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Leveraging plant functional traits in the design of nature‐based solutions: A research agenda
Journal of Ecology ( IF 5.3 ) Pub Date : 2024-07-16 , DOI: 10.1111/1365-2745.14371
Advyth Ramachandran 1, 2, 3 , Laura Dee 1, 3 , Meghan Hayden 1, 3 , Katharine Suding 1, 2, 3
Affiliation  

Nature‐based solutions (NbS) involve interventions that modify ecosystems to enhance multiple ecosystem services (ES). Yet, despite our increasing knowledge of the key role that functional traits play in determining ES, certain types of NbS often do not consider a functional trait perspective. A reason for this lack of translation may be the range of NbS approaches and levels of knowledge of trait–ES relationships. Functional traits may be most useful as targets for NbS design when knowledge on trait–ES mapping is established and the NbS involves a medium or high level of management intervention. A richer understanding of causality in trait–ES and trait–resilience linkages, and context dependency in those linkages, is needed to broaden the application of functional traits in NbS. An improved understanding of trait linkages with cultural ES and how traits interact with stakeholder values to shape NbS uptake would also improve application. Synthesis: A greater consideration of functional traits will increase the efficacy of NbS projects, and could be accelerated by tackling gaps in knowledge about functional traits. Here, we envision a research agenda that both advances NbS design and leverages the varied objectives of NbS to robustly test our knowledge about functional traits.

中文翻译:


利用植物功能特性设计基于自然的解决方案:研究议程



基于自然的解决方案(NbS)涉及修改生态系统以增强多种生态系统服务(ES)的干预措施。然而,尽管我们越来越了解功能性状在决定 ES 中所起的关键作用,但某些类型的 NbS 常常不考虑功能性状的观点。这种缺乏转化的原因可能是 NbS 方法的范围和知识水平。特质-ES关系。当建立了性状-ES 映射知识并且 NbS 涉及中等或高水平的管理干预时,功能性状可能最适合作为 NbS 设计的目标。为了拓宽功能性状在 NbS 中的应用,需要对性状-ES 和性状-复原力联系中的因果关系以及这些联系中的背景依赖性有更丰富的理解。更好地理解特质与文化 ES 的联系以及特质如何与利益相关者价值观相互作用以塑造 NbS 的吸收也将改善应用。综合:更多地考虑功能性状将提高 NbS 项目的效率,并且可以通过解决功能性状知识的差距来加速。在这里,我们设想了一个研究议程,既推进 NbS 设计,又利用 NbS 的不同目标来有力地测试我们对功能特征的了解。
更新日期:2024-07-16
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