• search hit 2 of 3
Back to Result List

A research framework for projecting ecosystem change in highly diverse tropical mountain ecosystems

  • 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 anTropical 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.show moreshow less

Export metadata

Additional Services

Search Google Scholar
Metadaten
Author: Jörg Bendix, Nicolay Aguire, Erwin Beck, Achim Bräuning, Roland Brandl, Lutz Breuer, Katrin Böhning‑Gaese, Mateus Dantas de Paula, Thomas Hickler, Jürgen Homeier, Diego Inclan, Christoph Leuschner, Eike L. Neuschulz, Matthias Schleuning, Juan P. Suarez, Katja TrachteORCiD, Wolfgang Wilcke, David Windhorst, Nina Farwig
DOI:https://doi.org/10.1007/s00442-021-04852-8
ISSN:0029-8549
ISSN:1432-1939
Title of the source (English):Oecologia
Document Type:Scientific journal article peer-reviewed
Language:English
Year of publication:2021
Tag:Biodiversity-land surface model; Functional traits; High mountains; Research framework; Response-effect-framework
Volume/Year:195
Issue number:3
First Page:589
Last Page:600
Faculty/Chair:Fakultät 2 Umwelt und Naturwissenschaften / FG Atmosphärische Prozesse
Einverstanden ✔
Diese Webseite verwendet technisch erforderliche Session-Cookies. Durch die weitere Nutzung der Webseite stimmen Sie diesem zu. Unsere Datenschutzerklärung finden Sie hier.