Grizzly bear (Ursus arctos) habitat use maps delineate predicted habitat use for grizzly bears around federally designated recovery zones in and near western Montana. These raster data are the official data release for Sells et al. (2022), “Grizzly Bear Habitat Selection Across the Northern Continental Divide Ecosystem” and Sells et al. (2023), “Grizzly bear movement models predict habitat use for nearby populations.” In summary, to better understand habitat selection by grizzly bears, Sells et al. (2022) developed and validated individual-based integrated step-selection functions (iSSFs) for 65 grizzly bears monitored in the Northern Continental Divide Ecosystem (NCDE; including 19 males and 46 females). Step-selection functions, developed from GPS location data, are highly versatile models that can be used to study and predict habitat selection, movement corridors, dispersal, and human-wildlife interactions. Sells et al. (2022)’s models involved variables that could be measured across a large landscape and were previously identified as important to habitat selection by this generalist omnivore. External validation with data omitted from model development demonstrated that the models were highly predictive of habitat use within the NCDE. Sells et al. (2023) built on Sells et al. (2022) as a second phase of the study. In this paper, we aimed to evaluate the transferability of the models to a larger landscape spanning multiple ecoregions. We simulated movements within the Selkirk (SE), Cabinet-Yaak (CYE), and Greater Yellowstone (GYE) Ecosystems using the 65 models Sells et al. (2022) developed from NCDE bears, summarized results to estimate relative habitat selection, and assessed model transferability over space and time using location data for bears in the SE, CYE, and GYE. Because the NCDE models can be accurately transferred to nearby populations, this demonstrates reliability of applying the models to predict habitat use for areas with few or no data, including potential connectivity pathways between populations or in uninhabited areas like the North Cascade (NCE) or Bitterroot Ecosystems (BE). In these datasets, all results are summarized and quantile binned as classes 1 (lowest relative predicted use) - 10 (highest relative predicted use) for each recovery zone. Each class is represented by 10% of each recovery zone. However, because the NCDE-CYE and SE-CYE slightly overlap, we averaged and rounded to the nearest integer at cells of overlap. The maps can be clipped down as desired to view details of specific areas. (Note: subsetting the maps will mean that the classes no longer each represent 10% of the landscape, as this binning was done independently for the NCDE, SE, CYE, and GYE.) Our predictive maps can facilitate on-the-ground application of this research for prioritizing habitat conservation, human-bear conflict mitigation, and transportation planning.

This map shows the grizzly bear's historic and current range and highlights the ecosystems upon which Defenders of Wildlife is focusing grizzly bear recovery. Current and historic grizzly bear distribution from IUCN, Yellowstone grizzly distribution (2002-2016) from the Interagency Grizzly Bear Study Team (Bjornlie et al. 2014) and USGS. Grizzly bear recovery zones from USFWS and USGS.(supports the following items: Grizzly Bear Current and Historic Range web map app by mlacey7)

This map looks at grizzly bear historic and present ranges as well as potential wildlife corridors and current grizzly bear moralities in Yellowstone.

Grizzly bear (Ursus arctos) habitat use maps delineate predicted habitat use for grizzly bears around the Bitterroot Ecosystem (BE), a federally designated recovery zone in western Montana and central Idaho. These raster data are the official data release for Sells and Costello (2024), “Predicting future grizzly bear habitat use in the Bitterroot Ecosystem under recolonization and reintroduction scenarios.” Many conservation actions must be implemented with limited data. This is especially true when planning recovery efforts for extirpated populations, such as grizzly bears within the Bitterroot Ecosystem (BE), where strategies for reestablishing a resident population are being evaluated. Here, we applied individual-based movement models developed for a nearby grizzly bear population to predict habitat use in and near the BE, under scenarios of natural recolonization, reintroduction, and a combination of the two strategies. All simulations predicted that habitat use by grizzly bea ...

Boundaries identifying similar behavioural ecotypes and sub-populations of Grizzly bears. This dataset contains versions from multiple years. From 2018 on, NatureServe conservation concern ranking categories (e.g., Very Low, Low, Moderate, High, Extreme Concern) supersede the pre-2018 population status categories (e.g., Viable, Threatened, Extirpated) contained in the field STATUS. NatureServe conservation concern ranking categories reflect population size and trend, genetic and demographic isolation, as well as threats to bears and their habitats. The NatureServe conservation concern ranking fields are named CONSERVATION_CONCERN_RANK and CONSERVATION_CONCERN_DESC. Please view the attached PDF file for a summary of changes to this dataset from 2012 onward. To download only the 2018 units, in the link below, select the "Export" tab, then select the "Provincial Layer Download" button: https://maps.gov.bc.ca/ess/hm/imap4m/?catalogLayers=7744,7745 Grizzly Bear Conservation Ranking results table is available here: https://catalogue.data.gov.bc.ca/dataset/e08876a1-3f9c-46bf-b69a-3d88de1da725 Grizzly Bear population estimates from various years are available here: https://catalogue.data.gov.bc.ca/dataset/2bf91935-9158-4f77-9c2c-4310480e6c29 Grizzly Bear reports are available here: https://www2.gov.bc.ca/gov/content/environment/plants-animals-ecosystems/wildlife/wildlife-conservation/grizzly-bear

The project lead for the collection of this data was Carrington Hilson. Elk (4 adult females) were captured and equipped with GPS collars (Lotek Iridium) transmitting data from 2018-2021. The Grizzly-Van Duzen herd does not migrate between traditional summer and winter seasonal ranges. Therefore, annual home ranges were modeled using year-round data to demarcate high use areas in lieu of modeling the specific winter ranges commonly seen in other ungulate analyses in California. GPS locations were fixed between 1-6 hour intervals in the dataset. To improve the quality of the data set as per Bjørneraas et al. (2010), the GPS data were filtered prior to analysis to remove locations which were: i) further from either the previous point or subsequent point than an individual pronghorn is able to travel in the elapsed time, ii) forming spikes in the movement trajectory based on outgoing and incoming speeds and turning angles sharper than a predefined threshold , or iii) fixed in 2D space and visually assessed as a bad fix by the analyst. The methodology used for this migration analysis allowed for the mapping of the herd''s home range. Brownian bridge movement models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data from 3 elk, including 8 annual home range sequences, location, date, time, and average location error as inputs in Migration Mapper. BBMMs were produced at a spatial resolution of 50 m using a sequential fix interval of less than 27 hours. Large water bodies were clipped from the final output. Home range is visualized as the 50thpercentile contour (high use) and the 99thpercentile contour of the year-round utilization distribution. Home range designations for this herd may expand with a larger sample.

Maps and summary plots of model projections for each species for the present and future, including (A) maps of model projections of probability of presence (PoP) for the present and future scenarios; (B) maps of projected change in habitat based on changes of modeled species presence/absence; (C) probability density function plots for projected PoPs; and (D) probability density function plots for elevations of projected suitable habitat.

Maps depicting the relative probability of occurrence of female grizzly bears in the mountain landscape of the Parsnip River study area, British Columbia, Canada, 1998–2003, based on study-wide extent, home range extent, and buffer extent.

The project leads for the collection of this data were Sara Holm and Julie Garcia. Mule deer (6 adult females) from the Grizzly Flat herd were captured and equipped with Lotek Iridium Track MGPS collars, transmitting data from 2018-2021. GPS fixes were between 11-13 hours. The Grizzly Flat herd migrates from winter ranges in the western foothills of the Sierra Nevada range near the Grizzly Flats eastward to higher altitude terrain in El Dorado national Forest, staying south of Interstate 50. To improve the quality of the data set as per Bjørneraas et al. (2010), the GPS data were filtered prior to analysis to remove locations which were: i) further from either the previous point or subsequent point than an individual deer is able to travel in the elapsed time, ii) forming spikes in the movement trajectory based on outgoing and incoming speeds and turning angles sharper than a predefined threshold , or iii) fixed in 2D space and visually assessed as a bad fix by the analyst. The methodology used for this migration analysis allowed for the mapping of winter ranges and the identification of migration corridors. Brownian Bridge Movement Models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data from 5 migrating deer, including 16 migration sequences, location, date, time, and average location error as inputs in Migration Mapper. The average migration time and average migration distance for deer was 11.63 days and 43.10 km, respectively. Corridors and stopovers were prioritized based on the number of animals moving through a particular area. BBMMs were produced at a spatial resolution of 50 m using a sequential fix interval of less than 27 hours. Due to the majority of BBMMs producing variance rates greater than 8000, a fixed motion variance of 1000 was set per migration sequence. Winter range analyses were based on data from 5 individual deer and 8 wintering sequences using a fixed motion variance of 1000. Winter range designations for this herd may expand with a larger sample, filling in some of the gaps between winter range polygons in the map. This collar project was not specifically designed to pinpoint precise migration routes or winter range designations, hence the low sample size. Additional migration routes and winter range areas likely exist beyond what was modeled in our output.Corridor tiers (low, medium, high) could not be computed with such a small dataset. Therefore, all corridors were given the same weight and designation in this analysis. Stopovers were calculated as the top 10 percent of the population level utilization distribution during migrations and can be interpreted as high use areas. Stopover polygon areas less than 20,000 m2were removed, but remaining small stopovers may be interpreted as short-term resting sites, likely based on a small concentration of points from an individual animal. Winter range is visualized as the 50th percentile contour of the winter range utilization distribution.

Grizzly bears (Ursus arctos) have been increasingly observed in central Montana’s plains in recent years. To assist with conservation planning, we sought to predict habitat use and connectivity pathways for grizzly bears east of the Northern Continental Divide Ecosystem (NCDE) and northeast of the Greater Yellowstone Ecosystem (GYE). We used the methods described in Sells et al. (2023b), "Predicted connectivity pathways between grizzly bear ecosystems in Western Montana," to simulate grizzly bear movements along the edges of the NCDE and GYE and into central Montana. Simulated grizzly bears used riparian areas in the plains most heavily, along with isolated mountain ranges. Based on known outlier locations and locations from GPS-collared bears, our resulting maps had high predictive capacity, with mean values at outlier or GPS locations of ≥7.1 and Spearman rank correlations of ≥0.84. The maps produced by these simulations are provided in this data release to contribute to conserv ...

Maps depicting the relative probability of occurrence of male grizzly bears in the plateau landscape of the Parsnip River study area, British Columbia, Canada, 1998–2003, based on study-wide extent, home range extent, and buffer extent.

Capability mapping showing provincially significant winter ranges from CORE for moose, bighorn sheep, mule deer, goat, black bear, grizzly bear and caribou. Disclaimer: This is older strategic scale mapping information that may be superseded in some areas with more detailed TEM mapping information

Delineate the regional distribution and quantify the abundance of caribou during the calving season in four survey areas (Kuparuk Field, Kuparuk South, Colville River delta, NE NPRA); Obtain a quantitative estimate of regional calf production and sex/age composition at the end of the calving season; Map the regional distribution and abundance of muskoxen, grizzly bears, and other large mammals encountered during caribou surveys. Lawhead BE, Prichard AK. 2010. Data Report for the Alpine pipeline Caribou Surveys. ABR Inc.--Environmental Research and Services. 13 p.