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  • Writer's pictureEmma Gillies

The importance of technology in wildlife conservation

In the field of wildlife conservation, ecologists are not the only ones working to ensure species and ecosystem prosperity; engineers and data scientists are also designing and implementing technologies to make conservation more efficient. As technology becomes more powerful and accessible, it’s driving how we collect and analyze data on species.


Launched in 1973, the Global Positioning System (GPS) was originally used for tracking US submarines. But this satellite-based navigation system, which gives the location coordinates of a user anywhere on Earth, has since become very important in biological research and conservation. GPS allows field ecologists to record the location of their sampling sites, follow the movement of animals, and analyze biogeographical trends. While GPS refers purely to positional data, a related concept is aerial imagery collected by sensors on drones, airplanes, and satellites. A rise in the availability of aerial imagery has allowed us to monitor how land use is changing, pinpoint the location of animals such as koalas, and even count individual trees from above the canopy.


Photo credit: Fisheries and Oceans Canada


Aerial imagery is essentially a type of remote sensing, which is the process of measuring the radiation of an area from a distance in order to gain information about its physical characteristics. In other words, remote sensing allows us to acquire information about an object without having any physical contact with it. When combined with GPS, remote sensing methods like aerial imagery give scientists geospatial data, which holds information not only about a place but its exact location. Light Detection and Ranging (Lidar) is another remote sensing method that uses light to measure distances to the earth. Lidar has allowed scientists to produce accurate shoreline maps, understand tree structure, and delineate streams.

On-the-ground technologies are also powering wildlife data collection.


Camera traps have made it possible to collect an enormous amount of data and study species that have rarely been seen by scientists in the wild. Meanwhile, acoustic monitoring devices can record the sounds of animals both underwater and aboveground, and have helped scientists measure fish abundance and understand the composition of bee communities. Portable genetic technologies such as Gene that collect and analyze genetic data have also proven to be valuable methods of species detection.


Finally, the increased accessibility of non-scientists to cell phones and apps has increased the potential for wildlife data collection and education. For example, scientists have analyzed citizen-science collected data on the eBird app to understand bird distributions, while iNaturalist helps scientists and non-scientists alike identify animals and plants, while also networking and learning from other naturalists.


Technology like remote sensing, camera traps, and phone apps are changing how we collect data, but this data must then be managed and analyzed. Geographic information systems (GIS) are frameworks that can manage, analyze, and visualize wildlife data, helping to understand population distributions, habitat use, conservation progress, and regional biodiversity over time. Open-source coding languages such as R and Python allow data scientists and biologists to analyze data and build artificial intelligence (AI) algorithms that are revolutionizing conservation. In fact, camera traps collect so many images that scientists are employing AI, rather than humans, to filter through them. Whale Seeker is another example: we use deep learning to locate whales from aerial images so that our clients save time and money that would otherwise be spent going through these images by hand. AI algorithms are also being used to predict migratory patterns, predict where poachers are most likely to enter a park, and identify animals from audio recordings and acoustic monitoring devices.

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