Sakschewski, B., von Bloh, W., Huber, V., Müller, C., & Bondeau, A. (2014). Feeding 10 billion people under climate change: How large is the production gap of current agricultural systems. Ecol. Model., 288, 103–111.
Abstract: The human population is projected to reach more than 10 billion in the year 2100. Together with changing consumption pattern, population growth will lead to increasing food demand. The question arises whether or not the Earth is capable of fulfilling this demand. In this study, we approach this question by estimating the carrying capacity of current agricultural systems (K-C), which does not measure the maximum number of people the Earth is likely to feed in the future, but rather allows for an indirect assessment of the increases in agricultural productivity required to meet demands. We project agricultural food production under progressing climate change using the state-of-the-art dynamic global vegetation model LPJmL, and input data of 3 climate models. For 1990 to 2100 the worldwide annual caloric yield of the most important 11 crop types is simulated. Model runs with and without elevated atmospheric CO2 concentrations are performed in order to investigate CO2 fertilization effects. Country-specific per-capita caloric demands fixed at current levels and changing demands based on future GDP projections are considered to assess the role of future dietary shifts. Our results indicate that current population projections may considerably exceed the maximum number of people that can be fed globally if climate change is not accompanied by significant changes in land use, agricultural efficiencies and/or consumption pathways. We estimate the gap between projected population size and K-C to reach 2 to 6.8 billion people by 2100. We also present possible caloric self-supply changes between 2000 and 2100 for all countries included in this study. The results show that predominantly developing countries in tropical and subtropical regions will experience vast decreases of self-supply. Therefore, this study is important for planning future large-scale agricultural management, as well as the critical assessment of population projections, which should take food-mediated climate change feedbacks into account
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Porter, J. R., Dyball, R., Dumaresq, D., Deutsch, L., & Matsuda, H. (2014). Feeding capitals: Urban food security and self-provisioning in Canberra, Copenhagen and Tokyo. Global Food Security, 3(1), 1–7.
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.
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Jaromir, K., Piotr, B., & Cezary, S. (2014). Field experiment in Lubelskie region to validate crop growth models in temperate climate..
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Krzyszczak, J., Baranowski, P., & Slawinski, C. (2014). Field experiment in Lubelskie region to validate crop growth models in temperate, climate..
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Destain, M. - F. (2014). Filtering methods for predicting and modelling wheat yield in the context of climate change. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: In this paper, an Improved Particle Filtering (IPF) based on minimizing Kullback-Leibler divergence will be proposed for biomass prediction of a wheat crop model in the context of climate change including heat and drought stresses.In a first stage, the performances of the proposed technique will be compared with those of the extended Kalman filter (EKF), unscented Kalman filter (UKF), Particle filter (PF). In a second stage, the state estimation techniques EKF, UKF, PF and IPF will be used for updating prediction of the model in order to predict winter wheat biomass, in specific field conditions, during several contrasted weather conditions. In a third stage, the effects of practical challenges on the performances of the state estimation algorithms will be assessed. Such practical challenges include the effect of measurement noise on the estimation performances and the measurement frequency of state variables.The first results show that the UKF provides a higher accuracy than the EKF due to the limited ability of EKF to accurately estimate the mean and covariance matrix of the estimated states through lineralization of the nonlinear process model. The results also show that the IPF provides a significant improvement over PF because, unlike the PF which depends on the choice of sampling distribution used to estimate the posterior distribution, the IPF yields an optimum choice of the sampling distribution, which also accounts for the observed data. For all techniques, the practical challenges affect the estimation accuracy as well as the convergence of the estimated states and parameters. However, the IPF can still provide both convergence as well as accuracy over other estimation methods. These advantages are precious in presence of high climate stresses.
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