AUTHORS: Olivia P. Reves, Department of Natural Resources and Environmental Sciences, University of Illinois Urbana-Champaign, Urbana, IL, USA; Mark A. Davis, Illinois Natural History Survey, Prairie Research Institute, University of Illinois Urbana-Champaign, Champaign, IL, USA; Eric R. Larson, Department of Natural Resources and Environmental Sciences, University of Illinois Urbana-Champaign, Urbana, IL, USA
ABSTRACT: The conversion of natural ecosystems to agriculture is a leading cause of habitat loss and threatens global biodiversity. For the past two centuries, the midwestern United States has experienced agricultural intensification and expansion, resulting in losses of natural ecosystems including tallgrass prairies, wetlands, and forests. Forest cover in states like Illinois has increased over the last several decades, partially due to agricultural conservation efforts like agroforestry, the Conservation Reserve Enhancement Program, and implementation of riparian buffers. However, does this increasing forest cover, intended to reduce nutrient and soil loss and benefit in-stream biota, also have benefits to terrestrial biodiversity? We used environmental DNA (eDNA), DNA collected and isolated from environmental samples, to evaluate how forest cover influences and potentially benefits terrestrial and semi-aquatic vertebrates in agricultural landscapes. In May and June of 2024, we collected eDNA samples from 47 low order streams over gradients of both riparian and whole-watershed forest cover from the U.S. National Land Cover Database. We then conducted eDNA metabarcoding of vertebrate communities using 12S and COI primers. Next, we used generalized linear mixed models to examine effects of forest cover on species richness, as well as non-metric multidimensional scaling to explore differences in community composition between sites of varying forest cover. Evaluating how terrestrial vertebrate communities respond to forest cover can shape management practices from riparian buffers to watershed-wide scales across agricultural regions.
AUTHORS: Jamie Goethlich, University of Wisconsin-Madison; Tim Van Deelen, University of Wisconsin-Madison
ABSTRACT: The basis of white-tailed deer (Odocoileus virginianus) management has traditionally focused on population size, which is important for establishing harvest goals for broad-scale deer management efforts. While population estimates are important for determining the number of individuals to harvest to reduce, maintain, or increase populations, population size does not provide detailed information on the health of the population. However, herd health is a major consideration for many contemporary deer management situations, and deer health is a common concern among deer managers, deer hunters, and people opposed to deer hunting. Although health and welfare are commonly used in the livestock industry and captive wildlife settings, animal welfare is an emerging segment of wildlife research. Recently, Smiley et al. (2020) created a technique to assess body condition using photographs of captured deer, which they validated by comparing body scores to ingesta-free body fat. We tested the efficacy of pairing their visual body condition estimation method with trail camera photos of deer in suburbs of the Northeast. We found that trail camera photos could easily be used for assessing body condition, and body condition scores were generally consistent among two independent observers. Additionally, we found body condition scores varied significantly across seasons, among sexes, and between does with and without fawns at heel. Lastly, we created a detailed training pamphlet to be used as a guide for researchers and citizen scientists. We conclude that this is a quick and easy method that can be useful in situations where deer managers want information about herd health/welfare but attaining robust sample sizes of harvested deer may be unattainable (e.g., unhunted urban populations, small private properties, etc.).
AUTHORS: Bianca Saftoiu, University of Illinois Urbana-Champaign; Dr. Mark Johnson, US Army Construction Engineering Research Laboratory; Patrick Wolff, US Army Construction Engineering Research Laboratory; Dr. Jinelle Sperry, University of Illinois Urbana-Champaign and US Army Construction Engineering Research Laboratory
ABSTRACT: Tall-grass prairies are among the most threatened ecosystems in North America with less than 0.01% remaining in the state of Illinois. Effective prairie restoration in the Midwest is thus essential and requires that the health of the ecosystem be managed by re-establishing functional ecological communities, including prairie-associated wildlife species. Small mammals serve as an effective taxonomic group to monitor given their importance to ecological functioning across trophic levels and their sensitivity to habitat disturbance. Various passive and invasive survey methods have been used to evaluate mammalian species because of challenges associated with varying body size, temporal activity patterns, and cryptic behaviors. In this study we compare three distinct methods including live trapping, bucket camera traps, and airborne environmental DNA (eDNA) sampling for monitoring small mammal communities in restored prairies. In 2023 we surveyed ten prairie sites in Illinois and found that live trapping allowed for more specific identification to the species level while bucket cameras generally detected a greater species richness. We were also able to detect vertebrate DNA within the ten prairies using eDNA methods, however, the quantity of DNA varied across sites. Based upon these preliminary results, we can infer that a combination of both traditional and modern methods will offer a more comprehensive assessment of small mammal community composition within restored prairies.
AUTHORS: David Delaney, Iowa State University Tyler Harms, Iowa Department of Natural Resources Stephen Dinsmore, Iowa State University
ABSTRACT: Techniques to estimate density of unmarked animals are logistically feasible and allow sampling over greater spatial extents than more intensive methods, such as mark-recapture. However, accuracy of density estimates relies on the validity of assumptions about the study system. We conducted a thermal-imaging drone survey at night to test the validity of two assumptions for conducting distance sampling on white-tailed deer (Odocoileus virginianus) in Iowa via nocturnal spotlight surveys. First, we tested whether deer are randomly distributed with respect to gravel roads, which represent line transects in our study. Second, we quantified the portion of the population that occurs in unsampleable locations (i.e., within forest) to estimate availability bias. Preliminary analyses suggest deer do not avoid gravel roads but do responsively move away from observers prior to being detected, leading to potential bias in estimates of detection probability and density. Secondly, deer increased the use of forest cover as spring vegetation green-up occurred, leading to up to 50% of the population being unavailable to sample during surveys. Each of these deviations from conventional distance sampling assumptions inform future sampling design protocols and can be analytically corrected, once quantified, to reduce bias in density estimates.
