| Records |
| Author |
Makowski, D. |
| Title |
A simple Bayesian method for adjusting ensemble of crop model outputs to yield observations |
Type |
Journal Article |
| Year |
2017 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
Europ. J. Agron. |
| Volume |
88 |
Issue |
|
Pages |
76-83 |
| Keywords |
Bayesian method; Climate change; Ensemble modelling; Uncertainty; Yield; Linear-Approach; Climate-Change; CO2 |
| Abstract |
Multi-model forecasting has drawn some attention in crop science for evaluating effect of climate change on crop yields. The principle is to run several individual process-based crop models under several climate scenarios in order to generate ensembles of output values. This paper describes a simple Bayesian method – called Bayes linear method- for updating ensemble of crop model outputs using yield observations. The principle is to summarize the ensemble of crop model outputs by its mean and variance, and then to adjust these two quantities to yield observations in order to reduce uncertainty. The adjusted mean and variance combine two sources of information, i.e., the ensemble of crop model outputs and the observations. Interestingly, with this method, observations collected under a given climate scenario can be used to adjust mean and variance of the model ensemble under a different scenario. Another advantage of the proposed method is that it does not rely on a separate calibration of each individual crop model. The uncertainty reduction resulting from the adjustment of an ensemble of crop models to observations was assessed in a numerical application. The implementation of the Bayes linear method systematically reduced uncertainty, but the results showed the effectiveness of this method varied in function of several factors, especially the accuracy of the yield observation, and the covariance between the crop model output and the observation. (C) 2015 Elsevier B.V. All rights reserved. |
| Address |
2017-08-07 |
| Corporate Author |
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| Language |
English |
Summary Language |
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| Series Editor |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1161-0301 |
ISBN |
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Medium  |
Article |
| Area |
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Expedition |
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Conference |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5171 |
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| Author |
Cortignani, R.; Dono, G. |
| Title |
Agricultural policy and climate change: An integrated assessment of the impacts on an agricultural area of Southern Italy |
Type |
Journal Article |
| Year |
2018 |
Publication |
Environmental Science and Policy |
Abbreviated Journal |
Environ. Sci. Pol. |
| Volume |
81 |
Issue |
|
Pages |
26-35 |
| Keywords |
Agricultural policy; Climate change; Bio-economic model; Integrated Assessment; Temperature-Humidity Index; Adaptation Pathways; Maximum-Entropy; Model; Cap; Uncertainty; Irrigation; Management; Scenarios; Systems |
| Abstract |
The European Union (EU) has recently reformed its Common Agricultural Policy (CAP) and, in parallel, has completely abolished the production quotas for milk. These changes will have important consequences for the use of land, of inputs (i.e., water and chemicals) and on the economic performance of rural areas. It is of interest to evaluate the integrated impact of these modifications and of climate change (CC), since the latter could neutralize or reverse some desired effects of the former. For this purpose, this paper evaluates the potential impact of the abolition of milk quotas, as well as of the reform of the first pillar of CAP in two different climate scenarios (present and near future). A bio-economic model simulates the possible adaptation of various farm types in an agricultural area of Southern Italy to these changes, given the available technological options and current market conditions. The main results show that the considered policy changes have small positive impacts on economic and environmental factors of the study area. However, some farm types are more affected. CC can effectively attenuate or reverse several of those effects, especially in some farm types. These results can inform the planning of future changes to the CAP, which will have to act in the context of deeper climate alteration. |
| Address |
2018-03-02 |
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| Language |
English |
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Edition |
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| ISSN |
1462-9011 |
ISBN |
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Article |
| Area |
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Conference |
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| Notes |
TradeM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5193 |
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| Author |
De Swaef, T.; Bellocchi, G.; Aper, J.; Lootens, P.; Roldan-Ruiz, I. |
| Title |
Use of identifiability analysis in designing phenotyping experiments for modelling forage production and quality |
Type |
Journal Article |
| Year |
2019 |
Publication |
Journal of Experimental Botany |
Abbreviated Journal |
J. Experim. Bot. |
| Volume |
70 |
Issue |
9 |
Pages |
2587-2604 |
| Keywords |
Breeding; grassland modelling; identifiability analysis; perennial; ryegrass; phenotyping; sensitivity analysis; pasture simulation-model; practical identifiability; crop; water; parameters; systems; carbon; uncertainty; sensitivity; emissions |
| Abstract |
Agricultural systems models are complex and tend to be over-parameterized with respect to observational datasets. Practical identifiability analysis based on local sensitivity analysis has proved effective in investigating identifiable parameter sets in environmental models, but has not been applied to agricultural systems models. Here, we demonstrate that identifiability analysis improves experimental design to ensure independent parameter estimation for yield and quality outputs of a complex grassland model. The Pasture Simulation model (PaSim) was used to demonstrate the effectiveness of practical identifiability analysis in designing experiments and measurement protocols within phe-notyping experiments with perennial ryegrass. Virtual experiments were designed combining three factors: frequency of measurements, duration of the experiment. and location of trials. Our results demonstrate that (i) PaSim provides sufficient detail in terms of simulating biomass yield and quality of perennial ryegrass for use in breeding, (ii) typical breeding trials are insufficient to parameterize all influential parameters, (iii) the frequency of measurements is more important than the number of growing seasons to improve the identifiability of PaSim parameters, and (iv) identifiability analysis provides a sound approach for optimizing the design of multi-location trials. Practical identifiability analysis can play an important role in ensuring proper exploitation of phenotypic data and cost-effective multi-location experimental designs. Considering the growing importance of simulation models, this study supports the design of experiments and measurement protocols in the phenotyping networks that have recently been organized. |
| Address |
2020-02-14 |
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English |
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Edition |
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| ISSN |
0022-0957 |
ISBN |
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Article |
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Conference |
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| Notes |
LiveM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5231 |
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| Author |
Tao, F.; Palosuo, T.; Roetter, R.P.; Hernandez Diaz-Ambrona, C.G.; Ines Minguez, M.; Semenov, M.A.; Kersebaum, K.C.; Cammarano, D.; Specka, X.; Nendel, C.; Srivastava, A.K.; Ewert, F.; Padovan, G.; Ferrise, R.; Martre, P.; Rodriguez, L.; Ruiz-Ramos, M.; Gaiser, T.; Hohn, J.G.; Salo, T.; Dibari, C.; Schulman, A.H. |
| Title |
Why do crop models diverge substantially in climate impact projections? A comprehensive analysis based on eight barley crop models |
Type |
Journal Article |
| Year |
2020 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
| Volume |
281 |
Issue |
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Pages |
107851 |
| Keywords |
agriculture; climate change; crop growth simulation; impact; model; improvement; uncertainty; air CO2 enrichment; elevated CO2; wheat growth; nitrogen dynamics; simulation-models; field experiment; atmospheric CO2; rice phenology; temperature; uncertainty |
| Abstract |
Robust projections of climate impact on crop growth and productivity by crop models are key to designing effective adaptations to cope with future climate risk. However, current crop models diverge strongly in their climate impact projections. Previous studies tried to compare or improve crop models regarding the impact of one single climate variable. However, this approach is insufficient, considering that crop growth and yield are affected by the interactive impacts of multiple climate change factors and multiple interrelated biophysical processes. Here, a new comprehensive analysis was conducted to look holistically at the reasons why crop models diverge substantially in climate impact projections and to investigate which biophysical processes and knowledge gaps are key factors affecting this uncertainty and should be given the highest priorities for improvement. First, eight barley models and eight climate projections for the 2050s were applied to investigate the uncertainty from crop model structure in climate impact projections for barley growth and yield at two sites: Jokioinen, Finland (Boreal) and Lleida, Spain (Mediterranean). Sensitivity analyses were then conducted on the responses of major crop processes to major climatic variables including temperature, precipitation, irradiation, and CO2, as well as their interactions, for each of the eight crop models. The results showed that the temperature and CO2 relationships in the models were the major sources of the large discrepancies among the models in climate impact projections. In particular, the impacts of increases in temperature and CO2 on leaf area development were identified as the major causes for the large uncertainty in simulating changes in evapotranspiration, above-ground biomass, and grain yield. Our findings highlight that advancements in understanding the basic processes and thresholds by which climate warming and CO2 increases will affect leaf area development, crop evapotranspiration, photosynthesis, and grain formation in contrasting environments are needed for modeling their impacts. |
| Address |
2020-06-08 |
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article |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5232 |
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| Author |
Holman, I.P.; Brown, C.; Janes, V.; Sandars, D. |
| Title |
Can we be certain about future land use change in Europe? A multi-scenario, integrated-assessment analysis |
Type |
Journal Article |
| Year |
2017 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
| Volume |
151 |
Issue |
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Pages |
126-135 |
| Keywords |
Climate change, Socio-economic change, Impacts, Integrated assessment, Uncertainty; Climate-Change Impacts; Water-Based Sectors; North-West England; Socioeconomic Change; Change Vulnerability; East-Anglia; Adaptation; Policy; Uncertainties; Agriculture |
| Abstract |
The global land system is facing unprecedented pressures from growing human populations and climatic change. Understanding the effects these pressures may have is necessary to designing land management strategies that ensure food security, ecosystem service provision and successful climate mitigation and adaptation. However, the number of complex, interacting effects involved makes any complete understanding very difficult to achieve. Nevertheless, the recent development of integrated modelling frameworks allows for the exploration of the co-development of human and natural systems under scenarios of global change, potentially illuminating the main drivers and processes in future land system change. Here, we use one such integrated modelling framework (the CLIMSAVE Integrated Assessment Platform) to investigate the range of projected outcomes in the European land system across climatic and socio-economic scenarios for the 2050s. We find substantial consistency in locations and types of change even under the most divergent conditions, with results suggesting that climate change alone will lead to a contraction in the agricultural and forest area within Europe, particularly in southern Europe. This is partly offset by the introduction of socioeconomic changes that change both the demand for agricultural production, through changing food demand and net imports, and the efficiency of agricultural production. Simulated extensification and abandonment in the Mediterranean region is driven by future decreases in the relative profitability of the agricultural sector in southern Europe, owing to decreased productivity as a consequence of increased heat and drought stress and reduced irrigation water availability. The very low likelihood (<33% probability) that current land use proportions in many parts of Europe will remain unchanged suggests that future policy should seek to promote and support the multifunctional role of agriculture and forests in different European regions, rather than focusing on increased productivity as a route to agricultural and forestry viability. |
| Address |
2017-02-23 |
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| Notes |
LiveM, TradeM, ft_MACSUR |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4937 |
| Permanent link to this record |
