Abstract Acknowledging complexity within relationships between fundamental ecology and societal research is critical in improving our current understanding of how natural ecosystems work and how they could be managed to achieve set management goals. Specifically, this challenge is linked to the multifunctional nature of ecosystems. We develop the Bayesian Belief Multifunctionality Framework to studying nature-people links that allows a holistic and transparent analysis of the relationships between species, their functional traits, multiple ecosystem functions and multiple nature's contributions to people (NCPs). We assess seven ecosystem functions common in marine soft-sediments (secondary production, metal sequestration, denitrification, N-release, sediment stability, primary production and sediment formation) and nine NCPs (food and feed, supporting services, climate regulation, regulation of coastal water quality, physical and psychological experience, habitat creation, learning, materials and erosion control). We use a case study based on an extensive and diverse intertidal sandflat macrofaunal community within Kaipara Harbour, New Zealand. By testing different scenarios in which we identify the set of traits responsible for the highest function performance for every function, we show that functional redundancy (i.e., the presence of multiple species that deliver the maximum performance for a specific function) was high for some functions but low for others. In our model, functional redundancy was the lowest for denitrification and secondary production, while primary production exhibited high functional redundancy. The network analysis also allowed us to gain insight into functional synergies and trade-offs, resulting from maximising individual function to a trait set. The trait set that maximised secondary production contributes to higher sediment stability; the trait set that maximised metal sequestration contributes to higher N-release; and the trait set that maximised denitrification contributes to high rates of metal sequestration and N-release. Negative effects were also apparent, e.g., the trait set that maximised metal sequestration resulted in a lower probability in sediment stability and secondary production. Finally, the scenario testing feature of the framework allowed for exploration of the changes in NCPs from changes in macrofauna density. High density of species with a trait set identified as important to individual functions generated an increase in the provision of the majority of considered NCPs. Thanks to its clear and transparent result presentation and flexible analysis, the BN Multifunctionality Framework can deliver insightful messages into multifunctionality links helping to reveal the multifunctional nature of diverse and complex natural ecosystems.

中文翻译：

---

理解自然与人的联系的先进方法

摘要 承认基础生态学和社会研究之间关系的复杂性对于提高我们目前对自然生态系统如何运作以及如何管理它们以实现既定管理目标的理解至关重要。具体而言，这一挑战与生态系统的多功能性有关。我们开发了贝叶斯信念多功能框架来研究自然与人类的联系，该框架允许对物种之间的关系、它们的功能特征、多种生态系统功能和多种自然对人类的贡献 (NCP) 进行全面和透明的分析。我们评估了海洋软沉积物中常见的七种生态系统功能（二次生产、金属封存、反硝化、氮释放、沉积物稳定性、初级生产和沉积物形成）和九种 NCP（食物和饲料、支持服务、气候调节、沿海水质调节、生理和心理体验、栖息地创造、学习、材料和侵蚀控制）。我们使用基于新西兰凯帕拉港内广泛多样的潮间带沙地大型动物群落的案例研究。通过测试不同的场景，在这些场景中，我们确定了负责每个功能的最高功能性能的一组特征，我们表明功能冗余（即存在多个物种，为特定功能提供最大性能）对于某些功能来说很高但对其他人来说很低。在我们的模型中，反硝化和二次生产的功能冗余最低，而初级生产表现出高的功能冗余。网络分析还使我们能够深入了解功能协同作用和权衡，这是将个体功能最大化为特征集所产生的结果。最大化二次生产的特性集有助于提高沉积物稳定性；最大化金属螯合的特征集有助于更高的氮释放；最大化反硝化作用的特性集有助于高速率的金属螯合和 N 释放。负面影响也很明显，例如，最大化金属螯合的特征集导致沉积物稳定性和二次生产的可能性较低。最后，该框架的情景测试功能允许探索大型动物群密度变化引起的 NCP 变化。具有被确定为对个体功能重要的特征集的高密度物种导致大多数考虑的 NCP 的供应增加。由于其清晰透明的结果呈现和灵活的分析，BN多功能框架可以将有见地的信息传递到多功能链接中，有助于揭示多样化和复杂自然生态系统的多功能性质。