Graduate Program in Environmental Science, State University of New York College of Environmental Science and Forestry (SUNY-ESF), 321 Baker, 1 Forestry Dr., Syracuse, NY 13210, USA.
Sci Total Environ. 2020 May 15;717:137269. doi: 10.1016/j.scitotenv.2020.137269. Epub 2020 Feb 11.
Trees provide numerous ecosystem services to benefit human health, and many cities have launched tree planting and management programs to increase tree populations and optimize tree locations through diverse tree priority schemes. Existing tree priority schemes are typically local-specific, expert-driven, and tree-planting-focused. In this study, a framework that captures interactions among the environment, tree and human demographic information is built. This framework provides a composite indicator, namely a tree priority planting or priority protection index (PPI), that can be integrated within a decision support system such as i-Tree Landscape to provide nationally consistent and locally relevant ways to strategically optimize tree planting and management locations across the entire United States. Three scenarios with the human health concerns are tested in a case study of New York City. The analyses are conducted at the census block group scale that is the finest-level scale available at i-Tree Landscape. The resulting PPI maps are analyzed using spatial statistics and compared against each other to investigate the impacts of alternative investments of limited public resources. The results show that: (1) tree priority patterns change greatly with alternative objectives; (2) adding more indicators to build PPIs lead to more diverse tree priority patterns as high (or low) values of different indicators are often not geographically coincident; (3) incorporating more indicators may not necessarily provide more useful information because the influences of individual indicators may be reduced and diluted by a higher level of aggregation; and (4) disaggregating PPIs may reveal corresponding contributions of individual indicators. Applying the proposed framework to build PPIs has important implications for tree priority effort, scientific exploration, education, and public engagement.
树木为人类健康提供了众多生态系统服务，许多城市已经启动了植树和管理计划，通过各种树木优先计划来增加树木数量并优化树木位置。现有的树木优先计划通常是特定于本地的、由专家驱动的、以植树为重点的。在这项研究中，构建了一个捕捉环境、树木和人类人口统计信息之间相互作用的框架。该框架提供了一个综合指标，即树木优先种植或优先保护指数（PPI），可以集成到决策支持系统（如 i-Tree 景观）中，为美国各地提供一致的、与当地相关的战略优化植树和管理位置的方法。在纽约市的案例研究中，测试了三种关注人类健康的情景。分析是在人口普查街区组级别上进行的，这是 i-Tree 景观中可用的最细级别。使用空间统计分析对生成的 PPI 地图进行分析，并相互比较，以研究有限公共资源的替代投资的影响。结果表明：（1）树木优先模式随着替代目标的变化而发生很大变化；（2）添加更多指标来构建 PPI 会导致更多不同的树木优先模式，因为不同指标的高（或低）值通常不在地理上重合；（3）纳入更多指标不一定会提供更多有用的信息，因为个别指标的影响可能会因更高的聚合水平而降低和稀释；（4）分解 PPI 可能会揭示个别指标的相应贡献。应用所提出的框架来构建 PPI 对于树木优先工作、科学探索、教育和公众参与具有重要意义。
