EAGER: Effects of environmental variability on population dynamics in the Long-Term Ecological Research network

一种普遍的看法是，环境波动——今年干旱，明年洪水——会对种群产生负面影响，并可能导致它们灭绝。该提案将使用在长期生态研究站点收集的现有长期人口数据来严格检验这种看法。研究结果可能推翻这一长期存在的假设，并为种群生态学领域提供根本性的新见解。这个项目合成的数据将通过全世界使用的全球人口动态数据库提供。更清楚地了解环境变化如何影响种群动态将改善保护和管理工作。环境变化积极影响的证据将改变保护濒危物种或管理入侵物种的策略。该项目将支持一名博士后研究员和一名数据分析师，并将为研究生和本科生提供建模、统计分析和数据综合方面的培训机会。这个项目将尝试首次大规模综合人口数据，以评估环境变化对人口动态的影响。几十年来，25个长期生态研究项目一直在收集种群水平的数据，但这些数据很少用于解决种群生态学的关键问题。研究者将通过人工检查从LTER数据门户获得的6000个数据集中的每一个，通过梳理数据档案，并通过直接联系LTER研究人员，收集所有LTER时间序列的丰度或生命率。将对这些数据进行分析，以检验对数（人口增长率）分布的偏度的大小和方向，以此作为对环境变化的非线性反应的指标。当空间复制时间序列可用时，将它们用于分离过程误差和抽样误差，并使用分层模型进行分析。一旦人口增长率分布的不均匀性被量化，研究者将试图确定关键的环境驱动因素。这是项目中风险最大的部分；在可能的情况下，这将使研究人员能够量化人口反应函数，并更有把握地预测变异对人口动态的影响。环境变异性的影响通常是中性或积极的，这一证据将从根本上改变对随机环境中种群动态的理解。

A common perception is that environmental fluctuations - drought one year, floods the next - have negative effects on populations and could drive them to extinction. This proposal will use existing long-term population data collected at Long Term Ecological Research sites to test this perception rigorously. Results could overturn this long-standing assumption and provide fundamental new insights to the field of population ecology. Data synthesized by this project will be available through a global population dynamics database that is used worldwide. A clearer understanding of how environmental variability affects population dynamics will improve conservation and management efforts. Evidence for positive effects of environmental variability will alter strategies to conserve threatened species or to manage invasive species. The project will support a postdoctoral researcher and a data analyst, and will provide training opportunities at the interface of modeling, statistical analyses, and data synthesis for graduate and undergraduate students. This project will attempt the first large-scale synthesis of demographic data to assess the effects of environmental variability on population dynamics. Twenty-five Long Term Ecological Research (LTER) projects have been collecting population-level data for decades, yet these data are rarely used to address key questions in population ecology. The investigator will collect all LTER time series of abundances or vital rates by manually inspecting each of the 6,000 data sets available from the LTER data portal, by combing data archives, and by contacting LTER researchers directly. The data will be analyzed to test the magnitude and direction of skewness in the distribution of log(population growth rate) as an indicator of non-linear responses to environmental variation. When spatially-replicated time series are available, they will be used to separate process error from sampling error and analyzed with hierarchical models. Once skewness in distributions of population growth rates is quantified, the investigator will attempt to identify key environmental drivers. This is the riskiest part of the project; when possible, these will allow the researcher to quantify demographic response functions and predict the effects of variability on population dynamics with greater confidence. Evidence that effects of environmental variability are commonly neutral or positive will fundamentally alter understanding of population dynamics in stochastic environments.