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Author (up) Bennetzen, E.H.; Smith, P.; Porter, J.R. doi  openurl
  Title Decoupling of greenhouse gas emissions from global agricultural production: 1970-2050 Type Journal Article
  Year 2016 Publication Global Change Biology Abbreviated Journal Glob. Chang. Biol.  
  Volume 22 Issue 2 Pages 763-781  
  Keywords climate change; energy use; global agriculture; greenhouse gas emissions; land use; mitigation; sustainable intensification  
  Abstract Since 1970 global agricultural production has more than doubled; contributing ~1/4 of total anthropogenic greenhouse gas (GHG) burden in 2010. Food production must increase to feed our growing demands, but to address climate change, GHG emissions must decrease. Using an identity approach, we estimate and analyse past trends in GHG emission intensities from global agricultural production and land-use change and project potential future emissions. The novel Kaya-Porter identity framework deconstructs the entity of emissions from a mix of multiple sources of GHGs into attributable elements allowing not only a combined analysis of the total level of all emissions jointly with emissions per unit area and emissions per unit product. It also allows us to examine how a change in emissions from a given source contributes to the change in total emissions over time. We show that agricultural production and GHGs have been steadily decoupled over recent decades. Emissions peaked in 1991 at ~12 Pg CO2 -eq. yr(-1) and have not exceeded this since. Since 1970 GHG emissions per unit product have declined by 39% and 44% for crop- and livestock-production, respectively. Except for the energy-use component of farming, emissions from all sources have increased less than agricultural production. Our projected business-as-usual range suggests that emissions may be further decoupled by 20-55% giving absolute agricultural emissions of 8.2-14.5 Pg CO2 -eq. yr(-1) by 2050, significantly lower than many previous estimates that do not allow for decoupling. Beyond this, several additional costcompetitive mitigation measures could reduce emissions further. However, agricultural GHG emissions can only be reduced to a certain level and a simultaneous focus on other parts of the food-system is necessary to increase food security whilst reducing emissions. The identity approach presented here could be used as a methodological framework for more holistic food systems analysis.  
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  Series Volume Series Issue Edition  
  ISSN 1354-1013 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4706  
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Author (up) Bennetzen, E.H.; Smith, P.; Porter, J.R. url  doi
openurl 
  Title Agricultural production and greenhouse gas emissions from world regions—The major trends over 40 years Type Journal Article
  Year 2016 Publication Global Environmental Change Abbreviated Journal Glob. Environ. Change  
  Volume 37 Issue Pages 43-55  
  Keywords Agriculture; Greenhouse gas intensity; Climate change; Kaya-Porter; identity; Decoupling emissions; Kaya-identity; land-use change; carbon-dioxide emissions; sustainable intensification; livestock production; forest transitions; global agriculture; crop; production; food security; deforestation; mitigation  
  Abstract Since 1970, global agricultural production has more than doubled with agriculture and land-use change now responsible for similar to 1/4 of greenhouse gas emissions from human activities. Yet, while greenhouse gas (GHG) emissions per unit of agricultural product have been reduced at a global level, trends in world regions have been quantified less thoroughly. The KPI (Kaya-Porter Identity) is a novel framework for analysing trends in agricultural production and land-use change and related GHG emissions. We apply this to assess trends and differences in nine world regions over the period 1970-2007. We use a deconstructed analysis of emissions from the mix of multiple sources, and show how each is changing in terms of absolute emissions on a per area and per produced unit basis, and how the change of emissions from each source contributes to the change in total emissions over time. The doubling of global agricultural production has mainly been delivered by developing and transitional countries, and this has been mirrored by increased GHG emissions. The decoupling of emissions from production shows vast regional differences. Our estimates show that emissions per unit crop (as kg CO2-equivalents per Giga Joule crop product), in Oceania, have been reduced by 94% from 1093 to 69; in Central & South America by 57% from 849 to 362; in sub-Saharan Africa by 27% from 421 to 309, and in Europe by 56% from 86 to 38. Emissions per unit livestock (as kg CO2-eq. GJ(-1) livestock product) have reduced; in sub-Saharan Africa by 24% from 6001 to 4580; in Central & South America by 61% from 3742 to 1448; in Central & Eastern Asia by 82% from 3,205 to 591, and; in North America by 28% from 878 to 632. In general, intensive and industrialised systems show the lowest emissions per unit of agricultural production. (C) 2016 Elsevier Ltd. All rights reserved.  
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  Language English Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 0959-3780 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4758  
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Author (up) Bindi, M.; Palosuo, T.; Trnka, M.; Semenov, M.A. url  doi
openurl 
  Title Modelling climate change impacts on crop production for food security INTRODUCTION Type Journal Article
  Year 2015 Publication Climate Research Abbreviated Journal Clim. Res.  
  Volume 65 Issue Pages 3-5  
  Keywords Crop production; Climate change impact and adaptation assessments; Upscaling; Model ensembles  
  Abstract Process-based crop models that synthesise the latest scientific understanding of biophysical processes are currently the primary scientific tools available to assess potential impacts of climate change on crop production. Important obstacles are still present, however, and must be overcome for improving crop modelling application in integrated assessments of risk, of sustainability and of crop-production resilience in the face of climate change (e.g. uncertainty analysis, model integration, etc.). The research networks MACSUR and AGMIP organised the CropM International Symposium and Workshop in Oslo, on 10-12 February 2014, and present this CR Special, discussing the state-of-the-art-as well as future perspectives-of crop modelling applications in climate change risk assessment, including the challenges of integrated assessments for the agricultural sector.  
  Address 2016-10-31  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0936-577x ISBN Medium Editorial Material  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4785  
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Author (up) Bojar, W.; Knopik, L.; Żarski, J.; Kuśmierek-Tomaszewska, R. url  openurl
  Title Integrated assessment of crop productivity based on the food supply forecasting Type Journal Article
  Year 2016 Publication Agricultural Economics – Czech Abbreviated Journal Agricultural Economics – Czech  
  Volume 61 Issue 11 Pages 502-510  
  Keywords climate changes; decision-making tools; estimation of parameters; forecasted outputs; gamma distribution; predicting yields; climate-change; emissions scenarios; impacts; potato; yield; growth; policy; scale; water  
  Abstract Climate change scenarios suggest that long periods without rainfall will occur in the future often causing instability of the agricultural products market. The aim of our research was to build a model describing the amount of precipitation and droughts for forecasting crop yields in the future. In this study, we analysed a non-standard mixture of gamma and one point distributions as the model of rainfall. On the basis of the rainfall data, one can estimate parameters of the distribution. Parameter estimators were constructed using a method of maximum likelihood. The obtained rainfall data allow confirming the hypothesis of the adequacy of the proposed rainfall models. Long series of droughts allow one to determine the probabilities of adverse phenomena in agriculture. Based on the model, yields of barley in the years 2030 and 2050 were forecasted which can be used for the assessment of other crops productivity. The results obtained with this approach can be used to predict decreases in agricultural production caused by prospective rainfall shortages. This will enable decision makers to shape effective agricultural policies in order to learn how to balance the food supplies and demands through an appropriate management of stored raw food materials and import/export policies.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0139-570x ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, TradeM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4644  
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Author (up) Bojar, W.; Knopik, L.; Żarski, J.; Sławiński, C.; Baranowski, P.; Żarski, W. url  openurl
  Title Impact of extreme climate changes on the forecasted agriculture production Type Journal Article
  Year 2014 Publication Acta Agrophysica Abbreviated Journal Acta Agrophysica  
  Volume 21 Issue 4 Pages 415-431  
  Keywords agricultural economics; agriculture; climate change; crop production; integrating assessments  
  Abstract The paper presents general characteristics of resources and outputs of agriculture in the Kujawsko-Pomorskie and Lubelskie Regions, based on statistical databases and literature review. Some specific features of the regions, with special consideration for the predicted extreme climate changes, are also included. Next, some statistically significant dependencies between the climatic parameters and yields of selected important crops in the abovementioned regions were worked out on the basis of empirical survey conducted in the University of Technology and Life Sciences, Bydgoszcz, and the Institute of Agrophysics in Lublin. Creating an appropriate method of forecasting long series of ten days without precipitation was necessary to find the desired dependencies. Third, some efforts were taken to make integrated assessments of forecast agricultural outputs influenced by climate extreme phenomena on the basis of the yield-precipitation relations obtained and on the data coming from wide area model regional outputs such as prices of farmland and produce.  
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  Area Expedition Conference  
  Notes CropM, TradeM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4619  
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