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Prohibition of grazing has significantly reduced soil erosion and enhanced soil organic carbon (SOC) stock on the Loess Plateau. However, this practice has reduced livestock production and consequently decreased herders’ income in the region. In this study, light grazing was therefore re-introduced to investigate effects of converting cropland to grassland on soil erosion and CO2 emission under light grazing practice. The light grazing trials (10 adult sheep grazing to 7–8 cm of the initial grass height in 1530 m2 land area) were conducted, where soil loss, SOC erosion and CO2 emission were measured using 7Be technique and Li−COR Automated Soil CO2 Flux System. Soil and SOC erosion were 60% and 56% lower in the light grazed grassland and 46% and 29% lower in the un-grazed grassland when compared with cropland, respectively. Light grazing and un-grazing practices increased soil CO2 emission by 15% and 33% respectively, relative to cropland. The mechanisms to control soil erosion by light grazing and un-grazing practices were similar, and governed by grass root biomass and near surface vegetation coverage. However, light grazing had higher potential than un-grazing practices in reducing Soil and SOC erosion and CO2 emission. Our results highlight the potential of light grazing in reducing soil erosion in the “Grain for Green” grassland ecosystems to achieve the dual goals of ecological and economic gains, and sustainability in China and elsewhere.

Excreta deposition by grazing livestock is the single largest source of agricultural nitrous oxide (N2O) emissions in New Zealand (NZ). N2O emissions and emission factors (EF3; percentage of excreta nitrogen emitted as N2O) from sheep, beef- and dairy-cattle excreta deposited can vary with differences in the hill land slope and disaggregation of EF3 based on slope may therefore result in a more accurate and improved inventory of national N2O emission. However, research data on N2O emissions from dairy cattle grazing on low and medium slopes of hill country or for beef cattle on low slopes is scarce. Field trials were therefore conducted in four regions of NZ on dairy-grazed (three regions) or sheep & beef cattle-grazed hill land (one region). N2O emissions were measured following dairy and beef cattle urine and dung application on low ( 0.05) slope-effect for EF3 values for beef and dairy cattle excreta (urine or dung) from each individual region, or combined from the three dairy-grazed sites. These findings confirm our hypothesis that N2O EF3 values for excretal inputs on established dairy hill land on low and medium slopes are similar for dairy-grazed hill land. However, the sheep & beef cattle grazed sites had lower (P

Applications of urea fertiliser and farm dairy effluent (FDE) to New Zealand pastures are the second and third largest sources of nitrous oxide (N2O) emissions, after emissions from excreta deposited during grazing (urine and dung). New Zealand currently employs emission factors (EF1) (percentage of N applied which is emitted as N2O) of 0.48% and 1% for urea fertiliser and FDE, respectively, for calculating its national N2O inventory. The country specific emission factors for urine and dung are 1% and 0.25% respectively. Because FDE has a higher organic nitrogen (N) content than urea, and because it is a diluted mixture of urine and dung, the mean FDE EF1 is expected to be less than 1%. With a recent increase in research trials measuring EF1 for FDE and urea, the objective of this study was to refine New Zealand-specific EF1 values for these N sources. We analysed urea fertiliser and FDE N2O emission data from 45 EF1 field trials conducted in New Zealand. This meta-analysis yielded a combined (urea and FDE) EF1 mean of 0.46% (95% confidence interval of 0.07% and 0.90%), with EF1 means for urea and FDE of 0.59% and 0.25%, respectively. There was no statistical difference between urea fertiliser and FDE EF1 values. However, we recommend separate country-specific EF1 means of 0.6 and 0.3% for urea fertiliser and FDE, respectively, for New Zealand’s agricultural soils N2O emissions inventory due to the different origin and characteristics of these N sources.

There is currently a limited number of New Zealand studies quantifying nitrous oxide (N 2 O) emission factors (EF 1 , N 2 O emissions as a percentage of N applied) for farm dairy effluent (FDE) and urea fertiliser. Therefore, two experiments were conducted in four regions of New Zealand to determine EF 1 for FDE and urea fertiliser applied to pastures with contrasting soils and climatic conditions. Experiment 1 included urease and nitrification inhibitors to determine their effect on EF 1 . Urea treatments included (i) standard urea; (ii) urea amended with the nitrification inhibitor dicyandiamide (DCD) at 0.02 kg DCD kg −1 nitrogen (N) and (iii) urea amended with the urease inhibitor N -( n -butyl) thiophosphoric triamide ( n BTPT) at 250 mg n BTPT kg −1 urea, while FDE was applied with or without DCD, at 10 kg DCD ha −1 . Experiment 2 focused solely on FDE, which was applied to pastures that had either never received FDE or had a history of repeated application of FDE over several years. Urea fertiliser produced a large variation in EF 1 values, ranging from 0.03% to 1.52%. Application of FDE resulted in EF 1 ranging from 0.06% to 0.94% across both experiments. The urease and nitrification inhibitors had little or no effect on reducing EF 1 from urea fertiliser and FDE application. The history of repeated applications of FDE to pasture also had no effect on EF 1 .

Urine patches represent hot-spots of nitrogen (N) loss in dairy-grazed soils. Targeted application of urease and nitrification inhibitors that slow down certain N transformations in the urine patches is a potential method to reduce N losses. However, for optimum effectiveness the inhibitors need to be in close physical contact with the urine in the soil under urine patches. In practice, there will always be some time delay between urine deposition and application of inhibitors. It is therefore important to understand how the urine is transported in the soil following deposition. In this study, we developed an empirical model of urine patch area from thermal images of urine patches applied on two different soil types, at two different initial moisture contents, and with three different applied urine volumes. Spatial measurements using Spikey®-R (a mobile device that measures soil surface layer electrical conductivity) were used to test the model. A linear regression model of the ratio (urine volume)/(patch area) against the soil air-filled pore space explained 45 % of the variation in the ratio and had a Nash-Sutcliffe efficiency of +0.74 in predicting the mean patch area. This regression model was then used to define the boundary conditions for HYDRUS2D/3D simulations of urine movement through the soil after application. These simulations reasonably predicted the amount of urine-N in the top 50 and 100 mm of the soil 4 h after application (model efficiencies +0.38 and +0.42, respectively), but the model efficiencies were only −0.18 and +0.14 after 24 h. The measurements also had a high degree of spatial variability. After 24 h 44–78 % of the urine-N measured in the profile was within 50 mm of the surface. This represents a limit on the proportion of urine-N that could be physically intercepted by a post-grazing inhibitor application.

Nearly one-half of New Zealand’s ruminant livestock graze on hill country pastures where spatial differences in soil conditions are highly variable and excretal deposition is influenced by pasture production, animal grazing and resting behaviour that impact the nitrous oxide (N2O) emission factor from excreta (EF3). New Zealand currently uses country-specific EF3 values for urine and dung of 0.01 and 0.0025, respectively, to estimate direct N2O emissions from excreta. These values have largely been developed from trials on flat pastoral land. The use of the same EF3 for hill pasture with medium and steep slopes has been recognised as a possible source of overestimation of N2O emissions in New Zealand. The objectives of this study were to develop and describe an approach that takes into account the effects of slope in estimating hill country N2O emissions from the dung and urine of ruminant animals (sheep, beef cattle, and deer) across different slope classes, and then compare these estimates with current New Zealand inventory estimates. We use New Zealand as a case study to determine the direct N2O emissions between 1990 and 2012 from sheep, beef cattle and deer excreta using updated estimates of EF3 for sloping land, the area of land in different slope classes by region and farm type, and a nutrient transfer model to allocate excretal-N to the different slope classes, and compare the changes between these hill pastures-specific and current inventory estimates. Our findings are significant – the proposed new methodology using New Zealand specific EFs calculated from a national series of hill country experiments resulted in 52% lower N2O estimates relative to using current inventory emission factors, for the period between 1990 and 2012 and reduces New Zealand’s total national agricultural N2O greenhouse inventory estimates by 16%. The improved methodology is transparent, and complete, and has improved accuracy of emission estimates. On this basis, the improved methodology of estimating N2O emission is recommended for adoption where hill land grasslands are grazed by sheep, beef cattle and deer.

Nitrous oxide (N2O) emissions exhibit a high degree of spatial variability. Within a grazed pasture the uneven deposition of urine patches is one of the major sources of spatial variability in soil attributes and environmental conditions. Understanding the spatial variability of N2O emissions is necessary to estimate the size of the sampling errors using a given number of static chambers. In this study we measured N2O emissions for three weeks following a grazing event using 100 chambers. These chambers were divided into 4 blocks of 25 chambers arranged in a 5 m × 5 m grid so the within-block and between block variability could be compared. A known amount of urine was applied to 20% of the chambers. The behaviour of the sample mean using different numbers of chambers was investigated by randomly sub-sampling the chamber measurements from the 80 chambers to which urine was not applied. A cluster analysis based on final soil NH4+, NO3− and cumulative N2O emissions correctly identified 90% of the known urine patches. As expected the presence or absence of urine patches was one source of differences in emissions. However, not all plots responded equally to urine application and the difference in response seemed to be regulated by soil moisture. The low emitting plots corresponded to very high moisture contents resulting in low nitrification rates supported by low measured soil NO3−, but high NH4+ in these chambers. However, a high degree of variability within a treatment and plot has not been accounted for in this study. The distribution of the sample mean remained skewed even up to 40 chambers per sample. However, the standard deviation and the 95% confidence interval reduced with increasing numbers of chambers. For random sampling with 16 chambers there was a 95% chance that the sample mean would be within −62% to 109% of the true mean. Stratifying the sampling, either by plot, urine patch/non-urine patch, or both factors combined reduced the skewness and narrowed the 95% confidence interval of the mean. The greatest improvement was seen with the combined plot/urine stratification. Stratifying by urine/non-urine patch produced a greater improvement than stratifying by plot. Therefore if it is possible to identify either urine patches or regions of high N2O production potential accurately then sampling errors could be reduced using a stratified sampling scheme. However, care would be needed to ensure that systematic errors were not introduced.

Sheep and beef cattle grazed hill land represents a potentially large source of nitrous oxide (N2O) emissions globally. However, N2O emissions and associated emission factors for the dominant nitrogen (N) source of excreta N (EF3) are thought to be highly variable due to spatial differences in soil conditions across hill land units (HLUs; defined according to slope, aspect and soil type). Variability is also determined by animal grazing and resting behaviour affecting excretal-N deposition. Knowledge of spatially different EF3 values could be used to improve estimates of N2O emissions from grazed hill land. This paper presents N2O emission factors for sheep urine (SU) and dung (SD) and for beef cattle dung (BD) determined in four regions in New Zealand (NZ) (Waikato, Southern Hawkes Bay, Manawatu and Otago). Urine (spring 2009) or urine and dung (autumn 2011) was applied to low (

The transition of land between forest and grassland has important implications for greenhouse gas emissions and removals. In this paper, we use New Zealand as a case study to comprehensively assess, compare and quantify the net climate change impact of shifting land use between temperate forest and grassland. Forests store large amounts of carbon in their biomass, whereas grasslands contain relatively little biomass carbon. These biomass changes tend to dominate the carbon balance under land-use change. Soil carbon stocks usually do not change much after deforestation unless subsequent erosion occurs, but some soil carbon is often lost when grasslands are reforested with exotic plantations. Forest soils usually release little nitrous oxide or methane and can even oxidise small amounts of methane. Grasslands, on the other hand, can release a large amount of nitrous oxide, which may be further increased with fertilisation, and is higher for cattle- than sheep-grazed systems. Grazing animals increase emissions because the concentrated forms of nitrogen in their excreta allow it to escape from the system. Ruminant animals can also emit large amounts of methane. Land cover change in addition has direct radiative effects through the amount of solar radiation that is either absorbed by vegetated surfaces or reflected back into space. As forests typically absorb more radiation than grasslands, this slightly negates the greenhouse consequences of changes in carbon storage, and methane and nitrous oxide emissions under land-use change.

New Zealand's grazed pastures receive large quantities of nitrogen (N) inputs from animal excreta and chemical fertilisers. While N promotes pasture growth, surplus N can cause environmental problems by leaching into waterways or by nitrifying and denitrifying to form the greenhouse gas, nitrous oxide (N2O). Various approaches have been attempted to mitigate the economic and environmental impacts of N losses. One such approach is the use of nitrification inhibitors (NIs). The value of these inhibitors in mitigating N losses in grazed pasture partly depends on their rate of biodegradation and persistence in soils. A simplified model of nitrification inhibition was used with the process-based NZ-DNDC model to investigate the effect of NI dicyandiamide (DCD) on transformations of N to nitrate (NO3−) and subsequent reduction to N2O in a grazed pasture system receiving cow urine at application rate of 600 kg N/ha. The modelled N2O emissions with and without DCD application were comparable to the field measurements on Tokomaru silt loam soil, assuming that the effect of the DCD was to decrease the nitrification rate by about 70%. An attempt was also made to simulate the effect of the biological degradation of DCD by exponentially decreasing the inhibitor effectiveness with time. However, this did not improve the fit of the modelled N2O emissions over the 50-day measurement period. Further refinements including the effects of soil type, and changes in NI concentration throughout the soil profile over time and its subsequent effect on N transformations will be developed as more experimental data become available.

Nitrous oxide (N 2 O) emissions from grazed pastures represent a significant source of atmospheric N 2 O. With an improved understanding and quantification of N sources, transformation processes, and soil and climatic conditions controlling N 2 O emissions, a number of management options can be identified to reduce N 2 O emissions from grazed pasture systems. The mitigation options discussed in this paper are: optimum soil management, limiting the amount of N fertiliser or effluent applied when soil is wet; lowering the amount of N excreted in animal urine by using low-N feed supplements as an alternative to fertiliser N-boosted grass; plant and animal selection for increased N use efficiency, using N process inhibitors that inhibit the conversion of urea to ammonium and ammonium to nitrate in soil; use of stand-off/feed pads or housing systems during high risk periods of N loss. The use of single or multiple mitigation options always needs to be evaluated in a whole farm system context and account for total greenhouse gas emissions including methane and carbon dioxide. They should focus on ensuring overall efficiency gains through decreasing N losses per unit of animal production and achieving a tighter N cycle. Whole-system life-cycle-based environmental analysis should also be conducted to assess overall environmental emissions associated the N 2 O mitigation options.

The high temporal and spatial variability of agricultural nitrous oxide (N2O) emissions from soil makes their measurement at regional or national scales impractical. Accordingly, robust process-based models are needed. Several detailed biochemical process-based models of N-gas emissions have been developed in recent years to provide site-specific and regional scale estimates of N2O emissions. Among these DNDC (Denitrification–Decomposition) simulates carbon and nitrogen biogeochemical cycles occurring in agricultural systems. Originally developed as a tool to predict nitrous oxide (N2O) emissions from cropping systems, DNDC has since been expanded to include other ecosystems such as rice paddies, grazed pastures, forests, and wetlands, and the model accounts for land-use and land-management effects on N2O emissions. As a process-based model, DNDC is capable of predicting the soil fluxes of all three terrestrial greenhouse gases: N2O, carbon dioxide (CO2), and methane (CH4), as well as other important environmental and economic indicators such as crop production, ammonia (NH3) volatilisation and nitrate (NO3−) leaching. The DNDC model has been widely used internationally, including in the EU nitrogen biogeochemistry projects NOFRETETE and NitroEurope. This paper brings together the research undertaken on a wide range of land-use and land-management systems to improve and modify, test and verify, and apply the DNDC model to estimate soil–atmosphere exchange of N2O, CH4 and CO2 from these systems.

Sheep grazing, one of the major land-uses in New Zealand occupies 7.1 million hectares and provides forage for about 40 million sheep. Spatially and temporally explicit data on nitrous oxide (N2O) and methane (CH4) fluxes from soils under this land use are needed at farm-scale to better estimate regional and national greenhouse gas inventories. In this study, we measured N2O and CH4 fluxes at the soil surface of a sheep-grazed pasture over a 20-month period, to assess the influence of soil moisture, temperature and seasonal variations in the emissions of N2O and CH4, and to calculate an N2O emission factor. The farm-scale N2O emissions were also simulated using a process-based NZ-DNDC model, and the model was tested against measurements of CH4. Measured annual N2O emissions from this pasture site are estimated to be 3.7 ± 2.2 kg N2O-N ha−1 year−1. The mean of daily N2O emission measurements (7.4 g N2O-N ha−1 day−1) for this sheep-grazed pasture was higher than the mean of daily emission measurements from ungrazed control site (3.4 g N2O-N ha−1 day−1) but significantly lower than reported value of 32.0 g N2O-N ha−1 day−1for pastures grazed by dairy cows on the same soil type at an adjacent farm. The emission factor (EF), i.e. amount of N2O-N emitted expressed as a percentage of excretal and fertiliser N input for this site, is 0.99, which is essentially the same as the New Zealand specific N2O emission factor of 1.0 for excretal N. The sheep-grazed pasture acted as a CH4 source and sink but was an overall annual CH4 sink (0.64 ± 0.19 kg CH4-C ha−1). Methane consumption was highest in the summer and lowest during the wetter, colder winter months. Thus mitigation strategies for reducing anaerobic N2O emissions will also favour greater CH4 oxidation at the soil surface. NZ-DNDC model simulated effectively general pulses and trends in both N2O and CH4 fluxes.

In situ farm-scale measurements are a prerequisite for improving the accuracy of greenhouse gas inventories, and for developing and modifying the modelling approaches to quantify emissions. We describe here the changes made to the process-based model NZ-DNDC to allow us to simulate emissions of nitrous oxide (N2O) from typical New Zealand grazed grassland soils, and subsequent improvements to account for periodic changes in pasture growth, N input from animals, and water balance/soil moisture status. In grazed pastures, N2O fluxes varied widely both spatially due to uneven excretal N inputs, and seasonally due to climatic conditions. The model was validated against field measurements from two dairy pastures with contrasting soils and from a sheep pasture. The model simulated effectively most of the soil water-filled pore-space (WFPS) and the general pulses and trends in N2O emission from both the sheep- and dairy-grazed pastures, and also captured the observed effects of excretal and fertiliser N inputs. It also fairly reproduced the real variability in underlying processes regulating N2O emissions. A series of sensitivity tests conducted on NZ-DNDC showed the model predicted changes in pasture production and N2O emissions with changes in climate, soil properties, fertiliser management and grazing regimes. Pasture production was more sensitive to rainfall, temperature and initial soil carbon levels than to fertiliser additions, and stocking rate while N2O emissions were strongly sensitive to rainfall, quantity and frequency of N inputs through both fertiliser and increased stocking rate, and initial soil carbon levels.

Effects of land-use management on agricultural sustainability and greenhouse gas emissions are major issues for researchers, regional councils and farmers in New Zealand. This study was undertaken to investigate the environmental impact of land-use management on field-CO2 emissions in Ohakea silt loam soil (Typic andoaqualf) that had been converted from permanent pasture to forage cropping for 2 years. The treatments were plow tillage (PT) and no-tillage (NT), with summer fodder maize (Zea mays L.) double-cropped in rotation with winter oat (Avena sativa L.); permanent pasture (PP) was used as control. Field-CO2 emissions measured every 3–4 weeks during 12 months, were significantly highest in the PP. Overall, results indicate that reduction in tillage had only a minor effect on field-CO2 emission throughout the crop growth period. During one year CO2 emissions ranged from 55–132 kg C ha−1 per day in the PP treatment, 43–91 kg C ha−1 per day in the NT treatment and 36–81 kg C ha−1 per day in the PT treatment. Daily field-CO2 emissions measured within a few days after cultivation were significantly highest in the PP treatment and were in the order of PP > NT > PT. Conversion of PP to NT cropping had no effect on surface organic C levels, but conversion to cropping with tillage markedly reduced C levels.

A nutrient-transfer model was developed using a mass balance approach to explain the variations in the amounts of soil phosphorus (P) and sulphur (S) found across a range of slopes and aspects in four 10-ha farmlets located in summer-moist hill-country pastures in the southern North Island of New Zealand. The farmlets were continuously grazed by sheep for a period of 12 years, during which time they received a total of 115, 187, 387, 603 and 126, 201, 405, 630 kg ha −1 of P and S, respectively, as single superphosphate (SSP). The model takes account of the effect of topography and local climate on stock behaviour, herbage accumulation and its nutrient content, pasture utilization and the uneven nutrient return through excreta. The developed P model was reliable. The predictions of the transfer model explained 95% of variation in soil P amounts (0–150 mm depth) between farmlets ( n =4), 89% of variation between slope units ( n =12) and 79% between slope-aspect units ( n =36) across all farmlets. When S input parameters were substituted for P parameters, the model was unable to predict the measured soil S levels in any of the four farmlets. Unlike P, S is subject to losses by leaching from these soils. The differences between predicted and measured soil S amounts were used to estimate S leaching losses and pinpoint areas from where they occurred. The concept of modelling the fate of P in P and S fertilized systems and then using the calculated nutrient-transfer functions of the model to evaluate the fate of S provides invaluable information for developing strategies for improving the efficiency of S fertilizer use.