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Shining a New Light on the Classical Concepts of Carbon-Isotope Dendrochronology

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Thomas Wieloch^*

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29 February 2024

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01 March 2024

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Abstract

Retrospective information about the climate system and plant ecophysiology are key inputs in climate and Earth system modelling. Dendrochronology provides such information with large spatiotemporal coverage, and stable carbon isotope (¹³C/¹²C) analysis across tree-ring series is among the most advanced dendrochronological tools. For the past seventy years, this analysis was performed on whole molecules, and, to this day, ¹³C/¹²C variation is attributed to ¹³C discrimination during CO₂ diffusion into leaves and assimilation by rubisco. By contrast, ¹³C discrimination by post-rubisco processes is presumed constant. Here, recently reported results on the first dataset of intramolecular ¹³C discrimination in tree rings were synthesised by variance component analysis. The emerging picture is not consistent with the classical (DR-discrimination-centred) concepts and practices of carbon-isotope dendrochronology. Specifically, leaf and stem post-rubisco discrimination each account for more variation in the data than diffusion-rubisco discrimination, i.e., post-rubisco discrimination is not constant. Furthermore, diffusion-rubisco discrimination is used widely as proxy of leaf intrinsic water-use efficiency (iWUE), a key determinant in the responses of global biogeochemical cycles to climate change. However, since diffusion-rubisco discrimination is a small component of the total data variance, whole-molecule analysis yields confounded iWUE estimates, yet intramolecular analysis will likely offer solutions. Lastly, all currently observed ¹³C/¹²C-climate relationships are attributed to diffusion-rubisco discrimination. However, here, relationships with temperature and radiation derive from leaf-level post-rubisco discrimination while relationships with precipitation derive from stem-level post-rubisco discrimination. That said, advances in mass spectrometry may soon make intramolecular ¹³C/¹²C analysis broadly available taking carbon-isotope dendrochronology to the next level.

Keywords:

Subject: Physical Sciences - Biophysics

Introduction

Tree rings are natural archives containing encoded information about plant-environment interactions and the climate of the past. This information is (to a large extent) inaccessible to manipulation and monitoring experiments, and dendrochronologists are striving to decipher it to contribute to a better understanding of the climate system, regional and global biogeochemical cycles, and plant functioning. Stable carbon isotope (¹²C, ¹³C) analysis across tree-ring series is among the most advanced dendrochronological tools available today. This tool has (inter alia) been used to reconstruct leaf intrinsic water-use efficiency (CO₂ uptake relative to H₂O loss, iWUE), air temperature, solar radiation, air relative humidity, precipitation, and drought over past centuries at various locations worldwide [1,2,3,4,5,6].

Seventy years ago, tree-ring ¹³C/¹²C ratios were measured for the first time [7,8]. While early studies analysed whole-wood samples, most recent studies analyse cellulose, a glucose polymer extracted from tree rings to preclude error due to variation in wood composition (arguments given below apply to cellulose but not necessarily to wood) [6]. Tree-ring cellulose ¹³C/¹²C data are commonly expressed in terms of ¹³C discrimination, Δ_trc, denoting carbon isotope changes caused by physiological processes [9]. Current data interpretations invoke a simple mechanistic model accounting for ¹³C discrimination accompanying two processes: CO₂ diffusion from ambient air into leaf intercellular air spaces (or chloroplasts) and carbon assimilation by rubisco [6,10,11], collectively termed diffusion-rubisco (DR) discrimination [12]. Carbon assimilated by leaf phosphoenolpyruvate carboxylase (PEPC) is thought to not enter cellulose biosynthesis or significantly affect its isotope composition [13].

Variation in DR discrimination depends on the ratio of intercellular-to-ambient CO₂ concentration [10,14]. Intercellular CO₂ concentration, in turn, varies with the rate of CO₂ supply through leaf stomata and the rate of CO₂ assimilatory demand. Since stomata respond to moisture conditions, Δ_trc correlations with humidity parameters are thought to derive from CO₂-supply-side effects on DR discrimination [6]. By contrast, CO₂ assimilation responds to air temperature and solar radiation, and corresponding Δ_trc correlations are thought to derive form CO₂-demand-side effects on DR discrimination [6]. Moreover, there is a mechanistic relationship between DR discrimination and iWUE [9,10] which forms the basis of iWUE reconstructions from Δ_trc [6,11]. Note, all current Δ_trc interpretations assume that DR discrimination governs Δ_trc variation [6]. Discrimination downstream of rubisco, denoted post-rubisco (PR) discrimination [12], is consider constant for any given species [11].

Recently, nuclear magnetic resonance spectroscopy was used (for the first time in dendrochronology) to measure intramolecular ¹³C discrimination, Δ_i’, in glucose extracted across a tree-ring series (i denotes glucose carbon position, C-1 to C-6) [12]. This provided 6-fold higher resolution than (whole-molecule) Δ_trc analysis. The dataset was shown to contain multiple independent ¹³C signals implying that DR discrimination is not the only variable component of Δ_trc [12]. Follow-up studies elucidated signal properties and put forward theories on the signals’ metabolic origins (see below, [13,15,16]). Here, the relative contribution of intramolecular ¹³C signals to Δ_trc were estimated by variance component analysis (SI Appendix, Supporting text T1). Furthermore, the capabilities of intramolecular versus whole-molecule carbon isotope analysis to investigate intramolecular ¹³C signals were compared by multiple linear regression analysis. The results from these analyses form the basis for a critical reassessment of the classical concepts and practices of carbon-isotope dendrochronology and recommendations on the future research direction of the field.

Intramolecular ¹³C Signals in Pinus nigra Tree-Ring Glucose

Previously, we measured intramolecular and whole-molecule ¹³C discrimination of glucose (Δ_i’ and Δ_glu, respectively) across an annually resolved series of Pinus nigra tree rings [12]. The dataset covers the period 1961 to 1995 but lacks measurements for 1977, 1978, 1981, and 1982 (n = 31*6). Δ_i’ was corrected for carbon redistribution by heterotrophic triose phosphate cycling (indicated by prime, 12). Results reported for tree-ring glucose (Δ_i’ and Δ_glu) presumably apply to tree-ring cellulose (Δ_trc) because the former can be expected to largely derive from the latter.

We analysed Δ₁’, Δ₂’, and Δ₃’ data pertaining to 1961 to 1980 (early period) and 1983 to 1995 (late period) separately, because the Δ_1-2’ and Δ_1-3’ series (denoting arithmetic averages of Δ₁’ and Δ₂’, and Δ₁’ to Δ₃’, respectively) exhibit a change point in 1980 [16]. This change point was also found in Δ_glu, and the variance of Δ_glu is four-fold higher during the late compared to the early period (1.47‰ versus 0.3‰, 16). Proposedly, the trees had access to groundwater during the early but not during the late period [17] causing metabolism affecting Δ₁’ to Δ₃’ to move from a largely homeostatic state into a climate-responsive state [16]. By contrast, no change point was detected in Δ₄’, Δ₅’, and Δ₆’ or average series thereof [16]. Therefore, splitting these series was not required.

We (inter alia) used multiple linear regression modelling to find environmental and physiological covariates of Δ_i’ (SI Appendix, Table S1) and proposed several ecophysiological mechanisms introducing the corresponding Δ_i’ signals (SI Appendix, Figure S1) [16]. First, air vapour pressure deficit (VPD) was found to affect both Δ₁’ and Δ₃’ during the late period (Table 1, 16). This relationship is thought to derive from DR discrimination (in leaves). Additional ¹³C discrimination by phosphoglucose isomerase (PGI) and/or glucose-6-phosphate dehydrogenase (G6PD) in leaves is thought to account for the stronger effect of VPD on Δ₁’ compared to Δ₃’. Second, during the late period, Δ₁’ and Δ₂’ are related to ε_met denoting hydrogen isotope fractionation at glucose H¹ and H², and ε_met can be substituted by precipitation without losing much of the models’ explanatory power [16,17]. These relationships are thought to derive from ¹³C discrimination by PGI and G6PD in tree stems [16]. Note, the described Δ₁’ to Δ₃’ models do not work for the early period [16]. Third, global radiation (RAD, data available from 1964) and air temperature (TMP) were found to affect Δ₄’ to Δ₆’ over the entire study period [16]. These relationships are thought to derive from ¹³C discrimination in leaves by glyceraldehyde-3-phosphate dehydrogenases (GAPDH) affecting Δ₄’ and enzymes modifying the carbon double bond of phosphoenolpyruvate affecting Δ₅’ and Δ₆’ [13,15]. For more comprehensive information about these mechanisms, the reader is referred to previous reports [12,13,15,16,18].

Components of Δ_glu Variation and Implications for Reconstructions Of Intrinsic Water-Use Efficiency

Figure 1 shows percent contributions of intramolecular isotope signals found by modelling (Table 1 and Table S1) and model residuals to Δ_glu variation for the more dynamic late period (1983 to 1995, n = 13, Δ_glu variance = 1.47‰). Data of Δ_i’ have significant measurement errors which largely account for the residuals of the Δ₁’, Δ₃’, Δ₄’, and Δ_5-6’ models (SI Appendix, Supporting text T2). By contrast, measurement errors account for only ≈30% of the residual variance of the Δ₂’ model. Hence, this model may require extensions to capture the entire systematic variation of Δ₂’. That said, the systematic Δ₂’ variation not captured by modelling accounts for only ≈9% of the total Δ_glu variation (13.1*0.7, 16). Disregarding this component, leaf ¹³C discrimination accounts for ≈43.5% of the total variance of Δ_glu while stem ¹³C discrimination (related to ε_met) accounts for ≈19.5%. Furthermore, the contribution of leaf PR discrimination (≈25.9%) exceeds the contribution of leaf DR discrimination (≈8.8%*2 ≈ 17.6%). Hence, in contrast to its current practical treatment [11], PR discrimination is neither constant in leaves nor in stems.

iWUE is regarded as an important functional property of plant ecosystems and a key determinant in the response of regional and global carbon, water, and energy cycles to climate change [19,20]. Retrospective assessment of iWUE across large spatiotemporal scales relies on Δ_trc analysis [1,2,3,4,5] which, in turn, relies on the assumption that DR discrimination governs Δ_trc variability [6,11,21]. However, DR discrimination accounts for merely ≈17.6% of the total variance of Δ_glu during the late period while PR discrimination accounts for ≈45.4% (Figure 1). Hence, in the present case, Δ_trc should probably not be used as proxy of iWUE since the iWUE signal is strongly confounded by other signals. Since the iWUE signal is better resolved at the intramolecular level, Δ_i’ analysis is expected to provide more accurate estimates of iWUE.

Findings presented for the late period are qualitatively consistent with findings pertaining to the early period (SI Appendix, Supporting text T3).

Physiological Interpretation of Δ_trc-Climate Relationships

Depending on site characteristics (dry, moist, etc.), various climate parameters may govern Δ_trc variability (‘Introduction’, 6). That said, all reported Δ_trc-climate relationships are currently interpreted with respect to DR discrimination.

At the dry site discussed here, DR discrimination responds to VPD [16]. However, while DR discrimination accounts for ≈17.6% of the total Δ_glu variance during the late period, VPD-dependent PR discrimination accounts for an additional ≈9.4% (Figure 1). Hence, both DR and PR discrimination contribute to the VPD signal in Δ_glu and their combined contribution accounts for ≈27% of the total Δ_glu variance. Interestingly, linear regression between Δ_glu and VPD falsely suggests that VPD accounts for ≈54% of the total Δ_glu variance. This twofold overestimation of the VPD signal can be expected to result from intercorrelation of VPD with other climate parameters (e.g., Pearson correlation between VPD and RAD: r = 0.6, p < 0.05, n = 13).

More importantly, relationships of Δ_glu with RAD and TMP derive from leaf-level PR discrimination [13,15,16]. Similarly, relationships of Δ_glu with ε_met and PRE derive from stem-level PR discrimination [16]. RAD-dependent PR discrimination accounts for ≈48.5% and ≈26.4% of the total Δ_glu variance during the early and late period, respectively, and exceeds the contribution of DR discrimination during both periods (Figure 1; SI Appendix, Supporting text T3). Hence, most of the climate information in Δ_glu derives from PR discrimination and this can be expected to also apply to Δ_trc.

Detecting Intramolecular Isotope Signals at the Whole-Molecule Level

It is highly interesting to ask whether intramolecular isotope analysis outperforms whole-molecule analysis or, more specifically, whether isotope signals detected in Δ_i’ can also be found in Δ_glu. To test this, Δ_glu data of the late period were modelled as function of VPD, ε_met, RAD, and TMP by multiple linear regression. Initially, potential interaction among independent variables was not considered. In the resulting model, Δ_glu is not significantly related with VPD and TMP (Table 2, M1). Subsequent models considered interaction among independent variables, and the model with the highest explanatory power is shown in Table 2 (M2). Again, in this model, Δ_glu is not significantly related with TMP. Hence, some isotope-climate relationships evident at the intramolecular level are invisible to whole-molecule analysis (cf. Table 1 and Table S1, and Figure 1). Additionally, whole-molecule analysis is blind to the intramolecular location of isotope signals and, therefore, offers no clues on the signals’ metabolic origins. Thus, intramolecular isotope analysis exceeds the capabilities of whole-molecule analysis.

Perspective

Here, recently reported results on the first dataset of intramolecular ¹³C discrimination in tree rings were synthesised. The picture emerging from this synthesis is not in line with the classical (DR-discrimination-centred) concepts and practices of carbon-isotope dendrochronology and indicates that intramolecular carbon isotope analysis has a significant disruptive potential with respect to the scientific development of the field. It is important to note, however, that all currently proposed physiological interpretations of intramolecular ¹³C signals require further testing and possibly revisions. Nevertheless, based on the large number of detected intramolecular ¹³C signals (Figure 1), the transition from whole-molecule to intramolecular carbon isotope analysis is expected to substantially enhance the amount and quality of information we can retrieve from tree rings. Furthermore, it is expected to substantially change how we interpretate and use tree-ring carbon isotope data.

Since disentangling intramolecular isotope signals by whole-molecule analysis cannot be achieved with sufficient confidence (Table 2), the field of carbon-isotope dendrochronology is strongly encouraged to enter the intramolecular level. Unfortunately, protocols using nuclear magnetic resonance spectroscopy to measure intramolecular ¹³C discrimination are labour-intensive and require technology and know-how that is inaccessible to most dendrochronological laboratories. However, protocols enabling such measurements by Orbitrap mass spectrometry are currently under development [22,23] and may soon facilitate the widespread use of intramolecular data in dendrochronology, paleoclimatology, biogeochemistry, and plant physiology. This exciting technological development will, in all probability, take our abilities to extract information archived in tree rings to the next level.

Supplementary Materials

The following supporting information can be downloaded at the website of this paper posted on Preprints.org.

Data Availability Statement

The author declares that the data supporting the findings of this study are available within the paper and its supporting information.

Acknowledgements

This work was carried out with funding from “Formas - a Swedish Research Council for Sustainable Development” (2022-02833, Grant recipient: TW).

Conflicts of Interest

None declared.

References

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Figure 1. Percent contributions of intramolecular carbon isotope signals and model residuals to Δ_glu variation for the more variable late period (1980 to 1995, n = 13, Δ_glu variance = 1.47‰). Carbon isotope signals and model residuals were found by multiple regression modelling of Δ_i’ as function of environmental and physiological covariates [16]: TMP, March to October air temperature; RAD, April to September global radiation; VPD, March to November air vapour pressure deficit; ε_met, metabolic hydrogen isotope fractionation at glucose H¹ and H². Δ_i’ denotes intramolecular ¹³C discrimination where i denotes individual glucose carbon positions and the prime denotes data corrected for ¹³C signal redistribution by heterotrophic triose phosphate cycling. Δ_glu denotes whole-glucose ¹³C discrimination. Glucose was extracted across an annually resolved tree-ring series of Pinus nigra from the Vienna Basin.

Table 1. Environmental and physiological covariates of Δ_i’ and proposed enzymatic origins of corresponding Δ_i’ signals.

			Proposed origin of introduction
Covariate	Relationship	Period	Tissue	Enzyme
Δ₁' ~ ε_met^(a)	negative	83 - 95	Stem	PGI, G6PD
Δ₁' ~ VPD	negative	83 - 95	Leaf	PGI, G6PD, Rubisco^(b)
Δ₂' ~ ε_met^(a)	negative	83 - 95	Stem	PGI
Δ₃' ~ VPD	negative	83 - 95	Leaf	Rubisco^(b)
Δ₄' ~ RAD	negative	64 - 95	Leaf	p-GAPDH, np-GAPDH
Δ₄' ~ TMP	positive	64 - 95	Leaf	p-GAPDH, np-GAPDH
Δ_5-6' ~ RAD	negative	64 - 95	Leaf	PEPC, PK, DAHPS, Enolase
Δ_5-6' ~ TMP	positive	64 - 95	Leaf	PEPC, PK, DAHPS, Enolase

Underlying models were published previously (SI Appendix, Models) [16]. Proposed origins of Δ_i’ signals in primary carbon metabolism are shown in SI Appendix, Figure S1. ε_met, Δ_i’, and Δ_5-6’ denote hydrogen isotope fractionation by metabolic processes at glucose H¹ and H², carbon isotope discrimination at glucose carbon position, i, and the arithmetic average of Δ₅’ and Δ₆’, respectively. Glucose was extracted across an annually resolved tree-ring series of Pinus nigra from the Vienna Basin. Climate data series: RAD, April to September global radiation (data available from 1964); TMP, March to October air temperature; VPD, March to November air vapour pressure deficit. Enzymes: DAHPS, 3-Deoxy-D-arabino-heptulosonate-7-phosphate synthase; G6PD, glucose-6-phosphate dehydrogenase; np- and p-GAPDH, non-phosphorylating and phosphorylating glyceraldehyde-3-phosphate dehydrogenase; PEPC, phosphoenolpyruvate carboxylase; PGI, phosphoglucose isomerase; PK, pyruvate kinase. ^(a) replacing ε_met by March to July precipitation results in models with only slightly reduced explanatory power. ^{(b) 13}C discrimination accompanying CO₂ diffusion and assimilation by rubisco is introduced into carbon metabolism at rubisco.

Table 2. Linear regression models of Δ_glu as function of ε_met, VPD, RAD, and TMP.

M1: Δ_glu ~ ε_met + VPD + RAD + TMP, 1983-1995
R² = 0.86, adjR² = 0.79, p < 0.002, n = 13
	Estimate	± SE	p ≤
Intercept	25.0	5.2	0.001
ε_met	-0.0142	0.0042	0.01
VPD	-0.00753	0.00475	0.15
RAD	-0.00475	0.00142	0.01
TMP	0.686	0.411	0.13
*M2: Δ_glu ~ ε_met + VPD RAD + TMP, 1983-1995**
R² = 0.95, adjR² = 0.91, p < 0.0003, n = 13
	Estimate	± SE	p ≤
Intercept	-21.7	14.2	0.2
ε_met	-0.0150	0.0028	0.001
VPD	0.0808	0.0263	0.02
RAD	0.0111	0.0048	0.05
TMP	0.347	0.289	0.27
*VPD RAD**	-0.0000269	0.0000079	0.01

Δ_glu and ε_met denote whole-molecule ¹³C discrimination of glucose and average hydrogen isotope fractionation caused by metabolic processes at glucose H¹ and H², respectively. Glucose was extracted across an annually resolved tree-ring series of Pinus nigra from the Vienna Basin. Climate data series: RAD, April to September global radiation; TMP, March to October air temperature; VPD, March to November air vapour pressure deficit.

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