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Picture: The diagram shows the Bayesian modelling cycle for a process-based vegetation model, slightly modified from Hartig et al Two Thousand Twelve.

The Biodiversity Exploratories have provided empirical evidence for the influence of diversity and land use on ecosystem functions. The mechanisms that lead to this influence, however, are in many cases still not entirely clear. This poses not only a challenge to scientific curiosity, but also limits our ability to extrapolate ecosystem reactions towards environmental conditions that are not currently covered by the data from the Biodiversity Exploratories.


The objective of this project is to compare the support and relative strength of different mechanisms that have been hypothesized to affect interactions between diversity, land use and ecosystem functions. Mechanisms of particular interest are:

  • Niche differentiation through growth strategies/competition for light
  • Niche differentiation through rooting strategy and differential water use
  • Niche differentiation through complementary nutrient / soil requirements
  • Intraspecific variability of traits, which could create the same effects through functional diversity, despite no apparent species diversity

CONNECT uses the LPJ-GUESS model, a well-known and well-tested process-based vegetation model. LPJ-GUESS allows the implementation of functional differences between species, e.g. through different parameters for root, stem and crown geometries or through different physiological parameters. We will use Bayesian inference to adjust the model parameters to the local site conditions, using data from the exploratories.

Subsequently, we will use the model to examine two main questions:

  1. How do the mechanisms described above affect diversity across the plots and community stability within plots, and can we explain the observed functional and species diversity across the Biodiversity Exploratories from those mechanisms?
  2. What is the contribution of these mechanisms to diversity effects on ecosystem functions?
Picture: The diagram shows the Bayesian modelling cycle for a process-based vegetation model, slightly modified from Hartig et al Two Thousand Twelve.
The Bayesian modelling cycle for a process-based vegetation model, slightly modified from Hartig et al., 2012

Doc
Speich M., Dormann C. F., Hartig F. (2021): Sequential Monte-Carlo algorithms for Bayesian model calibration – A review and method comparison. Ecological Modelling 455, 109608. doi: 10.1016/j.ecolmodel.2021.109608
More information:  doi.org
Doc
Dormann C. F., Bagnara M., Boch S., Hinderling J., Janeiro - Otero A., Schäfer D., Schall P., Hartig F. (2020): Plant species richness increases with light availability, but not variability, in temperate forests understorey. BMC Ecology 20, 43. doi: 10.1186/s12898-020-00311-9
More information:  doi.org
Doc
Bagnara M., Silveyra Gonzalez R., Reifenberg S., Steinkamp J., Hickler T., Werner C., Dormann C. F., Hartig F. (2019): An R package facilitating sensitivity analysis, calibration and forward simulations with the LPJ-GUESS dynamic vegetation model. Environmental Modelling and Software 111, 55-60. doi: 10.1016/j.envsoft.2018.09.004
More information:  doi.org

Scientific assistants

Prof. Dr. Carsten Dormann
Alumni
Prof. Dr. Carsten Dormann
Dr. Florian Hartig
Alumni
Dr. Florian Hartig
Dr. Maurizio Bagnara
Alumni
Dr. Maurizio Bagnara
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