Understanding complex systems is essential to ensure their conservation and management. Modelling has become a common tool for supporting our understanding of complex ecological systems and, by extension, their conservation. Modelling, however, is largely a social process constrained by individual's mental models (i.e. a small-scale internal model of how a part of the world works, on the basis of knowledge, experience, values, beliefs and assumptions) as well as system complexity. To account for both a system's complexity and the diversity of knowledge of complex systems, we developed a novel method for the development of a shared qualitative complex system model. Importantly, we disaggregated the system into smaller 'sub-system modules' that each represented a functioning unit, about which an individual is likely to have more comprehensive knowledge. This modular approach allowed us to elicit an individual mental model of a defined sub-system for which the individual had a higher level of confidence in their knowledge of the relationships between variables. The challenge then, was in bringing these sub-system models together to form a complete, shared model of the entire system. To achieve this goal, our method comprised four phases: Phase 1: develop the system framework and sub-system modules; Phase 2: develop the individual mental model elicitation methods; Phase 3: elicit the mental models; and Phase 4a: identify and isolate differences for exploration and Phase 4b: identify similarities to co-create a shared qualitative model. We anticipate that this method will improve models of complex systems, increasing their reliability for conservation management. Article impact statement: Integration of knowledge sets across disciplines improves understanding and conservation of complex systems. This article is protected by copyright. All rights reserved.

中文翻译：

---

一种开发复杂系统共享定性模型的方法

了解复杂系统对于确保其保护和管理至关重要。建模已成为支持我们理解复杂生态系统及其保护的常用工具。然而，建模在很大程度上是一个受个人心智模型（即基于知识、经验、价值观、信念和假设的世界一部分如何运作的小规模内部模型）以及系统复杂性约束的社会过程. 为了兼顾系统的复杂性和复杂系统知识的多样性，我们开发了一种用于开发共享定性复杂系统模型的新方法。重要的是，我们将系统分解为更小的“子系统模块”，每个模块代表一个功能单元，个人可能拥有更全面的知识。这种模块化方法使我们能够引出一个已定义子系统的个人心理模型，个人对他们对变量之间关系的知识有更高的信心。当时的挑战是将这些子系统模型组合在一起以形成整个系统的完整共享模型。为实现这一目标，我们的方法包括四个阶段： 阶段 1：开发系统框架和子系统模块；阶段 2：开发个人心智模型的启发方法；第三阶段：引出心智模型；阶段 4a：识别和隔离差异以进行探索 阶段 4b：识别相似性以共同创建共享的定性模型。我们预计这种方法将改进复杂系统的模型，提高保护管理的可靠性。文章影响声明：跨学科知识集的整合提高了对复杂系统的理解和保护。本文受版权保护。版权所有。