In the southern Great Plains, the encroachment of grassland ecosystems by mesquite (Prosopis glandulosa), is widespread, and prescribed fire is commonly used in its control. Despite this, substantial quantitative information concerning their influences on the community composition, functional dynamics, and soil organic carbon (SOC) storage potential of grassland ecosystems is lacking. The objectives of this study were to: a) quantify the effects of seasonal prescribed fire treatments and mesquite encroachment on aboveground net primary productivity (ANPP) and herbaceous community composition; b) characterize SOC pool sizes, turnover, and storage potential relative to vegetation type and fire treatment; c) evaluate the structure and diversity of soil microbial communities relative to vegetation type; and d) characterize the functional diversity of these same microbes using the GeoChip functional gene microarray. Repeated winter and summer fires led to increased ANPP rates (average, 434 and 313 g m-2 y-1, respectively), relative to unburned controls (average, 238 g m-2 y-1), altered herbaceous community composition, and increased the storage of resistant forms of SOC, but did not affect overall SOC storage. Herbaceous ANPP rates did not differ significantly as a result of mesquite encroachment, but herbaceous community composition and SOC storage did. Mesquite soils contained significantly more total, slow-turnover, and resistant forms of SOC than those that occurred beneath C3 or C4 grasses. Similarity among the soil bacterial and fungal communities associated with the major vegetation types in this system was low to moderate. Significant differences were detected among soil fungi, with the mesquite-associated fungi harboring significant differences in community structure relative to the fungal communities associated with each of the other vegetation types examined. Despite this result, few significant differences were detected with respect to the functional diversity of these communities, suggesting either a high degree of functional redundancy, or that the functional differences harbored by these communities are beyond the scope of the GeoChip. The results of this study demonstrate that both fire and mesquite encroachment have the potential to alter ecosystem components and processes significantly, providing new insight regarding the effects of these widespread land use and land cover changes on ecosystem structure and function.

Woody plant invasion of grasslands is prevalent worldwide, but the biogeochemical consequences of this vegetation shift remain largely unquantified. In the Rio Grande Plains, TX, grasslands and savannas dominated by C4 grasses have undergone succession over the past century to subtropical thorn woodlands dominated by C3 trees/shrubs. To elucidate mechanisms of soil organic carbon (SOC) and soil total N (STN) storage and dynamics in this ecosystem, I measured the mass and isotopic composition (δ13C, δ15N) of C and N in whole-soil and soil size/density fractions in chronosequences consisting of remnant grasslands (Time 0) and woody plant stands ranging in age from 10-130 years. Rates of SOC and STN storage averaged 10-30 g C m-2yr-1 and 1-3 g N m-2yr-1, respectively. These accumulation rates increased soil C and N pools 80-200% following woody encroachment. Soil microbial biomass (SMB-C) also increased after woody invasion. Decreasing Cmic/C org and higher qCO2 in woodlands relative to grasslands suggests that woody litter is of poorer quality than grassland litter. Greater SOC and STN following woody invasion may also be due to increased protection of organic matter by stable soil structure. Soil aggregation increased following woody encroachment; however, most of the C and N accumulated in free particulate organic matter (POM) fractions not protected within aggregates. Mean residence times (MRTs) of soil fractions were calculated based on changes in their δ13C with time after woody encroachment. Free POM had the shortest average MRTs (30 years) and silt+clay the longest (360 years). Fine POM had MRTs of about 60 years, reflecting protection by location within aggregates. δ15N values of soil fractions were positively correlated with their MRTs, suggesting that higher δ15N values reflect an increased degree of humification. Increases in SOC and STN are probably being sustained by greater inputs, slower turnover of POM (some biochemical recalcitrance), and protection of organic matter in aggregates and association with silt and clay. Grassland-to-woodland conversion during the past century has been geographically extensive in grassland ecosystems worldwide, suggesting that changes in soil C and N dynamics and storage documented here could have significance for global C and N cycles.

Diss. (sammanfattning) Uppsala : Sveriges lantbruksuniv., 2009. / Härtill 4 uppsatser.

The goal of this thesis was to characterize and quantify changes to Canadian Arctic organic matter (OM) induced by a physical disruption to the permafrost active layer by employing molecular-level techniques such as biomarker extraction and NMR to help elucidate its contribution to carbon turnover and global climate change. The initial biomarker characterization study determined that the extractable plant lipids were unaltered originating from the deposition of new vascular material or permafrost melt where a high alteration of lignin-derived OM was observed suggesting a long residence time in the ecosystem. Analysis of samples where there was a new and historical physical disruption to the permafrost landscape showed an initial increase in bacterial biomass biomarkers, and was corroborated with increased bacterial protein contributions and peptidoglycan signals in the NMR spectra. It is hypothesized that this increase in bacterial biomass resulted in a faster rate of degradation, possibly leading to OM priming.

The goal of this thesis was to characterize and quantify changes to Canadian Arctic organic matter (OM) induced by a physical disruption to the permafrost active layer by employing molecular-level techniques such as biomarker extraction and NMR to help elucidate its contribution to carbon turnover and global climate change. The initial biomarker characterization study determined that the extractable plant lipids were unaltered originating from the deposition of new vascular material or permafrost melt where a high alteration of lignin-derived OM was observed suggesting a long residence time in the ecosystem. Analysis of samples where there was a new and historical physical disruption to the permafrost landscape showed an initial increase in bacterial biomass biomarkers, and was corroborated with increased bacterial protein contributions and peptidoglycan signals in the NMR spectra. It is hypothesized that this increase in bacterial biomass resulted in a faster rate of degradation, possibly leading to OM priming.

This thesis presents the first modeling study on long-term carbon dynamics for the University of Guelph Elora Agricultural Research Station and the Environment Canada Borden Forest Research Station at the daily and half-hourly time-step. The daily version of the CENTURY (DayCENT) model and the Carbon- and Nitrogen-coupled Canadian Land Surface Scheme (CN-CLASS) model were validated for quantifying the effects of agricultural management and component respiration on the carbon budget. DayCENT indicated that conventional tillage (CT) enhanced the annual heterotrophic respiration relative to no-till (NT) by 38.4, 93.7 and 64.2 g C m-2 yr-1 for corn, soybean and winter wheat, respectively. The seasonal variation of total soil organic carbon (SOC) pool was greater in CT than NT due to tillage effects on carbon transfer from the active surface SOC pool to the active soil SOC pool at a rate of 50-100 g C m-2 yr-1. NT accounted for a 10.7 g C m-2 yr-1 increase in the slow SOC pool (20-year turnover time) at a site in Elora, Ontario, Canada. I found that the plant phenology algorithms used in CN-CLASS were not constructed and validated for crop growth, resulting in a high degree of uncertainty in the simulations. Therefore, I designed and tested a new agricultural module for CN-CLASS. The regression analysis indicated that the new crop module improved the net ecosystem productivity (NEP) simulation for a cornfield, with the coefficient of determination (r2) of annual NEP increasing from 0.51 in the original CN-CLASS to 0.78 in the modified version of the model. I verified CN-CLASS to simulate the dynamics of component respiration for tracing the contributions from litterfall, SOC and root respiration in a deciduous mixedwood forest in Borden, Ontario, Canada. The model estimated that the annual ecosystem CO2 respiration was 1366 g C m-2 yr-1, contributed by heterotrophic respiration (57%), maintenance respiration (37%) and growth respiration (6%). The annual accumulated soil respiration was estimated at 782 g C m-2 yr-1, which was dominated by CO2 emissions from soil organic matter (60%). The base respiration rates required further verification based on field measurements. Based on the verified modeling approach in this thesis, the modeling core of DayCENT can be constructed as an integral platform for Agriculture and Agri-Food Canada National Carbon and Greenhouse Gas Accounting and Verification System. The crop phenological module in CN-CLASS allows us to conduct further agricultural studies concerning global carbon budget and environmental change. The validated respiration algorithms in CN-CLASS would be helpful in developing global biological CO2 transport model for tracing emission sources. / Natural Science and Engineering Research Council of Canada

Für die montanen Regionen kontinental Südostasiens (Südwest China, Laos, Kambodscha, Myanmar, Nordost Thailand, Nordwest Vietnam) gibt es nur wenig Informationen über die organische Bodensubstanz (OBS) und ihre Beeinflussung durch Landnutzung, Bewirtschaftung und biophysikalische Eigenschaften. Zum Beispiel ist trotz großflächiger Entwaldung zu Gunsten von Kautschukplantagen der Einfluss dieser Landnutzungsänderung auf OBS Vorräte kaum bekannt. Auch wurde der Einfluss der Terrassierung, wie sie für den Kautschukanbau in montanen Regionen üblich ist, auf die Dynamik der OBS bislang nicht untersucht. Des Weiteren liegen nur begrenzt Informationen über die räumliche Verteilung von OBS Vorräten und die Rolle potentieller Regulationsfaktoren wie Landnutzung, Vegetation, Bodentextur und Topographie vor. Die vorliegende Arbeit zielte auf die genannten Wissenslücken und präsentiert in diesem Kontext drei Studien aus der montanen Region Xishuangannas, Süd Yunnan, China. In den ersten beiden, in einer tropischen Landschaft durchgeführten Studien, habe ich die Änderung des OBS Vorrats durch 1) die Umwandlung von Sekundärwald in Kautschukplantagen und 2) durch den Bau von Terrassen, quantifiziert. Um in der ersten Studie Landnutzungseffekte auf die OBS-Vorräte zu quantifizieren, habe ich den Ansatz der unechten Zeitreihe (space-for-time substitution) genutzt. Ich habe 11 terrassierte Kautschukplantagen im Alter von 5 bis 46 Jahren sowie sieben Sekundärwaldparzellen untersucht. Die Ergebnisse zeigten, dass die Umwandlung von Sekundärwald in Kautschukplantagen eine Abnahme der OBS Vorräte von 37.4 Mg C ha-1 im Bereich bis zu einer Tiefe von 1.2 m hervorrief; diese Abnahme entsprach 19% des ursprünglichen OBS Vorrats im Sekundärwald. Im Oberboden nahm der OBS Vorrat exponentiell ab; in den ersten 5 Jahren nach der Landnutzungsänderung war die Abnahme am stärksten, nach ca. 20 Jahren hat sich ein Gleichgewicht eingestellt. Der mittlere OBS-Verlust von 37.4 Mg C ha-1 war viel höher als literaturbasierte Schätzwerte für Änderungen der oberirdischen Kohlenstoffvorräte, welche zwischen einem Verlust von 18 Mg C ha-1 und einer Steigerung von 8 Mg C ha-1 liegen. Im Gegensatz zur IPCC tier 1-Methode, die davon ausgeht, dass OBS Vorratsänderungen bei einer Umwandlung von Wald zu Kautschuk gleich 0 sind, zeigen meine Ergebnisse, dass OBS-Verluste in Betracht gezogen werden müssen, um potentiell große Fehler bei der Schätzung von Kohlenstoffflüssen von Ökosystemen zu vermeiden. Terrassierte Kautschukplantage bestehen aus schmalen Terrassen mit einer Baumreihe, die sich mit ursprünglichen geneigten Flächen abwechseln. Bei der Konstruktion der Terrassen wird Boden vom Hang abgetragen, und so eine innere Kante der Terrasse entsteht (Entnahmebereich); der entfernte Boden wird dann auf den Hang unterhalb der Grabungsfläche aufgehäuft und bildet die äußere Kante der Terrasse (Ablagebereich). Die zweite Studie untersucht den Einfluss der Terrassierung auf OBS Vorräte in 5, 29 und 44 Jahre alten Plantagen. In jeder Plantage habe ich die Terrassen systematisch in den verschiedenen Bodenverteilungszonen beprobt, die ursprünglichen Hangflächen zwischen den Terrassen diente als Referenz. Die Ergebnisse dieser Studie zeigten, dass die Terrassierung die OBS Vorräte der 5 Jahre alten Plantage nicht beeinflusst hat. In den 29 und 44 Jahre alten Plantagen wurden jedoch in 0-1.2 m Tiefe höhere OBS Vorräte auf den Terrassen als auf den Referenzflächen beobachtet. Der positive Effekt der Terrassierung auf die OBS Vorräte in den beiden älteren Plantagen wurde auf die Erholung des OBS Vorrats im freiliegenden Oberboden des Entnahmebereichs, und die teilweise Erhaltung von OBS im begrabenen Boden des Ablagebereichs erklärt. Die Erholung der OBS Vorräte im Entnahmebereichen konnte durch die Aufnahme neuer OBS des freiliegenden Unterbodens in Form von Wurzeln und Laubfall sowie durch die Sedimentation von erodiertem Oberbodenmaterial des Oberhangs erklärt werden. Zusammenfassend zeigen die Ergebnisse, dass Terrassierung die Verluste von OBS verringern kann; ohne die Anlage von Terrassen könnte der Verlust von OBS durch die Umwandlung von Wald zu Kautschukplantagen größer sein. In der dritten Studie, durchgeführt in einer subtropischen Landschaft, habe ich die aktuellen OBS Vorräte pro dominanter Landnutzung quantifiziert und die Beziehungen zwischen OBS und Landnutzung, sowie Vegetation, Bodentextur und Topographie untersucht. In einem 10.000 Hektar großen Gebiet habe ich 28 ein Hektar große Probeflächen in Wäldern mit geschlossenem und offenem Kronendach, Teeplantagen und Buschland ausgewählt. Die OBS-Vorräte in einer Tiefe von 0-0.9 m waren unter den höchsten der Region: 228.6 ± 19.7 (SE) Mg C ha-1 in Wäldern mit geschlossenem Kronendach, 200.4 ± 15.5 Mg C ha-1 in Wäldern mit offenem Kronendach, 197.5 ± 25.9 Mg C ha-1 in Teeplantagen und 236.2 ± 13.7 Mg C ha-1 im Buschland. OBS Konzentrationen und Vorräte unterschieden sich nicht signifikant zwischen den Landnutzungstypen. Mehr als 50% der gesamten Varianz der OBS wurde innerhalb der ein Hektar großen Flächen beobachtet und war abhängig von der Variabilität der Grundfläche der Bäume, Kohlenstoffvorrat der Streuauflage und der Geländeneigung. Diese Ergebnisse illustrieren die Bedeutung lokaler Prozesse auf die Variabilität von OBS Vorräten in einer montanen Landschaft. Die Ergebnisse aller drei hier vorgestellten Studien tragen zu einem besseren Verständnis von OBS Vorräten und deren Dynamik in einer schnellen Änderungsprozessen ausgesetzten Region bei. Darüber hinaus bilden sie eine potentielle Grundlage für weitere Studien über Änderungen von Ökosystemdienstleistungen in montanen Regionen des kontinentalen Südostasiens.

The fate and behaviour of hydrophobic organic compounds (e.g. pesticides) in soils are largely controlled by sorption processes. Recent findings suggest that the chemical properties of soil organic carbon (OC) significantly control the extent of sorption of such compounds in soil systems. However, currently there is no practical tool to integrate the effects of OC chemistry into sorption predictions. Therefore, the K [subscript]oc model, which relies on the soil OC content (foc), is used for predicting soil sorption coefficients (K[subscript]d) of pesticides. The K[subscript]oc model can be expressed as K[subscript]d = K[subscript]oc × foc, where K[subscript]oc is the OC-normalized sorption coefficient for the compound. Hence, there is a need for a prediction tool that can effectively capture the role of both the chemical structural variation of OC as well as foc in the prediction approach. Infrared (IR) spectroscopy offers a potential alternative to the K[subscript]oc approach because IR spectra contain information on the amount and nature of both organic and mineral soil components. The potential of mid-infrared (MIR) spectroscopy for predicting K[subscript]d values of a moderately hydrophobic pesticide, diuron, was investigated. A calibration set of 101 surface soils from South Australia was characterized for reference sorption data (K[subscript]d and K[subscript]oc) and foc as well as IR spectra. Partial least squares (PLS) regression was employed to harness the apparent complexity of IR spectra by reducing the dimensionality of the data. The MIR-PLS model was developed and validated by dividing the initial data set into corresponding calibration and validation sets. The developed model showed promising performance in predicting K[subscript]d values for diuron and proved to be a more efficacious than the K[subscript]oc model. The significant statistical superiority of the MIR-PLS model over the K[subscript]oc model was caused by some calcareous soils which were outliers for the K[subscript]oc model. Apart from these samples, the performance of the two compared models was essentially similar. The existence of carbonate peaks in the MIR-PLS loadings of the MIR based model suggested that carbonate minerals may interfere or affect the sorption. This requires further investigation. Some other concurrent studies suggested excellent quality of prediction of soil properties by NIR spectroscopy when applied to homogenous samples. Next, therefore, the performance of visible near-infrared (VNIR) and MIR spectroscopy was thoroughly compared for predicting both foc and diuron K[subscript]d values in soils. Some eleven calcareous soils were added to the initial calibration set for an attempt to further investigate the effect of carbonate minerals on sorption. MIR spectroscopy was clearly a more accurate predictor of foc and K[subscript]d in soils than VNIR spectroscopy. Close inspection of spectra showed that MIR spectra contain more relevant and straightforward information regarding the chemistry of OC and minerals than VNIR and thus useful in modelling sorption and OC content. Moreover, MIR spectroscopy provided a better (though still not great) estimation of sorption in calcareous soils than either VNIR spectroscopy or the K[subscript]oc model. Separate research is recommended to fully explore the unusual sorption behaviour of diuron in calcareous soils. In the last experiment, two dimensional (2D) nuclear magnetic resonance/infrared heterospectral correlation analyses revealed that MIR spectra contain specific and clear signals related to most of the major NMR-derived carbon types whereas NIR spectra contain only a few broad and overlapped peaks weakly associated with aliphatic carbons. 2D heterospectral correlation analysis facilitated accurate band assignments in the MIR and NIR spectra to the NMR-derived carbon types in isolated SOM. In conclusion, the greatest advantage of the MIR-PLS model is the direct estimation of Kd based on integrated properties of organic and mineral components. In addition, MIR spectroscopy is being used increasingly in predicting various soil properties including foc, and therefore, its simultaneous use for K[subscript]d estimation is a resource-effective and attractive practice. Moreover, it has the advantage of being fast and inexpensive with a high repeatability, and unlike the K[subscript]oc approach, MIR-PLS shows a better potential for extrapolating applications in data-poor regions. Where available, MIR spectroscopy is highly recommended over NIR spectroscopy. 2D correlation spectroscopy showed promising potential for providing rich insight and clarification into the thorough study of soil IR spectra. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1415416 / Thesis (Ph.D.) - University of Adelaide, School of Earth and Environmental Sciences, 2009

Research Doctorate - Doctor of Philosophy (PhD) / Amidst growing concerns about global warming, efforts to reduce atmospheric CO2 concentrations (i.e. C sequestration) have received widespread attention. One approach to C sequestration is to increase the amount of C stored in terrestrial ecosystems, through improved land management. Terrestrial ecosystems represent a critical element of the C interchange system, however a lack of understanding of the C cycle at regional and sub-regional scales means that they represent a source of primary uncertainty in the overall C budget. This thesis aims to address this deficiency by developing an understanding of catchment-scale processes critical for accurate quantification of C in the landscape. An investigation into the spatial and temporal dynamics of soil organic carbon (SOC) was conducted for a 150ha temperate grassland catchment in the Upper Hunter Valley, New South Wales, Australia. The major factors controlling the movement, storage, and loss of SOC were investigated, including climate, vegetation cover, soil redistribution processes, topography, land use, and soil type. This study falls into four broad areas. In the first part of this study the spatio-temporal dynamics of soil moisture and temperature at the catchment scale are assessed for a range of soil depths. Data recorded from a network of monitoring sites located throughout the study catchment was compared with independently derived soil moisture and temperature data sets. The data indicates that soil moisture and temperature in surface soil layers were highly dynamic, in their response to rainfall and incoming solar radiation, respectively. Deeper soil layers however were less dynamic, with longer lag times observed with increasing soil depth, as topography, soil type, and landscape position were the dominant controlling factors. Climate related variables are important factors affecting plant growth and net primary productivity. The second part of the study quantified spatial and temporal vegetation patterns using both field-based measurements of above-ground biomass and remotely sensed vegetation indices from the MODIS and Landsat TM 5 platforms. A strong and statistically significant relationship was found between climate variables and MODIS derived NDVI, leading to the development of a predictive vegetation cover model using ground-based soil moisture, soil temperature, and sunshine hours data. The ability of remotely sensed data to capture vegetation spatial patterns was found to be limited, while it was found to be a good predictor of temporal above-ground biomass trends, enabling net primary productivity to be quantified over the three-year study period. In the third part of the thesis soil redistribution patterns and erosion rates were quantified using the caesium-137 method and empirical and physically-based modelling approaches. The impact of soil redistribution processes on SOC distribution was investigated, and the amount of erosion derived SOC loss quantified. A significant proportion of SOC stored within the catchment was found below a soil depth of 0.30m, which is the depth of sampling set out in the IPCC and Australian Greenhouse Office guidelines for carbon accounting. Soil depth was identified as a key factor controlling the spatial distribution of SOC, which is in turn determined by position in the landscape (i.e. topography). The fourth and final part of the study describes how data on erosion derived SOC loss were used in conjunction with net primary productivity estimates, to establish a SOC balance. This involved mapping the spatial distribution of SOC using a high resolution digital elevation model of the catchment, in conjunction with soil depth measurements, and quantifying the total SOC store of the catchment. It was observed that temporal changes in SOC were minimal over the limited three-year study period, however, the continuity of catchment management practices over the previous decades suggest that steady-state conditions have perhaps been reached. The study concludes that the key to increasing the amount of SOC and enhancing carbon sequestration in the soil, is to increase the amount of SOC stored at depth within the soil profile, where factors such as soil moisture and temperature, which control decomposition rates, are less dynamic in space and time, and where SOC concentrations will be less vulnerable to changes occurring at the surface in response to global warming and climate change.

The fate and behaviour of hydrophobic organic compounds (e.g. pesticides) in soils are largely controlled by sorption processes. Recent findings suggest that the chemical properties of soil organic carbon (OC) significantly control the extent of sorption of such compounds in soil systems. However, currently there is no practical tool to integrate the effects of OC chemistry into sorption predictions. Therefore, the K [subscript]oc model, which relies on the soil OC content (foc), is used for predicting soil sorption coefficients (K[subscript]d) of pesticides. The K[subscript]oc model can be expressed as K[subscript]d = K[subscript]oc × foc, where K[subscript]oc is the OC-normalized sorption coefficient for the compound. Hence, there is a need for a prediction tool that can effectively capture the role of both the chemical structural variation of OC as well as foc in the prediction approach. Infrared (IR) spectroscopy offers a potential alternative to the K[subscript]oc approach because IR spectra contain information on the amount and nature of both organic and mineral soil components. The potential of mid-infrared (MIR) spectroscopy for predicting K[subscript]d values of a moderately hydrophobic pesticide, diuron, was investigated. A calibration set of 101 surface soils from South Australia was characterized for reference sorption data (K[subscript]d and K[subscript]oc) and foc as well as IR spectra. Partial least squares (PLS) regression was employed to harness the apparent complexity of IR spectra by reducing the dimensionality of the data. The MIR-PLS model was developed and validated by dividing the initial data set into corresponding calibration and validation sets. The developed model showed promising performance in predicting K[subscript]d values for diuron and proved to be a more efficacious than the K[subscript]oc model. The significant statistical superiority of the MIR-PLS model over the K[subscript]oc model was caused by some calcareous soils which were outliers for the K[subscript]oc model. Apart from these samples, the performance of the two compared models was essentially similar. The existence of carbonate peaks in the MIR-PLS loadings of the MIR based model suggested that carbonate minerals may interfere or affect the sorption. This requires further investigation. Some other concurrent studies suggested excellent quality of prediction of soil properties by NIR spectroscopy when applied to homogenous samples. Next, therefore, the performance of visible near-infrared (VNIR) and MIR spectroscopy was thoroughly compared for predicting both foc and diuron K[subscript]d values in soils. Some eleven calcareous soils were added to the initial calibration set for an attempt to further investigate the effect of carbonate minerals on sorption. MIR spectroscopy was clearly a more accurate predictor of foc and K[subscript]d in soils than VNIR spectroscopy. Close inspection of spectra showed that MIR spectra contain more relevant and straightforward information regarding the chemistry of OC and minerals than VNIR and thus useful in modelling sorption and OC content. Moreover, MIR spectroscopy provided a better (though still not great) estimation of sorption in calcareous soils than either VNIR spectroscopy or the K[subscript]oc model. Separate research is recommended to fully explore the unusual sorption behaviour of diuron in calcareous soils. In the last experiment, two dimensional (2D) nuclear magnetic resonance/infrared heterospectral correlation analyses revealed that MIR spectra contain specific and clear signals related to most of the major NMR-derived carbon types whereas NIR spectra contain only a few broad and overlapped peaks weakly associated with aliphatic carbons. 2D heterospectral correlation analysis facilitated accurate band assignments in the MIR and NIR spectra to the NMR-derived carbon types in isolated SOM. In conclusion, the greatest advantage of the MIR-PLS model is the direct estimation of Kd based on integrated properties of organic and mineral components. In addition, MIR spectroscopy is being used increasingly in predicting various soil properties including foc, and therefore, its simultaneous use for K[subscript]d estimation is a resource-effective and attractive practice. Moreover, it has the advantage of being fast and inexpensive with a high repeatability, and unlike the K[subscript]oc approach, MIR-PLS shows a better potential for extrapolating applications in data-poor regions. Where available, MIR spectroscopy is highly recommended over NIR spectroscopy. 2D correlation spectroscopy showed promising potential for providing rich insight and clarification into the thorough study of soil IR spectra. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1415416 / Thesis (Ph.D.) - University of Adelaide, School of Earth and Environmental Sciences, 2009