The following piece was written by OAS Communications Specialist Rachel Fancsali for the Snapshot Wisconsin newsletter. To subscribe to the newsletter, visit this link.
If you are interested in branching out as a volunteer scientist, there are plenty of other opportunities to explore. The Snapshot Wisconsin team wanted to highlight some of the other exciting programs that our volunteers and their loved ones may be interested in. After all, volunteer scientists play an important role in more than just wildlife research.
The state of Wisconsin has a long history of volunteer science programs. The DNR has an extensive list of its own volunteer science programs and partner projects, including programs like the Wisconsin Bumble Bee Brigade and the Wisconsin Rare Plant Monitoring Program.
But what about programs outside of Wisconsin? There are plenty of national programs available on a wide variety of topics. If you are looking for something new to dip your toes in, check out these other programs:
Community Collaborative Rain, Hail And Snow Network (CocoRaHS)
- A community-based volunteer network of weather observers working together to measure and map precipitation (rain, hail and snow) in their local communities.
- CocoRaHS data is used by meteorologists, hydrologists, teachers, engineers and organizations such as the National Weather Service and the USDA.
- Visit the Wisconsin chapter of CocoRaHS.
- Volunteers report the calls of local frogs and toads heard during evenings from February to August, depending on the area and peak breeding season for local species. The data are then loaded into a public database, similar to Snapshot Wisconsin’s Data Dashboard.
- Partnered with the Citizen Science Academy (hosted by the Chicago Botanic Garden) and the National Geographic Society, FrogWatch USA data is used to help develop practical strategies for conserving frog and toad species.
- Visit FrogWatch USA to learn more.
- Map Earth’s oceans in this videogame that trains an artificial intelligence for a NASA supercomputer using FluidCam’s 3D images of the seafloor, the first instrument that can see through waves.
- Players identify coral reefs, other shallow marine environments and marine animals using 2D satellite and drone images and 3D reconstructions of underwater environments. Player classifications are used to teach the convolutional neural network (CNN) called NeMO-Net and help scientists better understand and protect coral reefs globally.
- To dive in, visit NASA NeMo-Net.
The Secchi Dip-In
- Operated by the North American Lake Management Society, this program collects water clarity measurements from rivers, lakes and estuaries to track water quality changes across the continent. Over the past 20 years, the database has accumulated more than 41,000 records on over 7,000 individual waterbodies.
- Volunteers are taught how to take water clarity measurements primarily using a Secchi disk unless the water body is a river or stream that would require a turbidity tube or black disk. Data is primarily collected in July, but the program does accept data year-round!
- Visit the Secchi Dip-In project site, then spend a day on the lake.
We certainly appreciate our volunteers at Snapshot Wisconsin, and we know these programs also appreciate their volunteers. Whether you want to expand your citizen science portfolio into finding collection water samples, listening to frog songs or teaching an AI, there are plenty of options. Have fun exploring!
The following piece was written by OAS Communications Specialist Rachel Fancsali for the Snapshot Wisconsin newsletter. To subscribe to the newsletter, visit this link.
You now know that Snapshot Wisconsin has contributed to important research not only statewide, but also nationwide with Snapshot USA. But did you know that over the past year and half, Snapshot Wisconsin has been contributing to an international collaborative art exhibit?
One Snapshot volunteer took on the challenge of running a special camera trap to contribute to the University of Zurich Graduate Campus’s Triggered by Motion project. The project will be creating an immersive, walk-through pavilion where visitors will be able to experience the biodiversity of wildlife from 14 countries around the world, and video footage of north woods Wisconsin wildlife will be on display for the world to see!
Connecting Science, Art, and the Public
The University of Zurich (UZH) Graduate Campus focuses on engaging with the public through events and exhibitions, utilizing its cross-faculty platform to create collaborative exhibitions that connect science, art and the public. The project Triggered by Motion is one of several collaboration projects that will be featured in the overarching Planet Digital exhibition, which explores the digital transformation of our world.
In the field of wildlife research, trail cameras are an excellent example of digital transformation in research. As many Snapshot volunteers already know, trail cameras are a non-invasive method, allowing a glimpse of wildlife behind the scenes. The goal of the Triggered by Motion project is to give a unique perspective on how researchers use camera traps to learn about the world, bringing the audience closer to this research method.
Each trail camera video for the project will condense a year’s worth of footage into a 20-minute time-lapse. Then the videos will be synchronized, so that daylight will slowly move from one screen to the other, circling around the pavilion to imitate the rotation of the earth.
In June 2020, UZH was referred to Snapshot Wisconsin. At the time, there was another trail camera in southern California, but UZH was looking to diversify its North American captures. The teams from UZH and Snapshot Wisconsin were able to connect and discuss the possibility of Snapshot Wisconsin participating in the international project.
Snapshot Wisconsin checked all the boxes for Triggered by Motion: it’s a well-established project, located in the northern half of the U.S. and operates year-round. Also, the cameras that Snapshot uses normally take still photos that fulfill the project’s data needs, but they are capable of capturing video footage. What really set Snapshot Wisconsin apart from other Triggered by Motion participants is our program’s applied research focus, with Snapshot data contributing to wildlife decision support.
With that, Snapshot Wisconsin became a part of the Triggered by Motion project. Now it was up to the Snapshot team to find a volunteer and set the modified camera.
Finding a Volunteer and a Camera Site
When it came time to choose a Snapshot volunteer to work with UZH, volunteer coordinator Claire Viellieux knew just the right person. “I met Blayne Zeise at the last in-person volunteer recognition event in 2019, and he has a good record of checking cameras and uploading in a timely manner,” Viellieux said.
After talking with Viellieux, Blayne Zeise was happy to help. “I had actually asked her at the volunteer event about adding another camera anyways,” Zeise said.
Zeise had already been running his own personal trail cameras on public lands for a couple of years before joining the Snapshot Wisconsin program in 2018. “I started out with a couple of $30 cameras from Walmart and started using them on public lands, then worked my way up from there,” Zeise said. He heard about Snapshot Wisconsin through some of Snapshot’s yearly advertising and decided to give it a try. “I thought it would be nice to have a better-quality camera with a lockbox on it, especially on public land,” Zeise said.
Zeise is very familiar with several public lands in the Marathon and southern Langlade County areas. His own cameras have been monitoring wildlife by river crossings on the Red River in Langlade County and Plover River in Marathon County. Zeise monitors his Snapshot Wisconsin camera in a fishery area just south of Antigo in Langlade County.
This familiarity with the landscape was a huge factor in Zeise’s decision on where to put the camera. “It’s mostly birds and deer at the river crossings,” says Zeise, “but there’s a larger diversity of animals at the other site [the fishery area].”
However, while biodiversity of the location was a large factor, it wasn’t the only one. Zeise knew that he may have to check batteries more often with capturing video footage, making it imperative that the location is easily accessible in all seasons. “The location I picked is a short hike, and there is still a lot of animals that pass through there,” Zeise said.
A Rough Start
Unfortunately, right off the bat, there were some roadblocks to deployment.
When setting up a Snapshot camera for filming at the office, Viellieux noticed the camera couldn’t meet the criteria set by UZH. To avoid motion blur and distortion once on the big screen exhibit, the video footage needed to be captured in 60 full frames per second with a 1920 x 1080 resolution. The Snapshot Wisconsin cameras, suitable for Snapshot Wisconsin’s research objectives that uses a large photo database, were not designed to meet that high of criteria for filming. Zeise tried one of his own personal cameras as well, but also had no luck.
UZH staff still wanted Zeise and Snapshot Wisconsin to be a part of the project, so they purchased and mailed a camera for Zeise to set up. After a small setback getting the UZH camera to film at appropriate times, Zeise’s next challenge was monitoring the camera’s battery pack with the extra demand filming had on battery life. “It just sucks up so much energy doing 30 second video every half hour during the day, and 15 second video at night,” said Zeise.
Most other Triggered by Motion trap sites were using solar packs to power the cameras. Zeise’s concern with this solution was how easy it would be for someone to walk off with the solar pack, especially being located on public lands. For most of the year, it was not difficult at the fishery area to change the rechargeable batteries that most Snapshot Wisconsin cameras use. With the rechargeable batteries, Zeise had to change them every three days.
Zeise’s main battery challenge would be in the north woods’ snowy and bitter winters; changing the rechargeable batteries every three days, or more frequently because of the cold, was not going to be efficient. He made the switch to lithium batteries, which meant changing batteries every two weeks. “Better than trudging through the snow!” Zeise joked.
Once the weather warmed back up, Zeise switched back to the rechargeable batteries. The system worked well for the year that Zeise collected data.
Capturing the Best of Wisconsin Wildlife
Zeise’s decision to record at the fishery area was spot on. A large variety of species were seen in the video clips including bear, bobcat, foxes, deer, coyotes and more. Zeise also saw a few neat interactions between species, such as the apparent squabble between a ruffed grouse and a pileated woodpecker (see screen capture below). UZH would also occasionally ask Zeise to confirm what animal was captured. “One time they asked me, ‘what are those really blue colored birds?’, said Zeise. “They were blue jays! I guess they don’t have them over there [in Switzerland].”
What Zeise found most interesting about using video is being able to see how animals used the area. “I was really surprised by how much the deer relied on that area for browsing,” Zeise said. “I even asked Emily [at Snapshot] if there was a way to ID the plants that the deer were using. She recommended a plant ID app, and I was able to ID species such as black ash, bitternut hickory, and black walnut.”
Operating a different kind of camera also brought new findings. “I was kind of surprised with the video that the coyotes were not spooked by it. With some of the Snapshot Wisconsin cameras, they hear the click and just about jump out of their skin,” Zeise observed.
The UZH camera, a Bushnell Dual Core No-Glow, is designed to remain inconspicuous. “They call it a no-glow, but it’s really like a hard black plastic filter to help hide the infrared. The coyotes and foxes probably see it, but the deer may not,” said Zeise.
With the completion of data collection, UZH was able to construct the exhibit. The project ended with 22 camera traps in 14 countries around the world, enlisting the help of 29 researchers and seven citizen-scientists to monitor the traps. The Triggered by Motion project is at the very center of the Planet Digital exhibition, and the physical exhibition premiered Feb. 11, 2022 at Museum für Gestaltung Zürich. The exhibition will stay at the museum until June, when it will be packed up and shown across the world. The dates and locations of the traveling exhibit are still to be determined.
However, a digital publication of the entire Planet Digital exhibition is available, and the Triggered by Motion project page can be viewed here.
Hopefully, the exhibit will make its way to the U.S. at some point, and we can walk through Snapshot Wisconsin and Zeise’s contribution to an international project! “If it travels to the U.S., I would definitely like to go see it in person,” said Zeise. “I think that was one of the coolest parts, just to be a part of a big project, with three locations in the U.S and over 20 worldwide.”
“I get to keep the camera too,” Zeise said, “It’s a pretty sweet deal.” Zeise mentioned he already has plans for the camera, including deploying it at one of the river crossings he monitors. There’s a spot where a lot of blue heron hang out, and he wants to capture that action.
The Snapshot team is honored to have played a part in connecting Zeise with this international project, and we are lucky to have great volunteers, willing to go beyond just hosting a Snapshot camera.
A big thank you goes to Blayne Zeise for all his help and really taking the reins on monitoring an extra special camera!
View the entire Planet Digital exhibition here.
The following piece was written by OAS Communications Coordinator Ryan Bower for the Snapshot Wisconsin newsletter. To subscribe to the newsletter, visit this link.
For the last three years, Snapshot Wisconsin has been contributing to a similar citizen science program called Snapshot USA, and Snapshot USA recently reached an important milestone worth celebrating. They released their first publication! Congratulations, Snapshot USA!
In honor of Snapshot USA reaching this milestone, the Snapshot Wisconsin team wanted to highlight this fellow citizen science project and share with our volunteers a lesser-known way that Snapshot Wisconsin data is being used.
What is Snapshot USA?
Snapshot USA is a national effort to bring together trail camera data from across the country and learn about what drives the distribution of mammal species within the United States. Snapshot USA takes a similar approach to Snapshot Wisconsin, having people classify trail camera photos to generate usable data for science. The main differences are that Snapshot USA is a nationwide effort and is focused entirely on mammals.
Snapshot USA was organized in 2019 by scientists from the North Carolina Museum of Natural Sciences and the Smithsonian Conservation Biology Institute. They asked fellow researchers, citizen science programs (including Snapshot Wisconsin) and private citizens to upload and classify their trail camera photos. Much to everyone’s excitement, over 150 people and programs participated in the effort.
Better yet, people contributed photos from 110 locations across all 50 states, proving that there are people all over this country who value efforts like Snapshot USA and Snapshot Wisconsin.
Snapshot Wisconsin’s Contributions
For our part, the Snapshot Wisconsin program was thrilled to support a fellow citizen science project. We submitted data from 2019 and 2020, and we are working on submitting data from this last year as well. It is important to us to support other programs like Snapshot USA and build up science together.
Every year, Snapshot Wisconsin has contributed data from around 10 of our trail cameras in the Clam Lake elk camera grid. Snapshot USA required at least ten cameras clustered within a 5km area, so only a few areas of our camera grid like the elk camera grids met the requirement.
Despite limitations in which cameras we could include, the Snapshot Wisconsin team is glad that we were able to contribute to this effort at all. Jennifer Stenglein, one of Snapshot Wisconsin’s lead scientists, said, “Snapshot Wisconsin is not set up to have areas with clustered cameras. We made a special exception for the elk grid because the data are used to monitor the growing elk herds across the state. Fortunately, the elk grid matched the minimum requirements to participate.”
Stenglein also mentioned how important it was to her personally that Snapshot Wisconsin contributed to this nationwide effort. “As a scientist, having open data is huge. There is so much trail camera data out there, but it’s [isolated] to specific programs or people. Snapshot USA created a place for trail camera data to come together and be available. That allows scientists to ask questions we couldn’t before, like how climate change is impacting species at a national level.” Stenglein is excited to see what other researchers do with the compiled data.
How Snapshot USA Operates
In addition to sampling populations from across a wider scale than Snapshot Wisconsin, Snapshot USA samples from all major habitats and development zones found within the United States. When a new collaborator joins the program, they select the combination of setting (Urban, Suburban, Rural, Wild, Other) and habitat (Forest, Grassland, Desert, Alpine, Beach, Anthropogenic, Other) that matches their camera site.
Our volunteers may notice that some of these site combinations differ from what Snapshot Wisconsin uses. For example, urban deployment does not fit Snapshot Wisconsin’s criteria for setting up a camera. Stenglein thought that the addition of urban areas adds an interesting element to the dataset, but it shows a fundamental difference in what Snapshot Wisconsin and Snapshot USA are trying to capture.
Next, collaborators upload their photos from a specified time window. In 2019, Snapshot USA collected photos from the 14-week period from August to November. Once uploaded, collaborators could start classifying photos, similarly to how our camera hosts do it.
One important difference is that Snapshot USA puts all their photos through a second round of classification – this time by an expert. Expert review happens within Snapshot Wisconsin as well, but only for the species we’ve learned are classified with lower accuracy. Our accuracy analyses have shown that volunteers do a great job of accurately classifying most species, especially the most common species, so Snapshot Wisconsin only expertly classifies the photos of the hard-to-classify species and rare species. Besides, Snapshot Wisconsin would not be able to expertly classify its 60+ million photos. However, this extra step is possible for a program like Snapshot USA.
“Limiting the time window for data collection is really common in trail camera studies,” said Stenglein. “I don’t know if there is any perfect time window for Snapshot USA to choose, since you will always miss something. However, it does make sense for them to select a window of time. It would be too challenging to collect a whole year’s worth of data, let alone have an expert review.”
Once both rounds of classifications are done, the data are assembled into a package and prepped for release in the form of a new publication. This type of publication is called a “data paper” because its main purpose is to release a new dataset for others to work with.
“It’s a cool, new trend in science for data papers to come out,” said Stenglein. “I’ve seen more effort being put towards proper archiving of data. Researchers can use these datasets to test their own hypotheses and come up with new and exciting insights into wildlife distributions in the USA. I think this is where research needs to be, so it’s encouraging to see this trend.”
2019 Data Is Released
In April 2021, Snapshot USA officially published their 2019 dataset. The paper was published in the scientific journal Ecology and had around 100 different authors.
In total, the dataset included photos from 1,509 cameras across 110 locations, and all 50 states and the District of Columbia contributed data. The dataset had 166,036 observations (photos) and found 83 unique mammal species. Seventeen bird species were also detected, which impressed Stenglein, but the project wasn’t looking for birds, only mammals.
“All together, that’s an impressive number of species detected,” said Stenglein. “Trail cameras aren’t set up to see all species equally. Birds, for example, often spend most of their time above the line of sight of cameras, so capturing 17 species of birds is pretty cool.”
Snapshot Wisconsin’s contributions included sightings of just over 20 of the 83 mammal species found by Snapshot USA. Given the small area that the photos came from, seeing 20 species is a healthy number. If we were able to use more of the grid, that number would have been much higher.
The paper reported that the three most detected species nationwide were white-tailed deer, squirrels and raccoons, in that order. Snapshot Wisconsin’s own data visualization tool, the Data Dashboard, also shows a similar trend, with white-tailed deer and squirrels being the top two species detected in Wisconsin. Racoons weren’t third, but they are high on the list.
Coyotes were the most widespread species detected across the nation, which surprised some of the Snapshot Wisconsin team. However, Stenglein explained, “It may be because there is only one major species of coyote. Deer and other common animals change species as you go across the country. Mule deer, white-tailed deer and black-tailed deer each have different ranges across the U.S.”
Stenglein was proud of the Snapshot USA team for pulling this effort together. As one of the main researchers for Snapshot Wisconsin, Stenglein knows how much work it is to collect photos from hundreds of sources and extract usable data from them. Stenglein mentioned that it is great to see another citizen science project release their first publication. “Our Snapshot Wisconsin team only has so much capacity to work on decision-support tools, so it is cool to know that these data will be used in more ways and by more people.”
Stenglein also mentioned that there is a second publication in the works already. This publication will release the 2020 dataset. It’s nice to see such a quick turn around time for the second publication.
“The peer review process can easily take months to years,” explained Stenglein, “so there will always be a lag. However, I expect that this first lag will be the biggest. I’ve already seen process improvements on the data uploading side. They’ve moved to a more efficient process, which really helps.”
Stenglein believes Snapshot USA has expanded its data collection to Europe as well for the 2021 season, which could offer some interesting comparisons for researchers.
Stenglein’s final thoughts for the Snapshot USA program were:
“I’m so impressed that they pulled this off. We know from Snapshot Wisconsin how difficult it can be to keep things running smoothly, especially when it comes to IT infrastructure and solutions. I wish Snapshot USA all the luck as they continue to expand their program, and I look forward to working with them each year. What you’ve accomplished is impressive. Remember that.”
The following piece was written by OAS Communications Coordinator Ryan Bower for the Snapshot Wisconsin newsletter. To subscribe to the newsletter, visit this link.
Continuing with the bird theme, the Snapshot Team wanted to highlight one of the five specific species that can be chosen while classifying photos: the sandhill crane. At the same time, the team wanted to use the new 2020 data on the Data Dashboard, so they decided to do both!
The team invited fellow DNR researcher, Jess Jaworski, Assistant Waterfowl Research Scientist within the Office of Applied Science, to look through the sandhill crane data on the Data Dashboard. Jaworski is currently working on waterfowl research, but she previously worked with cranes.
Jaworski’s graduate research involved studying the nesting behaviors of cranes in Wisconsin. “My graduate research was focused on the nest success of the reintroduced whooping crane population at the Necedah National Wildlife Refuge. The majority of my work was monitoring incubation behaviors of both whooping cranes and sandhill cranes under duress of an avian-specific black fly. This fly caused a wide-spread and synchronous abandonment of nests.” Jaworski put up several trail cameras at nests and went through thousands of photos to monitor behaviors at those nests; Not that different from what Snapshot Wisconsin does.
A Bit Of Background On Sandhill Cranes
Before we dive in, let’s make sure everyone knows a bit about sandhill cranes. Jaworski was happy to share her knowledge of sandhill crane behavior.
Wisconsin’s sandhill cranes are part of the Eastern population of migratory sandhill cranes, and there are over 70,000 individuals in this population. As implied by the term “migratory,” they don’t spend the entire year in Wisconsin. Jaworski explained that these birds spend the winter down South. Around mid-March, they come back north to their breeding grounds and establish pair bonds.
Sandhill cranes are typically a monogamous species, so they will find a mate and pair off if they don’t already have one. “They usually try to find a pair bond within up to two years of birth, and they start nesting at three to six years in open marsh wetlands, although sandhill cranes can nest in a wide variety of habitats. They hopefully will hatch within a 28-day incubation period and fledge their young within two to three months. Once that is done [usually in September/October], they migrate back to their wintering grounds.” Come the next March, they start the cycle over again.
Diving In To The Data Dashboard
Jaworski was curious how well the trail camera data would match the description she gave above. The team sat down with her to see. At first glance, Jaworski said the data seemed pretty consistent with what she knows about their behaviors and where cameras were located around the state.
Take the map of detections by county, for example. Jaworski pointed out a higher percentage of crane detections in the southeast quadrant of the state. “That is consistent with their habitat [preferences]. They typically nest in open marshes, and the map matches where I know wetlands exist in the state,” said Jaworski. “Dodge County has cranes in the Horicon Wetland Area, for example. To the northwest, there are more cameras picking up these birds, potentially from the Crex Meadow Area. There is a large amount of birds in Adams County nearby to Juneau County where birds nest at the Necedah National Wildlife Refuge, which is where I did my graduate work.”
Jaworski also looked at detections by the ecological landscape, a clickable option to the left of the map. Instead of counties, the map is blocked out into 16 regions with unique ecological attributes and management opportunities. “Generally, the southern and eastern sections of the state have more open, wetland areas, so I’m not surprised there are more detections in those areas. There are also a lot of agricultural fields here too,” said Jaworski.
“Sandhill cranes can adapt easily to human-made landscapes like agricultural fields, and it isn’t uncommon to see them nesting in smaller wetlands near agricultural fields, for example. If there are a lot of cameras in these areas, then there will be more sightings of sandhill crane.” In contrast, the northern part of the state tends to be more forested land, so the southeast is the ideal habitat for a crane looking to build a nest.
Activity By Month And Hour Of The Day
So far, the detection locations matched what Jaworski expected to see, but one of the more interesting features of the dashboard is the breakdown of detections by month and by hour of the day. How well would the data hold up?
Jaworski started with the month data and immediately zeroed in on the lull in detections during the winter months. “This is exactly what I’d expect to see,” said Jaworski. “These migratory cranes are down south in their winter grounds [during these months]. When you get to March and April, I see a heightened activity pattern from cranes migrating back and nesting. Then, there is a lull again later in the year, as they start migrating back south.”
Jaworski also noticed that the migration south occurs over a much longer period of time than the migration back, as seen by a more gradual decline in detections in September and October. “That could be a product of different nest initiation times or different successes/failures throughout the nesting period. If birds nested earlier, then they will have fledged their young earlier than others and potentially leave the state sooner.” Alternatively, pairs who failed to successfully rear a fledgling may start over again if there is time. These pairs wouldn’t be able to migrate as early as pairs who succeeded on their first try, and that may lead to more detections later in the year.
The Snapshot team discussed how the placement of cameras also can influence the detection of species like the sandhill crane. Not all species spend their time in areas that are easy for trail cameras to watch. Not many Snapshot cameras overlook the center of a lake or marsh, which can lead to biases in detections for certain species.
However, Jaworski did confirm that cameras set up near-ideal nesting habitats will be much more likely to detect cranes. Cranes can be seen while they are up and about from their nests, looking for food, or when adults swap who is incubating their nest.
Jaworski also looked at sandhill crane activity throughout the day. “In the morning hours, they will leave their roosting areas. When pairs are forming pair bonds, they will do dawn unison calls. You can often hear them in the early morning hours, [and the calls are quite distinct]. Throughout the day, they are probably feeding and moving about the wetland, so detections are more common then. In the evening, they return to their roosting site for the night.”
All in all, there were pretty clear patterns in the activity graph, and those patterns match what Jaworski expected to see. There is a small amount of variation between the hours of the daytime, but Jaworski didn’t think those peaks and valleys represented any meaningful behaviors for sandhill cranes. Jaworski said, “It is hard to determine fine-tuned patterns throughout the day. It could simply be from a bias in where the cameras are placed.”
The 2020 Data Are Accurate And Consistent
Jaworski and the Snapshot team adjusted the date slider in the left-most column of the dashboard to look at only the 2020 data. The 2020 data showed all of the same patterns that we’ve already mentioned and is consistent with what we know about where cranes are distributed across the state. “It shows that there is nothing unusual about this past year that indicated sandhill cranes are moving from their range or aren’t where you would normally see them occur,” said Jaworski.
Jaworski played around with the date slider some more and looked at each of the other years’ data individually. She noticed that the number of detections increased each year, starting from 2017. “It is really cool that detections are increasing. It says that interest in the program is also increasing,” said Jaworski. “Snapshot’s expansion each year provides more information about where these birds are located. Each year, you will find more detections, which helps inform research for this species. I also really like that there is a record of that data so that we can go back and analyze it if any questions arise in future studies.”
Jaworski’s Parting Thoughts
Before everyone parted ways, Jaworski shared some final thoughts with the team about the program and its impact.
“It’s wonderful that a program like Snapshot exists. If somebody is interested in knowing what is going on with a particular species, it is awesome that Snapshot allows people to find that information through the Data Dashboard. It is a great opportunity for people to get involved.
Additionally, that type of cooperation between researchers and those who aren’t in research is invaluable and helps inform [our] research. Its great from a research perspective and a curiosity perspective when we collaborate.
Plus, getting involved [in citizen science] can spark an interest in a science career! A lot of us in research didn’t initially start out that way. Many of us started out as citizens who observed something interesting or maybe as kids who tagged along with our parents while they were doing outdoor activities. Looking at species or finding out what a scientist did inspired us.
My family comes from a natural resource background. My dad started out as a forester, and my mom worked as a park ranger and a boating officer in New Mexico. I tagged along with my mom quite often when she was giving presentations at the nature center. We were outside recreating a lot, camping and fishing. It had a big influence on my life and my career choice.”
Jaworski encouraged more people to check out the Data Dashboard and learn something new about one of the species available. The Snapshot team suggests looking at the data in a similar way to how Jaworski did, piece by piece and thinking about what a species might be up to in different areas and at different times. It is a great way to think about the lives of these species. Plus, with the addition of the 2020 data, there is more data than ever to look at.
The following piece was written by OAS Communications Coordinator Ryan Bower for the Snapshot Wisconsin newsletter. To subscribe to the newsletter, visit this link.
A male American woodcock stretches his wings skyward in a courtship display, a great-horned owl strikes an unknown target on the forest floor and a male northern cardinal duteously feeds his newly fledged young.
These are moments in the lives of birds captured by Snapshot Wisconsin trail camera photos. Until recently, however, many of these avian images were hidden within the Snapshot Wisconsin dataset, waiting to be uncovered by a team of bird enthusiasts. Unlike how they normally watch birds, from behind a pair of binoculars, this time they were behind a keyboard.
When Snapshot volunteers classify an image, they normally can choose from a list of around 40 wildlife species. Only five of these species are among Wisconsin’s 250 regular bird species: wild turkey, ruffed grouse, ring-necked pheasant, sandhill crane, and the endangered whooping crane. These five species are options on the list because they either are of special management interest within the Wisconsin DNR or are easier to detect by Snapshot Wisconsin cameras.
The rest of the bird photos are classified into a catchall group, called “Other Bird.” Until recently, the “Other Bird” images were considered incidental images, but the increasing size of this category caught the attention of the Snapshot Wisconsin team. In fact, “Other Bird” is the second most common classification of the six bird categories, only second to Wild Turkey (Figure 1, Panel A), which comprises over a quarter of all bird photos.
The team reached out to the Wisconsin DNR’s Bureau of Natural Heritage Conservation (NHC) to brainstorm ideas on how to leverage the “Other Bird” dataset, which had amassed 150,000 images at the time and was still growing.
Planting A Seed Of Collaboration
During their discussion with the NHC, the idea was brought up that these “Other Bird” images could contribute to the Wisconsin Breeding Bird Atlas II (WBBA II). The WBBA II is an enormous, multi-year field survey to document breeding birds and their distribution across the state. Information like the frequency of breeding and which areas birds are breeding in help the DNR see changes in breeding status for many bird species. This information can also be compared to data from the previous survey (from 1995 to 2000) and sets a benchmark for future comparisons as well.
The current survey uses data collected from between 2015 and 2019. Coincidentally, the earliest Snapshot images are from 2015 as well, so the dates of the survey aligned quite well. This collaboration seemed like a good fit.
However, there are some important differences between data collected from birding in the field and from images captured by Snapshot trail cameras. For example, many birds spend much of their time in the canopy, outside the camera’s field of view. Additionally, birders often use sound cues to identify signs of breeding in the field. Trail camera images do not contain these types of breeding cues. Lastly, certain breeding behaviors can be too fleeting to observe from a set of three images.
The team wasn’t sure yet if the trail camera photos would truly contribute much to the WBBA II.
A Collaboration Was Born
Members of the Snapshot Wisconsin and NHC teams ran a test of the “Other Bird” photos. They reviewed a small, random subset of images and learned that many of the birds could be identified down to the species level. The teams also found enough evidence of breeding, such as sightings in a suitable habitat (for breeding) or the presence of recently fledged young. Both teams decided to go ahead with the collaboration and see what they could find.
The full dataset was sent to a special iteration of Zooniverse, called the Snapshot Wisconsin Bird Edition, and birders began classifying. All of the “Other Bird” images were classified down to the species level, as well as assigning a breeding code to each image. In just over a year, the large collection of bird photos was classified, thanks to some dedicated volunteers.
The NHC’s Breeding Bird Atlas Coordinator, Nicholas Anich, extracted these new records and added them to the WBBA II. The atlas utilizes a statewide survey block system that is based on a preexisting grid from the United States Geological Survey. The survey block system requires that certain blocks be thoroughly surveyed in order for the atlas to have adequate statewide coverage, and many of the new Snapshot data points contributed to these priority survey blocks. Anich said, “[The Snapshot data] will be valuable information for the WBBA II, and we even discovered a few big surprise species, [such as] Spruce Grouse, Western Kingbird, and Whooping Cranes.”
In addition to these rare species, many of the high-value classifications were what Anich described as breeding code “upgrades.” The observed species already had been recorded in a given block, but the photos showed stronger evidence of breeding than had previously been reported. For example, an adult of a given species may have already been spotted in the area during the breeding season, but a photo showed a courtship display. The courtship display is stronger proof of breeding in the area than a single adult sighting.
How Useful Were the Snapshot Photos?
Both the (in-person) birding efforts and the trail camera photos picked up species that the other did not, so both approaches brought different strengths to the table.
One of the strengths of the trail cameras was that they are round-the-clock observers, able to pick up certain species that the in-person birding efforts missed. Anich said he noticed that nocturnal species (American Woodcock and Barred Owl) and galliforms (Wild Turkey, Ruffed Grouse) were more common in the Snapshot dataset than reported by the birders in the field, in certain areas at least. “Running into gamebirds was a bit the luck of the draw,” Anich said.
Both Anich and the Snapshot team agreed that the trail cameras were best used in conjunction with in-person surveys, rather than a substitute for each other because they each observed a different collection of species.
Insights Into The “Other Bird” Category
As a bonus for anyone who is interested in this project, the Snapshot team analyzed the photos classified for the WBBA II and created an infographic of the orders and families included. The photos included were captured between 2015 and 2019.
An immediate trend the team saw was that many of the birds were from species with larger body sizes, ground-dwelling species and species that spend time near or on the ground. For example, Anseriformes (ducks and geese) and Pelecaniformes (herons and pelicans) are the second and third most common order in the “Other Bird” category. The next most observed groups include woodpeckers, hawks, eagles, owls and shorebirds. While these birds may not spend all of their time near the ground, food sources for these species are often found in the stratum, an area where most trail cameras are oriented.
It was interesting that the most common order (comprising over half of the “Other Bird” classifications) was from the bird order Passeriformes (perching birds or songbirds). This order does not initially appear to fit the trend of ground-dwelling or larger-bodied birds. However, closer inspection revealed that the most common families in this order did fit the trend. For example, Turdidae (thrushes, especially American Robins), Corvidae (crows, ravens and jays) and Icteridae (blackbirds and grackles) comprised much higher percentage of the photos than any other families.
Thanks To Everyone Who Helped Classify Bird Photos On Zooniverse!
Overall, the Snapshot Wisconsin Bird Edition project was a huge success. In total, 154 distinct bird species were identified by nearly 200 volunteers, and over 194,000 classifications were made. The Snapshot Wisconsin and WBBA II teams extend a huge thank you to the Zooniverse volunteers who contributed their time and expertise to this project. The team was happy to see such strong support from the Wisconsin birding community, as well as from around the globe.
If you weren’t able to help with this special project, stay tuned for other unique opportunities to get involved as Snapshot continues to grow and use its data in new ways. If you contributed to the project, reach out to the Snapshot team and let them know what your favorite species to classify was.
The Snapshot Team is happy to announce that the data from 2020 are now available on the Data Dashboard. Explore the 2020 dataset yourself today!
Snapshot’s Data Dashboard is a data visualization tool that lets the public interact with the data collected from over 2,000 trail cameras spread across the state. The Data Dashboard first was made available to the public in October 2020 and showcased the data of 18 species. Since then, an additional species have been added to the list, and the Snapshot Team plans to add more over time.
One of the unique features of the dashboard is that it lets people choose which data they want to visualize. You can look at data from individual years by selecting the desired date range on the slider along the left side of the dashboard. Four distinct years (2017-2020) are available to peruse. When a new date range is selected, the map of Wisconsin will update and show only the data for the selected dates, allowing anyone to see trends over time.
Check out the 2020 data on Snapshot Wisconsin’s Data Dashboard:
Snapshot Wisconsin volunteers have been asking to hear about unique ways others engage with the program. Today, the Snapshot Wisconsin team highlights, not an individual, but a group that manages one of the longer-running Snapshot trail cameras – River Bend Nature Center (RBNC) in Racine County.
RBNC is an outdoor environmental education center that leases and manages about 80 acres of upland and lowland forest, as well as a six-acre prairie, from the county. River Bend’s primary mission is environmental education, conservation and sustainability with a variety of programs for all ages, ranging from little tikes to seniors.
Christa Trushinsky, Naturalist and Director of Education at RBNC, has worked at the nature center since 2016 and oversees their Snapshot trail camera. “I went to grad school for Environmental Conservation, so I’m very interested in exactly what Snapshot Wisconsin does, looking at the dynamics of land and the species that use it,” said Trushinsky. Trushinsky first heard about the program from a Snapshot Wisconsin team member she went to graduate school with and got in touch with her to learn more.
Little did Trushinsky know, that connection would later play a role in developing many of the nature center’s programs.
A Good Fit for River Bend Nature Center
River Bend has been hosting a trail camera for four years now and has found some intriguing ways to incorporate Snapshot photos into their teaching. “Snapshot Wisconsin is such a crucial tool for what we are trying to do here, especially for species that are elusive or nocturnal,” said Trushinsky.
Trushinsky said they often use Snapshot photos in their Skulls, Skins, and Scat program to help kids identify species that they wouldn’t normally be able to see. “Since some animals are nocturnal or very elusive, we can use the images to prove that these animals are out there [in the forest] and using the landscape,” explained Trushinsky. “Seeing proof of these animals in the neighboring forest makes them real to the kids in a special way. The animals are more than
something they see on TV – they are real and nearby.”
The trail camera pictures also act as a segue to the hands-on portion of the program, where participants look for animals and signs of animals (e.g. nests, burrows and tracks). “If we find an animal that can be handled, we talk to the kids about how to do so gently and appropriately,” said Trushinsky. Sometimes the children interact with an animal for the first time, such as feeling a slug’s sliminess or a snake’s scaliness. “That’s all part of it, showing them how to handle wildlife appropriately, as well as which to respect and stay away from.”
RBNC incorporates Snapshot pictures in other ways as well. Staff have introduced the concept of predator-prey relationships to children by showing time-lapse photos of predators tracking their prey. Trushinsky recalled an example of a doe walking by the camera, and a minute later, a coyote followed closely behind. Trushinsky uses Snapshot photos to start discussions about different relationship dynamics between the species seen on the camera.
Trushinsky has also taken Snapshot images off-site and given presentations at schools and colleges. To highlight examples of camouflage, she shows participants sets of pictures from the trail camera and asks them if they can figure out where the animal is and identify it. “Basically, I introduce it as, ‘Hey, this is Snapshot Wisconsin. You guys could be doing this on your property!’ I talk about what [species] we see at River Bend and take them through the process of classifying photos. Kids especially seem to get a kick out of it,” said Trushinsky.
Learning Lessons Themselves
While most of what RBNC does is focused on educating others, they have also learned more about he land they manage by hosting a Snapshot trail camera. Their trail camera has confirmed which species inhabit their land, as well as how the species use the land at different times of the year.
The RBNC trail camera is in a unique location, tucked away in a floodplain area of the lowland forest. During the spring season, the Root River surges, spilling over into a nearby pond, flooding the lowland forest. The flooding dramatically changes the landscape around the camera. Herons, wood ducks, mallards, and other birds can be found wading and swimming in the forest around the camera. Since RBNC’s camera looks out over the flooded area, they capture some great images that have excited birders who visit the nature center. “These are species you typically don’t see using a forest habitat. You might also see swimming muskrats or mink [while the area is still covered in water],” added Trushinsky. “It’s offered a great place to raise early season ducklings — with lots of cover.”
As the season shifts towards summer, the water drains, and a new batch of animals begins to use the area. Tall grass soon fills everything the camera sees, and species like deer move in. Does raise their fawns in the tall grass, and other little land creatures start to emerge.
Trushinsky said the trail camera pictures tell such a different story every season, with different animals showing up and using the land in their own unique ways. “The Snapshot camera helps us see what species are out there and if there are any novel or threatened species we need to be aware of. The presence of these species may even impact our land use plans,” said Trushinsky.
To date, RBNC’s camera has seen deer, opossums, raccoons, mink, muskrats, coyotes, mallards and great blue herons at this single camera location, just to name a few. They have also been able to identify certain butterfly and bird species (like the golden warbler) from the images, even though Snapshot doesn’t currently classify these species. The RBNC staff are hoping to see a river otter this year, but they haven’t seen one at this location yet.
Trushinsky shared her thoughts on joining Snapshot Wisconsin and the center’s unique camera location. Check out the video to hear her describe the camera in her own words.
Advice for Others
Trushinsky had some parting advice for other nature centers and groups who are considering hosting a Snapshot trail camera. “Snapshot is something very easy to get into and do. There isn’t that much of a time commitment needed. You can leave the camera out there and check it every three months. The biggest time commitment is just getting to the camera and classifying the photos.”
Trushinsky also shared some of the little tricks that she has discovered over the years.
- Make sure the camera is in a place where you already see signs of wildlife. You won’t capture many photos of animals if wildlife aren’t using that area.
- Put the camera in a location that is harder for people to get to, especially if you have people who visit your land. Whenever you go out there, you leave a scent, which can impact how animals use the area. It’s good to use the same route to the camera with each visit.
- Be ready to thaw a frozen lock in the winter. Trushinsky learned that one the hard way.
- Be prepared—wear mosquito repellent or longer layers in the summer and burr-resistant clothing in the fall. If you go through tall grass to get to your camera, always check for ticks in the spring!
- Be aware that there may be a lot of little bugs that like to make their home inside of the camera case. Bring a tool or rag to remove them if you don’t like insects.
- If you are using a tree to mount your camera, don’t forget to loosen the cable lock or strap on it – that allows the tree to continue to grow.
If you are thinking about hosting your own Snapshot trail camera, check out the Snapshot Wisconsin website or visit the Apply to Host a Trail Camera page! You never know what you might find in your area.
A few months ago, the Snapshot team said farewell to someone who has worked with the Snapshot Wisconsin team for several years. John Clare, a former graduate student at the University of Wisconsin-Madison, completed his PhD in December, 2020 and has moved on to a post-doctoral position at the University of California-Berkley.
While completing his doctoral degree, Clare worked in Drs. Ben Zuckerberg and Phil Townsend’s labs, and his research has helped push Snapshot Wisconsin to the next level, expanding the capabilities and reach of Snapshot Wisconsin. Although he played a behind-the-scenes role, one of a few students studying how to use Snapshot data in new and useful ways, his contributions to the team are appreciated, so the Snapshot team decided to share a piece of his research with those of you who follow this newsletter.
Clare first connected with Snapshot Wisconsin when current Snapshot team leader, Jen Stenglein, got in touch. Stenglein, Quantitative Research Scientist at the DNR and a leading member on the data analysis side of Snapshot Wisconsin, was interested in the sampling parameters of Clare’s Masters research, which also dealt with trail cameras. Stenglein hoped to learn from that project and apply lessons to Snapshot Wisconsin.
“I didn’t know about Snapshot Wisconsin until after talking with [Stenglein],” said Clare. “I later saw a posting for a PhD assistantship related to the program, and I applied. That is how I first got involved.”
Clare was one of the first graduate students working with the project. He initially helped get the program up, and later he started to sort through the data and deliver some useful results.
While we don’t have the space to cover everything he worked on for his dissertation, Clare and the Snapshot team wanted to share a small piece of Clare’s research with the volunteer community and showcase part of how Clare contributed to the project.
Leveraging Snapshot Data
A central goal of Clare’s dissertation was to develop strategies to better leverage the spatial and temporal capabilities of the Snapshot database. Clare mentioned that two unique features of Snapshot Wisconsin are that Snapshot operates both statewide and year-round. Many other monitoring programs can’t operate at such wide and long scales because it would be too resource intensive for them. Fortunately, Snapshot has the help of thousands of people across Wisconsin (and the globe) to overcome that resource barrier and operate statewide and year-round.
“[Using data from all over the state and from all times of the year], we can explore questions in ways we didn’t have the ability to before,” said Clare, and Clare investigated a few of these questions in his dissertation. Two of Clare’s research questions were what broad factors drive where species are distributed and how species are active across the year.
To answer both questions, Clare needed to build a special type of model that leveraged both spatial and temporal data at the same time. Not an easy feat.
Setting Up Clare’s Model
Clare needed a unique model that could account for how species are spatially distributed around the state and temporally distributed throughout the year. “I think it’s important to take advantage of both the spatial and temporal components at the same time,” said Clare. “The question isn’t just where are species located, but also how species are distributed at time x, time y and time z.”
Both the spatial and temporal scales were needed because there are components of the environment that vary strongly across space and time. Snow depth, for example, is not fixed over the course of the year. One week, there may be six inches, and the next week there may be twelve. Snow depth also varies spatially. A few miles could be the difference between seeing snow on the ground or not. Many environmental factors are highly dynamic and variable like this, so Clare needed to think of these factors within a model that accounts for both.
It is common for models to use one type of data but incorporating both is a challenge. The main challenge is having enough data (and data of the right types) to run this kind of analysis. Fortunately, Snapshot images have both location and time data attached to each image.
Another unique aspect of Clare’s model is that it considers multiple species at once. “We were pretty sure that individual species are distributed dynamically throughout space and time, but entire communities have not been heavily studied in the same way,” Clare said. “The appeal of using a spatial-temporal structure across the entire community is that we can explore which species are interacting with others at different parts of the state and at different times of the year.”
This concept isn’t new to the realm of modeling, but it is hard to accomplish. Researchers would need separate data for each additional species they added in the model. It can be hard enough getting data for one species, let alone multiple. However, that is where Snapshot shines best. Volunteers can tag up to 50 unique species in their Snapshot photos, so an equal number of species-specific datasets can be pulled and created from the larger Snapshot dataset.
“The advantage of a multispecies approach is that you can take into account the responses of each of those species, as opposed to modeling one species and assuming the results apply uniformly for other species,” said Clare.
Driving Distribution and Activity
Knowing he had the ability to answer his questions, Clare thought about which factors might be most influential across the entire community, in terms of predicting where species were located and how active they are. “We had a couple ideas about what these factors might be,” said Clare. “Some were related to seasonal variation like the amount of snow and the greenness of the vegetation.”
Snow depth can change substantially from day to day, even during the winter. Snow depth could dramatically impact how species move around and where food is available. Snow can even correlate to which species are even seen during parts of the year. For example, black bear behavior is often related to the winter, and thus with snow.
Wisconsin’s black bears sleep through the winter. Since winter is also associated with snow, black bear activity inversely correlates well (in Clare’s model) with snow. When there’s more snow on the ground, we are (most likely) deep into winter and see the least activity from black bears.
Another environmental variable that Clare was interested in was vegetative greenness. Vegetative greenness is, from space, how green the landscape looks. In the spring, trees will start to bud burst, and the grass will grow. The landscape itself will just be greener than the previous months, and more nutritional energy will flood into the food web. Vegetative greenness varies throughout the year and can impact how animals use the land, depending on when and where food is available.
For example, a black bear’s seasonal activity could reflect the cycle of vegetative greenness. Black bears maximize their activity at times of the year when there are more food resources around, either plants or prey. These times of the year may strongly correlate to peak greenness of the landscape, or so Clare theorized.
But you might be thinking, “Wait, can the Snapshot cameras measure vegetative greenness and snow depth from the trail camera photos?” The answer is possible, but more research is needed before we can use the cameras that way. Instead, Clare used daily satellite images of the state to calculate vegetative greenness and snow depth.
Linking Satellites with Snapshot Wisconsin
Clare used satellite images from NASA to measure snow depth and vegetative greenness. Part of Clare’s assistantship position was funded by a NASA grant whose purpose was to figure out ways to integrate a continuous stream of animal observations with a continuous stream of Earth observations coming from space. Between the trail camera data and the satellite data, Clare aimed to find connections that were meaningful to wildlife management.
Consider winter severity in deer population modeling, for example. Winter severity is already used by the DNR to predict the impact of winter on deer populations and plays a partial role in making harvest decisions for the subsequent fall. One hope of the NASA collaboration was to develop more integrated measures like winter severity for deer overwintering, especially ones that impact multiple species in similar ways.
Using the images from satellites passing over the state, Clare derived data on land use, surface temperature, vegetative greenness and snow depth. All of these variables were tested across spatial and temporal scales for all classifiable species.
Confirmation and Surprise
Clare wanted to share two results from his dissertation with the Snapshot community. One of these results was a confirmation of what he expected, but the other was surprising and took longer for him to wrap his head around.
“I wasn’t surprised that snow depth was a major negative driver of species activity,” Clare said. “We expected that because snow provides a refuge for some species [and a signal for other behavioral changes like hibernation].” These behavior changes cause sightings of these species to drop off during the winter and strengthens the negative correlation between snow depth and species activity. Snow is also associated with winter, when species tend to be less active to conserve energy resources.
What was more surprising was that the peak period of species activity was not associated with the peak of the growing season, or when the land was at its greenest. Clare expected these two peaks to match because there would be a maximum amount of food on the landscape. However, after some rethinking, Clare came up with a new theory about why peak activity wasn’t at peak greenness. “What we [now] think is happening is that animals don’t have to move around as much during the peak of the growing season. They don’t have to go as far to find food. It is all in one
aisle,” Clare said.
As for linking satellite data with wildlife data, snow depth and vegetative greenness both were the best predictors of species distribution and activity out of the environmental variables Clare tested. Even though vegetative greenness didn’t function how he predicted it would, it still was a good predictor of community activity and distribution. Both of these variables showed promise as potential satellite-based metrics that NASA and the DNR can use to better predict how the environment is impacting the greater wildlife community.
Now that Snapshot Wisconsin has a few years of data across most of the state, Snapshot will start looking into broader trends like year-to-year weather variation and how species habitat associations may vary from year-to-year.
“As we anticipate global changes, including more extreme events like polar vortexes, heavy rain and droughts, there is a need to understand how species react to different weather phenomenon. By looking at how species are distributed at finer time scales, we can start to address those types of questions. That wasn’t the exact focus of my research, but my research can help us start to quantify what [counts] as an extreme event for different species,” explained Clare. However, that work will be done by someone else, since Clare has graduated and moved to California.
Clare took a moment to reflect on his years working with Snapshot Wisconsin. Clare said, “My favorite part has been seeing the broader project move from a concept to an operating system. It has been really exciting to see that dream come to fruition. Most of that credit is due to the folks on the Snapshot team like Jen Stenglein and Christine Anhalt-Depies.”
Clare was also appreciative of the community of volunteers that sustain Snapshot Wisconsin. “It has been rewarding to see so many Wisconsin residents get involved,” said Clare. “I’ve been blown away with how smoothly and effectively it all has worked.”
With Clare moving on to the next step of his career, the Snapshot team wishes him the best and thanks him for helping the program get set up and running, as well as his contributions on the research side of Snapshot.
Thanks John Clare, and good luck!