Phase 2: Data Analysis
Making Sense of Data from Over 1,200 Animals
Fieldwork during phase 1 of the Southwest Study saw data collection from over 1,200 captured animals (adult deer, fawns, coyotes and bobcats) in northern Iowa, Dane and Grant counties. This region is where chronic wasting disease (CWD) was first detected in Wisconsin in 2002 and has maintained a high CWD prevalence over the years since. With fieldwork now complete, scientists have entered into phase 2 of the project, data analysis, in order to fuel the study's research objectives. These objectives included:
- Estimate survival rates as a function of time, CWD infection status, age and sex. Document the breakdown of causes of mortality (i.e. starvation, disease, predation, hunting) and how these differ by CWD infection status and sex.
- Integrating estimates of survival of CWD-infected deer and recruitment (pregnancy rates and fawn survival) into an age-structured population model to determine deer population response across a gradient of CWD prevalence.
Analyzing the Data
A lot of data from a large sample of deer (810 adults and 323 fawns) was required to create a model that can help us understand the long-term impacts of CWD on Wisconsin’s deer herd. To do this, data points collected included the following:
| Data Point | Collection Method | Purpose |
|---|---|---|
| Age | Observing tooth wear and replacement (i.e. permanent teeth replacing juvenile teeth) Cementum annuli (ring patterns found in teeth) | Teeth can help distinguish between fawns, yearlings and adults. Both collection methods allow scientists to track how survival and CWD-infection patterns might differ across age classes. |
| Sex | ID at capture | Knowing the sex of these deer allows scientists to track how survival patterns might differ between males and females. |
| Antemortem (pre-death) CWD Status | Biopsy of Rectoanal Mucosa-Associated Lymphoid Tissue (RAMALT) during deer captures | This information allows scientists to track which deer already had CWD upon capture. |
| Time to Fate of Adult Deer | GPS Collars | Knowing how long each deer survived after collaring allows us to estimate survival rates, which tell us the percentage of deer surviving over a given time period. |
| Time to Fate of Fawns | Very High Frequency (VHF) Collars | Knowing how long each fawn survived after collaring allows us to estimate fawn survival rates, which are a strong determinant of recruitment (the number of deer added to the population each year) and can be highly variable. This metric helps inform overall herd productivity and resilience. Collared fawns that survive 1 year of life then begin to provide information on adult survival. |
| Mortality designations | GPS collars and VHF Collars, mortality investigations including necropsies (animal autopsies) | Mortality designations tell us how each deer died over a given time period. Because GPS and VHF collars alert scientists when a collared animal is deceased, mortality events can be separated into cause-specific categories after a mortality investigation, often including a necropsy, is performed. |
| Postmortem (post-death) CWD Status | Retropharyngeal (back of throat, just under jaw) lymph nodes | Determines the CWD status of deer at the time of death; informs infection rates and disease-status specific survival rates. |
By using a statistical model that will integrate the above information, researchers can estimate survival rates as a function of time, CWD infection status, age and sex. They will also be able to document the breakdown of causes of mortality (i.e. starvation, disease, predation, hunting) and how these differ by CWD infection status and sex.
A unique and innovative feature of this model is that it will account for the fact that deer can transition from being uninfected to infected with CWD, which is important for distinguishing survival rates based on CWD-infection status. It will also be able to separate how the risk of mortality changes with respect to time (year, season) and age. Finally, by integrating the age-specific survival estimates of infected and uninfected deer with data on pregnancy rates and litter sizes, scientists will be able to determine how population growth changes across a gradient of CWD prevalence.
Results from this analysis could be used to help deer management decision-makers better understand how CWD is realistically affecting deer populations and inform future management decisions. Because of the model's novelty, these results could have groundbreaking implications for management agencies in Wisconsin and beyond.
Additional Analyses
The animal captures and their collar transmissions have also provided scientists with a plethora of data that, in addition to supporting the primary analyses, will be incredibly useful for furthering wildlife and CWD research. This supplementary data includes things like movement, habitat use and predator survival rates. While some analyses remain ongoing, the additional Southwest Study objectives utilizing this data include:
| Objective | Importance | Findings |
|---|---|---|
| Bobcat and Coyote Survival and Mortality Rates | Understanding the causes of mortality for bobcats and coyotes and how often they occur will help inform the management of both species. | Survival and cause-specific mortality of coyotes in Wisconsin, Margenau, et al. November 2021 Field Notes: Results from Coyote Survival and Cause-specific Mortality Study |
| Bobcat and Coyote Movement and Habitat Use | This will inform which areas are favored or avoided by each species and help us understand how predators fit into the bigger picture of deer survival. | Ongoing |
| Seasonal Deer Movement and Habitat Use | This will tell us how deer respond to seasonal changes in the environment and where there is likely to be higher CWD transmission. | Ongoing |
| Deer Movement and Habitat Use During Hunting and Breeding Season | This examines how breeding season and hunting pressures might alter deer movement patterns and influence CWD exposure. | December 2023 Field Notes: Buck Movement Ecology During Rut |
| Impact of CWD on Deer Movement | This will tell us how deer movement changes once they are infected with CWD; looks for sex, age and seasonal patterns. | Ongoing |
| Deer Contact Rates | This will look for contact networks among deer and likely CWD transmission pathways. | Ongoing |
| Juvenile Deer Dispersal and Landscape Use | This examines how juvenile deer and the landscape could influence gene flow and CWD transmission. | Agricultural land use shapes deer dispersal, Gilbertson, et al. November 2022 Field Notes: Juvenile Deer Dispersal |
Updates from these additional analyses as well as final primary results will continue to be communicated on as they become available. Upon release, results will be published in the Southwest Study’s Field Notes Newsletter and on this webpage.