Type 2: The Future of Ecosystems and Extremes: Using Diverse Environmental Data Sets in Support of Regional to Global Earth-System Models and Predictions

类型 2：生态系统和极端情况的未来：使用不同的环境数据集支持区域到全球地球系统模型和预测

• 批准号: 1137306
• 负责人: C Schlosser
• 金额: $ 453.62万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-02-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1137306&HistoricalAwards=false
• 关键词: Type; Future; Ecosystems; Extremes; Using

Our nation's natural and managed ecosystems are essential to public livelihood and its sustainable future. Extreme climate and weather events impose a substantial risk to ecosystem productivity, as such events are the most damaging and costly. Further increases in the frequency, strength, and/or duration of extreme events under altered environmental conditions may also result in irrecoverable damages to ecosystems. Therefore, it is of critical importance to comprehensively observe, understand, document, and predict ecosystems' response and resiliency to extreme environmental conditions and the extent to which irreversible thresholds may be crossed as a result of changes in the Earth's natural and human systems. Improved performance in predictive models is achieved only through observational evidence of ecosystem behavior under the full range of environmental conditions. The current suite of ecologic, meteorological, and hydrologic observations combined with the nation's next-generation National Ecologic Observation Network (NEON) allow an exciting opportunity to enable new analyses that comprehensively span the diverse types of ecosystems across our nation. This study undertakes coordinated calibration, evaluation, enhancement, and experimentation with a hierarchy of predictive tools that includes: models representing the field-scale mechanisms of ecosystems; a high-resolution regional ecosystem-climate model; as well as a global integrated assessment model of the linked earth-human systems. Through these, region-specific thresholds in the productivity, response, and resiliency of ecosystems governed by human-altered shifts in weather and climate extremes as well as land use, which pose severe implications for ecosystem services, will be identified.The testing and evaluation of ecosystem models against the NEON observations will identify the critical model capabilities required to faithfully predict ecosystem response to extreme conditions. Under the auspice of potential climate and environmental change through the end of this century, projections with regional and global human-earth systems models will also allow for a risk-based assessment of ecologic change and resiliency. This is possible through the ability to run these models across the range of plausible human emissions and the climate/ecologic response. The atmospheric outputs of these regional ecosystem-climate projections could then also be used as boundary conditions for other detailed studies of regional climate impacts - such as air quality and water resources (quantity and quality). Overall, the scientific assessments and predictions from this study will enable local stakeholders as well as national and international policymakers to make more informed decisions regarding mitigation and adaptation strategies - particularly those that are relevant to the protection of natural and managed ecosystems threatened by extreme environments.

我们国家的自然和管理的生态系统对公共生计及其可持续未来至关重要。极端气候和天气事件给生态系统生产力带来了巨大风险，因为这类事件的破坏性最大，代价最高。在环境条件改变的情况下，极端事件的频率、强度和/或持续时间进一步增加，也可能对生态系统造成不可恢复的损害。因此，全面观察、了解、记录和预测生态系统对极端环境条件的反应和复原力，以及由于地球自然和人类系统的变化而可能跨越不可逆转阈值的程度，至关重要。只有通过在各种环境条件下观察到的生态系统行为证据，才能提高预测模型的性能。目前的生态，气象和水文观测套件与国家的下一代国家生态观测网络（氖）相结合，为全面跨越我国不同类型生态系统的新分析提供了一个令人兴奋的机会。这项研究进行了协调的校准，评估，增强和实验的层次结构的预测工具，其中包括：代表现场规模的生态系统机制的模型;高分辨率的区域生态系统-气候模型;以及全球综合评估模型的连接地球-人类系统。通过这些，在生产力，响应和生态系统的弹性由人为改变的天气和气候极端变化以及土地利用，这对生态系统服务的严重影响，将确定特定区域的阈值。测试和评估生态系统模型对氖观测将确定关键的模型能力，忠实地预测生态系统对极端条件的反应。在到本世纪末可能发生的气候和环境变化的背景下，利用区域和全球人地系统模型进行的预测也将有助于对生态变化和复原力进行基于风险的评估。通过在合理的人类排放和气候/生态响应范围内运行这些模型，这是可能的。这些区域生态系统-气候预测的大气输出也可用作其他区域气候影响详细研究的边界条件-如空气质量和水资源（数量和质量）。总体而言，本研究的科学评估和预测将使当地利益攸关方以及国家和国际决策者能够就缓解和适应战略做出更明智的决定，特别是那些与保护受极端环境威胁的自然和管理的生态系统有关的决定。