Tropical mountain ecosystems are threatened by climate and land-use changes. Their diversity and complexity make projections how they respond to environmental changes challenging. A suitable way are trait-based approaches, by distinguishing between response traits that determine the resistance of species to environmental changes and effect traits that are relevant for species' interactions, biotic processes, and ecosystem functions. The combination of those approaches with land surface models (LSM) linking the functional community composition to ecosystem functions provides new ways to project the response of ecosystems to environmental changes. With the interdisciplinary project RESPECT, we propose a research framework that uses a trait-based response-effect-framework (REF) to quantify relationships between abiotic conditions, the diversity of functional traits in communities, and associated biotic processes, informing a biodiversity-LSM. We apply the framework to a megadiverse tropical mountain forest. We use a plot design along an elevation and a land-use gradient to collect data on abiotic drivers, functional traits, and biotic processes. We integrate these data to build the biodiversity-LSM and illustrate how to test the model. REF results show that aboveground biomass production is not directly related to changing climatic conditions, but indirectly through associated changes in functional traits. Herbivory is directly related to changing abiotic conditions. The biodiversity-LSM informed by local functional trait and soil data improved the simulation of biomass production substantially. We conclude that local data, also derived from previous projects (platform Ecuador), are key elements of the research framework. We specify essential datasets to apply this framework to other mountain ecosystems.

热带山区生态系统受到气候和土地利用变化的威胁。它们的多样性和复杂性使得预测它们如何应对环境变化具有挑战性。一种合适的方法是基于特征的方法，通过区分决定物种对环境变化的抵抗力的响应特征和与物种相互作用、生物过程和生态系统功能相关的影响特征。这些方法与将功能群落组成与生态系统功能联系起来的地表模型 (LSM) 相结合，为预测生态系统对环境变化的响应提供了新方法。通过跨学科项目 RESPECT，我们提出了一个研究框架，该框架使用基于性状的响应-效应框架 (REF) 来量化非生物条件之间的关系，群落中功能性状的多样性，以及相关的生物过程，为生物多样性 LSM 提供信息。我们将该框架应用于一个巨大的热带山地森林。我们使用沿海拔和土地利用梯度的地块设计来收集有关非生物驱动因素、功能特征和生物过程的数据。我们整合这些数据来构建生物多样性 LSM 并说明如何测试模型。REF 结果表明，地上生物量生产与气候条件的变化没有直接关系，而是通过功能性状的相关变化间接相关。食草与不断变化的非生物条件直接相关。以当地功能性状和土壤数据为基础的生物多样性 LSM 显着改善了生物量生产的模拟。我们得出的结论是，本地数据，也源自以前的项目（厄瓜多尔平台），是研究框架的关键要素。我们指定了必要的数据集以将此框架应用于其他山区生态系统。