Abstract: Field-scale crop models are increasingly applied at spatio-temporal scales that range from regions to the globe and from decades up to 100 years. Sufficiently detailed data to capture the prevailing spatio-temporal heterogeneity in weather, soil, and management conditions as needed by crop models are rarely available. Effective sampling may overcome the problem of missing data but has rarely been investigated. In this study the effect of sampling weather data has been evaluated for simulating yields of winter wheat in a region in Germany over a 30-year period (1982-2011) using 12 process-based crop models. A stratified sampling was applied to compare the effect of different sizes of spatially sampled weather data (10, 30, 50,100, 500, 1000 and full coverage of 34,078 sampling points) on simulated wheat yields. Stratified sampling was further compared with random sampling. Possible interactions between sample size and crop model were evaluated. The results showed differences in simulated yields among crop models but all models reproduced well the pattern of the stratification. Importantly, the regional mean of simulated yields based on full coverage could already be reproduced by a small sample of 10 points. This was also true for reproducing the temporal variability in simulated yields but more sampling points (about 100) were required to accurately reproduce spatial yield variability. The number of sampling points can be smaller when a stratified sampling is applied as compared to a random sampling. However, differences between crop models were observed including some interaction between the effect of sampling on simulated yields and the model used. We concluded that stratified sampling can considerably reduce the number of required simulations. But, differences between crop models must be considered as the choice for a specific model can have larger effects on simulated yields than the sampling strategy. Assessing the impact of sampling soil and crop management data for regional simulations of crop yields is still needed.

Abstract: Most people live in cities, but most food system studies and food security issues focus on the rural poor. Urban populations differ from rural populations in their food consumption by being generally wealthier, requiring food trade for their food security, defined as the extent to which people have adequate diets. Cities rarely have the self-provisioning capacity to satisfy their own food supply, understood as the extent to which the food consumed by the city’s population is produced from the city’s local agro-ecosystems. Almost inevitably, a city’s food security is augmented by production from remote landscapes, both internal and external in terms of a state’s jurisdiction. We reveal the internal and external food flows necessary for the food security of three wealthy capital cities (Canberra, Australia; Copenhagen, Denmark; Tokyo, Japan). These cities cover two orders of magnitude in population size and three orders of magnitude in population density. From traded volumes of food and their sources into the cities, we calculate the productivity of the city’s regional and non-regional ecosystems that provide food for these cities and estimate the overall utilised land area. The three cities exhibit differing degrees of food self provisioning capacity and exhibit large differences in the areas on which they depend to provide their food. We show that, since 1965, global land area effectively imported to produce food for these cities has increased with their expanding populations, with large reductions in the percentage of demand met by local agro-ecosystems. The physical trading of food commodities embodies ecosystem services, such as water, soil fertility and pollination that are required for land-based food production. This means that the trade in these embodied ecosystem services has become as important for food security as traditional economic mechanisms such as market access and trade. A future policy question, raised by our study, is the degree to which governments will remain committed to open food trade policies in the face of national political unrest caused by food shortages. Our study demonstrates the need to determine the food security and self-provisioning capacity of a wide range of rich and poor cities, taking into account the global location of the ecosystems that are provisioning them. (C) 2013 Elsevier B.V. All rights reserved.

Abstract: The land-use sector can contribute to climate change mitigation not only by reducing greenhouse gas (GHG) emissions, but also by increasing carbon uptake from the atmosphere and thereby creating negative CO2 emissions. In this paper, we investigate two land-based climate change mitigation strategies for carbon removal: (1) afforestation and (2) bioenergy in combination with carbon capture and storage technology (bioenergy CCS). In our approach, a global tax on GHG emissions aimed at ambitious climate change mitigation incentivizes land-based mitigation by penalizing positive and rewarding negative CO2 emissions from the land-use system. We analyze afforestation and bioenergy CCS as standalone and combined mitigation strategies. We find that afforestation is a cost-efficient strategy for carbon removal at relatively low carbon prices, while bioenergy CCS becomes competitive only at higher prices. According to our results, cumulative carbon removal due to afforestation and bioenergy CCS is similar at the end of 21st century (600-700 GtCO(2)), while land-demand for afforestation is much higher compared to bioenergy CCS. In the combined setting, we identify competition for land, but the impact on the mitigation potential (1000 GtCO(2)) is partially alleviated by productivity increases in the agricultural sector. Moreover, our results indicate that early-century afforestation presumably will not negatively impact carbon removal due to bioenergy CCS in the second half of the 21st century. A sensitivity analysis shows that land-based mitigation is very sensitive to different levels of GHG taxes. Besides that, the mitigation potential of bioenergy CCS highly depends on the development of future bioenergy yields and the availability of geological carbon storage, while for afforestation projects the length of the crediting period is crucial.