@article{LohmannGuoTietjen2018,
  author    = {Lohmann, Dirk and Guo, Tong and Tietjen, Britta},
  title     = {Zooming in on coarse plant functional types-simulated response of savanna vegetation composition in response to aridity and grazing},
  series = {Theoretical ecology},
  volume    = {11},
  journal   = {Theoretical ecology},
  number    = {2},
  publisher = {Springer},
  address   = {Heidelberg},
  issn      = {1874-1738},
  doi       = {10.1007/s12080-017-0356-x},
  pages     = {161 -- 173},
  year      = {2018},
  abstract  = {Precipitation and land use in terms of livestock grazing have been identified as two of the most important drivers structuring the vegetation composition of semi-arid and arid savannas. Savanna research on the impact of these drivers has widely applied the so-called plant functional type (PFT) approach, grouping the vegetation into two or three broad types (here called meta-PFTs): woody plants and grasses, which are sometimes divided into perennial and annual grasses. However, little is known about the response of functional traits within these coarse types towards water availability or livestock grazing. In this study, we extended an existing eco-hydrological savanna vegetation model to capture trait diversity within the three broad meta-PFTs to assess the effects of both grazing and mean annual precipitation (MAP) on trait composition along a gradient of both drivers. Our results show a complex pattern of trait responses to grazing and aridity. The response differs for the three meta-PFTs. From our findings, we derive that trait responses to grazing and aridity for perennial grasses are similar, as suggested by the convergence model for grazing and aridity. However, we also see that this only holds for simulations below a MAP of 500 mm. This combined with the finding that trait response differs between the three meta-PFTs leads to the conclusion that there is no single, universal trait or set of traits determining the response to grazing and aridity. We finally discuss how simulation models including trait variability within meta-PFTs are necessary to understand ecosystem responses to environmental drivers, both locally and globally and how this perspective will help to extend conceptual frameworks of other ecosystems to savanna research.},
  language  = {en}
}