Samples used in this study were collected from the East Siberian Arctic Shelf, a region extending from 130 to 175∘ E and from 70 to 77∘ N, fed by four of the major GRARs (from west to east: Lena, Yana, Indigirka and Kolyma; see Fig. 1). Onshore, the East Siberian Arctic region consists largely of continuously permafrosted land. Enhanced climate warming in the next century is expected to increase the permeability of the permafrost layer , leading to the mobilisation of OC from deeper, older permafrost horizons .

Water depth across the ESAS is < 100 m for several hundred kilometres, before dropping steeply at the shelf break. In addition to fluvial input, coastal erosion also plays an important role in sediment and OC delivery. Coastal erosion rates in the ESAS region are among the fastest in the Arctic, measuring up to 10 myr-1 (; sections of particularly rapid coastal erosion are highlighted in Fig. 1). Erosion rates from ICDs are 5–7 times greater than other coastal permafrost and are responsible for a large proportion of the sediment and OC input to the ESAS and references therein. Biomarker investigations have been able to identify and model the contribution from fluvial and coastal delivery processes separately . showed that biomarker and radiocarbon values differed between areas dominated by ICDs (from coastal erosion) and topsoil (from river erosion), and that these values varied between size and density fractions. The annual OC delivery into this area is estimated to be 10 MtCyr-1 , whilst estimated 44 MtCyr-1 from ICDs. showed that, whilst terrOC was present across the ESAS, organic matter degradation in the eastern region, off the Kolyma River, was dominated by degrading marine OC, whilst in the western areas degradation was typically of terrOC.

Based on these findings, this study has sub-divided the ESAS into four smaller areas (see Fig. 1). The “nearshore Laptev Sea” zone (NLS) contains samples close to the eastern outflows of the Lena River delta. This includes the Buor-Khaya Bay between the Lena Delta and Cape Buor-Khaya. Suspended material and surface sediments in this area are rich in terrOC , and glycerol dialkyl glycerol tetraether (GDGT) biomarkers are dominated by river-derived material , but there are also areas of rapid coastal erosion (Muostakh Island, Cape Buor-Khaya) which deliver large amounts of sediment and OC to the bay. However, these coastal erosion sediments have noticeably different isotopic and biomarker signatures when compared to river sediments .

The “Dmitry Laptev Strait” zone (DLS), east of the NLS, is situated next to a rapidly eroding coastline up to 10 myr-1; but is over 300 km from major river inputs. Bulk measurements (δ13COC) and the branched and isoprenoid tetraether index (BIT, based on GDGTs) show a dominance of terrOC in this area – mainly due to a relatively low input of marine OC.

The “nearshore East Siberian Sea” (NESS) zone covers samples up to 200 km from the Indigirka and Kolyma River mouths. This region contains the terrOC-dominated section of the East Siberian Sea, as determined by , and is affected by influx from the Indigirka and Kolyma rivers, as well as the Oyagosski Yar region of extensive coastal erosion to the west of the Indigirka and between the two rivers Fig. 1. The Kolyma River outflow has been extensively studied as a terrestrial–marine transect . Bulk stable carbon isotopes and the bacteriohopanepolyol-based R′soil proxy showed linear trends offshore, but the BIT index decreased rapidly offshore, leading to a non-linear correlation between the terrestrial vs. marine proxies . This has been explained by both varying contributions to the bulk OC signal from different OC sources and settling-fractionated sediment sorting .

The “offshore Arctic shelf” (OAS) zone contains offshore sections of the Laptev and East Siberian seas, further than 200 km from the mouths of the great Russian Arctic rivers. Bulk isotopic measurements and terrestrial–marine biomarker proxies from this area all showed lower amounts of terrOC and a dominance of marine OC in this area .

Thirty-six surface sediment samples from across the ESAS were used in this study (Fig. 1), along with six ICD samples from two terrestrial sample sites. The offshore surface sediments were collected during the International Siberian Shelf Study research cruise in 2008 ISSS-08; by a GEMAX dual gravity corer or a van Veen grab sampler. Sediment cores were sliced into 1 cm sections and transferred into pre-cleaned polyethylene containers; grab samples were sub-sampled using stainless steel instruments into pre-cleaned polyethylene containers. ICD samples were collected from the upper, middle and lower portions of river-bank profiles. All samples were kept frozen before stabilisation by freeze or oven drying (50 ∘C). The sample sediments used for py-GCMS analysis were previously solvent-extracted for biomarker analysis . Briefly, an ultrasonic extraction process using methanol, dichloromethane and pH-buffered distilled water was used to remove extractable material, representing approximately 5 % of the total OC content. The sample residues were dried and stored at room temperature prior to analysis in this study.

In addition to existing radiocarbon data , bulk radiocarbon measurements were carried out at the accelerator mass spectrometer (AMS) facility of the Laboratory of Ion Beam Physics (LIP) of the Swiss Federal Institute of Technology (ETH Zurich, Switzerland). Samples were fumigated in 8×8×15 mm silver boats (Elemental) with HCl > 37 % under vacuum in a desiccator , followed by neutralisation for at least 24 h with NaOH. Prior to elemental analysis (EA) combustion, the samples were wrapped in a tin boat 8×8×15 mm (Elemental). Samples were measured in gas form with an EA directly coupled to the AMS. Gas targets were measured using the MICADAS instrument at the AMS facility of LIP at ETH Zurich. Samples have been corrected against an in-house anthracite coal blank and oxalic acid II standard reference material (NIST SRM 4990C).

Dried solvent-extracted residues were analysed using py-GCMS. All samples were analysed using an Agilent GC-MSD system interfaced to a CDS-5200 Pyroprobe. Briefly, 10–15 mg of sediment was placed into a clean fire-polished quartz tube along with a known amount of internal standard (5α-androstane) and pyrolysed at 700 ∘C for 20 s in a flow of helium. The resulting material was transferred via a heated transfer line to an Agilent 7980A GC fitted with an Agilent HP-5 column coupled to an Agilent 5975 MSD single quadrupole mass spectrometer in electron ionisation mode (scanning a range of m/z 50 to 650 at 2.7 scans s-1; ionisation energy: 70 eV). The pyrolysis transfer line and rotor oven temperatures were set at 325 ∘C, the heated GC interface at 280 ∘C, the EI source at 230 ∘C and the MS quadrupole at 150 ∘C. Helium was used as the carrier gas, and the samples were introduced in split mode (split ratio: 20 : 1; constant flow of 20 mLmin-1, gas saver mode active). The oven was programmed from 40 ∘C (held for 5 min) to 250 ∘C at 4 ∘C min-1, before being heated to 300 ∘C at 20 ∘C min-1 and held at this temperature for 1 min, for a total run time of 61 min sample-1. Each sample was run at least in triplicate.

Py-GCMS produces complex chromatograms containing hundreds of compounds. Approximately 70 of the most abundant pyrolysis moieties were identified (Fig. S1 and Table S1). Compounds were identified by comparison of relative retention times and spectra to those reported in the NIST library. Given the complexity of the GCMS chromatograms (see Fig. S1), it was not possible to integrate individual compounds in total ion current mode due to significant overlap between ion peaks. Instead, single ion filtering was used to measure the peak area of each compound. The major ion of each compound was filtered and integrated. In line with the approach taken in , a selection of nine representative moieties were chosen that represent key compound classes, many of which can be linked to particular groups of terrestrial or marine macromolecular materials. For example, phenol is a key component of lignin, so it can potentially be used as a proxy for the pyrolysis products of terrestrial plant material, although it is also found in other compounds including tannins. Pyridine, a nitrogen-containing aromatic compound, is likely sourced from proteins, which can be found in soils but will mostly come from marine primary productivity in offshore samples. Representative compounds and their inferred sources can be found in Table 1. These compounds are identical to those analysed by except for the addition of pyridine and methyl pyridine in the “pyridines” group for the present study. Following the “abundance index” approach of , the relative areas of the major ions in each group were compared to the total area of all measured compounds and are reported in Table S2. As discussed by , this approach does not attempt to represent all organic compounds in the sediments, and the relative areas of major ions do not correspond to the actual abundance of each compound. However, this approach uses the most important compounds to demonstrate differences between sediment samples in a defined manner. Expanding on the work of , this study includes samples from across the shelf, rather than just river mouths. Thus the E–W transect can be extended to a whole-shelf survey of macromolecular OC, and the spatial resolution increased.

Radiocarbon values ranged from -748 to -313 ‰ (see Table S3). The most depleted values were in the Dmitry Laptev Strait, and the most enriched values were in the offshore Arctic shelf zone. The values from stations off the Indigirka River were more depleted than those off the Kolyma and Lena rivers. The range of Δ14COC values is comparable to those measured by , and a comparison of the two datasets is shown in Fig. S3.

Figure 2 shows the distribution of each compound group across the ESAS. The proportion of phenols ranged from 3 to 62 % (Fig. 2a) with an average of 28 ± 16 % (1 SD). The value was highest in the nearshore Laptev Sea (average 42 %, n=8) and DLS (average 49 %, n=2), and lowest in the far offshore parts of the offshore Arctic shelf zone (YS-88 and YS-100, both 3 %). The proportion of pyridines ranged from 8 to 74 % (Fig. 2b) with an average of 33 ±20 % (1 SD). The value was highest in the far offshore samples, YS-88 (74 ± 5 %) and YS-100 (69 ± 1 %), whilst it is lowest in the nearshore Laptev Sea, at sample YS-15 (8 ± 2 %). Alkylbenzenes ranged from 1 to 10 % (Fig. 2c) with an average of 5 ± 2 % (1 SD). The highest proportions were in the coastal areas near to the Dmitry Laptev Strait (average 9 %), but not next to the Lena River mouth. The Kolyma River mouth sample, YS-34, also had high concentrations of alkylbenzenes (9 ± 1 %). Furfurals ranged from 6 to 38 % (Fig. 2d) with an average of 23 ± 6 % (1 SD). Their distribution does not show a clear pattern across the ESAS; large proportions of furfurals are found in both nearshore (TB-17, 37 ± 6 %) and offshore (YS-104, 37 ± 3 %) sediments. Aromatics ranged from 3 to 17 % (Fig. 2e) with an average of 9 ± 4 % (1 SD). They were most concentrated in the area between the Yana and Indigirka rivers, comprising the Dmitry Laptev Strait and the coastal area to the east of this (YS-22, YS-24, YS-26, YS-28; average: 16 %). Proportions were lowest in the far offshore samples (YS-88, YS-99, YS-100; average 4 %). Cyclopentenones ranged from 0 to 3 % (Fig. 2f) with an average of 1 ± 1 % (1 SD). Concentrations were highest in the western nearshore areas, close to the Lena River, in the Buor-Khaya Bay and in the Dmitry Laptev Strait. Proportions on the offshore Arctic shelf were negligible.

Terrestrial ICD samples were dominated by phenols, furfurals and pyridines, averaging 37, 25 and 23 % respectively. Samples from the Kolyma River (code “CH”) were richest in phenols, up to 47 %. There was not much difference between shallow, middle and deep samples. The nearshore Laptev Sea samples were dominated by phenols and furfurals, averaging 42 and 23 % respectively. Phenols proportions were highest close to the rapidly eroding Muostakh Island (YS-15, YS-17) and next to the Lena River mouth (TB-46) with proportions dropping further from the shoreline down to just 17 % at site TB-17. Pyridines proportions were low, just 15 % on average. Cyclopentenones proportions, at 1–3 %, were the highest of any region. The Lena River mouth samples (TB-46, TB-59) were highest in cyclopentenones. The Dmitry Laptev Strait samples were dominated by phenols (46 and 52 %) but low in pyridines (14 and 17 %). The proportion of aromatics was higher than average (13 and 16 %), as was the proportion of cyclopentenones (1 and 3 %). Sample YS-24 also reported the lowest proportion of furfurals of all samples (6 %). The nearshore East Siberian Sea region had a decreasing amount of phenols in an offshore direction (51 down to 6 %) and an increasing amount of pyridines (16 up to 61 %). The two samples away from the river outflows (YS-26 and YS-31) were relatively low in furfurals (15 and 18 % respectively) but high in alkylbenzenes (7 and 9 %) and relatively high in aromatics (16 and 15 %). The offshore Arctic shelf region contained few phenols (average 12 %) and was dominated by pyridines (average 55 %). Other compounds that were relatively enriched closer to shore were also reduced here (aromatics: 6 %; alkylbenzenes: 3 %; cyclopentenones: 0–1 %), but furfurals represent 24 % of the material studied. The area furthest offshore to the east of the sample area (YS-88 and YS-100) was the most dominated by pyridines (74 and 69 % respectively) and the most reduced in the other compounds (e.g. phenols: 3 %; aromatics: 3 %).

The 14COC results confirm observations that the ESAS sediments are dominated by old carbon . The additional data collected in this study allow a comprehensive map of radiocarbon ages across the ESAS to be produced (Fig. 4c). This shows that the oldest radiocarbon ages were measured in sediments from the Dmitry Laptev Strait region, whilst the youngest are found in the offshore Arctic shelf group, especially in the eastern East Siberian Sea. Even the youngest samples have quite negative Δ14COC values, lower than -350 ‰. This has been interpreted as a large input of old carbon from ICD permafrost deposits, especially via coastal erosion. Very negative Δ14COC values in the Dmitry Laptev Strait zone support this theory, since it is a region of high coastal erosion rates see Fig. 1;, low fluvial input and low marine productivity .

To investigate offshore trends in the macromolecular groups, and to explore the relationships between them, sediments collected along a river-shelf transect from the outflow of the Kolyma River to the distal shelf were used as a case study. These sediments were ICD sample CH (average values from top, middle and lower samples), YS-34, YS-35, YS-36, YS-37, YS-38, YS-39, YS-40, YS-41 and YS-90 (see Fig. 1). All transect sediment samples were dominated by furfurals, phenols and pyridines, which combined comprised 75 % (YS-37) to 90  % (YS-90) of the total abundance. In an off-shore direction, the relative phenol abundance decreased from 50 % (at YS-34) to 11 % (at YS-90, Fig. S2b). Phenols can have multiple terrestrial lignin, tannins and proteins; or marine origins algal polyphenols;. However, a strong correlation with lignin concentrations, determined in the same sediments using the CuO oxidation method r2=0.98, p<0.01, n=9; Fig. S2b;, suggests that the phenols in both the transect sediments and the ESAS as a whole (r2=0.67, p<0.01, n=24; Fig. 4a) are primarily lignin-derived. According to , plant material in these sediments is associated with large particles that deposit rapidly nearshore; OC from these particles forms a very minor component of the offshore sediment. Phenol abundance was 11 % in the sediment collected at offshore station YS-90 and only 3 % at nearby station YS-88, suggesting that terrestrial lignin-bearing particles were mostly deposited or degraded before they reached this part of the distal shelf. It also suggests that marine production of phenols was minimal. There is a strong linear correlation between phenol abundance and δ13COC (r2=0.69, p<0.01, n=9; Fig. S2d), reinforcing the idea that the major source of phenols was terrestrial plant material. However, the relationship is somewhat better represented as a logarithmic trend (r2=0.81) in which relative abundance of phenols diminishes faster than the bulk δ13COC value in nearshore settings. This may be due to the higher concentration of lignin phenols in large particles which deposit closer to the shoreline than the sediment as a whole. However, it has been shown that lignin phenols are present in all size fractions across the ESAS and therefore are not just tracking large terrOC-rich particles. The non-linear correlation with BIT values , and the high abundance of phenols within the ICD samples, suggests that this is not due to phenols being dominantly river-derived material as has been suggested for branched GDGT biomarkers .

Pyridines abundance increased from 16 to 64 % in an offshore direction along the same transect (Fig. S2a) and dominated the sediment collected at station YS-90 (64 %). The increasing pyridines abundance coincides with a shift towards more marine δ15N values (r2=0.75, p<0.01, n=9; Fig. S2c) and δ13COC (r2=0.93, p<0.01, n=9; Fig. S2d). Although pyridines were present in ICD samples (23 %, comparable to the 16 % found in the nearshore samples), these results suggest that in the ESAS sediments, particularly those further offshore, they were mainly of marine origin and that the low-phenol, high-pyridine pattern observed in the furthest offshore sediments could potentially be used as a marine endmember composition. Pyridines themselves are not a marker for marine OC since they are present in onshore samples, with plant proteins being a likely terrestrial source.

The patterns seen along the Kolyma River–distal shelf transect suggest that the distribution of phenols and pyridines in sediments may be usable as a proxy for measuring the relative input of terrestrial and marine carbon. There are several existing methods of performing this measurement, which can be used to test the applicability of the new py-GCMS-based approach. An index value, ranging from 0 to 1, can be obtained by comparing the relative peak areas of phenols and pyridines (NB: this index is not affected by changes in any other compounds): phenolsphenols+pyridines.

In this index, a value of 1 means phenols dominated and is therefore interpreted as terrestrial in origin, and a value of 0 means pyridines dominated, interpreted as marine in origin. Our expansive dataset allows the phenols / pyridines ratio index (PPRI) to be examined as a proxy for terrOC across the entire ESAS. Figure 3 shows that the PPRI is highest in the nearshore Laptev Sea (0.88), next to the coastline and the Lena River mouth, and is fairly high in all coastal settings west of the Kolyma River. This includes areas that have been described as river-dominated and coastal-erosion-dominated in biomarker studies . The value drops towards 0 in distal offshore settings and east of the Kolyma River. In the western sections of the study area, off the Lena and Indigirka rivers, the transition from phenols-rich to pyridines-rich sediments occurs at about 200 km offshore. Off the Kolyma River this transition happens closer to shore. This pattern may be due to the enhanced export of lignin-derived phenol from the Lena River, due to its greater annual discharge 4.3 times more water, twice as much sediment; and less permafrost basin area 71 % continuous permafrost in the Lena catchment compared to 99 % for the Kolyma;. This would lead to a greater amount of terrestrial material (from the active layer at the top of the permafrost in both catchments, and also some deeper permafrost soil regions in the Lena catchment) being discharged from the Lena than the Kolyma. Alternatively, there could be an increased proportion of pyridines in the sediments off the Kolyma River due to the influx of marine OC-rich Pacific Ocean water through the Bering Strait .

The PPRI can be compared to other terrestrial vs. marine proxy measurements in the region, namely the BIT index , R′soil proxy and δ13COC . Figure 5 shows the strong relationship between the phenol / pyridine ratio and these alternative proxies. There is very strong positive correlation with R′soil (r2=0.80, p<0.01, n=38) and very strong negative correlation with δ13COC (r2=0.74, p<0.01, n=34). There is also a significant correlation with BIT when analysed for a linear fit (r2=0.73, p<0.01, n=38). However, Fig. 5a shows that this relationship is likely non-linear in reality. The nearshore Laptev Sea, Dmitry Laptev Strait and nearshore East Siberian Sea samples show a fast reduction in BIT relative to PPRI, whilst offshore Arctic shelf samples have a range of PPRI values but uniformly low BIT. This relationship between BIT and PPRI is likely due to the biomarker sourcing and distribution patterns across the ESAS. Branched GDGT-rich river sediment deposits rapidly close to river mouths, whilst phenols, despite also depositing rapidly nearshore, are sourced from both rivers and coastlines see model in. Whilst it must be recognised that the Py-GCMS method described here is limited to dealing only with relative proportions of each compound group, the strength of these correlations with other terrestrial–marine proxies suggests that the PPRI is a useful tool for measuring the source of macromolecular organic carbon in a sediment. As the results are relative measurements, an increase in one compound class could represent either an enrichment in this group of molecules, or a decreased concentration of the other compound classes. Hydrodynamic sorting of particulate matter, rather than selective production or degradation, may produce changes in relative concentration . Despite these reservations, the Py-GCMS approach has the advantage that it samples the non-extractable portion of the organic matter, whereas biomarker studies concentrate on the smaller extractable portion. Further examination of the phenol / pyridine ratio, particularly in other laboratories or with other pyrolysis equipment, should be undertaken to test the widespread applicability of the ratio as a geochemical tool.

Unlike phenols and pyridines, and despite their relative abundance ranging from 6 to 38 %, there were no consistent nearshore–offshore patterns in the distribution of furfurals across the ESAS (Fig. 2d). One possible explanation for this observation is that furfurals may be representing the pyrolysis products of carbohydrates from both terrestrial and marine organic matter. Previous studies have suggested that there is a transition from terrestrial to marine domination of OC across the shelf, both for bulk OC and molecular biomarkers . Therefore, it is expected that common compounds present in both terrestrial and marine organic matter, such as carbohydrates, may not show a distinctive change in relative concentration from nearshore to offshore. Simple measurement of furfurals may not show the transition from terrestrial to marine carbohydrate sources.

The across-shelf pattern of the minor compounds (aromatics, alkylbenzenes and cyclopentenones) suggests that the sources of these may not be identical. For example, aromatics are proportionally higher in regions far from the major river mouths (Dmitry Laptev Strait stations YS-22 and YS-24), in areas which are dominated by coastal erosion and near the Indigirka River (stations YS-26 and YS-28). In both of these areas, the proportion of pyridines was low, but there was no correlation with other compound classes. Both phenols and cyclopentenones were high in the Dmitry Laptev Strait and low off the Indigirka River; alkylbenzenes were high in the Dmitry Laptev Strait and at YS-26 but low at YS-28; furfurals were low in the Dmitry Laptev Strait and high off the Indigirka River. This suggests that the delivery mechanism (i.e. fluvial vs. coastal erosion) or offshore behaviour of aromatics is unlike that of the other compound classes. A comparison with radiocarbon data suggests that aromatics may be tracing the input of ancient terrOC to the ESAS. 14COC data from this and previous studies are mapped across the ESAS in Fig. 4c and bear a striking resemblance to the distribution of aromatics (Fig. 2e). Figure 4b shows a negative correlation between relative proportion of aromatics and Δ14COC (r2=0.44, p<0.01, n=36). Note that there is weak or no correlation with other compound groups (r2 values: furfurals, 0.02; alkylbenzenes, 0.20; phenols, 0.13; cyclopentenones, 0.01; pyridines, 0.18). ICDs are much older than fluvially eroded topsoil or marine productivity, with very little to no radiocarbon present 14COC=-940±84 ‰, n=300;, and so areas dominated by coastal erosion rather than fluvial erosion have more negative 14COC values. In the ESAS sediments this corresponds to the Dmitry Laptev Strait and nearshore East Siberian Sea groups of samples. The youngest samples, with the least negative 14COC, are those from the offshore Arctic shelf group with the lowest proportion of aromatics, thought to be dominated by marine productivity. The BKB samples, highly influenced by river erosion of soils , also have relatively young radiocarbon ages and lower proportions of aromatics. This correlation between older OC and aromatic compounds may be due to maturation of permafrost over time into simpler structures, especially into aromatic ones , and the protection of these compounds on mineral surfaces. Studies of soils from along an age gradient found that aromatic compounds were more likely to form mineral–organic associations more resistant to biodegradation . ICD samples were not enriched in aromatics, so the source of these aromatics is likely to be permafrost soil rather than ice complexes. The potential for pyrolysis-derived aromatic compounds being a tracer for very old permafrost material, especially coastal-erosion derived terrOC, should be investigated in future using more detailed sampling and compound-specific radiocarbon analysis. This would confirm the radiocarbon age of the aromatic compounds, as well as the mechanisms for their production and release.

The changing proportions of each compound class and a variety of proxy measurements were investigated by principal component analysis (PCA) using the software package “R”. Principal components were calculated using the prcomp() function, which is a singular value decomposition method. Variables were automatically scaled and centred before analysis. Figure 6a shows the results of this analysis when performed on the py-GCMS compound classes. Principal component 1, accounting for 58 % of the variance, shows that the relative proportions of alkylbenzenes, aromatics, phenols and cyclopentenones are in opposition to the relative proportion of pyridines. This pattern can be broadly seen in Fig. 2, where the relative proportion of pyridines is highest where the other four are lowest, and vice versa. This variance is interpreted as the difference between terrestrial and marine OC-dominated sediments. A division of the PCA diagram at x=0 shows that all offshore Arctic shelf samples lie on the pyridines-dominated side of the chart and that all bar two of the nearshore Laptev Sea, Dmitry Laptev Strait, nearshore East Siberian Sea and ICD samples lie on the “terrestrial” side of the chart. Nearly orthogonal to these measurements is the proportion of furfurals, which is the main variable of principal component 2 (18 % of the variance). There are offshore Arctic shelf, nearshore Laptev Sea and nearshore East Siberian Sea sediments that are enriched in furfurals. This shows that the relative concentration of furfurals is not linked to the terrestrial–marine transition observed across the ESAS.

Figure 6b shows the results of principal component analysis carried out on the various terrestrial vs. marine proxies discussed in this paper (PPRI, BIT index, R′soil index and δ13COC) and Δ14COC. Principal component 1, accounting for 80 % of the variance, has δ13COC in opposition to PPRI, BIT and R′soil. These four terrestrial vs. marine proxies are oriented opposite to δ13COC in Fig. 6b since the latter becomes more negative with increasing terrestrial material, whereas the other proxies trend to higher values with increased terrOC. Therefore PC1 denotes the transition from terrestrial to marine dominance of the OC. It is notable that BIT lies slightly away from the PPRI, R′soil index and δ13COC vectors. We interpret this as being due to the BIT index being strongly linked to river-derived terrOC in this region , whereas δ13COC is measuring the entire sediment sample, and R′soil is thought to measure both river and coastally derived terrOC . This offset is seen in the sample groups – the samples from the nearshore Laptev Sea, especially those near to the Lena River, plot close to the BIT vector, whilst the coastal-erosion-dominated Dmitry Laptev Strait sample, along with the nearshore East Siberian Sea samples, plot further from the BIT vector. The Δ14COC vector is at 45∘ to the trend in terrestrial–marine proxies. This is interpreted as showing that all marine OC is dominated by young OC (high Δ14COC values), as is material coming from the rivers. Coastal erosion sediments contain older material and therefore plot opposite to the Δ14COC vector.

Therefore we can define three areas on the PCA diagram (Fig. 6b). As mentioned, PC1 divides the diagram into terrestrial and marine sections. Within the terrestrial half of the diagram, PC2 differentiates between river-derived and coastal-erosion-derived terrOC. Following the offshore trends of each major river (shown in Fig. 6b), there is a transition from river-influenced terrOC to ICD-influenced terrOC and finally marine OC-dominated compositions. The Lena River is the most river-influenced trend, followed by the Kolyma River, with the Indigirka River offshore transect mostly dominated by terrOC from ice complexes. The Indigirka River sits between two areas of extremely high coastal erosion rates , so this is not unexpected. These patterns agree with the model published in , which predicted a transition from river-derived upper permafrost to coastal-erosion-sourced ICD material to marine OC with distance offshore. Overall, principal component analysis has proven to be a valuable tool for understanding the transition between OC types across the ESAS. Multiple organic proxies agree that there is a large amount of terrestrial OC on the ESAS and that erosion of coastal sediments greatly increases the delivery and burial of terrestrial OC as compared to purely river-derived material.