School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Proc Natl Acad Sci U S A. 2013 Feb 12;110(7):2496-9. doi: 10.1073/pnas.1218022110. Epub 2013 Jan 22.
Long-term time series of marine ecological indicators often are characterized by large-amplitude state transitions that can persist for decades. Understanding the significance of these variations depends critically on the underlying hypotheses characterizing expected natural variability. Using a linear autoregressive model in combination with long-term zooplankton observations off the California coast, we show that cumulative integrations of white-noise atmospheric forcing can generate marine population responses that are characterized by strong transitions and prolonged apparent state changes. This model provides a baseline hypothesis for explaining ecosystem variability and for interpreting the significance of abrupt responses and climate change signatures in marine ecosystems.
长期的海洋生态指标时间序列通常具有可持续数十年的大幅状态转变的特点。理解这些变化的意义取决于描述预期自然变异性的基本假设。本文使用线性自回归模型结合加利福尼亚沿海的长期浮游动物观测数据,结果表明,大气白噪声累积积分可以产生具有强转变和长期明显状态变化的海洋种群响应。该模型为解释生态系统变异性以及解释海洋生态系统中突然响应和气候变化特征的意义提供了一个基本假设。