Before joining the Snapshot crew, I worked on a long-term fisher (Pekania pennanti) monitoring project in a beautiful section of Northern California, called the Klamath-Siskiyou eco-region.
Our study focused on one of two endemic populations of fishers on the West coast found in Northern California and Southern Oregon. Fisher populations declined in the 1800s and early 1900s due mainly to trapping and habitat loss. This study was undertaken 11 years ago in response to a petition to list the fisher as a federally endangered species (which was ultimately overruled).
The goals of the project are to better understand the size and robustness of the western fisher population, explore species interactions between meso-carnivores (such as gray fox and ringtail), and investigate fisher responses to wildfires. It’s a very dynamic and exciting project to work on, with lots of valuable questions to explore.
We used baited, corrugated plastic boxes at 100 historical locations to track our fisher populations. The boxes were fitted with a metal track plate covered in contact paper and ink, along with a glue strip that caught hair from critters passing through the box.
Every day for three months, my co-worker and I would set off into the woods to collect track plates and hair snares. This usually meant 10-12 hour days of driving around the Klamath National Forest, punctuated by steep hikes to retrieve samples in the forest.
Even though we never outright saw the feisty fishers, we began to expect “visits” from them at our boxes. We collected tracks and hair from the same boxes every week. The fishers certainly appreciated the chicken and cat food we left as bait for them! Our weekly box checks became like meeting up with old friends. At one site, I collected a female’s tracks and hair every week for two months. She never made a mess of the bait or destroyed the box (which I greatly appreciated)!
All in all, I had a terrific experience that helped me to understand the importance of non-invasive sampling (i.e., sampling that does not require capturing animals – like the camera trap method used in Snapshot Wisconsin)!
If you are still curious about the non-invasive sampling boxes, check out this video of the box setup.
The Snapshot Wisconsin team
Last week the Snapshot team traveled to Milwaukee to participate in the Midwest Fish and Wildlife Conference. As a sponsor of the conference, Snapshot Wisconsin hosted a booth where we met and chatted with wildlife folks from around the Midwestern U.S. We had a lot to show attendees, including some fun flashcards that the team put together to help people work on their classification skills. We were honored that our booth was chosen Best in Show!
We also organized a Citizen Science symposium called “Collaboration with the Public for Natural Resource Research, Management and Conservation.” The symposium focused on practical advice for citizen science project managers. Topics included protocol design, participant recruitment and training, data management, and evaluating program outcomes. Presenters included WDNR project coordinators, a developer from Zooniverse, and the new director of the UW-Madison Arboretum.
Christine Anhalt-Depies and Professor Tim Van Deelen
One of our Snapshot Wisconsin team members, Christine Anhalt-Depies, was chosen as the graduate student recipient of this year’s Leopold Scholarship from the Wisconsin Chapter of the Wildlife Society. Christine was chosen based on her commitment to the wildlife profession and her exceptional commitment to her professional development in a way that honors the memory of Aldo Leopold. Congratulations Christine!
Our new Snapshot Wisconsin mascot, Snappy the Snapshot Beaver, was a hit with students at the conference. We were offering up a gift for anyone who posed with Snappy for a selfie and many students were happy to participate.
The following post is by a guest blogger, Caitlin Henning, Communications Specialist at the Wisconsin Department of Natural Resources Office of Applied Science. Currently, her primary project is the WDNR’s landmark Southwest Wisconsin CWD, Deer & Predator Study. Thanks for the information on this project, Caitlin! Read More…
Our July #SuperSnap was all about fishers, and we’re just going to keep on rolling on the fisher train! This science update was inspired by recent comments on a photo of a fisher in central Wisconsin. The location of the photo might cause confusion if you base where fishers *should* be on the range map we have posted. The map shows fisher range extending to only the very northern part of the state:
Whereas we’ve seen fishers on Snapshot Wisconsin cameras in counties pretty far south:
In the case of a species like fisher, which was reintroduced to Wisconsin in the 1950s and expanded its range quickly, static distribution maps go out of date quickly. This brings up a larger point about range maps being inaccurate because they are based on old, incomplete or faulty data. We provide range maps to give volunteers an indication of where they are more likely to find a certain species, but these maps are by no means perfect. The fact that we do not have very good statewide data on the distribution of most species is indeed a major reason for starting a project like Snapshot Wisconsin!
Note that the above map shows counties where we’ve seen Snapshot Wisconsin photos correctly classified as fisher. Many of the gray counties do not have any Snapshot Wisconsin cameras and so we do not have any photos there yet. This is not to say there are no fishers in the gray counties!
Thanks to a dedicated effort by our volunteers, Wisconsin DNR staff and University of Wisconsin students, we were able to classify all of the elk photos from 2016!
This Science Update features data from the Clam Lake elk area only, due to a lack of elk photos from the Black River Falls area. From GPS collar information, we know that many of the Black River Falls elk prefer to hang out outside of our camera area (perhaps they are bashful?). When we have more Snapshot Wisconsin cameras in the counties surrounding Black River Falls, we hope to have enough data for a Science Update on those elk as well.
There were 120 cameras active in the Clam Lake area in 2016, capturing 3,996 triggers containing elk. After grouping consecutive triggers showing the same elk, we ended up with 305 unique elk events.
We graphed daily activity patterns of antlerless elk and bulls from the 305 unique elk events. Overall, elk were most active between 6 and 9 AM and 5 and 6 PM. Antlerless elk were most active around dawn and dusk, while bull activity peaked later in the morning and evening.
We also graphed monthly elk activity throughout 2016. Because not all of our cameras were active during the entire year, we corrected photo hit rate based on the percentage of cameras active each week. The image below shows this corrected photo count for antlerless elk and bull elk throughout 2016.
The marked spike in bull activity at weeks 36 through 40 indicates the annual rut period. That period corresponds to a sharp drop off in activity level for antlerless elk; cows tend to stay put during that period while bulls move around more. (Curious about why this might be? Click here for more information on elk life history and mating behavior.) The trail cameras give us the ability to pinpoint the time frame of the rut period more precisely than we were previously able.
Because Snapshot Wisconsin trail cameras put a time and date stamp on each photo, we are able to capture the diurnal (daytime), nocturnal (nighttime), and crepuscular (active early and late in the day) behavioral patterns of different species. The graphs below show daily activity patterns using the 24-hour clock for three categories of animals captured on Snapshot Wisconsin trail cameras in Iowa and Sawyer Counties from June 1 – September 7, 2016.
Bears were most active during the day and used the midday hours more than any of the other large mammals, while coyotes and deer showed the strongest crepuscular behaviors:
Porcupines were most active in the early morning hours before sunrise. Mustelids were uniquely active during a short portion of the early daytime hours:
Grouse activity was fairly steady through the day while turkey activity increased as the day progressed:
Food for thought: why might it be beneficial for animals to be more active during certain times of the day and not others?
Each year, the WDNR uses fawn and doe counts from August and September to calculate a fawn-to-doe ratio and estimate the size of the deer herd in Wisconsin. We get the fawn-to-doe ratio by dividing the number of fawns by the number of does. In 2015, the statewide fawn-to-doe ratio was 0.89, meaning there were about 9 fawns for every 10 does. Of course, this number varied a lot across Wisconsin.
Counts submitted by the public via Operation Deer Watch and by WDNR biologists are the primary data we use to calculate fawn-to-doe ratios. This information is very useful but somewhat biased, since observations are made during daylight hours and mainly along roadsides. Snapshot Wisconsin trail cameras give us a new way to count deer because the cameras operate all the time and are placed in more natural spaces.
In our first attempt to use Snapshot Wisconsin trail cameras to calculate fawn-to-doe ratios, we used Snapshot Wisconsin photos from August 2016 that were classified as deer by trail camera volunteers in Iowa and Sawyer Counties. There were 211 deer pictures from 13 cameras in Iowa County and 331 deer pictures from 13 cameras in Sawyer County. This is a very limited sample but it let us look for early patterns.
One thing was immediately obvious: we see the same does and fawns over and over again at each camera site. Before we could come up with any accurate estimates, we would have to account for repeated counts of the same deer. One method we tried was to use the maximum number of fawns and does seen in any single photo from each camera site. This leaves us with a much smaller number of deer observations at each site, but ensures that we do not over-count. When using this method, we end up with preliminary fawn-to-doe ratios between 0.7 and 1.0 that are close to what we would expect.
Stay tuned for more on fawn-to-doe ratios and other results as we continue to add photos and classifications!