Introduction

Large amounts of nitrogen (N) are required to maintain photosynthetic activities of plant canopies, and N availability is considered to be the cornerstone of temperate forest productivity (Norby et al. 2010; Terrer et al. 2019). Given that about 75% of total foliar N is invested in chloroplasts and up to one-third of this investment partitioned specifically to light-harvesting systems (Evans and Clarke 2019), N is an important regulator of canopy function. The key N-rich components for photosynthesis are pigments such as chlorophyll (Chl) as well as photosynthetic enzymes (Raven 2013). Chlorophyll can be divided into multiple components with chlorophyll a (Chla) and chlorophyll b (Chlb) important for the primary reaction (i.e., light harvesting) step of photosynthesis. As Chla and Chlb absorb sunlight at different wavelengths, total leaf chlorophyll (Chla + Chlb) is expected to directly influence the photosynthetic capacity of plants (Croft et al. 2017; Evans and Seemann 1989; Palta 1990). Chlorophyll, therefore, intimately links N and carbon (C) availability at the cell, leaf, and plant scales in tree canopies (Li et al. 2018). These relationships are utilised in remote sensing of canopies (Asner and Martin 2008; Ollinger et al. 2013). Additionally, much of our space-based analysis of carbon cycling (e.g., Zhu et al. 2013), and remote sensing of plant health (e.g., Sims and Gamon 2002), relies on colour indices derived from the optical properties of chlorophyll.

Increasing atmospheric carbon dioxide (CO2) is expected to affect processes within terrestrial ecosystems, such as in forests, by increasing photosynthesis (Bader et al. 2010; Ellsworth et al. 2017; Gardner et al. 2021). However, trees grown in elevated CO2 (eCO2) have also been hypothesised to reallocate nitrogen (N) as a critical growth resource to maximise productivity with limited resource availability (Drake et al. 1997). To date, trees in eCO2 have been found to have lower leaf nitrogen content (per unit area; Narea, in g m−2 leaf) compared to trees grown in ambient CO2 (aCO2) (Ainsworth and Long 2005; Ellsworth et al. 2004). Any changes in Narea with future increases in ambient CO2 concentrations may have an effect on the photosynthetic apparatus and lead to changes in the tree responses to increasing CO2 (Crous et al. 2008; Major et al. 2018). The effects of eCO2 on N allocation among photosynthetic components, such as in light-harvesting processes, remain unclear (Ainsworth and Long 2005; Caldararu et al. 2020) but is important given the N limitations in temperate forests (Zaehle 2013). An understanding of changes in the light-harvesting machinery, such as photosynthetic pigments, under eCO2 is vital to assess implications on leaf and canopy processes in our future climate. Furthermore, many land surface models seek to depict the allocation of N within photosynthesis processes (Caldararu et al. 2020; Zaehle et al. 2014) and require validation in novel conditions like eCO2. Thus, understanding how N is allocated among canopy leaves in eCO2 can help us forecast future changes in ecosystem functioning and, at larger scales, changes in linked biogeochemical cycles for C, N, and water (Medlyn et al. 2015; A. P. Walker et al. 2015).

Working at leaf scale, the abundance of chlorophyll and leaf N can both be expressed per unit mass or area of leaf, the two measures being related by leaf mass per unit area (Marea; see supplementary Information; Cornelissen et al. 2003). Below, we refer to ‘content’ meaning abundance (i.e., mass) per unit area of leaf, and ‘concentration’ meaning abundance per unit mass of dry leaf.

To date, reductions in photosynthetic pigments, such as chlorophyll content (Chlarea), have been found with exposure to eCO2 across a wide range of plants (Ainsworth and Long 2005; Creydt et al. 2019; Major and Mosseler, 2021 and citations therein), although not always (Rey and Jarvis 1998; Springer and Thomas 2007). Furthermore, the magnitude of the chlorophyll reduction has ranged considerably (2–25% reduction with relatively constant eCO2; + 150–300 μmol mol−1 above ambient) (Ainsworth and Long 2005; Warren et al. 2015). In trees, eCO2-driven reductions in Chlarea have been observed in tree seedlings and saplings (Houpis et al. 1988; Oberbauer et al. 1985; Thomas 2005; Wullschleger et al. 1992) predominantly grown in pots. Far fewer studies have been conducted on aged forest-grown trees (Warren et al. 2015; Wujeska-Klause et al. 2019) and, therefore, questions remain as to how eCO2 may affect Chlarea in mature forests. Previous research has highlighted that responses of trees grown in artificial environments, such as in chambers or pots, may not reflect that of mature forest-grown trees (Norby et al. 2016). Differences in plant responses are suggested to be the result of limitations associated with these artificial environments, such as root restrictions and nutrient limitations (Berntson et al. 1993; Hättenschwiler et al. 1997). Frequently, studies that report eCO2-driven reductions in chlorophyll content (Chlarea) have found similar reductions in foliar nitrogen content (Narea), suggesting that the response is dependent upon nutrient availability to the plant (Stitt and Krapp 1999) and indicates that N allocation to chlorophyll follows the pattern of total N in eCO2 (Cavender-Bares et al. 2000; Warren et al. 2015; Wujeska-Klause et al. 2019). In contrast, other studies have found reductions in chlorophyll concentrations (Chlmass), alongside reduced Nmass, but not Chlarea, implying that eCO2-related declines in Chlmass may be the result of morphological changes in Marea, that is, in a dilution effect, rather than limitations to, or the reallocation of, foliar N (Epron et al. 1996; Sholtis et al. 2004). With eCO2, plants may also alter the N allocation within the leaf to maximise photosynthesis; thus, one possibility may lead to eCO2-induced reductions in N investment in the light-harvesting photosynthetic apparatus (Ainsworth and Long 2005; Caldararu et al. 2020). If this is the case, eCO2 may lead to changes in canopy functioning in the future through these changes in N investment to components of leaf function. However, both the magnitude of changes in Chlmass and Chlarea in old forest-grown trees, and whether N allocation to chlorophyll changes with eCO2, remain unclear due to a lack of studies conducted on this topic (Warren et al. 2015; Wujeska-Klause et al. 2019).

In addition to the effects of eCO2, changes to Chlmass and Chlarea are known to occur spatially through the vertical canopy profile in forested systems as a result to changes in light (Hikosaka et al. 2016; Larcher, 2003; Richardson et al. 2002). For example, Chlmass was observed to increase with decreasing height in the canopy in a mature beech forest (up to 20 m) (Scartazza et al. 2016). Equivalently, Chlmass has been found to correlate negatively with increasing light levels (Lichtenthaler et al. 2007; Niinemets, 2007), whereby leaves developing under low light were found to allocate more nitrogen to light-harvesting components, such as chlorophyll, to increase light capture efficiency (Valladares and Niinemets 2008). In contrast, Chlarea is found to correlate positively with increasing light levels due to changes in Marea outweighing changes in Chlmass (Lichtenthaler et al. 2007). Both Marea and Narea have been observed to decrease from canopy top to bottom in both temperate (Ellsworth and Reich 1993; Koike et al. 2001) and tropical forests (Cavaleri et al. 2010; Kenzo et al. 2012). In broad-leaved canopies, Nmass often displays no, or a very small, gradient across the canopy (Ellsworth and Reich 1993; Montpied et al. 2009; Niinemets 1997). As a result, the vertical gradient in Narea is influenced by the gradient of Marea across the canopy. Therefore, it is common to observe a relationship between Marea and Chlarea both, presumably, driven by the vertical profiles of light effects on leaf development and thickness in forest canopies (Catoni et al. 2015; Ellsworth and Reich 1993; Jin et al. 2014; Wyka et al. 2012). However, the interactive effect of canopy position and eCO2 on Chlarea in aged forest trees has received no attention. Quantifying any interaction of responses to eCO2 and canopy position will be useful in understanding whole plant optimisation strategies (e.g., Walker et al. 2018) and whole canopy responses to future environmental change (Catoni et al. 2015).

The present study investigates Chlmass and Chlarea, Nmass, Narea, and Marea, across the vertical profile of the canopy-dominant species, Quercus robur, at the Birmingham Institute of Forest Research Free Air CO2 Enrichment (BIFoR FACE) facility in the 3rd and 4th season of eCO2 fumigation. Our objectives were to quantify the effect of eCO2 and canopy position on Chlmass and Chlarea, in addition to foliar N and Marea, for this Q. robur canopy. Our expectations were that (i) that Chlmass would increase from the top to bottom of the live canopy of canopy dominants, whilst Chlarea would decrease along this gradient, and (ii) that Chlarea would be unchanged by eCO2. Quantifying the effects of eCO2 and canopy position on Chlmass and Chlarea in an old-aged forest tree species will provide useful information to understand the sensitivity of photosynthetic pigments to changes in the physical environment and future climate. Furthermore, an understanding of N allocation in canopy leaves in eCO2 can help us understand potential effects of eCO2 on canopy processes, biogeochemical changes, and may provide new tools for monitoring canopy status in eCO2.

Methods

Site description

This study was conducted at the Birmingham Institute of Forest Research (BIFoR) Free Air Carbon Enrichment (FACE) facility located in Staffordshire (52.801°N, 2.301°W), United Kingdom. The BIFoR FACE facility is positioned in a mature northern temperate broadleaf deciduous woodland consisting of an over storey canopy dominated by 175-year-old English oak (Q. robur). Within the forest, six replicate circular experimental plots of woodland (~ 30 m in diameter) were established and encircled by 25 m tall steel structures (Hart et al. 2020). Three of these FACE plots are ambient controls (aCO2) (CO2 mole fraction ca. 405 μmol mol−1 at the time of measurements) and the remaining three plots are treatment plots supplied with CO2 enriched air, named elevated CO2 plots (eCO2) (ca. + 150 μmol mol−1 above ambient so receiving ca. 555 μmol mol−1). Across the study period, the mean day-time CO2 was 543 (± 24) μmol mol−1 in the eCO2 plots and 406 (± 13) μmol mol−1 in the ambient control plots (see Supplementary Fig. 1.). In each plot, canopy access to Q. robur trees was gained through a rope canopy access system (CAS) (Total Access Ltd., UK) (Gardner et al. 2021). One oak tree per plot (n = 3) was accessible using the CAS system as set up during this study. This facilitated in situ measurements (see details below) by allowing access to all canopy positions of each tree. Canopy positions were defined as follows: upper (top 2 m, generally between 20 and 25 m), middle (12–15 m), and lower canopy (8–10 m) for a typical 25 m Q. robur tree at BIFoR FACE. Further details of the site description can be found at (Hart et al. 2020) and (Gardner et al. 2021).

Chlorophyll measurements and plant material

To assess the effect of eCO2 and canopy position, chlorophyll content measurements were taken monthly, May to October, in 2019 and 2020. Chlorophyll content was measured using a portable Minolta chlorophyll meter SPAD-502 Plus (Konica-Minolta, Japan, SPAD-502) and a subsequent in vitro calibration was conducted using chemical chlorophyll extractions (See supplemental information). SPAD readings were taken in all six plots (3 ambient replicates and 3 elevated replicates) between 10:00 and 16:00 in the defined upper, middle, and lower canopy positions of Q. robur (see ‘Site description’). The adaxial side of the leaves were placed toward the emitting window of the instrument with the midrib and major veins being avoided and SPAD values were measured close to the midpoint of the leaf. The mean of three readings per leaf was taken to obtain one reading per leaf. In 2019, 30 leaves per canopy position per tree were measured and 15 leaves per canopy position per tree were measured in 2020.

Leaf samples were collected from the upper and lower canopy in July and August of 2019 and 2020, by arborist climbers, and stored immediately at -25 °C. Two upper canopy leaves, from one tree per plot, were selected for nutrient analysis (see ‘Leaf N analyses’ below); these trees corresponded to the measurement tree for SPAD measurements. Each leaf was photographed on white graph paper, with a ruler for reference. Leaf area analysis was conducted using imaging software Image J (IMAGE J v1.53, National Institutes of Health, Bethesda, MD, USA).

Leaf N analyses

Leaf material dried at 70 °C for at least 72 h, weighed for dry weight, and stored until further analysis. Known weights (~ 2 mg) of dried leaf fragments were ground and each sample was analysed for N using an elemental analyser interfaced with an isotope ratio mass spectrometer (Sercon Ltd., Cheshire, UK). Foliar N values were expressed as mg N per leaf dry weight (Nmass) and subsequently N per area (Narea).

Statistical analysis

Statistical analyses were performed in R version 4.0.3 (R Core Team, 2020). Before statistical analysis, all data were checked for normality by inspection of the Q–Q plots and Levene’s test.

SPAD-derived Chlmass and Chlarea, over the two growing seasons of 2019 and 2020, were analysed using a linear mixed-effects model (‘lmer’ package). Fixed categorical factors in this model were sampling year (i.e., 2019 or 2020), sampling month, canopy position (i.e., upper, middle or lower canopy), and CO2 treatment (i.e., aCO2 or eCO2). Additionally, ‘Marea’ and ‘plot’ were represented as random factors, the latter as individual trees were nested within each experimental plot. An additional linear mixed-effects model analysed Marea, area-based leaf nitrogen (Narea) and mass-based leaf nitrogen (Nmass) with sampling year, sampling month, canopy position and CO2 treatment as fixed categorical factors and ‘plot’ represented as a random factor. For all analyses, P values of < 0.05 were considered statistically significant and type III F-statistics associated with the mixed model analysis [repeated-measures analysis of variance (ANOVA)] were reported. When a main effect was found significant, it was further tested using a post hoc Tukey’s test using the R package “emmeans”.

The sample size in this study was n = 3 replicates, which is the number of replicate treatment plots at the BIFoR FACE site, and includes within-tree replicates that were averaged per plot before analysis. All three plot replicates were sampled, except for May 2019 where replicates were reduced to two, due to logistic constraints of safe tree access.

Results

The empirical relationship between SPAD values and photosynthetic pigment concentrations

There were strong positive and mildly non-linear correlations (p < 0.001) between SPAD values and extracted leaf chlorophyll and carotenoid concentrations for mature Q. robur (Supplementary Fig. 2; Supplementary Table 1). The empirical relationship obtained between total Chlmass and SPAD values can be represented by either linear, logarithmic, or quadratic fits (S Fig. 2a; S Table 1) according to goodness-of-fit criteria. Based on the criteria of high R2 and low RMSE, the logarithmic model was judged the best fit, whilst the quadratic and linear models performed similarly, but not as well as the logarithmic model (R2 values for all three models at 0.78).

Table 1 Linear mixed-effects model showing the statistical significance of year, month, canopy position, and CO2 treatment and their relevant interactions on chlorophyll concentration (Chlmass) in Q. robur trees
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Seasonal and inter-annual variations in chlorophyll

SPAD-derived measurements show that, in the two measurement years, each spring had a flush of foliage that comprised low Chlmass and Chlarea but rapidly rose over June and July, attaining a broad Chlmass maximum that persisted through summer and into early autumn (Fig. 1). A gradual decline in Chlmass and Chlarea began in September as the leaves start to senesce. In both sampling years, first autumnal leaf tint was recorded by visual observation in late September (18th and 29th of September, respectively) and first autumnal leaf fall occurred just under a month later (13nd and 26th Oct, respectively). The monthly differences for Chlmass and Chlarea were significant (Table 1, P < 0.001). Additionally, a significant year x month interaction was observed, where significantly lower total Chlmass and Chlarea were reported in May and June of 2019, compared to their 2020 counterparts (Table 1, P < 0.05) (Supplementary Fig. 3).

Fig. 1
figure 1

Mean monthly chlorophyll, expressed per unit mass (Chlmass) (mg g−1) (a, c) and per unit area (Chlarea) (g m−2) (b, d), across the growing seasons of 2019 (a, b) and 2020 (c, d). Points are staggered for clarity. Colours indicate the three different canopy layers; ‘upper’ (blue), ‘middle’ (green), and ‘lower’ (red) for Q. robur under ambient CO2 (aCO2) at the BIFoR FACE facility. Each point represents the six experimental plots at BIFoR FACE

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Effects of canopy position and elevated CO 2

Common to both sampling years, Chlmass was significantly higher in lower canopy leaves than in upper canopy leaves (Table 1, P < 0.05). Chlmass was 14% and 12% higher in the lower canopy leaves when compared to upper canopy in 2019 and 2020, respectively. In contrast, when expressed on an area basis (Chlarea), there was significantly higher Chlarea in the higher canopy leaves when compared to the lower canopy leaves (Table 1, P < 0.05). This study also found a significant month x canopy position effect for Chlmass, whereby significantly lower Chlmass was reported in August and May in upper canopy foliage in 2019 and 2020, respectively.

There was no effect of eCO2 on Chlmass (Fig. 2, Table 1). There was a significant increase in Chlarea, but this effect was removed once Marea had been accounted for (Fig. 2, Table 1). Additionally, there was no significant interaction between CO2 treatment x canopy position in either Chlmass or Chlarea.

Fig. 2
figure 2

Mean monthly chlorophyll, expressed per unit mass (Chlmass) (mg g−1) and per unit area (Chlarea) (mg cm−2), across the growing seasons of 2019 (a, b) and 2020 (c, d). Points are staggered for clarity. Colours indicate the CO2 treatment in Q. robur leaves at the BIFoR FACE facility with aCO2 (blue) and eCO2 (orange). Each data point consists of all three canopy positions and represents the number of replicate treatment plots at the BIFoR FACE facility (n = 3)

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Marea significantly decreased through the canopy from top to bottom (Fig. 3, P < 0.05; Table 2) and did not significantly change with CO2 treatment (Fig. 3, Table 2). Marea decreased by a mean of 44% (mean ± SD: 99 ± 20 g m−2) and 53% (mean ± SD: 85 ± 14 g m−2) for eCO2 and aCO2, respectively, in the lower canopy foliage when compared to upper canopy foliage. Additionally, Marea increased with eCO2 treatment by 16% and 23% in the upper and lower foliage, respectively. There was no effect of CO2 treatment or canopy position on Nmass (Fig. 3, Table 2). Additionally, there was no effect of CO2 on Narea; however, Narea decreased by 29% and 33%, from the canopy top to bottom, in eCO2 and aCO2 treatments respectively (Fig. 3, P < 0.05; Table 2).

Fig. 3
figure 3

Mean a leaf mass per area (Marea) (g m−2), b nitrogen per mass (Nmass) (mg g−1), c nitrogen per area (Narea) (g m−2), and d chlorophyll per area (Chlarea) (g m−2) in the upper (20-23 m) and lower (8-11 m) canopy positions. Data points represent true replicates (n = 3). Colours and shapes indicate the CO2 treatment in Q. robur leaves at the BIFoR FACE facility with aCO2 (blue circles) and eCO2 (orange triangles)

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Table 2 Linear mixed model showing the statistical significance of CO2 treatment and canopy position, and their interaction, on leaf mass per area (Marea), nitrogen per mass (Nmass), and nitrogen per area (Narea) in Q. robur trees
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Discussion

Very few studies have analysed the effect of eCO2 on Chlmass and Chlarea in aged forest-grown trees (Wujeska-Klause et al. 2019) and fewer have also assessed the role of canopy position in the eCO2 response (Crous et al. 2020; Sharwood et al. 2017). We found that both Chlmass and Chlarea significantly varied in response to canopy position, but that neither Chlmass nor Chlarea were affected by eCO2 exposure, once Marea had been accounted for. Additionally, we found no significant changes in Nmass with canopy position or CO2 treatment, although Narea increased with eCO2 and significantly increased with canopy height. We found Marea increased with canopy height and with eCO2, suggesting that changes in Marea rather than changes in foliar N could be attributed to the observed changes to Chlarea and Narea with canopy position and eCO2. The results suggest that the allocation of N to light harvesting is maintained with eCO2 exposure and in the upper canopy, but that more N is allocated to light harvesting in the lower canopy. These results are consistent with observations in other plantation and forest-grown tree species (Crous et al. 2008; Warren et al. 2015).

Seasonal and inter-annual variations in chlorophyll

Chlorophyll (Chlarea and Chlmass) increases in the first part of the growing season for both years studied, and then attains a broad maximum through July and August, before decreasing in September (S. Figure 3)(Morecroft et al. 2003). Summer maximum Chl amounts are a factor of 1.4–1.8 larger than the springtime (May) measurements. This study reported significant seasonal variation in Chlmass and Chlarea, in addition to significant month x year interactions (S. Figure 4, Table 1). The lower Chlmass and Chlarea observed in May and June of 2019 than in the following year (Fig. 2a vs. Figure 2c) may be attributable to inter-annual differences in leaf age in the trees at the site as a result of herbivory. In 2019, an outbreak of winter month (Operophtera brumata) occurred in April and resulted in widespread defoliation across the site (Supplementary Fig. 4). The leaf regrowth likely contributed to a delay in greening of leaves in this season. There was no effect of eCO2 on defoliation across the site, although this has not been explicitly quantified, but there a spatial pattern was observed where two plots (one aCO2 and one eCO2) were not affected by herbivory to the same extent as the others (pers. obs.). Measurements over more seasons would be required to disentangle the effects of herbivory, phenology, eCO2, and month that are currently confounded in this study.

The effect of eCO 2

Elevated CO2 treatment did not significantly affect Chlmass, which has been observed in other field eCO2 experiments on trees (Liberloo et al. 2007; Wujeska-Klause et al. 2019). We found no significant effect of eCO2 for Chlarea, once Marea had been accounted for; that is, the mass of chlorophyll through the column of a square centimetre of leaf was unchanged. As discussed in the supplementary information, the mass fraction and areal density of a compound in a leaf are related by the leaf mass per unit area (Marea). Hence, the derived Chlarea content can be due to a change in the measured Chlmass concentration and/or a change in Marea. In support of this, we found that Marea increased with eCO2, which is a common response of trees to CO2 enrichment (as reviewed in Ainsworth and Long 2005). For a constant areal density, increasing Marea leads to a decreasing dry mass fraction; that is, to a dilution effect (Epron et al. 1996; Feng et al. 2015). Decreases in Chlmass, alongside decreases in Nmass, have been observed under eCO2 previously and have primarily been attributed to a dilution effect as a result of increases in Marea (Ainsworth and Long 2005; Sholtis et al. 2004; Wullschleger et al. 1992). However, in the present study, we did not see any reductions in Chlmass or Nmass with eCO2 suggesting the lack of a dilution effect occurring with exposure to eCO2.

Increases in Marea can be the result of increases in mass components that are either structural mass (such as leaf thickness and density) or photosynthetic mass (such as chlorophyll density), parameters not measured in the present study (Osnas et al. 2018). As Marea as a covariate was found to account for the significant eCO2 effect on Chlarea, this indicates that the eCO2-driven increases in Marea, may primarily increase structural and photosynthetic mass proportionally. Marea is considered a key trait in plant growth (Lambers and Poorter, 1992) and an indicator of plant strategies (Poorter et al. 2009); therefore, it will be important to assess implications on Marea with changes in atmospheric CO2.

Previously, eCO2-driven reductions in Chlarea have been suggested to be the result of eCO2-driven reductions in Narea and, therefore, lead to a reduced N investment in the photosynthetic apparatus (Ainsworth and Long 2005; Drake et al. 1997). However, there have not been many measurements to test this hypothesis, particularly for aged forests in whose canopies N allocation to light harvesting is important. Foliar N had been maintained in the first three years of CO2 fumigation at the BIFoR FACE site (Gardner et al. 2021), so we expected to see no eCO2-driven reductions in foliar N in the present study, as was indeed the case. In the present study, we found Narea either increased or remained unchanged in response to eCO2, suggesting that there were no limitations to the nitrogen supply (Warren et al. 2015). If the allocation of N to chlorophyll, with eCO2, follows that of total N, we would therefore expect Chlarea to follow the relationship of Narea, as observed.

It has previously been suggested that N may be reallocated with exposure to eCO2 away from light-harvesting apparatus to other processes (Caldararu et al. 2020; Drake et al. 1997). This has primarily been suggested in instances where nutrients have or may become limiting and can lead to reductions in photosynthetic capacity (Crous et al. 2008; Major et al. 2018). Our results suggest that this is not the case in sesquicentennial Q. robur, as Chlarea was not reduced with eCO2 exposure. Instead, the results indicate that N availability is in excess to meet the requirements for leaf processes, such as for photosynthetic apparatus (Warren et al. 2015) and, therefore, the tree is able to maintain leaf stoichiometry with eCO2. This is supported by previous analysis at this site that found the maintenance of foliar N with eCO2 in addition to a sustained 33% photosynthetic enhancement in mature Q. robur (Gardner et al. 2021).

The data in the present study are from the first 4 years of eCO2 exposure, and future seasons of eCO2 fumigation could lead to a progressive decline in soil N over time. A progressive decline or nutrient limitation has been previously observed in other FACE experiments and can lead to reductions in Narea that consequently affect Chlarea (Rey and Jarvis 1997; Warren et al. 2015). An understanding of N allocation in canopy leaves in eCO2 can help us understand potential effects of eCO2 on canopy processes, biogeochemical changes (given that N–C cycles are coupled in the biota of an ecosystem), and may provide new tools for monitoring canopy status in eCO2.

The effect of canopy position

This study reported significantly higher Chlmass in the lower canopy, compared to the upper canopy (P < 0.05, Fig. 1, Table 1), in agreement with previous studies of plantation and forest-grown trees in eCO2 (Crous et al. 2008; Liberloo et al. 2007; Scartazza et al. 2016). Increases in photosynthetic pigments are expected with increasing depth in the canopy and have been attributed to decreasing light availability through the canopy (Hikosaka et al. 2016; Niinemets 2007). This is due to increased requirement of light capture in shaded leaves and therefore a greater allocation of resources to the light-harvesting apparatus (Lennon et al. 2021; Lichtenthaler and Buschmann 2001; Sharwood et al. 2017). In contrast, upper canopies naturally receive high light levels and thus require less N investment in their light-harvesting capability (Sharwood et al. 2017). Previous research suggests lower Chlmass in upper canopy leaves may occur, because the leaves have thicker cell walls, lower leaf water content, and higher dry weight (Lichtenthaler and Buschmann 2001). In support of this, the present study found upper canopy leaves to have significantly higher leaf mass per unit area (Marea), compared to leaves from the lower canopy (Fig. 3) (Ellsworth and Reich 1993; Norby et al. 2021). Therefore, the decline in Chlmass with increasing canopy height is likely attributable to a dilution effect as a result of the increases in Marea (Epron et al. 1996; Houpis et al. 1988; Sholtis et al. 2004; Wullschleger et al. 1992).

Similarly, we found Chlarea significantly increased with increasing canopy height, paralleling the response of both Marea and Narea. Increases in Marea and Narea with increasing canopy height has been found previously (Fig. 3) (Crous and Ellsworth 2004; Jin et al. 2014; Norby et al. 2021). Our results suggest that Marea leads to the changes in Chlarea with canopy position and has been found previously (Herrick and Thomas 1999; Liberloo et al. 2007). The upper canopy leaves are primarily associated with higher rates of photosynthesis and therefore greater amount of nitrogen per leaf unit area and, assuming there is no photosynthetic downregulation or N reallocation occurring, would present similar increases Chlarea. This suggests that there are enough nutrients to support the photosynthetic process (i.e., no nitrogen limitation present) and is supported by previous findings (Warren et al. 2015). In support of this, previous research has shown that the structural adjustments in Marea, as a result of light gradients, are responsible for much of the variation regarding photosynthetic capacity (Niinemets, 2007). These results support the importance of accurate representation of Marea through the vertical canopy that is parameterised in vegetation models.

The present study found no significant interaction of CO2 treatment and canopy position for Chlmass or Chlarea. The lack of interaction of CO2 treatment and canopy position indicates that future changes in atmospheric CO2 may not influence plant traits differently across the canopy compared with the relationships in the present day. Additionally, there was no effect of eCO2 on the pattern of Narea with canopy height which suggests that eCO2 has no effect on N content integrated through the depth of the leaf. Similar results have been reported previously (Norby et al. 2021; Takeuchi et al. 2001), and so, we provide further confidence for the representation of Narea as a constant with exposure to eCO2 in models.

Conclusion

In mature Q. robur canopies considering season, canopy height, and CO2 treatment, Chlmass varied significantly with most of these factors. This suggests that canopy chlorophyll is highly dynamic in oak canopies, which needs to be considered in remote-sensing measures using canopy light absorptance or greenness as proxies for light-use efficiency. There were eCO2-driven increases in Chlarea, that were consistent with eCO2-driven increases in Marea, suggesting that increased cell stacking and chlorophyll density in oak leaves may help regulate the eCO2 response and within-canopy variation. The results suggest that season and canopy position are particularly important to consider for scaling leaf-to-ecosystem light harvesting and canopy N-use and photosynthetic processes.