Collaborative Research: Integrating Antarctic Environmental and Biological Predictability to Obtain Optimal Forecasts

该奖项的全部或部分资金来自《2021年美国救援计划法案》(公法117-2)。许多生物地球化学和生物物理过程在当前和即将到来的世纪中正在发生变化。人们对这些过程的机制和可预测性仍然知之甚少。对这些进展的理解的局限性限制了气候预测。同样，生态预测仍然是一门新兴学科。对物种内部和物种之间的可预测性进行比较评估，对于理解允许(或阻止)有用的生态预测的因素至关重要。这项研究将揭示气候系统动力学对一系列尺度上的生态可预测性的影响，并将研究这种作用在南极生态过程、物种和地区之间的差异。项目研究将使用几个极地物种可用的最长数据集，研究南极气候的可预测性及其对海鸟种群响应的影响。具体地说，PI将1)确定引起南极洲气候可预测性的物理机制，2)在一定范围内确定气候和生态过程之间的关系，以及3)揭示在一系列尺度上控制生态可预测性的因素(例如，与短期适应性管理相关的因素与与世纪末时间尺度相关的因素)。这些目标将通过对现有气候数据和百年时间尺度、大气-海洋全球环流模型(AOGCMS)的分析，以及对横跨整个大陆的一系列生态位、生活史和研究地点的多种海鸟物种的现有长期人口数据的结合分析来实现。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).Many biogeochemical and biophysical processes are changing in the present and coming century. The mechanisms and the predictability of these processes are still poorly understood. Limits in understanding of these progress limits climate forecasting. Similarly, ecological forecasting remains a nascent discipline. Comparative assessments of predictability, both within and among species, are critically needed to understand the factors that allow (or prevent) useful ecological forecasts. This study will reveal the influence of climate system dynamics on ecological predictability across a range of scales, and will examine how this role differs among ecological processes, species and regions of Antarctic.The project research will examine the predictability of Antarctic climate and its influence on seabird demographic response, predictability at various temporal and spatial scales, using the longest datasets available for several polar species. Specifically, the PI will 1) identify the physical mechanisms giving rise to climate predictability in Antarctica, 2) identify the relationships between climate and ecological processes at a range of scales, and 3) reveal the factors controlling ecological predictability across a range of scales (e.g., those relevant for short-term adaptive management versus those relevant at end-of-century timescales). These objectives will be achieved using the analysis of existing climate data and century length time-scales, Atmosphere-Ocean Global Circulation Models (AOGCMs), with coupled analysis of existing long-term demographic data for multiple seabird species that span a range of ecological niches, life histories, and study sites across the continent.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.