Abstract: Explorations of future land use change are important to understand potential conflicts between competing land uses, trade-offs associated with particular land change trajectories, and the effectiveness of policies to steer land systems into desirable states. Most model-based explorations and scenario studies focused on conversions in broad land use classes, but disregarded changes in land management or focused on individual sectors only. Using the European Union (EU) as a case study, we developed an approach to identifying typical combinations of land cover and management changes by combining the results of multimodel simulations in the agriculture and forest sectors for four scenarios from 2000 to 2040. We visualized land change trajectories by mapping regional hotspots of change. Land change trajectories differed in extent and spatial pattern across the EU and among scenarios, indicating trajectory-specific option spaces for alternative land system outcomes. In spite of the large variation in the area of change, similar hotspots of land change were observed among the scenarios. All scenarios indicate a stronger polarization of land use in Europe, with a loss of multifunctional landscapes. We analyzed locations subject to change by comparing location characteristics associated with certain land change trajectories. Results indicate differences in the location conditions of different land change trajectories, with diverging impacts on ecosystem service provisioning. Policy and planning for future land use needs to account for the spatial variation of land change trajectories to achieve both overarching and location-specific targets.

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 accurate estimation of crop grain nitrogen (N; N in grain yield) is crucial for optimizing agricultural N management, especially in crop rotations. In the present study, 12 process-based models were applied to simulate the grain N of i) seven crops in rotations, ii) across various pedo-climatic and agro-management conditions in Europe, under both continuous simulation and single year simulation, and for iv) two calibration levels, namely minimal and detailed calibration. Generally, the results showed that the accuracy of the simulations in predicting grain N increased under detailed calibration. The models performed better in predicting the grain N of winter wheat (Triticum aestivum L.), winter barley (Hordewn vulgare L.) and spring barley (Hordeum vulgare L.) compared to spring oat (Avena saliva L.), winter rye (Secale cereale L.), pea (Piswn sativum L.) and winter oilseed rape (Brassica napus L.). These differences are linked to the intensity of parameterization with better parameterized crops showing lower prediction errors. The model performance was influenced by N fertilization and irrigation treatments, and a majority of the predictions were more accurate under low N and rainfed treatments. Moreover, the multi-model mean provided better predictions of grain N compared to any individual model. In regard to the Individual models, DAISY, FASSET, HERMES, MONICA and STICS are suitable for predicting grain N of the main crops in typical European crop rotations, which all performed well in both continuous simulation and single year simulation. Our results show that both the model initialization and the cover crop effects in crop rotations should be considered in order to achieve good performance of continuous simulation. Furthermore, the choice of either continuous simulation or single year simulation should be guided by the simulation objectives (e.g. grain yield, grain N content or N dynamics), the crop sequence (inclusion of legumes) and treatments (rate and type of N fertilizer) included in crop rotations and the model formalism.