| Records |
| Author |
Lindeskog, M.; Arneth, A.; Bondeau, A.; Waha, K.; Seaquist, J.; Olin, S.; Smith, B. |
| Title |
Implications of accounting for land use in simulations of ecosystem carbon cycling in Africa |
Type |
Journal Article |
| Year |
2013 |
Publication |
Earth System Dynamics |
Abbreviated Journal |
Earth System Dynamics |
| Volume |
4 |
Issue |
2 |
Pages |
385-407 |
| Keywords |
global vegetation model; sub-saharan africa; climate-change; yield gaps; co2; balance; dynamics; atmosphere; cover; variability |
| Abstract |
Dynamic global vegetation models (DGVMs) are important tools for modelling impacts of global change on ecosystem services. However, most models do not take full account of human land management and land use and land cover changes (LULCCs). We integrated croplands and pasture and their management and natural vegetation recovery and succession following cropland abandonment into the LPJ-GUESS DGVM. The revised model was applied to Africa as a case study to investigate the implications of accounting for land use on net ecosystem carbon balance (NECB) and the skill of the model in describing agricultural production and reproducing trends and patterns in vegetation structure and function. The seasonality of modelled monthly fraction of absorbed photosynthetically active radiation (FPAR) was shown to agree well with satellite-inferred normalised difference vegetation index (NDVI). In regions with a large proportion of cropland, the managed land addition improved the FPAR vs. NDVI fit significantly. Modelled 1991-1995 average yields for the seven most important African crops, representing potential optimal yields limited only by climate forcings, were generally higher than reported FAO yields by a factor of 2-6, similar to previous yield gap estimates. Modelled inter-annual yield variations during 1971-2005 generally agreed well with FAO statistics, especially in regions with pronounced climate seasonality. Modelled land-atmosphere carbon fluxes for Africa associated with land use change (0.07 PgC yr(-1) release to the atmosphere for the 1980s) agreed well with previous estimates. Cropland management options (residue removal, grass as cover crop) were shown to be important to the land-atmosphere carbon flux for the 20th century. |
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English |
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| ISSN |
2190-4979 |
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Article |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4494 |
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| Author |
Murat, M.; Malinowska, I.; Hoffmann, H.; Baranowski, P. |
| Title |
Statistical modelling of agrometeorological time series by exponential smoothing |
Type |
Journal Article |
| Year |
2016 |
Publication |
International Agrophysics |
Abbreviated Journal |
International Agrophysics |
| Volume |
30 |
Issue |
1 |
Pages |
57-65 |
| Keywords |
exponential smoothing; meteorological time series; statistical forecasting; daily temperature records; weighted moving averages; climate-change; prediction; forecasts; state; weather |
| Abstract |
Meteorological time series are used in modelling agrophysical processes of the soil-plant-atmosphere system which determine plant growth and yield. Additionally, longterm meteorological series are used in climate change scenarios. Such studies often require forecasting or projection of meteorological variables, eg the projection of occurrence of the extreme events. The aim of the article was to determine the most suitable exponential smoothing models to generate forecast using data on air temperature, wind speed, and precipitation time series in Jokioinen (Finland), Dikopshof (Germany), Lleida (Spain), and Lublin (Poland). These series exhibit regular additive seasonality or non-seasonality without any trend, which is confirmed by their autocorrelation functions and partial autocorrelation functions. The most suitable models were indicated by the smallest mean absolute error and the smallest root mean squared error. |
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English |
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Edition |
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| ISSN |
0236-8722 |
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Article |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4728 |
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| Author |
Minet, J.; Laloy, E.; Tychon, B.; François, L. |
| Title |
Bayesian inversions of a dynamic vegetation model at four European grassland sites |
Type |
Journal Article |
| Year |
2015 |
Publication |
Biogeosciences |
Abbreviated Journal |
Biogeosciences |
| Volume |
12 |
Issue |
9 |
Pages |
2809-2829 |
| Keywords |
eddy-covariance data; terrestrial ecosystem model; bioclimatic affinity; groups; monte-carlo-simulation; dry-matter content; leaf-area; climate-change; stomatal conductance; parameter-estimation; plant |
| Abstract |
Eddy covariance data from four European grassland sites are used to probabilistically invert the CARAIB (CARbon Assimilation In the Biosphere) dynamic vegetation model (DVM) with 10 unknown parameters, using the DREAM((ZS)) (DiffeRential Evolution Adaptive Metropolis) Markov chain Monte Carlo (MCMC) sampler. We focus on comparing model inversions, considering both homoscedastic and heteroscedastic eddy covariance residual errors, with variances either fixed a priori or jointly inferred together with the model parameters. Agreements between measured and simulated data during calibration are comparable with previous studies, with root mean square errors (RMSEs) of simulated daily gross primary productivity (GPP), ecosystem respiration (RECO) and evapotranspiration (ET) ranging from 1.73 to 2.19, 1.04 to 1.56 g C m(-2) day(-1) and 0.50 to 1.28 mm day(-1), respectively. For the calibration period, using a homoscedastic eddy covariance residual error model resulted in a better agreement between measured and modelled data than using a heteroscedastic residual error model. However, a model validation experiment showed that CARAIB models calibrated considering heteroscedastic residual errors perform better. Posterior parameter distributions derived from using a heteroscedastic model of the residuals thus appear to be more robust. This is the case even though the classical linear heteroscedastic error model assumed herein did not fully remove heteroscedasticity of the GPP residuals. Despite the fact that the calibrated model is generally capable of fitting the data within measurement errors, systematic bias in the model simulations are observed. These are likely due to model inadequacies such as shortcomings in the photosynthesis modelling. Besides the residual error treatment, differences between model parameter posterior distributions among the four grassland sites are also investigated. It is shown that the marginal distributions of the specific leaf area and characteristic mortality time parameters can be explained by site-specific ecophysiological characteristics. |
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English |
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Series Issue |
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Edition |
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| ISSN |
1726-4189 |
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Medium |
Article |
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Conference |
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| Notes |
CropM LiveM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4571 |
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| Author |
Bojar, W.; Knopik, L.; Żarski, J.; Kuśmierek-Tomaszewska, R. |
| Title |
Integrated assessment of crop productivity based on the food supply forecasting |
Type |
Journal Article |
| Year |
2016 |
Publication |
Agricultural Economics – Czech |
Abbreviated Journal |
Agricultural Economics – Czech |
| Volume |
61 |
Issue |
11 |
Pages |
502-510 |
| Keywords |
climate changes; decision-making tools; estimation of parameters; forecasted outputs; gamma distribution; predicting yields; climate-change; emissions scenarios; impacts; potato; yield; growth; policy; scale; water |
| Abstract |
Climate change scenarios suggest that long periods without rainfall will occur in the future often causing instability of the agricultural products market. The aim of our research was to build a model describing the amount of precipitation and droughts for forecasting crop yields in the future. In this study, we analysed a non-standard mixture of gamma and one point distributions as the model of rainfall. On the basis of the rainfall data, one can estimate parameters of the distribution. Parameter estimators were constructed using a method of maximum likelihood. The obtained rainfall data allow confirming the hypothesis of the adequacy of the proposed rainfall models. Long series of droughts allow one to determine the probabilities of adverse phenomena in agriculture. Based on the model, yields of barley in the years 2030 and 2050 were forecasted which can be used for the assessment of other crops productivity. The results obtained with this approach can be used to predict decreases in agricultural production caused by prospective rainfall shortages. This will enable decision makers to shape effective agricultural policies in order to learn how to balance the food supplies and demands through an appropriate management of stored raw food materials and import/export policies. |
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English |
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Series Issue |
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Edition |
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| ISSN |
0139-570x |
ISBN |
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Article |
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Conference |
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| Notes |
CropM, TradeM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4644 |
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| Author |
Daccache, A.; Ciurana, J.S.; Diaz, J.A.R.; Knox, J.W. |
| Title |
Water and energy footprint of irrigated agriculture in the Mediterranean region |
Type |
Journal Article |
| Year |
2014 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
| Volume |
9 |
Issue |
12 |
Pages |
124014 |
| Keywords |
food security; CO2 emissions; nexus; water productivity; water resources; climate-change; southern spain; management; impacts; deficit; grids |
| Abstract |
Irrigated agriculture constitutes the largest consumer of freshwater in the Mediterranean region and provides a major source of income and employment for rural livelihoods. However, increasing droughts and water scarcity have highlighted concerns regarding the environmental sustainability of agriculture in the region. An integrated assessment combining a gridded water balance model with a geodatabase and GIS has been developed and used to assess the water demand and energy footprint of irrigated production in the region. Modelled outputs were linked with crop yield and water resources data to estimate water (m(3) kg(-1)) and energy (CO2 kg(-1)) productivity and identify vulnerable areas or `hotspots’. For a selected key crops in the region, irrigation accounts for 61 km(3) yr(-1) of water abstraction and 1.78 Gt CO2 emissions yr-1, with most emissions from sunflower (73 kg CO2/t) and cotton (60 kg CO2/t) production. Wheat is a major strategic crop in the region and was estimated to have a water productivity of 1000 tMm(-3) and emissions of 31 kg CO2/t. Irrigation modernization would save around 8 km(3) of water but would correspondingly increase CO2 emissions by around +135\%. Shifting from rain-fed to irrigated production would increase irrigation demand to 166 km(3) yr(-1) (+137\%) whilst CO2 emissions would rise by +270\%. The study has major policy implications for understanding the water-energy-food nexus in the region and the trade-offs between strategies to save water, reduce CO2 emissions and/or intensify food production. |
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English |
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Edition |
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| ISSN |
1748-9326 |
ISBN |
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Article |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4747 |
| Permanent link to this record |
