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No description available.

The objectives of this research were to develop and evaluate a field method for in situ measurement of soil properties using visible near-infrared reflectance spectroscopy (Vis-NIRS). A probe with an independent light source for acquiring soil reflectance spectra from soil cores was developed around an existing portable field spectrometer (ASD FieldSpecPro, Boulder, CO, USA; 350-2500 nm). Initial experiments tested the ability of the acquired spectra to predict plant root density, an important property in soil carbon dynamics. Reflectance spectra were acquired from soil containing ryegrass roots (Lolium multiflorum) grown in Allophanic and Fluvial Recent soils in a glasshouse pot trial. Differences in root density were created by differential nitrogen and phosphorus fertilization. Partial least squares regression (PLSR) was used to calibrate spectral data (pre-processed by smoothing and transforming spectra to the first derivative) against laboratory-measured root density data (wet-sieve technique). The calibration model successfully predicted root densities (r2 = 0.85, RPD = 2.63, RMSECV = 0.47 mg cm-3) observed in the pots to a moderate level of accuracy. This soil reflectance probe was then tested using a soil coring system to acquire reflectance spectra from two soils under pasture (0-60 mm soil depths) that had contrasting root densities. The PLSR calibration models for predicting root density were more accurate when soil samples from the two soils were separated rather than grouped. A more accurate prediction was found in Allophanic soils (r2 = 0.83, RPD = 2.44, RMSECV = 1.96 mg g-1) than in Fluvial Recent soils (r2 = 0.75, RPD = 1.98, RMSECV = 5.11 mg g-1). The Vis-NIRS technique was then modified slightly to work on a soil corer that could be used to measure root contents from deeper soil profiles (15- 600 mm depth) in arable land (90-day-old maize crop grown in Fluvial Recent soils). PLSR calibration models were constructed to predict the full range of maize root densities (r2 = 0.83, RPD = 2.42, RMSECV = 1.21 mg cm-3) and also soil carbon (C) and nitrogen (N) concentrations that had been determined in the laboratory (LECO FP- 2000 CNS Analyser; Leco Corp., St Joseph, MI, USA). Further studies concentrated on improving the Vis-NIRS technique for prediction of total C and N concentrations in differing soil types within different soil orders in the field. The soil coring method used in the maize studies was evaluated in permanent and recent pastoral soils (Pumice, Allophanic and Tephric Recent in the Taupo-Rotorua Volcanic Zone, North Island) with a wide range of soil organic matter contents resulting from different times (1-5 years) since conversion from forest soils. Without any sample preparation, other than the soil surface left after coring, it was possible to predict soil C and N concentrations with moderate success (C prediction r2 = 0.75, RMSEP = 1.23%, RPD = 1.97; N prediction r2 = 0.80, RMSEP = 0.10%, RPD = 2.15) using a technique of acquiring soil reflectance spectra from the horizontal cross-section of a soil core (H method). The soil probe was then modified to acquire spectra from the curved vertical wall of a soil core (V method), allowing the spectrometer’s field of view to increase to record the reflectance features of the whole soil sample taken for laboratory analysis. Improved predictions of soil C and N concentrations were achieved with the V method of spectral acquisition (C prediction r2 = 0.97, RMSECV = 0.21%, RPD = 5.80; N prediction r2 = 0.96, RMSECV = 0.02%, RPD = 5.17) compared to the H method (C prediction r2 = 0.95, RMSECV = 0.27%, RPD = 4.45; N prediction r2 = 0.94, RMSECV = 0.03%, RPD = 4.25). The V method was tested for temporal robustness by assessing its ability to predict soil C and N concentrations of Fluvial Recent soils under permanent pasture in different seasons. When principal component analysis (PCA) was used to ensure that the spectral dimensions (which were responsive to water content) of the data set used for developing the PLSR calibration model embraced those of the “unknown” soil samples, it was possible to predict soil C and N concentrations in “unknown” samples of widely different water contents (in May and November), with a high level of accuracy (C prediction r2 = 0.97, RMSEP = 0.36%, RPD = 3.43; N prediction r2 = 0.95, RMSEP = 0.03%, RPD = 3.44). This study indicates that Vis-NIRS has considerable potential for rapid in situ assessment of soil C, N and root density. The results demonstrate that field root densities in pastoral and arable soil can be predicted independently from total soil C, which will allow researchers to predict C sequestration from root production. The recommended “V” technique can be used to assess spatial and temporal variability of soil carbon and nitrogen within soil profiles and across the landscape. It can also be used to assess the rate of C sequestration and organic matter synthesis via root density prediction. It reduces the time, labour and cost of conventional soil analysis and root density measurement.

The objectives of this research were to develop and evaluate a field method for in situ measurement of soil properties using visible near-infrared reflectance spectroscopy (Vis-NIRS). A probe with an independent light source for acquiring soil reflectance spectra from soil cores was developed around an existing portable field spectrometer (ASD FieldSpecPro, Boulder, CO, USA; 350-2500 nm). Initial experiments tested the ability of the acquired spectra to predict plant root density, an important property in soil carbon dynamics. Reflectance spectra were acquired from soil containing ryegrass roots (Lolium multiflorum) grown in Allophanic and Fluvial Recent soils in a glasshouse pot trial. Differences in root density were created by differential nitrogen and phosphorus fertilization. Partial least squares regression (PLSR) was used to calibrate spectral data (pre-processed by smoothing and transforming spectra to the first derivative) against laboratory-measured root density data (wet-sieve technique). The calibration model successfully predicted root densities (r2 = 0.85, RPD = 2.63, RMSECV = 0.47 mg cm-3) observed in the pots to a moderate level of accuracy. This soil reflectance probe was then tested using a soil coring system to acquire reflectance spectra from two soils under pasture (0-60 mm soil depths) that had contrasting root densities. The PLSR calibration models for predicting root density were more accurate when soil samples from the two soils were separated rather than grouped. A more accurate prediction was found in Allophanic soils (r2 = 0.83, RPD = 2.44, RMSECV = 1.96 mg g-1) than in Fluvial Recent soils (r2 = 0.75, RPD = 1.98, RMSECV = 5.11 mg g-1). The Vis-NIRS technique was then modified slightly to work on a soil corer that could be used to measure root contents from deeper soil profiles (15- 600 mm depth) in arable land (90-day-old maize crop grown in Fluvial Recent soils). PLSR calibration models were constructed to predict the full range of maize root densities (r2 = 0.83, RPD = 2.42, RMSECV = 1.21 mg cm-3) and also soil carbon (C) and nitrogen (N) concentrations that had been determined in the laboratory (LECO FP- 2000 CNS Analyser; Leco Corp., St Joseph, MI, USA). Further studies concentrated on improving the Vis-NIRS technique for prediction of total C and N concentrations in differing soil types within different soil orders in the field. The soil coring method used in the maize studies was evaluated in permanent and recent pastoral soils (Pumice, Allophanic and Tephric Recent in the Taupo-Rotorua Volcanic Zone, North Island) with a wide range of soil organic matter contents resulting from different times (1-5 years) since conversion from forest soils. Without any sample preparation, other than the soil surface left after coring, it was possible to predict soil C and N concentrations with moderate success (C prediction r2 = 0.75, RMSEP = 1.23%, RPD = 1.97; N prediction r2 = 0.80, RMSEP = 0.10%, RPD = 2.15) using a technique of acquiring soil reflectance spectra from the horizontal cross-section of a soil core (H method). The soil probe was then modified to acquire spectra from the curved vertical wall of a soil core (V method), allowing the spectrometer’s field of view to increase to record the reflectance features of the whole soil sample taken for laboratory analysis. Improved predictions of soil C and N concentrations were achieved with the V method of spectral acquisition (C prediction r2 = 0.97, RMSECV = 0.21%, RPD = 5.80; N prediction r2 = 0.96, RMSECV = 0.02%, RPD = 5.17) compared to the H method (C prediction r2 = 0.95, RMSECV = 0.27%, RPD = 4.45; N prediction r2 = 0.94, RMSECV = 0.03%, RPD = 4.25). The V method was tested for temporal robustness by assessing its ability to predict soil C and N concentrations of Fluvial Recent soils under permanent pasture in different seasons. When principal component analysis (PCA) was used to ensure that the spectral dimensions (which were responsive to water content) of the data set used for developing the PLSR calibration model embraced those of the “unknown” soil samples, it was possible to predict soil C and N concentrations in “unknown” samples of widely different water contents (in May and November), with a high level of accuracy (C prediction r2 = 0.97, RMSEP = 0.36%, RPD = 3.43; N prediction r2 = 0.95, RMSEP = 0.03%, RPD = 3.44). This study indicates that Vis-NIRS has considerable potential for rapid in situ assessment of soil C, N and root density. The results demonstrate that field root densities in pastoral and arable soil can be predicted independently from total soil C, which will allow researchers to predict C sequestration from root production. The recommended “V” technique can be used to assess spatial and temporal variability of soil carbon and nitrogen within soil profiles and across the landscape. It can also be used to assess the rate of C sequestration and organic matter synthesis via root density prediction. It reduces the time, labour and cost of conventional soil analysis and root density measurement.

The objectives of this research were to develop and evaluate a field method for in situ measurement of soil properties using visible near-infrared reflectance spectroscopy (Vis-NIRS). A probe with an independent light source for acquiring soil reflectance spectra from soil cores was developed around an existing portable field spectrometer (ASD FieldSpecPro, Boulder, CO, USA; 350-2500 nm). Initial experiments tested the ability of the acquired spectra to predict plant root density, an important property in soil carbon dynamics. Reflectance spectra were acquired from soil containing ryegrass roots (Lolium multiflorum) grown in Allophanic and Fluvial Recent soils in a glasshouse pot trial. Differences in root density were created by differential nitrogen and phosphorus fertilization. Partial least squares regression (PLSR) was used to calibrate spectral data (pre-processed by smoothing and transforming spectra to the first derivative) against laboratory-measured root density data (wet-sieve technique). The calibration model successfully predicted root densities (r2 = 0.85, RPD = 2.63, RMSECV = 0.47 mg cm-3) observed in the pots to a moderate level of accuracy. This soil reflectance probe was then tested using a soil coring system to acquire reflectance spectra from two soils under pasture (0-60 mm soil depths) that had contrasting root densities. The PLSR calibration models for predicting root density were more accurate when soil samples from the two soils were separated rather than grouped. A more accurate prediction was found in Allophanic soils (r2 = 0.83, RPD = 2.44, RMSECV = 1.96 mg g-1) than in Fluvial Recent soils (r2 = 0.75, RPD = 1.98, RMSECV = 5.11 mg g-1). The Vis-NIRS technique was then modified slightly to work on a soil corer that could be used to measure root contents from deeper soil profiles (15- 600 mm depth) in arable land (90-day-old maize crop grown in Fluvial Recent soils). PLSR calibration models were constructed to predict the full range of maize root densities (r2 = 0.83, RPD = 2.42, RMSECV = 1.21 mg cm-3) and also soil carbon (C) and nitrogen (N) concentrations that had been determined in the laboratory (LECO FP- 2000 CNS Analyser; Leco Corp., St Joseph, MI, USA). Further studies concentrated on improving the Vis-NIRS technique for prediction of total C and N concentrations in differing soil types within different soil orders in the field. The soil coring method used in the maize studies was evaluated in permanent and recent pastoral soils (Pumice, Allophanic and Tephric Recent in the Taupo-Rotorua Volcanic Zone, North Island) with a wide range of soil organic matter contents resulting from different times (1-5 years) since conversion from forest soils. Without any sample preparation, other than the soil surface left after coring, it was possible to predict soil C and N concentrations with moderate success (C prediction r2 = 0.75, RMSEP = 1.23%, RPD = 1.97; N prediction r2 = 0.80, RMSEP = 0.10%, RPD = 2.15) using a technique of acquiring soil reflectance spectra from the horizontal cross-section of a soil core (H method). The soil probe was then modified to acquire spectra from the curved vertical wall of a soil core (V method), allowing the spectrometer’s field of view to increase to record the reflectance features of the whole soil sample taken for laboratory analysis. Improved predictions of soil C and N concentrations were achieved with the V method of spectral acquisition (C prediction r2 = 0.97, RMSECV = 0.21%, RPD = 5.80; N prediction r2 = 0.96, RMSECV = 0.02%, RPD = 5.17) compared to the H method (C prediction r2 = 0.95, RMSECV = 0.27%, RPD = 4.45; N prediction r2 = 0.94, RMSECV = 0.03%, RPD = 4.25). The V method was tested for temporal robustness by assessing its ability to predict soil C and N concentrations of Fluvial Recent soils under permanent pasture in different seasons. When principal component analysis (PCA) was used to ensure that the spectral dimensions (which were responsive to water content) of the data set used for developing the PLSR calibration model embraced those of the “unknown” soil samples, it was possible to predict soil C and N concentrations in “unknown” samples of widely different water contents (in May and November), with a high level of accuracy (C prediction r2 = 0.97, RMSEP = 0.36%, RPD = 3.43; N prediction r2 = 0.95, RMSEP = 0.03%, RPD = 3.44). This study indicates that Vis-NIRS has considerable potential for rapid in situ assessment of soil C, N and root density. The results demonstrate that field root densities in pastoral and arable soil can be predicted independently from total soil C, which will allow researchers to predict C sequestration from root production. The recommended “V” technique can be used to assess spatial and temporal variability of soil carbon and nitrogen within soil profiles and across the landscape. It can also be used to assess the rate of C sequestration and organic matter synthesis via root density prediction. It reduces the time, labour and cost of conventional soil analysis and root density measurement.

Land application of wastes has become increasingly popular, to promote nutrient recycling and environmental protection, with soil functioning as a partial barrier between wastes and groundwater. Dairy shed effluent (DSE), may contain a wide variety of pathogenic micro-organisms, including bacteria (e.g. Salmonella paratyphyi, Escherichia coli. and Campylobacter), protozoa and viruses. Groundwater pathogen contamination resulting from land-applied DSE is drawing more attention with the intensified development of the dairy farm industry in New Zealand. The purpose of this research was to investigate the fate and transport of bacterial indicator-faecal coliform (FC) from land-applied DSE under different irrigation practices via field lysimeter studies, using two water irrigation methods (flood and sprinkler) with contrasting application rates, through the 2005-2006 irrigation season. It was aimed at better understanding, quantifying and modelling of the processes that govern the removal of microbes in intact soil columns, bridging the gap between previous theoretical research and general farm practices, specifically for Templeton soil. This study involved different approaches (leaching experiments, infiltrometer measurements and a dye infiltration study) to understand the processes of transient water flow and bacterial transport; and to extrapolate the relationships between bacterial transport and soil properties (like soil structure, texture), and soil physical status (soil water potential ψ and volumetric water content θ). Factors controlling FC transport are discussed. A contaminant transport model, HYDRUS-1D, was applied to simulate microbial transport through soil on the basis of measured datasets. This study was carried out at Lincoln University’s Centre for Soil and Environmental Quality (CSEQ) lysimeter site. Six lysimeters were employed in two trials. Each trial involved application of DSE, followed by a water irrigation sequence applied in a flux-controlled method. The soil columns were taken from the site of the new Lincoln University Dairy Farm, Lincoln, Canterbury. The soil type is Templeton fine sandy loam (Udic-Ustochrept, coarse loamy, mixed, mesic). Vertical profiles (at four depths) of θ and ψ were measured during leaching experiments. The leaching experiments directly measured concentrations of chemical tracer (Br⁻ or Cl⁻) and FC in drainage. Results showed that bacteria could readily penetrate through 700 mm deep soil columns, when facilitated by water flow. In the first (summer) trial, FC in leachate as high as 1.4×10⁶ cfu 100 mL⁻¹ (similar to the DSE concentration), was detected in one lysimeter that had a higher clay content in the topsoil, immediately after DSE application, and before any water irrigation. This indicates that DSE flowed through preferential flow paths without significant treatment or reduction in concentrations. The highest post-irrigation concentration was 3.4×10³ cfu 100 mL⁻¹ under flood irrigation. Flood irrigation resulted in more bacteria and Br⁻ leaching than spray irrigation. In both trials (summer and autumn) results showed significant differences between irrigation treatments in lysimeters sharing similar drainage class (moderate or moderately rapid). Leaching bacterial concentration was positively correlated with both θ and ψ, and sometimes drainage rate. Greater bacterial leaching was found in the one lysimeter with rapid whole-column effective hydraulic conductivity, Keff, for both flood and spray treatments. Occasionally, the effect of Keff on water movement and bacterial transport overrode the effect of irrigation. The ‘seasonal condition’ of the soil (including variation in initial water content) also influenced bacterial leaching, with less risk of leaching in autumn than in summer. A tension infiltrometer experiment measured hydraulic conductivity of the lysimeters at zero and 40 mm suction. The results showed in most cases a significant correlation between the proportion of bacteria leached and the flow contribution of the macropores. The higher the Ksat, the greater the amount of drainage and bacterial leaching obtained. This research also found that this technique may exclude the activity of some continuous macropores (e.g., cracks) due to the difference of initial wetness which could substantially change the conductivity and result in more serious bacterial leaching in this Templeton soil. A dye infiltration study showed there was great variability in water flow patterns, and most of the flow reaching deeper than 50 cm resulted from macropores, mainly visible cracks. The transient water flow and transport of tracer (Br⁻) and FC were modelled using the HYDRUS-1D software package. The uniform flow van Genuchten model, and the dual-porosity model were used for water flow and the mobile-immobile (MIM) model was used for tracer and FC transport. The hydraulic and solute parameters were optimized during simulation, on the basis of measured datasets from the leaching experiments. There was evidence supporting the presence of macropores, based on the water flow in the post-DSE application stage. The optimised saturated water content (θs) decreased during the post-application process, which could be explained in terms of macropore flow enhanced by irrigation. Moreover, bacterial simulation showed discrepancies in all cases of uniform flow simulations at the very initial stage, indicating that non-equilibrium processes were dominant during those short periods, and suggesting that there were strong dynamic processes involving structure change and subsequently flow paths. It is recommended that management strategies to reduce FC contamination following application of DSE in these soils must aim to decrease preferential flow by adjusting irrigation schemes. Attention needs to be given to a) decreasing irrigation rates at the beginning of each irrigation; b) increasing the number of irrigations, by reducing at the same time the amount of water applied and the irrigation rate at each irrigation; c) applying spray irrigation rather than flood irrigation.

Understanding the fundamentals of composting science from a pragmatic perspective of necessity involves mixtures of different sizes and types of particles in constantly changing environmental conditions, in particular temperature. The complexity of composting is affected by this environmental variation. With so much "noise" in the system, a question arises as to the need to understand the detail of this complexity as understanding any part of composting with more precision than this level of noise is not likely to result in greater understanding of the system. Yet some compost piles generate offensive odours while others don‟t and science should be able to explain this difference. A driver for this research was greater understanding of potential odour, which is assumed to arise from the anaerobic core of a composting particle. It follows that the size of this anaerobic core could be used as an indicator of odour potential. A first step in this understanding is the need to determine which parts of a composting particle are aerobic, from which the anaerobic proportion can be determined by difference. To this end, this thesis uses a finite volume method of analysis to determine the distribution of oxygen at sub-particle scales. Diffusion laws were used to determine the thickness of each finite volume. The resulting model, called micro-environment analysis, was applied to a composting particle to enable determination of onion ring type volumes of compost (called micro-environments) containing substrates (further subdivided into substrate fractions) whose concentrations could be determined to high precision by the application of first-order degradation kinetics to each of these finite volumes. Determination of the oxygen concentration at a micro-environment's inner boundary was achieved by using the Stępniewski equation. The Stępniewski model was derived originally for application to soil aeration and enables each micro-environment to have its own oxygen uptake rate and diffusion coefficient. This first version of micro-environment analysis was derived from the simpler solution to diffusion laws, based on the assumption of non-diffusible substrate. It was tested against three sets of experimental data with two different substrates: Particle size trials using dog sausage as substrate – where the peak composting rate was successfully predicted, as a function of particle size. Temperature trials using pig faeces and a range of particle sizes – the results showed the potential of micro-environment analysis to identify intriguing temperature effects, in particular, a different temperature effect (Q10) and fraction proportion was indicated for each substrate fraction. Smaller particle sizes, and possibly outward diffusion of substrate confounded a clear experimental signal. Diffusion into a pile trials which showed that the time course of particles deeper in the pile could be predicted by the physics of oxygen distribution. A fully computed prediction would need an added level of computational complexity in micro-environment analysis, arising from there being two intertwined phases, gas phase and substrate (particle) phase. Each phase needs its own micro-environment calculations which can not be done in isolation from each other. Unexplainable parts of the composting time course are likely to be partly explained by the outward diffusion of substrate towards the inward-moving oxygen front. Although the possibility of alternative electron acceptors can not be discounted as a partial explanation. To test the theory, a new experimental reactor was developed using calorimetry. With an absolute sensitivity of 0.132 J hr-1 L-1 and a measurement frequency of 30 minutes, the reactor was able to detect the energy required to humidify the input air, and "see" when composting begins to decline as oxygen is consumed. Optimisation of the aeration pumping frequency using the evidence from the data was strikingly apparent immediately after setting the optimum frequency. Micro-environment analysis provides a framework by which several physical effects can be incorporated into compost science.

Worldwide there is considerable concern over the effects of human activities on the quantity and quality of freshwater. Measurement of infiltration behaviour will be important for improving freshwater management. This study identifies that New Zealand has a sporadic history of measuring soil water movement attributes on a limited number of soil types, although the current practical demand should be large for management of irrigation, dairy farm effluent disposal, as well as municipal / domestic waste- and storm-water disposal. Previous research has demonstrated that infiltration behaviour is governed by the interplay between numerous mechanisms including hydrophobicity and preferential flow, the latter being an important mechanism of contaminant leaching for many NZ soils. Future characterisation will need to recognise the dynamic nature of these interactions, and be able to reliably characterise the key infiltration mechanisms. Since macropores are responsible for preferential flow, it is critical that infiltration studies use a representative sample of the macropore network. The aim of this project was to study the mechanisms governing the infiltration behaviour of a layered soil in large (50 x 70 cm) monolith lysimeters, where the connectivity of the macropore network remains undisturbed. Four lysimeters of the Gorge silt loam were collected, a structured soil with four distinct layers. On each lysimeter there were four separate infiltration experiments, with water applied under suctions of 0, 0.5, 1, and 1.5 kPa by a custom-built tension infiltrometer. Each lysimeter was instrumented with 30 tensiometers, located in arrays at the layer boundaries. There was also a field experiment using ponded dye infiltration to visually define preferential flowpaths. Analysis of dye patterns, temporal variability in soil matric potential (Ψm), and solute breakthrough curves all show that preferential flow is an important infiltration mechanism. Preferential flowpaths were activated when Ψm was above -1.5 kPa. During saturated infiltration, at least 97% of drainage was through the ‘mobile’ pore volume of the lysimeter (θm), estimated among the lysimeters at 5.4 – 8.7 % of the lysimeter volume. Early-time infiltration behaviour did not show the classical square-root of time behaviour, indicating sorptivity was not the governing mechanism. This was consistent across the four lysimeters, and during infiltration under different surface imposed suctions. The most likely mechanism restricting sorptivity is weak hydrophobicity, which appears to restrict infiltration for the first 5 – 10 mm of infiltration. Overall, the Gorge soil’s early-time infiltration behaviour is governed by the dynamic interaction between sorptivity, hydrophobicity, the network of air-filled pores, preferential flow and air encapsulation. Long-time infiltration behaviour was intimately linked to the temporal dynamics of Ψm, which was in turn controlled by preferential flow and soil layer interactions. Preferential flowpaths created strong inter-layer connectivity by allowing an irregular wetting front to reach lower layers within 2 – 15 mm of infiltration. Thereafter, layer interactions dominate infiltration for long-time periods, as Ψm in soil layers with different K(Ψm) relationships self-adjusts to try to maintain a constant Darcy velocity. An important finding was that Ψm rarely attained the value set by the tension infiltrometer during unsaturated infiltration. The results show that ‘true’ steady-state infiltration is unlikely to occur in layered soils. A quasi-steady state was identified once the whole column had fully wet and layer interactions had settled to where Ψm changes occurred in unison through each soil layer. Quasi-steady state was difficult to identify from just the cumulative infiltration curve, but more robustly identified as when infiltration matched drainage, and Ψm measurements showed each layer had a stable hydraulic gradient. I conclude that the in-situ hydraulic conductivity, K(Ψm), of individual soil layers can be accurately and meaningfully determined from lysimeter-scale infiltration experiments. My results show that K(Ψm) is different for each soil layer, and that differences are consistent among the four lysimeters. Under saturated flow the subsoil had the lowest conductivity, and was the restricting layer. Most interestingly this pattern reversed during unsaturated flow. As Ψm decreased below -0.5 to -1 kPa, the subsoil was markedly more conductive, and the topsoil layers became the restricting layers. All four soil layers demonstrate a sharp decline in K(Ψm) as Ψm decreases, with a break in slope at ~ -1 kPa indicating the dual-permeability nature of all layers.

Changes brought about by chemical and physical weathering were investigated in a chronosequence of terrace soils near Reefton, New Zealand. The parent materials of the soil, which ranged in age from about 1000 to over 130,000 years were outwash gravels, sands and silts derived from granite (dominant) and indurated sandstone. Variations in pH, organic matter, particle size, cation exchange properties, total Mg, Al, Si, K, Ca, Fe and Ti, poorly-ordered and organic-complexed forms of Al and Fe, and mineralogy caused by increasing duration of weathering and by short range, short term variations in the intensity of the biotic factor were determined. It was concluded that the younger soils represented dynamic systems in which alternative weathering cycles could replace each other as the growth, death and eventual disappearance of individual red beech trees caused localised fluctuations in pH. It was further concluded that these processes would lead ultimately to the formation of gley podzols as are now found on the two oldest surfaces p and that podzolisation preceded gleying. Attempts were made to determine if minerals of the plumbogummite group were responsible for the high proportion of soil phosphate from these soils that, on fractionation, appeared in the residual P fraction. It was found that attempts to concentrate these minerals by prolonged digestion with HF resulted in their solution, and in precipitation of complex fluorides that yielded diffraction spacings that have been mistaken for minerals of the plumbogummite group.