Angeler David G, Allen Craig R, Garmestani Ahjond, Pope Kevin L, Twidwell Dirac, Bundschuh Mirco
Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden.
School of Natural Resources, University of Nebraska - Lincoln, Lincoln, NE, USA.
Bull Environ Contam Toxicol. 2018 Nov;101(5):543-548. doi: 10.1007/s00128-018-2467-5. Epub 2018 Oct 24.
Different resilience concepts have different assumptions about system dynamics, which has implications for resilience-based environmental risk and impact assessment. Engineering resilience (recovery) dominates in the risk assessment literature but this definition does not account for the possibility of ecosystems to exist in multiple regimes. In this paper we discuss resilience concepts and quantification methods. Specifically, we discuss when a system fails to show engineering resilience after disturbances, indicating a shift to a potentially undesired regime. We show quantification methods that can assess the stability of this new regime to inform managers about possibilities to transform the system to a more desired regime. We point out the usefulness of an adaptive inference, modelling and management approach that is based on reiterative testing of hypothesis. This process facilitates learning about, and reduces uncertainty arising from risk and impact.
不同的恢复力概念对系统动态有着不同的假设,这对基于恢复力的环境风险和影响评估具有重要意义。工程恢复力(恢复)在风险评估文献中占主导地位,但该定义并未考虑生态系统存在多种状态的可能性。在本文中,我们讨论了恢复力概念和量化方法。具体而言,我们讨论了系统在受到干扰后未能表现出工程恢复力的情况,这表明系统转变为一种潜在的不理想状态。我们展示了能够评估这种新状态稳定性的量化方法,以便为管理者提供有关将系统转变为更理想状态的可能性的信息。我们指出了一种基于假设反复检验的适应性推理、建模和管理方法的实用性。这一过程有助于了解风险和影响,并减少由此产生的不确定性。