Roberts Caleb P, Twidwell Dirac, Burnett Jessica L, Donovan Victoria M, Wonkka Carissa L, Bielski Christine L, Garmestani Ahjond S, Angeler David G, Allred BradyW, Jones Matthew O, Naugle David E, Sundstrom Shana M, Allen Craig R
University of Nebraska, Department of Agronomy & Horticulture, Keim Hall, Lincoln, NE 66583-0915, USA.
Nebraska Cooperative Fish and Wildlife Research Unit, University of Nebraska, School of Natural Resources, Hardin Hall, Lincoln, NE 68583-0961, USA.
Rangel Ecol Manag. 2018 Nov;71(6):659-670. doi: 10.1016/j.rama.2018.04.012.
New concepts have emerged in theoretical ecology with the intent to quantify complexities in ecological change that are unaccounted for in state-and-transition models and to provide applied ecologists with statistical early warning metrics able to predict and prevent state transitions. With its rich history of furthering ecological theory and its robust and broad-scale monitoring frameworks, the rangeland discipline is poised to empirically assess these newly proposed ideas while also serving as early adopters of novel statistical metrics that provide advanced warning of a pending shift to an alternative ecological regime. Were view multivariate early warning and regime shift detection metrics, identify situations where various metrics will be most useful for rangeland science, and then highlight known shortcomings. Our review of a suite of multivariate-based regime shift/early warning indicators provides a broad range of metrics applicable to a wide variety of data types or contexts, from situations where a great deal is known about the key system drivers and a regime shift is hypothesized a priori, to situations where the key drivers and the possibility of a regime shift are both unknown. These metrics can be used to answer ecological state-and-transition questions, inform policymakers, and provide quantitative decision-making tools for managers.
理论生态学中出现了一些新的概念，旨在量化生态变化中的复杂性，这些复杂性在状态和转换模型中未得到考虑，并为应用生态学家提供能够预测和预防状态转换的统计预警指标。凭借其在推进生态理论方面的丰富历史以及强大而广泛的监测框架，牧场学科准备好对这些新提出的观点进行实证评估，同时还将成为新统计指标的早期采用者，这些指标能为即将转向另一种生态状态提供预警。我们审视多变量预警和状态转换检测指标，确定各种指标在哪些情况下对牧场科学最有用，然后突出已知的缺点。我们对一系列基于多变量的状态转换/预警指标的审视提供了广泛适用于各种数据类型或背景的指标，从对关键系统驱动因素了解很多且先验假设存在状态转换的情况，到关键驱动因素和状态转换可能性均未知的情况。这些指标可用于回答生态状态和转换问题，为政策制定者提供信息，并为管理者提供定量决策工具。
