Classifying sedimentary organics:

Abstract

Sediments are crucial to the understanding of environmental processes and conditions in a variety of systems. The study of sediments often focuses on quantity, but should involve more emphasis on the quality of the organic component, by utilising commonplace techniques employed by other disciplines. We provide a classification scheme that will allow those interested in organic matter quality to decide on appropriate techniques to apply, and discuss a variety of applications of the investigation of organic matter quality in diverse areas of Physical Geography. Firstly, this paper conceptualises organic matter quality by examining how different groups identify with this term, providing a classification scheme that may assist individuals in their exploration of organic matter character. Secondly, it identifies key areas of investigation linked to Physical Geography where research into organic matter quality may provide a necessary or useful component. Finally, it explains and evaluates crucial techniques for characterising organic matter quality.

Keywords

Organic matter quality sediments classification applications measurement techniques

I Introduction

Physical geographers that study sediments, have tended to be interested in the quantity and quality of the mineral rather than the organic material. Allogenic or potentially autogenic change in a sediment system, such as climatic perturbation or anthropogenic interference, can have effects on both the quantity and quality of the mineral component in terrestrial and surface water sediment systems; consequently, sediment properties may be used as an indicator of these changes. This is not to say that the organic component of collected sediments is simply ignored; the organic component is often investigated in a rather restricted manner, limited to basic characteristics such as the ratio of organic to mineral content derived from loss on ignition (LOI), or the concentrations of dissolved and particulate organic carbon (OC) in water samples. This is a limited approach as quantifying organic matter (OM) is not the same as quantifying OC, with some commonly applied analytical methods used to quantify OM solely determining carbon content (Hiriart-Baer et al., 2013). In fact, OC is often molecularly bound to other elements in compounds that are not taken into consideration when making measurements, such as total organic carbon (TOC) or particulate organic carbon/dissolved organic carbon (POC/DOC). LOI is a more rudimentary measure of OM content, but does not exclude these other elements. There is no doubt that this information is useful; however, these types of analysis indicate the quantity of OM relative to a particular temporal scale or volume, rather than treating the organic fraction as a separate entity worthy of substantial investigation.

1.1 Defining organic matter quality

OM ‘quality’ is typically less well defined, as a variety of disciplines have an interest in the quality and accordingly define it in different ways. These disparities in the definition of OM quality, and thus how it may be measured, have vital implications for the study of carbon cycling, biogeochemical processing and ultimately ecosystem structure and function. The quality and quantity of OM have an influence on the chemical, biological and physical functioning of systems and may reveal a wealth of past or contemporary environmental information. Models and theories on OM processing in a variety of environmental systems have been developed without clearly defining OM quality, because most results do not depend on an outright measure of quality (Bosatta and Ågren, 1999). With approaches and techniques varying between fields, there is a need to consider a more systematic approach to the analysis and definition of OM quality. In this paper we provide a classification of OM quality, outlining examples of potential applications and suitable techniques for the analysis of the main classes of OM character. Before introducing this classification scheme it is useful to outline a variety of ways in which OM quality may be considered.

One useful measure of OM quality is age, determined by the amount of time that has elapsed during which OM decomposition may occur, modifying the chemical composition and structure of the original organic material. However, age is a proxy for OM quality since rates of change of quality in time are dependent on the initial in-situ composition of OM, and any compositional changes during subsequent transport and deposition. These factors are site specific. Related to this, Vidon et al. (2014) associate OM quality with the ‘freshness’ of OM in addition to origin. Freshness of OM is a poorly defined term; is freshness defined solely by age?

Let us look at a hypothetical example of overbank deposition on a floodplain (Figure 1), to illustrate that freshness is not exclusively a function of age. Assume that two separate and equal samples of OM, in terms of age, quantity and quality (chemical composition and structure in this instance), are deposited in different positions with depth on a floodplain during a single, large flood event. One sample is deposited at a greater depth at the beginning of the flood event, while the other is deposited at the end of the flood event. Within the floodplain, the oxygen reduction potential varies with depth, and is controlled by both compaction and water table position. Compaction controls the rate of decomposition by regulating the pore space that air may occupy, thus determining whether decomposition by microorganisms mainly ensues under aerobic or anaerobic pathways. It is well known that the rate of decomposition occurs more rapidly and may focus on different organic components under abundant oxygen conditions (Killops and Killops, 2004). The frequency, duration and vertical extent of inundation of the floodplain by oxic waters, is also a control on the decomposition pathway. The sample at the top of the floodplain is in a more oxic zone with regard to proximity to exchange with the atmosphere and lesser compaction, with the result being more pore spaces of a greater size. Conversely, the sample is reached less frequently by hydrological inundation resulting in exposure to oxic waters. The identical sample that is deeper in the sediment is in a less oxic zone as there is reduced opportunity for gaseous exchange with the atmosphere and more compaction, reducing the amount and size of pore spaces. However, the sample is exposed more frequently to oxic waters, due to the smaller return period associated with lower flows that may interact with the sample, as it is closer to the position of the normal water table. Thus, the interactions between burial and exchange to the atmosphere, and position relative to the water table, are controlling factors related to decomposition rate and dominant pathway. If we had a way to extract and identify the quantity and chemical structure of these two OM samples that were of equal age, we would most likely see that the ‘quality’ of the samples was different based on the rate and pathway of decomposition, and thus age is not the lone factor in the ‘freshness’ of OM. This also means that the environmental conditions that OM is exposed to are inherent in the resultant quality, in addition to location, despite the small scale. However, it is not apparent which factor is the most important in inducing the most change in decomposition rate and OM quality, in this example. It could be assumed that gaseous exchange with the atmosphere is more important in supporting decomposition by aerobic microbial communities rather than more frequent inundation by oxic waters. Nonetheless, the interactions between different factors remain complex, with this example illustrating this effectively, and of course in reality OM samples deposited are unlikely to be equal in age, quantity and quality.

Figure 1.

Hypothetical example of overbank deposition of organic matter in a floodplain environment, considering the factors controlling rate of decomposition and the resultant quality.

The quality of OM is a popular concept in soils literature, but is more commonly discussed as a component of overall soil quality rather than being treated as a dynamic element. Nevertheless, to those interested in soil science, and also in the ecological functioning of other environmental systems, the extent to which the OM is bioavailable (i.e. how easily OM may be utilised by microorganisms both in terms of a source of energy and building the carbon skeletons of their own physiological structures) is how OM quality should be defined. Gray et al. (2002) emphasise the importance of the lability of the OM rather than its absolute quantity, since it is lability that determines the degree to which it stimulates microbial metabolisms. In this sense, quality is a function of the degree of lability of OM (Rovira and Vallejo, 2002). Rovira and Vallejo (2002) argue that quality is a function of the chemical and biological features of the substrate, with indices such as C/N (Meyers and Lallier-Vergès, 1999), lignin/N and lignin/cellulose ratios (Taylor et al., 1989) used as key measures of quality. d’Annunzio et al. (2008) link quality to stoichiometry of degrading OM and also estimate that a rough measure of this is the C/N ratio. These indices reflect to some degree the distribution of labile and recalcitrant molecular groups in the OM. However, these rudimentary ratios, although useful as a general measure, have a variety of limitations, including that the elements only account for a small fraction of the plant material and they do not take into account more complex compounds that may be important in the decomposition process (Joffre et al., 2001).

An alternative approach, linked to bioavailability, is defining how easily carbon resident in litter debris, soils or sediments can be mineralised, i.e. the stability of the carbon (C). Bosatta and Ågren (1999) suggest that OM quality is related to thermodynamics and the number of enzymatic steps required to release a C atom from an organic compound as CO₂, with the larger the number of steps indicating a ‘lower quality’ of OM. An excellent review of thermodynamic properties in the degradation of OM is provided by La Rowe and Van Cappellen (2011). However, carbon, although the primary element of interest for microorganisms to build their physiological structures, is not the only element that is utilised and, as argued by Ågren and Bosatta (1996), not all carbon is equally decomposable. Two of the concepts discussed here – bioavailability (incorporation into microbial biomass) versus instability (mineralisation to the atmosphere) – are, arguably, two contrasting pathways that OC present in soils and sediments may take and OM is often simply classified as more easily decomposed (labile – low stability, high quality) or less easily decomposed (recalcitrant – high stability, low quality) by microbial populations in relative terms (Plante et al., 2011). These processes are facilitated by the same organisms, with the preferred pathway linked to a number of factors including environmental conditions that are subject to future change, and it is these that are generally of interest to physical geographers.

II Classifications and exemplars

From the different approaches used to define OM quality, we have suggested a classification scheme that may enable those with an interest to determine why and how they may examine OM quality. As Figure 2 demonstrates, classifications of quality are inherently interlinked. Often it is impossible to examine one category without at least considering another. This does not mean, however, that this classification scheme is not useful, as each of these classifications may be succinctly defined.

Figure 2.

OM quality classifications and interactions.

Thermodynamic quality is the number of enzymatic steps and energy exchange required to remove a C atom from a compound as CO₂ (Bosatta and Ågren, 1999). Thermodynamic quality links to bioavailable quality as thermodynamic transformations are facilitated by microorganisms, and the number of steps taken is dependent on the efficiency of utilisation of the components of OM by microorganisms, which can be simplified by defining this as labile and recalcitrant OM. However, deciding what defines labile and recalcitrant OM is not a simple process and may vary depending on a number of factors (microorganism type, environmental conditions and initial substrate quality) and indeed the bioavailable classification may be better described as a continuum of labile to recalcitrant OM. This continuum is linked to the macro OM components defined by the macromolecular quality, which is defined by the types and proportions of major structural components in the OM, e.g. carbohydrates, proteins and lipids, as well as fractions such as lignin, which is specific to some types of plants. Biochemical quality is the macro, micro and molecular structures that make up these macromolecular components and ultimately determines the number of enzymatic steps taken to remove a C atom from its surrounding structure, linking back to thermodynamic quality.

A hierarchy of OM composition can be defined (Figure 3). This consists of, in descending order: the elemental composition making up a single sample of OM; the functional groups contained in macromolecular structures and whether they are arranged in an aliphatic or aromatic manner, or a combination; the major organic components such as cellulose, lignin, carbohydrates, proteins and lipids; and finally how these components were formerly organised to form an original organism or organisms.

Figure 3.

Biochemical hierarchy divided into macro, micro and molecular structures.

This classification of approaches to understanding OM quality provides a framework to consider the ways in which an understanding of OM quality can contribute to understanding in Physical Geography. There are an abundance of studies that involve investigations into OM quality although they may not explicitly state that this is the intent. This paper does not attempt to provide a comprehensive review, but aims to highlight areas of potential application, emphasising the importance of quality by exploring studies that have used techniques that should become more standard and widespread in Physical Geography.

2.1 Decomposition dynamics

Plant decomposition involves physical, chemical and biological processes (Kelleher et al., 2006) and may be defined as mass loss during mineralisation causing selective transformation of labile compounds, and preferential preservation and residual enrichment of recalcitrant compounds (Biester et al., 2013). However some (e.g. Von Lutzow et al., 2006) argue that rather than the selective preservation of recalcitrant compounds in the process of OM stabilisation, stable compounds are altered by biological activities and a series of chemical reactions on the partially broken down compounds, which leads to the production of complex, decay-resistant secondary compounds (Grandy and Neff, 2008). Thus, decompositional processes not only alter the quantity of OM, but also the composition (Koiter et al., 2013). The composition of the OM at various stages of decomposition in terrestrial and marine ecosystems is dependent on the stability of the OM (recalcitrance and physical mechanisms of protection) and environmental factors that affect the rate of decomposition and the duration of exposure to processes of decomposition (Baldock et al., 2004). Some integral environmental factors include temperature, redox, pH and an available substrate; decomposition dependent on these factors being suitable at the same location, at the same time. The factors that may influence decomposition dynamics in a particular setting depend on location in terms of type of sedimentary environment, geographical location and wider environmental characteristics.

The rate of decomposition of OM during soil development is commonly assessed through the litterbag technique. This permits measurements of mass loss from a fixed aliquot of OM over time and has resulted in comparative studies among different climatic gradients, litter types and treatments. A large number of such studies are compared in a meta-analysis by Zhang et al. (2008), which concluded that litter decomposition rates had substantial relationships with mean annual temperature and litter quality, with the latter being the most important regulator at the global scale. Studying decomposition rates continues to be vital for a number of reasons; decomposition is a critical ecosystem process, making nutrients available for consumption, and plays a role in mineralization of carbon with the release to the atmosphere as a possible pathway. However, Prescott (2010) argued for a change in the research focus of litter decomposition studies from studying rates to understanding the separate drivers of environmental factors, such as climate and soil to site-specific biological processes (original plant species and soil activity), with the aim of diverting the litter into humus or soil OM, accordingly averting its decay.

Understanding the wider drivers of decomposition is significant as the effects of climate change on decomposition pathways are unlikely to be similar among sites with varying litter quality (Parsons et al., 2014). According to kinetic theory, ‘low quality’ recalcitrant compounds with high activation energies should be relatively sensitive to temperature (Bosatta and Ågren, 1999; Davidson and Janssens, 2006; Wagai et al., 2013), implying that warming could disproportionately accelerate the decomposition of recalcitrant compounds. However, attention should remain on the study of thermodynamic response on labile OM as this is the major source of carbon dioxide to the atmosphere (Pautler et al., 2010).

Ziegler et al. (2013) showed that experimental warming in boreal forest soils induced changes in the microbial substrate routing. There were preferential increases in slow-turnover carbon pools such as compounds with low C:N ratios, thus changes may occur in the assimilable compounds for microbial uptake under warming in these environments. In addition to changes in temperature, (Billings et al., 2010) also calls for increased understanding into how elevated atmospheric CO₂ concentrations will modify the formation and decomposition of soil OC. Small changes in the formation and/or decay could result in large changes in the feedback to the atmosphere, but the lengthy turnover time of soil OC makes any effects difficult to study.

Prescott (2010) explores approaches that may help in diverting litter to recalcitrant, stable forms with the optimal strategy to have litter microbiologically transformed into recalcitrant humic substances and then chemically or physically protected in the mineral soil, which aids its residence time. The physical protection within aggregates or within other more recalcitrant molecules is perceived as an important mechanism in mineral soils to reduce the accessibility and bioavailability of OM (e.g. Kelleher and Simpson, 2006; Sollins et al., 1996; Von Lutzow et al., 2006).

The drivers of chemical change are poorly understood in comparison to the rates of decay in a range of environments, particularly those that are less organic, and provide a future pathway for physical geographers to explore. Furthermore, the hierarchy of importance of distinct drivers in shaping chemical characteristics during decomposition is unsatisfactorily understood. This is largely due to the difficulty in defining global averages because of the complexity of the ecological processes involved (Wagai et al., 2013). However, in contrast to soils, in peatlands, which are almost devoid of mineral matter, it is a reasonable assumption that chemical composition of carbon compounds is a major factor in defining OM decomposability (Hilasvuori et al., 2013). Dominantly organic soils therefore represent an ideal location to study decomposition dynamics with less confounding factors.

This research area arguably spans across all categories, with the thermodynamic, bioavailable and biochemical categories particularly relevant in many research themes here, examining the current and future drivers of the quality of OM over a variety of temporal and spatial scales and environmental conditions.

2.2 Carbon cycling and budgeting

Studies often quantify the proportion of carbon mineralised (Moody et al., 2013), rather than examining the processes that lead to carbon storage and the composition and structure of the carbon that remains. Another important research focus should also be to examine the organic compounds that are not mineralised to investigate whether there are certain compositional or environmental characteristics that make them more likely to resist photochemical and biological degradation, leading to storage. This is inherent in the aim of understanding the quality as well as the quantity of OM involved in the terrestrial carbon cycle.

Decomposition of plant biomass is a control on terrestrial CO₂ flux and ecosystem storage (Aerts, 1997). A key factor in determining rates of litter decomposition and subsequent carbon cycling pathways is temperature, with decomposition rates more sensitive than primary production rates (Kirschbaum, 2000; Schimel et al., 1994). Thus, carbon fixation in stable forms versus mineralisation is dependent on location in terms of current climate and the future climate (Fierer et al., 2005). For simplification purposes some ecosystem carbon models assume that the temperature sensitivity of decomposition is indistinguishable in OM. However, the Q10 (the factor by which a 10°C increase in temperature will increase the decomposition rate) can vary by up to 40% depending on the OM composition and the level of decomposition (Fierer et al., 2005). To gauge the impacts of potential climate change on terrestrial dynamics, we need to better understand the factors that control the temperature sensitivity of decomposition in a variety of systems.

Peatlands store substantial amounts of OM and thus represent an important focus of OM dynamics and mineralisation studies. During peat formation, labile OM is preferentially lost and more recalcitrant moieties accumulate with depth, partially related to compaction, water saturation and loss of gaseous exchange. Decomposition proceeds in the catotelm, but at a reduced rate, causing a general change in composition with depth from oxygen-rich compounds to aromatic compounds (Cocozza et al., 2003; Zaccone et al., 2008). However, changing land use and future climate change pose the risk of OM loss when formerly anoxic peat layers oxidise. Whereas organo-mineral associations provide a protection mechanism in some soils, in peatlands these mechanisms are less common; consequently, these ecosystems are particularly vulnerable to changing conditions (Fierer et al., 2005). Laboratory and on-site measurements of gaseous fluxes have been useful in the controls on decomposition in peat and similar sediment systems containing OM. In addition to temperature, water table position effects on carbon cycling may be studied using flask experiments measuring CO₂ and CH₄ efflux (Öquist and Sundh, 2009). Studies generally show that low water tables increase C mineralisation rates (Blodau et al., 2010). Quality-dependent carbon loss estimates from degraded peatlands may help to target management schemes aiming for preservation at vulnerable sites (Leifeld et al., 2012).

Floodplains represent a good example of less organically rich deposits, with relatively few studies that have analysed carbon storage in deposits at a range of scales (Battin et al., 2009; Hoffmann et al., 2010; Walling et al., 2006). This is mainly because of limited availability of data on global floodplain extent, sedimentation rates, duration of inundation and gas exchange velocities between floodplains and the atmosphere. This is an area where physical geographers, particularly fluvial geomorphologists who have expertise in understanding these sedimentary systems, can make a significant contribution. Resolving these uncertainties, and obtaining a better understanding of the fate of sediment associated carbon in systems such as these and their impact on the global carbon cycle, requires integrated investigations of carbon and sediment fluxes at the catchment scale (Hoffmann et al., 2010; Kuhn et al., 2009; Stallard, 1998).

It has become apparent that lateral fluxes of OC across terrestrial landscapes are substantial and require quantification, particularly those fluxes from agricultural soil erosion, resultant from climate and land use change, both at the sites of erosion and at redistribution (Quinton et al., 2010; Van Oost et al., 2007). Quinton et al. (2010) indicate that water, wind and tillage erosion cause the mobilization of 35 (+/–10) Pg of soil per year. This body of literature has been a subject of great debate about the fate of eroded soil OC and whether erosion contributes to an area becoming a net source or sink of carbon on the landscape scale (Kuhn et al., 2009; Lal and Piementel, 2008). The controversy surrounds the lack of spatial data and models to reproduce the transfer of OC down hillslopes and potentially into river systems (Kuhn, 2013). The effect of erosion on OC dynamics contrasts for sites of erosion, deposition and during transportation, with more considerations needed if agricultural practices have taken place on the land. Kirkels et al. (2014) promote an eco-geomorphologic approach, encompassing biological, pedogenic and geomorphologic processes integrated over these three landscape domains – eroding sites, the transport pathway along hillslopes and depositional sites – to link sediment, lateral and vertical carbon fluxes, and ultimately determine sink or source status.

Erosion exposes OC that was previously incorporated in soils and sediments to processes that may increase the likelihood of degassing to the atmosphere. Soil erosion has been shown to have the potential to become a process that results in a net sink of C to the terrestrial system (Berhe et al., 2007) because: (1) new vegetation can establish on the eroded surface, incorporating carbon from the atmosphere into its structure and partially replacing carbon that was lost, which is known as dynamic replacement (Harden et al., 1999); and (2) depositional sites potentially have reduced short-term rates of decomposition due to the removal of processes that readily mineralise carbon in surface positions by burial (Berhe et al., 2012). If these two effects can neutralise losses from erosion, and even produce carbon gains, then soil erosion can become a positive factor for carbon sequestration. However, a question that arises is whether processes during transportation from site of erosion to site of deposition negate this potential for carbon sequestration, and whether carbon benefits are likely at the landscape scale rather than being limited to localities.

Deposits relating to hillslope processes, such as colluvial accumulations, have perhaps received even less attention than floodplains with regard to the study of carbon storage and cycling (Berhe, 2012). Relatively little is known about rates of OM decomposition along catenas, which often represent substantial sources of soil erosion to the surrounding environment. If little is known about the rate of decomposition, then there have certainly been even fewer studies into the OM quality across catenas. Colluvial accumulations in particular are interesting as soil OC may become enriched due to transportation from areas subject to erosion upslope (Hu and Kuhn, 2014), but what happens to this accumulation prior to deposition (mineralisation versus burial) is dependent on microclimate and other environmental conditions.

Measurements of carbon fluxes prior to, and after, erosion can be assessed relatively simply. However, the rates of decomposition in varying landform positions have not been as thoroughly studied. The usual assumed relationship of decreasing rates of decomposition with depth in soil profiles may not be as straightforward in dynamic hillslopes where large lateral fluxes are experienced (Berhe, 2012), and may cause issues when modelling soil OC dynamics. Soil characteristics and physicochemical properties, in addition to the geomorphology, can vary considerably with depth and are variable between different landform positions (i.e. low lying depositional landforms in comparison to hillslope landforms). Factors that may vary based on these positional criteria include: slope and curvature of the profile; soil texture, drainage and thickness. Therefore the position of OM in terms of both depth and position along a catena can affect the decomposition rate and, in turn, affect OM quality.

The debate surrounding natural and agricultural soil erosion, and whether this induces a carbon source or sink, requires more research. It is clear that a better understanding of both the quality and quantity of OM are needed in relation to erosional processes, transportation processes, depositional processes and post-depositional changes with regard to the effect on global carbon cycling. Whether the combination of hillslope erosion and colluvial deposition become an active (net source) or passive (neutral or net sink) process in the local carbon cycle depends partially on the quality of the organic material that is eroded, transported and subsequently deposited. If the eroded material is labile it has greater potential to be released as a greenhouse gas and alter the cycle more than the ability that dynamic replacement has to neutralise the loss. Thus, examining the quality of the material involved in lateral transport is important and techniques that identify labile versus recalcitrant material may aid with the calculation of mass flux balances.

Carbon budgets could thus be enhanced by considering OM quality. Failure to address the quality of C in soils and sediments, and consequently the longer term fate of that material, may result in uncertainties over whether a system is a carbon sink or source, and account incorrectly for both lateral and vertical fluxes. It is a reasonable assumption that the quality and quantity of OM will vary with depth and position in a sediment system and therefore simply classifying sediment from the surface is not adequate.

In order to contribute to an increased understanding of carbon cycling and storage in soil and sedimentary environments it is important to understand why OM decomposes and how this happens; primarily, what structural and chemical changes occur and what mechanisms control storage versus mineralisation. It is increasingly important to predict the effect of global climate change on sedimentary OM for the development of management approaches to enhance sequestration in ecosystems and to produce accurate estimates of carbon cycling and budgeting (Marschner et al., 2008), with interdisciplinary approaches vital in understanding how to manage the stability of existent recalcitrant OM (Lorenz et al., 2007). It is particularly clear that more work is required to investigate landform position and burial depth on both rate of decomposition and changes in chemical composition of the decomposing OC in areas that experience substantial lateral fluxes, such as on agricultural hillslopes.

Figure 4 identifies characteristic sedimentary environments that make up landscapes. These landscapes can be classified in a number of ways: topography and relief; hydrology; sediment type, but form logical categories within a landscape. For example, floodplains, wherever they may be in terms of geographical location, have factors in common that enable them to be classified as a single unit in their ability to cycle carbon. A key control within this environment is the type of microbial communities that process carbon, which in turn is associated with the oxygen status. A further key control is the length of time that microbes have to act on OM. Therefore, in theory, material of the same age can be of a different composition depending on the environments that the material has been transported through or deposited in.

Figure 4.

Key landscape contexts where carbon cycling or storage is important. a) Carbon turnover potential is dominantly hydrologically controlled by the position of the water table. This affects the boundary of the acrotelm and catotelm and therefore the oxidation/reduction status. b) Carbon turnover potential in this landscape is partly topographically controlled. The steeper the landscape, the stronger the likelihood of lateral redistribution of carbon to colluvial footslope landforms due to their preferable topographic position. Dynamic replacement may occur to return this system into equilibrium or even initiate carbon gains. c) Carbon turnover potential is high in fluvial environments where conditions are suitable for particulate and dissolved OM to be transformed to gaseous C. Floodplains may be hotspots of C cycling with potential for both mineralisation and storage, dependent on hydrological, sedimentological and climatic conditions. Floodplain environments also provide mineral material which may form aggregates to protect OM from microbial action. d) Lakes and reservoirs can be dynamic environments with autochthonous OM production, reworking, mixing, storage and gaseous release.

Thus, the key controls which these environments have in common, with relation to OM cycling and decomposition, are their oxidation status and residence time. Approximations of where these specific sedimentary environments reside with regard to oxidation status and residence time is displayed in Figure 5. Evidently, this may vary both between the same type of landform and within an individual landform depending on environmental characteristics and position. Fluvial systems have a high oxidation status and a short residence time, thus POC and DOC may be converted to gaseous forms rapidly. They therefore have a low preservation potential of the original OM input to the system, as even if the input material is recalcitrant, the OM is likely to be evaded to the atmosphere in a gaseous form because of rapid photodegradation and microbial processes. OM stored in colluvial deposits generally has a short residence time because of unstable topography; however, oxygen status can vary based on sediment wetness and the height of the water table. Floodplains have low gradient surfaces, but are susceptible to erosion from fluvial action. They typically have a longer residence time than colluvial deposits. Floodplains are complex environments, which in theory have relatively high water tables that limit oxidation in comparison to colluvial footslope deposits. However, as they are exposed to fluvial action, the sediments have the potential to be reworked and exposed to oxic conditions, including that from the frequent inundation of oxic waters during periods of flood. Thus floodplains may have a wide variation in oxidation status. Colluvial footslope deposits have a higher residence time as they are present on relatively flat topography and protected from fluvial action by floodplains. They are likely to have higher water tables than hillslopes due to drainage from upslope, but are not typically perennially saturated so that OM within the profile is exposed to aerobic microbial processes. OM in peatlands generally has the longest residence time with oxidation restricted based on a high water table. These environments thus have a high preservation potential of the original plant matter as high water tables limit oxidation, resulting in minor gaseous release and changes in quality. Clearly there are more than two key factors involved in the controls on carbon cycling in these environments. For example, sediment type has not been discussed as a key control, but remains important as the presence of mineral material in some of these systems can lead to the formation of aggregates that protect OM and make it less bioavailable. However, this simplification is an effective representation that shows how these landforms may be classified. Fluvial systems have a low preservation potential of the original input, whereas peatland systems have a high preservation potential. This scale may aid in selecting which environments should be the focus of management and restoration to improve preservation potential, with those environments that lie in the centre being a particular priority.

Figure 5.

Key landforms/environments in relation to their oxidation status and residence time. Landforms are represented by irregular shapes to show the range of variation within a landform type. Preservation potential of the original OM input to the environment is inferred, with those environments in the top left having a low preservation potential and those towards the bottom right having a high preservation potential.

Research on carbon cycling and budgeting fits into the bioavailable category primarily as it is whether the OM is bioavailable, and consequently rapidly turned over, that will primarily determine whether a landform is a carbon sink or source. This in turn is dependent on the biochemical category as it is the functional groups available to microorganisms that determine the extent of the bioavailability. The factors that control oxidation status and residence time in different systems are also worthy of substantial investigation.

2.3 Source determination

Sediment fingerprinting has become a commonplace term used within environmental science literature to attempt to differentiate the source of sediment that is stored or is in flux in a particular environment. The ability to determine the provenance of sediment may be broadly grouped into tracing or fingerprinting studies, based on contemporary and palaeo- approaches respectively. Sediment tracing infers tracking sediment movement in a downstream direction to determine a temporary or final resting point, whereas sediment fingerprinting refers to working in an upstream direction to determine the origins of a sediment sample or system (Koiter et al., 2013). A range of techniques involving the inorganic fractions of sediment are used to attempt to determine the provenance of the sediment, including the magnetic and geochemical signature, which must be compared to potential sources at catchment level and beyond depending on the scope of the sedimentary environment. The organic component may also provide a viable fingerprinting technique within the environment, with biomarkers emerging as particularly powerful in distinguishing between marine and terrestrial provenance in sediment in marine environments (Meyers and Ishiwatari, 1993).

A biomarker is typically a compound or a set of compounds whose structure or compositional distribution can be correlated with origin. Biomarkers are molecular fossils (Belicka et al., 2009; White et al., 2008) associated with specific organisms or specific sets of organisms; they must be stable and difficult to degrade or mineralise. During diagenesis, biomarkers undergo the same main types of reactions as other biogenic organic compounds – defunctionalisation, aromatisation and isomerisation (Killops and Killops, 2004) – but, despite this, most biomarkers stay relatively intact so that they are distinguishable. A combination of biomarkers may be adequate to recognise a sedimentary input of a family or potentially, if distinct enough, a species, as long as it can be proven that this combination does not result from combined contributions of several organisms (Killops and Killops, 2004). It is challenging to quantify absolute inputs from biomarkers alone as this would require information on the abundance relative to total OM, and this has the potential to have changed through time relative to environmental conditions. Usually biomarkers are lipids (n-alkanes, sterols, fatty acids) with their utility extended and validated by correlations with carbon isotopic composition data and C/N ratios (Horst et al., 2013).

Source determination in marine systems is made easier by the fact that terrestrial plants have specific molecular components which differ from marine plants. But what about source determination in environments where OM input is solely terrestrially derived, but still comes from different sources? In certain environments where autochthonous OM is produced, there may be additional allochthonous, fluvial- or aeolian- derived inputs of OM. Is it possible for these two different types of terrestrial material to be distinguished? This certainly represents a pathway of future investigation and will depend on the complexity of the system and whether distinctive biomarkers are present at source sites and remain intact upon transport and subsequent deposition. Table 1 examines some potential biomarkers that may suit this purpose.

Table 1.

Biomarkers that may indicate source.

System	Biomarkers	Interpretation	Problems
Marine versus terrestrial or aquatic (water-bodies – non-marine) versus terrestrial (see Meyers and Ishiwatari, 1993; Meyers, 1994, 1997)	Lignin and cutin.	Unique to terrestrial plants. Gymnosperms and angiosperms synthesise different types of lignin allowing identification.	The problem with all of these techniques is the extrication of the effects of diagenetic alteration versus source determination. Decomposition can occur at all stages through transport to final resting point, with the potential to acquire altered characteristics to an extent where they may no longer reflect their original source (Koiter et al., 2013). Techniques are therefore often used in combination.
	C/N ratio.	Algae ratios of 4:10, terrestrial higher plants > 20. This divergence arises from two factors: the absence of cellulose in algae, and, in contrast, its abundance in terrestrial plants, and because algae are protein rich, thus having more N.
	Lipids, n-alkanes, sterols, fatty acids and pigments.	Some may indicate biological origin of aquatic versus terrestrial plants. See Meyers and Ishiwatari, (1993) for a detailed review.
	C and N stable isotopes.	Different carbon assimilation pathways. Freshwater algae generally utilise dissolved CO₂, which is usually in equilibrium with isotopic CO₂. However, in marine environments, algae often utilise dissolved bicarbonate which has a different isotopic ratio. Incorporation of dissolved nitrates versus atmospheric N in aquatic and terrestrial plants. The two different N reservoirs differ in isotopic ratios.
	Rock Eval pyrolysis.	H/C and O/C ratios derived from the results of this technique may reveal three types of OM in a van Krevelen plot distinguishing between waxy coatings of land plants, algae and woody plants based on hydrocarbon and carbohydrate content.
Terrestrial systems	4-isopropenylphenol (unique to sphagnum acid). Sphagnum grows in waterlogged sedimentary systems such as peatlands; see (Van Smeerdijk and Boon, 1987) and (McClymont et al., 2011).	Sphagnum acid is a biomarker and could have potential use as a tracer in some environmental systems, e.g. floodplains, lakes and reservoirs downstream of peatland systems.	Dependent on whether the species has grown in the system of interest in the past. For example, Sphagnum may grow on floodplains if the conditions are suitable. These biomarkers may also simply indicate presence or relative quantities between samples and thus may not provide robust quantification. In addition, specific compounds are limited to specific geographical areas.
Terrestrial systems	Some pasture species have unique compounds, e.g. Arctotheca calendula (capeweed) contains an as yet unidentified compound (m/z 163). Other pasture species that do not contain unique compounds do contain unique ratios of some compounds, enabling their identification (see Nash et al., 2005).	Unique compounds may allow source determination in some environmental systems.

Understanding carbon source is important in creating meaningful carbon budgets (Belicka et al., 2009) in addition to gaining general palaeoenvironmental information. It is important to use a combination of organic markers just as would be done with the minerogenic component, analysing for a composite fingerprint in order to determine whether the mixture is unique. It is clear that unique biomarkers that indicate different terrestrial sources are lacking and may continue to present a complex problem. In this case, minerogenic source determinations may be of more use, but continued research into potential terrestrial biomarkers deposited in terrestrial systems is needed. Most source determination research using OM clearly fits into the biochemical classification as it is often dependent on investigation at a molecular and structural level.

2.4 Aquatic environments

OM is ubiquitous in the aquatic environment with both quantity and quality central to the functioning of these environments, affecting biochemical and biogeochemical pathways in aquatic organisms and ecosystems (Stedmon et al., 2003). Steinberg et al. (2006) argue that humic substances are active environmental chemicals interacting with aquatic organisms and, as such, need to be quantified and chemically characterised as they may be controlling factors as important in aquatic ecology as nutrients, temperature or even light.

Thus characterising OM is important for understanding its role in ecosystem functioning, mobilising or mediating pollutants and its effects on drinking water treatment (Dawson et al., 2009). As OM is transported from source through the aquatic system, the concentration and structure reveal the source composition and distance downstream along the continuum (Fellman et al., 2009). In the past, models that consider trophic networks have solely focused on global descriptions of OM, which do not take into account temporal variations and, indeed, the level of prior decomposition. On a seasonal basis there may be variations in the types of OM delivered and consumed in these ecosystems. Differences in OM quality at a range of spatial scales are another important consideration for these models (Gremare et al., 1997). Sediment traps may be employed in all aquatic environments to study changes in the composition at a variety of contemporary temporal and spatial scales.

The reported increasing trend of DOC concentrations in surface waters of some regions has been a research focus in recent years, but ambiguity remains in demonstrating a global trend and causation (Evans et al., 2005; Roulet and Moore, 2006). It is a reasonable assumption that the mechanisms creating changes in the quantity of DOC could also cause changes in the quality (Dawson et al., 2009); however, less interest has been placed on whether the quality is changing and why that would be. Understanding the implications of these increases, and the potential changes in chemistry of OM delivered to surface waters, requires knowledge of the baseline state of these systems, which has so far proved difficult to reconstruct. This trend has been monitored for approximately 25 years in the most comprehensive scenarios (Evans et al., 2005); however, quality measurements that correlate are rare. Although monitoring studies are useful, they are limited on a temporal scale, with palaeo-reconstructions of OM providing an opportunity to monitor past trends in both quality and quantity (Rosén and Hammarlund, 2007; Rosén et al., 2009).

The opportunity to examine palaeo-trends in OM quality in aquatic environments exists in the form of lake, reservoir and fluvial sediments, which have been long established as providing excellent records of environmental change (Mackereth, 1966; Oldfield, 1977). Lakes and reservoirs in particular are C sequestration hotspots due to low decomposition rates and high terrestrial carbon inputs, with C storage inversely proportional to lake size (Cole et al., 2007; Downing et al., 2006; Kortelainen et al., 2004; Mulholland and Elwood, 1982; Von Wachenfeldt and Tranvik, 2008). Despite the importance of C cycling in these environments, the mechanisms that actually regulate C storage, both currently and in the past, still need to be constrained. Sequestration in aquatic systems is primarily due to anoxia because of the lower energy yield available to heterotrophs per unit of substrate consumed and restricted attack by reactive oxygen species (Bastviken et al., 2004). Yet there are other factors playing a role in impeding decomposition in these systems, including nutrient availability and pH. Boreal lake databases have shown that both CO₂ and CH₄ concentrations and mineralisation to the atmosphere are closely linked to lake nutrient status (Kortelainen et al., 2006).

Areas of sediment deposition may be dissimilar, and the origins and post-depositional processes of OM are spatio-temporally irregular, thus a basic global description of what happens to the properties of OM during diagenesis after burial are not available. Despite the importance of OM in surface water systems, the specific structural transformations occurring during sinking within a waterbody and early diagenesis remain largely unknown (Pawson et al., 2012) and can be difficult to study, particularly in the sediment–water interface as the use of equipment provides a perturbation in this sensitive environment. The combined analysis of the quality of OM deposited in sediment traps in comparison to OM quality in sediment accumulation from a core can provide useful comparisons (Gälman et al., 2008).

An example of reconstruction from OM in aquatic sediment records exists in the development of molecular approaches to study palaeohydrology, of which an excellent review is provided by Sachse et al. (2012). Palaeohydrology may be reconstructed as water is the primary hydrogen source of photosynthesising organisms and thus is believed to record the isotopic composition of water used during photosynthesis (Estep and Hoering, 1980). However, as previously established, OM is a complex mixture and, as such, different compounds may have different isotopic compositions because of different biosynthetic pathways (Schimmelmann et al., 2006). Accordingly, bulk sedimentary matter presents a problem in establishing robust palaeohydrological records (Krishnamurthy et al., 1995), but, as organic compounds can be separated, lipids have been discovered as a promising proxy. Furthermore, combined with multiple proxies of both organic and minerogenic forms, erroneous factors including certain biological processes or changes in vegetation may be accounted for.

Perhaps the most relevant categories in studies involving OM in both contemporary and palaeo aquatic environments are biochemical and bioavailable. The biochemical characteristics may allow reconstructions of palaeohydrology, for example, whereas in contemporary approaches it is often extremely important to consider how the bioavailability may change over time for organisms that reside in aquatic environments.

2.5 Palaeovegetation and climate

Organic components of sediments are often used in palynological studies to make inferences about palaeoclimate and palaeovegetation, as pollen is resistant to decay due to the sporopollenin outer sheath, but less focused upon are other organic components of accumulated sediments. However, in peatlands organic geochemistry has been heavily used in palaeoclimate and palaeovegetation studies due to their naturally dominant organic composition. The molecular composition of OM is often used as a proxy for past environmental conditions and biomarkers are not restricted to source determination. Some may be able to indicate environmental parameters, such as temperature, humidity and salinity. A comprehensive review of organic macromolecules that may provide biomarkers is provided by De Leeuw et al. (2006).

Some investigations of peat species have demonstrated the potential for biomarker analysis to be applied to gain both palaeohydrological and palaeoecological information. C and N isotope ratios have also been used as a sign of decomposition processes in peatland systems, as changes are assumed to reflect isotope fractionation by microbes because of preferential consumption of ¹²C (Kalbitz and Geyer, 2002). However, as changes in flora, microhabitat or climate also affect δ¹³C, their understanding with reference to decomposition or palaeoenvironment requires caution (Pancost et al., 2003).

The interpretation of peat profiles and extricating driving factors is intricate (Yeloff and Mauquoy, 2006). Despite this, studies have been successful in interpreting records with Biester et al. (2013) successfully disentangling decomposition processes and vegetation changes using a wide range of techniques. The assumptions and techniques applied to determine palaeoenvironmental information in peatlands may be able to be used in other environments, although, naturally, this may become even more complex once mineral matter is considered. These types of studies naturally fit into the biochemical category, as most types of analyses for determining palaeoenvironmental information require molecular studies of biomarkers (with increased age there is a strong likelihood that most OM will have been utilised by microorganisms, leaving only the most recalcitrant OM).

Pollen and other plant macrofossil analyses produce information about vegetation assemblages at high taxonomic resolution (Battarbee, 2000), but, due to a variety of pollen representation issues, the information may be only semi-quantitative at best. However, with the addition of other OM properties, such as δ¹³C, C/N ratios and specific biomarkers, additional quantitative information may be provided that aids interpretation but, conversely, is able to provide poor taxonomic resolution (Herzschuh et al., 2005). Thus, not negating the effects of pollen and other macrofossil studies, the addition of the study of other aspects of OM quality may aid the interpretation of sediment records for a variety of purposes. The most appropriate classifications here are, again, biochemical classifications, with the consideration of the bioavailable category as it must be remembered that in all likelihood labile material has long been removed in old sediment records and thus will never be able to provide a full environmental interpretation.

2.6 Pollutants

Fine-grained minerogenic and organic sediments are well known to have a high affinity to transport pollutants and nutrients (He and Walling, 1996). Terrestrial and marine environments receive high loadings of metals from anthropogenic and natural sources (Galloway et al., 1982). Excessive concentrations of trace metals in OM can both constrain decomposition and limit nutrient availability (Brynhildsen and Rosswall, 1997) as OM is a strong complexing agent for metals, affecting their solubility, transport and toxicity (Hope et al., 1994). In eroding terrestrial environments dominated by organic sediment, the increases in the quantity of organics may be accompanied by increases in contaminants, including metals (Frangipane et al., 2009). In addition, OM has been shown to play a key role in mediating the release of As to groundwater systems (McArthur et al., 2004).

Hence it is of utmost importance to extend traditional sediment studies, which are generally interested in the quantity of OM, to also examine chemical compositions and structures of sediments containing organics (Ballantine et al., 2008; Van Dongen et al., 2008). In addition, litterbag experiments have indicated that metals such as Al, Fe and Pb that form stable compounds with OM can become naturally enhanced through the first few years of SOM decomposition as carbon is oxidised (Kaste et al., 2011). In this context, OM quality is defined by its structural ability to provide a high affinity for pollutants. Physical geographers need to know about the quality of OM in order to deduce why certain types of OM may be more important vectors or mediators of pollution than others.

It is clear that study of chemical structures that bind pollutants is a component of the biochemical category of OM composition. One interesting application of this approach would be to consider whether it is possible to manipulate OM condition in the environment to manage metal storage. This would require first identifying samples that are heavily and minimally contaminated by metals, and then using techniques that allow the examination of organic functional groups and structures that may be associated with these contaminants in particular environments. There is pre-existing knowledge on the types of organic structures that do bind to trace metals (Chen et al., 2002; Kumpiene et al., 2008; Reuter and Perdue, 1977; Rottmann and Heumann, 1994).

III Available techniques for the determination of OM quality

Most OM present in terrestrial or surface water environments is in macromolecular structures that cannot be examined at a molecular level without a degradative step. Examination encompasses thermolytic and / or chemolytic degradation of macromolecules into small fragments that are separated and scrutinised by chromatographic or colorimetric methods. Secondary reactions (rearrangement, cracking, hydrogenation and polymerisation) may transpire, and consequently deductions concerning the original structure have to be drawn with care (Kogel-Knaber, 2000). In the first instance, it is useful to determine the kind of structure that is of primary interest, i.e. macro (main groups) versus micro (functional groups) versus molecular (elemental groups).

In conventional decomposition analyses, macromolecular components are measured by extraction methods appropriate to the chemical individualities of the sample in question (Kelleher et al., 2006). Various chemical and physical fractionation processes have been developed to separate the entire organic fraction of sediments into reduced fractions that are indicative of biologically significant pools of OM with different turnover times. Settling velocity is a physical fractionation technique that could be used to understand soil OC redistributions and mimic the spatial distribution of OM (Hu and Kuhn, 2014) as this is largely related to transport distance of eroded aggregates. The settling velocity of aggregates is dependent on actual size (not just mineral particle size), shape, porosity of soil fractions and their incorporation with OC (Kinnell and McLachan, 1988). Aggregation may increase the settling velocity of soil particles and reduce transport distances, making it more likely soil would stay within the terrestrial system and not reach the aquatic system (Hu et al., 2013), which has implications for the likelihood of storage versus mineralisation.

With regard to chemical techniques, humic, fulvic and humin fractions are commonly separated based on their solubility in acid and base; however, Baldock et al. (2004) describes the connection of these fractions to biological processes as feeble, with other physical fractionation schemes linked to particle size and density. This type of analysis is useful, but reveals little information as to the structural transformations taking place (Kelleher et al., 2006). Thermolytic cleaving techniques may remove the signal of macro variability, thus careful selection of the classification of interest must be selected. The studies discussed above use a variety of techniques to characterise OM quality in different environments with the selection of technique or techniques dependent on the specific information required. In this review, chemical extraction techniques are not examined, only techniques that allow a bulk sediment sample to be analysed are examined, and categorised in Table 2.

Table 2.

Classification of available methods to assess organic matter quantity and quality.

Method	Classification	Description	Interpretation	Cost	Time	Advantages	Difficulties	Relevant studies
Quantification
Loss on Ignition.	None (quantification only).	Destruction of all OM by heating, with gravimetric determination of weight loss before and after.	Estimate of OM in a sample and a rough estimation of OC content may be derived.	Inexpensive.	Rapid.	Rapid and simple determination. Furnaces are inexpensive in comparison to CHN or TOC analysers.	Semi-quantitative determination of C content by the conventional ‘Von Bemmelen’ factor. Loss of structural water may increase weight loss. Mass loss also from inorganic C.	(Frangipane et al., 2009).
Total organic carbon (TOC), dissolved organic carbon (DOC) and particulate organic carbon (POC).	None (quantification only).	Sum of total OC, dissolved OC and particulate OC. DOC operationally defined as OM that may pass through a 0.45-μm filter. After extracting the desired fraction, a TOC analyser is used.	A quantitative estimation of OC may be derived.	Moderate.	Rapid.	Robust quantitative estimates in solution or solid samples.	Quantitative, but no information about the composition or structure.	(Matilainen et al., 2011)
Biodegradable dissolved organic carbon (BDOC).	Bioavailable.	Introduce bacteria to a dissolved OM sample and measure DOC concentration before and after.	Allows knowledge on the amount of DOC assimilated and perhaps the quality of the sample could also be examined before and after using an alternative technique, e.g. Pyrolysis GC-MS.	Moderate.	Design dependent.	Quantitative estimates of bioavailable carbon.	Requires additional techniques to learn what OM has been assimilated by bacteria.	(Fellman et al., 2009; Marschner and Kalbitz, 2003; Servais et al., 1989)
CHNX elemental analysis.	Bioavailable, biochemical. macromolecular.	Determination of mass fractions of C, H, N and X (e.g. halogens, sulphur) of a sample.	Derivation of C/N ratio. Microbial decomposition preferentially degrades C and H rich compounds, causing a decreased abundance of C relative to N as decomposition progresses.	Moderate.	Rapid.	Accurate, quantitative determinations of key components of OM.	No structural information provided. Inorganic C and N issues. Other techniques needed to support conclusions.	(Meyers, 1997).
Spectroscopic
Fourier Transform Infrared Spectroscopy (FTIR).	Biochemical, bioavailable, macromolecular.	Infrared radiation instigates molecular vibrations, which are subsequently absorbed at specific wavelengths.	Used to distinguish principal functional groups in OM. Relative abundances can be compared; recalcitrant moieties, such as aliphatics or aromatics, compared to labile fractions such as carbohydrates can thus be identified.	Inexpensive.	Rapid.	Relatively inexpensive and rapid results gathered. Often best as a preliminary technique for comparison purposes between samples. Possibility for remote sensing applications for Near Infrared (NIR) and Shortwave Infrared (SWIR) (McMorrow et al., 2004).	Quantitative information difficult to obtain.	(Cocozza et al., 2003; Artz et al., 2008; Broder et al., 2012).
¹³C Nuclear Magnetic Resonance (NMR).	Biochemical, bioavailable, macromolecular.	Measures shifts in the frequency at which atomic nuclei resonate relative to a reference when subjected to an external magnetic field. Range of more specialised techniques including cross-polarisation and high resolution magic angle spinning NMR.	The spectrum is generally split into four main regions indicating functional groups (carbonyl, aromatic, O alkyl, and alkyl) with the area of a specific region proportional to the amount of that group.	Very expensive.	Time consuming.	The entire analytical structure may be analysed without extraction. The technique is non-destructive.	Poor quantification, no structural information obtained, ambiguous assignments caused by overlapping chemical shifts, paramagnetic cations may interfere and prior demineralisation may be needed.	(Baldock et al., 2004; Kelleher et al., 2006; Dickens et al., 2011; Mao et al., 2011; Spence et al., 2011).
Thermal degradation (see Plante et al., 2009).
Thermogravimetric Analysis (TGA).	Thermodynamic.	Measures precise mass change of a sample over time as a function of temperature in an atmosphere of N, air, an inert gas or a vacuum.	Assesses thermal stability by enforcing chemical reactions and physical changes. Records the dehydration, decomposition and oxidation points allowing characterisation of unknown samples against characteristic thermogravimetric curves for known materials caused by physicochemical reactions occurring over specific temperature ranges and/or heating rates.	Inexpensive.	Moderate.	Inexpensive, rapid, reproducible.	Not all reactions associated with a change in mass.	(DeLapp et al., 2004; Frangipane et al., 2009).
Differential Thermal Analysis (DTA).	Thermodynamic.	Differences in temperature between samples and an inert reference material are recorded while samples are heated at a constant rate in a controlled atmosphere.	Changes in sample are attributed to endothermic or exothermic phase transitions occurring in the sample such as glass transitions, crystallization, melting and sublimation.	Inexpensive.	Moderate.	Inexpensive, rapid, reproducible.	Incapable of quantifying enthalpy. No information on mass change.	(Rovira et al., 2008).
Differential Scanning Calorimetry (DSC).	Thermodynamic.	The difference in the amount of heat required to increase the temperature of a sample and reference over a set temperature programme is measured as a function of temperature.	Allows the examination of the energy required for phase transitions to occur.	Inexpensive.	Moderate.	More sophisticated as it also allows the heat flow to be measured. Measurement of specific heat capacity possible.	No information on mass change.	(DeLapp et al., 2004; Merino et al., 2014; Plante et al., 2011).
Molecular
Pyrolysis Gas Chromotography-Mass Spectrometry (Py-GC/MS).	Biochemical, macromolecular.	Uses heat to break large macromolecules into smaller molecules and a gas chromatograph (GC) coupled to a mass spectrometer (MS) to separate, identify and quantify complex mixtures.	It gives a molecular fingerprint of the sample thus enabling inferences to be made about past vegetation and decomposition.	Expensive.	Time consuming.	Only a few mg of material needed. Provides detailed interpretations. Allows qualitative or quantitative interpretation.	Difficult and time consuming data interpretation. Destructive. Some unwanted thermal reactions may occur.	(Carr et al., 2010; Schellekens et al., 2009).
High Pressure Liquid Chromatography Mass Spectrometry (HPLC-MS).	Biochemical, macromolecular.	A pressurised liquid solvent containing the sample is injected into a column filled with a solid adsorbent material such as silica beads. Components are separated via their interaction with this medium and the timing of these reactions is measured by an MS.	Similar to Py-GC-MS, the technique allows molecular identification of components within an entire sample.	Expensive.	Moderate.	Capable of analysing a wider range of components in comparison to Py-GC-MS, e.g. those that are thermally labile, exhibit high polarity or have a high molecular mass.	Difficult and time consuming data interpretation.	(Hopmans et al., 2004; Lepane et al., 2010).
Other
Rock Eval Pyrolysis.	Biochemical.	Pyrolysis in an inert atmosphere and combustion in an oxic atmosphere involving progressive heating to release different fractions of hydrocarbons.	H and O indices are derived. In turn these indices are proxies for H/C and O/C ratios. These parameters may help in identifying biological source and level of decomposition.	Moderate.	Rapid.	Rapid screening technique that may derive TOC but additionally provide environmental information.	Need to combine the technique with other tools to avoid misinterpretation, particularly in terms of source determination.	(Carrie et al., 2012; Delarue et al., 2013; Luniger and Schwark, 2002).
C and N isotopes.	Biochemical.	Measured through isotope ratio MS. The sample is purified so that only the C or N species remain usually via combustion or pyrolysis.	C and N isotopes may aid source interpretation between marine and terrestrial plant sediment sources. Plants have varying isotopic C compositions due to different C photosynthetic pathways. Decomposition may also be recorded by isotopic ratios as different OM components have varying isotopic ratios and components are degraded at different rates.	Expensive.	Time consuming.	Can provide information about both changing source and decomposition.	Needs to be combined with other analysis to avoid misinterpretation. Potentially complicated interpretation.	(Higueras et al., 2014; Kalbitz and Geyer, 2002; Meyers, 1997).

As is evident from Table 2, there are a wealth of techniques available for analysing OM quality with the choice of technique(s) dependent on the aim of the study, availability of equipment, cost permitted and time required to obtain results. Generally, at an increasing molecular level the skill and knowledge of the operator and interpreter will also increase. With chromatographic techniques in particular, more skill is required to operate the instrument, interpret results and problem solve. It is clear that there is no perfect technique and, within environmental studies, rarely is one technique used as a standalone. However, the combination of multiple techniques may allow robust interpretations of the different types of OM character outlined in this paper.

IV Conclusions

At the beginning of this paper it was stated that a definition for OM quality remains elusive as it has different meanings to different research groups. It is evident from this short discussion that OM quality of a sediment sample at a particular moment in time is dependent on a number of factors including: original composition; age; level of decomposition; duration and type of environmental factors exposed to; degradation pathways – microbial or macrofaunal. The study of OM quality in relation to these factors is vital in many research areas that have relevance to physical geographers, and in fact there are a number of techniques that may be used to ‘measure’ this abstract property.

The biochemical and bioavailable categories appear to be the most relevant to studies involving physical geographers (Figure 6). The macromolecular category has not been mentioned often as the determination of the absolute quantities of the components that make up the macromolecular category often require wet chemistry techniques; however, inferences may be made on the relative proportions using some molecular techniques, such as Py-GC/MS. The thermodynamic classification has perhaps appeared the least in these discussions, with the thermal degradation techniques exploring the reactions that determine thermodynamic quality coming the closest to examining this category. This category still remains relevant to physical geographers as energy flow is fundamental to the functioning of individual organisms, and ecosystems as a whole, and may be explored using other techniques, such as bomb calorimetry.

Figure 6.

Exemplars and techniques placed on the OM quality classification diagram.

Understanding OM environment dynamics is becoming especially pressing as OM in soils and sediments are likely to be exposed to rapid and unevenly distributed changes in temperature, precipitation and land use. Studying the quality as well as the quantity of OM in these environments is imperative. A wealth of techniques commonly used in other disciplines could be utilised by physical geographers, with consideration of their complexity, costliness and applicability, to address future research objectives.

This paper has argued for the much wider adaptation by physical geographers of approaches to OM quality determination, and, through the development of a novel classification and provision of practical guidelines on laboratory procedures, seeks to advance the consideration of OM quality by physical geographers as a fundamental aspect of sedimentary analysis.

Footnotes

Acknowledgement

The authors would like to thank two anonymous reviewers for their comments that have undoubtedly improved the manuscript.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: We would like to thank the School of Environment, Education and Development at the University of Manchester for funding this research as part of a PhD studentship.

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