Challenges in quantifying biosphere-atmosphere exchange of nitrogen species

Recent research in nitrogen exchange with the atmosphere has separated research communities according to N form. The integrated perspective needed to quantify the net effect of N on greenhouse-gas balance is being addressed by the NitroEurope Integrated Project (NEU). Recent advances have depended on improved methodologies, while ongoing challenges include gas-aerosol interactions, organic nitrogen and N(2) fluxes. The NEU strategy applies a 3-tier Flux Network together with a Manipulation Network of global-change experiments, linked by common protocols to facilitate model application. Substantial progress has been made in modelling N fluxes, especially for N(2)O, NO and bi-directional NH(3) exchange. Landscape analysis represents an emerging challenge to address the spatial interactions between farms, fields, ecosystems, catchments and air dispersion/deposition. European up-scaling of N fluxes is highly uncertain and a key priority is for better data on agricultural practices. Finally, attention is needed to develop N flux verification procedures to assess compliance with international protocols.     

Sensitivity analysis for models of greenhouse gas emissions at farm level. Case study of N(2)O emissions simulated by the CERES-EGC model

Modelling complex systems such as farms often requires quantification of a large number of input factors. Sensitivity analyses are useful to reduce the number of input factors that are required to be measured or estimated accurately. Three methods of sensitivity analysis (the Morris method, the rank regression and correlation method and the Extended Fourier Amplitude Sensitivity Test method) were compared in the case of the CERES-EGC model applied to crops of a dairy farm. The qualitative Morris method provided a screening of the input factors. The two other quantitative methods were used to investigate more thoroughly the effects of input factors on output variables. Despite differences in terms of concepts and assumptions, the three methods provided similar results. Among the 44 factors under study, N₂O emissions were mainly sensitive to the fraction of N₂O emitted during denitrification, the maximum rate of nitrification, the soil bulk density and the cropland area.     

Soil carbon stocks after conversion of Amazonian tropical forest to grazed pasture: importance of deep soil layers

Recent studies suggest that carbon (C) is stored in the topsoil of pastures established after deforestation. However, little is known about the long-term capacity of tropical pastures to sequester C in different soil layers after deforestation. Deep soil layers are generally not taken into consideration or are underestimated when C storage is calculated. Here we show that in French Guiana, the C stored in the deep soil layers contributes significantly to C stocks down to a depth of 100 cm and that C is sequestered in recalcitrant soil organic matter in the soil below a depth of 20 cm. The contribution of the 50–100 cm soil layer increased from 22 to 31 % with the age of the pasture. We show that long-term C sequestration in C4 tropical pastures is linked to the development of C3 species (legumes and shrubs), which increase both inputs of N into the ecosystem and the C:N ratio of soil organic matter. The deep soil under old pastures contained more C3 carbon than the native forest. If C sequestration in the deep soil is taken into account, our results suggest that the soil C stock in pastures in Amazonia would be higher with sustainable pasture management, in particular by promoting the development of legumes already in place and by introducing new species.     

Cross-sectional biomonitoring study of pesticide exposures in Queensland,Australia, using pooled urine samples

A range of pesticides are available in Australia for use in agricultural and domestic settings to control pests, including organophosphate and pyrethroid insecticides, herbicides, and insect repellents, such as N,N-diethyl-meta-toluamide (DEET). The aim of this study was to provide a cost-effective preliminary assessment of background exposure to a range of pesticides among a convenience sample of Australian residents. De-identified urine specimens stratified by age and sex were obtained from a community-based pathology laboratory and pooled (n = 24 pools of 100 specimens). Concentrations of urinary pesticide biomarkers were quantified using solid-phase extraction coupled with isotope dilution high-performance liquid chromatography–tandem mass spectrometry. Geometric mean biomarker concentrations ranged from <0.1 to 36.8 ng/mL for organophosphate insecticides, <0.1 to 5.5 ng/mL for pyrethroid insecticides, and <0.1 to 8.51 ng/mL for all other biomarkers with the exception of the DEET metabolite 3-diethylcarbamoyl benzoic acid (4.23 to 850 ng/mL). We observed no association between age and concentration for most biomarkers measured but noted a “U-shaped” trend for five organophosphate metabolites, with the highest concentrations observed in the youngest and oldest age strata, perhaps related to age-specific differences in behavior or physiology. The fact that concentrations of specific and non-specific metabolites of the organophosphate insecticide chlorpyrifos were higher than reported in USA and Canada may relate to differences in registered applications among countries. Additional biomonitoring programs of the general population and focusing on vulnerable populations would improve the exposure assessment and the monitoring of temporal exposure trends as usage patterns of pesticide products in Australia change over time.     

Development of the Pasture Simulation Model for assessing livestock production under climate change

To simulate climate change impacts on pastures and domestic herbivores as well as feedbacks to the atmosphere in terms of greenhouse gas emissions, we have improved a process-based biogeochemical pasture model, PaSim. The overall aim was to simulate the meat and milk production of cattle (suckler cows with their calves, dairy cows and heifers) in response to climate and management, as well as feedbacks to the atmosphere through enteric methane emissions. Herbage intake at grazing was calculated from animal characteristics, herbage availability, diet digestibility and air temperature. With suckler cows, milk production and changes in daily liveweight and body condition were calculated from net energy balance. The net energy intake of dairy cows and their body reserves at turnout to pasture were used to simulate milk production at pasture, daily liveweight and body condition changes, taking into account cow energy requirements and intake capacity. Heifer growth was determined from heifer net energy intake and liveweight. Net energy intake was used to assess enteric methane production through a conversion factor, which depends both on the energy level of the diet and on the herbivore type. The model was assessed against experimental data for animal performance and methane emissions at grazing. Predictions show good agreement with observations. On average, the root mean square error was 6.5, 4 and 2.5% for the liveweights of suckler cows, suckler calves and heifers, respectively, 18% for dairy milk production and 12% for enteric methane emissions. By comparing this new version of the PaSim model to the previous version, we show that a greater accuracy in animal performance modelling improves the sensitivity of the model to interannual climate variability. However, long term (30 years) projections of climate change impacts on grasslands and of radiative feedbacks to the atmosphere are not significantly modified. The originality and the validity domain of the model are discussed.