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Author |
Coles, G.D.; Wratten, S.D.; Porter, J.R. |
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Title |
Food and nutritional security requires adequate protein as well as energy, delivered from whole-year crop production |
Type |
Journal Article |
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Year |
2016 |
Publication |
PeerJ |
Abbreviated Journal  |
PeerJ |
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Volume |
4 |
Issue |
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Pages |
17 |
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Keywords |
Agroecology; Forage utilisation; Food costs; Nutrition; Whole-year; production; New Zealand; Food access; Food security; humans |
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Abstract |
Human food security requires the production of sufficient quantities of both high-quality protein and dietary energy. In a series of case-studies from New Zealand, we show that while production of food ingredients from crops on arable land can meet human dietary energy requirements effectively, requirements for high-quality protein are met more efficiently by animal production from such land. We present a model that can be used to assess dietary energy and quality-corrected protein production from various crop and crop/animal production systems, and demonstrate its utility. We extend our analysis with an accompanying economic analysis of commercially available pre-prepared or simply-cooked foods that can be produced from our case-study crop and animal products. We calculate the per-person, per-day cost of both quality-corrected protein and dietary energy as provided in the processed foods. We conclude that mixed dairy/cropping systems provide the greatest quantity of high quality protein per unit price to the consumer, have the highest food energy production and can support the dietary requirements of the highest number of people, when assessed as all-year-round production systems. Global food and nutritional security will largely be an outcome of national or regional agroeconomies addressing their town food needs. We hope that lour model will be used for similar analyses of food production systems in other countries, agroecological zones and economies. |
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2016-09-13 |
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2167-8359 |
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Notes |
CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4774 |
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Author |
Nelson, G.C.; Valin, H.; Sands, R.D.; Havlík, P.; Ahammad, H.; Deryng, D.; Elliott, J.; Fujimori, S.; Hasegawa, T.; Heyhoe, E.; Kyle, P.; Von Lampe, M.; Lotze-Campen, H.; Mason d’Croz, D.; van Meijl, H.; van der Mensbrugghe, D.; Müller, C.; Popp, A.; Robertson, R.; Robinson, S.; Schmid, E.; Schmitz, C.; Tabeau, A.; Willenbockel, D. |
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Title |
Climate change effects on agriculture: economic responses to biophysical shocks |
Type |
Journal Article |
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Year |
2014 |
Publication |
Proceedings of the National Academy of Sciences of the United States of America |
Abbreviated Journal |
Proc. Natl. Acad. Sci. U. S. A. |
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Volume |
111 |
Issue |
9 |
Pages |
3274-3279 |
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Keywords |
Agriculture/*economics; Carbon Dioxide/analysis; *Climate Change; Commerce/statistics & numerical data; Computer Simulation; Crops, Agricultural/*growth & development; Forecasting; Humans; *Models, Economic; agricultural productivity; climate change adaptation; integrated assessment; model intercomparison |
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Abstract |
Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change’s representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change. |
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0027-8424 1091-6490 |
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CropM, TradeM, ft_macsur |
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MA @ admin @ |
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4535 |
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Author |
Piontek, F.; Müller, C.; Pugh, T.A.; Clark, D.B.; Deryng, D.; Elliott, J.; Colón González, F.J.; Flörke, M.; Folberth, C.; Franssen, W.; Frieler, K.; Friend, A.D.; Gosling, S.N.; Hemming, D.; Khabarov, N.; Kim, H.; Lomas, M.R.; Masaki, Y.; Mengel, M.; Morse, A.; Neumann, K.; Nishina, K.; Ostberg, S.; Pavlick, R.; Ruane, A.C.; Schewe, J.; Schmid, E.; Stacke, T.; Tang, Q.; Tessler, Z.D.; Tompkins, A.M.; Warszawski, L.; Wisser, D.; Schellnhuber, H.J. |
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Title |
Multisectoral climate impact hotspots in a warming world |
Type |
Journal Article |
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Year |
2014 |
Publication |
Proceedings of the National Academy of Sciences of the United States of America |
Abbreviated Journal |
Proc. Natl. Acad. Sci. U. S. A. |
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Volume |
111 |
Issue |
9 |
Pages |
3233-3238 |
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Keywords |
Agriculture/statistics & numerical data; Computer Simulation; Conservation of Natural Resources/*methods; Ecosystem; *Environment; Geography; Global Warming/economics/*statistics & numerical data; Humans; Malaria/epidemiology; *Models, Theoretical; *Public Policy; Temperature; Water Supply/statistics & numerical data; Isi-mip; coinciding pressures; differential climate impacts |
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Abstract |
The impacts of global climate change on different aspects of humanity’s diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 °C above the 1980-2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 °C. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty. |
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0027-8424 |
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CropM |
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MA @ admin @ |
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4538 |
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