Jörg Bendix1, Nicolay Aguire2, Erwin Beck3, Achim Bräuning4, Roland Brandl5, Lutz Breuer6, Katrin Böhning-Gaese7,8, Mateus Dantas de Paula7, Thomas Hickler7,9, Jürgen Homeier10,11, Diego Inclan12,13, Christoph Leuschner10,11, Eike L Neuschulz7, Matthias Schleuning7, Juan P Suarez14, Katja Trachte15, Wolfgang Wilcke16, David Windhorst6, Nina Farwig17. 1. LCRS, Department of Geography, University of Marburg, Marburg, Germany. bendix@staff.uni-marburg.de. 2. Biodiversidad, Bosques y Servicios Ecosistemicos, Universidad Nacional de Loja, Loja, Ecuador. 3. Department of Plant Physiology and Bayreuth Centre of Ecology and Environmental Research, University of Bayreuth, Bayreuth, Germany. 4. Institute of Geography, Friedrich-Alexander-University (FAU) Erlangen-Nuremberg, Erlangen, Germany. 5. Animal Ecology, Department of Biology, University of Marburg, Marburg, Germany. 6. Institute for Landscape Ecology and Resources Management (ILR), Research Centre for BioSystems, Land Use and Nutrition (IFZ), Justus Liebig University, Giessen, Germany. 7. Senckenberg Biodiversity Climate Research Center (SBiK-F), Frankfurt am Main, Germany. 8. Institute for Ecology, Evolution and Diversity, Goethe University Frankfurt, Frankfurt am Main, Germany. 9. Department of Physical Geography, Goethe University Frankfurt, Frankfurt am Main, Germany. 10. Plant Ecology and Ecosystems Research, Albrecht Von Haller Institute for Plant Sciences, University of Göttingen, Göttingen, Germany. 11. Centre of Biodiversity and Sustainable Land Use (CBL), University of Göttingen, Göttingen, Germany. 12. Instituto Nacional de Biodiversidad, Sección Invertebrados, Quito, Ecuador. 13. Facultad de Ciencias Agrícolas, Universidad Central del Ecuador, Quito, Ecuador. 14. Departamento de Ciencias Biológicas, Universidad Técnica Particular de Loja, UTPL, Loja, Ecuador. 15. Institute for Environmental Sciences, Brandenburg University of Technology (BTU) Cottbus-Senftenberg, Cottbus, Germany. 16. Institute of Geography and Geoecology, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany. 17. Conservation Ecology, Department of Biology, University of Marburg, Marburg, Germany.
Abstract
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.
Tropical mountain ecosystems are threatened by climate and land-un class="Gene">se changes. Their diversity and complexity make projections how they respond to environmenpan>tal changes challenpan>ging. 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.
Entities:
Keywords:
Biodiversity-land surface model; Functional traits; High mountains; Research framework; Response-effect-framework
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