Environmental changes in biodiversity hotspot ecosystems of
South Ecuador: RESPonse and feedback effECTs (FOR2730)

Abstract:

Plant roots have a large diversity of form and function, which is also related to their degree of mycorrhizal association. This is known as the fungal collaboration gradient, where thinner roots acquire resources by themselves, and thicker roots depend on mycorrhizae. In this study, we, for the first time, implement the fungal collaboration gradient in a trait-based dynamic vegetation model (DVM, LPJ-GUESS-NTD). We test if the DVM can predict fine-root-trait distributions and estimate the effects of arbuscular-mycorrhiza-fungus (AMF)-mediated nutrient uptake on ecosystem processes along an elevation gradient in a tropical montane forest in southern Ecuador. The model reproduces the observed fine-root traits of specific root length (SRL) and AMF colonization along the elevation gradient, which ranges from low AMF colonization at 1000 m (25 %) to high AMF colonization at 3000 m (61 %). When AMF-mediated nutrient uptake is deactivated, site average biomass values are reduced by up to 80 %. Accounting for AMF-related belowground traits also affects simulated community leaf traits, suggesting linkages between below- and aboveground traits as AMF promotes more leaf-acquisitive traits. In addition, deactivation of AMF uptake reduced simulated soil C stocks by up to 68 %. The model suggests that the collaboration gradient has a substantial influence on vegetation diversity and functioning as well as soil carbon in the study system. We thus advocate more explicit treatment of fine-root traits and mycorrhizae in DVMs. The model scheme here is based on general trade-offs and could be implemented in other DVMs and be tested for other study regions.

Abstract:

Summary Community trait assembly in highly diverse tropical rainforests is still poorly understood. Based on more than a decade of field measurements in a biodiversity hotspot of southern Ecuador, we implemented plant trait variation and improved soil organic matter dynamics in a widely used dynamic vegetation model (the Lund-Potsdam-Jena General Ecosystem Simulator, LPJ-GUESS) to explore the main drivers of community assembly along an elevational gradient. In the model used here (LPJ-GUESS-NTD, where NTD stands for nutrient-trait dynamics), each plant individual can possess different trait combinations, and the community trait composition emerges via ecological sorting. Further model developments include plant growth limitation by phosphorous (P) and mycorrhizal nutrient uptake. The new model version reproduced the main observed community trait shift and related vegetation processes along the elevational gradient, but only if nutrient limitations to plant growth were activated. In turn, when traits were fixed, low productivity communities emerged due to reduced nutrient-use efficiency. Mycorrhizal nutrient uptake, when deactivated, reduced net primary production (NPP) by 61–72% along the gradient. Our results strongly suggest that the elevational temperature gradient drives community assembly and ecosystem functioning indirectly through its effect on soil nutrient dynamics and vegetation traits. This illustrates the importance of considering these processes to yield realistic model predictions.

Abstract:

Tropical mountain ecosystems are threatened by climate and land-use changes. Their diversity and complexity make projec- tions 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 efect 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-efect-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.