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Author Sanna, M.; Bellocchi, G.; Fumagalli, M.; Acutis, M. url  doi
openurl 
  Title A new method for analysing the interrelationship between performance indicators with an application to agrometeorological models Type Journal Article
  Year (down) 2015 Publication Environmental Modelling & Software Abbreviated Journal Env. Model. Softw.  
  Volume 73 Issue Pages 286-304  
  Keywords model evaluation; performance indicators; stable correlation; solar-radiation; simulation-model; environmental-models; statistical-methods; crop nitrogen; validation; rice; uncertainty; calibration; software  
  Abstract The use of a variety of metrics is advocated to assess model performance but correlated metrics may convey the same information, thus leading to redundancy. Starting from this assumption, a method was developed for selecting, from among a collection of performance indicators, one or more subsets providing the same information as the entire set. The method, based on the definition of “stable correlation”, was applied to 23 performance indicators of agrometeorological models, calculated on large sets of simulated and observed data of four agronomic and meteorological variables: above-ground biomass, leaf area index, hourly air relative humidity and daily solar radiation. Two subsets were determined: {Squared Bias, Root Mean Squared Relative Error, Coefficient of Determination, Pattern Index, Modified Modelling Efficiency}, {Persistence Model Efficiency, Root Mean Squared Relative Error, Coefficient of Determination, Pattern Index}. The method needs corroboration but is statistically founded and can support the implementation of standardized evaluation tools. (C) 2015 Elsevier Ltd. All rights reserved.  
  Address  
  Corporate Author Thesis  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1364-8152 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM LiveM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4503  
Permanent link to this record
 

 
Author Schmitz, C.; Kreidenweis, U.; Lotze-Campen, H.; Popp, A.; Krause, M.; Dietrich, J.P.; Müller, C. url  doi
openurl 
  Title Agricultural trade and tropical deforestation: interactions and related policy options Type Journal Article
  Year (down) 2014 Publication Regional Environmental Change Abbreviated Journal Reg Environ Change  
  Volume 15 Issue 8 Pages 1757-1772  
  Keywords Land-use change; Trade liberalisation; Tropical deforestation; Forest; protection; Agricultural productivity growth; land-use; brazilian amazon; co2 concentrations; carbon emissions; conservation; climate; mitigation; forests; impact; growth; Environmental Sciences & Ecology  
  Abstract The extensive clearing of tropical forests throughout past decades has been partly assigned to increased trade in agricultural goods. Since further trade liberalisation can be expected, remaining rainforests are likely to face additional threats with negative implications for climate mitigation and the local environment. We apply a spatially explicit economic land-use model coupled to a biophysical vegetation model to examine linkages and associated policies between trade and tropical deforestation in the future. Results indicate that further trade liberalisation leads to an expansion of deforestation in Amazonia due to comparative advantages of agriculture in South America. Globally, between 30 and 60 million ha (5-10 %) of tropical rainforests would be cleared additionally, leading to 20-40 Gt additional emissions by 2050. By applying different forest protection policies, those values could be reduced substantially. Most effective would be the inclusion of avoided deforestation into a global emissions trading scheme. Carbon prices corresponding to the concentration target of 550 ppm would prevent deforestation after 2020. Investing in agricultural productivity reduces pressure on tropical forests without the necessity of direct protection. In general, additional trade-induced demand from developed and emerging countries should be compensated by international efforts to protect natural resources in tropical regions.  
  Address 2016-10-31  
  Corporate Author Thesis  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1436-3798 1436-378x ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial 4810  
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Author Dumont, B.; Leemans, V.; Ferrandis, S.; Bodson, B.; Destain, J.-P.; Destain, M.-F. url  doi
openurl 
  Title Assessing the potential of an algorithm based on mean climatic data to predict wheat yield Type Journal Article
  Year (down) 2014 Publication Precision Agriculture Abbreviated Journal Precision Agric.  
  Volume 15 Issue 3 Pages 255-272  
  Keywords stics model; yield prediction; real-time; proxy-sensing; stochastic weather generator; crop yield; mediterranean environment; simulation-model; variability; nitrogen; ensembles; forecasts; demeter; europe  
  Abstract The real-time non-invasive determination of crop biomass and yield prediction is one of the major challenges in agriculture. An interesting approach lies in using process-based crop yield models in combination with real-time monitoring of the input climatic data of these models, but unknown future weather remains the main obstacle to reliable yield prediction. Since accurate weather forecasts can be made only a short time in advance, much information can be derived from analyzing past weather data. This paper presents a methodology that addresses the problem of unknown future weather by using a daily mean climatic database, based exclusively on available past measurements. It involves building climate matrix ensembles, combining different time ranges of projected mean climate data and real measured weather data originating from the historical database or from real-time measurements performed in the field. Used as an input for the STICS crop model, the datasets thus computed were used to perform statistical within-season biomass and yield prediction. This work demonstrated that a reliable predictive delay of 3-4 weeks could be obtained. In combination with a local micrometeorological station that monitors climate data in real-time, the approach also enabled us to (i) predict potential yield at the local level, (ii) detect stress occurrence and (iii) quantify yield loss (or gain) drawing on real monitored climatic conditions of the previous few days.  
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  Language English Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 1385-2256 1573-1618 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial 4621  
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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. doi  openurl
  Title Multisectoral climate impact hotspots in a warming world Type Journal Article
  Year (down) 2014 Publication Proceedings of the National Academy of Sciences of the United States of America Abbreviated Journal Proc. Natl. Acad. Sci. U. S. A.  
  Volume 111 Issue 9 Pages 3233-3238  
  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  
  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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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0027-8424 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial 4538  
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Author Müller, C.; Waha, K.; Bondeau, A.; Heinke, J. doi  openurl
  Title Hotspots of climate change impacts in sub-Saharan Africa and implications for adaptation and development Type Journal Article
  Year (down) 2014 Publication Global Change Biology Abbreviated Journal Glob. Chang. Biol.  
  Volume 20 Issue 8 Pages 2505-2517  
  Keywords Africa South of the Sahara; *Climate Change; Crops, Agricultural; Environment; Hydrology; *Models, Theoretical; Uncertainty; adaptation; climate change; development; impacts; modeling; sub-Saharan Africa  
  Abstract Development efforts for poverty reduction and food security in sub-Saharan Africa will have to consider future climate change impacts. Large uncertainties in climate change impact assessments do not necessarily complicate, but can inform development strategies. The design of development strategies will need to consider the likelihood, strength, and interaction of climate change impacts across biosphere properties. We here explore the spread of climate change impact projections and develop a composite impact measure to identify hotspots of climate change impacts, addressing likelihood and strength of impacts. Overlapping impacts in different biosphere properties (e.g. flooding, yields) will not only claim additional capacity to respond, but will also narrow the options to respond and develop. Regions with severest projected climate change impacts often coincide with regions of high population density and poverty rates. Science and policy need to propose ways of preparing these areas for development under climate change impacts.  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1354-1013 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4534  
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