Statistical Methods for Regime Shifts

该项目将制定和评估正式的统计方法，以追溯性地确定生态系统中相互作用种群丰度的时间序列数据中的状态变化。 它将进一步制定和评估正式的统计方法，以确定这种生态系统是否是反应性的（即，系统的动力学是否会放大扰动）。 既定的统计学原则将被应用，并基于一个相互作用的人口系统的动力学的一般模型。这些方法的性能将通过一系列的模拟实验，并与他们的应用程序，以前公布的数据集进行评估。 扰动可能导致自然生态系统发生状态转变的可能性（即，从一个局部稳定的稳定状态到另一个局部稳定的稳定状态的突然转变）对于管理具有重要的意义。为了理解真实的系统中的这种现象，有必要能够区分状态转换和其他类型的可变性。本项目的第一个目标是提供这些方法，没有这些方法，就难以在这一领域的管理方面取得科学进展。该项目的第二个目标是开发用于确定系统是否是反应性的方法（即，能够放大扰动）。 这一点很重要，因为反应性代表了一种可能的“机制转变途径”。“因此，了解一个系统是否是反应性的，对于寻求避免制度转变的管理人员来说很重要。 这项工作将有助于为渔业管理和养护方面的决策提供信息。该项目的结果将发表在同行评审的科学文献中，并将免费提供应用这些方法的MATLAB例程。

This project will develop and assess formal statistical methods for the retrospective identification of a regime shift in time series data of the abundances of interacting populations in an ecosystem. It will further develop and assess formal statistical methods for determining whether such an ecosystem is reactive (i.e., whether the dynamics of the system would amplify a perturbation). Well-established principles of statistics will be applied and based on a general model of the dynamics of a system of interacting populations. The performance of these methods will be assessed through a series of simulation experiments and with their application to previously published data sets. The possibility that a perturbation can cause a natural ecosystem to undergo a regime shift (i.e., an abrupt shift from one locally stable steady state to another) has important implications for management. To develop an understanding of this phenomenon in real systems, it is necessary to be able to distinguish between regime shifts and other types of variability. The first objective of this project is to provide such methods, without which scientific progress in support of management in this area is difficult. The second objective of the project is to develop methods for determining whether a system is reactive (i.e., capable of amplifying a perturbation). This is important because reactivity represents one possible "route to regime shift." Knowing whether a system is reactive is therefore important to managers seeking to avoid a regime shift. This work will help inform decision-making in fisheries management and conservation. The results of this project will be published in the peer-reviewed scientific literature and MATLAB routines for applying the methods will be made freely available.