Ghislain Gosse

Development and evaluation of a CERES-type model for winter oilseed rape

Abstract Because of its large N fertiliser requirements and long growth cycle, winter oilseed rape (Brassica napus L.) is considered to expose its environment to substantial risks of N losses. Soil–crop models provide unique tools to analyse such impacts, with an accuracy that primarily relies on the simulation of crop C and N budgets. Here, we describe a model simulating the growth and development of oilseed rape that was adapted from CERES-N Maize and a previously existing rape model. In addition to its soil components, the model, called CERES-Rape, has modules for crop phenology, net photosynthesis, leaf area development and grain filling, as influenced by crop N status. A new feature compared to previous rape models is the ability to predict the crops C and N budgets throughout its growth cycle, including losses from leaves by senescence. It also contains a mechanistic description of N translocation from vegetative parts to pods and grains after the onset of flowering. The model has been calibrated on a one-year experiment with three fertiliser N levels conducted in France, and subsequently tested on a similar experiment from Denmark for which no parameters were adjusted. In the vegetative phase, the time course of biomass and N accumulations in the various plant compartments was well simulated, with predicted values falling within one or two standard deviations from the mean in the measurements, except for the low-N treatments for which the high rates of leaf senescence could not be mimicked. After the onset of flowering, some bias appeared in the simulation of crop N uptake which impaired the predictions of final grain N yields. Simulated grain dry matter yields matched observations within ±15% for the calibration data set, but were over-estimated by a factor of 2 for the other data set. Despite the above shortcomings, the simulation of fertiliser effects on the dynamics of crop N uptake and dry matter was judged sufficiently satisfactory to allow an investigation of N losses from rapeseed–cropped soils with the CERES-Rape model.

A MODEL OF LEAF AREA DEVELOPMENT AND SENESCENCE FOR WINTER OILSEED RAPE

Abstract In winter crops, leaf area is a major determinant of the final yield, and is substantially affected by losses occurring during vegetative growth. Here, we propose and test a submodel simulating the development of leaf area and pod area, along with leaf senescence, for winter oilseed rape ( Brassica napus L.), which was included in a CERES-type model for rape adapted from CERES-N Maize. This crop model, called CERES-Rape, has components for crop phenology, net photosynthesis, N uptake, and assimilate partitioning. As a new feature compared to previously published work, the leaf area submodel includes senescence from shading due to competition for light in the canopy, and from leaf N deficiencies. The model has been developed and parameterised on a 1-yr-long experiment with three fertilizer N treatments in northeastern France, during which measurements of senescing parts allowed calibration of the equations for leaf area index (LAI) senescence and total generated LAI. The leaf area submodel, once coupled to the CERES-Rape model, was tested against two additional experiments from Denmark and northern France. This process-oriented submodel proved accurate for the simulation of actual LAI whether in the calibration or in the validation phase, with an overall Root Mean Square Error (RMSE) of 0.496 m 2 m −2 , falling close to the mean experimental standard deviation. Extrapolation did not require any further adjustment, although a different cultivar was involved.

Simulation of carbon and nitrogen dynamics in arable soils: a comparison of approaches

Although mechanistic soil-crop models are increasingly accepted as valuable tools in analysing agronomical or environmental issues, potential users are faced with an equally increasing number of available models. In principle, model selection should be based on a rational assessment of its merit with respect to the objectives pursued. Such information may be obtained by comparing the ability of candidate models to predict given sets of experimental data. However, because the basic components of soil-crop models interact strongly in producing model outputs, little can be drawn as to the validity of the approaches used for the individual components. Here, we focused on the soil carbon and nitrogen turnover module of four soil-crop models (CERES, NCSOIL, SUNDIAL, and STICS), which were selected based on their representativity of currently used models, and the range of complexity and process approaches they offered. The C-N modules of models other than CERES were extracted and linked within CERES, so that they were all supplied with the same physical and chemical data. Inputs and outputs other than those involved the N cycle were provided with good reliability by the common CERES shell. The performance of the various modules was assessed according to two criteria: short-term response of topsoil inorganic N to climate and crop residues input, and long-term dynamics of soil organic matter (SOM). Accordingly, data sets involving net mineralization and topsoil inorganic N dynamics under contrasting bare or wheat-cropped soils, and long-term soil carbon data were used to test them. The results highlight a trade-off between the prediction of N mineralization in the short-term (day to year) and SOM dynamics in the long-term (year to decade). On a yearly basis, NCSOIL over-estimated immobilization of inorganic N associated with the decomposition of crop residues, and CERES predicted extremely low mineralization fluxes. STICS and SUNDIAL gave good predictions of soil N supply, but over-estimated the rate at which soil carbon from slow-turnover pools was degraded as a result. Comparison with a model dedicated to predicting SOM turnover (RothC) showed that the discrepancy may be attributed to a strong under-estimation of the turnover of below-ground plant material by the plant modules of CERES. Crop models should thus be improved from this point of view before coupling with SOM models.

Implications of productivity and nutrient requirements on greenhouse gas balance of annual and perennial bioenergy crops

Biomass from dedicated crops is expected to contribute significantly to the replacement of fossil resources. However, sustainable bioenergy cropping systems must provide high biomass production and low environmental impacts. This study aimed at quantifying biomass production, nutrient removal, expected ethanol production, and greenhouse gas (GHG) balance of six bioenergy crops: Miscanthus × giganteus, switchgrass, fescue, alfalfa, triticale, and fiber sorghum. Biomass production and N, P, K balances (input‐output) were measured during 4 years in a long‐term experiment, which included two nitrogen fertilization treatments. These results were used to calculate a posteriori ‘optimized’ fertilization practices, which would ensure a sustainable production with a nil balance of nutrients. A modified version of the cost/benefit approach proposed by Crutzen et al. (2008), comparing the GHG emissions resulting from N‐P‐K fertilization of bioenergy crops and the GHG emissions saved by replacing fossil fuel, was applied to these ‘optimized’ situations. Biomass production varied among crops between 10.0 (fescue) and 26.9 t DM ha−1 yr−1 (miscanthus harvested early) and the expected ethanol production between 1.3 (alfalfa) and 6.1 t ha−1 yr−1 (miscanthus harvested early). The cost/benefit ratio ranged from 0.10 (miscanthus harvested late) to 0.71 (fescue); it was closely correlated with the N/C ratio of the harvested biomass, except for alfalfa. The amount of saved CO2 emissions varied from 1.0 (fescue) to 8.6 t CO2eq ha−1 yr−1 (miscanthus harvested early or late). Due to its high biomass production, miscanthus was able to combine a high production of ethanol and a large saving of CO2 emissions. Miscanthus and switchgrass harvested late gave the best compromise between low N‐P‐K requirements, high GHG saving per unit of biomass, and high productivity per hectare.