Rocky Mountain elk may grow up to eight and half feet in height and weigh more than a thousand pounds but these larger-than-life creatures are as elusive as they are majestic. The Utah Division of Wildlife Resources (DWR) is responsible for the conservation of these elk and 800 other species. In 2020, while many were scrambling to get the Covid vaccine, the Utah DWR took their first steps on a journey to improve their monitoring ability with cloud technology from Google Public Sector.
Google Public Sector helped Utah’s DWR tap into BigQuery, a serverless data warehouse in Google Cloud which offers both data storage and analysis capabilities. With BigQuery, DWR created a new Wildlife Tracker app which lets it use machine learning to process vast volumes of data, including fresh location information from tracking collars as well as 20 years of historical data from legacy systems.
According to DWR, its staff are now able to pull data from more than 10,000 animals and 40 million location data points on demand. The new cloud-based system also allowed them to add additional tracking features, including alerts for mortality events, animal speed and elevation.
“Regardless of your desired outcome, data is at the forefront of every project,” said Brent Mitchell, Vice President, US State & Local Government and Education, Google Cloud. “BigQuery is the cornerstone of public sector projects nationwide, as it has the capacity to audit petabytes of data, outlining bottlenecks and silos, while also making that data readily accessible.”
Previously, the DWR tracked animals by hunting for signals emitted by radio collars using a high frequency antenna. “Tracking could take up to a week, which meant field operatives attempting to identify the cause of death of an animal would often arrive to find the cadaver picked clean by scavengers,” said Blair Stringham, a wildlife biologist at the Utah DWR.
“We were not realizing the true potential of what the data was telling us, and we needed to change that,” Jessie Shapiro, GIS manager for the Utah DWR, added.
But transitioning to serverless data was not a ‘drag and drop’ shift. The primary challenge for DWR was the learning curve that comes with a new program. The organization works with wilderness experts who spend much of their time outside and away from modern technology and had to be brought up to speed. Despite this, these outdoor experts much prefer the new system.
Now, the difference is night and day, Stringham said, with both real time information and years of legacy data just a just a search away. The DWR has used its ability to surveil the wilderness and its inhabitants to improve existing habitat needs while not interfering with the ecosystem at large.
Notably the DWR has used the data to identify areas in which animal-on-vehicle collisions are most common, allowing them to reroute the animals or even the roads for better safety. This data has also been used to open new migratory routes within existing habitats. In the case of the pronghorn antelope this involved the deconstruction of fencing the species is notorious for getting stuck in.