Search

Your search keyword '"Sanna, Mattia"' showing total 103 results
Start Over Author "Sanna, Mattia"
103 results on '"Sanna, Mattia"'

2. On the equivalence of 3-adic Galois representations

Author

Sanna, Mattia

Subjects
512, QA Mathematics
Abstract

Throughout this thesis, we develop theory and the algorithms that lead to an effective method to study the equivalence of two-dimensional 3-adic Galois representations attached to number fields. In order to reach our goal we need three steps: recognising the determinant characters, determining the residual or mod3 representations, and finally proving that the representations agree modulo 3k for any positive integer k. We are able to achieve this using only a finite amount of information coming from the representations. We start with a method that allows us to recognise any one-dimensional Galois representation of any number field K that is unramified outside a given finite set S of primes of K. Afterwards, we extend the methods developed by Argaez- Garcia and Cremona to determine 2-dimensional black box Galois representations of K, unramified outside a given finite set S, whose image lies in GL2(F3). If such representations are irreducible, we can also prove if they are equivalent over GL2(F3). Moreover, due to recent results in modularity lifting, these two methods have an impact on solving modularity problems. Furthermore, starting from two 2-dimensional 3-adic Galois representations of K unramified outside the same S, which we proved by the previous results to have the same determinant character and equivalent residual representations, we are able to prove whether they are equivalent over GL2(Z3) by checking their traces at finitely many places. Finally, since we are able to achieve each step by just computing characteristic polynomials of Frobenius elements of GK, the absolute Galois group of K, at a suitable and computable finite set of primes of K, all our theoretical result are actually effective. That is, we can, and we did, implement them as algorithms that return a precise answer in a finite (and reasonable) amount of time. An application of the algorithms developed is to prove modularity of elliptic curves. We address this studying Galois representations attached to Bianchi modular forms and elliptic curves defined over imaginary quadratic fields of class number one.

Published
2020

10. Classifying Multi-Model Wheat Yield Impact Response Surfaces Showing Sensitivity to Temperature and Precipitation Change

Author

Fronzek, Stefan, Pirttioja, Nina, Carter, Timothy R, Bindi, Marco, Hoffmann, Holger, Palosuo, Taru, Ruiz-Ramos, Margarita, Tao, Fulu, Trnka, Miroslav, Acutis, Marco, Asseng, Senthold, Baranowski, Piotr, Basso, Bruno, Bodin, Per, Buis, Samuel, Cammarano, Davide, Deligios, Paola, Destain, Marie-France, Dumont, Benjamin, Ewert, Frank, Ferrise, Roberto, Francois, Louis, Gaiser, Thomas, Hlavinka, Petr, Jacquemin, Ingrid, Kersebaum, Kurt Christian, Kollas, Chris, Krzyszczak, Jaromir, Lorite, Ignacio J, Minet, Julien, Ines Minguez, M, Montesino, Manuel, Moriondo, Marco, Muller, Christoph, Nendel, Claas, Ozturk, Isik, Perego, Alessia, Rodriguez, Alfredo, Ruane, Alex C, Ruget, Francoise, Sanna, Mattia, Semenov, Mikhail A, Slawinski, Cezary, Stratonovitch, Pierre, Supit, Iwan, Waha, Katharina, Wang, Enli, Wu, Lianhai, Zhao, Zhigan, and Rotter, Reimund P

Subjects
Meteorology And Climatology, Earth Resources And Remote Sensing
Abstract

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (minus 2 to plus 9 degrees Centigrade) and precipitation (minus 50 to plus 50 percent). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.

Published
2017
Full Text
View/download PDF

15. Geo-temporal distribution of 1,688 Chinese healthcare workers infected with COVID-19 in severe conditions – a secondary data analysis

Author

Gao, Wayne, Sanna, Mattia, and Wen, Chi Pang

Subjects
Coronavirus disease 2019 (COVID-19), Disease severity, business.industry, Health care, Case fatality rate, Outbreak, Distribution (economics), Medicine, Secondary data, business, China, Demography
Abstract

IntroductionThe COVID-19 outbreak is posing an unprecedented challenge to healthcare workers. This study analyzes the geo-temporal effects on disease severity for the 1,688 Chinese healthcare workers infected with COVID-19.MethodUsing the descriptive results recently reported by the Chinese CDC, we compare the percentage of infected healthcare workers in severe conditions over time and across three areas in China, and the fatality rate of infected healthcare workers with all the infected individuals in China aged 22-59 years.ResultsAmong the infected Chinese healthcare workers whose symptoms onset appeared during the same ten-day period, the percentage of those in severe conditions decreased statistical significantly from 19.7% (Jan 11 – 20) to 14.4% (Jan 21 – 31) to 8.7% (Feb 1 – 11). Across the country, there was also a significant difference in the disease severity among patients symptoms onset during the same period, with Wuhan being the most severe (17%), followed by Hubei Province (10.4%), and the rest of China (7.0%). The case fatality rate for the 1,688 infected Chinese healthcare workers was significantly lower than that for the 29,798 infected patients aged 20-59 years—0.3% (5/1,688) vs. 0.65% (193/29,798), respectively.ConclusionThe disease severity improved considerably over a short period of time in China. The more severe conditions in Wuhan compared to the rest of the country may be attributable to the draconian lockdown. The clinical outcomes of infected Chinese healthcare workers may represent a more accurate estimation of the severity of COVID-19 for those who have access to quality healthcare.

Published
2020

19. Smoking, Air Pollution and Emphysema/COPD in Six US Cities 2000-2018: Contextualizing Statistical Association in Health Communication

Author

Gao, Wayne, Sanna, Mattia, and Wen, Chi Pang

Subjects
life_sciences_other
Abstract

A recent study found that a 3ppb increase in O3 ambient concentration was associated with an increased progression of 0.18 percentage points in percent emphysema and that such increase was equal to smoking 20 cigarettes per day for 29 years. A simple estimation of population attributable fraction shows that COPD diagnoses due to smoking are actually 30 times more than those attributed to a 3 ppb increment in O3 concentration. Labelling ozone pollution as the new smoking may distort perception of the risks and hinder proper response to real life threatening risk such as smoking.

Published
2019

20. Sensitivity analyses of simulated biomass yield and carbon-fluxes from Euro-Mediterranean grasslands

Author

Sandor, Renata, Bellocchi, Gianni, Bottyán, E, Acutis, Marco, Doro, Luca, Hidy, Dora, Hollós, R, Minet, J, Lellei-Kovács, Eszter, Ma, S, Perego, Alessia, Ruget, Francoise, Sanna, Mattia, Seddaiu, Giovanna, Wu, L, Barcza, Zoltán, Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Agricultural Research Institute, Department of Meteorology, Università degli Studi di Milano [Milano] (UNIMI), Università degli Studi di Sassari, MTA Centre for Ecological Research, Université de Liège, Hungarian Academy of Sciences (MTA), Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Rothamsted Research, Faculty of Forestry and Wood Sciences, and MACSUR

Subjects
modélisation, sensibilité, prairies, [SDE.MCG]Environmental Sciences/Global Changes, prairie, Milieux et Changements globaux, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2019

27. Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change

Author

Fronzek, S., Pirtioja, Nina, Carter, Timothy, Bindi, Marco, Hoffmann, Holger, Palosuo, Taru, Ruiz Ramos, Margarita, Tao, Fulu, Trnka, M., Acutis, Marco, Asseng, Senthold, Baranowski, Piotr, Basso, Bruno, Bodin, Per, Buis, Samuel, Cammarano, Davide, Deligios, Paola, Destain, Marie-France, Dumont, Benjamin, Ewert, Frank, Ferrise, Roberto, François, Louis, Gaiser, Thomas, Hlavinka, P., Jacquemin, I., Kersebaum, K.C., Kollas, Chris, Krzyszczak, Jaromir, Lorite, I. J., Minet, Julien, Minguez Tudela, Maria Ines, Montesino, Manuel, Moriondo, Marco, Müller, Christoph, Nendel, Claas, Öztürk, Isik, Perego, Alessia, Rodríguez Sánchez, Alfredo, Ruane, Alex C., Ruget, François, Sanna, Mattia, Semenov, Mikhail A., Slawinski, Cezary, Stratonovitch, Pierre, Supit, Iwan, Waha, Katharina, Wang, E., Wu, Lianhai, Zhao, Z., Röter, R.P., Fronzek, S., Pirtioja, Nina, Carter, Timothy, Bindi, Marco, Hoffmann, Holger, Palosuo, Taru, Ruiz Ramos, Margarita, Tao, Fulu, Trnka, M., Acutis, Marco, Asseng, Senthold, Baranowski, Piotr, Basso, Bruno, Bodin, Per, Buis, Samuel, Cammarano, Davide, Deligios, Paola, Destain, Marie-France, Dumont, Benjamin, Ewert, Frank, Ferrise, Roberto, François, Louis, Gaiser, Thomas, Hlavinka, P., Jacquemin, I., Kersebaum, K.C., Kollas, Chris, Krzyszczak, Jaromir, Lorite, I. J., Minet, Julien, Minguez Tudela, Maria Ines, Montesino, Manuel, Moriondo, Marco, Müller, Christoph, Nendel, Claas, Öztürk, Isik, Perego, Alessia, Rodríguez Sánchez, Alfredo, Ruane, Alex C., Ruget, François, Sanna, Mattia, Semenov, Mikhail A., Slawinski, Cezary, Stratonovitch, Pierre, Supit, Iwan, Waha, Katharina, Wang, E., Wu, Lianhai, Zhao, Z., and Röter, R.P.

Abstract

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (−2 to +9°C) and precipitation (−50 to +50%). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed th

Published
2018

28. Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change

Author

Fronzek, Stefan, Pirttioja, Nina, Carter, Timothy R., Bindi, Marco, Hoffmann, Holger, Palosuo, Taru, Ruiz-Ramos, Margarita, Tao, Fulu, Trnka, Miroslav, Acutis, Marco, Asseng, Senthold, Baranowski, Piotr, Basso, Bruno, Bodin, Per, Buis, Samuel, Cammarano, Davide, Deligios, Paola, Destain, Marie-France, Dumont, Benjamin, Ewert, Frank, Ferrise, Roberto, François, Louis, Gaiser, Thomas, Hlavinka, Petr, Jacquemin, Ingrid, Kersebaum, Kurt Christian, Kollas, Chris, Krzyszczak, Jaromir, Lorite, Ignacio J., Minet, Julien, Minguez, M. Ines, Montesino San Martin, Manuel, Moriondo, Marco, Müller, Christoph, Nendel, Claas, Öztürk, Isik, Perego, Alessia, Rodríguez, Alfredo, Ruane, Alex C., Ruget, Françoise, Sanna, Mattia, Semenov, Mikhail A., Slawinski, Cezary, Stratonovitch, Pierre, Supit, Iwan, Waha, Katharina, Wang, Enli, Wu, Lianhai, Zhao, Zhigan, Rötter, Reimund P., Fronzek, Stefan, Pirttioja, Nina, Carter, Timothy R., Bindi, Marco, Hoffmann, Holger, Palosuo, Taru, Ruiz-Ramos, Margarita, Tao, Fulu, Trnka, Miroslav, Acutis, Marco, Asseng, Senthold, Baranowski, Piotr, Basso, Bruno, Bodin, Per, Buis, Samuel, Cammarano, Davide, Deligios, Paola, Destain, Marie-France, Dumont, Benjamin, Ewert, Frank, Ferrise, Roberto, François, Louis, Gaiser, Thomas, Hlavinka, Petr, Jacquemin, Ingrid, Kersebaum, Kurt Christian, Kollas, Chris, Krzyszczak, Jaromir, Lorite, Ignacio J., Minet, Julien, Minguez, M. Ines, Montesino San Martin, Manuel, Moriondo, Marco, Müller, Christoph, Nendel, Claas, Öztürk, Isik, Perego, Alessia, Rodríguez, Alfredo, Ruane, Alex C., Ruget, Françoise, Sanna, Mattia, Semenov, Mikhail A., Slawinski, Cezary, Stratonovitch, Pierre, Supit, Iwan, Waha, Katharina, Wang, Enli, Wu, Lianhai, Zhao, Zhigan, and Rötter, Reimund P.

Published
2018

33. Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change

Author

Fronzek, Stefan, primary, Pirttioja, Nina, additional, Carter, Timothy R., additional, Bindi, Marco, additional, Hoffmann, Holger, additional, Palosuo, Taru, additional, Ruiz-Ramos, Margarita, additional, Tao, Fulu, additional, Trnka, Miroslav, additional, Acutis, Marco, additional, Asseng, Senthold, additional, Baranowski, Piotr, additional, Basso, Bruno, additional, Bodin, Per, additional, Buis, Samuel, additional, Cammarano, Davide, additional, Deligios, Paola, additional, Destain, Marie-France, additional, Dumont, Benjamin, additional, Ewert, Frank, additional, Ferrise, Roberto, additional, François, Louis, additional, Gaiser, Thomas, additional, Hlavinka, Petr, additional, Jacquemin, Ingrid, additional, Kersebaum, Kurt Christian, additional, Kollas, Chris, additional, Krzyszczak, Jaromir, additional, Lorite, Ignacio J., additional, Minet, Julien, additional, Minguez, M. Ines, additional, Montesino, Manuel, additional, Moriondo, Marco, additional, Müller, Christoph, additional, Nendel, Claas, additional, Öztürk, Isik, additional, Perego, Alessia, additional, Rodríguez, Alfredo, additional, Ruane, Alex C., additional, Ruget, Françoise, additional, Sanna, Mattia, additional, Semenov, Mikhail A., additional, Slawinski, Cezary, additional, Stratonovitch, Pierre, additional, Supit, Iwan, additional, Waha, Katharina, additional, Wang, Enli, additional, Wu, Lianhai, additional, Zhao, Zhigan, additional, and Rötter, Reimund P., additional

Published
2018
Full Text
View/download PDF

34. Classifying simulated wheat yield responses to changes in temperature and precipitation across a european transect

Author

Fronzek, Stefan, Pirttioja, N., Carter, Timothy R., Bindi, M., Hoffmann, H., Palosuo, T., Ruiz-Ramos, Margarita, Tao, F., Trnka, M., Acutis, M., Asseng, S., Baranowski, P., Basso, Benjamin, Bodin, P., Buis, Samuel, Cammarano, D., Deligios, P., Destain, Marie-France, Dumont, Bertrand, Ewert, Franck, Ferrise, R., FRANCOIS, Léa, Gaiser, T., Hlavinka, P., Jacquemin, Ingrid, Kersebaum, K. C., Kollas, C., Krzyszczak, J., Lorite, Ignacio J., Minet, Julien, Minguez, M. Ines, Montesino, M., Moriondo, Marco, MULLER, C, Nendel, C., Peregon, Anna, Rodríguez, A., Ruane, A. C., Ruget, Francoise, Sanna, Mattia, Semenov, M. A., Slawinski, Cezary, Stratonovitch, P., Supit, I., Waha, K., Wang, E., Wu, L., Zhao, Z., Rotter, R. P., Finnish Environment Institute (SYKE), Abeilles et Environnement (AE), Institut National de la Recherche Agronomique (INRA)-Avignon Université (AU), Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité Mixte de Recherche sur les Herbivores - UMR 1213 (UMRH), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Reproduction et développement des plantes (RDP), École normale supérieure de Lyon (ENS de Lyon)-Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), FACCE-JPI Knowledge Hub MACSUR, Knowledge Hub FACCE MACSUR. INT. Agricultural Model Intercomparison and Improvement Project (AgMIP), USA., Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, and École normale supérieure - Lyon (ENS Lyon)-Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL)

Subjects
changement de température, sensitivity analysis, crop model, pluviomètre, [SDE.MCG]Environmental Sciences/Global Changes, région européenne, rendement du blé, transect, snow gauges
Abstract

Classifying simulated wheat yield responses to changes in temperature and precipitation across a european transect. International Crop Modelling Symposium

Published
2016

36. Wheat yield sensitivity to climate change across a European transect for a large ensemble of crop models

Author

Pirttioja, Nina, Carter, Timothy, Fronzek, S., Bindi, Marco, Hoffmann, Holger, Palosuo, Taru, Ruiz Ramos, Margarita, Tao, Fulu, Trna, Michal, Acutis, Marco, Asseng, Senthold, Baranowsk, Piotr, Basso, Bruno, Bodin, Per, Buis, Samuel, Cammarano, Davide, Deligios, Paola, Destain, Marie-France, Dumont, Benjamin, Ewert, Frank, Ferrise, Roberto, François, Louis, Gaiser, Thomas, Hlavinka, P., Jacquemin, I., Kersebaum, K. C., Kollas, Chris, Kryszczak, Jaromir, Lorite, I. J., Minet, Julien, Minguez, M. Ines, Montesino, Manuel, Moriondo, Marco, Müller, Christoph, Nendel, Claas, Öztürk, Isik, Perego, Alessia, Rodríguez, A., Ruane, Alex C., Ruget, François, Sanna, Mattia, Semenov, Mikhail A., Slawinski, Cezary, Stratonovitch, Pierre, Supit, Iwan, Waha, Katharina, Wang, E., Wu, Lianhai, Zhao, Z., and Rötter, Reimund

Subjects
Agricultura
Abstract

The sensitivity of a 26 member ensemble of process based wheat simulation models to perturbations in baseline temperature and precipitation was examined to construct impact response surfaces (IRS) of simulated yields.

Published
2015

37. Avoiding social traps in the ecosystem stewardship: The Italian Fontanile lowland spring

Author

Balderacchi, Matteo, Perego, Alessia, Lazzari, Giovanni, Trevisan, Marco, Munoz-Carpena, Rafael, Acutis, Marco, Laini, Alex, Giussani, Andrea, Sanna, Mattia, Kane, Davide, Trevisan, Marco (ORCID:0000-0002-4002-9946), Balderacchi, Matteo, Perego, Alessia, Lazzari, Giovanni, Trevisan, Marco, Munoz-Carpena, Rafael, Acutis, Marco, Laini, Alex, Giussani, Andrea, Sanna, Mattia, Kane, Davide, and Trevisan, Marco (ORCID:0000-0002-4002-9946)

Abstract

Fontanile is a Po Valley (Italy) quasi-natural lowland spring built in the middle age. This paper identifies options for the conservation of the Fontanilewater dependent ecosystem, using scenarios and simulations, and exploring different policy options. Three modeling analysis have been performed: the first was carried out for estimating groundwater contamination and recharge from above, the second for evaluating the function of vegetative filter strip on the surface water quality and the last one for testing pesticide drift reduction due to the vegetative filter strip. Uncertainty characterization included climate change projections. Despite the nitrate concentration in water could favorite the eutrophication phenomena, this not occurs because of the lowphosphate concentration in water and of the presence of arboreal shade. Therefore, the protection strategies must focus on sustaining desirable water quantity conditions. Water saving and conservation technologies that improve the agricultural productivity but reduce the Fontanile water flow and large buffer strips that have a limited efficacy due to the Fontanile hydrological settings can be judged as ecological traps. Inefficient irrigation systems, good agricultural practices, integrated pest management and arboreal filter strip can preserve the quality of those ecosystems.

Published
2016

38. Simulazione di flussi di carbonio da ecosistemi pratensi: applicazione del modello colturale ARMOSA al sito di Laqueuille (Francia)

Author

Perego, Alessia, Sanna, Mattia, Bellocchi, Gianni, Acutis, Marco, Università degli Studi di Milano [Milano] (UNIMI), UR 0874 Unité de recherche sur l'Ecosystème Prairial, Institut National de la Recherche Agronomique (INRA)-Unité de recherche sur l'Ecosystème Prairial (UREP)-Ecologie des Forêts, Prairies et milieux Aquatiques (EFPA), and Institut National de la Recherche Agronomique (INRA)

Subjects
Prairies, Modélisation, [SDE.MCG]Environmental Sciences/Global Changes, Comparaison, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2014

39. Examining wheat yield sensitivity to temperature and precipitation changes for a large ensemble of crop models using impact response surfaces

Author

Pirttioja, Nina, Fronzek, S., Bindi, Marco, Carter, Timothy, Hoffmann, Holger, Palosuo, Taru, Ruiz Ramos, Margarita, Trnka, M., Acutis, Marco, Asseng, Senthold, Baranowsk, Piotr, Basso, Bruno, Bodin, Per, Buis, Samuel, Cammarano, Davide, Deligios, Paola, Destain, Marie-France, Doro, Luca, Dumont, Benjamin, Ewert, Frank, Ferrise, Roberto, François, Louis, Gaiser, Thomas, Hlavinka, P., Kersebaum, K. C., Kollas, Chris, Krzyszczak, Jaromir, Lorite, I. J., Minet, Julien, Minguez, M. Ines, Montesino, Manuel, Moriondo, Marco, Nendel, Claas, Öztürk, Isik, Perego, Alessia, Ruget, François, Rodríguez, A., Sanna, Mattia, Semenov, Mikhail A., Slawinski, Cezary, Stratonovitch, Pierre, Supit, Iwan, Tao, Fulu, Wu, Lianhai, and Rötter, Reimund

Subjects
Agricultura
Abstract

Impact response surfaces (IRSs) depict the response of an impact variable to changes in two explanatory variables as a plotted surface. Here, IRSs of spring and winter wheat yields were constructed from a 25-member ensemble of process-based crop simulation models. Twenty-one models were calibrated by different groups using a common set of calibration data, with calibrations applied independently to the same models in three cases. The sensitivity of modelled yield to changes in temperature and precipitation was tested by systematically modifying values of 1981-2010 baseline weather data to span the range of 19 changes projected for the late 21st century at three locations in Europe.

Published
2014

41. Interrelationship between evaluation metrics to assess agro-ecological models

Author

Sanna, Mattia, Acutis, Marco, Bellocchi, Gianni, Università degli Studi di Milano [Milano] (UNIMI), UR 0874 Unité de recherche sur l'Ecosystème Prairial, Institut National de la Recherche Agronomique (INRA)-Unité de recherche sur l'Ecosystème Prairial (UREP)-Ecologie des Forêts, Prairies et milieux Aquatiques (EFPA), and Institut National de la Recherche Agronomique (INRA)

Subjects
[SDE.MCG]Environmental Sciences/Global Changes, Model Evaluation, Stable Correlation, Performance indicators, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, évaluation de modèles
Abstract

International audience; When evaluating the performances of simulation models, the perception of the quality of the outputs may depend on the statistics used to compare simulated and observed data. In order to have a comprehensive understanding of model performance, the use of a variety of metrics is generally advocated. However, since they may be correlated, the use of two or more metrics may c onvey the same information, leading to redundancy. This preliminary study intends to investigate the interrelationship between evaluation metrics, with the aim of identifying the most useful set of indicators, for assessing simulation performance. Our focus is on agro ecological modelling. Twenty-one performance indicators were selected to compare simulated and observed data of three agronomic and meteorological variables: above --ground biomass, hourly air relative humidity and daily solar radiation. Indicat ors were calculated on large data sets, collected to effectively apply correlation analysis techniques. For each variable, the interrelationship between each pair of indicators was evaluated, by computing the Spearman’s rank correlation coefficient. A defi nition of “stable correlation” was proposed, based on the test of heterogeneity, allowing to assess whether two or more correlation coefficients are equal. An optimal subset of indicators was identified, striking a balance between number of indicators, amo unt of provided information and information redundancy. They are: Index of Agreement, Squared Bias, Root Mean Squared Relative Error, Pattern Index, Persistence Model Efficiency and Modified Modelling Efficiency. The present study was carried out in the co ntext of CropM -¬‐ LiveM cross -¬‐ cutting activities of MACSUR knowledge

Published
2014

43. Temperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfaces

Author

Pirttioja, Nina, Carter, T. R., Fronzek, S., Bindi, Marco, Hoffmann, H., Palosuo, Taru, Ruiz Ramos, Margarita, Tao, Fulu, Trnka, M., Acutis, Marco, Asseng, Senthold, Baranowsk, Piotr, Basso, Bruno, Bodin, Per, Buis, Samuel, Cammarano, Davide, Deligios, Paola, Destain, Marie-France, Dumont, Benjamin, Ewert, Frank, Ferrise, Roberto, Fraçois, F., Gaiser, Thomas, Hlavinka, P., Jacquemin, I., Kersebaum, K. C., Kollas, Chris, Krzyszczak, Jaromir, Lorite, I. J., Minet, Julien, Minguez Tudela, Maria Ines, Montesino, Manuel, Moriondo, Marco, Müller, Christoph, Nendel, Claas, Öztürk, Isik, Perego, Alessia, Rodríguez, A., Ruane, Alex C., Ruget, François, Sanna, Mattia, Semenov, Mikhail A., Slawinski, Cezary, Stratonovitch, Pierre, Supit, Iwan, Waha, Katharina, Wang, E., Wu, Lianhai, Zhao, Z., Rötter, Reimund, Pirttioja, Nina, Carter, T. R., Fronzek, S., Bindi, Marco, Hoffmann, H., Palosuo, Taru, Ruiz Ramos, Margarita, Tao, Fulu, Trnka, M., Acutis, Marco, Asseng, Senthold, Baranowsk, Piotr, Basso, Bruno, Bodin, Per, Buis, Samuel, Cammarano, Davide, Deligios, Paola, Destain, Marie-France, Dumont, Benjamin, Ewert, Frank, Ferrise, Roberto, Fraçois, F., Gaiser, Thomas, Hlavinka, P., Jacquemin, I., Kersebaum, K. C., Kollas, Chris, Krzyszczak, Jaromir, Lorite, I. J., Minet, Julien, Minguez Tudela, Maria Ines, Montesino, Manuel, Moriondo, Marco, Müller, Christoph, Nendel, Claas, Öztürk, Isik, Perego, Alessia, Rodríguez, A., Ruane, Alex C., Ruget, François, Sanna, Mattia, Semenov, Mikhail A., Slawinski, Cezary, Stratonovitch, Pierre, Supit, Iwan, Waha, Katharina, Wang, E., Wu, Lianhai, Zhao, Z., and Rötter, Reimund

Abstract

This study explored the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and winter wheat Triticum aestivum yields were constructed from a 26-member ensemble of process-based crop simulation models for sites in Finland, Germany and Spain across a latitudinal transect. The sensitivity of modelled yield to systematic increments of changes in temperature (-2 to +9°C) and precipitation (-50 to +50%) was tested by modifying values of baseline (1981 to 2010) daily weather, with CO2 concentration fixed at 360 ppm. The IRS approach offers an effective method of portraying model behaviour under changing climate as well as advantages for analysing, comparing and presenting results from multi-model ensemble simulations. Though individual model behaviour occasionally departed markedly from the average, ensemble median responses across sites and crop varieties indicated that yields decline with higher temperatures and decreased precipitation and increase with higher precipitation. Across the uncertainty ranges defined for the IRSs, yields were more sensitive to temperature than precipitation changes at the Finnish site while sensitivities were mixed at the German and Spanish sites. Precipitation effects diminished under higher temperature changes. While the bivariate and multi-model characteristics of the analysis impose some limits to interpretation, the IRS approach nonetheless provides additional insights into sensitivities to inter-model and inter-annual variability. Taken together, these sensitivities may help to pinpoint processes such as heat stress, vernalisation or drought effects requiring refinement in future model development.

Published
2015

44. Filiera del nocciolo: la ricerca a supporto della competitività del prodotto piemontese

Author

Botta, Roberto, Contessa, Cecilia, Valentini, Nadia, Caviglione, Mauro, D'Oria, Marco, Strano, Tiziano Camillo, Calizzano, Federico, Beltramo, Chiara, Zeppa, Giuseppe, Rolle, Luca Giorgio Carlo, Ghirardello, Daniela, Tavella, Luciana, Silvia, Moraglio, Federico, Spanna, Sanna, Mattia, Maria, Corte, Vincenzo, Patrone, and Gianluca, Griseri

Subjects
taleaggio, conservazione, cimiciato, nocciolo, Corylus avellana L, irrigazione, difesa, curculio nucum
Published
2011

49. Biocontrol of Fusarium crown and root rot of tomato and growth-promoting effect of bacteria isolated from recycled substrates of soilless crops.

Author

Jianbin Liu, Gilardi, Giovanna, Sanna, Mattia, Gullino, M. Lodovica, and Garibaldi, Angelo

Subjects
BIOLOGICAL pest control, FUSARIUM oxysporum, TOMATO diseases & pests, PSEUDOMONAS, TRICHODERMA, ROOT rots, HYDROPONICS
Abstract

Fusarium crown and root rot (FCRR) of tomato caused by Fusarium oxysporum f. sp. radicis-lycopersici is a serious problem in agriculture today. Biological control of this disease may be an effective option to deal with this problem. Antagonistic bacteria isolated from suppressive substrates or soils were tested against FCRR in the glasshouse in a sandy soil mixture infested with the pathogen and compared with other experimental or commercial FCRR biocontrol agents. The antagonistic bacteria were applied twice before artificial infection with the pathogen. Pseudomonas sp. strain FC-24B and P. putida FC-8B provided the best and most effective suppression in all trials, reducing vascular discoloration significantly from 65 to 77% and from 52 to 100% respectively. These strains also reduced root rot by 66% and 70% respectively. Pseudomonas sp. FC-24B also substantially increased plant growth, when the pathogen was absent. Pseudomonas sp. FC-9B, Achromobacter xylosoxydans MM1, Streptomyces griseoviridis strain K61 and the commercial formulation Trichoderma harzianum ICC012 + T. viride ICC080 also gave promising results in terms of disease control. [ABSTRACT FROM AUTHOR]

Published
2010

Catalog

Books, media, physical & digital resources
See catalog results