@article{GeldmacherSchaphoffWoitheetal.2000,
  author    = {Geldmacher, Karl and Schaphoff, Sibyll and Woithe, Franka and Bork, Hans-Rudolf},
  title     = {Landscape Development and Land Use in the Pacific Nothwest (USA)},
  year      = {2000},
  language  = {en}
}
@article{CramerBondeauSchaphoffetal.2004,
  author    = {Cramer, Wolfgang and Bondeau, Alberte and Schaphoff, Sibyll and Lucht, Wolfgang and Smith, Benjamin and Sitch, Stephan},
  title     = {Tropical forests and the global carbon cycle : impacts of atmospheric carbon dioxide, climate change and rate of deforestation},
  issn      = {0962-8436},
  year      = {2004},
  abstract  = {The remaining carbon stocks in wet tropical forests are currently at risk because of anthropogenic deforestation, but also because of the possibility of release driven by climate change. To identify the relative roles of CO2 increase, changing temperature and rainfall, and deforestation in the future, and the magnitude of their impact on atmospheric CO2 concentrations, we have applied a dynamic global vegetation model, using multiple scenarios of tropical deforestation (extrapolated from two estimates of current rates) and multiple scenarios of changing climate (derived from four independent offline general circulation model simulations). Results show that deforestation will probably produce large losses of carbon, despite the uncertainty about the deforestation rates. Some climate models produce additional large fluxes due to increased drought stress caused by rising temperature and decreasing rainfall. One climate model, however, produces an additional carbon sink. Taken together, our estimates of additional carbon emissions during the twenty-first century, for all climate and deforestation scenarios, range from 101 to 367 Gt C, resulting in CO2 concentration increases above background values between 29 and 129 p.p.m. An evaluation of the method indicates that better estimates of tropical carbon sources and sinks require improved assessments of current and future deforestation, and more consistent precipitation scenarios from climate models. Notwithstanding the uncertainties, continued tropical deforestation will most certainly play a very large role in the build-up of future greenhouse gas concentrations},
  language  = {en}
}
@article{FrielerSchaubergerArnethetal.2017,
  author    = {Frieler, Katja and Schauberger, Bernhard and Arneth, Almut and Balkovic, Juraj and Chryssanthacopoulos, James and Deryng, Delphine and Elliott, Joshua and Folberth, Christian and Khabarov, Nikolay and M{\"u}ller, Christoph and Olin, Stefan and Pugh, Thomas A. M. and Schaphoff, Sibyll and Schewe, Jacob and Schmid, Erwin and Warszawski, Lila and Levermann, Anders},
  title     = {Understanding the weather signal in national crop-yield variability},
  series = {Earths future},
  volume    = {5},
  journal   = {Earths future},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {2328-4277},
  doi       = {10.1002/2016EF000525},
  pages     = {605 -- 616},
  year      = {2017},
  abstract  = {Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather-induced crop-yield variability is essential for adaptation strategies, so far it has only been addressed by empirical models. Here, we provide conservative estimates of the fraction of reported national yield variabilities that can be attributed to weather by state-of-the-art, process-based crop model simulations. We find that observed weather variations can explain more than 50\% of the variability in wheat yields in Australia, Canada, Spain, Hungary, and Romania. For maize, weather sensitivities exceed 50\% in seven countries, including the United States. The explained variance exceeds 50\% for rice in Japan and South Korea and for soy in Argentina. Avoiding water stress by simulating yields assuming full irrigation shows that water limitation is a major driver of the observed variations in most of these countries. Identifying the mechanisms leading to crop-yield fluctuations is not only fundamental for dampening fluctuations, but is also important in the context of the debate on the attribution of loss and damage to climate change. Since process-based crop models not only account for weather influences on crop yields, but also provide options to represent human-management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations.},
  language  = {en}
}