One of the major Wildlife Management implications for Snapshot Wisconsin is the project’s contributions toward a system the DNR uses to calculate the size of the white-tail deer population in Wisconsin. Fawn-to-doe ratios, or FDRs, are found by dividing the number of does by the number of fawns seen during the summer months and are summarized by the (82) management units across the state.
In total, three programs contribute to FDR estimates: Snapshot Wisconsin, Operation Deer Watch, and the Summer Deer Observation Survey. An advantage of incorporating Snapshot Wisconsin data in these estimates is that Snapshot cameras tend to be placed in secluded, natural areas, whereas the other two collection methods are opportunistic, meaning they’re biased toward counting deer seen near roadways.
One challenge associated with trail camera data is that the same individual animals may walk by the camera multiple times throughout the data collection period. To account for this, we average the total number of does seen in photos with at least one doe, and then average the total number of fawns in each photo containing at least one fawn. We then take the average number of fawns and divide it by the average number of does.
Fawns and does may or may not be in the same photo to contribute to their respective averages. Defining a single camera-level average for each site drastically reduces the amount of data involved but ensures that the FDR is not skewed toward does, which tend to appear much more frequently on Snapshot cameras.
The above maps show the camera sites that contributed to FDR estimates in 2017 and in 2018. Photos from exclusively July and August were analyzed. A site only contributes to the estimate if there were at least 10 doe observations in one of the two months, but can be counted twice if it had at least 10 doe observations in both months. Statewide, 897 cameras contributed to 2018 FDR estimates, a 44% increase from the 622 sites that contributed in 2017. Some deer management units decreased in sample size from 2017, but
Above are the results of the 2017 and 2018 FDR estimates using Snapshot Wisconsin data. Only deer management units with a minimum of 5 camera sites were included in the analysis. In 2018, the range of FDR was 0.75 – 1.2, which is an overall increase from the range of 0.62 – 1.13 in 2017. Snapshot Wisconsin was launched statewide in August 2018, meaning most cameras in the newly open counties were not deployed until after the data collection period. We expect that the number of cameras in the 2019 analysis will increase again, which would give us even more accurate estimates.
Recently, I was running, lost in my thoughts, and—WHOOPS—almost tripped over a shivering opossum crossing the bike path! After we both recovered our wits, I jogged in place and watched it waddle away, naked tail dragging through the snow. I rubbed my gloved—and still cold—hands together and wondered, why the heck do opossums live in Wisconsin?
When I got home, some Googling revealed an interesting fact: Wisconsin is at the limit of the opossum’s geographic range. In turn, this got me wondering—what governs the limits of a species’ range?
Ecologists typically classify range-limiting factors as either abiotic or biotic. Abiotic factors do not involve living organisms; climate is the quintessential example. Biotic factors are interactions with other organisms. A classic example is competition between organisms, which is a direct biotic interaction. However, biotic interactions can also be indirect, such as when one species improves or degrades habitat for another. Abiotic and biotic factors usually work in concert to limit an organism’s range.
The opossum I saw behind Olbrich Gardens bespeaks both. Opossums, with their naked tails and ears, have a difficult time surviving cold environments. And yet, opossums live in snowy Wisconsin! However, this is a relatively new phenomenon—opossums did not occur in Wisconsin until the 1850’s, when their range expanded northward. The opossum’s conquest of Wisconsin has been aided and abetted by another organism, namely Homo sapiens. Humans provide extra resources (like trash), which help opossums survive Wisconsin’s cold winters. A biotic interaction has helped opossums overcome an abiotic limitation.
Regardless of the exact cause, opossums reach the northern limit of their range in Wisconsin. Several other species reach range limits in the state, a fact that can come in handy while classifying Snapshot Wisconsin photos. Look a photo’s metadata—what county was it taken in? In some cases, this can narrow down identification possibilities. For example, any rabbit-looking creature in Waueksha County is likely an eastern cottontail, since snowshoe hares do not occur in southern Wisconsin. A good source for species range maps is NatureServe Explorer.
For more information about opossums, see this recent Snapshot Wisconsin blog post by Emily Buege.
For more information about the opossum’s range expansion northward, I recommend reading Walsh and Tucker (2017).
We are throwing it back to summer last year for this Snapshot Saturday featuring a bobcat and her three kittens caught on a Vilas County camera. Can you spot them all?
View and classify photos collected from Snapshot Wisconsin cameras across the state at https://www.SnapshotWisconsin.org.
February’s Volunteer of the Month is
Mike from Iowa County!
February’s Volunteer of the Month goes to Mike from Iowa County, one of the first two counties where Snapshot Wisconsin started recruiting volunteers. Mike was no stranger to trail cameras when he joined the project two years ago—he had spent his career as a biologist in the tropics where he used trail cameras as one technique to study and conserve wildlife.
“Camera trap techniques motivate me because the photos are a fantastic way to learn about wildlife. The pictures are a moment in time of critters’ daily movement that is captured forever,” Mike said.
Birds are among his favorite critters captured at his site, including sandhill cranes, pileated woodpeckers and a great horned owl (who Mike noted doesn’t appear to have caught the squirrel repeatedly triggering his camera). Check out this awesome photo below that Mike shared of a squabbling pileated woodpecker and crow. In addition to participating in Snapshot Wisconsin, he is also involved with wintertime roosting eagle counts with the Ferry Bluff Eagle Council.
Thank you, Mike! Thank you to all our trail camera hosts and Zooniverse volunteers for helping us discover our wildlife together.
Emerging from the polar vortex and a foot of snow, we couldn’t help but reminisce on summer days for January’s #SnapshotSaturday! This summertime buck from Iowa County was nominated by Zooniverse volunteer TJPer.
Continue classifying photos on Zooniverse and hashtagging your favorites for a chance to be featured in the next #SuperSnap blog post. Check out all of the nominations by searching “#SuperSnap” on the Snapshot Wisconsin Talk boards.
Whether you’re enjoying ice fishing or a fisher enjoying the ice, happy Snapshot Saturday!
Interested in hosting your own Snapshot Wisconsin camera? Visit our webpage to find out how to get involved: https://dnr.wi.gov/topic/research/projects/snapshot/.
For January’s Science Update, also featured in The Snapshot monthly e-newsletter, we explored the accumulation of Snapshot Wisconsin photos over time and how the number of photos taken fluctuates with the seasons. To date, our data set contains more than 24 million photos, and their content is a vital component of the Snapshot Wisconsin project.
The bar chart above indicates that over half of the photos are blank. This can be attributed to the fact that our cameras contain a motion trigger function, which is designed to capture wildlife as it moves through the frame. However, this mechanism only detects movement and cannot differentiate between animals and vegetation. This means that on windy days during the spring green up period, thousands of blank photos can be captured. Occasionally cameras will malfunction and continuously take blank photos without being triggered by motion. This issue was more prevalent with earlier versions of our cameras; the model we currently use does not take as many blank photos. Additionally, over time volunteers have learned that trimming vegetation in front of their camera helps prevent blank photos.
Every day at 10:40AM, the cameras are programmed to record a time lapse photo. This is not only to document the “spring green up” period and the “fall brown down” period, but also to sync ground-level measures of greenness with satellite data. These photos are primarily used by our partners at UW-Madison and compose 7% of our data set.
It is not uncommon for our trail camera hosts to trigger the camera themselves during check events, which is the cause of most of the 3% of photos that are tagged as human. Although these photos are removed from the data set prior to analysis, they can be helpful in instances where the camera has been recording photos with the wrong date and time. A photo of a hand in front of the camera combined with the date and time reported by the volunteer at each check event are enough for us to adjust the date and time for the whole set of photos.
Twenty percent of the Snapshot Wisconsin photos are untagged, meaning they have yet to be classified as blank, human or animal. Many of these photos will be sent to the crowd sourcing website, Zooniverse, for classification. We hope to implement a program to automatically classify photos to work through this backlog as well.
Finally, about 14% of Snapshot Wisconsin photos are of confirmed animals. In the graph above, we have broken down which species appear in these photos. Deer are by far the most common species, appearing in about two-thirds of photos, followed by squirrels, raccoons, turkey, cottontail rabbits, coyotes, and elk. The remaining 8 percent of animal tags are divided up across 34 categories including other bird, opossum, snowshoe hare, bear, crane, and fox. Elk may have a higher proportion of triggers than expected because Snapshot Wisconsin cameras are placed more densely in the elk reintroduction areas than in other areas of the state.