Publications
Found 4 publication(s)
- of type article
Dantas De Paula, M.; Forrest, M.; Langan, L.; Bendix, J.; Homeier, J.; Velescu, A.; Wilcke, W. & Hickler, T. (2021): Nutrient cycling drives plant community trait assembly and ecosystem functioning in a tropical mountain biodiversity hotspot. New Phytologist -(-), -.
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DOI: 10.1111/nph.17600
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Abstract:
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.
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Keywords: |
mycorrhiza |
dynamic vegetation model |
nutrient cycling |
plant community assembly |
plant functional traits |
tropical montane forests (TMF) |
Bendix, J.; Aguirre, N.; Beck, E.; Bräuning, A.; Brandl, R.; Breuer, L.; Boehning-Gaese, K.; Dantas De Paula, M.; Hickler, T.; Homeier, J.; Inclan, D.; Leuschner, C.; Neuschulz, E.; Schleuning, M.; Suarez, J.P.; Trachte, K.; Wilcke, W. & Farwig, N. (2021): A research framework for projecting ecosystem change in highly diverse tropical mountain ecosystems. Oecologia 2021, 1-13.
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DOI: 10.1007/s00442-021-04852-8
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Abstract:
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.
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Keywords: |
Biodiversity-Land-Surface-Model |