How important is "colored" stochasticity for plant population dynamics?

“有色”随机性对于植物种群动态有多重要？

• 批准号: 1020889
• 负责人: Elizabeth Crone
• 金额: $ 50.26万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2014-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1020889&HistoricalAwards=false
• 关键词: How; important; colored; stochasticity; plant

Ecologists need to predict the impacts of human-caused change on plant and animal populations. These predictions are often made using demographic models, which combine vital rates (birth, growth, and death rates) into estimates of how population size changes in response to changes in the environment. Variation in vital rates is usually modeled as "white noise", meaning that rates in one year are not correlated with rates in the recent past or recent future. However, there are good reasons to believe that variation may be "red", meaning good years tend to follow good years (due to trends in environmental conditions or carry-over through physiological condition), and there is evidence that some species experience "blue" noise, meaning bad years tend to follow good years (for example, if reproduction depletes stored resources). In the few cases where researchers have looked for "colored" noise in plant and animal populations, these effects have substantially changed predictions about population dynamics. This project will develop methods for estimating "colored" stochasticity and also evaluate how important this variation is for population dynamics. The research will compare population dynamics of three species of perennial wildflowers, representing different extremes: 1) a perennial wildflower of arid environments, which experiences high costs of reproduction, typical of "blue noise"; 2) a wildflower that lives along meandering rivers, which experiences directional changes in the environment, typical of "red noise"; and 3) an orchid near the northern edge of its global distribution. In this this latter species the color of noise is unknown, but likely important for life-history evolution and responses to climate change. As part of this project, the researcher will also evaluate if and how hundreds of short-term (3-10 year) studies of different plant species (more than 300 have been published to date) can be used to infer long-term effects of environmental change for plants in general. Additional broader impacts include developing statistical methods for analysis of short time series, educating students in mathematical biology and ecological forecasting, and promoting international awareness through collaboration with botanists in Oulanka, Finland (near the intersection of the Arctic Circle with the Finland/Russia border) and with statistical ecologists in Brisbane, Australia.

生态学家需要预测人为变化对动植物种群的影响。这些预测通常是使用人口模型进行的，该模型将联合收割机生命率（出生率，生长率和死亡率）结合到人口规模如何响应环境变化的估计中。 生命率的变化通常被建模为“白色噪声”，这意味着一年中的速率与最近的过去或最近的将来的速率不相关。 然而，有充分的理由相信，变异可能是“红色”的，这意味着好年份往往跟随好年份（由于环境条件的趋势或生理条件的延续），并且有证据表明，一些物种经历了“蓝色”噪音，这意味着坏年份往往跟随好年份（例如，如果繁殖耗尽了储存的资源）。 在少数情况下，研究人员在植物和动物种群中寻找“有色”噪音，这些影响大大改变了对种群动态的预测。 本计画将发展估计“有色”随机性的方法，并评估这种变异对族群动态的重要性。 这项研究将比较三种代表不同极端情况的多年生野花的种群动态：1）干旱环境中的多年生野花，经历高繁殖成本，典型的“蓝噪音”; 2）生活在沿着蜿蜒河流的野花，经历环境的方向变化，典型的“红噪音”;以及3）一种兰花，靠近其全球分布的北方边缘。在后一种物种中，噪音的颜色是未知的，但可能对生命史进化和对气候变化的反应很重要。 作为该项目的一部分，研究人员还将评估数百项不同植物物种的短期（3-10年）研究（迄今已发表300多项）是否以及如何用于推断环境变化对植物的长期影响。 其他更广泛的影响包括开发用于分析短时间序列的统计方法，对学生进行数学生物学和生态预测方面的教育，并通过与芬兰奥兰卡（靠近北极圈与芬兰/俄罗斯边界的交叉点）的植物学家和澳大利亚布里斯班的统计生态学家合作，提高国际认识。