Climate signals in tree-ring width, density and δ 13C from larches in Eastern Siberia (Russia

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(2008) xxx–xxx

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Chemical Geology xx

Climate signals in tree-ring width, density and δ13C from larches inEastern Siberia (Russia)

Alexander V. Kirdyanov a,⁎,1,2, Kerstin S. Treydte b,1,2, Anatolii Nikolaev c,3,Gerhard Helle d,3, Gerhard H. Schleser d,2

a V.N.Sukachev Institute of Forest SB RAS, Akademgorodok, Krasnoyarsk, 660036, Russiab Swiss Federal Research Institute WSL, 8903 Birmensdorf, Switzerland

c Melnikov Institute of Permafrost SB RAS Yakutsk, Russiad Research Centre Juelich GmbH, Institute of Chemistry and Dynamics in Geosphere: ICG-V, Juelich, Germany

Accepted 31 January 2008

Abstract

We present the first and longest (413 years) dataset on stable carbon isotope ratios in tree-ring cellulose (δ13C), tree-ring width(TRW), and maximum latewood density (MXD) obtained from larch trees growing on permafrost under continental climate in theSuntar Khayata mountain ridge in Eastern Siberia (Russia). With this first study we calibrate tree-ring parameters against climatequantities, and based on these results assess the potential added value of MXD and especially of δ13C complementing TRWanalysis for future climate reconstruction purposes. δ13C chronologies were corrected for human induced changes in atmosphericCO2 since AD 1800. Two different approaches were compared i) a correction referring merely to the decline in atmospheric δ13C(δ13Catm) and ii) a correction additionally accounting for the increase in atmospheric partial pressure of CO2. δ

13C chronologies arecharacterized by strong signal strength with only 4 trees representing the population signal at the site (mean inter-seriescorrelation=0.71 and EPS=0.90). δ13C variation shows low similarity to TRW and MXD, while correlation between TRW andMXD is highly significant. Correlation analysis of tree-ring parameters with gridded instrumental data (Climate Research Unit,CRU TS 2.1) over the AD 1929–2000 calibration period demonstrates that TRW and MXD react as reported from other sites atcold and humid northern latitudes: precipitation plays no significant role, but strong dependencies on monthly mean, maximum andminimum temperatures, particularly of the current summer (June to August), are found (up to r=0.60, pb0.001). Combininginstrumental data to a summer season mean (JJA) and TRW and MXD to a growth parameter mean (TRW+MXD), clearly showsthe importance of the number of frost days and minimum temperatures during summer (r=0.67, pb0.001) to dominate tree growthand highlights the potential for climate reconstruction. Carbon isotope fixation in tree rings is obviously less controlled bytemperature variables. In particular, the frost days and minimum temperature have a much smaller influence on δ13C than on treegrowth. δ13C strongly reacts to current-year July precipitation (r=−0.44, pb0.05) and June–July maximum temperature (r=0.46,pb0.001). All significant (pb0.05) correlation coefficients are higher when using the corrected δ13C chronology considering anadditional plant physiological response on increasing atmospheric CO2 concentration, than using the chronology corrected forδ13Catm changes alone. Spatial distribution of correlations between tree-ring data and climate variables for Eastern Siberia indicates

⁎ Corresponding author. Fax: +7 3912 433686.E-mail addresses: [email protected] (A.V. Kirdyanov), [email protected] (K.S. Treydte), [email protected] (A. Nikolaev),

[email protected] (G. Helle), [email protected] (G.H. Schleser).1 Authors contributed equally in this article.2 Designed the research.3 Performed the research.

0009-2541/$ - see front matter © 2008 Elsevier B.V. All rights reserved.doi:10.1016/j.chemgeo.2008.01.023

Please cite this article as: Kirdyanov, A.V., et al., Climate signals in tree-ring width, density and δ13C from larches in Eastern Siberia (Russia),Chemical Geology (2008), doi:10.1016/j.chemgeo.2008.01.023

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http://dx.doi.org/10.1016/j.chemgeo.2008.01.023


2 A.V. Kirdyanov et al. / Chemical Geology xx (2008) xxx–xxx

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that the summer temperature regime in the studied region is mostly influenced by Arctic air masses, but precipitation in July seemsto be brought out from the Pacific region. Both the combined TRW+MXD record and the δ13С record revealed a high recon-struction potential for summer temperature and precipitation, respectively, particularly on decadal and longer-term scales.© 2008 Elsevier B.V. All rights reserved.

Keywords: Tree rings; Stable carbon isotopes; Maximum latewood density; Eastern Siberia; Permafrost; Dendroclimatology

1. Introduction

Annual tree rings provide an excellent archive forinformation on environmental changes affecting treegrowth. To obtain as comprehensive and significantclimatic data (temperature, precipitation, humidity etc.)as possible, various tree-ring parameters are nowadaysused in addition to tree-ring width (TRW). Particularlymaximum latewood density (MXD) of tree-ring seriesfrom cold-moist sites has proved its potential for thereconstruction of summer temperatures on regional tohemispheric scales, mirroring high as well as low-fre-quency domains (Schweingruber et al., 1991; Briffaet al., 2001; Frank and Esper, 2005a; Büntgen et al.,2005, 2006). Carbon stable isotope analysis (δ13C) inwood is currently a rapidly developing field because ofits potential to reveal additional plant physiological in-formation e.g. on moisture influence or photosyntheticactivity (e.g. Panek, 1995; Lui et al., 1996; Panek andWaring, 1997; Edwards et al., 2000; Kagawa et al.,2003; Helle and Schleser, 2004; McCarroll and Loader,2004). Especially under warm and arid conditions stablecarbon isotope ratios of tree-ring cellulose reflectseasonal and annual changes in the trees' water regime(Ramesh et al., 1986; Leavitt and Long, 1989; Leavittand Long, 1991; Leavitt, 1992, 1993; Yakir et al., 1994;Feng and Epstein, 1995; Saurer et al., 1997; Treydte etal., 2001). A combination of widely-used ring width andwood density with other growth indicators such asheight increment, needle production, cambiumdynamics, pollen deposition or stable isotope ratiosmay improve climate reconstructions (McCarroll et al.,2003). There exist, however, only few studies evaluatingdifferent tree-ring parameters at the same sites or evenfrom identical tree individuals (Barber et al., 2000;McCarroll et al., 2003; Gagen et al., 2004, 2006;Skomarkova et al., 2006; Tardif et al., 2008-thisvolume) and only one exists from arid permafrostregions (Kagawa et al., 2003). Well-designed multi-parameter approaches at a broad range of ecologicallydifferent sites are, however, of great need (i) for a betterunderstanding of the complex plant physiologicalresponse to environmental changes and (ii) for detailed

Please cite this article as: Kirdyanov, A.V., et al., Climate signals in tree-riChemical Geology (2008), doi:10.1016/j.chemgeo.2008.01.023

climate reconstructions including diverse meteorologi-cal variables (e.g. temperature, precipitation, relativehumidity, wind speed, solar radiation etc.).

Here we present the first long-term records of TRW,MXD and δ13C obtained for individual trees growing atSuntar Khayata site in Eastern Siberia, a permafrostregion under continental climate. Temperature plays aleading role in the initiation of tree-ring growth early inthe season, but later during the vegetation period growthis limited by decreasing soil water supply for the trees(Kagawa et al., 2003). Recently it was shown that storedcarbon from previous years has a distinct impact on theisotope composition of earlywood of larch in Siberia(Kagawa et al., 2006a,b). Hence, in this study it wasexpected that the climate signal of δ13C in cellulose fromwhole tree rings (earlywood+ latewood) is affected bysignal carryover, probably leading to correlations withclimate quantities of the growing season(s) prior to theseason of tree-ring growth. Furthermore, δ13C values ofstored carbohydrates are, among others, governed bypost-photosynthetic fractionation processes (Helle andSchleser, 2004), that could result in significantly damp-ened climate signals as compared to other tree-ringparameters. Therefore, different seasonal signals ofvarious strengths should be recorded in the diversetree-ring parameters. With this study we are aiming at i)comparing TRW, MXD and δ13C obtained from thesame trees per site in a permafrost region in EasternSiberia, ii) evaluating sign and strength of tree-ringparameter relationships to climate quantities, and iii)based on these results, assessing the potential addedvalue of MXD and especially of δ13C complementingTRWanalysis for future climate reconstruction purposes.

2. Materials and methods

2.1. Study site and tree species

The study site is located in the Suntar Khayata moun-tain ridge in Eastern Siberia (63° 06′ N, 139° 05′ E,900 m a.s.l.) approximately 400–500 m below the uppertree line (Fig. 1). Preliminary dendochronological inves-tigations showed that tree radial growth in this region is

ng width, density and δ13C from larches in Eastern Siberia (Russia),


Fig. 1. Site location in Eastern Siberia. ZAP (Zapadnaya) and VOS (Vostochnaya) are the closest meteorological stations, Grid is the ClimaticResearch Unit (CRU) grid cell (TS 2.1 0.5°×0.5° resolution) used in this study.

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mainly controlled by summer temperature (Nikolaev,1999). Since trees become fairly old whilst being char-acterized by relatively high radial growth, they were seento be rather suitable for tree-ring density as well as stableisotope measurements. The region is characterized bytypical continental climate with a mean annual tempera-ture of −12.3 °C (1943–1994) and a seasonal amplitudeof 49.6 °C (minimum in January at −36.5 °C and maxi-mum in July at 13.1 °C) andmean annual precipitation of334.4 mm (1943–1994) with a maximum in the summerperiod (62% falling from June to August and 82% fromMay to September). In the long-term mean (1960–1980)70 days per year show daily temperatures above 0 °C(June–August). In the region, permafrost is one of themain environmental factors influencing vegetation dis-tribution and productivity. Depending on relief andgeology, permafrost depth in Suntar Khayata variesbetween 400 and 700 m with only 2 m of seasonallythawing from the surface in sandy soils and 0.6m in peat.Mean temperature of perennially frozen ground is −8 °Cto −10 °C (Gavrilova, 1964, 1975). The forests in thiscontinuous permafrost area are dominated by frost-tolerant Cajander larch (Larix cajanderi Mayr). Woodmaterial (cores and discs) was collected from ten dom-inant larch trees growing on a well-drained southexposed 10–15° slope with seasonal thaw depthestimated to be 1 m. The uneven-age larch stand is char-acterized by low crown projection of 30%. Trees were upto 18 m high with diameters at breast height (DBH) of18 cm and some trees even reaching 35 cm. Cores fromall ten sampled trees were used for maximum latewood


density (MXD) and ring-width (TRW) measurements.For carbon isotope measurements (δ13C) samples fromtrees with the lowest number ofmissing rings and highestcorrelation of individual TRW series with the site ring-width chronology were screened and finally four treeswere selected for further analysis (Leavitt and Long,1984; Robertson et al., 1997).

2.2. Sample and data preparation

Wood sample preparation for densitometric measure-ments (including ring-width analysis) was carried outaccording to the technique described by Schweingruber(1988). The spatial resolution of the microdensitometerDENDRO-2003 (Walesch Electronics, Switzerland)was 10 μm.

All measurements were checked for missing rings anddating errors using the program COFECHA (Holmes,1983). Prior to growth trend removal, adaptive PowerTransformation (PT; Cook and Peters, 1997) was appliedto TRW and MXD series, using the program ARSTAN(Cook, 1985). This transformation is used due to theheteroscedastic nature of raw ring-width (and partlyMXD) series with a yearly spread depending on thegrowth level. It results in homoscedastic time series withstable variance (Cook and Peters, 1997; Büntgen et al.,2004). The individual TRW and MXD series werestandardized to remove non-climatic, tree-geometry and/or age-related trends (Cook and Kairiukstis, 1990). A300-year cubic smoothing spline with 50% frequency-response cutoff was fitted to the individual records and




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residuals calculated in ARSTAN. This standardizationwas used because it is reported to be one of the mostappropriate detrending approaches for records of 300–500-year length (Frank and Esper, 2005a). The standardmaster chronology was used for MXD, but the residualone for TRW to reduce the high autocorrelation of 0.74(AC_1=0.42 for MXD and 0.41 for δ13C). Coherence ofyear-to-year variations of the tree-ring parameters, i.e.signal strength of the chronologies was estimated by inter-series correlation (rbar) and the expressed populationsignal (EPS, Wigley et al., 1984), each of them calculatedas an average of values obtained for a number of 50-yearperiods lagged by 25 years. This procedure allows cov-ering almost the whole interval of the tree-ring records.

For carbon isotope analysis tree rings were manuallydissected using a razor blade. Cellulose was extractedfrom homogenized wood samples by using sodium hy-droxide and sodium chlorite according to Sohn and Reiff(1942). Details of the procedure are given by Wiesberg(1974). 100 to 200 µg of tree-ring cellulose was com-busted to CO2 in an elemental analyser (Carlo Erba NA1500, Milan, Italy) and carbon isotope ratios of generatedCO2 were determined on an Optima-IRMS (Micromass,Ltd.Manchester, UK). δ13C is referred to the internationalstandard VPDB: δ13C (‰) = (RS /RVPDB−1)×1000,where RS and RVPDB are the molecular abundance ratiosof carbon isotopes, 13C/12C, of the sample and thestandard VPDB (Vienna Pee Dee Belemnite), respec-tively. Sample replication, including all errors of samplepreparation was better than ±0.1‰.

2.3. Stable isotope theory and δ13C corrections

The use of δ13C from tree-ring cellulose as a climateproxy is based on models which consider the fractiona-tion of the stable carbon isotopes during photosyntheticuptake of CO2 in the leaves. These models indicate thata number of direct and indirect factors influence theisotopic composition of plant organic matter, such asgenetic properties, type of photosynthesis, changes inphotosynthetic rate/RuBisCO activation and environ-mental factors such as relative humidity or precipitation,temperature, photosynthetic active radiation and atmo-spheric partial pressure of CO2 (e.g. Roeske andO'Leary, 1984; Salvucci and Crafts-Brandner, 2004;McNevin et al., 2006).

An expression for the photosynthetically generatedcarbon isotope composition in C3 plants like trees hasfirst been given by Farquhar et al. (1982) which reads inits most elementary form:

d13CTR ¼ d13Ca þ eD 1� ci=cað Þ þ eC ci=cað Þ ð1Þ


δ13CTR is the isotope value of tree material (basically onthe leaf level), eD is the fractionation for diffusion(−4.4‰) (Craig, 1954), eC is the fractionation at theCO2 fixing enzyme RuBisCO (−28‰) (Roeske andO'Leary, 1984), including the equilibrium effect forCO2 dissolution in cell sap. ci and ca are the leaf inter-cellular and ambient atmospheric CO2 concentrations,respectively.

In principle, isotope variations of plant organic mattershould be given relative to the source value, i.e. the δ13Cvalue of atmospheric CO2, because any changes in thesource value will otherwise be interpreted as a falseenvironmental or climatic signal. Therefore, isotopeshifts should be given as deviations from the sourcevalue, characterizing the 13C discrimination of the wholeprocess. This discrimination is expressed by Δ, givingthe shift of 13C/12C ratio between air (δ13Ca) and tree-ring cellulose (δ13CTR). To a good approximation Δ isgiven by:

Did13Ca � d13CTR ð2Þ

As long as δ13Ca is constant, δ13CTR variations are in-

dependent of the source. If δ13Ca is variable but known,adequate corrections can be applied and δ13CTR or Δ canbe used similarly. Note, from the expression ofΔ (Eq. (2))follows that atmospheric δ13Ca and ca, which constitutethe input level of the system, affect the carbon isotopecomposition of organic matter, either directly (δ13Ca) orindirectly (ci/ca — with regard to stomata index or sto-matal density).

Since approximately AD 1800, δ13Ca is decreasingand the atmospheric CO2 concentration is increasing dueto burning of fossil fuels and deforestation (Mook et al.,1983). δ13Ca directly controls δ

13Cp, as explained above,and therefore, δ13Cp values were corrected accordinglysince AD 1800 using measurements of atmospheric CO2

concentration and its δ13CO2 derived from ice cores(Freidly et al., 1986; Francey et al., 1999) and directmeasurements (Keeling et al., 1979; Francey et al., 1999)(McCarroll and Loader, 2004). A plant physiologicalresponse to changing atmospheric CO2 concentration (ca),however, is currently under debate, although discrimina-tion changes of up to 0.2‰/10 ppmv are reported (e.g.Feng and Epstein, 1995; Kürschner, 1996; Feng, 1999). Inthis study we tested an additional correction assuming amoderate plant physiological response on increasing ca of0.073‰/10 ppm over the last 200 years (Treydte et al.,2001), a coefficient derived from greenhouse experimentswith trees (Kürschner, 1996). Finally we used two tree-ring carbon isotope chronologies, corrected with differentapproaches: one corrected for the atmospheric change in




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δ13C only (‘common’ correction), named ‘corr1’, and asecond one including a plant physiological responsenamed ‘corr2’.

2.4. Climate data

Dendroclimatic correlation analysis of the tree-ringparameters was based on data from the nearest ClimaticResearch Unit (CRU) grid cell (63° 15′ N 139° 15′ E)(Mitchell and Jones, 2005; TS 2.1). Data available fromthis dataset allowed comparison of tree-ring chronolo-gies with mean monthly, minimum, maximum tempera-ture, precipitation and the number of frost days. Griddedmonthly temperature and precipitation data show highsimilarity to the instrumental records from the nearestmeteorological stations Vostochnaya (63° 13′, 139° 36′)and Zapadnaya (63° 13′N 138° 17′ E) both available forthe period AD 1943–1994 with correlation of instru-mental monthly temperature averaged for two stationsversus grid cell ranging from 0.82 in January andFebruary to 0.93 in May and August and for monthlyprecipitation r being from 0.69 in January to 0.95 inMay (pb0.000001). Although the CRU dataset spansthe 1901–2002 period, we cut off the early part of therecords and used the AD 1929–2000 period only basedon the beginning of instrumental measurements in thecloser region (station Oimyakon (63.3° N 143.2° E). Allcalculations were carried out in ARSTAN40c (Cook,1985), Dendrochronological Program Library (Holmes,2001), and STATISTICA 6.0 (StatSoft, Inc., 2001).

3. Results

3.1. Tree-ring parameter chronologies

The length of all three chronologies (TRW, MXD andδ13С) is 413 years (Table 1 and Fig. 2). Low annualincrement is characteristic for larch radial growth under

Table 1Characteristics of tree-ring parameter chronologies

Tree-ring parameter Number of trees/cores Time span (AD)

A. Chronologies obtained for all the measured treesTRW 10/19 1588–2000MXD 10/19 1588–2000δ13С 4/4 1588–2000

B. Chronologies obtained for trees with δ13С dataTRW 4/4 1613–2000MXD 4/4 1613–2000

SD = standard deviation of individual raw time series; AC_1 = first order aresidual chronology); rbar = inter-series correlation; EPS = expressed populatlagged by 25 years. AC_1, rbar and EPS are calculated for indexed chronol


the considered environmental conditions, with thenumber of missing rings being 2.1%. The highest var-iability among the tree-ring parameters is found for TRW.Insignificant 1st order autocorrelation (AC_1) of TRWindexed series is accounted for by data treatment, since theautocorrelation high-frequency component was removedfrom ring width by choosing the residual chronology(AC_1 for raw values of 0.74). In contrast raw MXD andδ13С chronologies are characterized by lowAC_1 of 0.42and 0.41, respectively and hence, autocorrelation was notremoved from these tree-ring data. Both, rbar and EPStestify a strong common signal in all tree-ring parameters,which leads to high synchronicity of individual chron-ologies (Fig. 2). The highest rbar for δ13С indicates par-ticularly good coherence in carbon isotope ratios. EPS ofthis tree-ring parameter clearly demonstrates that onlyfour trees with one core are satisfactory to develop apopulation representative site record, capturing more than85% of the variance of the theoretical, infinite populationchronology. This result is in contrast to TRW and MXDchronologies obtained from our four ‘isotope’ trees,which are clearly below the defined threshold of 0.85.

TRW and MXD chronologies correlate by 0.61(pb0.000001) for the well-replicated AD 1650–2000period (with 7/10 trees/cores) and indicate that particu-larly years with narrow rings show corresponding lowervalues of MXD (e.g. 1728, 1764, 1817, 1823, 1972)(Fig. 2). Similar results have been observed in the northof Siberia (Kirdyanov et al., 2007) and can be accountedfor by the specific anatomical features of extremelynarrow rings. Annual rings formed under unfavorableenvironmental conditions consist of only several trac-heids in a radial row with radial sizes smaller than usualand thinner cell walls.

Isotope ratios in tree rings seem to depend on otherfactors than TRW and MXD, since both high- and low-frequency dynamics of δ13С master chronologies (corr1and corr2) are different from those of the other parameters

Mean value SD AC_1 rbar EPS

0.29 mm 0.18 mm −0.03 0.54 0.950.86 g cm−1 0.15 g cm−1 0.41 0.40 0.91

−22.74‰ 0.68‰ 0.42 0.71 0.90

0.26 mm 0.15 mm −0.06 0.52 0.800.88 g cm−1 0.13 g cm−1 0.58 0.41 0.71

utocorrelation (of MXD and δ13C standard chronologies and of TRWion signal. rbar and EPS are mean value statistics for 50-year windowsogies (corr2 in case of δ13С).



Fig. 2. Tree-ring widths (TRW), maximum latewood density (MXD) and carbon isotopes (δ13C) with grey being individual series and black beingaveraged site chronologies. Thick grey lines indicate sample depths for each parameter (‘Number’). rbar represents mean inter-series correlation.


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(Fig. 2) what is confirmed by weak relationships ofisotope data to MXD and TRW. δ13С chronology corr2shows a slight increase after the 1950s compared to corr1(Fig. 2), with high-frequency variations, however, beingnot touched by the correction. For the period since 1650,δ13С chronologies correlate weak (pb0.05) by 0.15(corr1) and 0.13 (corr2) with MXD and insignificantlywith TRWby 0.04 (corr1) and 0.04 (corr2). This tendencyof low and/or insignificant correlations of δ13С time-series with TRWand MXD was also observed in centen-nial periods (separately for the 18th, 19th and 20th cen-tury). This finding is in linewith results from comparisonsof earlywood and latewood width with correspondingδ13C values. Positive correlations between earlywoodwidth and δ13C were found, whereas latewood width andδ13C were negatively correlated (Kagawa et al., 2003).These relationships are outweighing each other whenwidth and δ13C of total rings are compared. Consider-


ing the high correlation of TRW and MXD this suggeststhat these tree-ring parameters depend on the sameenvironmental factor, and δ13С is to be seen as a sourceof additional, but only to a certain extent independent,information.

3.2. Climate response

To capture the influence of climatic conditions ontree-ring growth, correlation analysis of TRW, MXDand δ13С with CRU TS 2.1 gridded data was carried outfor the period from previous-year April to current-yearSeptember (Fig. 3). Since we found very early in thisstudy that TRW and MXD capture rather commoninformation (Kirdyanov et al., 2007), we decided to usea composite TRW+MXD chronology as additional tree-ring parameter. For that ring width and maximumlatewood density records were adjusted in their mean



Fig. 3. Correlations of δ13C (corr2), MXD, TRWand TRW+MXD chronologies with climatic parameters over the AD 1929–2000 period. Horizontaldotted lines indicate 95% significance levels.


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and variance (z-scores= (indexed value−mean value) /standard deviation) and resulting records were averagedto the mean chronology TRW+MXD.

Generally, TRW and particularly MXD react as ex-pected and reported from other sites at cold and humidnorthern latitudes (e.g. Vaganov et al., 1996; Briffa et al.,1998; Davi et al., 2003; Knorre et al., 2006). Precipita-tion plays no significant role, but strong dependencies ontemperature particularly of the current summer (June toAugust) are found. Compared to that, previous-yearconditions are less important, although some significantcorrelation can be observed (Fig. 3). Current June is themost outstanding month initiating and influencing tree-ring growth more than the following months, with


especially TRW showing only a minor response to Julytemperatures. Interestingly, correlation coefficientsreach highest values with the number of frost daysduring summer of the current year (and significant butmuch lower values to the summer–autumn period of theprevious year). This holds also for minimum tempera-tures, the variable most closely related to frost. Com-bining, on one hand, instrumental data to a summerseason mean (JJA) and, on the other hand, TRW andMXD to a growth parameter mean (TRW+MXD),clearly pronounces the number of frost days (r=−0.67)(and minimum temperatures, r=0.67) during summer todominate tree growth and highlights the potential fortemperature reconstruction.




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Carbon isotope fixation in tree rings is obviously lesscontrolled by the variables and season described above(although significant as well), but a different signal isdominating. In contrast to the other parameters, it highlycorrelates with precipitation, particularly in July (r=−0.42 for corr1 and r=−0.44 for corr2). δ13C responseto July maximum temperature, which, however, itself issignificantly (negatively) inter-correlated with precipi-tation, is in the range of correlation coefficients forprecipitation (r=0.42 and r=0.46 for corr1 and corr2,respectively), but significantly lower than that of TRWand MXD. Concerning previous-year conditions, onlythe temperature of previous October and precipitation ofprevious November show correlations with δ13C. Interms of different δ13C correction approaches describedearlier, all correlation coefficients reaching significanceare higher when using the ‘corr2’ chronology consider-ing an additional plant physiological response on in-creasing ca, than using the chronology corrected forδ13Catm changes only.

3.3. Prospects for climate reconstructions

To explore prospects for climate reconstructions, thefollowing pairs of tree-ring parameter–climate variablewere chosen for further comparison, as showing thehighest correlations both for temperature and precipita-tion: TRW+MXDwith averaged JJA minimum tempera-ture and δ13С (corr2) with July precipitation. Bettercorrelation is found for TRW+MXD and the strength of

Fig. 4. Averaged June–August (JJA) monthly minimum temperature and Julδ13С, respectively. δ13С (corr2) was scaled by multiplying by −1. Gridded dfrom meteorological stations Vostochnaya and Zapadnaya (AD 1943–1994)


climate signal contained in this composite tree-ring pa-rameter is quite stable in time with r=0.72 for AD 1929–1964, r=0.63 for 1965–2000 and r=0.67 for the wholeAD 1929–2000 period (pb0.0001) (Fig. 4A). Year-to-year variations of δ13С are less similar to precipitationdata (Fig. 4B): correlation is high for the AD 1929–1964period (r=−0.60, pb0.001), but becomes insignificantfor the AD 1965–2000 period (r=−0.26, pb0.12), al-though still relatively high for the overall period of AD1929–2000 (r=−0.44, pb0.0001). Correlation of carbonisotope ratios to cumulative summer precipitation (JJA) issomewhat lower, but improves the temporal robustness ofthe signal with r=−0.42 for AD 1929–1964 (pb0.05),r=−0.34 for AD 1965–2000 (pb0.05) and r=−0.41for the whole AD 1929–2000 period (pb0.001) (notshown). Interestingly, the strength of all relationshipsbetween tree-ring parameters and climate variablesdecrease in the recent period, since 1965. Nevertheless,long-term trends of TRW+MXD and δ13С, pronouncedthrough distance weighted least squares fittings (McLain,1974), are pretty similar to that of the correspondentclimate variables in both cases. This demonstrates a highpotential for reconstructions of particularly decadal orlonger-term changes in both, summer temperature as wellas precipitation.

Based on these results from simple calibration analysiswith meteorological data of one single CRU grid point,we could identify the most important climate variablesdominating the tree-ring parameters studied. To establishfuture climate reconstructions, it is, however, useful to get

y precipitation adjusted from grid data versus scaled TRW+MXD andata were adjusted to values for the site based on instrumental records.




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some additional information about the spatial extension ofthe signal derived. Utilizing the KNMI climate explorer(Royal Netherlands Meteorological Institute; http://cli-mexp.knmi.nl as on November 3, 2006) enables to reachthis goal by correlating the proxy record with CRU 2.1meteo dataset (Mitchell and Jones, 2005) of all grid cellsavailable for a user-defined region.

Fig. 5 presents the spatial distribution of correlationsbetween tree-ring data and climate variables availablefor Eastern Siberia (basically precipitation sums andmean monthly temperatures). First of all, the results

Fig. 5. Correlation fields of tree-ring parameters (corr2 in case of δ13С) andKNMI climate explorer (Royal Netherlands Meteorological Institute; http://clClimatic Research Unit (CRU TS 2.1). Black dots indicate location of the st


derived using the KNMI climate explorer generallyconfirm the climate–tree-ring relationships shown inFig. 3. TRWandMXD strongly respond on JJA tempera-tures with precipitation playing no role (Fig. 5A, B).Combining TRW and MXD to a composite chronology,even improves the strength of the temperature relationship(Fig. 5C). In general, areas with significant correlations ofTRW and MXD with summer temperatures are directedlongitudinally (north–south), allowing for the assump-tion, that the summer temperature regime in the studiedregion is mostly influenced by Arctic air masses.

climate variables over the AD 1929–2000 period. Produced with theimexp.knmi.nl as on November 3, 2006) for gridded climate data fromudy site.


http://climexp.knmi.nl





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Although δ13C shows also significant correlations toJuly temperature over a vast territory (however lessstrong; Fig. 5D), it is the only parameter providingvaluable additional information on the impact of summerprecipitation. The region with significant correlations ofδ13С to July precipitation is mostly extended over theeast and south-east (Fig. 5E). It probably indicates thatthe direction air masses saturated with moisture arecoming from, namely the Pacific region.

Spatial correlation analysis of the tree-ring para-meters indicates that the results of reconstructions canbe representative for a large territory in Eastern Siberia:from Lena-river in the west to Indigirka-river in the eastand from the Arctic in the north to the Pacific in thesouth. A comparison and combination of our data withthe multi-millennial TRW chronology from the north ofYakutia (Hughes et al., 1999; Naurzbaev et al., 2003),one of the very few multi-millennial records existing inthe world, seems to be feasible.

All together, the results presented above providegood prospects for future climate reconstructions in-cluding temperature and precipitation of the summerperiod, covering large territories over Siberia.

4. Discussion

To a certain extent the climate calibration analysisrevealed the expected results for TRW, MXD and δ13Cas proxies for temperature and humidity/precipitation atpermafrost sites under continental climate. Temperaturerises above 0 °C at the end of May–beginning of Juneand permanently exceeds the physiologically importantthreshold of 5 °C for tree growth (Lindsey and Newman,1956; Hänninen, 1990; Vaganov et al., 2006) in June.Vegetation period starts at the same time and can last tillthe end of August–beginning of September. This 3-month period (JJA) reveals the highest correlationcoefficients for all tree-ring parameters with climatequantities. Basically cell numbers and latewood cellstructure define TRW and MXD, respectively (Yasueet al., 2000; Vaganov et al., 2006). Considering the shortinterval of tree growth, environmental conditions at thevery beginning of a growing season are rather importantfor the initiation of cambial activity and define thenumber of tracheids as well as the overall tree-ring cellstructure (Vaganov et al., 2006). This explains thecorrelations of TRW and MXD with June temperatureconditions being higher than those with any other singlemonth. For tree-ring δ13C, climate conditions (T and P)of July are more important than June conditions. Thereason might be that the intensity of cambial activity inJune is governed by varying temperature but fueled by a


surplus of stored carbohydrates with a certain isotopesignature that, in contrast to cambial activity, does notchange very much with temperature. With more andmore current photosynthates being incorporated intowood during the course of June and July, the varyingclimate conditions affecting 13C discrimination of theneedles become important for tree-ring δ13C.

Interestingly, at our site minimum temperature andnumber of frost days dominate tree-ring growth andformation more than maximum and mean temperaturesbeing a new result for the study region. Hence, thegrowth promoting effects of higher temperatures haveless influence than the negative effects of low tempera-tures and frost. Possible frosts and snow in August (onlong-term average the 23rd August is the first day withtemperature falling below 0 °C) can abruptly cease tree-ring formation. It explains the significant correlation ofTRW with August temperature, although TRW in thenorth of Eurasia is usually connected to temperature ofthe June–July period and MXD to temperature condi-tions of a longer period (Briffa et al., 1998; Vaganovet al., 1999; Kirdyanov et al., 2003; etc.), which partlyholds also for alpine regions (Frank and Esper, 2005a,b;Büntgen et al., 2005, 2006).

δ13С response to temperature and precipitation ofcurrent-year July is in agreement with the well-knownmodel of stable carbon isotope fractionation byFarquhar et al. (1982). Increased δ13С values in woodare directly related to the rate of carbon assimilation(photosynthetic rate) and inversely to stomatal con-ductance. The latter depends on air temperature, light,but most importantly on the amount of available waterand related transpiration. Hence, the positive relation ofδ13С to July conditions is likely connected to stomatalconductance during the period when most of photo-synthates are produced to be used in building the late-wood tracheid walls. During photosynthesis, treesattempt to optimize the relationship between waterloss and carbon acquisition, which is primarily governedby stomatal movement of the needles due to watervapour pressure difference. Since stomatal aperture is toa great extent responsible for ci/ca (Eqs. (1) and (2)) thissuggests a direct influence of relative humidity or pre-cipitation on δ13C. However, a reduction of ci can alsobe the result of increased photosynthetic activity (e.g.higher turnover of CO2 by RuBisCO) possibly due tohigher temperatures. Hence, estimating from the carbonisotope response alone, whether a plant reacts morestrongly on the CO2-supply side (stomata; water supply(relative humidity, precipitation) or the demand side(biochemical; temperature) of photosynthesis is cur-rently not possible.




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Direct influence of air temperature and precipitationon tree-ring growth and formation in the region isdampened by an additional impact of permafrost dy-namics and snow cover. On one hand, intense snowcover provides thermo-isolation of soil from extremelylow air temperatures and leads to less damage of rootsand, consequently better nutrient supply and higherphotosynthetic rates during the season. On the otherhand, late snow and seasonal permafrost melting candefine delay in initiation of tree-ring growth and, conse-quently smaller TRW (Vaganov et al., 1999; Kirdyanovet al., 2003). Additionally, melting of permafrost as wellas snow can partly reduce water stress to the tree pro-viding additional water supply and thus dampens theprecipitation signal contained in δ13C variations. An-other possible reason for extenuation of the precipitationsignal could be low relative humidity and accordinglyhigh vapour pressure deficit for trees growing in con-tinental areas. This may force stomata to close evenunder sufficient soil water supply (Zimmermann et al.,2000).

Nevertheless, from the climatologic-ecological pointof view particularly the moisture sensitivity of theisotope parameter is of great relevance and, despite ofexisting uncertainties, could be used for comprehensiveclimate reconstruction. Importantly, the strength of theclimate signals could be enhanced by including a cor-rection factor to our tree-ring δ13C records, which takesinto account a moderate plant physiological reaction onincreasing CO2 concentrations in the atmosphere(Kürschner 1996). We are aware, that this correctionmight not fully represent the “true” range of the plantresponse, but it clearly indicates, that those effects cannotbe neglected in future studies particularly when aimingto reconstruct long-term climate variations.

5. Conclusions

We have presented a new set of tree-ring data fromEastern Siberia with δ13С being one of the longest multi-parameter records in Eurasia. The comparison of carbonisotope ratios in tree rings, TRWand MXD chronologiesobtained for individual trees is the first step to establishprinciples for sample collection and to find out the nec-essary number of replicate measurements (TRW, MXD,δ13C). Furthermore, it allows extracting asmuch climaticinformation as possible from tree rings, and providesvaluable information to develop a strategy for the bestcombination of these parameters for future climate re-construction purposes. Our analysis demonstrates thebest reconstruction potential of TRW+MXD for summerminimum temperature as well as the number of frost days,


however, δ13C is the only tree-ring parameter, providingsignificant information on summer precipitation.

Further investigations will in detail concentrate on theapplication of the full 400-year chronologies for recon-structing the full range of environmental conditions inEastern Siberia over the past centuries. Moreover,oxygen isotope variations as another novel tree-ringparameter will be included, which recently could provetheir potential for long-term climate reconstruction overthe past millennium in High Asia (Treydte et al., 2006).Such a multi-parameter approach should enable to fullyexploit the potential for a spatio-temporarily robustclimate reconstruction from seasonal to centennialscales, being representative for a broad region of EasternSiberia.

Acknowledgements

Part of the work was done during the FulbrightScholarship of KAV at LTRR, University of Arizona,Tucson. KAV thanks Prof. M. Hughes for his supportand useful comments on data treatment. We also thanktwo anonymous reviewers and Dr. Iain Robertsonfor their help in improving the manuscript. Fig. 5 wasgenerated using the KNMI climate explorer (http://climexp.knmi.nl as on November 3, 2006). Financialsupport for this study was partly provided by SNSFunder SCOPES IP (IB74A0-110950), JRP (IB73A0-111134), RFBR-KKFN and by the European Union(ISONET; EVK2-CT-2002-00147 and MILLENNIUM;017008-2).

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Climate signals in tree-ring width, density and δ 13C from larches in Eastern Siberia (Russia

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