Natural ecosystems are currently experiencing unprecedented rates of anthropogenic disturbance. Given the potential ramifications of more frequent disturbances, it is imperative that we accurately quantify ecosystem responses to severe disturbance. Specifically, ecologists and managers need estimates of resistance and recovery from disturbance that are free of observation error, not biased by temporal stochasticity and that standardize disturbance magnitude among many disparate ecosystems relative to normal interannual variability. Here, I propose a statistical framework that estimates all four components of ecosystem responses to disturbance (resistance, recovery, elasticity and return time), while resolving all of the issues described above. Coupling autoregressive time series with exogenous predictors (ARX) models with impulse response functions (IRFs) allows researchers to statistically subject all ecosystems to similar levels of disturbance, estimate lag effects and obtain standardized estimates of resistance to and recovery from disturbance that are free from observation error and stochastic processes inherent in raw data.

中文翻译：

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将生态系统对干扰的反应统一到一个统计框架中

自然生态系统目前正遭受着前所未有的人为干扰。考虑到更频繁发生的干扰的潜在后果，我们必须准确地量化生态系统对严重干扰的响应。具体而言，生态学家和管理者需要估计不受干扰，不受观测误差，不受时间随机性影响，并且相对于正常年际变化标准化许多不同生态系统中干扰幅度的干扰的抵抗力和恢复力的估计值。在这里，我提出了一个统计框架，该框架估计了生态系统对干扰的响应的所有四个组成部分（阻力，恢复，弹性和返回时间），同时解决了上述所有问题。