Coordination Funds

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The tropical mountain rain and dry forests (MRF, MDF) of SE-Ecuador are threatened by climate and land-use changes. Their diversity and complexity make projections how they respond to environmental changes challenging. As a solution, we combined a trait-based Response-Effect-Framework (REF) with an improved Land Surface Model (LSM) in phase 1 of RESPECT to project the response of two target ecosystem functions (TF), biomass production and water fluxes, to environmental changes. We focused on the MRF where we successfully implemented a plot system and sampled abiotic drivers, biotic trait and process data for a-priori selected plant functional types (PFTs). We conducted first REF analyses that pointed to a complex interplay between abiotic drivers, trait diversity and biotic processes for the TFs. We developed the locally adapted, biodiversity informed LSM HUMBOL-TD (Hydroatmo Unified Model of BiOtic interactions and Local Trait Diversity) by coupling three models that cover the relevant compartments of the MRF. Improvements were new modules on herbivory and mycorrhiza-mediated nutrient uptake. Model testing with independent data showed that local functional trait and soil data substantially improve the simulations.In phase 2, we will keep our focus on unveiling how ecosystem biomass production and water fluxes are affected by climate and land-use changes through alterations in response and effect traits but extend our core plot system and sampling scheme based on a-priori selected PFTs to the adjacent MDF. The very large abiotic gradient and the differing seasonality offers unprecedented opportunities to gain a mechanistic understanding of the interplay between abiotic drivers, functional traits and biotic processes in these ecosystems forming the biodiversity hotspot. We will adapt and test the HUMBOL-TD to/for the MDF on the new core plot system. We will implement an area-wide version of the model for the entire catchments (MDR and MRF) by means of gridded remote sensing products, climate change scenario data and spatial-explicit optimized land-use scenarios. Our main aim is to test our central hypotheses on ecosystem resistance under different climate change scenarios and land-use change options with the area-wide model results and the REF. We expect that functional trait diversity is driven by water availability and seasonality in the MDF, whereas it is driven by nutrient availability and temperature in the MRF. We also expect that functional redundancy stabilizes responses of biotic processes to climate change. We hypothesize that functional trait diversity increases the resistance of the TFs to climate change. Similarly, we expect that functional trait diversity, and the resistance of the TFs decreases from natural forests to anthropogenic replacement systems. Nevertheless, we expect that adapted and sustainable land-use systems and landscape composition will enhance the resistance of MDF and MRF to climate change.