Evaluating paleoproxies for peat decomposition and their relationship to peat geochemistry

Abstract

The past decade has seen a rapid increase in interest in the biogeochemical record preserved in peat, particularly as it relates to carbon dynamics and environmental change. Importantly, recent studies show that carbon dynamics, that is, organic matter decomposition, can influence the record of atmospherically derived elements such as halogens and mercury. Most commonly, bulk density, light transmission, or carbon/nitrogen (C/N) ratios are used as a proxy to qualitatively infer the degree of decomposition in peat, but do these three proxies reflect the same patterns? Furthermore, how do each of these proxies relate to other geochemical data? To address these questions, we analyzed bulk density, light transmission, and C/N ratios, as well as multielement geochemistry (wavelength-dispersive x-ray fluorescence (WD-XRF)), in three hummock cores (70 cm in length, c. 500 years) from an ombrotrophic Swedish bog. To compare the proxies, we applied principal component analysis (PCA) to identify how the proxies relate to and interact with the geochemical matrix. This was coupled with changepoint modeling to identify and compare statistically significant changes for each proxy. Our results show differences between the proxies within and between cores, indicating each responds to a different part of the decomposition process. This is supported by the PCA, where the three proxies fall on different principal components. Changepoint analysis also showed that the inferred number of changepoints and their depths vary for each proxy and core. This suggests that decomposition is not fully captured by any one of these commonly used proxies, and thus, more than one proxy should be included.

Keywords

bulk density C/N ratio decomposition humification light transmission peat

Introduction

Cores from peatlands and other natural archives allow us to study aspects of the atmospheric cycling, deposition, and net accumulation of elements on timescales much longer than the few decades available from monitoring programs. Of particular interest is how peat records reflect significant environmental changes such as climate (Barber et al., 2000; Chambers et al., 1997, 2012), atmospheric pollution (Martínez-Cortizas et al., 2012; Weiss et al., 1997), and dust (Kylander et al., 2007; Shotyk et al., 2001). An important component of interpreting geochemical signals is to understand the influence of organic matter decomposition. During decomposition, organic compounds are reorganized, and the deposit experiences a loss of mass and increase in humification; these can both influence metal concentrations and accumulation rates (Biester et al., 2003; Kuhry and Vitt, 1996).

Several proxies involving more time-consuming analytical procedures or microscopic work have been used to characterize peat decomposition, for example, fossil lipids, plant macrofossils, testate amoebae, and isotopic ratios (e.g. δ¹³C) (Borgmark and Schoning, 2006; Menot and Burns, 2001; Nott et al., 2000). The most commonly used proxies are, however, bulk density (Chambers et al., 2011; Clymo, 1965; Fenton, 1982; Franzén, 2006; Johnson et al., 1990; Malmer and Wallen, 1993), light transmission (or absorption; Aaby, 1976; Blackford and Chambers, 1993; Borgmark, 2005; Borgmark and Schoning, 2006; Caseldine et al., 2000; Yeloff and Mauquoy, 2006), and carbon/nitrogen (C/N) ratios (Kuhry and Vitt, 1996; Malmer and Holm, 1984; Malmer and Wallen, 2004; Malmer et al., 1997). These have the advantage in that they are relatively rapid, inexpensive, and accessible methods, which require relatively little sample material making them ideal in geochemical studies where high-resolution sampling (≤1 cm) can result in small sample masses (e.g. Kylander et al., 2013). We therefore focus on these three main decomposition proxies, namely, bulk density, light transmission, and C/N ratio, and compare these within a geochemical framework. The key question is do these proxies show the same patterns? As these proxies are gradually incorporated into the permanent peat record, do they record the same information regarding the degree of decomposition as plant material is transformed to peat and ultimately buried in the catotelm? Most importantly, how do these three proxies relate to the geochemical composition of the peat, are they interchangeable? To answer these questions, we analyzed triplicate hummock surface cores (70 cm long, spanning c. 500 years) from an ombrotrophic bog in southern Sweden for bulk density, C/N ratios, and light transmission as well as multielement geochemistry.

Material and analytical methods

Site description and sampling

Store Mosse (Figure 1) is a ~8000 ha bog complex in the boreal–nemoral zone of south-central Sweden (57°15′N, 13°55′E; 160–170 m a.s.l.), for which extensive studies have been published (Kylander et al., 2013; Malmer et al., 1997; Svensson, 1988a, 1988b). In 2008, three surface hummock cores (SM1–SM3) were collected from a ~25 × 25 m² area in the southern part of the bog (within ~100 m of the coring site described in Bindler et al., 2004) using a Wardenaar corer (Wardenaar, 1987). The cores were wrapped in plastic film and aluminum foil, and then stored in a walk-in freezer (−18°C). These cores (~70 cm in length) represent about 500 years of peat accumulation, based on carbon-14 (¹⁴C) dating of bulk samples from 66 cm to 68 cm depth (SM1/LuS 9862: 505 ± 50 ¹⁴C yr BP and SM2/LuS 9863: 520 ± 45 ¹⁴C yr BP); the cores fall within the Magellanicum bog phase, which began 940 yr BP (Svensson, 1988a, 1988b).

Figure 1.

Location of Store Mosse in south-central Sweden.

We also included a small selection of plant samples collected in 2002 to assess differences in plant composition as a starting reference point for the decomposition proxies. These samples include Sphagnum magellanicum, Sphagnum rubellum, Sphagnum cuspidatum, and Cladonia portentosa.

Sample preparation and analytical methods

In a walk-in freezer, we removed the outer surfaces of the frozen cores, marked out 2-cm intervals on the frozen surface, and then, cut the cores into 2-cm slices on a band saw with a stainless steel blade (0.36 mm thick). All samples (peat and plant) were dried to constant weight at 30°C, after which their dry masses were recorded and bulk density (peat) calculated. The samples were then ground in a ball mill before further analysis which was carried out at the geochemistry lab at Umeå University. Bulk density was calculated based on the dimensions at the midpoint for the length and width of each slice and an average thickness of 1.95 cm, assuming a loss of 0.5 mm during slicing. Assuming a measurement uncertainty of ±2 mm for length and width and ±0.5 mm for thickness, the estimated uncertainty for the calculated bulk densities is ≤15%.

Light transmission was measured following an alkaline extraction based on the methods of Blackford and Chambers (1993), but using smaller masses (Roos-Barraclough et al., 2004). In brief, 0.02 g samples were digested in 10 mL 8% NaOH (95°C, 1 h), diluted with an equal volume of deionized water (10 mL), filtered (Whatman No.1), and then diluted again with an equal volume of deionized water, whereafter light transmission (% T) was measured using 1-cm quartz cuvettes and a Hitachi U-1100 spectrophotometer at a wavelength of 540 nm. Data are reported as the average value of triplicate measurements. Replicate analyses were within ±0.08% (relative standard error).

Total-carbon and total-nitrogen contents were determined using an elemental analyzer (Perkin-Elmer Series II CHNS/O analyzer 2400) operating in CHN-mode only. Analytical quality was controlled using internal standards and replicates, which were included with every 10 samples. The relative deviation for standards and replicates was within ±2.8% for C and ±3.1% for N.

Major (Na, P, Si, Mg, Al, Ca, Mn, and Fe) and trace (Ti, Zn, Ba, Rb, Cl, Br, and Sr) elements were measured using a Bruker S8 Tiger wavelength-dispersive x-ray fluorescence (WD-XRF) spectrometer equipped with a Rh anticathode x-ray tube set-up with a 34-mm mask. A specific calibration based on 27 standard reference materials was developed in order to optimize the WD-XRF for the organic matrix of the samples (modified from De Vleeschouwer et al., 2011, see supplementary information: Table S2–S4 and Figure S1, available online). The detection limits for trace elements were in the range of 1–7 µg/g, reproducibility was within ±5%, and accuracy was within ±9% for most elements except for P (20%) and Br (27%).

Data analysis methods

We used principal component analysis (PCA; SPSS Statistics v.18) to assess how the three decomposition proxies relate to the geochemical composition of the peat (Biester et al., 2012; Jolliffe, 2002; Kylander et al., 2013). If all three proxies describe exactly the same underlying decomposition pattern, they should group together within the PCA scatter plots (where bulk density would plot opposite the other two proxies since it would increase with decomposition, while the other two proxies would decrease). To avoid the effects of different scales and variance between variables, the raw data were transformed into Z-scores (Z = (X_i − X_avg)/X_std), where X_i is the measured concentration of an element in a sample, and X_avg and X_std are the average concentration and standard deviation. The three proxies were used as passive variables (i.e. they are related to the geochemical PCs through their respective correlation), which has the advantage that the decomposition proxies do not control the relationship between the geochemical variables, and instead, they are only related to the geochemical composition of the peat. We performed the PCA separately for each core, and with all three cores combined, which gave similar results, we have chosen to report only the results from the separate PCAs. We also applied changepoint modeling, as described by Gallagher et al. (2011), to identify the locations of significant changes in each decomposition proxy within each core.

Results and discussion

All three proxies are well studied, including the driving mechanisms behind them. We therefore describe each proxy only in brief in relation to the patterns observed in our data (Figure 2).

Figure 2.

Results from the analysis of the three Store Mosse peat cores for (a) bulk density (g/cm³), (b) light transmission (%Trans), and (c) C/N ratio (SM1, filled circles; SM2, gray squares; and SM3, open triangles).

Bulk density

Bulk density shows some common patterns among the three cores, in accordance with previous studies from Store Mosse and other bogs (Borgmark, 2005; Caseldine et al., 2000; Clymo, 1965; Fenton, 1982; Franzén, 2006; Johnson et al., 1990; Malmer and Holm, 1984; Malmer and Wallen, 2004; Svensson, 1988b; Yeloff and Mauquoy, 2006). Bulk density initially increases approximately twofold to threefold, from ≤0.05 g/cm³ in the uppermost layers to values of ≥0.1 g/cm at depths of 25–35 cm, then declines to values of ~0.05 g/cm³ and levels off. However, the declining trend varies among the cores.

As a proxy for decomposition, bulk density increases with depth because increasing decomposition results in a loss of strength in the organic matrix, which leads to compaction as more mass accumulates above (Johnson et al., 1990). Changes in bulk density occur in three stages: (1) in the upper few centimeters, the bulk density changes relatively little due to limited compaction; (2) compaction increases almost linearly with depth due to the compression of peat caused by loss of structure in the organic material and the weight of the overlying material; and (3) the decay process weakens, and compaction increases rapidly before leveling off or even declining at or below the lowest water-table, where the peat becomes permanently saturated and is supported by water and therefore cannot be further compressed. These stages are clearly reflected in our cores (Figure 2a). The primary stage (≤5–7 cm depth) consists largely of fresh plant material and partly decomposed litter. In the second stage (~5 cm to ~20–25 cm), the bulk density increases almost linearly with depth, and the overall trend is consistent in all three cores, although the absolute values differ. In the third stage (~20–25 cm down to 30–35 cm), the bulk density increases up to twofold due to the collapse of the moss structure. Below the water-table, the peat is permanently saturated and cannot be compacted further.

Although the general pattern is similar between cores, there are some quantitative differences. This is particularly evident when looking at the peak values, which vary from 0.096 g/cm³ in SM2 and SM3 to 0.119 g/cm³ in SM1, and the depth over which it occurs (25–35 cm). One additional factor influencing the density, that cannot be excluded, is the compression and extension of the cores during coring (Givelet et al., 2004; Shotyk and Steinmann, 1994).

Light transmission

As a proxy for decomposition, light transmission declines with increasing humification due to the decomposition of plant material and the formation of humic acids, which are dark brown in solution (Aaby, 1976; Blackford and Chambers, 1993). In our five plant samples, light transmission varied from 80% to 100%, where the lichen had the highest value (100.7%T based on replicate samples) and Sphagnum the lowest (80–96%T), which is similar to values reported by Overbeck (1947; light absorbance values ranging from 7%T to 13%T). As suggested by Kuhry and Vitt (1996) and Yeloff and Mauquoy (2006), these data show that plant composition can affect the initial values for light transmission before any changes are superimposed by decomposition. In the cores, light transmission declines continuously from the surface downward, that is, from values of ~70%T, in the uppermost layers to ~30%T at the bottom of each core. Although the general pattern is again similar between cores, there are differences between them. The highest light transmission value varies slightly from 68%T (SM2), 72%T (SM3) to 74%T (SM1), and the depth at which this value occurs also differs between cores (between 1 and 23 cm).

Carbon/nitrogen ratio

The C/N ratio declines with depth due to the preferential loss of carbon and conservation of nitrogen during decomposition (Malmer and Holm, 1984; Malmer and Wallen, 2004). The driving factor that determines the C/N ratio is the balance between litter input to the acrotelm and the loss of carbon to the catotelm through the decay process (Malmer and Wallen, 2004). Through aerobic decomposition, the litter will continue to lose carbon at a proportional rate until it is included in the catotelm as peat, and it is therefore the residence time in the acrotelm that determines the loss of carbon and thereby the C/N ratio (Clymo, 1984; Malmer and Wallen, 2004).

In the plant samples, the Sphagnum had C/N ratios of 42–50, whereas the lichen had a C/N ratio of 107. In the cores, the C/N ratio should show a general decrease with depth in the acrotelm. However, the C/N ratio first rapidly increases from ~48 to 50 in the first few samples – values similar to the Sphagnum – to values of 72–86 at the so-called litter deposition level (LDL; Malmer et al., 1997). Previous studies have shown that C/N ratios >50 are indicative of decomposition under mainly aerobic conditions (Kuhry and Vitt, 1996). The C/N ratio then declines irregularly with depth to ~30 near the nitrogen peak level (NPL; Malmer et al., 1997). As with bulk density, these data are consistent with previous results from Store Mosse (Bindler and Klaminder, 2006; Bindler et al., 2004; Malmer and Wallen, 1993). Above ~20 cm depth, the trends in the cores are generally similar, but below this, the cores have quite variable C/N ratios – especially for SM3. This variation is evident considering the peak in C/N ratio, which varies from 72 (SM2), 80 (SM3) to 87 (SM1), while the depth at which the peak occurs is similar (5–7 cm). A secondary peak occurs at 43 cm depth in SM3 with a C/N ratio of 81, but no such secondary peak exists in SM1 or SM2.

PCA

In comparing the three proxies against the geochemical composition (i.e. PCA), there are clear differences between them (Figure 3a–c). In both PCAs using the proxies as either active or passive variables, four (SM1 and SM3) or five (SM2) principal components (PC) could be identified, which explains ~90% of the total variance of element concentrations in the cores. Although there is some overlap between the proxies in the PCA space, the main component for each proxy is different. Bulk density mostly falls on PC1 (34–46% of total variance) together with biophilic elements (C, Ba, Br, and Sr), light transmission (%T) falls mostly on PC2 (17–25% of total variance) with relatively mobile or redox-sensitive elements (Ca, Na, Mn), while C/N falls mostly on PC3 (11–17% of total variance) with conservative lithogenic elements (e.g. Al and Ti) and also P, Si, and N and metals (Zn). Note that in the PCA for SM3, PC2 and PC3 are reversed, that is, they are still driven by the same underlying process as the other two cores, but the order in which they are presented has changed. A fourth component (PC4, 11–15% of total variance), generally driven by Fe and Mg, was present in all PCA outcomes. However, only in SM3 did some of the variance in the light transmission relate to this PC. In SM2, a fifth component (PC5, 8–10% of total variance), driven by Cl and Rb, was present, but it was not related to the decomposition proxies.

Figure 3.

PCA-scatterplots of the geochemical data together with the decomposition proxies for (a) SM 1, (b) SM 2, and (c) SM 3. All PCA results are based on the calculated Z-scores and the three decomposition proxies included as passive variables.

Based on the PCA, it is clear that the three proxies do not reflect the same signal. However, there is a consistent pattern in how each of the respective proxies relates to the geochemical data in all three cores, which suggests that the three proxies and the geochemistry reflect spatially coherent processes across the bog area. Some common underlying process(es) must exist for each proxy that is consistent among the cores. At the same time, the three proxies relate differently to the geochemical composition of the peat, and thus that they do not reflect the same specific underlying process. We interpret this as indicating that the three proxies reflect different aspects of the decomposition process and that decomposition is not fully captured by any one proxy.

Changepoint analysis

The aim of the changepoint analysis is to statistically identify at what depth significant changes in each proxy occur (Figure 4a–i), and whether these depths are common for all proxies. We present the inferred statistical probability of a changepoint to occur for each proxy and core as well as the maximum likelihood model and the weighted average model. In all cores, the changepoint modeling indicates that the number of changepoints for each proxy differs and also the depth at which they occur. Using SM1 as an example (Figure 4a–c), bulk density and light transmission both show four depths where a changepoint occurs (maximum likelihood model indicating changepoints at 15, 25, 36, and 60 cm depth for bulk density, but 15, 30, 45, and 57 cm depth for light transmission), whereas the C/N ratio only shows three such points (maximum likelihood model indicating changepoints at 1, 12, and 42 cm). More important is that these changepoints do not occur at the same depth. This is most evident in the top ≤12 cm of the core where the C/N ratio shows two distinct phases of change, whereas bulk density and light transmission do not. This lack of a common pattern in changepoints is consistent within each core and among the cores. It is therefore noteworthy that because the number and depth of the changepoints differ within and between the three cores, this would indicate some within-bog spatial variation in the decomposition signal as was previously shown for plant macrofossils, Pb and Hg (Bindler et al., 2004).

Figure 4.

Results from the inferred changepoint analysis for (a) bulk density (g/cm³), (b) light transmission (%Trans), (c) C/N ratio in SM1, (d) bulk density, (e) %Trans, (f) C/N ratio in SM2, (g) bulk density, (h) %Trans, and (i) C/N ratio in SM3. The weighted average model is shown as a solid red line, and the maximum likelihood model as a dashed black line. The gray filled area represents the statistical probability of a changepoint based on the posterior distribution for the model parameters (see Gallagher et al., 2011 for more details).

Although it can be argued that our results only reflect triplicate cores from one bog, the patterns we show for each proxy are consistent with those shown for each proxy from other ombrotrophic bogs. Over centennial or millennial timescales, where one to two decades may be compressed into a 1-cm slice, some of the differences in depth among the proxies may be ‘removed’; however, Kylander et al.’s (2013) recent analysis of the 8500-year record from Store Mosse indicates that the differences between bulk density and humification at least persist.

In this study, we have shown that although some general decomposition trends could be identified, which correspond to previous studies of decomposition, the trends here are not consistent among all cores. While each proxy can provide valuable information on decomposition and changes in the organic matter, our results indicate that the decomposition signal is not fully captured by any one proxy. We therefore suggest that more than one decomposition proxy be included – and when possible also more than one core – in order to obtain a more representative assessment of long-term biogeochemical responses of peatlands to environmental changes. This is important as studies increasingly seek to make quantitative links between the peat geochemical record and monitoring data.

Footnotes

Acknowledgements

The authors wish to thank the County Administrative Board of Jönköping for granting permission for fieldwork within Store Mosse National Park, Professor Lars Ericson for help with the species identification of the vegetation samples, and Antonio Martínez-Cortizas for valuable discussions regarding the PCA.

Funding

This research was supported by grants from the Stiftelsen Anna och Gunnar Vidfelts fond för biologisk forskning, the Kempe Foundation, and the Swedish Research Council.

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