Resilient urban forests for Canadians: Adapting to climate change for enhanced tree-related benefits

加拿大人的弹性城市森林：适应气候变化以增强与树木相关的效益

• 批准号: 536064-2018
• 负责人: Paquette, Alain
• 金额: $ 13.11万
• 依托单位: Université du Québec à Montréal
• 依托单位国家: 加拿大
• 项目类别: Advancing Climate Change Science in Canada
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=661504
• 关键词: Resilient; urban; forests; Canadians; Adapting

Urban forests (UF) are associated with important ecosystem services, such as reduced heat and improved air**quality, which benefit both environmental and human health. These benefits will become even more important**with climate change (CC), yet it is unclear how the UF will be impacted by CC, how that will affect human**health, and how the UF can be adapted to face CC and better support ecosystem services. This includes**removing carbon, which Canada has an obligation to report on. Current estimates of the UF carbon in Canada**use rates based on empirical observations made in United States and/or in natural forests. This has been**identified as an important source of uncertainty that needs to be addressed to forecast future UF density and**composition, and to investigate the hypothesis that the effects of CC on people may be greater than previously**thought if trees are also themselves affected negatively. Features such as tree size and crown shape that**influence resilience to CC and ecosystem services in UF are also different than in natural forests. Yet**incomplete inventories of urban trees and a paucity of data on canopies means that relevant data for modeling**and prediction of service production is scarce. Our goal is to better characterize UF with richer data, and to**identify best practices for developing resilient UFs that will support ecosystem services now and in the future.

城市森林（UF）与重要的生态系统服务有关，例如减少热量和改善空气质量，这有利于环境和人类健康。随着气候变化（CC），这些好处将变得更加重要 **，但目前尚不清楚UF将如何受到CC的影响，这将如何影响人类健康，以及UF如何适应CC并更好地支持生态系统服务。加拿大 ** 目前对UF碳使用率的估计是根据在美国和/或天然森林中进行的经验性观察得出的。这已被确定为一个重要的不确定性来源，需要解决预测未来的UF密度和 ** 成分，并调查假设CC对人的影响可能大于以前 ** 认为，如果树木本身也受到负面影响。特征，如树的大小和树冠形状，** 影响力，以CC和生态系统服务的UF也不同于天然林。然而，城市树木的不完整库存和树冠数据的缺乏意味着建模和预测服务生产的相关数据是稀缺的。我们的目标是用更丰富的数据更好地描述UF，并确定开发弹性UF的最佳实践，以支持现在和未来的生态系统服务。