TY - JOUR A1 - Frieler, Katja A1 - Schauberger, Bernhard A1 - Arneth, Almut A1 - Balkovic, Juraj A1 - Chryssanthacopoulos, James A1 - Deryng, Delphine A1 - Elliott, Joshua A1 - Folberth, Christian A1 - Khabarov, Nikolay A1 - Müller, Christoph A1 - Olin, Stefan A1 - Pugh, Thomas A. M. A1 - Schaphoff, Sibyll A1 - Schewe, Jacob A1 - Schmid, Erwin A1 - Warszawski, Lila A1 - Levermann, Anders T1 - Understanding the weather signal in national crop-yield variability JF - Earths future N2 - 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. Y1 - 2017 U6 - https://doi.org/10.1002/2016EF000525 SN - 2328-4277 VL - 5 SP - 605 EP - 616 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Franck, Siegfried A1 - von Bloh, Werner A1 - Müller, Christoph A1 - Bondeau, Alberte A1 - Sakschewski, B. T1 - Harvesting the sun new estimations of the maximum population of planet Earth JF - Ecological modelling : international journal on ecological modelling and engineering and systems ecolog N2 - The maximum population, also called Earth's carrying capacity, is the maximum number of people that can live on the food and other resources available on planet Earth. Previous investigations estimated the maximum carrying capacity as large as about 1 trillion people under the assumption that photosynthesis is the limiting process. Here we use a present state-of-the-art dynamic global vegetation model with managed planetary land surface, Lund-Potsdam-Jena managed Land (LPJmL), to calculate the yields of the most productive crops on a global 0.5 degrees x 0.5 degrees grid. Using the 2005 crop distribution the model predicts total harvested calories that are sufficient for the nutrition of 11.4 billion people. We define scenarios where humankind uses the whole land area for agriculture, saves the rain forests and the boreal evergreen forests or cultivates only pasture to feed animals. Every scenario is run in an extreme version with no allowance for urban and recreational needs and in two soft versions with a certain area per person for non-agricultural use. We find that there are natural limits of the maximum carrying capacity which are independent of any increase in agricultural productivity, if non-agricultural land use is accounted for. Using all land planet Earth can sustain 282 billion people. The save-forests-scenario yields 150 billion people. The scenario that cultivates only pasture to feed animals yields 96 billion people. Nevertheless, we should always have in mind that all our calculated numbers for the carrying capacity refer to extreme scenarios where humankind may only vegetate on this planet. Our numbers are considerably higher than the general median estimate of upper bounds of human population found in the literature in the order of 10 billion. KW - Maximum population KW - Human carrying capacity KW - Photosynthesis KW - Dynamical global vegetation model Y1 - 2011 U6 - https://doi.org/10.1016/j.ecolmodel.2011.03.030 SN - 0304-3800 VL - 222 IS - 12 SP - 2019 EP - 2026 PB - Elsevier CY - Amsterdam ER -