Marrett D. Grund

LANDSCAPE INFLUENCES ON DEER-VEHICLE ACCIDENT AREAS IN AN URBAN ENVIRONMENT

Deer-vehicle accidents (DVA) have become an important human safety concern in the United States, and few studies have focused specifically on urban areas. We used remotely sensed data, multivariate statistics, and a geographic information system (GIS) to quantify landscape factors influencing DVA in 2 suburbs of Minneapolis, Minnesota, USA, during 1993-2000. We determined DVA areas (n = 80) containing ≥2 roadkills and control areas (n = 80) containing 0 or 1 roadkill based on numbers of DVA within 0.13-km2 buffered road segments. The most important variables (based on Akaike weights) that differentiated between DVA areas and control areas were number of buildings and number of public land patches. A logistic regression model containing these variables best fit the data and correctly classified 31 of 40 (77.5%) areas not used for model building. Local wildlife biologists and urban planners can use this information in managing deer habitat to minimize DVA by reducing forest cover and shrubby areas on public land near roads. We suggest that community officials consider using the potential for DVA as justification for proactive population and habitat management programs to maintain deer populations at levels that minimize deer-human conflicts.

Seasonal movements and habitat use of female white-tailed deer associated with an urban park

Many cities throughout the United States have implemented programs for managing white-tailed deer (Odocoileus virginianus) populations. However, basic ecological questions, such as seasonal movement patterns and habitat use of deer in urban landscapes, have gone relatively unstudied. We conducted a telemetry study to investigate seasonal movements and habitat use of female white-tailed deer in Bloomington, Minnesota, USA, during 1996-1999. Home range size varied seasonally, with the largest occurring during the spring (x = 144 ha [SD = 7 ha]) and smallest during the summer (x = 50 ha [SD = 7 ha]). Home ranges during fall (x = 93 ha [SD = 11 ha]) and winter (x = 85 ha [SD = 6 ha] ) were similar in size. Deer in this study demonstrated a high degree of fidelity with their seasonal home ranges, except during a severe winter when 75% of the deer shifted their fall home range. These deer all returned to their original home range the following spring. Habitat analysis indicated that deer used woody cover habitats during every season. Habitats within parks and conservation areas made up the greatest percentage (52-68%) of home range compositions during all seasons except the severe winter when 78% of the home range encompassed residential neighborhoods. Our data suggest that a major difference between urban and rural deer is in spatial scale. Deer in this study used habitats that might be expected based on studies of deer in rural landscapes but occupied smaller home ranges than normally reported for deer in rural landscapes. Deer management programs developed for urban communities should consider movement patterns of deer to ensure the most effective control of particular nuisance individuals.

Assessing Deer Hunter Attitudes Toward Regulatory Change Using Self-Selected Respondents

State wildlife agencies are charged with managing wildlife populations of harvestable species. Opinions regarding how species should be managed differ dramatically and decisions are often made without comprehensive data. There is interest among deer hunters in Minnesota to change harvest regulations that benefit mature bucks. Beginning in 2005, research focused on the biological and social implications of changing deer regulations. We used data collected via random surveys, public input meetings, and an Internet survey to assist with the decision-making process. We observed demographic differences among respondents for the three data collection methods; however, the attitudinal differences were “minimal” (i.e., Cramérs V ≈ .1). We believe that a structured public input process, even if self-selected, can help inform decision-makers. Agencies that use public input meetings should reevaluate their public input process to include an Internet component if there are adequate baseline data available to make comparisons.

What Predicts Support for Antler Point Restrictions

Although considerable research has focused on satisfaction with recreation experiences, limited work has examined factors related to regulatory support. In 2005, an antler point restriction (APR) regulation was introduced for hunting white-tailed deer (Odocoileus virginianus) in Minnesota’s Itasca State Park. Hunter surveys were conducted following the 2005, 2006, 2007, and 2009 seasons. We modeled how (a) satisfaction with the deer seen, (b) type of deer pursued, (c) agency trust, and (d) years of deer-hunting experience, influenced support for the APR, and compared the model over the four survey years. Type of deer pursued and agency trust were the strongest predictors of APR support, followed by satisfaction with deer seen, and years of hunting experience. Hunters who targeted big bucks, had more trust in the agency, and expressed more satisfaction with deer seen in the field, were more supportive of the APR. Hunters who had more deer-hunting experience were less supportive.

Design and Analysis of Simple Choice Surveys for Natural Resource Management

Abstract We used a simple yet powerful method for judging public support for management actions from randomized surveys. We asked respondents to rank choices (representing management regulations under consideration) according to their preference, and we then used discrete choice models to estimate probability of choosing among options (conditional on the set of options presented to respondents). Because choices may share similar unmodeled characteristics, the multinomial logit model, commonly applied to discrete choice data, may not be appropriate. We introduced the nested logit model, which offers a simple approach for incorporating correlation among choices. This forced choice survey approach provides a useful method of gathering public input; it is relatively easy to apply in practice, and the data are likely to be more informative than asking constituents to rate attractiveness of each option separately.