Carolyn Hedley

Modelling nitrous oxide emissions from dairy-grazed pastures

Soil N2O emissions were measured during four seasons from two highly productive grass-clover dairy pastures to assess the influences of soil moisture, temperature, availability of N (NH4+ and NO3–) and soluble C on N2O emissions, and to use the emission data to validate and refine a simulation model (DNDC). The soils at these pasture sites (Karapoti fine sandy loam, and Tokomaru silt loam) differed in texture and drainage characteristics. Emission peaks for N2O coincided with rainfall events and high soil moisture content. Large inherent variations in N2O fluxes were observed throughout the year in both the ungrazed (control) and grazed pastures. Fluxes averaged 4.3 and 5.0 g N2O/ha/day for the two ungrazed sites. The N2O fluxes from the grazed sites were much higher than for the ungrazed sites, averaging 26.4 g N2O/ha/day for the fine sandy loam soil, and 32.0 g N2O/ha/day for the silt loam soil. Our results showed that excretal and fertiliser-N input, and water-filled pore space (WFPS) were the variables that most strongly regulated N2O fluxes. The DNDC model was modified to include the effects of day length on pasture growth, and of excretal-N inputs from grazing animals; the value of the WFPS threshold was also modified. The modified model ‘NZ-DNDC’ simulated effectively most of the WFPS and N2O emission pulses and trends from both the ungrazed and grazed pastures. The modified model fairly reproduced the real variability in underlying processes regulating N2O emissions and could be suitable for simulating N2O emissions from a range of New Zealand grazed pastures. The NZ-DNDC estimates of total yearly emissions of N2O from the grazed and ungrazed sites of both farms were within the uncertainty range of the measured emissions. The measured emissions changed with changes in soil moisture resulting from rainfall and were about 20% higher in the poorly drained silt loam soil than in the well-drained sandy loam soil. The model accounts for these climatic variations in rainfall, and was also able to pick up differences in emissions resulting from differences in soil texture.

A review of emissions of methane, ammonia, and nitrous oxide from animal excreta deposition and farm effluent application in grazed pastures

Abstract The agricultural sector in New Zealand is the major contributor to ammonia (NH3), nitrous oxide (N2O), and methane (CH4) emissions to the atmosphere. These gases cause environmental degradation through their effects on soil acidification, eutrophication, and stratospheric ozone depletion. With its strong agricultural base and relatively low level of heavy industrial activity, New Zealand is unique in having a greenhouse‐gas‐emissions inventory dominated by the agricultural trace gases, CH4 and N2O, instead of carbon dioxide which dominates in most other countries. About 96% of this anthropogenic CH4 is emitted by ruminant animals as a byproduct during the process of enteric fermentation. Methane is also produced by anaerobic fermentation of animal manure and many other organic substrates. In pastoral soils, NH3 and N2O gases are generated from N originating from dung, urine, biologically fixed N2, and fertiliser. The amount of these gaseous emissions depends on complex interactions between soil properties, climatic factors, and agricultural practices. In this review paper, the animal‐excretal inputs and farm‐effluent applications to New Zealand pastures are quantified. Data from overseas and New Zealand studies on CH4, NH3, and N2O emissions from excretal deposition and animal effluents, and the factors affecting these emissions, are synthesised with an aim to improve the New Zealand estimates of emissions from these sources. The practical implications of these emissions are described in relation to environmental impacts and management strategies for reducing these emissions.

14C-labelled glucose turnover in New Zealand soils

The influence of soil mineralogy, as well as texture, on organic-C turnover was determined with 14C-labelled glucose. Samples of 16 soils from major mineralogical classes of New Zealand pastures and providing a range of organic C, clay contents and surface area, were incubated with 14C-labelled glucose for 35 d. The amounts of 12CO2 and 14CO2 evolved during incubation were monitored and the residual 14C concentrations determined. Periodically, the samples were removed and microbial biomass 12C and 14C determined using the fumigation-extraction technique. System mean residence times (MRTs) were obtained by three independent methods: (i) a compartmental model using 14C microbial biomass data, (ii) a non-compartmental model using 14C microbial biomass data and (iii) a biexponential equation as an empirical equation from residual 14C data. The effect of soil characteristics on MRTs was compared. The 14CO2 respired, after 35 d incubation, accounted for 51 to 66% of the glucose 14C input to these soils. The soils differed significantly in their amounts of 14CO2 evolution and in the proportions of labelled 14C in the biomass. The extent of mineralization of 14C-labelled glucose was influenced by soil clay content and clay surface area. Soils of low clay content (3–12%) had high biophysical quotients (respired: residual 14C); the highest (1.93) was in the soil with least clay (3%) and lowest mineral surface area, suggesting that clay is effective in C stabilization immediately after substrate assimilation. A biexponential model was found to be suitable for describing changes in the residual 14C and microbial biomass 14C during the 35 d glucose decomposition for most of the soils. MRTs for microbial biomass 14C were correlated with clay content (P<0.001), surface area estimated by para-nitrophenol (pNP) (P<0.003) and pH (P<0.01). Our results also showed that the MRTs of microbially assimilated 14C are similar despite differences in the chemical nature of the applied 14C-labelled substrate. However, the MRT for humus 14C differed with the chemical nature of the applied substrate. Clay and surface area played a major role in controlling the decomposition of added substrate through the stabilization and protection of the microbial biomass.

Rapid identification of soil textural and management zones using electromagnetic induction sensing of soils

Three surveys of a pastoral–cropping farming system were carried out over a period of 1 year, using an electromagnetic sensor and real-time-kinematic (RTK)-GPS. The maps produced delineated areas of different apparent soil electrical conductivity (ECa). These delineated areas were compared with soil units of a conventional soil map and results showed the ECa map related well to soil-particle-size classes. In addition ECa could be used to predict groupings of soil phases accurately within one soil type. Soil coring to depths of 1 m, to determine soil physical and chemical properties, showed ECa values were moderately well correlated (R2 = 0.72) to soil clay percentage, weighted for the soil profile. Soil fertility indicators, Olsen P (R2 = 0.61), cation exchange capacity (R2 = 0.59), and exchangeable magnesium (R2 = 0.76) also related well. The linear regression (R2 = 0.76) of ECa with exchangeable magnesium is thought to reflect the dominant clay mineralogy of the study area, i.e. chlorites weathering to illites and releasing magnesium to the soil solution. Discriminant statistical analysis of results showed point ECa values could be used to predict 2 major groupings of the mapped soil phases with 100% accuracy. More precise prediction of these mapped soil units is constrained by localised management effects. Elevated ECa values occur at areas of soil compaction, which have been deduced from measurements of soil strength, aggregate size distribution and visual soil assessment.

Soil microbial biomass, metabolic quotient, and carbon and nitrogen mineralisation in 25-year-old Pinus radiata agroforestry regimes

To understand the effects of agroforestry on soil biological processes we assessed the conditions in Pinus radiata plantations of 50, 100, 200, and 400 stems/ha after 25 years of growth, and in a grassland. Agroforestry resulted in a 15–25% decline in soil organic C and N compared with grassland, and had a significant negative influence on soil microbial biomass. There was less microbial C and N in soils under 50–400 stems/ha of P. radiata than in soils under grassland (0 stems/ha). Soil carbon decomposition and microbial activity were measured by trapping the carbon dioxide produced by incubating soils over a 60-week period. The results showed that soil C decomposition rates were ~1.5 times as much (c. 15 mg CO2-C/kg soil) in soil from grassland as in that from plots with 50 or100 stems/ha (c. 10 mg CO2-C/kg soil), and were further reduced to one half (c. 5.5 mg CO2-C/kg soil) in the plots with 200 or 400 stems/ha. The soils under P. radiata gave off less carbon dioxide per unit of biomass (the metabolic quotient) than soils under grassland. These shifts in microbial biomass and its metabolic quotients appear to be associated with differences in the quantity and ‘quality’ of inputs and soil organic matter decomposition rates, and to reflect the land use change from grassland to forest. Given the general ability of soil microbial biomass to recolonise depopulated areas after tree harvest, we see no problem in restoring populations of these soil organisms vital in controlling nutrient cycling after tree felling, provided adequate adjustments to soil pH are made.

Procedure for Fast Simultaneous Analysis of the Greenhouse Gases: Methane, Carbon Dioxide, and Nitrous Oxide in Air Samples

Abstract A comprehensive procedure has been developed and is reported here for (i) sampling air above a soil surface and (ii) analyzing it for the three greenhouse gases: methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O). The automated gas‐chromatography procedure simultaneously analyzes for CH4, CO2, and N2O and has a precision of 0.87, 2.17, and 0.74%, respectively. Method-detection limits are 0.04 ppm for CH4, 25.5 ppm for CO2, and 7.4 ppb for N2O. The procedure is used to monitor greenhouse gas exchanges at soil surfaces; its precision and automated ability to analyze large sample numbers produces quality data available for upscaling and modeling for inventory purposes; and it is used for developing a process‐based understanding of the mechanisms controlling greenhouse gas fluxes at the soil surface, which can then be applied to develop mitigation strategies.

The role of precision agriculture for improved nutrient management on farms.

Precision agriculture uses proximal and remote sensor surveys to delineate and monitor within-field variations in soil and crop attributes, guiding variable rate control of inputs, so that in-season management can be responsive, e.g. matching strategic nitrogen fertiliser application to site-specific field conditions. It has the potential to improve production and nutrient use efficiency, ensuring that nutrients do not leach from or accumulate in excessive concentrations in parts of the field, which creates environmental problems. The discipline emerged in the 1980s with the advent of affordable geographic positioning systems (GPS), and has further developed with access to an array of affordable soil and crop sensors, improved computer power and software, and equipment with precision application control, e.g. variable rate fertiliser and irrigation systems. Precision agriculture focusses on improving nutrient use efficiency at the appropriate scale requiring (1) appropriate decision support systems (e.g. digital prescription maps), and (2) equipment capable of varying application at these different scales, e.g. the footprint of a one-irrigation sprinkler or a fertiliser top-dressing aircraft. This article reviews the rapid development of this discipline, and uses New Zealand as a case study example, as it is a country where agriculture drives economic growth. Here, the high yield potentials on often young, variable soils provide opportunities for effective financial return from investment in these new technologies.

Surface area of soils of contrasting mineralogies using para-nitrophenol adsorption and its relation to air-dry moisture content of soils

The specific surface area (SSA) of a range of soils has been measured by adsorption of para-nitrophenol (pNP). These surface soils are representative of the major soil groups of New Zealand, varying in mineralogy, clay and organic carbon contents, and cation exchange capacity (CEC). All of the soils are under pastures of introduced grasses and legumes that have been regularly fertilised and grazed. The SSAs measured by pNP are compared with the values calculated from the clay content, clay mineral composition, and organic carbon content of the soils. Measured SSAs are also related to the air-dry soil moisture contents. There is a good 1:1 relation between measured and calculated SSAs. This correspondence improves when allophanic and smectitic soils are omitted from the relation. The SSAs measured by pNP are also well correlated with the air-dry moisture content and CEC of the soils. When allophanic soils are excluded, a highly significant correlation (r = 0.894; P < 0.001) is obtained between pNP surface area and moisture content of the air-dry soils. When the same relation is applied to an independent set of soils, 89% of the variations in SSA can be accounted for. We suggest that the SSAs of many soils can be reasonably deduced from their air-dry moisture content.

Key Performance Indicators for Simulated Variable-Rate Irrigation of Variable Soils in Humid Regions

Decision support tools for precise irrigation scheduling are required to improve the efficiency of irrigation water use globally. This article presents a method for mapping soil variability and relating it to soil hydraulic properties so that soil management zones for variable-rate irrigation can be defined. A soil-water balance is used to schedule hypothetical irrigation events based on one blanket application of water to eliminate plant stress (uniform rate irrigation, or URI) and compares this to variable-rate irrigation (VRI), where irrigation is tailored to specific soil zone available water-holding capacity (TAWC) values. The key performance indicators, i.e., irrigation water use, drainage water loss, nitrogen leaching, energy use, irrigation water use efficiency (IWUE), and virtual water content, are used to compare URI and VRI at three contrasting sites using four years of climate data for a dairy pasture and maize crop and two years of climate data for a potato crop. Our research found that VRI saved 9% to 19% irrigation water, with accompanying energy saving. Loss of water by drainage, during the period of irrigation, was also reduced by 25% to 45% using VRI, which reduced the risk of nitrogen leaching. Virtual water content of these three primary products further illustrates potential benefits of VRI and shows that virtual water content of potato production used the least water per unit of dry matter production.

Soil C and N sequestration and fertility development under land recently converted from plantation forest to pastoral farming

Abstract Soil organic matter accumulation and concomitant fertility changes in soils recently converted from plantation forest to pastoral agriculture in the Taupo‐Rotorua Volcanic Zone have been observed, with a probable soil C sequestration rate of 6.1 t ha‐1 year‐1, and a soil N sequestration rate of 0.451 ha‐1 year‐1, to 150 mm soil depth, for the first 5 years after conversion attwo of three selected farms. Rapid increases in Olsen P were observed, with soils reaching their optimum agronomic range within 3–5 years after conversion, at two of three farms. A decreasing C:N ratio with time since conversion reflects improved fertility status, and implies that in initial years of pasture establishment, N losses are reduced due to its immobilisation into soil organic matter. These research findings suggest that land‐use change from plantation forest to pastoral farm, with inputs of N, P, K and S to soils, allows significant soil C and N sequestration for at least 5 years after conversion. This rate of C sequestration could be used as an offset for forest C sink loss in future emissions trading systems. Further research is required to at least 0.3 m depth to confirm this preliminary study.