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    Biomass production in plantations: Land constraints increase dependency on irrigation water
    (Oxford : Wiley-Blackwell, 2018) Jans, Yvonne; Berndes, Göran; Heinke, Jens; Lucht, Wolfgang; Gerten, Dieter
    Integrated assessment model scenarios project rising deployment of biomass-using energy systems in climate change mitigation scenarios. But there is concern that bioenergy deployment will increase competition for land and water resources and obstruct objectives such as nature protection, the preservation of carbon-rich ecosystems, and food security. To study the relative importance of water and land availability as biophysical constraints to bioenergy deployment at a global scale, we use a process-detailed, spatially explicit biosphere model to simulate rain-fed and irrigated biomass plantation supply along with the corresponding water consumption for different scenarios concerning availability of land and water resources. We find that global plantation supplies are mainly limited by land availability and only secondarily by freshwater availability. As a theoretical upper limit, if all suitable lands on Earth, besides land currently used in agriculture, were available for bioenergy plantations (“Food first” scenario), total plantation supply would be in the range 2,010–2,300 EJ/year depending on water availability and use. Excluding all currently protected areas reduces the supply by 60%. Excluding also areas where conversion to biomass plantations causes carbon emissions that might be considered unacceptably high will reduce the total plantation supply further. For example, excluding all areas where soil and vegetation carbon stocks exceed 150 tC/ha (“Carbon threshold savanna” scenario) reduces the supply to 170–290 EJ/year. With decreasing land availability, the amount of water available for irrigation becomes vitally important. In the least restrictive land availability scenario (“Food first”), up to 77% of global plantation biomass supply is obtained without additional irrigation. This share is reduced to 31% for the most restrictive “Carbon threshold savanna” scenario. The results highlight the critical—and geographically varying—importance of co-managing land and water resources if substantial contributions of bioenergy are to be reached in mitigation portfolios.
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    Tree mortality submodels drive simulated long-term forest dynamics: assessing 15 models from the stand to global scale
    (Ithaca, NY : ESA, 2019) Bugmann, Harald; Seidl, Rupert; Hartig, Florian; Bohn, Friedrich; Bruna, Josef; Cailleret, Maxime; Francois, Louis; Heinke, Jens; Henrot, Alexandra-Jane; Hickler, Thomas; Huelsmann, Lisa; Huth, Andreas; Jacquemin, Ingrid; Kollas, Chris; Lasch-Born, Petra; Lexer, Manfred J.; Merganic, Jan; Merganicova, Katarna; Mette, Tobias; Miranda, Brian R.; Nadal-Sala, Daniel; Rammer, Werner; Rammig, Anja; Reineking, Bjoern; Roedig, Edna; Sabate, Santi; Steinkamp, Jorg; Suckow, Felicitas; Vacchiano, Giorgio; Wild, Jan; Xu, Chonggang; Reyer, Christopher P.O.
    Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration. Quantitative studies on the importance of mortality submodels are scarce. We evaluated 15 dynamic vegetation models (DVMs) regarding their sensitivity to different formulations of tree mortality under different degrees of climate change. The set of models comprised eight DVMs at the stand scale, three at the landscape scale, and four typically applied at the continental to global scale. Some incorporate empirically derived mortality models, and others are based on experimental data, whereas still others are based on theoretical reasoning. Each DVM was run with at least two alternative mortality submodels. Model behavior was evaluated against empirical time series data, and then, the models were subjected to different scenarios of climate change. Most DVMs matched empirical data quite well, irrespective of the mortality submodel that was used. However, mortality submodels that performed in a very similar manner against past data often led to sharply different trajectories of forest dynamics under future climate change. Most DVMs featured high sensitivity to the mortality submodel, with deviations of basal area and stem numbers on the order of 10–40% per century under current climate and 20–170% under climate change. The sensitivity of a given DVM to scenarios of climate change, however, was typically lower by a factor of two to three. We conclude that (1) mortality is one of the most uncertain processes when it comes to assessing forest response to climate change, and (2) more data and a better process understanding of tree mortality are needed to improve the robustness of simulated future forest dynamics. Our study highlights that comparing several alternative mortality formulations in DVMs provides valuable insights into the effects of process uncertainties on simulated future forest dynamics. © 2019 The Authors.