Realities of Immunocontraception as a Management Option for White-tailed Deer in Suburban Environments

Symposium: The Increasing Conflicts of Deer and Human Populations in Suburban Area

A landscape-based approach for delineating hotspots of wildlife-vehicle collisions

Imposing human perceptions about the scales of ecological processes can produce unreliable scientific inferences in wildlife research and possibly misinform mitigation strategies. An example of this disconnect occurs in studies of wildlife-vehicle collisions (WVCs). Subjective procedures are often used to delineate hotspots of WVCs, resulting in hotspots that are not spatially independent. We developed a new approach that identifies independent hotspots using attributes of the landscape to inform delineations instead of subjective measures. First, we generated a candidate set of grouping scenarios using unique combinations of kernel-density estimation parameterization (i.e., bandwidth and isopleth values). Next, we associated the groups of WVCs with attributes of the surrounding landscape. Finally, we identified the grouping scenario with the highest amount of variation in the landscape among the groups. The highest variation corresponded to hotspots that were most distinguishable from each other (i.e., most independent) based on the surrounding landscape. We tested our approach on 3 species of wildlife [island foxes (Urocyon littoralis) on San Clemente Island, CA; white-tailed deer (Odocoileus virginianus) in Onondaga County, NY; and moose (Alces alces) in western Maine] that exemplified varying degrees of space-use in different landscapes. We found that the landscape based approach was able to effectively delineate independent hotspots for each species without using subjective measures. The landscape-based approach delineated fewer or larger hotspots than currently used methods, suggesting a reduction in spatial dependency among hotspots. Variation in the landscape indicated that hotspots may be larger than previously identified; therefore current mitigation strategies should be adjusted to include larger areas of high risk

Underreporting of wildlife-vehicle collisions does not hinder predictive models for large ungulates

Conflicts from wildlife–vehicle collisions (WVCs) pose serious challenges for managing and conserving large ungulates throughout the world. However, underreporting of large proportions of WVCs (i.e., two-thirds of WVCs in some cases) creates concern for relying on governmental databases to inform management strategies of WVCs. Our objective was to test the sensitivity of WVC studies to underreporting using 2 species of large ungulates that experience substantial incidences of collisions but exist in different environmental settings: white-tailed deer (Odocoileus virginianus) in agricultural-dominated central Illinois and moose (Alces alces) in forest-dominated western Maine, USA. We estimated baseline relationships between the landscape, traffic, and abundance of wildlife on the probabilities of WVCs using the total number of reported WVCs. Then, we simulated underreporting by randomly excluding reports of WVCs and evaluated for relative changes in precision, parameter estimates, and prediction. Point estimates of the relationships between environmental influences and WVCs for both species were reliable until high rates of underreporting occurred (≥70%). When underreporting occurred with spatial bias, shifts in point estimates were detected only for variables that spatially-corresponded with the rate of reporting. Prediction estimates for both species were also reliable until high rates of underreporting occurred (≥75%). These findings suggest that predictive models generate reliable estimates about WVCs with large ungulates unless underreporting is severe; possibly because they occur in non-random patterns (i.e., hotspots) and variability in their environment influences is low. We recommend that concern about underreporting not impede research with existing databases, such as those in this study, for analyzing predictive models and developing management strategies for reducing WVCs

A landscape-based approach for delineating hotspots of wildlife-vehicle collisions

Imposing human perceptions about the scales of ecological processes can produce unreliable scientific inferences in wildlife research and possibly misinform mitigation strategies. An example of this disconnect occurs in studies of wildlife-vehicle collisions (WVCs). Subjective procedures are often used to delineate hotspots of WVCs, resulting in hotspots that are not spatially independent. We developed a new approach that identifies independent hotspots using attributes of the landscape to inform delineations instead of subjective measures. First, we generated a candidate set of grouping scenarios using unique combinations of kernel-density estimation parameterization (i.e., bandwidth and isopleth values). Next, we associated the groups of WVCs with attributes of the surrounding landscape. Finally, we identified the grouping scenario with the highest amount of variation in the landscape among the groups. The highest variation corresponded to hotspots that were most distinguishable from each other (i.e., most independent) based on the surrounding landscape. We tested our approach on 3 species of wildlife [island foxes (Urocyon littoralis) on San Clemente Island, CA; white-tailed deer (Odocoileus virginianus) in Onondaga County, NY; and moose (Alces alces) in western Maine] that exemplified varying degrees of space-use in different landscapes. We found that the landscape based approach was able to effectively delineate independent hotspots for each species without using subjective measures. The landscape-based approach delineated fewer or larger hotspots than currently used methods, suggesting a reduction in spatial dependency among hotspots. Variation in the landscape indicated that hotspots may be larger than previously identified; therefore current mitigation strategies should be adjusted to include larger areas of high risk

Students’ Perceptions of Factors that Affect College Funding Decisions

This exploratory study examines the factors that college students perceive are important in helping them make good financial decisions about paying for a college education. The study categorizes and summarizes students\u27 self-reported responses to an openended survey question about recommendations for changes in financial aid counseling practices. The 335 student responses had a recurring theme of better information provided through individual counseling sessions

An Outbreak of Community-Acquired Foodborne Illness Caused by Methicillin-Resistant Staphylococcus aureus

Infections with methicillin-resistant Staphylococcus aureus (MRSA) are increasingly community acquired. We investigated an outbreak in which a food handler, food specimen, and three ill patrons were culture positive for the same toxin-producing strain of MRSA. This is the first report of an outbreak of gastrointestinal illness caused by community-acquired MRSA