Midwest Fish & Wildlife Conference 2019

AUTHORS: Michelle Carstensen, Erik C. Hildebrand, Dawn Plattner, Margaret Dexter – Minnesota Department of Natural Resources; Arno Wünschmann, Anibal Armien – University of Minnesota-Veterinary Diagnostic Laboratory

ABSTRACT: Minnesota’s moose (Alces alces) are dying at rates much higher than elsewhere in North America. Moose have been nearly extirpated from the northwestern part of the state and aerial surveys indicate the northeastern population has declined 55% over the past decade. In 2013, a new study began to determine cause-specific mortality of adult moose in northeastern Minnesota by using GPS-satellite collars to get rapid notification of mortality events and recover carcasses within 24 hours of death. A total of 173 moose were collared over 3 years with annual non-hunting mortality rates of 19%, 12%, 15%, 13% and 14% in 2013-2017, respectively, and an overall mean of 14.4%. In total, 57 moose have died from non-hunting sources of mortality and 3 moose were legally harvested. Response times from mortality notification to arrival at the carcass were within 24 hours for 65% of death events. Most causes of mortality were health-related (65%), which included parasites (30%; e.g., winter ticks, brainworm, and liver flukes), bacterial infections (20%), accidents (3%), calving (2%) and other undetermined health issues (10%).The remainder was wolf-related (30%), with predisposing health conditions identified in nearly half of these moose.  Legal harvest accounted for 5% of moose deaths. During the same time period, we also necropsied anecdotal moose deaths (n=91) across northern Minnesota, which included vehicle or train collisions, sick, and found dead animals. Parelaphostrongylus tenuis was confirmed in 42% of these cases, which is nearly twice the rate of detection of this parasite as in the collared moose studied during the same time period. 

AUTHORS: Lucas O. Olson, Timothy R. Van Deelen, John D. J. Clare – University of Wisconsin-Madison; Maximilian L. Allen, Illinois Natural History Survey

ABSTRACT: Wildlife conservation and management depends on understanding patterns and changes in the populations and distributions. Moose (Alces alces) sub-populations are alternately declining and increasing in abundance across their circumpolar distribution. Within regional populations a similar variable pattern sometimes exists, such as in the upper Midwest region of the United States where sub-populations are declining in Minnesota but steady or increasing in Michigan. Although abundant before European settlement, little is known about the current state of moose in Wisconsin. We examined citizen science observations of moose collected by the Wisconsin Department of Natural Resources over 25 years to determine the drivers and trends of moose distribution in Wisconsin. Because opportunistically collected citizen-science data may be unreliable for abundance estimates, we used an occupancy framework to understand how variables affect county-level detection and occupancy of moose. We found that detection was driven by area of Intermix Wildland Urban Interface and road density, and occupancy was driven primarily by proximity to Minnesota and Michigan, and appears to have been stable over the previous 25 years. This study offers insight for understanding moose populations on the southern fringe of their circumpolar distribution, and a foundation for understanding the moose population in Wisconsin.

AUTHORS: Christopher Jacques, Western Illinois University; Evan Phillips, Colorado Parks and Wildlife; Angela Jarding, National Park Service; Susan Rupp, Enviroscapes Ecological Consulting, LLC; Robert Klaver, U.S. Geological Survey; Chadwick Lehman, South Dakota Game, Fish and Parks; Jonathan Jenks, South Dakota State University

ABSTRACT: Since 1993, elk (Cervus canadensis nelsoni) abundance in the Black Hills of South Dakota has been estimated using a detection probability model previously developed in Idaho, though are likely negatively biased because of a failure to account for visibility biases under local conditions. To correct for this bias, we evaluated the current detection probability across the Black Hills during January and February 2009-2011 using radiocollared elk. We used logistic regression to evaluate topographic features, habitat characteristics, and group characteristics relative to their influence on detectability of elk. Elk detection probability increased with less vegetation cover (%), increased group size, and snow cover (%); overall detection probability was 0.60 (95% CI = 0.52-0.68) with 91 of 152 elk groups detected. Predictive capability of the selected model was excellent (ROC = 0.807), and prediction accuracy ranged from 70.2% to 73.7%. Cross-validation of the selected model with other population estimation methods resulted in comparable estimates. Application of our model should be applied cautiously if characteristics of the area (e.g., vegetation cover > 50%, snow cover > 90%, group sizes > 16 elk) differ notably from the range of variability in these factors under which the model was developed.

AUTHORS: Chad R. Williamson, Henry Campa III, Scott R. Winterstein – Michigan State University; Alexandra B. Locher, Grand Valley State University; Dean E. Beyer, Jr., Michigan Department of Natural Resources

ABSTRACT: To determine current habitat suitability for elk (Cervus elaphus) in Michigan, we developed a stand-level (fine-scale) habitat suitability index (HSI) model for public lands, and a landscape-level (coarse-scale) HSI model for public and private lands. For our stand-level HSI model, we used forest compartment inventory data to identify cover types important to elk, and assigned suitability values (0=low, 1=high) to each cover type for elk life requisites (spring food, winter food, winter thermal cover). Additionally, we modified suitability values based on stand conditions (e.g., stand size, age of aspen [Populus spp.], % canopy closure). For our landscape-level HSI model, we used satellite imagery to classify cover types and assigned suitability values to cover types for each life requisite. Our HSI models indicate a heterogeneous arrangement of high suitability for spring food (openings, aspen) and winter food (aspen, hardwoods, conifers) throughout our study area, and several large areas of high suitability for winter thermal cover (conifers) in the southern edge of our study area. Our landscape-level model provided suitability for private lands, but overestimated areas of high suitability in comparison to our stand-level model. Habitat potential was modeled by delineating habitat types by overlaying digital spatial data layers (soils, land-type associations, vegetation) and identifying successional trajectories using habitat classification guides and literature. We assigned suitability values to each habitat type for life requisites at early to late successional stages. Comparisons between current elk habitat suitability and habitat potential identify key areas where managers can maximize management efforts for elk in Michigan. Areas determined to have higher habitat potential may become focus areas if they are not currently being managed or have low suitability. Conversely, areas with low habitat potential may be avoided for continued or future elk habitat management.

AUTHORS: Amanda McGraw, Daniel Storm – Wisconsin Department of Natural Resources

ABSTRACT: Deer health reflects habitat quality, climate, and interspecific competition. Deer health, in turn, is reflected in body condition, including body weight and fat reserves. To relate deer health to habitat quality, climate, deer density levels, the Wisconsin Department of Natural Resources began a collaborative project with landowners enrolled in the state’s Deer Management Assistance Program (DMAP) to collect data on harvested deer and available forage on private properties. DMAP cooperators were recruited as to participate as citizen scientists through outreach including public presentations and email announcements during 2017 and 2018. Several training tools were developed to facilitate quality data collection by cooperators. Data collection kits containing all necessary supplies was provided to cooperators. In 2017 we received data from 57 DMAP cooperators for 280 deer. Cooperators measured several morphological characteristics indicative of body condition and overall health, such as antler dimensions and carcass weight. Cooperators extracted a tooth for aging via cementum annuli and photographed hearts for organ fat estimation. Age explained 66% of variance for female deer carcass weight (R² = 0.64, F_1,6 = 20.61, p < 0.001) and 81.7% of variance for male carcass weight (R² = 0.81 F_1,6 = 64.19, p < 0.001). Less variation in antler width (Deviance = 0.57, R² = 0.56, F_1,6 = 13.39, p < 0.001) and number of antler points (Deviance = 0.55, R² = 0.53, F_1,6 = 12.45, p < 0.001) was explained by age for male deer. We are continuing to explore the potential effects of density, habitat, and weather on deer body condition and antler development. This study highlights methods developed to ensure quality data collection by citizen scientists, and feasibility of operating a citizen-science based research project at a state-wide scale. We also provide insights about how habitat quality on private lands impacts deer health and productivity.