| Records |
| Author |
Kipling, R.P.; Bannink, A.; Bellocchi, G.; Dalgaard, T.; Fox, N.J.; Hutchings, N.J.; Kjeldsen, C.; Lacetera, N.; Sinabell, F.; Topp, C.F.E.; van Oijen, M.; Virkajärvi, P.; Scollan, N.D. |
| Title |
Modeling European ruminant production systems: Facing the challenges of climate change |
Type  |
Journal Article |
| Year |
2016 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agricultural Systems |
| Volume |
147 |
Issue |
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Pages |
24-37 |
| Keywords |
Food security; Livestock systems; Modeling; Pastoral systems; Policy support; Ruminants |
| Abstract |
Ruminant production systems are important producers of food, support rural communities and culture, and help to maintain a range of ecosystem services including the sequestering of carbon in grassland soils. However, these systems also contribute significantly to climate change through greenhouse gas (GHG) emissions, while intensi- fication of production has driven biodiversity and nutrient loss, and soil degradation. Modeling can offer insights into the complexity underlying the relationships between climate change, management and policy choices, food production, and the maintenance of ecosystem services. This paper 1) provides an overview of how ruminant systems modeling supports the efforts of stakeholders and policymakers to predict, mitigate and adapt to climate change and 2) provides ideas for enhancing modeling to fulfil this role. Many grassland models can predict plant growth, yield and GHG emissions from mono-specific swards, but modeling multi-species swards, grassland quality and the impact of management changes requires further development. Current livestock models provide a good basis for predicting animal production; linking these with models of animal health and disease is a prior- ity. Farm-scale modeling provides tools for policymakers to predict the emissions of GHG and other pollutants from livestock farms, and to support the management decisions of farmers from environmental and economic standpoints. Other models focus on how policy and associated management changes affect a range of economic and environmental variables at regional, national and European scales. Models at larger scales generally utilise more empirical approaches than those applied at animal, field and farm-scales and include assumptions which may not be valid under climate change conditions. It is therefore important to continue to develop more realistic representations of processes in regional and global models, using the understanding gained from finer-scale modeling. An iterative process of model development, in which lessons learnt from mechanistic models are ap- plied to develop ‘smart’ empirical modeling, may overcome the trade-off between complexity and usability. De- veloping the modeling capacity to tackle the complex challenges related to climate change, is reliant on closer links between modelers and experimental researchers, and also requires knowledge-sharing and increasing technical compatibility across modeling disciplines. Stakeholder engagement throughout the process of model development and application is vital for the creation of relevant models, and important in reducing problems re- lated to the interpretation of modeling outcomes. Enabling modeling to meet the demands of policymakers and other stakeholders under climate change will require collaboration within adequately-resourced, long-term inter-disciplinary research networks |
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English |
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Series Issue |
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| ISSN |
0308521x |
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Medium |
Review |
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| Notes |
LiveM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4734 |
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| Author |
Eza, U.; Shtiliyanova, A.; Borras, D.; Bellocchi, G.; Carrère, P.; Martin, R. |
| Title |
An open platform to assess vulnerabilities to climate change: An application to agricultural systems |
Type |
Journal Article |
| Year |
2015 |
Publication |
Ecological Informatics |
Abbreviated Journal |
Ecological Informatics |
| Volume |
30 |
Issue |
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Pages |
389-396 |
| Keywords |
climate change; grasslands; modeling platform; vulnerability assessment; pasture simulation-model; software component; solar-radiation; crop production; change impacts; adaptation; indicator; makers |
| Abstract |
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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English |
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| ISSN |
1574-9541 |
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Article |
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| Notes |
CropM LiveM, ft_macsur |
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no |
| Call Number |
MA @ admin @ |
Serial |
4708 |
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| Author |
Ben Touhami, H.; Bellocchi, G. |
| Title |
Bayesian calibration of the Pasture Simulation model (PaSim) to simulate European grasslands under water stress |
Type |
Journal Article |
| Year |
2015 |
Publication |
Ecological Informatics |
Abbreviated Journal |
Ecological Informatics |
| Volume |
30 |
Issue |
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Pages |
356-364 |
| Keywords |
Bayesian calibration framework; Grasslands; Pasture Simulation model; (PaSim); integrated assessment models; chain monte-carlo; climate-change; computation; impacts; vulnerability; likelihoods; france |
| Abstract |
As modeling becomes a more widespread practice in the agro-environmental sciences, scientists need reliable tools to calibrate models against ever more complex and detailed data. We present a generic Bayesian computation framework for grassland simulation, which enables parameter estimation in the Bayesian formalism by using Monte Carlo approaches. We outline the underlying rationale, discuss the computational issues, and provide results from an application of the Pasture Simulation model (PaSim) to three European grasslands. The framework was suited to investigate the challenging problem of calibrating complex biophysical models to data from altered scenarios generated by precipitation reduction (water stress conditions). It was used to infer the parameters of manipulated grassland systems and to assess the gain in uncertainty reduction by updating parameter distributions using measurements of the output variables. |
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English |
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1574-9541 |
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Article |
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| Notes |
CropM, LiveM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4697 |
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| Author |
Ma, S.; Lardy, R.; Graux, A.-I.; Ben Touhami, H.; Klumpp, K.; Martin, R.; Bellocchi, G. |
| Title |
Regional-scale analysis of carbon and water cycles on managed grassland systems |
Type |
Journal Article |
| Year |
2015 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
| Volume |
72 |
Issue |
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Pages |
356-371 |
| Keywords |
carbon flux; eddy flux measurements; model evaluation; pasture simulation model (pasim); water balance; pasture simulation-model; nitrous-oxide emissions; primary productivity npp; comparing global-models; net ecosystem exchange; greenhouse-gas balance; climate-change; agricultural systems; co2 exchange; european grasslands |
| Abstract |
Predicting regional and global carbon (C) and water dynamics on grasslands has become of major interest, as grasslands are one of the most widespread vegetation types worldwide, providing a number of ecosystem services (such as forage production and C storage). The present study is a contribution to a regional-scale analysis of the C and water cycles on managed grasslands. The mechanistic biogeochemical model PaSim (Pasture Simulation model) was evaluated at 12 grassland sites in Europe. A new parameterization was obtained on a common set of eco-physiological parameters, which represented an improvement of previous parameterization schemes (essentially obtained via calibration at specific sites). We found that C and water fluxes estimated with the parameter set are in good agreement with observations. The model with the new parameters estimated that European grassland are a sink of C with 213 g C m(-2) yr(-1), which is close to the observed net ecosystem exchange (NEE) flux of the studied sites (185 g C m(-2) yr(-1) on average). The estimated yearly average gross primary productivity (GPP) and ecosystem respiration (RECO) for all of the study sites are 1220 and 1006 g C m(-2) yr(-1), respectively, in agreement with observed average GPP (1230 g C m(-2) yr(-1)) and RECO (1046 g C m(-2) yr(-1)). For both variables aggregated on a weekly basis, the root mean square error (RMSE) was similar to 5-16 g C week(-1) across the study sites, while the goodness of fit (R-2) was similar to 0.4-0.9. For evapotranspiration (ET), the average value of simulated ET (415 mmyr(-1)) for all sites and years is close to the average value of the observed ET (451 mm yr(-1)) by flux towers (on a weekly basis, RMSE similar to 2-8 mm week(-1); R-2 = 0.3-0.9). However, further model development is needed to better represent soil water dynamics under dry conditions and soil temperature in winter. A quantification of the uncertainties introduced by spatially generalized parameter values in C and water exchange estimates is also necessary. In addition, some uncertainties in the input management data call for the need to improve the quality of the observational system. |
| Address |
2015-10-09 |
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English |
Summary Language |
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Original Title |
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Series Issue |
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Edition |
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| ISSN |
1364-8152 |
ISBN |
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Article |
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Conference |
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| Notes |
CropM, LiveM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4695 |
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| Author |
Lardy, R.; Bellocchi, G.; Martin, R. |
| Title |
Vuln-Indices: Software to assess vulnerability to climate change |
Type |
Journal Article |
| Year |
2015 |
Publication |
Computers and Electronics in Agriculture |
Abbreviated Journal |
Computers and Electronics in Agriculture |
| Volume |
114 |
Issue |
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Pages |
53-57 |
| Keywords |
climate change; Java; vulnerability indices; pasture simulation-model; integrated assessment; environmental-change; change impacts; system |
| Abstract |
Vuln-Indices Java-based software was developed on concepts of vulnerability to climate change of agro-ecological systems. It implements the calculation of vulnerability indices on series of state variables for assessments at both site and region levels. The tool is useful because synthetic indices help capturing complex processes and prove effective to identify the factors responsible for vulnerability and their relative importance. It is suggested that the tool may be plausible for use with stakeholders to disseminate information of climate change impacts. (C) 2015 Elsevier B.V. All rights reserved. |
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English |
Summary Language |
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Series Title |
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Edition |
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| ISSN |
0168-1699 |
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Article |
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| Notes |
LiveM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4648 |
| Permanent link to this record |
