WASHINGTON, DC -- A new study by World Wildlife Fund (WWF) scientists finds that sampling large volumes of stream water for environmental DNA (eDNA) can measure the diversity of terrestrial mammals in an ecosystem as effectively as established camera trap monitoring methods.
In this study, eDNA sampling detected the presence of 25% more terrestrial mammal species than detected via camera traps, and for a fraction of the cost.
This study is the first to demonstrate the higher efficiency of this method compared to traditional camera traps to assess the diversity of terrestrial mammals in a large landscape. Previous studies have demonstrated the efficiency of eDNA sampling to detect aquatic species.
The study, published today in Scientific Reports, compared detection rates of terrestrial mammals in eDNA samples recovered from stream water to similar estimates from a camera trap survey in a mountainous study site in British Columbia, Canada and compared the sampling costs of both methods.
To draw this comparison, scientists took water samples from Tyaughton Creek and Gun Creek in the South Chilcotin mountains of Gold Bridge, British Columbia. When they analyzed the samples, traces of red squirrel, mule deer, grizzly bear and wolverine were detected, among other species, which was on par with camera trap images.
Between 2018 and 2019, the eDNA sampling detected the presence of 35 mammal taxa and cost USD $46,415. The camera trap survey data used for comparison over the same period detected 29 mammal taxa and cost USD $64,195.
The enormous diversity of life on earth makes monitoring species and discovering new ones challenging and costly. The most common methods for taking inventory of species, like camera traps and aerial surveys, are often difficult to execute due to capacity, budget, labor and time constraints.
"Previous scientific research has proven eDNA sampling and analysis to be a powerful tool that can help us make informed decisions about conservation," said Arnaud Lyet, Senior Conservation Scientist at WWF. "Our findings build upon that and show the full utility of this method as a tool for large-scale terrestrial biodiversity monitoring."
