Animation of road-wildlife interactions around Banff National Park, Canada

This animation demonstrates the use of the Environmental COntextual-Data And TrAk (ECODATA) Prepare and Animate software applications (https://www.movebank.org/cms/movebank-content/ecodata). The ECODATA apps are free tools to support geospatial data exploration and analysis, designed with and for movement ecologists and animal tracking data. The ECODATA software used and additional background are described in Missik et al. (2025). The goal of this animation is to visualize movements of an herbivore (Cervus elaphus, elk) and a carnivore (Canis lupus, wolves) in relation to roads that provide visitor access to Banff National Park, Canada, in particular the TransCanada Highway, labeled as Hwy 1 in the animation. Transportation infrastructure and traffic have largely negative, species-specific effects on wildlife (Fahrig & Rytwinski, 2009). Impacts of road traffic on wildlife in and around Banff National Park, Alberta, Canada, have been the focus of research and mitigation efforts for decades (Clevenger, 1997; Whittington et al. 2019; Edwards et al., 2022). Wildlife tracking data can be used to quantify wildlife behavior near roads, related ecosystem dynamics (Whittington et al. 2019, 2022), effectiveness of crossing structures (Clevenger and Waltho, 2001) and impacts of human recreation on wildlife movements. Millions of people visit Banff National Park each year (Clevenger, 1997; Hebblewhite & Whittington, 2020). Well-designed mitigation structures, such as fencing and crossing structures, have been shown to reduce mortalities and traffic accidents in the area (Edwards et al., 2022). However, their effectiveness can vary by species (Clevenger & Waltho, 2000) and season (Edwards et al., 2022). Wildlife tracking data can be used to quantify wildlife behavior near roads, related ecosystem dynamics (Hebblewhite & Whittington, 2020), and the effectiveness of mitigation structures (Clevenger and Waltho, 2001). The animation shows movements of 47 individuals (26 elk and 21 wolves) during February–December 2004 based on data recorded by GPS collars (Hebblewhite et al., 2020; Hebblewhite, 2025). The animation shows migration of both elk and wolves from their winter ranges in the northeast to their summer ranges during late spring, and back to their winter ranges in fall. Considerable activity occurs near roads along the Trans-Canada Highway 1 during the peak traffic season in the summer. Parks Canada has invested millions of dollars in mitigating collision risk in this area through one of the world's most comprehensive wildlife crossing structure systems, hundreds of kilometers of fencing, and other features (Ford et al. 2010). However, this visualization demonstrates frequent crossings by wolves and elk in the northwestern part of the study area, where crossing structures did not exist on Highway 1 at the time, and along Highway 93, which lacks crossing infrastructure and remains a wildlife mortality hotspot in Banff National Park. This visualization demonstrates how custom animations of wildlife movements can help in planning infrastructure and prioritizing investments to reduce human-wildlife conflict. Visualizing successful highway crossings on over- and underpasses help managers interpret efficacy of crossing structures, and identify potential locations for future mitigation. ECODATA allows flexible modifications of existing animations to address different questions or data sources. For example, future versions could include data representing traffic volume or recreation to visualize the impacts of dynamic human activity on wildlife (e.g., Whittington et al. 2019), including on Highway 1A, which has seasonal closures to promote wildlife movements. Alternate versions could also integrate reported collisions, road crossing events inferred from tracking data, or emerging threats such as expanding residential development (Whittington et al. 2022). Input layers include the following: GPS tracking data for elk (Hebblewhite et al., 2020): blue dots and trace lines GPS tracking data for wolves (Hebblewhite, 2025): orange dots and trace lines Normalized difference vegetation index (NDVI), a measure of vegetation greenness, at 16-day, 250-m resolution (MOD13Q1) (Didan, 2021): green background shading A digital elevation model representing land elevation (Amante & Eakins, 2009; NOAA National Geophysical Data Center, 2009): light gray lines River features at 10-m resolution (Natural Earth, naturalearthdata.com): light blue lines Road features (Natural Resources Canada, 2010a, 2010b): dark gray lines Labels for the major highways and known crossing structures: black dots and labels Custom settings for preparing the animation and creating image frames in ECODATA-Animate are described in the file ECODATA_settings_Hebblewhite_elk_wolves_Banff_roads.pdf. Several of these inputs required processing prior to use. First, to prepare the tracking data, we evaluated GPS tracking datasets from the region on Movebank (Kays et al., 2022), looking for movements in Banff National Park of multiple species during the same years and checking for outliers. After identifying target studies, we ran MoveApps workflow (Davidson et al., 2025) to merge data from two long-term tracking studies, identify 2004 as the year with the most number of deployments of both species and a 2-hour frequency as the frequency rate for the final animation frames based on the typical GPS fix rate in the data (Chatterjee & Kölzsch, 2024), and evaluate possible bounding boxes by creating draft animations (Schwalb-Willmann et al., 2020). Second, for the background of the animation, we chose to display vegetation greenness represented by NDVI to indicate changing seasons. We reviewed available data products and obtained a netCDF file containing data for the chosen region and time range using NASA’s EARTHDATA AppEEARS interface (https://appeears.earthdatacloud.nasa.gov/). To define the bounding box for this data request, we used a .geojson file created in the ECODATA-Prepare Tracks Explorer App. Next, to prepare the netCDF file for input to ECODATA-Animate, we used the ECODATA-Prepare Gridded Data Explorer App to view the retrieved data and create a new file with daily images interpolated from the original 16-day NDVI estimates. Third, for the road infrastructure, we needed to ensure that detailed and accurate road infrastructure were shown, so that animal behaviors near roads could be correctly distinguished, for example from those around the adjacent Bow River. However, the complete provincial road datasets from the Government of Canada (Natural Resources Canada, 2010a-b) contain over 570,000 features, reducing performance of ECODATA-Animate and other software programs. To prepare the road shapefiles for input to ECODATA-Animate, we used the ECODATA-Prepare Subsetter App to create shapefiles containing only road features from the originals that fell within the bounding box for the animation. We used the open-source software QGIS (http://www.qgis.org) to compile and compare potential input layers. For example, in QGIS we quickly determined that both "rivers" and "lake centerlines" shapefiles from Natural Earth were needed to display rivers within the study area.

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