Institute of Marine Sciences (ICM-CSIC), Passeig Marítim de la Barceloneta, n° 37-49, 08003, Barcelona, Spain .
National Institute of Water and Atmospheric Research, P.O. Box 11-115, Hamilton, New Zealand.
J Environ Manage. 2018 Dec 15;228:319-327. doi: 10.1016/j.jenvman.2018.09.034. Epub 2018 Sep 18.
It is crucial that societies are informed on the risks of impoverished ecosystem health for their well-being. For this purpose, Ecological Integrity (EI) is a useful concept that seeks to capture the complex nature of ecosystems and their interaction with social welfare. But the challenge remains to measure EI and translate scientific terminology into operational language to inform society. We propose an approach that simplifies marine ecosystem complexity by applying scientific knowledge to identify which components reflect the state or state change of ecosystems. It follows a bottom-up structure that identifies, based on expert knowledge, biological components related with past and present changing conditions. It is structured in 5 stages that interact in an adaptive way: stage 1, in situ observations suggest changes could be happening; stage 2 explores available data that represent EI; stage 3, experts' workshops target the identification of the minimum set of variables needed to define EI, or the risk of losing EI; an optative stage 4, where deviance from EI, or risk of deviance, is statistically assessed; stage 5, findings are communicated to society. We demonstrate the framework effectiveness in three case studies, including a data poor situation, an area where lack of reference sites hampers the identification of historical changes, and an area where diffuse sources of stress make it difficult to identify simple relationships with of ecological responses. The future challenge is to operationalise the approach and trigger desirable society actions to strengthen a social-nature link.
必须让社会了解生态系统健康不良对其福祉的风险。为此，生态完整性 (EI) 是一个有用的概念，旨在捕捉生态系统的复杂性及其与社会福利的相互作用。但仍面临挑战，需要衡量 EI 并将科学术语转化为操作语言，以便为社会提供信息。我们提出了一种方法，通过应用科学知识来识别反映生态系统状态或状态变化的组件，从而简化海洋生态系统的复杂性。它遵循自下而上的结构，根据专家知识识别与过去和现在变化条件相关的生物组件。它由 5 个相互作用的阶段构成：第 1 阶段，现场观测表明可能正在发生变化；第 2 阶段，探索代表 EI 的现有数据；第 3 阶段，专家研讨会旨在确定定义 EI 或失去 EI 风险所需的最小变量集；第 4 阶段，选择偏离 EI 或偏离风险的情况进行统计评估；第 5 阶段，将研究结果传达给社会。我们在三个案例研究中展示了该框架的有效性，包括数据匮乏的情况、缺乏参考点的区域（这阻碍了对历史变化的识别）以及弥散性压力源使得难以识别与生态响应的简单关系的区域。未来的挑战是将该方法付诸实践，并引发社会采取行动，以加强社会与自然的联系。
