Jukuri, open repository of the Natural Resources Institute Finland (Luke) All material supplied via Jukuri is protected by copyright and other intellectual property rights. Duplication or sale, in electronic or print form, of any part of the repository collections is prohibited. Making electronic or print copies of the material is permitted only for your own personal use or for educational purposes. For other purposes, this article may be used in accordance with the publisher’s terms. There may be differences between this version and the publisher’s version. You are advised to cite the publisher’s version. This is an electronic reprint of the original article. This reprint may differ from the original in pagination and typographic detail. Author(s): Yu Tang, Elina Sahlstedt, Giles Young, Pauliina Schiestl-Aalto, Matthias Saurer, Pasi Kolari, Tuula Jyske, Jaana Bäck & Katja T. Rinne-Garmston Title: Estimating intraseasonal intrinsic water-use efficiency from high-resolution tree- ring δ13C data in boreal Scots pine forests Year: 2022 Version: Published version Copyright: The Author(s) 2022 Rights: CC BY 4.0 Rights url: http://creativecommons.org/licenses/by/4.0/ Please cite the original version: Tang, Y., Sahlstedt, E., Young, G., Schiestl-Aalto, P., Saurer, M., Kolari, P., Jyske, T., Bäck, J. and Rinne-Garmston, K.T. (2022), Estimating intraseasonal intrinsic water-use efficiency from high- resolution tree-ring δ13C data in boreal Scots pine forests. New Phytol. https://doi.org/10.1111/nph.18649 Estimating intraseasonal intrinsic water-use efficiency from high- resolution tree-ring δ13C data in boreal Scots pine forests Yu Tang1,2 , Elina Sahlstedt1 , Giles Young1 , Pauliina Schiestl-Aalto3 , Matthias Saurer4 , Pasi Kolari3 , Tuula Jyske5 , Jaana Bäck2 and Katja T. Rinne-Garmston1 1Bioeconomy and Environment Unit, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, 00790 Helsinki, Finland; 2Faculty of Agriculture and Forestry, Institute for Atmospheric and Earth System Research (INAR) / Forest Sciences, University of Helsinki, PO Box 27, 00014 Helsinki, Finland; 3Faculty of Science, Institute for Atmospheric and Earth System Research (INAR) / Physics, University of Helsinki, PO Box 68, 00014 Helsinki, Finland; 4Forest Dynamics, Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Zürcherstrasse 111, 8903 Birmensdorf, Switzerland; 5Production Systems Unit, Natural Resources Institute Finland, Tietotie 2, 02150 Espoo, Finland Author for correspondence: Yu Tang Email: yu.tang@helsinki.fi Received: 15 June 2022 Accepted: 16 November 2022 New Phytologist (2022) doi: 10.1111/nph.18649 Key words: eddy covariance, intrinsic water- use efficiency, laser ablation, leaf gas exchange, mesophyll conductance, Pinus sylvestris L., postphotosynthetic isotopic fractionation, tree-ring δ13C. Summary � Intrinsic water-use efficiency (iWUE), a key index for carbon and water balance, has been widely estimated from tree-ring δ13C at annual resolution, but rarely at high-resolution intraseasonal scale. � We estimated high-resolution iWUE from laser-ablation δ13C analysis of tree-rings (iWUEiso) and compared it with iWUE derived from gas exchange (iWUEgas) and eddy covari- ance (iWUEEC) data for two Pinus sylvestris forests from 2002 to 2019. � By carefully timing iWUEiso via modeled tree-ring growth, iWUEiso aligned well with iWUEgas and iWUEEC at intraseasonal scale. However, year-to-year patterns of iWUEgas, iWUEiso, and iWUEEC were different, possibly due to distinct environmental drivers on iWUE across leaf, tree, and ecosystem scales. We quantified the modification of iWUEiso by postphotosynthetic δ13C enrichment from leaf sucrose to tree rings and by nonexplicit inclusion of mesophyll and pho- torespiration terms in photosynthetic discrimination model, which resulted in overestimation of iWUEiso by up to 11% and 14%, respectively. � We thus extended the application of tree-ring δ13C for iWUE estimates to high-resolution intraseasonal scale. The comparison of iWUEgas, iWUEiso, and iWUEEC provides important insights into physiological acclimation of trees across leaf, tree, and ecosystem scales under cli- mate change and improves the upscaling of ecological models. Introduction How trees respond to climate change has profound impact on the carbon and water balances in forest ecosystems (Mathias & Thomas, 2021). This is because trees regulate stomata to control carbon dioxide uptake during photosynthesis and to control water loss that occurs with transpiration. The trade-off between carbon gain and water loss can be quantified as intrinsic water- use efficiency (iWUE), expressed as the ratio between net assimi- lation rate and stomatal conductance (Osmond et al., 1980). A common approach to estimate iWUE is via analysis of stable car- bon isotope composition (δ13C) of annual tree rings (Farquhar et al., 1982, 1989). However, since tree-ring δ13C reflects a time- integrated signal (Cernusak, 2020), this method has been rarely applied for detecting high-resolution intraseasonal variations in iWUE (but see Michelot et al., 2011). Owing to recent advances in online methods for obtaining car- bon isotope data from wood, via laser ablation coupled to an iso- tope ratio mass spectrometry (hereafter LA-IRMS), the ease of determining the intraseasonal tree-ring δ13C has been greatly improved (Soudant et al., 2016; Rinne-Garmston et al., 2022). A pioneer study, which compared intraseasonal δ13C data of leaf sucrose and tree rings for Larix gmelinii (Rupr.), found similar low-frequency trends for the two records but a systematic isotopic offset, caused by postphotosynthetic isotopic fractionation (Rinne et al., 2015). In future, it needs to be verified that such consistent, common patterns between sucrose and tree-ring δ13C are also found for other species and site conditions. But consider- ing that δ13C of leaf sucrose can accurately record iWUE at leaf level (Tang et al., in press) and that the sucrose δ13C signal is transported to and laid down in tree rings (Gessler et al., 2009), there is high potential to apply LA-IRMS-derived tree-ring δ13C data for estimating iWUE at intraseasonal scale. As δ13C signal can be potentially retrieved from tree-ring archives which cover a wide range of areas and periods, such applications, if successful, will be of high value to study the short-term dynamics of CO2 and H2O trade, especially for areas and periods without instru- mental records. For a reliable and accurate estimation of iWUE from tree-ring δ13C (hereafter iWUEiso), it is important to quantify how a δ13C signal may be altered from leaf assimilates to tree rings in post- photosynthetic processes (Fiorella et al., 2022). These processes � 2022 The Authors New Phytologist � 2022 New Phytologist Foundation. New Phytologist (2022) 1 www.newphytologist.com This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Research 14698137, 0, D ow nloaded from https://nph.onlinelibrary.w iley.com /doi/10.1111/nph.18649 by L uonnonvarakeskus, W iley O nline L ibrary on [20/12/2022]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense https://orcid.org/0000-0002-2851-4762 https://orcid.org/0000-0002-2851-4762 https://orcid.org/0000-0001-8612-6007 https://orcid.org/0000-0001-8612-6007 https://orcid.org/0000-0002-1102-3553 https://orcid.org/0000-0002-1102-3553 https://orcid.org/0000-0003-1369-1923 https://orcid.org/0000-0003-1369-1923 https://orcid.org/0000-0002-3954-3534 https://orcid.org/0000-0002-3954-3534 https://orcid.org/0000-0001-7271-633X https://orcid.org/0000-0001-7271-633X https://orcid.org/0000-0002-0459-4358 https://orcid.org/0000-0002-0459-4358 https://orcid.org/0000-0002-6107-667X https://orcid.org/0000-0002-6107-667X https://orcid.org/0000-0001-9793-2549 https://orcid.org/0000-0001-9793-2549 http://creativecommons.org/licenses/by/4.0/ http://crossmark.crossref.org/dialog/?doi=10.1111%2Fnph.18649&domain=pdf&date_stamp=2022-12-19 include the use of reserves in early growing season (McCarroll et al., 2017; Fonti et al., 2018), isotopic fractionation associated with metabolic processes (Gessler et al., 2009; Rinne et al., 2015), and integration of phloem sugars that are assimilated at different canopy heights (Schleser, 1990; Bögelein et al., 2019). These processes are suggested to be species-specific and site- specific. For example, the use of reserves has been detected for Quercus petraea at a temperate forest in Fontainebleau-Barbeau (Vincent-Barbaroux et al., 2019), but not for Larix gmelinii Rupr. in the permafrost zone of Central Siberia (Rinne et al., 2015). Furthermore, whereas phloem sugars at breast height orig- inated largely from the upper crown for Fagus sylvatica, they orig- inated mainly from the inner and self-shaded crown parts for Pseudotsuga menziesii (Bögelein et al., 2019). For a certain site or tree species, concomitant high temporal tracking of leaf sucrose δ13C along with tree-ring δ13C measurements can help to quan- tify the extent of postphotosynthetic δ13C modification (fpost) and the consequent impact on the iWUEiso estimates. Such infor- mation can also be used as a guideline in studies conducted under similar growth conditions for the same species. The accuracy of iWUEiso calculation may also be improved by the use of a complex photosynthetic discrimination model, for instance, via the explicit consideration of mesophyll (Gimeno et al., 2021; Ma et al., 2021) and photorespiratory effects (Keel- ing et al., 2017; Schubert & Jahren, 2018). Nevertheless, imple- menting the complex version of photosynthetic discrimination model can be difficult (Lavergne et al., 2019, 2022), partly due to a limited understanding of mesophyll conductance (gm) and photorespiration dynamics, both of which are dependent on plant species and leaf environment (Sun et al., 2014; Schubert & Jahren, 2018). Hence, the simplified model (Farquhar et al., 1982, 1989) has been applied in the majority of iWUEiso recon- struction studies (e.g. Frank et al., 2015; Guerrieri et al., 2019). However, it is worthwhile to evaluate how mesophyll and pho- torespiratory effects may impact iWUEiso estimates, as this may help to reconcile the trends and absolute values of iWUE derived from different methods. Intrinsic water-use efficiency can be also estimated from gas exchange and eddy covariance (EC) measurements (iWUEgas and iWUEEC, respectively; e.g. Keenan et al., 2013; Medlyn et al., 2017). iWUEgas, iWUEiso, and iWUEEC represent signals at different scales: leaf level, whole-tree level, and ecosystem level, respectively. Comparisons between these ‘scale-specific’ methods not only reveal the limitations of each method (Medlyn et al., 2017) but also show promise to cross-validate different sources of iWUE data (Guerrieri et al., 2019). Since the gas exchange and EC data are of high temporal resolution, they can overall help verify the intraseasonal pattern of iWUE derived from tree-ring δ13C data, albeit uncertainties exist in each iWUE estimation method (Medlyn et al., 2017; Knauer et al., 2018; Lavergne et al., 2019). The three methods have been scantly com- pared for their absolute iWUE values, at a global scale for differ- ent plant functional types (Medlyn et al., 2017) or at a local site for different tree species (Yi et al., 2019). Studies that compare temporal changes in these iWUE estimates have not been pub- lished at intraseasonal scale, and few exist at interannual resolution (Guerrieri et al., 2019; Lavergne et al., 2019). Previous studies have demonstrated a site-specific (Martı́nez-Sancho et al., 2018; Marchand et al., 2020) and temporally dynamic (Liu et al., 2014; Wieser et al., 2018) response of interannual iWUE to environmental drivers. Further knowledge on the scale-specific temporal trends of iWUE is not only valuable for in-depth understanding of tree physiological responses to environmental change but also can improve the upscaling of ecological models. The main objective of this study was to evaluate the reliability of high-resolution tree-ring δ13C data to estimate intraseasonal changes in iWUE. For this purpose, we (1) compared the intraseasonal trends and absolute values of iWUEiso, derived from tree-ring LA-IRMS δ13C analysis, with that of iWUEEC and iWUEgas. The comparison was made using a unique set of EC and gas exchange data covering the period from 2002 to 2019, at two Scots pine-dominated boreal forests with contrasting growth conditions. Next, in the effort to reconcile differences between absolute values of the three iWUE series, we (2) quantified the impact of fpost, gm, and photorespiration on iWUEiso estimates. Furthermore, we (3) discussed the environmental and physiologi- cal controls on iWUEiso, iWUEgas, and iWUEEC at both intraseasonal and interannual scales, and strengths and weak- nesses of each iWUE estimation method. Materials and Methods Site description and environmental data The study was conducted at two boreal forests dominated by Scots pine (Pinus sylvestris L.) in northern and southern Finland (Fig. S1), both of which belong to the Stations for Measuring Ecosystem-Atmosphere Relations (SMEAR) network. The north- ern site, Värriö, is close to the arctic-alpine timberline for Scots pine. The growth conditions are harsher in Värriö, evident in the lower tree heights, sparser canopy (Fig. S1), lower temperature, and shorter growing season, compared with Hyytiälä (Table S1). More characteristics of the study sites are listed in Table S1. Air temperature (T) and relative humidity (RH) at the canopy height (16.8 m in Hyytiälä and 9 m in Värriö), precipitation, soil moisture at the topsoil, and air pressure (Pa) at ground level were retrieved from the AVAA Smart SMEAR portal (https://smear. avaa.csc.fi/). Vapor pressure deficit (VPD) was calculated from T and RH. Cumulative precipitation and the means of other envi- ronmental variables at half-hourly scale and during the daytime, which was defined as the period from 2 h after sunrise to 2 h before sunset, were calculated. Sampling and δ13C analysis Sampling To determine fpost from leaf sugars to phloem sugars and eventually to tree rings, we collected needle and phloem sam- ples during the season 2018 at both sites. One-year-old needles (1 N) and current-year needles (0 N) were collected every 1 or 2 wk from the sun-exposed top canopy of five mature trees for sugar δ13C analysis. Sampling started before the onset of radial growth (early May in Hyytiälä and late May in Värriö) and ended New Phytologist (2022) www.newphytologist.com � 2022 The Authors New Phytologist� 2022 New Phytologist Foundation. Research New Phytologist2 14698137, 0, D ow nloaded from https://nph.onlinelibrary.w iley.com /doi/10.1111/nph.18649 by L uonnonvarakeskus, W iley O nline L ibrary on [20/12/2022]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense https://smear.avaa.csc.fi/ https://smear.avaa.csc.fi/ after the cessation of radial growth (October in both sites), con- ducted all together 20 times per site. Phloem samples were col- lected at breast height from five mature trees on 6 d per site and season, twice in May and once per month from June to Septem- ber. Needle and phloem samples were put in a cool box immedi- ately upon collection, and microwaved at 600 W for 1 min within 2 h to stop metabolic activities (Wanek et al., 2001). Tree-ring samples were taken at breast height after the cessation of growth in 2019. In Värriö, one 5-mm-diameter core sample was collected from five mature trees, while in Hyytiälä, five trees were felled, and cross sections were obtained. Average δ13C from five trees was used to represent the average conditions experi- enced by trees at the study sites (Leavitt & Long, 1984). All sam- pled trees were within the 80% footprint boundaries of the EC towers, which are c. 400 m in Hyytiälä (Launiainen et al., 2022) and 200 m in Värriö (Kulmala et al., 2019). δ13C of leaf and phloem sugars Water-soluble carbohydrates (WSCs) were extracted and purified from homogenized needle and phloem samples, according to Wanek et al. (2001) and Rinne et al. (2012). Briefly, the supernatant was separated from the water extraction at 85°C and then purified by three types of sample preparation cartridges (Dionex OnGuard II H, A and P; Thermo Fisher Scientific, Waltham, MA, USA). The purified WSCs were lyophilized, dissolved in deionized water, and filtered through a 0.45-μm syringe filter (Acrodisc). δ13C of WSCs was measured using an elemental analyzer (EA; Europa EA-GSL; Sercon Ltd, Crewe, UK) coupled to an IRMS (20–22 IRMS; Sercon Ltd) at the Stable Isotope Laboratory of Luke (SILL) at Natural Resources Institute Finland (Luke, Hel- sinki). Before δ13C analysis, aliquots of solubilized WSCs were pipetted into individual tin capsules (IVA Analysentechnik, Meerbusch, Germany), freeze-dried, and wrapped. Three refer- ence materials were used to calibrate the δ13C values of WSCs, IAEA-CH3 (cellulose, −24.724‰), IAEA-CH7 (polyethylene, −32.151‰), and an in-house sucrose reference (Sigma-Aldrich, −12.22‰). Repeat measurement of a quality control material indicates a measurement precision of 0.1‰ (SD). δ13C of leaf WSCs was calculated as the average δ13C of WSCs in 1 N and 0 N. δ13C values of sucrose were analyzed at WSL (Birmensdorf, Switzerland), using a Delta V Advantage IRMS (Thermo Fisher Scientific) coupled with a high-performance liquid chromatogra- phy (HPLC) system with a Finnigan LC Isolink interface (Thermo Fisher Scientific) (Rinne et al., 2012). External sucrose standards, with known δ13C values and comparable concentra- tions to samples (from 20 to 180 ng C μl−1), were analyzed every 10 samples. Correction for HPLC-IRMS δ13C values was performed according to Rinne et al. (2012). The measurement precision of sucrose standards was 0.26‰ (SD). δ13C of leaf sucrose was calculated as the average δ13C of sucrose in 1 N and 0 N. δ13C of tree rings Tree-ring samples were air-dried before the preparation for isotope analysis. Each sample was sanded with progressively finer grades of sandpaper until ring boundaries and individual cells were clearly identifiable. To ensure that any saw- dust collected in voids and intercellular spaces did not affect the isotope signal, each sample was placed in distilled water in an ultrasonic bath for 30 min to remove the sawdust. Samples were then visually inspected under a binocular microscope. Tree rings were measured using WINDENDRO� and statistically cross- matched against local chronologies to ensure the correct year was assigned to each ring. Mobile resin and extractives of the samples were removed using a 2 : 1 mixture of toluene and ethanol in a Soxhlet extractor for a duration of 48 h (Loader et al., 1997). After extraction, any residual toluene and ethanol in the samples were removed by rinsing the samples with distilled water in the Soxhlet extractor. Samples were then air-dried. Resin-extracted wood was used for LA-IRMS analysis, as suggested by Schulze et al. (2004). Intraseasonal δ13C was analyzed for each tree-ring sample using LA-IRMS at SILL (Methods S1), following the operation principle by Schulze et al. (2004) and Loader et al. (2017). In brief, ablated dust particles were carried by helium flow through a combustion device, the resulting CO2 was collected with liquid nitrogen, and subsequently, the CO2 was released upon heating and purified in a GC-column before its introduction to IRMS. A series of 40 μm tangential laser tracks were sampled along the same radial direction on tree rings at an interval of 40 μm (years from 2010 to 2019) or 80 μm (Fig. 1a). Depending on the ring width, between 5 and 33 laser tracks per tree ring were ablated for δ13C analysis. Each sample was run against an in-house CO2 reference gas. The raw δ13C values were calibrated against USGS-55 (Mexican ziricote tree powder, −27.13‰) and an in- house reference (yucca plant powder, −15.46‰), which were both measured concurrently with the tree-ring samples. The USGS-55 and the in-house reference were in the form of a 10- mm-diameter disk, which had been prepared by compressing powder using a manual hydraulic press, providing a smooth, solid surface for ablation. In addition, IAEA-C3 cellulose paper was measured multiple times during each run for quality control of the produced δ13C values. The LA-IRMS measured δ13C value for IAEA-C3 was −24.69 � 0.24‰, which is in line with the certified value of −24.91 � 0.49‰. Spot sizes and track lengths of the reference materials were varied to produce variation in signal size, which enabled monitoring of a size effect on δ13C values, and the data were corrected when needed (Werner & Brand, 2001). Averaging and timing intraseasonal δ13C Individual tree-ring δ13C series had in general similar intrasea- sonal patterns (Figs S2, S3), enabling the calculation of site- representative tree-ring δ13C series. First, considering tree-to-tree differences in tree-ring widths, we aligned the intraseasonal tree- ring δ13C data against their relative position within a tree ring (from 0 to 1) per tree, year, and site. Then, we interpolated tree- ring δ13C per tree, year, and site against relative position from 0.05 to 1 at an interval of 0.05 (Figs S2, S3). Finally, we calcu- lated site-representative tree-ring δ13C as averages of five tree rings at the interpolated relative position. � 2022 The Authors New Phytologist� 2022 New Phytologist Foundation. New Phytologist (2022) www.newphytologist.com New Phytologist Research 3 14698137, 0, D ow nloaded from https://nph.onlinelibrary.w iley.com /doi/10.1111/nph.18649 by L uonnonvarakeskus, W iley O nline L ibrary on [20/12/2022]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense To time intraseasonal tree-ring δ13C, tree-ring growth curves against day of year (DOY) were simulated per year and site via a dynamic growth model Carbon Allocation Sink Source Interaction (CASSIA; Schiestl-Aalto et al., 2015). The performance of CAS- SIA model results was evaluated by comparison with xylogenesis observational results for years 2007, 2008, 2009, 2018, and 2019, for both sites (Methods S2; Fig. S4). With simulated growth curves, the start DOY of tracheid production and the end DOY of tracheid maturation could be determined for each site- representative tree-ring δ13C data point (Fig. 1). iWUE estimates iWUE from leaf gas exchange (iWUEgas) CO2 fluxes (A) and H2O fluxes (E) were measured online with leaf gas exchange sys- tems, as described by Altimir et al. (2002) and Aalto et al. (2014) from 2002 to 2019 at both sites. However, no data were available for years 2005 and 2014 in Hyytiälä. In brief, transparent acrylic plastic chambers were installed at the top canopy of one to four mature trees with a debudded 1- or 2-yr-old shoot enclosed. Four chamber designs were employed over the years in Hyytiälä, whereas the chamber design in Värriö was the same all the time. The non- airtight chambers were automatically closed intermittently for 50 to 80 times (in Hyytiälä) or 150 to 180 times (in Värriö) per day, with sample air drawn to gas analyzers (URAS-4; Hartmann & Braun, Siek, Germany; LI-840; Li-Cor, Lincoln, NE, USA). CO2 fluxes and E were calculated from instantaneous CO2 and H2O records taken during the first 30–40 s of chamber closure (Kolari et al., 2012). Flux data were omitted when RH exceeded 85% to avoid biased results due to adsorption of water on cham- ber walls and tubing (Altimir et al., 2006). Small fluxes (A < 0.5 μmol m−2 s−1 and E < 0.1 mmol m−2 s−1) were also discarded given the uncertainties they may cause in the calculation of iWUEgas. Half-hourly A and E data series were produced and applied to calculate iWUEgas (Eqn 1; Beer et al., 2009), where g is stomatal conductance. In the well-stirred chambers, boundary layer conductance is high (Uddling & Wallin, 2012) and thus for sim- plicity not considered in the calculation of iWUEgas. iWUEgas ¼ A=g ¼ A=E � VPD=P að Þ Eqn 1 iWUE from eddy covariance (iWUEEC) The net ecosystem CO2 exchange (NEE) and H2O flux (ET) were measured using a closed-path EC system above the stand at 24 m height from 2002 to 2017 and at 27 m height from 2018 to 2019 in Hyytiälä, and at 16.6 m height from 2012 to 2019 in Värriö. Briefly, the EC data were: screened for outliers and erroneous measurements using standard methods (Aubinet et al., 2012); fil- tered by the turbulence criteria (Markkanen et al., 2001); aver- aged to half-hourly scale and gap-filled (Kulmala et al., 2019); and corrected for the storage of CO2 below the measuring height (Kolari et al., 2009; Launiainen et al., 2016). Half-hourly gross primary production (GPP) was calculated by subtracting the modeled total ecosystem respiration from NEE (Kulmala et al., 2019). Furthermore, half-hourly GPP and ET data were discarded, when precipitation occurred before the measurements, or when RH was higher than 85% to minimize the effect of con- densation on canopy surfaces or instruments. More detailed description of the EC systems can be found in Vesala et al. (2005) and Kulmala et al. (2019), and EC data processing in Launiainen et al. (2016) and Mammarella et al. (2016). Assuming infinite aerodynamic conductance and no contribution of nontranspiratory water fluxes, half-hourly iWUEEC was calcu- lated from GPP and ET data by Eqn 2 (Beer et al., 2009), where Gs is surface conductance. Twenty-three percentage of half- hourly EC data were gap-filled. Using the gap-filled data had lim- ited impact on the temporal trends and absolute values of iWUEEC, considering that the iWUEEC series with and without days that had high percentage (≥ 50%) of gap-filled flux records were highly correlated (r = 0.98, P < 0.001). Fig. 1 Example of how the formation period of a tree-ring δ13C measurement of Scots pine was defined. (a) Relative position of a tree-ring δ13C measure- ment within a tree ring; (b) formation period of the tree-ring δ13C measurement based on the growth curves of tracheid production and tracheid matura- tion for the specific year and site. The growth curves were modeled via the Carbon Allocation Sink Source Interaction model (Schiestl-Aalto et al., 2015). First, the relative position of a δ13C measurement within a tree ring was defined, for example from 0.37 to 0.42 in (a). Then, the initial development date of the tracheids representing that δ13C measurement was determined, according to the tracheid production curve in (b) (day of year, DOY) 177 for relative position 0.37). Next, the date was defined when the tracheids for that δ13C measurement were fully mature, according to the tracheid maturation curve (DOY 202 for relative position 0.42). Finally, the obtained period representing a tree-ring δ13C value and intrinsic water-use efficiency derived therefrom (iWUEiso), in this case from DOY 177 to DOY 202, was used to align iWUEiso with iWUE derived from eddy covariance (iWUEEC) and gas exchange (iWUEgas) data. New Phytologist (2022) www.newphytologist.com � 2022 The Authors New Phytologist� 2022 New Phytologist Foundation. Research New Phytologist4 14698137, 0, D ow nloaded from https://nph.onlinelibrary.w iley.com /doi/10.1111/nph.18649 by L uonnonvarakeskus, W iley O nline L ibrary on [20/12/2022]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense iWUEEC ¼ GPP=G s ¼ GPP=ET � VPD=P að Þ Eqn 2 iWUE from tree-ring δ13C (iWUEiso) Intrinsic water-use effi- ciency can also be estimated from isotope data via the photosyn- thetic discrimination model of Farquhar et al. (1982, 1989) (Eqns 3–6). iWUEiso ¼ c a�c ið Þ=1:6 Eqn 3 Δ ¼ a þ b�að Þ � c i c a � b�amð Þ � A= gm � c a � ��f � Γ�=c a Eqn 4 Γ� ¼ 42:75 � exp 37830 � T k�298ð Þ= 298 � R � T kð Þ½ � Eqn 5 Δ ¼ δ13Cair�δ13Ctree � � = 1þ δ13Ctree=1000 � � Eqn 6 ca and ci are the atmospheric and intercellular CO2 concentra- tions, respectively; Δ is the photosynthetic discrimination; a (4.4‰) is the fractionation due to diffusion of CO2 through stomata; b (29‰) is the fractionation due to carboxylation; am (1.8‰) is the fractionation during the mesophyll CO2 transfer; f is the fractionation during photorespiration; Γ� is the CO2 com- pensation point in the absence of dark respiration in μmol mol−1, estimated according to Eqn 5 (Bernacchi et al., 2001); Tk is the leaf temperature in K, taken as the air T measured inside the chamber; R is the universal gas constant (8.3145 J mol−1- K−1); δ13Cair is the δ13C of atmospheric CO2; and δ13Ctree is the site-representative δ13C of the tree rings (resin-extracted whole wood). Event-based ca and δ13Cair values in a northern Finnish site, Pallas (67°580N, 24°70E, 565 m asl (above sea level), https:// gml.noaa.gov/dv/site/PAL.html), the closest site with continuous records for both ca and δ13Cair, were interpolated to daily scale and used. As there were no δ13Cair data observed during 2015 to 2019 in Pallas, we estimated δ13Cair from ca and the linear regres- sion between δ13Cair and ca in Pallas (Fig. S5). The average ca and δ13Cair for the formation period of each tree-ring δ13C measure- ment were used as the input for Eqns 3, 4, 6. Fractionation asso- ciated with day respiration was not considered here, considering that day respiration is intensively inhibited (Keenan et al., 2019) and has insignificant impact on Δ when net assimilation rate is high (Busch et al., 2020). To test the impact of mesophyll and photorespiratory terms on iWUEiso, we took following assumptions: with no explicit consideration of gm and f, by setting gm = ∞, f = 0, and b = 27‰, which is the simplified model widely used for esti- mating iWUEiso; constant gm of 0.127 mol m−2 s−1, cor- rected for all-sided leaf area (Stangl et al., 2019) and f = 8‰ (Ghashghaie et al., 2003); constant gm and f = 16‰ (Evans & von Caemmerer, 2013); dynamic gm varying with T (Methods S3; Sun et al., 2014) and f = 8‰; dynamic gm and f = 16‰. We compared how the absolute values of iWUEiso changed across different assumptions, and evaluated whether the intraseasonal variations or interannual trends of iWUEiso varied between different assumptions. In later sec- tions, iWUEiso from the simplified model was reported, unless otherwise specified. Data analysis To align iWUEgas, iWUEEC, and iWUEiso at intraseasonal scale, we averaged daytime iWUEgas and iWUEEC over the period rep- resenting each iWUEiso estimate (Fig. 1). For simplicity, we did not consider changes in carbon allocation rate over time. Phloem transport time from top canopy to breast height was set to 2 d in Hyytiälä and 1 d in Värriö, according to Mencuccini & Hölttä (2010), that is, each period representing an iWUEiso esti- mate (Fig. 1) was corrected for these lags. Due to differences in absolute values of iWUE and a more dampened trend in iWUEiso in comparison with the other records, iWUE series were z-scored per site, year, and method for intraseasonal comparisons. Pearson correlations between the three iWUE series were calculated per year and site. For annual values of iWUE, we compared the means of each iWUE series for the growing periods of earlywood, latewood, and the whole tree ring. To examine the significance of interan- nual iWUE trends, we applied the Mann–Kendall trend test with R package ‘Kendall’ (McLeod, 2011). All statistical analyses were made in R v.4.0.0 (R Core Team, 2020). Results Comparison of intraseasonal patterns of iWUE In Hyytiälä, iWUEiso aligned in the intraseasonal trends with iWUEEC and/or iWUEgas, except for year 2019 (Fig. 2), the year that had the smallest variations in T between June, July, and August (15.7°C, 15.9°C, and 15.2°C, respectively) among the studied years and had a small variability in tree-ring δ13C (−27.0 � 0.2‰). iWUEiso aligned clearly better with iWUEgas than with iWUEEC in years 2006, 2007, 2009, 2010, 2011, and 2016, which were marked by significantly higher VPD in June compared with other years (0.74 kPa vs 0.56 kPa, P = 0.002). In comparison, iWUEiso aligned better with iWUEEC than with iWUEgas in years 2003, 2004, 2013, and 2018. These years had higher soil temperature in May than the other years (6.9°C vs 5.8°C), although the difference was not significant (P = 0.08). In Värriö, iWUEiso, iWUEEC, and iWUEgas aligned with each other in the intraseasonal trends except for year 2012 (Fig. 3). In this year, albeit showing a similar low-frequency trend, iWUEEC and iWUEiso were not significantly correlated. In year 2012, the site experienced a dry period, with lowest precipitation amount in August among the studied years. For both sites, the intraseasonal trends of iWUEiso were clearly more dampened than that of iWUEEC and iWUEgas, when abso- lute values instead of z-scores were compared. The amplitudes of intraseasonal variations in iWUEiso, iWUEgas, and iWUEEC were 13 � 6, 24 � 8, and 29 � 9 ppm, respectively, in Hyytiälä, and 8 � 3, 19 � 6, and 30 � 14 ppm, respectively, in Värriö. This dampened intraseasonal variation in iWUEiso corresponded to a lower amplitude of intraseasonal variability in tree-ring δ13C compared with leaf sucrose δ13C (1.3‰ vs 4.3‰ in Hyytiälä; 1.3‰ vs 4.2‰ in Värriö; Fig. S6). � 2022 The Authors New Phytologist� 2022 New Phytologist Foundation. New Phytologist (2022) www.newphytologist.com New Phytologist Research 5 14698137, 0, D ow nloaded from https://nph.onlinelibrary.w iley.com /doi/10.1111/nph.18649 by L uonnonvarakeskus, W iley O nline L ibrary on [20/12/2022]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense https://gml.noaa.gov/dv/site/PAL.html https://gml.noaa.gov/dv/site/PAL.html Comparison of interannual patterns of iWUE For each three iWUE estimates, the average absolute value of iWUE did not significantly differ between the growing periods of earlywood, latewood, and the whole ring (P > 0.05, Fig. S7). Hence, for examining interannual iWUE variability, we used the average iWUE values for the whole growing season. Annual iWUEgas presented a statistically significant increasing trend in both Värriö (1.4 ppm yr−1, P = 0.01) and Hyytiälä (1.5 ppm yr−1, P = 0.03; Fig. 4). Annual iWUEiso and iWUEEC did not significantly increase during the studied period in Värriö (0.8 ppm yr−1, P = 0.20 and 0.9 ppm yr−1, P = 0.54, respec- tively) or Hyytiälä (0.7 ppm yr−1, P = 0.06 and −0.2 ppm yr−1, P = 0.40, respectively; Fig. 4). Annual iWUEgas, iWUEiso, and iWUEEC were not significantly correlated with each other for either site (Fig. 4). Among all tested environmental variables, which were ca, RH, T, VPD and soil moisture, annual iWUEgas correlated best with ca at both sites (Table 1), whereas annual iWUEiso and iWUEEC correlated best with VPD (Table 1). Impact of fpost, gm, and f on iWUEiso To reconcile differences between iWUEiso, iWUEgas, and iWUEgas, we evaluated the impact of fpost, gm, and f on iWUEiso. fpost differed between the two sites, thus posing site-specific impacts on iWUEiso. Among all analyzed carbon pools, leaf WSCs had the lowest δ13C values, whereas phloem sucrose had the highest δ13C values (Fig. 5). Water-soluble carbohydrates were significantly 13C-depleted in comparison with sucrose in both leaves (P < 0.001 for both sites) and phloem (P < 0.001 for both sites) (Fig. 5), due to the contribution of pinitol/myo- inositol (33 � 6% in leaves, and 18 � 4% in phloem) with low δ13C values (−31.4 � 0.4‰ in leaves, −30.6 � 0.6‰ in phloem). In Hyytiälä, tree-ring δ13C was 0.9‰ (P < 0.001), 2.8‰ (P < 0.001), and 0.7‰ (P = 0.03) higher than δ13C of leaf sucrose, leaf WSCs, and phloem WSCs, respectively, but 0.4‰ (P = 0.24) lower than δ13C of phloem sucrose (Fig. 5a). In Värriö, the δ13C differences from tree rings to leaf sucrose, leaf WSCs, phloem WSCs, and phloem sucrose were 0‰ 2019 0.99 *** −0.26 ns −0.27 ns 2014 0.91 *** 2009 0.52 * 0.83 *** 0.39 ns 2004 −0.47 * −0.39 ns 0.93 *** 2018 0.59 ** 0.13 ns 0.48 * 2013 −0.22 ns −0.28 ns 0.87 *** 2008 0.94 *** 0.53 * 0.57 * 2003 −0.38 ns −0.40 ns 0.93 *** 2017 0.83 *** 0.64 ** 0.62 ** 2012 0.67 ** 0.60 ** 0.71 *** 2007 0.73 *** 0.93 *** 0.51 * 2002 0.51 * 0.70 *** 0.71 *** 2016 0.84 *** 0.97 *** 0.68 ** 2011 0.84 *** 0.88 *** 0.65 ** 2006 0.72 *** 0.95 *** 0.70 *** 2015 0.76 *** 0.69 ** 0.75 *** 2010 0.17 ns 0.77 *** 0.66 ** 2005 0.96 *** Jun Jul Aug Sep Jun Jul Aug Sep Jun Jul Aug Sep Jun Jul Aug Sep Jun Jul Aug Sep 150 200 250 150 200 250 150 200 250 150 200 250 150 200 250 −2 0 2 −2 0 2 −2 0 2 −2 0 2 Date Day of year (DOY) z− sc or es o f i W U E in H yy tiä lä iWUEiso iWUEEC iWUEgas Fig. 2 Z-scores of intrinsic water-use efficiency (iWUE) of Scots pine from 2002 to 2019 in Hyytiälä. Intrinsic water-use efficiency was derived from gas exchange (iWUEgas), tree-ring δ13C (iWUEiso), and eddy covariance (iWUEEC) data. For each year, the Pearson correlation coefficient and significance level for iWUEgas and iWUEiso (upper right), iWUEEC and iWUEiso (lower right), and iWUEgas and iWUEEC (lower left) are given: *, P < 0.05; **, P < 0.01; ***, P < 0.001; ns, not significant. Middle day of year (DOY) of the formation period representing each iWUEiso data point is presented. New Phytologist (2022) www.newphytologist.com � 2022 The Authors New Phytologist� 2022 New Phytologist Foundation. Research New Phytologist6 14698137, 0, D ow nloaded from https://nph.onlinelibrary.w iley.com /doi/10.1111/nph.18649 by L uonnonvarakeskus, W iley O nline L ibrary on [20/12/2022]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense (P = 0.99), 1.6‰ (P < 0.001), 0.5‰ (P = 0.10), and − 0.7‰ (P = 0.08), respectively (Fig. 5b). Common seasonal courses existed in δ13C variability of leaf sucrose and tree rings for both sites (Fig. S6). In Hyytiälä, both leaf sucrose δ13C and tree-ring δ13C presented an inverse ‘V’ shape variation from June to September (Fig. S6a). In Värriö, δ13C of tree ring followed the general increasing trend in leaf sucrose for the whole ring forma- tion period (Fig. S6b). Taken together, fpost from leaf sucrose to tree rings was 0.9‰ in Hyytiälä but 0.0‰ in Värriö (Fig. 5). By subtracting the 0.9‰ offset from tree-ring δ13C for Hyytiälä, iWUEiso decreased by 11% (Fig. 6a). The explicit consideration of gm and f in the calculation of iWUEiso did not change the intraseasonal or interannual patterns of iWUEiso (Fig. S8), but it lowered the absolute values of iWUEiso for both sites (P < 0.001, Fig. 6). Constant gm (r = 0.96, P < 0.001) and dynamic gm (r = 0.97, P < 0.001) assumptions both produced iWUEiso that linearly correlated with iWUEiso from the simplified model. Similarly, iWUEiso from the assumptions f = 8‰ (r = 0.93, P < 0.001) and f = 16‰ (r = 0.92, P < 0.001) both linearly correlated with iWUEiso from the simplified model. iWUEgas, iWUEiso, and iWUEEC differed significantly in their absolute values for both sites (P < 0.05), in the following order: iWUEiso > iWUEgas > iWUEEC (Fig. 6). In Hyytiälä, iWUEgas and iWUEEC were on average 19% and 39%, respectively, lower than iWUEiso, whereas in Värriö, the differences were 7% and 41%. If applying constant gm and f = 8‰ and correcting iWUEiso by fpost, the differences from iWUEiso to iWUEgas and iWUEEC decreased to 1% and 25%, respectively, in Hyytiälä; and to 3% and 39%, respectively, in Värriö (Fig. 6). Discussion Validity of tree-ring δ13C for intraseasonal iWUE estimates We observed a general agreement in the intraseasonal trends of iWUEiso, iWUEgas, and iWUEEC (Figs 2, 3), which clearly sup- ports the validity of using tree-ring δ13C for estimating iWUE at 2019 0.74 *** 0.80 *** 0.89 *** 2014 0.93 *** 0.92 *** 0.93 *** 2009 0.73 *** 2004 0.63 ** 2018 0.99 *** 0.98 *** 0.98 *** 2013 0.63 ** 0.61 ** 0.89 *** 2008 0.86 *** 2003 0.89 *** 2017 0.73 *** 0.83 *** 0.82 *** 2012 0.79 *** 0.48 * 0.37 ns 2007 0.69 ** 2002 0.88 *** 2016 0.88 *** 0.58 ** 0.80 *** 2011 0.97 *** 2006 0.49 * 2015 0.69 *** 0.48 * 0.85 *** 2010 0.73 *** 2005 0.96 *** Jun Jul Aug Sep Jun Jul Aug Sep Jun Jul Aug Sep Jun Jul Aug Sep Jun Jul Aug Sep 150 200 250 150 200 250 150 200 250 150 200 250 150 200 250 −2 0 2 −2 0 2 −2 0 2 −2 0 2 Date Day of year (DOY) z− sc or es o f i W U E in V är riö iWUEiso iWUEEC iWUEgas Fig. 3 Z-scores of intrinsic water-use efficiency (iWUE) of Scots pine from 2002 to 2019 in Värriö. Intrinsic water-use efficiency was derived from gas exchange (iWUEgas), tree-ring δ13C (iWUEiso), and eddy covariance (iWUEEC) data. For each year, the Pearson correlation coefficient and significance level for iWUEgas and iWUEiso (upper right), iWUEEC and iWUEiso (lower right), and iWUEgas and iWUEEC (lower left) are given: *, P < 0.05; **, P < 0.01; ***, P < 0.001; ns, not significant. Middle day of year (DOY) of the formation period representing each iWUEiso data point is presented. � 2022 The Authors New Phytologist� 2022 New Phytologist Foundation. New Phytologist (2022) www.newphytologist.com New Phytologist Research 7 14698137, 0, D ow nloaded from https://nph.onlinelibrary.w iley.com /doi/10.1111/nph.18649 by L uonnonvarakeskus, W iley O nline L ibrary on [20/12/2022]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense high-resolution intraseasonal scale. This is partly in line with Michelot et al. (2011), where the latewood section of deciduous Quercus petraea recorded well-seasonal variations in iWUE. Nev- ertheless, our results indicate that earlywood of boreal conifers can also be a good recorder for iWUEiso. This is in line with Kress et al. (2010), although earlywood has been removed by default in some earlier annual iWUEiso studies (Waterhouse et al., 2004) in case of possible use of reserves for earlywood growth (McCarroll & Loader, 2004). Our conclusion on the suitability of both earlywood and latewood sections for iWUEiso studies is based on the following observations: variations of iWUEiso during the earlywood growing period aligned with that of iWUEEC and/or iWUEgas (Figs 2, 3); iWUEiso values averaged for the growing periods of earlywood, latewood, and the whole ring were not significantly different (Fig. S7); we did not observe a previous-year reserve δ13C signal in earlywood (Fig. S9). Factors affecting iWUEiso estimates The impact of fpost, that is, overall apparent isotope fractionation between tree rings and new assimilates, on iWUEiso has been addressed in earlier studies with a correction factor that has been obtained by measuring δ13C difference between tree rings and leaf water-soluble organic matter (Frank et al., 2015) or total organic matter (Belmecheri & Lavergne, 2020). Considering that leaf bulk materials have varying and significant δ13C offsets from new assimilates and that sucrose accurately records assimilate δ13C (Tang et al., in press), our comparison between tree rings and leaf sucrose presents a more precise quantification of fpost. From this comparison, we defined fpost of 0.9‰ for Hyytiälä but 0.0‰ for Värriö (Fig. 5), which can reduce iWUEiso by 11% in Hyytiälä (Fig. 6). In our study, the site-specific fpost values were not associated with site-specificity in the use of previous-year reserves for tree- ring growth (Fig. S9) but may be related to site-to-site differ- ences in postphotosynthetic metabolisms. First, fpost can be partly ascribed to the remobilization of 13C-enriched transitory starch during the night (Gessler & Ferrio, 2022), which causes an overall 13C-enrichment in phloem sucrose relative to leaf sucrose (Fig. 5). The proportion of starch-derived 13C-enriched sucrose in breast-height phloem depends on the phloem trans- port velocity and tree height (Gessler & Ferrio, 2022), which differed between Hyytiälä and Värriö (Table S1). Second, fpost can be affected by the mixing of assimilates formed at different canopy heights, which may have a δ13C gradient of up to 8‰ (Bögelein et al., 2019). Apparently, the vertical mixing of assimilates should have less impact on fpost for Värriö compared with Hyytiälä, on account of a sparser canopy density and therewith lower intracanopy light gradients and assimilate δ13C Fig. 4 Interannual intrinsic water-use efficiency (iWUE) of Scots pine derived from gas exchange (iWUEgas), eddy covariance (iWUEEC), and tree-ring δ13C (iWUEiso) in (a) Hyytiälä and (b) Värriö from 2002 to 2019. Yearly increase rates of iWUE and P values of Mann–Kendall trend test are given. Pearson correlations between iWUEiso and iWUEEC, between iWUEgas and iWUEEC, and between iWUEiso and iWUEgas were 0.46 (P = 0.05), 0.48 (P = 0.06) and 0.05 (P = 0.87), respectively, in Hyytiälä; and 0.55 (P = 0.16), 0.42 (P = 0.08), and −0.31 (P = 0.46), respectively, in Värriö. Table 1 Pearson correlations between environmental variables and annual intrinsic water-use efficiency (iWUE) of Scots pine. Site Variables ca RH SM T VPD Hyytiälä iWUEgas 0.59* −0.19 ns 0.11 ns 0.19 ns 0.25 ns Hyytiälä iWUEiso 0.53* −0.62** −0.50* 0.66** 0.75*** Hyytiälä iWUEEC −0.10 ns −0.76*** −0.54* 0.71*** 0.84*** Värriö iWUEgas 0.69** 0 ns −0.04 ns −0.25 ns 0 ns Värriö iWUEiso 0.55* −0.50* −0.52 ns 0.33 ns 0.58* Värriö iWUEEC 0.45 ns −0.88** −0.76* 0.86** 0.95*** Intrinsic water-use efficiency was derived from gas exchange (iWUEgas), tree-ring δ13C (iWUEiso), and eddy covariance (iWUEEC) data. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ns, not significant. The best correlation for each category is in bold. ca, ambient CO2 concentration; RH, relative humidity; SM, soil moisture; T, temperature; VPD, vapor pressure deficit. New Phytologist (2022) www.newphytologist.com � 2022 The Authors New Phytologist� 2022 New Phytologist Foundation. Research New Phytologist8 14698137, 0, D ow nloaded from https://nph.onlinelibrary.w iley.com /doi/10.1111/nph.18649 by L uonnonvarakeskus, W iley O nline L ibrary on [20/12/2022]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense gradients in Värriö (Fig. S1). Third, fpost is partly determined by the activity of phosphoenolpyruvatecarboxylase (PEPc), which favors 13C when catalyzing CO2 refixation in stems (Far- quhar, 1983) and thus enriches the organic matter. Since PEPc activity varies with temperature (Chinthapalli, 2003), which differed remarkably between our study sites (Table S1), fpost may have differed between the two sites. Fourth, fpost may be affected by the ratio between 13C-enriched cellulose and 13C- depleted lignin (Loader et al., 2003), which may vary between the two sites with different environmental conditions (Kilpelai- nen et al., 2005). While the explicit consideration of gm and f generally reduced iWUEiso values by up to 14% (Fig. 6), it did not change the intraseasonal (Fig. S8) or interannual trends of iWUEiso. This is in contrast to earlier studies that have reported the potential of gm and f for modulating isotopic discrimination in long term (Keeling et al., 2017; Lavergne et al., 2022). Our results thereby indicate that the simplified model for iWUEiso is able to capture the intraseasonal trends of iWUEiso for our study species, albeit the accuracy of absolute values of iWUEiso may benefit from a better understanding of gm dynamics in future studies. However, our results are in contrast to the report of Gimeno et al. (2021) for Eucalyptus, where a better fit between iWUEgas and iWUEiso was obtained after incorporating gm into the calculations of iWUEiso. This contradiction probably comes from the use of a constant gm value or temperature-dependent gm in this study, considering that gm can vary with photosynthetic rate and water stress (Schiestl-Aalto et al., 2021). Environmental and physiological controls on iWUE Differences in intraseasonal patterns of iWUEiso, iWUEEC, and iWUEgas existed in some cases, likely associated with environ- mental control. For instance, the intraseasonal pattern of Tree rings (a) Hyytiälä Phloem WSCs Phloem sucrose Leaf sucrose Leaf WSCs δ13 C d iff er en ce re la tiv e to tr ee ri ng s (‰ ) 0.4 0 –0.7 –0.9 –2.8 Contribution of 13C-depleted leaf pinitol Remobilization of 13C-enriched transitory starch during the night; mixing of phloem sugars formed at different canopy heights; PEPc acvitity Contribution of 13C-depleted phloem pinitol Fractionation against 13C during lignification Tree rings (b) Värriö Phloem WSCs Phloem sucrose Leaf sucrose Leaf WSCs δ13 C d iff er en ce re la tiv e to tr ee ri ng s (‰ ) 0.7 0 –0.6 –1.6 Fig. 5 δ13C difference between resin- extracted tree rings and sugar pools of Scots pine in (a) Hyytiälä and (b) Värriö, together with possible underlying mechanisms. PEPc, phosphoenolpyruvate carboxylase; WSCs, water-soluble carbohydrates. (a) (b) Fig. 6 Boxplot showing the intrinsic water- use efficiency (iWUE) of Scots pine in (a) Hyytiälä and (b) Värriö. iWUEiso, iWUEgas, and iWUEEC were derived from tree-ring δ13C, gas exchange, and eddy covariance data, respectively. iWUEiso was estimated from different assumptions of mesophyll conductance (gm) and photorespiration fractionation factor (f) and corrected by postphotosynthetic δ13C alteration (fpost). Horizontal line represents the median, box represents the interquartile range, the tails extend to 1.5 times of the interquartile range, and dots represent outliers that are outside 1.5 times of the interquartile range. Mean � SD value (ppm) for each category is given at the bottom. � 2022 The Authors New Phytologist� 2022 New Phytologist Foundation. New Phytologist (2022) www.newphytologist.com New Phytologist Research 9 14698137, 0, D ow nloaded from https://nph.onlinelibrary.w iley.com /doi/10.1111/nph.18649 by L uonnonvarakeskus, W iley O nline L ibrary on [20/12/2022]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense iWUEiso did not align with that of iWUEgas and iWUEEC for year 2019 in Hyytiälä (Fig. 2), possibly due to a dampened low- frequency trend in tree-ring δ13C data governed by low variabil- ity in T this year. It demonstrates that a certain degree of variabil- ity in environment conditions and tree-ring δ13C data within a growing season is crucial for reliable estimation of intraseasonal iWUEiso. Furthermore, the intraseasonal pattern of iWUEEC is impacted by water stress. For example, for years with higher VPD in Hyytiälä (Fig. 2) and for the dry year 2012 in Värriö (Fig. 3), iWUEEC aligned less well with iWUEiso than iWUEgas did. This is probably because iWUEEC integrates the species- specific physiological response to water stress (Yi et al., 2019) across various plant species over the stand (Table S1). Moreover, high spring temperatures tend to cause high uncertainties in gas exchange measurements, as the measuring shoot may recover fas- ter than the whole canopy, resulting in divergent variability in iWUEgas for years 2003, 2004, 2013, and 2018 in Hyytiälä (Fig. 2). Environmental drivers for annual iWUE were diverse across leaf (iWUEgas), tree (iWUEiso), and ecosystem (iWUEEC) scales (Table 1). At leaf level, rising ca tightly regulates iWUEgas (Table 1) by enhancing assimilation rate (Streit et al., 2014) and reducing gs (Brodribb et al., 2009). However, the ca effect on whole-tree level iWUEiso was reduced (Table 1), because the prevalent photosynthesis at lower canopy is limited by RuBP- regeneration and less sensitive to rising ca compared with Rubisco-limited photosynthesis at top canopy (Yang et al., 2020). At ecosystem level, the ca effect was further damp- ened (iWUEEC in Table 1) due to species-specific responses of iWUE to ca (Marchand et al., 2020) and changes in leaf area and soil water savings (Lavergne et al., 2019). Instead of ca, VPD dominated changes in annual iWUEiso and iWUEEC (Table 1), as also identified in Kannenberg et al. (2021) and Zhang et al. (2019), respectively. This is probably because carbon uptake decreases less than gs with increasing VPD (Zhang et al., 2019). We also note that environmental control on iWUE varies between interannual and intraseasonal scales and from year to year, possibly related to changes in leaf area (Launiainen et al., 2016) and soil moisture (Beer et al., 2009). The strengths and weaknesses of the three iWUE estimation methods Each of the three iWUE estimation approaches has its own strengths and weaknesses (Table 2). Eddy covariance measure- ments have the merits in the manner that global networks, such as FLUXNET (Baldocchi et al., 2001), provide EC data at vary- ing temporal coverage up to decades (Medlyn et al., 2017). How- ever, as an ecosystem-level integrated signal, EC data are not able to discern species-specific iWUE responses (Yi et al., 2019). Meanwhile, iWUEEC estimates have multiple sources of uncer- tainties (Knauer et al., 2018), including within-canopy gradients, nontranspiratory water fluxes, energy balance nonclosure, issues in NEE partitioning, aerodynamic conductance, and meteorolog- ical differences between measurement height and canopy surface. Some of these uncertainties are site-specific and may vary with time. For example, within-canopy gradient, which may result in lower iWUEEC with a higher contribution of fluxes from the Table 2 Method comparison between intrinsic water-use efficiency (iWUE) derived from gas exchange (iWUEgas), tree-ring δ13C (iWUEiso) and eddy covariance data (iWUEEC). iWUEgas iWUEiso iWUEEC Factors affecting iWUE estimates (1) Possible chamber artifacts, for example, occasional mechanical flaws and inconsistence in measurement systems over years (2) Uncertainties arising from limited sampling coverage (1) Uncertainties arising from the photosynthetic discrimination model due to, for example, limited knowledge of mesophyll conductance (2) δ13C alteration from leaf assimilates to tree rings, due to vertical mixing of assimilates, postphotosynthetic isotopic fractionation, and possible use of reserves (1) Energy balance nonclosure (2) Uncertainties in net ecosystem CO2 exchange (NEE) partitioning (3) Within-canopy gradient impacted by stand structure (4) Contribution of nontranspiratory water fluxes (5) Other sources of uncertainties, for example, aerodynamic conductance Strength of the method (1) High temporal resolution data, for example, at daily or diurnal scale (2) Information on species-specific dynamics (1) Signal is archived in tree materials and can be retrieved for sites (periods) where (when) no instrumental data are available years after tree-ring formation (2) Suitable for long-term iWUE reconstructions (3) No need for on-site δ13C measurements (4) Information on species-specific dynamics (1) High temporal resolution data (2) Continuous and long-term EC records are available for many sites globally Weakness of the method (1) Labor-intensive and requires accessing leaves of tall trees (2) Restricted in their spatial and temporal coverage (3) Low consistency in chamber systems in long term (4) Chamber systems are prone to mechanical flaws (1) May be influenced by other sources of isotopic discrimination (1) Can not resolve species-specific leaf- or tree-scale dynamics (2) Subject to noise and errors in, for instance, unclosed energy balance problem and NEE partition New Phytologist (2022) www.newphytologist.com � 2022 The Authors New Phytologist� 2022 New Phytologist Foundation. Research New Phytologist10 14698137, 0, D ow nloaded from https://nph.onlinelibrary.w iley.com /doi/10.1111/nph.18649 by L uonnonvarakeskus, W iley O nline L ibrary on [20/12/2022]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense understory (Domingues et al., 2007; Sellin et al., 2010), has a site-specific impact. iWUEEC calculated from subcanopy flux data was 30.5% lower than the gradient-integrated iWUEEC in Hyytiälä, whereas the difference was negligible in Värriö (6%). This site-specific trait rises from an open stand structure in Värriö (Fig. S1), which results in lower intracanopy light gradients and a higher coupling of air exchange to the atmosphere relative to a closed canopy structure in Hyytiälä (Wieser et al., 2018). More- over, iWUEEC is underestimated due to the contribution of non- transpiratory water fluxes (Eqn 2), mainly soil evaporation in this study as canopy evaporation should be minimal after excluding the time periods following precipitation. This underestimation is in the order of 15%, assuming soil evaporation accounted for half of forest floor ET, which contributed to c. 30% of total ecosys- tem ET at our sites (estimated from subcanopy EC data and Lau- niainen et al., 2005). However, this proportion would change with the increase in leaf area index in Hyytiälä (Table S1) but stay almost constant over the years with roughly unchanged leaf area index in Värriö. Leaf gas exchange measurements have the advantages of tracing instantaneous changes in iWUE, but this method is labor- intensive and requires accessing leaves of tall trees (Yi et al., 2019). Meanwhile, even though a global compilation of gas exchange measurements is available (Lin et al., 2015), there is currently a lack of long-term continuous datasets. Also, iWUEgas estimates are subject to uncertainties regarding chamber artifacts, limited sampling coverage, and low consistency in measurement systems in long term. Occasional mechanical flaws, for example leaks, and possible damages to the measuring shoots may affect the observed seasonal cycle. Limited sampling coverage on one or several measuring shoots on the top canopy may induce uncer- tainties, for example, during warm springs. Changes in measure- ment systems over years may bias the interannual trend of iWUEgas. Nevertheless, not including boundary layer conduc- tance in calculating iWUEgas overall has a limited impact on absolute values (Seibt et al., 2008) and intraseasonal patterns of iWUEgas (Figs 2, 3). Tree-ring δ13C can be retrieved even decades or centuries after tree-ring formation without laborious work on site (Cer- nusak, 2020). Hence, a major advantage of tree-ring δ13C records is their potential for reconstructing long-term iWUEiso. Accuracy of iWUEiso estimates can be further improved by a better under- standing of fpost, gm, and f. More importantly, our study shows that iWUE can be obtained from tree-ring δ13C at intraseasonal scale with reasonable effort using LA-IRMS, extending the appli- cation of this iWUE estimation method from annual resolution to intraseasonal resolution. This finding is inspiring in the way that it provides a valuable method for intraseasonal iWUE esti- mates, especially for sites and periods where and when no gas exchange or EC data are available. Conclusions This work presented the first comparison between intraseasonal and interannual iWUE signal derived from leaf gas exchange, tree- ring δ13C, and EC data, resting on a unique set of 18-yr-long records in two boreal forest sites. The alignment in intraseasonal iWUE trends across different methods demonstrated the reliability of tree-ring δ13C derived intraseasonal iWUE estimates. This result is of special significance to studies, which seek to detect intrasea- sonal tree physiological dynamics in terms of iWUE but with no access to instrumental data. The absolute values of iWUE across different datasets can be reconciled by taking into account an overestimation in iWUEiso of up to 11% due to fpost, and of up to 14% due to nonexplicit consideration of mesophyll and photores- piratory effects. A significant increasing interannual trend existed in iWUEgas, but not in iWUEiso or iWUEEC, for both sites, possibly resulting from a predominant control of ca on iWUEgas but VPD control on iWUEiso and iWUEEC. We encourage more across- method comparisons of iWUE at various temporal and spatial scales in the future. Such studies will not only deepen our under- standing of how trees physiologically adapt to climate change but also provide insights into ecological models in respect of linking ecological information across scales. Acknowledgements We would like to thank Esko Karvinen, Aino Ovaska, Salla Kuit- tinen, Jukka Kärki, Aino Seppänen, Marine Manche, Fana Teferra, Ari Kinnunen, Janne Levula, Juho Aalto, Teuvo Hie- tajärvi, Tarmo Kylli, Bartosz Adamczyk, Petri Kilpeläinen, and Haoran Li for their help in field work. Further thanks go to Man- uela Oettli for HPLC-IRMS δ13C analysis, Antti Tiisanoja, Natalia Kiuru, and Nikol Ilchevska for microcore preparation and microscopy analysis. This study was financially supported by the European Research Council (no. 755865), the Academy of Finland (nos. 295319, 323843), the Finnish Cultural Founda- tion (no. 00221014), and the Swiss National Science Foundation SNSF (no. 207360). Competing interests None declared. Author contributions KTR-G and YT planned and designed the study. YT, PS-A, KTR- G, ES and GY conducted fieldwork. YT prepared sugar samples for δ13C analysis. GY prepared tree-ring samples for δ13C analysis. ES conducted bulk and LA-IRMS δ13C analysis. MS conducted HPLC-IRMS δ13C analysis. PK calculated eddy covariance and leaf gas exchange data. PS-A modeled tree-ring growth via CASSIA. YT and TJ conducted xylogenesis observations. YT conducted data analysis. YT was responsible for writing the manuscript. JB and all other authors contributed to the interpretation of data and the writ- ing of the manuscript at various stages. ORCID Jaana Bäck https://orcid.org/0000-0002-6107-667X Tuula Jyske https://orcid.org/0000-0002-0459-4358 Pasi Kolari https://orcid.org/0000-0001-7271-633X � 2022 The Authors New Phytologist� 2022 New Phytologist Foundation. New Phytologist (2022) www.newphytologist.com New Phytologist Research 11 14698137, 0, D ow nloaded from https://nph.onlinelibrary.w iley.com /doi/10.1111/nph.18649 by L uonnonvarakeskus, W iley O nline L ibrary on [20/12/2022]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense https://orcid.org/0000-0002-6107-667X https://orcid.org/0000-0002-6107-667X https://orcid.org/0000-0002-6107-667X https://orcid.org/0000-0002-0459-4358 https://orcid.org/0000-0002-0459-4358 https://orcid.org/0000-0002-0459-4358 https://orcid.org/0000-0001-7271-633X https://orcid.org/0000-0001-7271-633X https://orcid.org/0000-0001-7271-633X Katja T. 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Environmental Research Letters 14: 074023. Supporting Information Additional Supporting Information may be found online in the Supporting Information section at the end of the article. Fig. S1 Locations and photographs of the study sites in Finland. Fig. S2 Intraseasonal tree-ring δ13C of Scots pine from 2002 to 2019 in Hyytiälä. Fig. S3 Intraseasonal tree-ring δ13C of Scots pine from 2002 to 2019 in Värriö. Fig. S4 Comparison of growth curves of Scots pine from CAS- SIA model and from xylogenesis observations. Fig. S5 Relationship between event-based δ13C of atmospheric CO2 (δ13Cair) and concentration of ambient CO2 (ca) in Pallas. Fig. S6 Comparison of δ13C signal in leaf sugars, phloem sugars, and resin-extracted wood of Scots pine in Hyytiälä and Värriö in 2018. Fig. S7 Boxplot showing the intrinsic water-use efficiency of Scots pine averaged for the growing periods of earlywood, late- wood, and whole ring. Fig. S8 Boxplot showing correlations between intraseasonal intrinsic water-use efficiency of Scots pine derived from different methods under different mesophyll and photorespiratory assumptions. Fig. S9 Across-border correlations in tree-ring δ13C of Scots pine, which denotes the degree of use of previous-year reserves. Methods S1 LA-IRMS systems. Methods S2 Tracheid growth curves from xylogenesis observa- tions and CASSIA model. Methods S3 Dynamic gm assumption. Table S1 General description, site characteristics, and data avail- ability for our study sites. Please note: Wiley is not responsible for the content or function- ality of any Supporting Information supplied by the authors. Any queries (other than missing material) should be directed to the New Phytologist Central Office. New Phytologist (2022) www.newphytologist.com � 2022 The Authors New Phytologist� 2022 New Phytologist Foundation. Research New Phytologist14 14698137, 0, D ow nloaded from https://nph.onlinelibrary.w iley.com /doi/10.1111/nph.18649 by L uonnonvarakeskus, W iley O nline L ibrary on [20/12/2022]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense Tang et al 2021.pdf New Phytologist - 2022 - Tang - Estimating intraseasonal intrinsic water‐use efficiency from high‐resolution tree‐ring 13C Sum�mary Intro�duc�tion Mate�ri�als and Meth�ods Site descrip�tion and envi�ron�men�tal data Sam�pling and &dgr;13C anal�y�sis Sam�pling &dgr;13C of leaf and phloem sug�ars &dgr;13C of tree rings Aver�ag�ing and tim�ing intrasea�sonal &dgr;13C iWUE esti�mates iWUE from leaf gas exchange (iWUEgas) nph18649-disp-0001 iWUE from eddy covari�ance (iWUEEC) nph18649-disp-0002 nph18649-fig-0001 iWUE from tree-ring &dgr;13C (iWUEiso) nph18649-disp-0003 nph18649-disp-0004 nph18649-disp-0005 nph18649-disp-0006 Data anal�y�sis Results Com�par�ison of intrasea�sonal pat�terns of iWUE Com�par�ison of inter�an�nual pat�terns of iWUE Impact of fpost, gm, and f on iWUEiso nph18649-fig-0002 Dis�cus�sion Valid�ity of tree-ring &dgr;13C for intrasea�sonal iWUE esti�mates nph18649-fig-0003 Fac�tors affect�ing iWUEiso esti�mates nph18649-fig-0004 Envi�ron�men�tal and phys�i�o�log�i�cal con�trols on iWUE nph18649-fig-0005 nph18649-fig-0006 The strengths and weak�nesses of the three iWUE esti�ma�tion meth�ods Con�clu�sions Acknowl�edge�ments Com�pet�ing inter�ests Author con�tri�bu�tions The data that sup�port the find�ings of this study are openly avail�able in Figshare at doi: . 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