Project Details
Projekt
Biodiversity impacts on ecosystem functioning under climate change - lessons from a biodiversified land surface model
Subject Area
Ecology and Biodiversity of Plants and Ecosystems
Term
since 2025
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 386807763
There is increasing evidence that biodiversity underpins the resistance and resilience of ecosystems to climate change. This implies that biodiversity is also important for feedback processes from ecosystems on atmospheric dynamics, but how to best include biodiversity in land surface models is still unresolved. In this synthesis project, we plan to finalize the implementation of plant functional diversity in a land surface model, using unique field data from a mountain rainforest and mountain dry forest area in southern Ecuador. We focus on plant functional traits related to the leaf and wood economic spectra as well as traits that are important for forest regeneration. Furthermore, we include one important biotic interaction, namely insect herbivory. We plan land surface modelling at the plot scale and across the whole study area to address joined RESPECT hypotheses and one hypothesis specific to the project here. Downscaled climate scenarios will be used for future projections. For the area-wide runs, we will complement our plot-scale land surface model HUMBOL-TD with a recently developed land surface version of the LPJ-GUESS vegetation model. The LPJ-GUESS-NTD model, which we developed during the last two project phase, will be the biological core of both land surface models. We, e.g., hypothesize that plant functional diversity positively influences the resistance of the RESPECT target functions (biomass production and evapotranspiration) to climate change and extremes. We also hypothesize that the resistance of the target functions to climate change and extremes is higher in natural ecosystems than in anthropogenic replacement systems. Our simulated target functions will feed into a land use scenario generator from Syn-A1 to derive optimized land use change scenarios, which will feed back into the area-wide land surface modelling here. Specifically, in the synthesis project here, we hypothesize that increasing nitrogen availability drives a shift towards more acquisitive plant traits (e.g. high specific leaf are, high vegetation growth rates, high nutrient demand), whereby the increasing nitrogen availability is partly driven by nitrogen deposition stemming from fires in the Amazon rainforests. Such a vegetation trait shift would have profound impacts not only on ecosystem processes but also on the unique biodiversity in the study region. We will address this hypothesis with a process-based model that might reveal longer-term changes that might occur on time scales too long for experiments or high-quality satellite data. Nevertheless, corresponding satellite data will be analyzed by the Syn-A1 project, and corresponding latest data from nitrogen fertilization experiments will be analyzed by Syn-B1. We expect that our results will guide future efforts aiming at the development of land surface models that represent the impacts of biodiversity on ecosystem functioning and feedbacks on atmospheric dynamics.
DFG Programme
Research Units
