This month’s #SuperSnap was nominated by @eaglecon. Thanks for this fantastic photo series of a pileated woodpecker (Dryocopus pileastus) in action from Waupaca county! Fun fact: the pileated woodpecker’s brain is completely protected by a reinforced skull and neck. This protection is important since the woodpecker pecks into trees for carpenter ant snacks and “drums” for mates. (source )
Check out all the nominations by searching “#SuperSnap” in Talk. Hashtag your favorite photos for a chance to be featured in the next #SuperSnap blog post.
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…
Thanks to everyone who participated in our first annual #SuperSnap contest! First prize goes to the 3 bear cubs featured above. This photo was taken in May of 2017 in Sawyer County. Thanks to @Lefthooklooie for nominating these cute bear cubs!
Second prize goes to this happy buck! This buck was captured on camera in Iowa County in November 2016, thanks to @Snowdigger for this nomination.
Third prize goes to this wintery wolf! This wolf sequence is from an Iron County camera and was taken in March 2017. Original #SuperSnap nomination by @SteveMeurett.
While up north recently, the Snapshot Wisconsin Team had the opportunity to go out and check cameras in the Flambeau River elk monitoring grid. The weather was a balmy 27 °F, and the fresh air was much needed after long hours of travel. We split up into two groups of two, and headed out in separate directions to check cameras in different areas of the grid. Flambeau River State Park is a known dead zone for cell service, so we chose a time to reconvene before we split up. Both teams took two full hours longer than expected to complete their camera checks – which at least brought us back to the van at the same time! During the morning adventures, the team was reminded of some of the challenges unique to winter camera checks:
Waterproof boots will always be your friend. Melted snow, recent rainfall, or areas that are naturally wet may “dampen” your overall camera checking experience. If you have a pair of waterproof boots, or thick socks, you may want to consider bringing these along! Soggy shoes are never fun, especially in below freezing temperatures.
Tall waterproof boots (or waders) will always be your friend. No matter how waterproof your boots may be, they will only protect you for as high up as they cover. Also, what appears to be a puddle may actually be more like a miniature lake.
If you have a padlock for your camera, it may be frozen. If moisture gets inside the padlock and freezes, spinning the numbers can be difficult or impossible with fingers alone. To be on the safe side, bring an appropriate tool along to help thaw your padlock such as lock deicer, windshield deicer, or hand warmers.
Budget your time appropriately. Even if you think that your hike to your camera will only take thirty minutes, budget some wiggle room for inclement conditions. If you know you won’t have cell phone service in the woods, tell a friend or family member of your plans – this may include where you are parking your car, your intended route, what time you expect to be back, and what time to take further measures if you don’t return by. It’s easy to underestimate how long a camera check may take if you are comparing to previous checks during nicer weather.
Double check your GPS coordinates. Sometimes your phone and your personal GPS will tell you to go opposite directions, and you will find yourself circling around a swamp for thirty minutes. Sometimes it may be a technological glitch, but likely it will be human error. It never hurts to double check your GPS coordinates before venturing into the woods, especially if you know you won’t have good cell phone service, and especially if it’s cold outside.
Getting outside to check cameras was an overall great experience – and makes us even more appreciative of our volunteers and all their efforts they put forth for the project. Whether classifying photos online or hosting trail cameras, we couldn’t do this without all of you! Thank you!
It has now been a year and a half since Snapshot Wisconsin launched to the public in the first two counties, Iowa and Sawyer County! To commemorate the wonderful volunteers who have been with us since the beginning, the Snapshot Wisconsin team recently traveled to Dodgeville and Hayward to hold our very first volunteer recognition events.
The evenings included locally catered dinners, a presentation about project updates and scientific findings, as well as certificates and a prize basket drawing. It was great to reunite with volunteers that we haven’t seen since trainings, and to have face to face contact with those who are used to hearing from us solely by phone or email.
Overall it was a wonderful experience, and something that we look forward to putting together again in the future. We hope all who attended enjoyed their evening, and as always we welcome any and all feedback!
As many volunteers know, one of the primary purposes of Snapshot Wisconsin is to get a better handle on where species are located throughout the state. We now have enough pictures classified (and a reasonable handle on the effects of error within the classification process) to be able to start the process.
The essence of this exercise is to model associations between 1) locations where animals are and are not found on trail cameras, and 2) environmental or spatial characteristics at those camera locations. As noted in a previous blog post, in order to effectively map predictions about animal distribution, we need to have spatially explicit environmental variables, many of which are derived from satellite imagery. Examples of environmental variables include land cover, seasonal patterns in plant productivity/greenness, snow cover, and the intensity of night-lighting, which is a good index for human activity.
Below are a collection of maps resulting from our first attempt at mapping statewide species distributions based on Snapshot Wisconsin data.
A couple things to note:
- How we think about commonness or rarity depends on the species being considered. For example, “less common” for turkey may mean an area is visited by only a few turkeys over a couple weeks, while “less common” for bear may mean that the area has not had a bear visit for a year or more.
- There are some imperfections. In particular, the tip of the Bayfield peninsula tends to exhibit some patterns that are probably wrong. Mapping will continue to be an iterative process based on our best metrics.
The below maps are accurate enough to be useful, but there’s always room for improvement. We hope that volunteers find this first round of analysis interesting, and maybe even useful for classifying.
With Season 6 in full swing, it has been a tough decision choosing this month’s #SuperSnap! Thank you to @momsabina for nominating this playful fawn series from Manitowoc County. With frigid temperatures on the horizon, we couldn’t help but throw it back to sunny springtime days!
Check out all the nominations by searching “#SuperSnap” in Talk (most recent photos will appear on the last page!) Continue hashtagging your favorite photos for a chance to be featured in the next #SuperSnap blog post.
Here at Snapshot Wisconsin Headquarters, we’re up to our ears in data and we’re scurrying around to compile, assess and analyze what we’ve got. We’ll be posting updates soon on what we’ve got so far (including some really cool maps!). In the meantime, new photos just keep on rolling in, and it’s time for more classifying!
A few new features for Season 6:
- Fewer photos of common species! That means fewer deer, squirrels, turkeys, raccoons, and bunnies proportional to the total number of photos.
- New retirement rules that will retire all photos (especially deer photos) more quickly
- Streamlined interface. Instead of getting a screen showing your classifications, you’ll pop straight to the next photo after pressing “Done.”
- By and large, we’ve corrected wrong dates and times on the photos. There are still a few (literally just a few) that will have a clearly wrong year (1934 or 2021), but there shouldn’t be any that say nighttime when it’s really day, or winter when it’s really summer.
Snapshot Wisconsin trail cameras currently collect about 1 million photos per month, and we’re planning to add a lot more cameras over the next few years! That’s A LOT of photos, and we can’t send them all to Zooniverse. Our trail camera hosts get the first look at the photos they collect, and they do an excellent job helping us identify photos that don’t need to go to Zooniverse. Starting this season, their efforts will allow 75% of the total photos to bypass Zooniverse, leaving just 25% – the cream of the crop.
We hope you enjoy the season with these changes in place! Thanks again for all you do.
Here in the northern hemisphere, the autumn days are getting shorter and shorter. It’s getting darker earlier in the day, and our eyes have to adjust to dim conditions.
Without the help of fire or electric lights, we humans are pretty bad at night vision. Unlike many other animals, our eyes lack a specialized reflective surface that aids sight at night and in low light environments (caves, under water, etc.). This surface, called a tapetum lucidum, located behind the retina, acts as a mirror to reflect light photons.
Light enters the eye and hits photo receptors in the retina. Some light, however, will miss the photo receptors and pass past the retina. The tapetum lucidum reflects that light and gives it a second chance to hit the photo receptors and illuminate the scene.
Some of this light is reflected back out of the eye, which is why some animals’ eyes appear to glow in nighttime trail camera photos. All types of camera flash, even the low-glow infrared flash of the Snapshot Wisconsin cameras, can reflect off the tapetum lucidum and cause an animal’s eyes to light up. (This is not the same as the red-eye effect seen in photos of human eyes which is caused by light reflecting off the blood vessel-rich choroid behind the retina.)
There is variation in mineral content and structure of the tapetum lucidum, which causes eyeshine in different species – and even different breeds of dog – to look different. Eyeshine may appear white, blue, green, yellow, pink or red. It’s too bad nighttime trail cam photos are in black and white and we can’t see these color differences!
Animals having a tapetum lucidum (not extensive):
- carnivores: canids and felids
- grazing animals: sheep, goats, cattle, horses
- fruit bats
- ray-finned fishes and cartilaginous fishes including sharks
- owls and a few other nocturnal birds
- crocodilians including alligators (bright red eyeshine – spooky!)
Animals lacking a tapetum lucidum (not extensive):
- higher apes including humans
*I’ve read that squirrels don’t have a well developed tapetum, but flying squirrel eyes certainly glow in our nighttime trail cam photos. Anyone who can shed some light on this mystery, please leave a note in the comments!
- What causes the red eye effect? Yale Scientific Magazine.
- Candid Creatures: How Camera Traps Reveal the Mysteries of Nature. Johns Hopkins University Press.
- Why do animals’ eyes glow in the dark? NPR All Things Considered.
- Comparative morphology of the tapetum lucidum (among selected species). Veterinary Ophthalmology 7(1):11-22.
- Crystals of riboflavin making up the tapetum lucidum in the eye of a lemur. Letters to Nature.
- Ocular comparative anatomy of the family Rodentia. Veterinary Ophthalmology.
In this post, I’ll be talking a little bit about my experiences with citizen science and camera trapping projects prior to joining Snapshot Wisconsin.
Before I decided to become a wildlife conservation professional, I was involved with citizen science projects as a volunteer. I found pleasure in natural history, making observations and collecting data for scientists. This was my contribution to saving the world, I thought! As a volunteer, I have done large mammal surveys in India, from counting tiger prey species to collecting carnivore scat. I learned a lot from participating in these projects. More than anything else, I think they provided a welcome distraction from my day job as a software programmer *chuckle*.
I was also involved with conservation groups in the Western Ghats landscape of India. One project I am proud of being associated with is the Bisle Frog Watch. Every year citizen scientists congregate at Bisle (a tiny village in the Western Ghats) to learn about amphibian ecology and identify them in the wild under the guidance of researchers. What is heartening is that over a period of 6 years, we have made a checklist of 36 species of amphibians!
Apart from mammals and amphibians, I also love bird watching and regularly submit my bird lists to eBird.
Some of these experiences with citizen science gave me the confidence that I too can do scientific research. And, that’s also how I decided to pursue a Master’s degree.
Talking about my camera trapping experiences, I worked on a trail camera survey in Ecuador for my Master’s capstone project. I worked with an Ecuador based non-profit called Ceiba Foundation for Tropical Conservation. We set up a total of 16 camera traps on several private properties and nature reserves in the Manabi province of coastal Ecuador.
Whereas the most common species in Snapshot Wisconsin is the white-tailed deer, in my project in Ecuador it was the agouti. (Although white-tailed deer have been recorded in the study site in Ecuador, they are uncommon in those parts of the world.) Whereas in Snapshot Wisconsin we see bobcats, in Ecuador we frequently recorded wild cats like ocelot, margay and jaguarundi.
In fact, I am even leaving an identification challenge for some pictures from Ecuador. Feel free to leave your guesses( along with the picture number) in the comments below. I shall post the answers soon-ish!
All in all, it is exciting to be working on the Snapshot Wisconsin project – with the many citizen scientists who host camera traps across Wisconsin and many others from around the world classifying pictures – knowing we have something in common.
Picture credits: Frog watch pictures – Deepika Prasad; Camera trap pictures from Ecuador – Ceiba Foundation for Tropical Conservation.