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-一年干旱，下一年洪水-对种群产生负面影响，可能使它们灭绝。该提案将使用在长期生态研究地点收集的现有长期人口数据来严格测试这一观点。这些结果可能会推翻这一长期存在的假设，并为种群生态学领域提供新的基本见解。该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异性如何影响种群动态将改善养护和管理工作。环境变化的积极影响的证据将改变战略，以保护受威胁的物种或管理入侵物种。该项目将支持一名博士后研究员和一名数据分析员，并将为研究生和本科生提供建模、统计分析和数据合成接口方面的培训机会。该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（LTER）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中的关键问题。研究者将通过手动检查LTER数据门户提供的6，000个数据集中的每一个，通过梳理数据档案，并直接联系LTER研究人员，收集所有LTER丰度或生命率的时间序列。将对数据进行分析，以测试对数（种群增长率）分布的偏度大小和方向，作为对环境变化的非线性反应的指标。当空间复制的时间序列是可用的，他们将被用来从抽样误差分离过程误差和分层模型进行分析。一旦人口增长率分布的偏度得到量化，调查人员将试图确定关键的环境驱动因素。这是该项目风险最大的部分;在可能的情况下，这些将使研究人员能够量化人口响应函数，并更有信心地预测变异性对人口动态的影响。有证据表明，环境变异的影响通常是中性或积极的，这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.