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Bennetzen, E.H.; Smith, P.; Porter, J.R. |
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Title |
Decoupling of greenhouse gas emissions from global agricultural production: 1970-2050 |
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Journal Article |
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Year |
2016 |
Publication |
Global Change Biology |
Abbreviated Journal |
Glob. Chang. Biol. |
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Volume |
22 |
Issue |
2 |
Pages |
763-781 |
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Keywords |
climate change; energy use; global agriculture; greenhouse gas emissions; land use; mitigation; sustainable intensification |
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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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1354-1013 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4706 |
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Eza, U.; Shtiliyanova, A.; Borras, D.; Bellocchi, G.; Carrère, P.; Martin, R. |
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Title |
An open platform to assess vulnerabilities to climate change: An application to agricultural systems |
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Journal Article |
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Year |
2015 |
Publication |
Ecological Informatics |
Abbreviated Journal |
Ecological Informatics |
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30 |
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389-396 |
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Keywords |
climate change; grasslands; modeling platform; vulnerability assessment; pasture simulation-model; software component; solar-radiation; crop production; change impacts; adaptation; indicator; makers |
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Numerous climate futures are now available from global climate models. Translation of climate data such as precipitation and temperatures into ecologically meaningful outputs for managers and planners is the next frontier. We describe a model-based open platform to assess vulnerabilities of agricultural systems to climate change on pixel-wise data. The platform includes a simulation modeling engine and is suited to work with NetCDF format of input and output files. In a case study covering a region (Auvergne) in the Massif Central of France, the platform is configured to characterize climate (occurrence of arid conditions in historical and projected climate records), soils and human management, and is then used to assess the vulnerability to climate change of grassland productivity (downscaled to a fine scale). We demonstrate how using climate time series, and process-based simulations vulnerabilities can be defined at fine spatial scales relevant to farmers and land managers, and can be incorporated into management frameworks. (C) 2015 Elsevier B.V. All rights reserved. |
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1574-9541 |
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CropM LiveM, ft_macsur |
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MA @ admin @ |
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4708 |
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Paas, W.; Kanellopoulos, A.; van de Ven, G.; Reidsma, P. |
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Integrated impact assessment of climate and socio-economic change on dairy farms in a watershed in the Netherlands |
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Journal Article |
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Year |
2016 |
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NJAS – Wageningen Journal of Life Sciences |
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NJAS – Wageningen Journal of Life Sciences |
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climate change; bio-economic model; explorations; land-use; 2050-scenario |
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Climate and socio-economic change will affect the land use and the economic viability of Dutch dairy farms. Explorations of future scenarios, which include different drivers and impacts, are needed to perform ex-ante policy assessment. This study uses a bio-economic farm model to assess impacts of climate and socio-economic change on dairy farms in a sandy area in the Netherlands. Farm data from the Farm Accountancy Data Network provided information on the current production levels and available farm resources. First, the farm plans of individual farms were optimized in the current situation to benchmark farms and assess the current scope for improvement. Secondly, simulations for two scenarios were included: a Global Economy with 2 °C global temperature rise (GE/W+) and a Regional Community with 1 °C global temperature rise (RC/G). The impacts of climate change, extreme events, juridical change (including abolishment of milk quota), technological change and price changes were evaluated in separate model runs within the predefined scenarios. We found that farms can increase profit both by intensification and land expansion; the latter especially for medium sized farms (less than 70 cows). Climate change including the effect of increased occurrence of extreme events may negatively affect farm gross margin in the GE/W+ scenario. Lower gross margins are compensated for by the effects of technology and price changes. In contrast with the GE/W+ scenario, climate change has positive impacts on farm profit in RC/G, but less favourable farm input-output price ratios have a negative effect. Technological change is needed to compensate for revenue losses due to higher input prices. In both GE/W+ and RC/G scenarios, dairy farms increase production and the use of artificial fertilizer. Medium sized farms have more options to increase profit than the large farms: they benefit more from the abolishment of the milk quota and better adapt to negative and positive impacts of climate change. While the exact impact of different drivers will always remain uncertain, this study showed that changes in prices, technology and markets have a relatively larger impact than climate change, even when extreme events are taken into account. By using whole farm plans as activities that can be selected, the model is grounded in observations, and it was shown that half of the farms are gross margin maximizers as assumed in the model. The model therefore indicates ‘what could happen if’, and gives insights in drivers and impacts of dairy farming in the region. |
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1573-5214 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4712 |
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Author |
Sánchez, B.; Rasmussen, A.; Porter, J.R. |
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Title |
Temperatures and the growth and development of maize and rice: a review |
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Journal Article |
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Year |
2014 |
Publication |
Global Change Biology |
Abbreviated Journal |
Glob. Chang. Biol. |
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20 |
Issue |
2 |
Pages |
408-417 |
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Keywords |
Climate Change; Oryza/*growth & development; Temperature; Zea mays/*growth & development; cardinal temperatures; climatic change impacts; development; growth; lethal temperatures; maize; rice |
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Abstract |
Because of global land surface warming, extreme temperature events are expected to occur more often and more intensely, affecting the growth and development of the major cereal crops in several ways, thus affecting the production component of food security. In this study, we have identified rice and maize crop responses to temperature in different, but consistent, phenological phases and development stages. A literature review and data compilation of around 140 scientific articles have determined the key temperature thresholds and response to extreme temperature effects for rice and maize, complementing an earlier study on wheat. Lethal temperatures and cardinal temperatures, together with error estimates, have been identified for phenological phases and development stages. Following the methodology of previous work, we have collected and statistically analysed temperature thresholds of the three crops for the key physiological processes such as leaf initiation, shoot growth and root growth and for the most susceptible phenological phases such as sowing to emergence, anthesis and grain filling. Our summary shows that cardinal temperatures are conservative between studies and are seemingly well defined in all three crops. Anthesis and ripening are the most sensitive temperature stages in rice as well as in wheat and maize. We call for further experimental studies of the effects of transgressing threshold temperatures so such responses can be included into crop impact and adaptation models. |
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1354-1013 |
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CropM, ftnotmacsur, IPCC-AR5 |
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MA @ admin @ |
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4693 |
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Moriondo, M.; Ferrise, R.; Trombi, G.; Brilli, L.; Dibari, C.; Bindi, M. |
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Title |
Modelling olive trees and grapevines in a changing climate |
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Journal Article |
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2015 |
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Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
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72 |
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387-401 |
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Keywords |
tree crops; climate change; simulation models; crop yield; vitis-vinifera l.; air co2 enrichment; soil-water content; elevated co2; mediterranean basin; cropping systems; growth; yield; carbon; simulation |
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The models developed for simulating olive tree and grapevine yields were reviewed by focussing on the major limitations of these models for their application in a changing climate. Empirical models, which exploit the statistical relationship between climate and yield, and process based models, where crop behaviour is defined by a range of relationships describing the main plant processes, were considered. The results highlighted that the application of empirical models to future climatic conditions (i.e. future climate scenarios) is unreliable since important statistical approaches and predictors are still lacking. While process-based models have the potential for application in climate-change impact assessments, our analysis demonstrated how the simulation of many processes affected by warmer and CO2-enriched conditions may give rise to important biases. Conversely, some crop model improvements could be applied at this stage since specific sub-models accounting for the effect of elevated temperatures and CO2 concentration were already developed. (C) 2014 Elsevier Ltd. All rights reserved. |
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1364-8152 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4691 |
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