Doctoral Dissertation Research: The Exurban Frontier: Predicting Human-Wildlife Interactions and Conservation Attitudes Where People Live, Work, and Play

人类和野生动物之间的冲突越来越多。 这种增长的原因包括：（1）景观变化导致栖息地丧失，栖息地恢复，以及野生动物种群迁移到人类社区附近的地区;（2）顶级捕食者的丧失导致某些物种种群的爆炸;以及（3）不断增长的人口。 郊区的增长，定义为低密度的发展，从5至40英亩每建筑物，作为一个催化剂的物理和社会景观的变化。 然而，很少有研究将郊区发展与人类与野生动物互动的增加具体联系起来。 本博士论文研究计画的目的是探讨远郊发展、人类与野生动物互动与保育态度之间的关系。 该项目将集中在北方纽约州和阿迪朗达克公园的600万英亩公有和私有土地上。 方法将包括现有数据的空间分析和自我管理的邮件调查问卷分发给一组随机的土地所有者在四个研究社区和所有居民在研究社区报告人类与野生动物的相互作用在过去三年。 将对前几年绘制的3，900份野生动物投诉分布进行空间分析，包括森林覆盖率，道路和住房密度等其他数据集，以确定郊区景观特征是否是人类与野生动物相互作用的有用预测因子。 这些调查将收集有关人口统计、野生动物经验以及对栖息地和野生动物保护的态度的信息，以便对有野生动物投诉报告的居民和没有野生动物投诉报告的居民进行比较。 博士生将分析调查结果，以评估最有用的人口统计学特征和态度，用于预测人类与野生动物的相互作用是否被认为是积极或消极的，并确定人类与野生动物相互作用的看法与支持更广泛的野生动物和土地保护实践之间的关系。 空间统计和逻辑回归将被用来检验假设，并建立预测模型，展示城市外围的发展，人类与野生动物的相互作用和保护态度之间的关系。本研究项目将通过空间整合土地利用，人口和态度的信息，推进人类与野生动物相互作用的基本理解。 这项研究的结果将对野生动物管理者、土地使用规划者和保护工作者有用，他们都必须解决这些复杂的问题。 野生动物管理者可以为特定地区和/或易于与人类-野生动物互动的人群开发有针对性的信息。 土地使用规划者可以利用这些信息来展示土地使用决策如何影响人类与野生动物的相互作用。 保护工作者可以利用关于哪些核心特征影响人类与野生动物相互作用的看法以及对自然资源保护和土地利用的其他态度的信息来建立一个强大的选区。 如果从这项研究中开发的模型可以成功地预测人类与野生动物的相互作用，这种方法可以应用于快速发展的地方，必须预测和尽量减少新出现的野生动物滋扰和损害问题。 作为博士论文研究改进奖，该奖项还将提供支持，使有前途的学生建立一个强大的独立的研究生涯。

Conflicts between humans and wildlife are increasing. Reasons for this increase include (1) landscape changes leading to habitat loss, habitat recovery, and movements of wildlife populations into areas near human communities; (2) loss of top predators resulting in explosions of some species populations; and (3) a continuously growing human population. Exurban growth, defined as low-density developments ranging from 5 to 40 acres per building, acts as a catalyst for physical and social landscape change. Little research has specifically connected exurban development to increases in human-wildlife interactions, however. The purpose of this doctoral dissertation research project is to explore the relationships among exurban development, human-wildlife interactions, and conservation attitudes. This project will focus on northern New York State and the six million acre publicly and privately owned lands of the Adirondack Park. Methods will include spatial analysis of existing data and a self-administered mail questionnaire distributed to a random set of landowners in four study communities and to all residents within the study communities reporting human-wildlife interactions during the previous three years. The distribution of 3,900 mapped wildlife complaints from prior years will be spatially analyzed with other data sets including forest cover, roads, and housing densities to determine whether exurban landscape characteristics are useful predictors of human-wildlife interactions. The surveys will elicit information related to demographics, experience with wildlife, and attitudes towards habitat and wildlife conservation, allowing for comparisons between residents with and without reported wildlife complaints. The doctoral candidate will analyze the survey results to assess the most useful demographic characteristics and attitudes for predicting whether a human-wildlife interaction is perceived as positive or negative and to determine the relationships between perceptions of human-wildlife interactions and support for broader wildlife and land conservation practices. Spatial statistics and logistic regression will be used to test hypotheses and build predictive models that demonstrate the relationships among exurban development, human-wildlife interactions, and conservation attitudes.This research project will advance basic understanding of human-wildlife interactions by spatially integrating land-use, demographic, and attitudinal information. Results of the study will be useful for wildlife managers, land-use planners, and conservation practitioners, all of whom often must address these complex issues. Wildlife managers may develop targeted messages for specific areas and/or types of people prone to human-wildlife interactions. Land-use planners may use the information to demonstrate how land use decisions can influence human-wildlife interactions. Conservation practitioners can use information regarding what core characteristics influence perceptions of human-wildlife interactions and other attitudes toward conservation of natural resources and land use to build a strong constituency. If models developed from this research can successfully predict human-wildlife interactions, this approach may be applied in places where rapid development is occurring and emerging wildlife nuisance and damage issues must be anticipated and minimized. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.