Wildlife Population Management II

Contributed Oral

 
Survival and Cause-Specific Mortality of Neonate White-Tailed Deer in Western Virginia
Garrett Clevinger, Nelson Lafon, Mark Ford, Marcella Kelly, Randy W. DeYoung, Michael Cherry

Fawn recruitment is an important population parameter of white-tailed deer (Odocoileus virginianus) that influences harvest potential and is often modified by landscape conditions and local predator assemblages. In the Central Appalachian Mountains, deer co-occur with black bears (Urus americanus), coyotes (Canis latrans), and bobcats (Lynx rufus) in a landscape characterized by long linear forested ridges with poor soils separated by fertile valleys with less forest cover. Our objectives were to evaluate survival rates and cause-specific mortality of neonate white-tailed deer across a of range of environmental conditions. During 2019-2020, we captured 57 neonates by monitoring pregnant does equipped with vaginal implant transmitters (VITs) and by searching transects for fawns.  We monitored fawns until they died or reached 12 weeks of age and then used an information-theoretic approach to compare Cox proportional hazards models containing habitat features associated with fawn locations to predict survival. We assigned causes of death using field evidence, lab necropsy, and DNA from residual predator saliva found on fawns. Pooling years, neonate survival was 0.40 (95% CI = 0.288-0.562). Of the 30 documented mortalities, we attributed 21 (70%) to predation, and 9 (30%) to starvation and disease. Although DNA analysis is ongoing, field evidence suggested that black bears accounted for 70% of predation events, which primarily occurred during the first few days of a fawn’s life. Our top model included elevation as an informative predictor of fawn survival, with mortality risk increasing with elevation. In our study, survival was higher near valley bottoms where deer likely were in better nutritional condition, and lower near ridges where black bears were more common. Our work links fawn survival to a landscape pattern that is useful in predicting deer population performance across space and thus can inform habitat enhancements and harvest management. 

 
Estimating Animal Size and Distance in Camera Trap Images: Photogrammetry Using the Pinhole Camera Model
Scott Leorna, Todd Brinkman, Shawn Crimmins, Timothy Fullman

As camera trapping has become a standard practice in wildlife ecology, developing techniques to extract additional information from images will increase the utility of generated data. Despite rapid advancements in camera trapping practices, methods for estimating animal size or distance from the camera from captured images have not been standardized. Deriving animal sizes directly from images creates opportunities to collect wildlife metrics such as growth rates or changes in body condition. Distances to animals may be used to quantify important aspects of sampling design such as the effective area sampled or distribution of animals in the camera’s field-of-view. We present a method of using pixel measurements in an image to estimate animal size or distance from the camera using a conceptual model in photogrammetry known as the “pinhole camera model”. We evaluated performance of this approach by capturing images of three-dimensional animal targets ranging in size and distance from the camera using camera traps from two different manufacturers, each with two different image settings. We found total mean relative error of estimated animal sizes and distances from the cameras was -3.0% (n=120, SD=4.2) and 3.3% (n=120, SD=4.6) respectively. Mean relative error of size or distance estimates did not differ between image settings within camera models, between camera models, or between the measured dimension used in calculations (all p>0.05). We provide recommendations on how to apply this approach in the context of wildlife camera trapping. Our method for estimating animal size or distance from the camera produced accurate and precise estimates using a single image while remaining easy to implement and generalizable to different camera trap models and installations, thus enhancing its utility for a wide diversity of camera trap applications and expanding opportunities to use camera trap images in novel ways.

 
Resiliency of the Southwestern Pond Turtle after Drought in Southern California
Hannah Lee, Lyell Buttermore, Barry Nerhus

Southwestern pond turtle (Actinemys pallida) populations have been consistently declining throughout their range. This growing concern for population decline is exacerbated by increasing drought, urbanization, and fragmentation. Little is known about the local stability and demographics in Southern California. Despite this, previous studies at the San Joaquin Marsh in Orange County, California have demonstrated continuous population stability. We hypothesized that southwestern pond turtle populations at the San Joaquin Marsh demonstrate population stability and resilience despite two years of drought-like conditions. We analyzed the population demographics to determine impacts on population stability in the context of drought. To test this we conducted a mark-recapture survey study over two years at the San Joaquin Marsh. We found that the population estimate at this location had significantly increased in comparison to previous status reports, even in the face of drought-like conditions. Additionally, we observed lower juvenile recruitment and a lower proportion of females in reference to males when compared to a previous study conducted prior to drought conditions. These demographic changes could significantly impact future population dynamics. Our results indicate a need for conservation management of southwestern pond turtles and further investigation into the status of pond turtle populations, especially after stochastic disturbance events (i.e. drought, fire, isolation). This investigation emphasizes a need for continued monitoring and surveying of local populations, especially after drought.

 
Managing for Multiple Pathogens Simultaneously in Complex Ecosystems
Lindsey Pekurny, Brittany Mosher, Evan Grant

Emerging infectious diseases are an increasingly common threat to wildlife and are challenging to manage for. In some cases, the complexity is increased because multiple pathogens co-occur and management must consider both simultaneously. Pathogens may interact with the environment differently; one pathogen may be amplified by a certain environmental condition, but a separate pathogen may be harmed. Pathogens may also affect each other; when a pathogen is amplified by a second pathogen’s presence, synergy occurs. An antagonistic relationship occurs when one pathogen is reduced by the presence of a second pathogen. When just one of multiple pathogens is considered, management decisions targeted for one pathogen may inadvertently amplify/improve conditions for another. 

Amphibian populations are declining due to multiple emerging infectious diseases and managers are tasked with taking action to slow these declines. Without understanding similarities and differences in effects of environmental variables on pathogens, managers may not be able to make optimal management choices. Our research focuses on identifying and modeling the environmental interactions of ranavirus and Batrachochytrium dendrobatidis (Bd), as well as the synergistic or antagonistic effects they have on each other, to inform conservation decision-making. To do this, we first conducted a literature review to identify key environmental variables. With this information, we created a conceptual diagram to visualize these interactions. Finally, we used a Bayesian belief network to graphically and probabilistically model the interactions among the key variables. 

The results from our work can be used by managers at a local level to account for the environmental conditions specific to their amphibian populations. More broadly, this framework has the capacity to model multiple pathogens for any wildlife population. As emergent diseases become a greater threat to wildlife populations, managers will need to rely on tools that can predict disease behavior and interactions within an environment. 

 
Optimal Strategies for Managing Wildlife Harvest Under System Change
Anna Tucker, Michael Runge

Wildlife populations are experiencing shifting dynamics due to climate and landscape change. Management policies that fail to account for non-stationary dynamics may fail to achieve management objectives. We establish a framework for understanding optimal strategies for managing a theoretical harvested population under non-stationarity. Building from harvest theory, we develop scenarios representing changes in population growth rate (r ) or carrying capacity (K ) and derive time-dependent optimal harvest policies using stochastic dynamic programming. We then evaluate the cost of falsely assuming stationarity by comparing the outcomes of forward projections in which either the optimal policy or a stationary policy is applied. When K  declines over time, the stationary policy leads to an underharvest of the population, resulting in less harvest over the short term but leaving the population in a higher-value state. When r  declines over time, the stationary policy leads to overharvest, resulting in greater harvest returns in the short term but leaving the population in a lower and potentially more vulnerable state. This work demonstrates the basic properties of time-dependent harvest management and provides a framework for evaluating the many outstanding questions about optimal management strategies under climate change.

 
Population Size Estimation Methods for a Hard-To-Enumerate Pinniped
Rebecca Taylor, Anthony Fischbach

Managers are concerned about the Pacific walrus (Odobenus rosmarus divergens) population because the species is susceptible to climate change and its harvest is important to indigenous peoples. However, all walrus population size estimates (both regional and range-wide) are imprecise. Imprecision is driven by (1) the clumped but unpredictable distribution of walruses at sea, which results from their gregarious but nomadic habits and (2) uncertainty in availability, the proportion of the population hauled out of the water (on ice or land) and therefore available to be counted. Historically, walruses in the Chukchi Sea have rested on sea ice, however recent reductions in sea ice increasingly force walruses to gather and rest at large coastal haulouts, where they may be counted and tagged to measure their availability using satellite-linked telemetry. However, initial efforts to estimate regional population size from one such coastal haulout in the northeast Chukchi Sea were impaired by sampling and analytic obstacles.  Three aerial surveys conducted in 2014 and corrected with telemetry data using design-based ratio estimators produced three point estimates that varied by an order of magnitude and suffered confidence interval widths 1 – 12x the point estimate size. We improved on this effort in 2018 and 2019 by (1) using unoccupied aerial systems (UAS) to increase the number of surveys to 13/year, and (2) developing a Bayesian hierarchical model to analyze all within-year surveys jointly with telemetry data to obtain a single regional population size estimate for each year. Our study year estimates were similar and reasonably precise: posterior means (CrIs) were 166,000 (133,000 – 201,000) and 161,000 (111,000 – 218,000).  Here we compare the two analyses and discuss the future potential to estimate the total walrus population size based on UAS counts and telemetry-based availability corrections.

 
The Benefits of a New Hierarchical Bayesian Model for Estimating Migratory Bird Harvest in Canada
Michel Gendron, Adam Smith

The Canadian Wildlife Service requires reliable harvest estimates of migratory game birds to effectively manage these species. Canada’s National Harvest Survey is conducted annually to estimate hunting activity and species-specific harvest. The analytical methods have not changed since the survey was first designed in the early 1970s. In this presentation, we will describe a new hierarchical Bayesian model (HBM), and demonstrate its benefits to harvest management in Canada. The HBM uses Poisson and multinomial distributions to model mean hunter activity, harvest, species composition, and harvest by age and sex. We estimated many of the key model parameters as time series, allowing the model to share information across years and reducing the sensitivity of the estimates to annual sampling noise. The HBM estimates are generally very similar to those from the old model, particularly for the most common species in the harvest, and so the results do not suggest any major changes to harvest management decisions and regulations. However, estimates for all species from the new model are more precise and less susceptible to annual sampling error, particularly for the less common species in the harvest (e.g., sea ducks). We are now using this HBM to generate estimates for the 2019-2020 hunting season, and we have updated estimates for all earlier years. We will outline some of the benefits to harvest management from the HBM, including the potential to incorporate the rich prior knowledge of hunting behaviour and species biology, which will facilitate future improvements and elaborations to fill more specific management information needs.

 
Linking Landscape-Scale Conservation to Regional and Continental Outcomes for a Migratory Species
Brady Mattsson, James Devries, James Dubovsky, Darius Semmens, Wayne Thogmartin, Jonathan Derbridge, Laura Lopez-Hoffman

Land-use intensification on arable land is expanding and posing a threat to biodiversity and ecosystem services worldwide. We predicted population trajectories of a migratory bird species at a continental scale under varying levels of landscape-scale conservation investments within a core breeding region while accounting for hunting regulation across all regions.  In particular, we developed methods to link funding for avian breeding habitat conservation and management at landscape scales to equilibrium abundance of a migratory species at the continental scale. Our methods combined a landscape habitat model, fecundity model, harvest model and a full-annual-cycle population-projection model. We applied this novel approach to a species valued by birders and hunters in North America, the northern pintail duck (Anas acuta), a species well below its population goal. Based on empirical observations from 2007-2016, habitat conservation investments for waterfowl cost $313M (2016 USD) and affected <2% of the pintail’s primary breeding area in the Prairie Pothole Region of Canada. Realistic scenarios for harvest and habitat conservation costing an estimated $588M led to predicted pintail population sizes < 3M when assuming average parameter values.  Given competing needs for remaining lands and fiscal limitations on conservation funding, our models suggest that achieving the continental population goal of 4M individuals under the current harvest policy is unlikely. Using our work as a starting point, we propose continued development of modeling approaches that link conservation funding, habitat delivery, and population response to better integrate conservation efforts and harvest management of economically important migratory species.

 
Reproductive Capabilities of Nilgai in South Texas
Megan Granger, Clayton Hilton, Scott Henke, Humberto Perotto-Baldivieso

Nilgai antelope (Boselaphus tragocamelus) are bovids that are endemic to India and portions of Pakistan and Nepal. They were introduced into South Texas in the 1920’s and now have a free-roaming population of approximately 33,000 individuals. Past knowledge in both native and introduced ranges indicate that nilgai have high reproductive rates, commonly have twins, and reach sexual maturity at approximately 2-3 years of age. However, these studies do not provide reliable quantitative data to prove these claims. Further research is needed to better understand the reproductive capabilities of nilgai in southern Texas. Commercial nilgai harvests were conducted during the summers of 2018-2020 on three ranches in southern Texas resulting in 571 harvested nilgai. Pregnancies and fetal sex and crown-rump lengths were recorded. Of 412 adult cows harvested, 320 (77.7%) individuals were pregnant, and of those cows, 200 (62.5%) produced twins. Feti occurred in an even sex ratio (291 males:295 females). The fetus crown-rump lengths varied by month, and on average, increased with each successive month, except during August where the average fetal size was smaller than the previous month. The large variability each month in fetal size suggests that nilgai do not have a set breeding season, although a peak in breeding may occur during late December. Our results confirm previous assumptions of nilgai having high reproductive rates in southern Texas. Considering their reproductive rate and that natural predators to nilgai appear lacking in Texas, nilgai populations have the potential to drastically increase.

 
Reproduction and Habitat Selection of Reintroduced, Translocated, Columbian Sharp-Tailed Grouse
Steven Mathews, Peter Coates, Brianne Brussee, Shawn O’Neil, Shawn Espinosa, David Delehanty

Resource managers have determined a need to augment Columbian sharp-tailed grouse (Tympanuchus phasianellus columbianus; hereafter, sharp-tails) populations using translocation techniques. Although translocation is a common management practice, little research has evaluated breeding habitat requirements in selection and survival models of translocated sharp-tails. Spatially explicit maps can quantify suitable habitat at a release site and identify breeding areas that inform management decisions and potential release locations. Furthermore, evaluation of microhabitat characteristics within these areas can inform specific vegetation requirements that further promote breeding success. We translocated 215 sharp-tails to Nevada as a species reintroduction project and documented all nest and brood attempts by translocated individuals. Using Bayesian regression and shared-frailty models, we quantified selection for microhabitat factors at nests and brood locations, respectively, and analyzed which factors had the largest impact on nest and brood survival while accounting for spatial correlation to the release location. In Nevada, translocated females avoided mountain shrubs within 25 m of their nest bowl (β = -0.97, 95% credible interval [CRI]-2.14 – -0.08), and strongly selected nests with taller residual grasses (β = 0.81, 95% CRI= 0.22 – 1.49). Tall perennial forbs however, had the largest impact on nest survival (β=-0.56, 95% CRI = -1.05–0) wherein taller forbs substantially reduced the probability of nest failure. Translocated females with broods avoided higher percentages of shrub (β = -0.61, 95% CRI = -0.92 – -0.30) and selected locations with taller sagebrush (β = 0.54, 95% CRI = 0.26 – 0.84) and increased percentages of horizontal cover (β = 0.51, 95% CRI = 0.20 – 0.83) with minor effects on the probability of brood survival. Finally, we mapped habitat selection and survival on a macro scale to identify potential future release sites that could maximize reproduction by translocated individuals. These findings are preliminary and provided for timely best science.

Contributed Oral
Location: Virtual Date: November 3, 2021 Time: 12:00 pm - 1:00 pm