Forests in flux: reconstructing ecotone shifts to improve understanding of climate--vegetation feedbacks

预计气候变化将影响加拿大经济的所有部门。社会缓解和适应这些影响的能力部分依赖于了解气候-植被反馈（CVF）如何放大或调解气候变化;这是全球变化生态学的核心问题。CVF在多个时间尺度上运行。快速处理（例如，叶尺度碳通量）在次年度时间尺度上运行，而缓慢的过程（例如，受森林组成和结构变化的驱动）发生在十年和更长的时间尺度上。缓慢的过程很少直接从仪器数据中观察到。然而，对未来陆地生物圈、CVFs和碳循环的预测取决于目前对这些缓慢过程的理解。网络的古生态数据，特别是沉积物花粉和树木生态学数据，提供了最强的观测约束长期植被动态，他们允许生态过程和反馈的推断。提高对影响CVFs的缓慢过程的理解需要开发利用古生态数据和理解生物圈-大气相互作用的新方法。这项研究计划的长期目标是提高对陆地生物圈和大气之间反馈的理解。该提案描述了通过一系列复杂性增加的脚手架项目实现这一目标的途径。更具体地说，我的中间目标按照复杂性的增加顺序是：（1）开发新的方法，从古生态代用数据重建生物物理土地覆盖属性，（2）利用和整合这些生物物理重建和现有方法的信息，以检验关于植被对气候影响的假设，反之亦然，（3）开发新方法，将生物物理重建正式纳入地球系统模型;（4）开发和实施数据优化策略，填补古生态学数据空白。预计加拿大将经历本世纪最大的气候变化;北方森林被认为对气候破坏高度敏感。这些预测的变化迫使土地管理者制定新的管理战略。然而，对CVF的理解仍然是一个关键的不确定性领域。该研究计划通过将先进的定量方法与现有的证据和理解相结合，解决了对使用现代数据模型集成方法管理CVF的基本过程缺乏了解的问题。这些进展将为气候适应规划提供信息，为管理者和政策制定者提供关于缓慢过程及其对CVF影响的变革性知识。

Climate change is predicted to impact all sectors of the Canadian economy. The ability of society to mitigate and adapt in response to these impacts relies in part on understanding how how climate-vegetation feedbacks (CVFs) amplify or mediate climatic changes; this is a central question in global change ecology. CVFs operate at multiple timescales. Fast processes (e.g., leaf-scale carbon fluxes) operate at sub-annual timescales, while slow processes (e.g., driven by changes in forest composition and structure) occur over decadal and longer timescales. Slow processes are rarely directly observed from instrumental data. However, predictions of the future terrestrial biosphere, CVFs, and the carbon cycle depend on current understanding of these slow processes. Networks of paleoecological data, particularly sediment pollen and dendroecological data, offer the strongest observational constraints on long-term vegetation dynamics; they allow for inference about ecological processes and feedbacks. Improved understanding of slow processes that influence CVFs requires the development of new approaches that leverage paleoecological data and understanding of biosphere-atmosphere interactions. The long-term objective of this research program is to improve understanding of feedbacks between the terrestrial biosphere and the atmosphere. This proposal describes a path towards this objective via a series of scaffolded projects that increase in complexity. More specifically, my intermediary objectives in order of increasing complexity are to: (1) develop new methods to reconstruct biophysical land cover attributes from paleoecological proxy data, (2) leverage and integrate information from these biophysical reconstructions and existing methods to test hypotheses about the impacts of vegetation on climate and vice versa, (3) develop new methods to formally assimilate biophysical reconstructions into Earth System Models, and (4) develop and implement data optimization strategies to fill in paleoecological data gaps. Canada is predicted to experience some of the largest climate changes this century; Boreal forests are thought to be highly sensitive to climate disruptions. These predicted changes are forcing land managers to develop new management strategies. However, understanding of CVFs remains a critical area of uncertainty. This research program addresses the lack of understanding of the fundamental processes that govern CVFs using a modern approach to data-model integration by combining advanced quantitative methods with existing evidence and understanding. These advances will inform climate adaptation planning by providing both managers and policymakers with transformative knowledge about slow processes and their impacts on CVFs.