A growing challenge for risk, vulnerability, and resilience assessment is the ability to understand, characterize, and model the complexities of our joint socioecological systems, often delineated with differing natural (e.g., watershed) and imposed (e.g., political) boundaries at the landscape scale. To effectively manage such systems in the increasingly dynamic, adaptive context of environmental change, we need to understand not just food web interactions of contaminants or the flooding impacts of sea level rise and storm surges, but rather the interplay between social and ecological components within the inherent and induced feedforward and feedback system mechanisms. Risk assessment, in its traditional implementation, is a simplification of a complex problem to understand the basic cause‐and‐effect relationships within a system. This approach allows risk assessors to distill a complex issue into a manageable model that quantifies, or semiquantifies, the effects of an adverse stressor. Alternatively, an integrated risk and resilience assessment moves toward a solution‐based assessment with the incorporation of adaptive management practices as 1 of 4 parts of system resilience (i.e., prepare, absorb, recover, and adapt), and directly considers the complexities of the systems being modeled. We present the Multilevel Risk and Resilience Assessment Parameterization framework for the systematic parameterization and deconstruction of management objectives and goals into assessment metrics and quantifiable risk measurement metrics and complementary resilience measurement metrics. As a proof‐of‐concept, the presented framework is paired with the Bayesian Network–Relative Risk Model for a human‐focused subset of a larger risk and resilience assessment of climate change impacts within the Charleston Harbor Watershed of South Carolina. This new parameterization framework goes beyond traditional simplification and embraces the complexity of the system as a whole, which is necessary for a more representative analysis of an open, dynamic complex system. Integr Environ Assess Manag 2021;17:131–146. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC)

中文翻译：

---

综合风险和复原力评估的参数化框架和量化方法。

风险，脆弱性和复原力评估面临的挑战越来越大，那就是能够理解，表征和建模我们共同的社会生态系统的复杂性的能力，这些复杂性通常由景观的不同自然（例如分水岭）和强加（例如政治）边界来描绘规模。为了在环境变化日益动态，适应性强的环境下有效管理此类系统，我们不仅需要了解污染物的食物网相互作用或海平面上升和风暴潮的洪水影响，还需要了解社区内社会与生态成分之间的相互作用。固有的和诱发的前馈和反馈系统机制。在传统的实施方式中，风险评估是对复杂问题的简化，以了解系统内的基本因果关系。这种方法使风险评估者可以将复杂的问题提炼成可管理的模型，该模型可以量化或半量化不利压力源的影响。另外，综合的风险和弹性评估将基于适应性管理实践作为系统弹性4个部分（即准备，吸收，恢复和适应）中的1个纳入到基于解决方案的评估中，并直接考虑了复杂性。系统建模。我们提出了多级风险和复原力评估参数化框架，用于将管理目标和目标进行系统化的参数化和解构，以评估指标，可量化的风险衡量指标和补充的复原力衡量指标。作为概念证明，提出的框架与贝叶斯网络相对风险模型结合使用，以人为中心，对南卡罗来纳州的查尔斯顿港流域内的气候变化影响进行了更大的风险和适应力评估。这个新的参数化框架超出了传统的简化范围，涵盖了整个系统的复杂性，这对于更开放，动态的复杂系统的代表性分析是必需的。Integr环境评估管理2021; 17：131–146。©2020作者。Wiley Periodicals LLC代表环境毒理化学协会（SETAC）发布的《综合环境评估与管理》