Privacy Policy Disclaimer
  Advanced SearchBrowse




Journal Article

Do details matter? Disentangling the processes related to plant species interactions in two grassland models of different complexity


Wirth,  Stephen Björn
Potsdam Institute for Climate Impact Research;

Taubert,  Franziska
External Organizations;

Tietjen,  Britta
External Organizations;


Müller,  Christoph
Potsdam Institute for Climate Impact Research;


Rolinski,  Susanne
Potsdam Institute for Climate Impact Research;

External Ressource
No external resources are shared
Fulltext (public)
There are no public fulltexts stored in PIKpublic
Supplementary Material (public)
There is no public supplementary material available

Wirth, S. B., Taubert, F., Tietjen, B., Müller, C., Rolinski, S. (2021): Do details matter? Disentangling the processes related to plant species interactions in two grassland models of different complexity. - Ecological Modelling, 460, 109737.

Cite as: https://publications.pik-potsdam.de/pubman/item/item_25955
Despite extensive research on the role of plant species richness for the regulation of ecosystem functions, the mechanistic understanding of the underlying processes, especially in species-rich communities, is still limited. Biogeochemical models of vegetation dynamics could potentially be used to complement empirical studies, but it is unclear how the particular process description within these models affects simulations of species performance and resulting ecosystem functions. We evaluate the models’ process descriptions to simulate the response of different species, their inter- actions and their joint performance to drought and mowing. Therefore, we compare simulations of two grassland models of different complexity for monocultures and two-species mixtures in a grassland experi- ment in Jena, Germany. Models’ process representations are crucial for species’ performance and interaction. We provide an in-depth analysis of the processes responsible for model behavior to identify potential fields of model devel- opment and discuss our findings in the context of other modeling approaches. Both models simulated similar average above-ground biomass (AGB) but showed different intra-annual variability. Generally, the models had difficulties representing a balanced species composition in multiple species mixtures and competition for space was the main driver of community composition in both models. The resulting communities were dominated by the more competitive species, while the weak competitor was only marginally present in most mixtures independent of drought and mowing. The competitive strength which we derived from the calibrated parameter sets of the species differed between the models and the agreement on which species dominate specific mixtures was mixed. While both models simulated reduced soil water content and above-ground biomass in response to drought, the strength and duration of these responses differed. Despite these differences, simulated species interactions were barely affected, and strong competitors remained dominant. In both models, the representation of competition for below-ground re- sources (water and nutrients) is less complex than that for above-ground resources (space and light). We found that in both models the transpiration reduction from water stress is too strong when soil water con- tent is close to field capacity, which weakened the drought effects. Mowing had opposing effects on the competition for space in the models, which could be attributed to the different representations of plants in the two models. Here, we demonstrated that process-based vegetation models in general allow for a detailed comparison of the modelled processes and their links to both – emerging vegetation responses and underlying plant parameters/traits. Such a model intercomparison supports the understanding of how much model complexity is necessary to simulate specific research questions and objectives. Concerning our example of drought effects on plant species competition, we conclude that a better representation of multi-species mixtures and their response to disturbances in grassland models is needed to allow for more robust future projections of grassland dynamics under future management and climate change.