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正在增加。这一增长的原因包括(1)导致栖息地丧失、栖息地恢复和野生动物种群向人类社区附近地区迁移的景观变化；(2)顶级捕食者的丧失导致一些物种种群的爆炸性增长；(3)人类种群的持续增长。郊区发展是指每栋建筑面积在5英亩到40英亩之间的低密度开发，是物质和社会景观变化的催化剂。然而，很少有研究明确将郊区发展与人与野生动物互动的增加联系起来。这项博士论文研究项目的目的是探索城郊发展、人与野生动物的互动和保护态度之间的关系。该项目将集中在纽约州北部和阿迪朗达克公园的600万英亩公有和私有土地上。方法将包括对现有数据进行空间分析，并向四个研究社区的随机土地所有者和研究社区内的所有居民分发一份自我管理的邮寄问卷，报告过去三年人与野生动物的互动情况。前几年绘制的3900份野生动物投诉地图的分布将与其他数据集一起进行空间分析，包括森林覆盖率、道路和住房密度，以确定郊区景观特征是否有助于预测人与野生动物的相互作用。这些调查将获得与人口统计数据、野生动物经历以及对栖息地和野生动物保护的态度有关的信息，以便对有和没有报告野生动物投诉的居民进行比较。博士生将分析调查结果，以评估最有用的人口统计特征和态度，以预测人与野生动物的互动是积极的还是消极的，并确定对人与野生动物互动的看法与对更广泛的野生动物和土地保护做法的支持之间的关系。空间统计学和Logistic回归将被用来检验假设和建立预测模型，以展示城郊发展、人与野生动物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、人口统计和态度信息来促进对人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、土地利用规划者和保护从业者有用，他们通常都必须解决这些复杂的问题。野生动物管理人员可能会针对特定地区和/或易发生人与野生动物互动的人群开发有针对性的信息。土地利用规划者可能会利用这些信息来展示土地利用决定如何影响人与野生动物的互动。保护从业者可以利用关于哪些核心特征影响对人与野生动物相互作用的看法以及对自然资源和土地利用保护的其他态度的信息来建立强大的支持者。如果从这项研究开发的模型可以成功地预测人与野生动物的相互作用，这种方法可能会应用于快速发展且必须预见和尽量减少新出现的野生动物滋扰和破坏问题的地方。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.