Snowballs for Conservation: Taking DNA from Snow to Detect Rare Carnivores

Franklin, T.W., McKelvey, K.S., Golding, J.D., Mason, D.H., Dysthe, J.C., Pilgrim, K.L., Squires, J.R., Aubry, K.B., Long, R.A., Greaves, S.E., Raley, C.M., Jackson, S., MacKay, P, Lisbon, J., Sauder, J.D., Pruss, M.T., Heffington, D., Schwartz, M.K. (2019). Using environmental DNA methods to improve winter surveys for rare carnivores: DNA from snow and improved noninvasive techniques. Biological Conservation, 229 (October 2018), 50–58. https://doi.org/10.1016/j.biocon.2018.11.006 

 

Researchers spotted the tracks of a lynx in the snow ahead of them. Stooping down, they donned plastic bags over their winter gloves and piled the printed snow into a nalgene water bottle. The print was, of course, malformed from the transfer– but a trace of the lynx likely remained behind in the snow itself, through the DNA the lynx left behind. 

It’s one of those scientific techniques that seems almost magical– to take a sample of water, snow, or soil, and to be able to tease out the species that were there, by analyzing the fragments of DNA left behind. This mix of fragments is known as environmental DNA, or eDNA, and while it has been around since the 1980’s, its analysis is continually being improved and used in new ways. The snow-collecting researchers from the U.S. Forest Service, for example, were trying to improve methods for detecting rare carnivores– lynx, fisher, and wolverine– in the winter. 

 

Detectives of DNA

Canadian lynx near Whitehorse, Yukon, taken by Keith Williams 2010. From: https://commons.wikimedia.org/wiki/File:Canadian_lynx_by_Keith_Williams.jpg 

Wildlife conservation programs need a lot of data, even for the simple information on the population: How many lynx and wolverines are there in an area? To answer this, you would try to sample the population, ideally with non-invasive methods. This could mean taking pictures of animals that pass by a camera, collecting hair that gets snagged on barbed wire as the animal walks by, collecting scat, following footprints, or even collecting the ground beneath their feet. 

Error, however, plagues all of science. If a camera trap takes a grainy picture with a mammal-sized blob in the background, the researcher might call the animal a lynx instead of a bobcat. On the opposite side, if the animal never happens to walk by the camera or strike the wire, the animal might be around but not detected. Add into the mix the lack of accessibility to these animals, and the unreliability of technology in the harsh weather of the winter, and the potential for error increases.

Having the wrong numbers can lead to unfounded conclusions, which impacts the species under protection. In one case, it could overestimate the number of individuals so that the species does not have the protection it needs. Should the true population shrink, it could go unnoticed. In short, the accuracy of this gathered data has real-world importance. 

Once the surveyor happens upon the animal tracks, the old methods would dictate that they should follow the tracks backwards until they find the animals scat or hair sample– decreasing the identification error by finding corroborating evidence. This means trudging through more snow at the expense of time and energy. But if they could just collect the snow and use technology to analyze the leftover DNA, it would back up their hunch about the tracks, save time, and increase accuracy. This is the potential power of using eDNA.

 

Snow around the tracks was scooped into a 2L bottle, DNA was later extracted and analyzed. From Franklin et al 2019.

DNA to Data

With their samples collected, now the scientists needed to analyze the DNA. For this team, this meant collecting the snow under the tracks, collecting the snow once the animal was spotted on camera, and collecting hair samples from wire that was left over the winter. 

With the nalgene of snow melted into water and filtered, the team needed to copy the DNA so they could amplify the signal left in their collection of DNA fragments. To do this, they employed a technique called quantitative PCR. The use of qPCR distinguishes this study from previous analyses of eDNA in snow, and this method gave promising results.

On the whole, their methods worked to detect the species with accuracy. The method can also be used when multiple species are present at a site, such as multiple animals using the same snowy trail. It also greatly improves the ability for researchers to detect these rare species in the winter.

The future is bright for eDNA, and there is plenty of room for growth. The writers highlighted that it would be useful to have a test that could give positive identification; to go beyond saying, “this sample is not a wolverine,” and instead say “this is not a wolverine, this is a lynx.”

Using new methods gives a clearer picture of what’s out there, and makes conservation decisions more informed– a lot of power in a snowball.

Feature Image: Mink and Wolverine Tracks in the snow at Telaquana Lake. Credit: NPS / J. Mills. 2012. From https://www.flickr.com/photos/lakeclarknps/37345257382/in/photostream/

Díaz-Ferguson, E. E., & Moyer, G. R. (2014). History, applications, methodological issues and perspectives for the use environmental DNA (eDNA) in marine and freshwater environments. Revista de Biología Tropical, 62(4), 1273. https://doi.org/10.15517/rbt.v62i4.13231 

 

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Abigail Bezrutczyk

I’m a fourth-year undergraduate at Cornell University, where I study environmental science and plant science, and do research with invasive plants. I’m interested in pursuing a career in science communication after college. Outside of school, I enjoy cooking, drawing, and snacking on goldfish crackers.

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