DISSERTATION RESEARCH: Determining the drought sensitivity of the Amazon forest

论文研究：确定亚马逊森林的干旱敏感性

• 批准号: 1110540
• 负责人: Paul Moorcroft
• 金额: $ 1.5万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2013-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1110540&HistoricalAwards=false
• 关键词: DISSERTATION; RESEARCH; Determining; drought; sensitivity

Most large scale computer models are limited in their ability to predict the dynamics of forests under novel environmental conditions because the critical process of inter-plant competition and the physiological responses to water stress are not adequately represented. This project addresses these two fundamental problems by incorporating a more realistic hydrodynamic model of water movement in trees into a large scale model designed to predict changes in the composition and structure of forests. Direct field measurements of the conductivity of water in stems of trees and the point at which low water availability in the soil leads to a loss in plant vigor are required to constrain the model. This project will enable these critical field data to be collected. This research addresses the fundamental mechanisms that cause a tree to die under extreme water stress, particularly the physiological traits that control plant water use and adjust under water stress. That information will be formalized within the modeling framework that can then be used to identify the fundamental processes and associated tradeoffs that lead to survival or mortality within a dynamic tropical forest under extreme drought, and predict how shifts in species composition will play out as precipitation patterns change. This project will fill a large gap in our knowledge about water use and stress in tropical trees. With the models updated and coupled, advances can be made in terms of predicting how forests of the Amazon will evolve as climate change evolves over the next hundred years.

大多数大型计算机模型在预测新环境条件下森林动态的能力方面受到限制，因为它们不能充分代表植物间竞争的关键过程和对水分胁迫的生理反应。该项目解决这两个基本问题，将一个更现实的水在树木中运动的流体动力学模型纳入一个大规模的模型，旨在预测森林的组成和结构的变化。需要直接实地测量树木茎中水的电导率和土壤中低水可用性导致植物活力损失的点来约束模型。该项目将使这些重要的实地数据得以收集。这项研究探讨了导致树木在极端水分胁迫下死亡的基本机制，特别是控制植物水分利用和在水分胁迫下调整的生理特征。这些信息将在建模框架内正式化，然后可用于识别导致极端干旱下动态热带森林生存或死亡的基本过程和相关权衡，并预测随着降水模式的变化，物种组成的变化将如何发挥作用。这个项目将填补我们对热带树木用水和压力的认识上的一个巨大空白。随着模型的更新和耦合，可以在预测亚马逊森林将如何随着气候变化在未来一百年内演变方面取得进展。