegetation to determine how visibility of roads impacts grizzly selection of habitat. Used GPS-collared grizzly bears in conjunction with habitat modeling using LIDAR. Analyzed impact of habitat selection on mortality. Unsurprisingly, grizzlies tended to select areas farther and less visible from roads when traveling slowly or not moving, whereas grizzlies were more commonly found near roads when traveling. Grizzly bears in territory farther from roads had higher survival rates. Emphasizes the importance of using species environmental perception in determining habitat selection. For example, instead of just focusing on distance from a road, this analysis also infers habitat selection from vegetation density as this impacts visibility, foraging, breeding, etc. This study focused on roads and grizzly bears in Alberta, Canada, but is useful in understanding how roads and habitat visibility impacts grizzly selection of habitat.

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Peck, C., Van Manen, F., Costello, C., Haroldson, M., Landenburger, L., Roberts, L., Bjornlie, D., and Mace, R. (2017). Potential Paths for Male-Mediated Gene Flow To and From An Isolated Grizzly Bear Population. Ecosphere, 8(10), e01969. https://doi.org/10.1002/ecs2.1969

Emphasizes the importance and potential likelihood of creating habitat connectivity between the GYE and NCDE populations given the gap in occupied range is estimated to be ~110 kilometers. The importance of genetic exchange between these two populations is key to ensuring continued success of the GYE population which is isolated from other grizzly bear populations. Focuses on potential male connectivity by analyzing GPS locations of bears in conjunction with habitat and human development to determine potential connectivity pathways. Used a randomized shortest path algorithm to estimate the approximate number of pathways between two areas. There were several potential pathways determined, and those most likely to recur in the model tended to run along mountain ranges, likely because of the lack of development and human influence in the more rugged terrain. This mapping could be useful in determining priority conservation areas to promote connectivity between grizzly bear populations.

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Podruzny, S., Cherry, S., Schwartz, C., and Landenburger, L. (2002). Grizzly Bear Denning and Potential Conflict Areas in the Greater Yellowstone Ecosystem. International Association for Bear Research and Management, 13, 19 – 28.

Maps den locations from 1975 – 1999 and performs GIS analysis to determine the similarities in attributes such as elevation slope, solar radiation, and forest cover to create a predictive model of potential den sites. Gallatin National Forest used the model to impose regulations on certain areas to minimize risk of snowmobile disturbance on potential bear dens. Dens were identified using GPS collared bears, and terrain was mapped using a DEM and Arc / Grid format. Snowmobile use areas were mapped separately, and then snowmobile use, protected wilderness / nonmotorized areas, and potential denning habitat maps were overlaid to determine key potential conflict areas. This allowed land managers to determine areas where additional restrictions should be implemented to minimize disturbance of denning bears.

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Proctor, M., Nielsen, S., Kasworm, W., Servheen, C., Radandt, T., Machutchon, A., and Boyce, M. (2015). Grizzly Bear Connectivity Mapping in the Canada-United States Trans-Border Region. The Journal of Wildlife Management, 79(4), 544-558. https://doi.org/10.1002/jwmg.862

Highlights the impacts of habitat and population fragmentation to species. Attempts to create a methodology to predict grizzly use of connectivity habitat in the trans-border area (US / Canada) by creating a model using resource selection function (RSF) and data on building density. Compares projections by the model with GPS data on grizzly movement and found accurate predictions of habitat use by grizzlies. This model could therefore be useful in determining and predicting future connectivity pathways for grizzly populations. In the trans-border area, there are five subpopulations of fewer than 100 individuals that lack female dispersal. These subpopulations are separated by highways or human development, and ultimately rely on genetic exchange and dispersal with larger populations to survive. Female grizzly bears disperse slowly, and thus during the multi-year dispersal period, are at higher risk of mortality due to either vehicle collisions or other conflict with humans. By determining the predictability of preferred linkage habitat, certain areas can be prioritized for conservation and habitat connectivity in lieu of human development.

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Sage, A., Hillis, V., Graves, R., Burnham, M. and Carter, N. (2022). Paths of Coexistence: Spatially Predicting Acceptance of Grizzly Bears Along Key Movement Corridors. Biological Conservation, 266, 109468. https://doi.org/10.1016/j.biocon.2022.109468

Maps attitudes towards grizzly bears in western Montana and eastern Idaho near the Continental Divide. Ranchers who are near more conservation easements and wildland-urban interface had more positive attitudes towards grizzlies. Creates a predictive map to determine attitudes and acceptance towards grizzly bears, enabling effective decision-making regarding human-wildlife conflict mitigation efforts and analysis of changing attitudes as grizzly populations expand. Highlights the importance of human attitudes in shaping a community’s or town’s willingness towards implementing proactive wildlife-mitigation strategies, and thus the importance of leveraging this tool when planning for connectivity. To determine and categorize rancher attitudes, the authors focused on their experiences with grizzlies, means of income (i.e. ranching or ancillary as well), and attitudes towards conservation.

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Sells, S., Costello, C., Lukacs, P., van Manen, F., Haroldson, M., Kasworm, W., Teisberg, J., VInks, M., and Bjornlie, D. (2023). Grizzly Bear Movement Models Predict Habitat Use for Nearby Populations. Biological Conservation, 279, 1-11. https://doi.org/10.1016/j.biocon.2023.109940

Emphasizes the importance of mapping models being transferrable to different areas. Evaluates several different individual-based, integrated step selection functions based off of GPS-collared grizzly bears in the NCDE. Applies these models to other grizzly bear recovery zones including the Selkirk, Cabinet-Yaak, and Greater Yellowstone Ecosystems. Overlaid GPS collar data from bears in the recovery zones and determined that these models were very accurate in predicting female grizzly ranges. The models were less accurate for male grizzly bears, though this is likely due to higher dispersal distances, ranges, and seasonal variability. Overall, the assessment determined that these models are fairly accurate in assessing adequate grizzly bear habitat in ecosystems other than where the models were developed. This is useful in evaluating potential connectivity corridors for isolated grizzly bear populations.

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GIS | Applications in Grizzly Habitat Connectivity

Taylor Kwait | GEOG 560 | Spring 2023 | Oregon State University