Simulating species-rich grasslands with GRASSMIND

We have developed the dynamic grassland model GRASSMIND (individual- and process-based) for simulating plant growth and dynamics of species-rich grasslands (including management). The model simulates the daily growth dynamics of individual plants and thereby explicitly considers

• competition between individual plants for light, space, soil water and nitrogen
• different management regimes (e.g. mowing, irrigation, fertilization)
• climatic variables and potential changes (e.g. increasing air temperatures, reduced soil water)
  

Since its initial development, the model constantly has further been advanced and applied to different German study sites to understand how plant traits (and related vegetation processes) influence grassland productivity and species composition.

Important publications:

• Hetzer, J., Huth, A., Taubert, F., (2021): The importance of plant trait variability in grasslands: a modelling study. Ecol. Model. 453 , art. 109606. full text (doi)
• Schmid, J.S., Huth, A., Taubert, F., (2021): Influences of traits and processes on productivity and functional composition in grasslands: A modeling study. Ecol. Model. 440 , art. 109395. full text (doi)
• Taubert, F., Hetzer, J., Schmid, J.S., Huth, A., (2020): The role of species traits for grassland productivity. Ecosphere 11 (7), e03205. full text (doi)
• Taubert, F., Hetzer, J., Schmid, J.S., Huth, A., (2020): Confronting an individual-based simulation model with empirical community patterns of grasslands. PLOS One 15 (7), e0236546. full text (doi)
• Taubert, F., Frank, K., Huth, A., (2012): A review of grassland models in the biofuel context. Ecol. Model. 245 , 84 - 93. full text (doi)

Here you can download the GRASSMIND model and its model description.

Understanding global forest fragmentation patterns

By the analysis of high-resolution remote sensing data, we show that in the tropics and subtropics similar patterns of the distribution of fragment sizes across the continents America, Africa and Asia-Australia emerge. These patterns closely follow analytical predictions of percolation theory at some specific point (critical point of percolation). We developed a dynamic fragmentation model based on principles of percolation theory which allows to simulate fragmentation of coninental-wide tropical forest areas (of 30 m resolution). In our simulations, we demonstrate that beyond the critical point continental tropical landscapes will consist of 33-fold small and isolated forest fragments in the future if deforestation proceeds as currently observed. Our scenario analysis shows that even efforts of reforestation and decreased deforestation still would lead to an enhanced fragmentation of forests.

See also

Publication: Global patterns of tropical forest fragmentation

Download (accepted manuscript version of 9 January 2018) (1.4 MB)

UFZ press release

Online-Blog (Nature Ecology & Evolution Community, Behind the Paper)

Forests and Grassland Dynamics

Remote Sensing and Ecological Modelling

The aerial photo shows forest fragments of the Brazilian Atlantic rainforest in Northeastern Brazil (Mata Atlântica), surrounded by sugar cane plantations.
Photo: Mateus Dantas de Paula

Explaining the structure of tropcial forests

We developed a forest packing model (FPM) which uses simple principles of stochastic geometry and successfully reproduces the structure of natural tropical forests in terms of

• their tree size distribution,
• vertical leaf area distribution, and
  
• local horizontal structure (e.g. local forest height, local packing density)
  

See also

Publication: The structure of tropical forests and sphere packings (open-access)

Forests and Grassland Dynamics