Evolutionary vegetation modeling and management

Understanding the structure and dynamics of worldwide vegetation patterns is critical for predicting future climatic change. Research by the Evolution and Ecology Program (EEP) applies mathematical models to elucidate the formation and maintenance of vegetation diversity, structure, and functioning.

© Les Cunliffe | Dreamstime

© Les Cunliffe | Dreamstime

Research in 2015 has seen progress on five fronts:

  • A new study has provided a mechanistic explanation for an unresolved riddle in carbon cycling: CO2 emissions following rainfall generally exceed model predictions. The new model helps improve understanding and predictions of soil microbial activity in the global carbon cycle [1].
  • A related study established an unexpected link between soil microbial activity and EEP’s research on the Equitable Governance of Common Goods: observed microbial activity arises from the interplay between decomposers that accomplish their work by producing extracellular enzymes and “cheaters” exploiting these publically available enzymes for their selfish benefit. On this basis, the study shows how the dynamical balance between these two functional groups fundamentally alters traditional predictions of soil microbial activity [2].
  • Underscoring the intricate relationship between climate change and vegetation responses, research demonstrated that climate change can either advance or delay the timing of flowering in annual plants depending on the growth constraints they experience [3].
  • Responding to the need among vegetation researchers for a flexible toolbox for investigating the eco-evolutionary dynamics of vegetation, EEP co-developed the Plant model, a comprehensive software package for studying the ecology and evolution of plant communities [4].
  • The new Plant model shows how community evolution in two functional traits can give rise to species-rich communities matching empirical observations (Figure 1). The research also shows, for the first time, the emergence of neutral fitness ridges in niche models of plant communities, thereby demonstrating an assumption previously used a priori by the neutral theory of biodiversity [5].

Figure 1. The Plant model generates realistic vegetation patterns matching observations in dependence on a site’s environmental conditions. The vegetation’s biodiversity is shown in terms of the successional dynamics of different species (distinguished by color) after a disturbance [5].


[1] Evans S, Dieckmann U, Franklin O & Kaiser C (2016). Synergistic effects of diffusion and microbial physiology reproduce the Birch effect in a micro-scale model. Soil Biology and Biochemistry 93: 28–37.

[2] Lindh M, Johansson J, Bolmgren K, Lundström NL, Brännström Å & Jonzén N (2016). Constrained growth flips the direction of optimal phenological responses among annual plants. New Phytologist 209: 1591–1599.

[3] Kaiser C, Franklin O, Richter A & Dieckmann U (2015). Social dynamics within decomposer communities lead to nitrogen retention and organic matter build-up in soils. Nature Communications 6: 8960.

[4] Falster DS, FitzJohn RG, Brännström Å, Dieckmann U & Westoby M (2016). Plant: A package for modelling forest trait ecology and evolution. Methods in Ecology and Evolution 7: 136–146.

[5] Falster DS, Brännström Å, Westoby M & Dieckmann U (2016). Extended niche models yield rich competitive coexistence and near-neutrality in forests. Science Advances, in press.

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Last edited: 09 May 2016


Ulf Dieckmann

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Evolution and Ecology


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International Institute for Applied Systems Analysis (IIASA)
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