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Southwest Wisconsin CWD, Deer & Predator Study Newsletter

Issue 3: December 14, 2017

Winter is finally here! Our seasonal field crew has started training to begin the next adult deer collaring season later this month, and predator trapping is already off to a great start.

In this issue, we look at fawn survival results, go in-depth on a volunteer-assisted deer study and we get into the field with a video on coyote CSI.

Click the titles below to read this issue’s full articles and view our videos.

This study is part of the Governor’s CWD Initiative. Our goal is to comprehensively examine factors that could impact deer survival and deer population growth in Southwest Wisconsin.

Learn more about our study design by visiting our website.


Summer fawn survival numbers are in

Last May and June, WDNR researchers and volunteers collared 91 newborn deer fawns to better understand deer recruitment. What is recruitment? Simply put, it’s the number of new deer that are added to the population each year. Why are we interested in deer recruitment? Recruitment is one of the most important factors that affects population growth, and it determines how much mortality – whether from hunting, CWD or other causes – the herd can sustain. Recruitment is determined by pregnancy rates, litter sizes and fawn survival.

Pregnancy rates and litter size of adult does don’t vary much, but pregnancy rates of juvenile does (does getting bred in their first rut and giving birth around their first birthday) are variable. Also, fawn survival can vary tremendously. How and why these two metrics vary from year to year and place to place is complicated and interesting. In future articles, we’ll dig into the many facets of deer recruitment, but for now let’s check back in with the fawns we collared last spring.

We collared 91 fawns. Of those, 45 were male and 45 were female. (The sex of one fawn was not recorded.) We collared our first fawn on May 16 and the last on June 14. May 29 was our biggest day with 13 fawns collared. They weighed in at an average of 10.5 pounds. The largest and smallest fawns were both bucks, and they weighed 18.7 pounds and 4 pounds, respectively.

From the time the fawns were collared through the end of August, WDNR technicians checked each deer every day using radio telemetry to determine whether each fawn was dead or alive. Current GPS collars are too big and heavy for fawns, so we use smaller, lightweight VHF radio collars that require technicians to track each fawn daily. Once September arrived, we scaled back our checks to once a week. When it appeared that a fawn died, the crew conduced a CSI-style investigation to try to determine how the fawn died. (In future newsletters, we will describe how we monitor deer survival and conduct our mortality investigations.)

So what did we find with our first summer of fawn survival monitoring? Through September, up to 32 of our 91 fawns died. Why do we say ‘up to’? Because sometimes there is uncertainty as to whether the fawn actually died. On eight occasions this summer, only the collar was found with no additional information present to indicate exactly what happened. One time, the collar was found hanging from a barb-wired fence. In this instance, we’re pretty sure the collar got hung up and the fawn wriggled its way out. Other times, it wasn’t so clear – a collar just lying on the ground, no blood, no bite marks on the collar. Did it just slip off? Did the fawn get killed and then the predator (probably a coyote) carry the collar away? Either is possible.

Questions such as these are standard in wildlife survival studies. If we assume that the eight open cases were really mortalities, then 32 fawns died. If we assume none of those died, then 24 fawns died. The reality is probably somewhere in the middle. As we gather more data throughout the study, our analysis will account for these unknown cases.

Here is the breakdown of those we know died: Coyotes are the probable cause of death for 12 of the fawns; bobcats likely took four more. Three died of starvation, and three more died of disease or injury. A domestic dog killed one fawn. The final confirmed death was the result of haying equipment.

What does this mean? First, let’s remember that this is just year one of four years of fawn survival data collection, so we’ll be collecting a lot more data before we can make firm conclusions. Initial impressions are that this is pretty high survival, which probably reflects the mild winter that preceded fawning.

Our previous study found that fawn survival depended partly on winter severity. This study was conducted in Northern and Eastern Wisconsin, where we found that fawn survival varied from 27% to 71%. It will be interesting to see how fawn survival in Southwestern Wisconsin compares based on location and variability in winter weather.

Volunteer with us

Lastly, we could not have collected this data without the army of volunteers that joined us in the field for fawn capture and the generous landowners who granted us access to fawn search. We encourage all of you to get out with us next year. Late spring is a beautiful time of year to be out in nature, it’s a lot of fun and you get to support deer research and management! If you’d like to be added to the volunteer information email that will go out next spring, send an email to Caitlin Henning at caitlin.henning@wisconsin.gov.

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Predator trapping up and running fast

Coyote trapping video

To fully understand the drivers of deer mortality, we’re also tracking two top predators in the study area: coyotes and bobcats. When our first trapping season ended in April, we had seven coyotes and seven bobcats with GPS collars on the air. Predator trapping started up again in mid-October, and we have rocketed to 38 coyotes in a matter of weeks! Bobcats are more elusive and difficult to capture. We’ve had 12 successful bobcat collarings so far, and we’re determined to find more as the season continues.

While it does appear bobcats are players in fawn predation in this study, coyotes are number one. Will this pattern hold? We’ll see. Are there places where fawns are more at risk of being preyed upon than others? Is fawn survival lower where CWD prevalence is higher? Stay tuned! We really look forward to digging into this data and sharing the results with you.

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DMAP cooperators help DNR study deer & forest health

Each year in mid-November, the Noll family return to their farm in Buffalo County for the nine-day gun season. The Nolls have been farming and hunting here for generations, and even though the family has spread out, they return to the homestead every year for deer season. “My dad was one of five siblings,” said Mark Noll, “The whole clan has been coming back since the 1940s. Four generations come together for the hunt.”

All told, the Nolls take 25 to 30 deer each year, and everyone participates in the processing. This season, for the second year running, they’ll add a few extra steps to their hunt. The Nolls will collect field data from each deer they harvest as part of a three-year study being run by the Office of Applied Science (OAS) in conjunction with the Deer Management Assistance Program, or DMAP, to understand the relation between habitat and deer health.

“We can match each deer to its exact harvest location thanks to DMAP volunteers. Based on those measurements, we will be able to estimate the quantity and quality of food that is available to deer on those properties and across the state,” says Amanda McGraw, an OAS researcher helping to coordinate the study.

Dana Sharp is a DMAP collaborator from Jefferson County and another hunter volunteering with the study. This fall he took his father and five-year-old son along on one of his hunts to show them the data collection process. “My dad thought it was pretty cool, said Mr. Sharp, “He always guessed at the weight and age. They never thought about taking it to that next level with data. My son was like, ‘is that really the heart?’ He thought it was pretty cool too.”

This fall, 75 DMAP cooperators have volunteered to weigh and measure their deer, pull a tooth for aging and assess their condition through a dozen other metrics. Then they mark the deer’s exact harvest location on an aerial map of their property. Together, the Office of Applied Science anticipates that volunteers will contribute measurements on 300-500 deer to the study. Later, DNR staff will visit DMAP properties where deer were harvested to make measurements of available deer browse.

DMAP volunteers for the study receive deer body condition reports for each harvested animal. We provide participants with individualized reports that summarize results and let people see how their deer compare to other deer submitted from DMAP cooperators across the state. “It’s nice to be able gauge the age of the animal, what kind of condition he was in. It just adds to the hunt. It’s a whole other level. The data I collected last year and this year really help with my ability to understand the age class of the animals I’m seeing, whether they’re good eating,” Mr. Sharp said.

The measurements taken by Mr. Noll, Mr. Sharp and other study volunteers help us know the condition of the deer at harvest. Knowing, for example, antler size, whether they’re stocky or lean, small or large for their age in conjunction with harvest location can help us understand location-specific relationships between deer and their habitat.

Researchers refer to this overall assessment of deer health as fitness. Fit does are better able to birth and provide for their fawns in the spring, and fit bucks will have more muscle and bigger antlers for the rut. As for fawns, a high level of fitness improves their chances of surviving their first winter when temperatures drop and food is scarce. Habitat quality is one of the primary drivers of deer fitness, and one of the primary drivers of habitat quality is how much forage the forest provides. By studying deer fitness alongside the quality of habitat around harvest sites, we will be able to provide better management recommendations for healthy deer and healthy forests.

There is concern that deer health is lower than expected in some regions of Wisconsin, and we suspect declining habitat quality contributes to lower-than-expected deer condition. By researching a variety of deer-habitat indicators, we can determine which provide the most information about the health of our forests and the deer that live in them. Perhaps there is a strong relationship between rump fat and browse quality, or then again, there could be a strong tie between litter size and forage quantity. Collecting this broad range of data will lead us to the most informative indicators. This will then allow us to develop metrics that will be used to improve management tools so that we continue to have healthy forests and healthy deer across Wisconsin.

None of this work would be possible without the committed volunteers from the DMAP program. In the 2016 trial run, they collected high quality field data. “They were clearly attentive to their work, and they submitted pretty meticulous data for us to analyze,” said Amanda McGraw.

Since 2014, the DNR’s Deer Management Assistance Program has helped landowners around Wisconsin manage their properties to increase the numbers deer and other wildlife. Both Mr. Noll and Mr. Sharp have been DMAP collaborators since the program’s launch, and both just renewed their membership for another three-year term. Asked about the value of the program, Mr. Sharp said, “Nothing in this world compares to following a forester and a biologist through your woods and having them explain the different things they’re picking out. It’s amazing. You can take your deer hunting and management to the next level.”

Landowners who are interested in becoming a part of DMAP can visit the program’s website for more details and contact information.

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A better measure for deer recruitment

Driving a back road in Iowa County in late September, Beth Wojcik pointed to the tree line as she spotted three deer browsing a harvested corn field. She rolled to a stop and pulled out her binoculars to get a better look. Across the field stood a trio of young bucks, and they paused their meal to look toward our van. Before they could change their minds and run for the woods, Wojcik had taken out a range finder, gauging how far away the bucks are from where we stopped. Then back in the van, she noted our GPS coordinates and took notes on her observation before moving on, scanning for more deer.

Wojcik and a team of surveyors covered 78 routes spread across 12 counties in August and September. Together they covered each route multiple times, filling in the same standardized field journal with their observations. They note the GPS location of their stopping points; distance to the deer they see; the type of cover the deer is occupying as well as whether they are does, fawns or bucks.

This work is part of the DNR’s annual roadside fawn-to-doe survey, a study that has been running for decades to estimate the average number of fawns born to a doe each year. Now Wojcik is helping to move the survey into the 21st century. The numbers this survey generates are used to determine deer recruitment, an important metric for measuring the herd’s population growth.

The idea to improve the fawn-to-doe ratio survey began in the DNR a few years back. The DNR had begun an effort to develop deer metrics that County Deer Advisory Councils can use to make deer harvest and management decisions. Dr. Daniel Storm, Deer & Elk Research Scientist with the DNR, collaborated with Dr. Tim Van Deelen from UW-Madison about what a better survey could look like. Then they brought in Wojcik, a veteran of deer and predator research projects around the country, to fine tune and implement the new survey for her master’s project.

“Driving around Wisconsin, you might see deer. Sometimes you see them, and sometimes they’re not there. Casual observation gives us an impression that there are a certain number of deer,” said Wojcik. But casual or inconsistent observations won’t work to generate truly rigorous data at the population level. Working with the DNR, Wojcik is developing a standardized survey that can produce more reliable fawn-to-do ratio estimates at the level of the deer management unit.

One of Wojcik’s first challenges was to map the routes. Each of the 12 counties has four to six routes. “They need to be back roads, secondary roads so that we can safely drive at 20 miles per hour and stop frequently,” Wojcik explained. But the routes also need to represent the types of cover found in each county. “Then,” Wojcik said, “I put a half mile buffer on each side of a route. Let’s say a doe has a square mile range. I want to make sure we’re not double counting between routes, so their ranges can’t overlap.”

Designing the field journal and training a fleet of observers came next, and the new survey was on the road for the Fall of 2016. Now in her second year, Wojcik has fine-tuned the survey design and is preparing to analyze the data it has generated.

“It’s always challenging work,” says Wojcik, “When the corn is high, we miss some deer, and once everything is brown and dormant, they camouflage so well with their cover. Making sure we have consistent notetaking between drivers and routes is always a challenge on a survey this big, so I’m looking at how we can make that process better as well.”

Efficiency is also important to Wojcik’s design. How many times do surveyors need to drive each route? Her analysis will try to uncover “what is the minimum amount of cost and effort needed to get really good data?”

Wojcik is excited to see the new and improved survey continue. “I’m interested in science that has a direct application for management,” she said, “I like knowing that this work can have a direct benefit for wildlife managers and the public because it gives us a better understanding of the deer herd.”

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Predator cluster investigations

Deer are often easy to spot from the roadside, especially during the fall rut, but predators like coyotes and bobcats are more elusive and difficult to study. That’s why GPS collars have been such a breakthrough in carnivore research. When we collar an animal, we can track their day-to-day movements and learn more about their behavior.

Part of the Southwest Wisconsin CWD, Deer and Predator study’s mission is to learn more about how coyotes and bobcats interact with deer. Do these predators put significant pressure on deer in the area? Is there seasonal variation to their interactions? How do these predators’ ranges overlap with each other and with the deer herd? These are just a few of the research questions that collars help us answer.

Monitoring daily movements tells us a lot about an animal’s range and habits, but to know how they interact with deer, we need to get into the field. Here again, GPS collars make our work so much more precise than the radio telemetry used in previous studies. The predator research team is developing a computer model to evaluate clusters of GPS points, multiple locations in close proximity to each other, and relating those clusters to predator events.

Being on the move is the norm for coyotes and bobcats, who cover expansive ranges. If they stay in one spot for several days or weeks, we have good reason to suspect there’s something of high value keeping them there. Perhaps it’s a den, or maybe it’s a predation site.

Over the summer and into the fall, Nick Forman, predator coordinator for the study, and members of the field crew went into the field to investigate cluster sites. They searched the woods for bones, tweezed tufts of hair out of the brush, and belly-crawled into former den sites in search of information on our collared animal’s behavior.

Once we’ve analyzed the data, we’ll be able to share our preliminary observations, but for now check out our video from one of last summer’s cluster investigations:

Cluster investigation video

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Last revised: Monday December 18 2017