Biogeochemical properties and diagenetic changes during the past 3 . 6 Ma recorded by FTIR spectroscopy in the sediment record of Lake El ’ gygytgyn , Far East Russian Arctic

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Introduction
The understanding of past environmental changes is of particular importance to facilitate the prediction of the magnitude and the regional implications of future environmental changes, especially in view of an anthropogenic-forced global warming (IPCC, 2007).Lake sediment records are valuable archives preserving these changes.Records such as those from Lake Baikal (e.g.Williams et al., 1997), Lake Malawi (e.g.Scholz et al., 2006) and Lake Biwa (e.g.Fuji, 1988) extend several million years back in time and consist of several hundred meters of sediment.However, multiproxy analyses of such long records are very time-consuming and cost-intensive.Furthermore, high resolution sampling of these records can be restricted by the amount of sample material available for the different analyses.Fourier transform infrared spectroscopy (FTIRS) is a promising tool that copes with the above-mentioned problems due to its potential to analyse several components at once, simple sample pre-treatments, and the small sample size required for analysis (0.01 g).Because the excitation of polar bonds in molecules by IR-radiation is wavenumber-specific depending on the structural and atomic composition of the molecules, it is possible to gather information about organic and minerogenic components from one single measurement.The technique has been applied to sediment to assess the concentration of silicate minerals (Sifeddine et al., 1994;Bertaux et al., 1996Bertaux et al., , 1998;;Wirrmann et al., 2001), and carbonates (Mecozzi et al., 2001), as well as to characterize humic substances (Braguglia et al., 1995;Belzile et al., 1997;Calace et al., 1999Calace et al., , 2006;;Mecozzi and Pietrantonio, 2006).
FTIRS has also successfully been applied in paleolimnological studies to quantify biogeochemical properties (e.g.biogenic silica (BSi), total organic carbon (TOC), total inorganic carbon (TIC), and total nitrogen (TN)) (Vogel et al., 2008;Ros én et al., 2010).The developed FTIRS models of these approaches were based on site-specific and regional calibrations, respectively.Further, Ros én et al. ( 2011) have shown that universally applicable models can be developed and be applied to globally distributed lakes with considerably different settings.However, in these studies reconstructions of selected properties by means of FTIRS have been conducted on sediment records of only few meters length (< 17 m) and not extending further back in time than 340 ka.It remains uncertain, weather calibration models based on IR spectral information can be developed for and applied on several hundred meters long sediment sequences extending millions of years back in time.In particular, it is important to know, whether Introduction

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Full variations in sediment composition arising from climatic, environmental or diagenetic changes bias the robustness of IR calibrations.In this study, FTIRS is applied to a 318 m long sediment record from Lake El'gygytgyn, Far East Russian Arctic (67 • 30 N, 172 • 5 E) (Fig. 1), which was recovered during an ICDP (International Continental Scientific Drilling Program) funded deep drilling campaign in 2009 (ICDP site 5011-1) (Melles et al., 2011).With its continuous formation and basal age of 3.6 Ma (Melles et al., 2012;Nowaczyk et al., 2012), the record of Lake El'gygytgyn for the first time provides high-resolution insights into the climatic and environmental evolution of the Arctic during the Quaternary and late Pliocene.
Within the framework of this study, we aim to test for the first time the applicability of IR based calibration models for BSi, TOC, and TIC using a sediment record extending several million years back in time.This test will shed light on the impact of potential diagenetically triggered changes in sediment composition on FTIR calibration models.Moreover, this study aims at providing initial insights into the climatic and environmental evolution of the Arctic from the Pliocene to the present as recorded by bioproductivity indicators in the sediment record of Lake El' gygytgyn.

Core recovery
Drilling operations were performed, from the lake ice cover, by Drilling, Observation and Sampling of the Earth's Continental Crust (DOSECC) Inc. using a GLAD-800 drilling system (Global Lake Drilling 800 m) in spring 2009.The lake sediments were sampled by three holes (A, B, and C) at ICDP site 5011-1, forming a core composite that penetrates down to the underlying impact breccia at 318 m below lake floor (m b.l.f.) (Fig. 1).The sample site is situated in the deepest part of the lake.Introduction

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Full FTIRS measurements were performed on 380 samples covering the entire composite profile of site 5011-1.The samples were taken from core catchers (∼ every 3 m) and core cuttings (∼ every 1 m) of the drill cores.In addition, samples from percussion piston cores PG1351 and Lz1024 were included in the calibrations.These 12.9 and 16.6 m long cores were recovered in 1998and 2003, respectively (Juschus et al., 2005;;Melles et al., 2007).

Analytical methods
Conventionally measured concentrations of biogeochemical properties (BSi, TOC, TIC) were used as reference data for the development of our calibration models.All sediment samples were freeze-dried and ground to a particle size < 63 µm using either a swing mill (samples from ICDP site 5011-1) or a planetary mill (samples from PG1351 and Lz1024).TC and TIC in samples from site 5011-1 were determined by suspension method using a DIMATOC ® 100 liquid analyser (Dimatec Corp.).TOC was then calculated by subtracting TIC from TC.The TOC content in samples from core PG1351 was analysed with a Metalyt-CS-1000-S (ELTRA Corp.) after sample pretreatment with HCL (10 %) at a temperature of 80 • C to remove carbonate.Concentrations of BSi in all sediment cores were obtained by applying the wet chemical leaching method according to M üller and Schneider (1993).Accumulation rates (AR X ) of BSi (AR BSi ), TOC (AR TOC ), and TIC (AR TIC ) in g cm −2 yr −1 were calculated according to Eq. ( 1) (Bralower and Thierstein, 1987): where SR is the sedimentation rate in cm yr −1 , WBD is the wet bulk density in g cm −3 , Φ is the porosity, and %X is the concentration of the property of interest.Sedimentation rates were determined according to the age model of Nowaczyk et al. (2012) and WBD and Φ were reconstructed by their physical properties measured by a Geotek Multi-Sensor Core Logger (MSCL) according to Gebhardt et al. (2013).WBD and Φ were Introduction

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Full averaged over 4 cm and sample levels affected by mass movements (Sauerbrey et al., 2013) were not considered in the reconstruction of accumulation rates.
Prior to the FTIR measurement, all samples were freeze-dried and ground to a particle size < 63 µm.0.011 ± 0.0001 g sample material was then mixed with 0.5 ± 0.0005 g of oven-dried spectroscopic grade potassium bromide (KBr) (Uvasol ® , Merck Corp.), which does not influence the FTIR spectrum due to its transparency in the IR region.Afterwards the mixture was homogenized using a mortar and pestle.The low sample concentration (2.2 %) was chosen to avoid spectral distortions by very high absorbance and optical effects (Herbert et al., 1992;Griffiths and de Haseth, 2007).To gain constant measuring conditions and avoid variability caused by variations of temperature, the measurements were performed in a temperature controlled laboratory with a constant temperature of 25 ± 0.2 • C. Samples were stored in the same room at least 5 h prior to the measurement.A Bruker IFS 66v/S FTIR spectrometer (Bruker Optics Inc.) equipped with a diffuse reflectance accessory (Harrick Inc.) was used for the analysis under vacuum (4 mbar).Each sample was scanned 64 times at a resolution of 4 cm −1 (reciprocal centimeters) for the wavenumber range from 3750 to 400 cm −1 or from 2666 to 25 000 nm.

Numerical analyses
Baseline correction and multiplicative scatter correction (MSC) were applied to normalize the recorded FTIR spectra and to remove spectral variations caused by noise (Geladi et al., 1985;Martens and Naes, 1989).We used partial least squares regression (PLSR) to develop calibration models between FTIR spectral information and the corresponding conventionally measured BSi, TOC, and TIC concentrations.Conventionally measured primary sediment properties were square root transformed prior to analysis.Both external and internal validations were applied to quantitatively estimate the complexity and the prediction ability of the calibration models.The internal validation was performed by 10 % cross validation (CV), which evaluates how much of the variation in the primary data is predicted by the model as well as assesses the significance of Introduction

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Full each model component.In this evaluation a calibration model based on 90 % of the available data was applied to the remaining 10 % to estimate its prediction ability.This procedure was then repeated a total of 10 times until the entire data set was predicted solely based on the corresponding spectral information.The resulting cross-validated coefficient of determination R 2 cv and root mean square error of cross-validation (RM-SECV) were used to evaluate the internal model performance.The external validation was performed on 50 samples randomly chosen and equally distributed over the entire composite profile of ICDP site 5011-1.The coefficient of determination (R 2 ) between conventionally measured and FTIR-inferred concentrations of biogeochemical properties as well as the root mean square error of prediction (RMSEP) were considered to estimate the prediction ability of the developed calibration applied to samples not included in the calibration set.We performed the multivariate data analyses using SIMCA-P 11.5 (Umetrics AB, SE-907 19 Ume å, Sweden).OPUS 5.5 (Bruker Optics Inc.) was used for the visualization of single FTIR spectra.For more information about the numerical analysis in this approach, see Vogel et al. (2008) andRos én et al. (2010).1).Corresponding RMSECV are low: 2.4 % for BSi (4.3 % of the gradient), 0.09 % for TOC (3.1 % of the gradient), and 0.03 % for TIC (2.1 % of the gradient).The external validation showed good statistical performance.The R 2 values are 0.94 for BSi and 0.83 for TOC (Fig. 2), and the RMSEP values are 2.1 % for BSi (7.0 % of Introduction

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Full the gradient) and 0.13 % for TOC (7.9 % of the gradient), which indicate both a high prediction ability of the general trend and high prediction accuracies with respect to the absolute values of the proxy of interest.
However, Ros én et al. (2010,2011) have shown that a PLS model for TIC solely based on wavenumbers related to the C-O molecular vibrations of calcite (700-725, 860-890, 1300-1560, 1780-1810, 2460-2640 cm −1 ) (Huang and Kerr, 1960;Mecozzi et al., 2001) can yield a high statistical performance as well.In this study, a 7-component TIC-model based on these selected wavenumbers shows an improved performance with an R 2 cv of 0.85, an RMSECV of 0.03 % (2.1 % of the gradient), and for the external validation set, an R 2 of 0.89 (Fig. 2) and an RMSEP of 0.03 % (7.9 % of the gradient).This indicates that the TIC model using selected wavenumbers has higher prediction ability of the general trend as well as of the absolute values.

Spectral information
Pronounced absorption bands in the loadings of the FTIRS models can be related to known absorption bands of organic and minerogenic compounds.For the BSi model the most important spectral regions positively correlated to the BSi concentration are situated between 790-860, 1060-1320 and 2750-3580 cm −1 (Fig. 3).Previous studies have shown that these regions can be attributed to absorptions caused by molecular vibrations of biogenic silica.Absorptions at around 1100 cm −1 are assigned to the stretching vibration mode of the [SiO 4 ] tetrahedron, while the absorption band at around 800 cm −1 is caused by inter-tetrahedral Si-O-Si bending vibrations (Moenke, 1974b;Gendron-Badou et al., 2003).A FTIR spectrum of purified BSi from Lake El'gygytgyn sediment shows two additional absorption bands at around 471 and 945 cm −1 (Fig. 4), which are not pronounced in the loadings.The band at around Introduction

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Full the band at around 945 cm −1 is related to Si-OH molecular vibrations (Rickert et al., 2002;Gendron-Badou et al., 2003).Instead, these spectral regions show a negative correlation to the BSi concentration due to fact that other silicates (e.g.feldspars, clay minerals) cause absorption in this part of the IR-spectrum as well (Farmer, 1974;Moenke, 1974b).This can result in an anti-correlation to the BSi content, because measurements of concentrations of biogeochemical properties reflect the relative proportion of biogeochemical and minerogenic compounds.The positive loading values in the spectral regions between 2750 and 3580 cm −1 can be linked to stretching vibrations of OH molecules (Moenke, 1974a), which are embedded in the molecular structure of BSi.The loadings of our BSi calibration model are consistent with the loading plots previously reported by Vogel et al. (2008) and Ros én et al. (2010,2011).
The most important absorption band in the loadings of the TOC model is situated between 1050 and 1275 cm −1 (Fig. 3).Absorption of IR radiation in this region can be linked to known absorption bands of organic compounds.For instance, absorptions between 1040 and 1070 cm −1 are ascribed to C-O stretching vibrations of carbohydrates or polysaccharides (Calace et al., 1999;Chapman et al., 2001;Cocozza et al., 2003).Absorptions at around 1125 cm −1 are due to C-O-C stretching vibrations of complex carbohydrates, and absorption between 1230 and 1265 cm −1 are attributed to C-O stretching vibrations of ethers or carboxyl groups (Cocozza et al., 2003;Mecozzi and Pietrantonio, 2006).However, the similarity of the loading plots of TOC and BSi indicates an interdependency between both proxies.Sediment samples of Lake El'gygytgyn used for the calibration models are in general characterized by low TOC concentrations (mean: 0.41 %) and high BSi concentrations (mean: 12.1 %).It is likely that the positive loading values from 1050 to 1275 cm −1 are therefore attributed to Si-O molecular vibrations of BSi rather than to vibrations caused by organic matter.
Positive loading values between 2800 and 3000 cm −1 with distinct peaks at 2850 and 2920 cm −1 can be attributed to stretching vibrations of C-H molecules in -CH, -CH 2 and -CH 3 groups of aliphatic and protein chains (Chapman et al., 2001;Cocozza et al., 2003;Mecozzi and Pietrantonio, 2006).Absorption in this part of the IR spectrum is Introduction

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Full characteristic of organic matter, since an overlap with specific absorption bands of BSi can be excluded.The positive values between 2560 and 3575 cm −1 as well as at around 3700 cm −1 are related to absorptions caused by hydroxide groups, which are common in organic matter.However, because the influence of BSi on the calibration model for TOC is likely, it is difficult to determine how much of the absorption is caused by hydroxide contained in organic matter (direct relationship) and how much of the absorption results from hydroxide groups associated with BSi (indirect relationship).
Distinctive positive absorption peaks in the loadings of the TIC calibration model at around 715, 875, 1795, 2515 cm −1 as well as the broad absorption band at around 1460 cm −1 (Fig. 3) correspond well with known absorption bands caused by molecular vibrations of carbonates (Huang and Kerr, 1960;Mecozzi et al., 2001).Furthermore, FTIRS model developments by Vogel et al. (2008) and Ros én et al. (2010,2011) as well as FTIR spectra of carbonate-rich sediments (Ros én et al., 2010) have shown that these spectral regions are the most important for carbonates.The negative loading values between 1025 and 1270 cm −1 as well as the negative values between 2630 and 3730 cm −1 can partly be explained by an indirect relationship between the occurrence of TIC and BSi.The appearance of carbonates in the analysed samples is almost exclusively restricted to the lowermost part of the sediment record and accompanied by low BSi concentrations, which result in a negative correlation of spectral regions related to molecular vibrations of BSi to the TIC content.developed for BSi, but has an inverse trend (Fig. 5c).This can be explained by the general trend of decreasing BSi concentrations with increasing depth within the sediment record (Fig. 6).An R 2 of 0.45 highlights the moderate correlation between both parameters.However, this correlation explains only partly the possibility to determine the sample burial depth on the basis of spectral information, because different FTIRSinferred burial depths result for samples of equal BSi content.

Indications for diagenetic changes
The spectral region between 2600 and 3750 cm −1 might be particularly relevant to explain the depth-related information in the FTIR spectra.Absorption in this region is mostly related to molecular vibrations of hydroxyl groups (Moenke, 1974a) contained in organic matter and several minerals such as clay minerals or biogenic silica.A 9component calibration model (n = 329) only based on this spectral region provides a statistical performance comparable to the model based on the entire spectral range.An R 2 cv of 0.84, an RMSECV of 29.9 m (9.6 % of the gradient), an R 2 of 0.91 (Fig. 5b), and an RMSEP of 28.7 m (9.4 % of the gradient) result from the internal and external validation, respectively.The negative correlation of this range indicates a dehydration/dehydroxylation of certain sediment components with increasing burial depth.For instance, biogenic silica loses hydroxyl water due to condensation reactions during its maturation in the surface sediments (Schmidt et al., 2001;Rickert et al., 2002).This process is likely to proceed with increasing burial depth and might explain the influence of BSi on the loadings of our FTIRS-depth model.Further investigations are required to determine from which components the depth-related information in the IR spectrum derive.Nevertheless, these findings indicate that IR spectroscopy might be a useful tool to estimate sediment maturation and provide information on diagenetic processes occurring along a sediment profile.

Variability of the biogeochemical properties throughout the last 3.6 Ma
The FTIRS-inferred concentrations for BSi and TOC strongly vary throughout the sediment record of Lake El'gygytgyn and range between 3.2-55.7 % for BSi (mean: 12.2 %) and 0.02-2.66% for TOC (mean: 0.41 %) (Fig. 6).Both values show a generally Introduction

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Full increasing trend from the bottom to the top of the sediment profile.The lowest concentrations of BSi and TOC occur in sediments from the basal part of the record, which were deposited prior to 3.54 Ma and, somewhat less pronounced, between 3.54 and ∼ 3.27 Ma.Sediments of the marine isotope stage (MIS) 11 interglacial (∼ 400 ka) contain the highest BSi concentrations, while the most recent of the analysed samples (145 ka) shows the highest TOC concentration.
The inferred concentrations of TIC vary between 0 and 1.45 % (mean: 0.08 %) (Fig. 6).Samples deposited between ∼ 3.27-3.54Ma contain low concentrations of carbonate up to 0.3 %, whereas sediments formed within the first ∼ 50 kyr after the lake formation show the highest concentrations of TIC up to 1.5 %.Samples covering the last ∼ 3.27 Myr (mean: 0.05 %), in contrast, are supposed to be free of carbonate, due to the RMSECV and RMSEP of 0.03 % and the limit of detection of approximately 0.05 % for the conventional method on which the calibration model for TIC is based.The only exception is one sample at around 223 ka, which has a TIC content of 0.50 %.Two different carbonate mineral phases, calcite and siderite, were determined in the analysed samples from their wavenumber-specific IR absorbance.Calcite (Ca[CO 3 ]) shows distinct absorption peaks at 712, 876, 1435, 1812, and 2545 cm −1 , while siderite (Fe[CO 3 ]) has specific peaks at 737, 866, 1422, and 1818 cm −1 (Huang and Kerr, 1960).Whilst calcite was determined in the basal sediments, siderite was detected in the ∼ 223 ka old sample from the upper part of the sediment profile.The occurrence of both mineral phases has been confirmed by XRD and thermomagnetic measurements, respectively.The occurrence of carbonate in the basal sediments might be connected to the origin of the lake depression created by a meteorite impact 3.58 ± 0.04 Ma ago (Layer, 2000).The impact may have induced hydrothermal activity, which is common after impact events where the melted/heated target material acting as heat source interacts with near-surface H 2 O (Naumov, 2002).Amongst others, calcite can be precipitated in such a hydrothermal system (Osinski et al., 2005).This process is also indicated by the existence of calcite veins in the underlaying impact breccia (U.Raschke, personal communication, 2012).

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Full Because the sedimentation rate significantly changes during the past 3.6 Ma (Nowaczyk et al., 2012), accumulation rates were calculated to evaluate the carbonate accumulation and paleobioproductivity in Lake El'gygytgyn (Fig. 6).The accumulation rates of TIC (AR TIC ) confirm the pattern already shown by the TIC concentrations, with high carbonate values at the core base, which more or less successively decrease to zero by ∼ 3.27 Ma, and a single occurrence in the sample at ∼ 223 ka.Accumulation rates of BSi (AR BSi ) and TOC (AR TOC ) show similar patterns in the lower part of the record (Fig. 6).The initial sedimentation during the first ∼ 50 kyr is characterised by high but rapidly decreasing AR BSi from > 60 to 7.3, while AR TOC fluctuate around a relatively low mean value of 0.5 g m −2 yr −1 .The high AR BSi at the base of the record does not necessarily reflect a high primary production by diatoms, because sediments deposited after the meteorite impact probably contain other amorphous silicates formed by the impact (e.g.ashes, glasses).IR absorbance caused by these components can have strong similarities to absorption bands of biogenic silica and therefore may lead to poor estimates by the BSi-FTIRS calibration model.Further, it can be assumed that biological activity was strongly impaired during the initial sedimentation in the El'gygytgyn impact structure as a consequence of the meteorite impact.This is corroborated by the almost entire absence of microfossils in the first post-impact sediments (Brigham-Grette et al., 2013).
Notable algae productivity might have been initiated as late as about 3.54 Ma ago, when both AR BSi and AR TOC increase to average rates of 30.0 and 1.0 g m −2 yr −1 , respectively, and remain high until ∼ 3.27 Ma (Fig. 6).However, both flux rates show strong variations between 6.5-81.2g m −2 yr −1 for BSi and 0.1-3.8g m −2 yr −1 for TOC, suggesting substantial fluctuations in bioproduction during this period.The period 3.54 to ∼ 3.27 Ma coincides with the early Pliocene warm period (∼ 5-3 Ma), which was characterized by ∼ 2-3 • C higher global surface temperatures compared to today (Haywood and Valdes, 2004;Brierley et al., 2009), an atmospheric pCO 2 of ∼ 400 ppmv (Pagani et al., 2010;Seki et al., 2010), reduced high-latitude ice sheet extents (Hill et al., 2010;McKay et al., 2012) and a global sea level 10-40 m above present (Raymo Introduction

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Full  , 2011).The termination of the productivity maximum at Lake El'gygytgyn between 3.25-3.29Ma is consistent with the onset of ice sheet expansion and cooling of coastal waters in Antarctica at about 3.3 Ma (McKay et al., 2012) and with decreasing pCO 2 concentrations from 3.2 Ma on (Seki et al., 2010).Pollen-based temperature and precipitation reconstructions from the El'gygytgyn sediment record suggest temperatures of 7-8 • C and precipitation values of around 400 mm yr −1 higher than today for the period between 3.6 and 3.4 Ma.Further, this period is characterized by a significantly larger size of the dominant planktonic diatom (Pliocaenicus sp.) compared to any other interval in the sediment record, indicating increased nutrient availability and reduced seasonal ice cover (Brigham-Grette et al., 2013).
During the late Pliocene and Quaternary -∼ 3.27 Ma to present -accumulation rates of BSi and TOC are considerably lower.The decreased fluxes indicate a deterioration of environmental and climatic conditions in the Siberian Arctic impeding bioproductivity.Variations in the accumulation rates are comparatively small during the past 3.27 Myr and probably an effect of large scale glacial-interglacial climate change.During these large scale cycles, bioproductivity at Lake El'gygytgyn is primarily controlled by the duration of lake ice cover.Warm periods are characterised by high aquatic primary production and a mixing of the entire water body due to the summer melt of the ice cover, while during cold periods the bioproductivity is limited due to the year-round ice cover causing a stratification of the water column with anoxic bottom waters (Melles et al., 2007).However, the dataset does not reflect the entire glacial-interglacial pattern due to the low sample resolution.

Conclusions
The results of our study demonstrate that robust FTIRS calibration models can be developed for the quantitative assessment of biogeochemical properties in very long (> 300 m) sediment records extending several million years back in time.The developed models relating FTIR spectral information to conventional measurements for Introduction

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Full TOC, TIC and BSi for the 3.6 Ma old sediment record of Lake El'gygytgyn show a good statistical performance.Furthermore, our results suggest that FTIRS provides information about the sample burial depth and therefore about post-depositional changes in sediment composition.For the sediment record of Lake El'gygytgyn, our findings indicate a dehydration/dehydroxylation of certain mineral phases with increasing burial depth/age.It remains uncertain which components are affected by these processes, but future analyses comparing IR information of single sediment components of different age might answer this question.The fact that robust FTIRS models can be developed despite the indicated diagenetic changes in the sediment column suggests that the technique is not limited to young, unconsolidated sediments.However, an internal calibration might be needed to provide results of high accuracy for sediment succession affected by diagenesis.
Our study demonstrates that FTIRS is a fast and cost-effective analytical alternative to conventional methods for the quantitative estimation of biogeochemical properties like BSi, TOC, or TIC.Its successful application to a record extending several million years back in time corroborates the potential of the technique for other lake deep drilling projects dealing with long sediment successions potentially affected by diagenetic processes.Introduction

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Full  Full Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | All three models, the 2-component FTIRS-BSi-model, the 8-component FTIRS-TOCmodel, and the 8-component FTIRS-TIC-model, are based on the spectral range from 450 to 3750 cm −1 and show a strong correlation between FTIRS-inferred and conven- Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

A 9 -
component calibration model relating spectral information to the sample burial depth (n = 329, 450-3750 cm −1 ) shows a significant correlation between the FTIRinferred and measured depth (R 2 cv = 0.85, RMSECV = 29.3m (9.4 % of the gradient), R 2 = 0.85, and RMSEP = 35.8m (11.7 % of the gradient)) (Fig. 5a).This indicates that IR spectra of sediment samples contain information on burial depth/age and thus likely on changes in sediment composition after deposition.The loading plot of the developed model shows strong similarities to the loading plot of the calibration model Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | et al.

Fig. 5 .
Fig. 5. (a,b) Conventionally measured (x-axis) versus FTIRS-inferred burial depth (y-axis) with the cross-validated coefficient of determination (R 2 cv ) and root mean square error of crossvalidation (RMSECV) resulting from the internal validation of the developed models (included wavenumbers: (a) 450-3750 cm −1 and (b) 2600-3750 cm −1 ).(c) Loadings of the developed FTIRS-burial depth calibration model showing the contribution of each wavenumber to the partial least squares regression (PLSR) model.Positive values indicate wavenumbers positively correlated to the property of interest and negative values indicate wavenumbers negatively correlated to the property of interest.Loadings are expressed by weight vectors (w • c) of the first PLSR model component (x-axis) and the corresponding spectral range (y-axis).

Table 1 .
Statistical performance of developed calibration models using wavenumbers from 450-3750 cm −1 (all WN) and selected wavenumbers (selected WN) for biogenic silica (BSi), total organic carbon (TOC), and total inorganic carbon (TIC) based on sediments from Lake El'gygytgyn.