@misc{LangerwischWalzRammigetal.2016,
  author    = {Langerwisch, Fanny and Walz, Ariane and Rammig, Anja and Tietjen, Britta and Thonicke, Kirsten and Cramer, Wolfgang},
  title     = {Deforestation in Amazonia impacts riverine carbon dynamics},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {535},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-41022},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-410225},
  pages     = {16},
  year      = {2016},
  abstract  = {Fluxes of organic and inorganic carbon within the Amazon basin are considerably controlled by annual flooding, which triggers the export of terrigenous organic material to the river and ultimately to the Atlantic Ocean. The amount of carbon imported to the river and the further conversion, transport and export of it depend on temperature, atmospheric CO2, terrestrial productivity and carbon storage, as well as discharge. Both terrestrial productivity and discharge are influenced by climate and land use change. The coupled LPJmL and RivCM model system (Langerwisch et al., 2016) has been applied to assess the combined impacts of climate and land use change on the Amazon riverine carbon dynamics. Vegetation dynamics (in LPJmL) as well as export and conversion of terrigenous carbon to and within the river (RivCM) are included. The model system has been applied for the years 1901 to 2099 under two deforestation scenarios and with climate forcing of three SRES emission scenarios, each for five climate models. We find that high deforestation (business-as-usual scenario) will strongly decrease (locally by up to 90 \%) riverine particulate and dissolved organic carbon amount until the end of the current century. At the same time, increase in discharge leaves net carbon transport during the first decades of the century roughly unchanged only if a sufficient area is still forested. After 2050 the amount of transported carbon will decrease drastically. In contrast to that, increased temperature and atmospheric CO2 concentration determine the amount of riverine inorganic carbon stored in the Amazon basin. Higher atmospheric CO2 concentrations increase riverine inorganic carbon amount by up to 20\% (SRES A2). The changes in riverine carbon fluxes have direct effects on carbon export, either to the atmosphere via outgassing or to the Atlantic Ocean via discharge. The outgassed carbon will increase slightly in the Amazon basin, but can be regionally reduced by up to 60\% due to deforestation. The discharge of organic carbon to the ocean will be reduced by about 40\% under the most severe deforestation and climate change scenario. These changes would have local and regional consequences on the carbon balance and habitat characteristics in the Amazon basin itself as well as in the adjacent Atlantic Ocean.},
  language  = {en}
}
@article{LangerwischWalzRammigetal.2016,
  author    = {Langerwisch, Fanny and Walz, Ariane and Rammig, Anja and Tietjen, Britta and Thonicke, Kirsten and Cramer, Wolfgang},
  title     = {Deforestation in Amazonia impacts riverine carbon dynamics},
  series = {Earth system dynamics},
  volume    = {7},
  journal   = {Earth system dynamics},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {2190-4979},
  doi       = {10.5194/esd-7-953-2016},
  pages     = {953 -- 968},
  year      = {2016},
  abstract  = {Fluxes of organic and inorganic carbon within the Amazon basin are considerably controlled by annual flooding, which triggers the export of terrigenous organic material to the river and ultimately to the Atlantic Ocean. The amount of carbon imported to the river and the further conversion, transport and export of it depend on temperature, atmospheric CO2, terrestrial productivity and carbon storage, as well as discharge. Both terrestrial productivity and discharge are influenced by climate and land use change. The coupled LPJmL and RivCM model system (Langerwisch et al., 2016) has been applied to assess the combined impacts of climate and land use change on the Amazon riverine carbon dynamics. Vegetation dynamics (in LPJmL) as well as export and conversion of terrigenous carbon to and within the river (RivCM) are included. The model system has been applied for the years 1901 to 2099 under two deforestation scenarios and with climate forcing of three SRES emission scenarios, each for five climate models. We find that high deforestation (business-as-usual scenario) will strongly decrease (locally by up to 90 \%) riverine particulate and dissolved organic carbon amount until the end of the current century. At the same time, increase in discharge leaves net carbon transport during the first decades of the century roughly unchanged only if a sufficient area is still forested. After 2050 the amount of transported carbon will decrease drastically. In contrast to that, increased temperature and atmospheric CO2 concentration determine the amount of riverine inorganic carbon stored in the Amazon basin. Higher atmospheric CO2 concentrations increase riverine inorganic carbon amount by up to 20\% (SRES A2). The changes in riverine carbon fluxes have direct effects on carbon export, either to the atmosphere via outgassing or to the Atlantic Ocean via discharge. The outgassed carbon will increase slightly in the Amazon basin, but can be regionally reduced by up to 60\% due to deforestation. The discharge of organic carbon to the ocean will be reduced by about 40\% under the most severe deforestation and climate change scenario. These changes would have local and regional consequences on the carbon balance and habitat characteristics in the Amazon basin itself as well as in the adjacent Atlantic Ocean.},
  language  = {en}
}
@article{GuoLohmannRatzmannetal.2016,
  author    = {Guo, Tong and Lohmann, Dirk and Ratzmann, Gregor and Tietjen, Britta},
  title     = {Response of semi-arid savanna vegetation composition towards grazing along a precipitation gradient-The effect of including plant heterogeneity into an ecohydrological savanna model},
  series = {Ecological modelling : international journal on ecological modelling and engineering and systems ecolog},
  volume    = {325},
  journal   = {Ecological modelling : international journal on ecological modelling and engineering and systems ecolog},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0304-3800},
  doi       = {10.1016/j.ecolmodel.2016.01.004},
  pages     = {47 -- 56},
  year      = {2016},
  abstract  = {Ecohydrological models of savanna rangeland systems typically aggregate plant species to very broad plant functional types (PFTs), which are characterized by their trait combinations. However, neglecting trait variability within modelled PFTs may hamper our ability to understand the effects of climate or land use change on vegetation composition and thus on ecosystem processes. In this study we extended and parameterized the ecohydrological savanna model EcoHyD, which originally considered only three broad PFTs (perennial grasses, annuals and shrubs). We defined several sub-types of perennial grasses (sub-PFTs) to assess the effect of environmental conditions on vegetation composition and ecosystem functioning. These perennial sub-PFTs are defined by altering distinct trait values based on a trade-off approach for (i) the longevity of plants and (ii) grazing-resistance. We find that increasing grazing intensity leads to a dominance of the fast-growing and short-lived perennial grass type as well as a dominance of the poorly palatable grass type. Increasing precipitation dampens the magnitude of grazing-induced shifts between perennial grass types. The diversification of perennial grass PFTs generally increases the total perennial grass cover and ecosystem water use efficiency, but does not protect the community from shrub encroachment. We thus demonstrate that including trait heterogeneity into ecosystem models will allow for an improved representation of ecosystem responses to environmental change in savannas. This will help to better assess how ecosystem functions might be impacted under future conditions. (C) 2016 Elsevier B.V. All rights reserved.},
  language  = {en}
}
@article{FerTietjenJeltsch2016,
  author    = {Fer, Istem and Tietjen, Britta and Jeltsch, Florian},
  title     = {High-resolution modelling closes the gap between data and model simulations for Mid-Holocene and present-day biomes of East Africa},
  series = {Palaeogeography, palaeoclimatology, palaeoecology : an international journal for the geo-sciences},
  volume    = {444},
  journal   = {Palaeogeography, palaeoclimatology, palaeoecology : an international journal for the geo-sciences},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0031-0182},
  doi       = {10.1016/j.palaeo.2015.12.001},
  pages     = {144 -- 151},
  year      = {2016},
  abstract  = {East Africa hosts a striking diversity of terrestrial ecosystems, which vary both in space and time due to complex regional topography and a dynamic climate. The structure and functioning of these ecosystems under this environmental setting can be studied with dynamic vegetation models (DVMs) in a spatially explicit way. Yet, regional applications of DVMs to East Africa are rare and a comprehensive validation of such applications is missing. Here, we simulated the present-day and mid-Holocene vegetation of East Africa with the DVM, LPJ-GUESS and we conducted an exhaustive comparison of model outputs with maps of potential modern vegetation distribution, and with pollen records of local change through time. Overall, the model was able to reproduce the observed spatial patterns of East African vegetation. To see whether running the model at higher spatial resolutions (10\&\#8242; × 10\&\#8242;) contribute to resolve the vegetation distribution better and have a better comparison scale with the observational data (i.e. pollen data), we run the model with coarser spatial resolution (0.5° × 0.5°) for the present-day as well. Both the area- and point-wise comparison showed that a higher spatial resolution allows to better describe spatial vegetation changes induced by the complex topography of East Africa. Our analysis of the difference between modelled mid-Holocene and modern-day vegetation showed that whether a biome shifts to another is best explained by both the amount of change in precipitation it experiences and the amount of precipitation it received originally. We also confirmed that tropical forest biomes were more sensitive to a decrease in precipitation compared to woodland and savanna biomes and that Holocene vegetation changes in East Africa were driven not only by changes in annual precipitation but also by changes in its seasonality.},
  language  = {en}
}