1 Introduction

The visionary scientist Harmon Craig was one of the first to measure stable isotopes in wood and argued that δ13C in tree rings might be linked to environmental variation (Craig 1954). Others followed and measured different isotopes such as δ2H and δ18O (Schiegl 1974; Gray and Thompson 1976, see also Chap. 1). However, due to instrument and sample size limitations, most early studies focused on one element at a time. Once it became possible to measure more than one element on a single sample, researchers began to see the benefits of multiple proxy information to reconstruct historical climate and physiological responses to climate variability. With the advent of software that can switch tuning during analysis of a single sample, IRMS instruments commonly provide both δ13C and δ15N values after combustion and separation for the same organic matter sample (Pate et al. 1998; Cernusak et al. 2007). While this approach has many uses in ecological studies (Ohkouchi et al. 2015), wood contains very little nitrogen and so relatively few stable isotope dendrochronologists have applied δ15N as secondary proxy (although see Chap. 12). Although measuring both δ13C and δ18O values for the same sample commonly involves separate IRMS runs (combustion for δ13C and pyrolysis for δ18O), analysis of the carbon and oxygen isotope ratios from one sample is also possible with newer pyrolysis techniques (Woodley et al. 2012; Weigt et al. 2015). With the advent of new techniques to more easily measure δ2H in cellulose (to deal with exchangeable H, see methods in Chaps. 7 and 11), some are beginning to look at all three primary stable isotopes in cellulose (Etien et al. 2009; Loader et al. 2016).

Regardless of using a dual-isotope approach as a way to constrain physiological interpretations of one isotope, multiple isotopic information from the same sample provide added information for analysis. Each element has a different pathway for inclusion into organic matter with different fractionation events that potentially capture a unique set of physiological and environmental information. Even oxygen and hydrogen, which are both incorporated into cellulose via source water and thus would seemingly provide identical environmental information, can be used to examine evaporative conditions through measuring deuterium excess (Voelker et al. 2014) and may also act as a proxy for carbon metabolism (Cormier et al. 2019). In addition, it is always useful to add non-isotope components of the annual ring as a third or fourth proxy (see Churakova (Sidorova) et al. 2019). Ring width is related to growth rates and can help to interpret isotope variation that, for example, may be indicating drought or other growth limiting conditions. Though not commonly done, there is good reason to think that combining newer techniques of tree ring analysis (maximum latewood density, Chen et al. 2012 or Blue Intensity, Campbell et al. 2007) with isotopes could clarify climatic relationships (temperature and precipitation). This chapter will focus on the most common dual-isotope approach, the measurement of both δ13C and δ18O from the same sample. We first explain the relevant isotope fractionation processes in plants, then detail the principles of the conceptual model and later discuss the potential and caveats when this concept is applied to plant studies, with a particular focus on tree rings.

2 Carbon Isotope Fractionation

Briefly (see also Chap. 9), the δ13C variation in photosynthate that could be incorporated into tree rings is primarily the function of internal CO2 concentrations (ci, Farquhar et al. 1989) for a given δ13C value of atmospheric CO2. Since Rubisco discriminates against 13C, the amount incorporated into organic matter will be determined by its potential to use 12C preferentially. At high ci, unfixed 13CO2 can diffuse back out the stomatal pores whereas at low ci the enzyme will discriminate less and capture relatively more 13C because it is substrate limited. As a consequence, conditions that promote relatively low ci during the growing season (e.g. stomatal closure due to water stress) will result in relatively high δ13C in organic matter, and vice versa for high ci. Ci is set by a supply (stomatal conductance) and demand (photosynthetic rate) process (Farquhar and Sharkey 1982; Farquhar et al. 1989; Ehleringer 1993) and thus numerous studies also demonstrate a relationship between δ13C and intrinsic water-use efficiency (the ratio of photosynthetic rate to stomatal conductance, see Chap. 17).

When making use of variations in stable isotopes to interpret and disentangle plant responses to a changing environment, we must keep in mind that numerous environmental factors impact CO2 and H2O gas exchange, (the primary drivers for isotopic fractionation in leaves). In the real world, a whole assemblage of variables impact plant metabolism simultaneously. Therefore because δ13C variation of plant organic matter (also tree-ring cellulose) relates to supply and demand, it reflects a variety of aspect of tree functional biology. Any aspect of tree status that leads to modifications of photosynthetic rates (light interception associated with tree fall gaps, nitrogen fertilization, temperature changes etc., Flanagan et al. 1997; Roden and Farquhar 2012) would modify δ13C values through an altered CO2 demand. Factors that modify CO2 supply primarily through changes in stomatal conductance (water status, humidity etc., Saurer et al. 1995b; Leavitt et al. 2002), will also influence tree-ring δ13C values. Thus δ13C variation could be associated with either changes in stomatal conductance, net carbon assimilation or a combination of both. And herein lies the impetus for the approach developed by Scheidegger et al. (2000), see also Grams et al. (2007) where they add a second element (δ18O) as a way to distinguish between stomatal vs assimilatory control over δ13C variation.

3 Oxygen Isotope Fractionation

It is useful to distinguish the isotope fractionation processes on two different levels: (1) processes which alter the isotope ratio before water is taken up by plants (source effects) and (2), changes which result from fractionation processes in the leaf during transpiration (E) and incorporation into plant organic matter (plant effects).

3.1 Source Effects (see Chap. 18)

Source water δ18O depends on three main components, (1) the geographic origin of clouds that provide meteoric waters and associated δ18O values. Precipitation falling in warmer regions is more enriched in 18O than colder ones (Dansgaard 1953, 1964). Meteoric water δ18O is also impacted by continental effects causing precipitation to be more depleted in 18O toward interior regions associated with rain out events (Rozanski et al. 1993) and altitude with colder condensation temperatures producing more depleted precipitation with increasing elevation (Bortolami et al. 1979). Another source of variation is (2) seasonality which can have annual cycles closely linked to temperature variation such that summer rainfall is more enriched in 18O than winter precipitation (Dansgaard 1964; Rozanski et al. 1993). As water infiltrates into soils further fractionation can occur particularly during periods of high evaporation demand. As such, (3) soil matrix water δ18O may vary with depth depending on soil structure, season and climate (Darling and Bath 1988; Allison et al. 1984). Since roots can absorb water from a large range of soil depths (Dawson et al. 2002) source water δ18O values (xylem water) can differ from meteoric water inputs, which provides the baseline water that is modified by leaf-level processes (Goldsmith et al. 2019; Allen et al. 2018a, b).

3.2 Plant Effects

Briefly (see also Chap. 10), the δ18O variation in organic matter that could be incorporated into wood cellulose is primarily impacted by source water δ18O, atmospheric vapor δ18O and evaporative conditions influencing fractionation processes in the leaf during transpiration (Roden et al. 2000; Barbour 2007; Cernusak et al. 2016; Lehmann et al. 2018). Further factors influence bulk leaf water such as progressive enrichment where leaf venation patterns lead to previously enriched water re-entering the xylem and moving to more distal regions and becoming further enriched in 18O (Helliker and Ehleringer 2002) and compartmentation where pools of water are isolated from evaporation leading to a leaf being less enriched that expected based on models (Roden et al. 2015). Péclet effects, where the back diffusion of water from the sites of evaporative enrichment in the leaves as opposed by the flow of less-enriched water from the xylem, also impact bulk leaf water enrichment (Farquhar and Lloyd 1993). The δ18O signals from leaf water are incorporated into carbohydrates and are then modified by proportional exchange during phloem transport as well as at the site of organic matter synthesis (Barbour et al. 2004; Barbour 2007; Sternberg 2009; Gessler et al. 2014).

3.3 Combined Effect on Tree Rings

As a result of these processes, oxygen isotope variation in tree rings can be used to probe a number of environmental impacts on tree physiology. Due to the primary influence of source water δ18O associated with variation in meteoric waters, which in turn can be a function of condensation temperature, tree-ring δ18O time series may be a proxy for temperature variation (Gray and Thompson 1976). While this may appear straight forward, there are a variety of potential fractionation events that can modify that signal (e.g. soil evaporation) even to the extent of ecohydrolic separation leading to soil water available to trees in antiphase to seasonal temperatures (Brooks et al. 2010; Allen et al. 2019). Many studies have demonstrated that δ18O variation in organic matter track leaf evaporative conditions, especially vapor pressure deficit (VPD, but also relative humidity, Edwards et al. 1985; Lipp et al. 1996; Kahmen et al. 2011). The connection between tree ring δ18O values and stomatal conductance relates to evaporative enrichment through non-steady state conditions (but see Chap. 10). The Craig–Gordon model (Craig and Gordon 1965; Dongmann et al. 1974) was developed for bodies of water and mostly over-predicts evaporative enrichment in leaves. This model assumes a known fractionation for a given VPD and temperature, and when used with leaves, is insensitive to stomatal conductance. However, diurnal variation in leaf water δ18O can be quite dramatic and sensitive to stomatal opening (Cernusak et al. 2002, 2005). Despite the numerous processes impacting the isotopic ratio from source via leaf water to organic matter, controlled experiments have confirmed that tree ring δ18O does indeed record evaporative conditions (Roden and Ehleringer 1999; Grams et al. 2007; Roden and Farquhar 2012) and thus should capture stomatal conductance variation, which is mostly accounted for via the Péclet effect.

Physiologically, photosynthetic rates do not directly influence δ18O, in contrast to transpiration and stomatal conductance and its associated impact on evaporative enrichment. This is the link that Scheidegger et al. (2000) aimed to exploit with their dual-isotope model in that δ18O helps constrain interpretations of δ13C variation in leaves by using δ18O as an indicator of changes in stomatal conductance. While this appears reasonable and promising, we must keep in mind the many additional factors that influence leaf evaporative enrichment described above and others that modify that signal as sucrose is transported to sites of cellulose synthesis in the stem (Gessler et al. 2009; Offermann et al. 2011, see also Chap. 13). These factors contribute to signal complexity and make the use of δ18O variation as a proxy for stomatal conductance in tree rings more challenging, which requires a careful evaluation of the data and its interpretation, as outlined henceforth.

4 Dual-Isotope Conceptual Model

The seminal paper to propose the dual-isotope approach was Scheidegger et al. (2000). They proposed measuring both δ13C and δ18O on the same sample in order to constrain the interpretation of δ13C variation as primarily a function of carbon assimilation (A) or stomatal conductance (gs) or a combination of both. To achieve this goal, Scheidegger et al. (2000) developed a theoretical framework for interpreting all possible changes in both isotopes. The concepts for this approach are strictly based on well-accepted carbon (Farquhar et al. 1982, 1989) and oxygen isotope fractionation models (Dongmann et al. 1974; Farquhar and Lloyd 1993; Cernusak et al. 2016) and CO2 and H2O gas exchange principles (Gaastra 1959; von Caemmerer and Farquhar 1981). If any of these principles are violated, the dual-isotope approach would yield non-plausible results. Carbon isotope ratios (δ13C) or inverse discrimination (−Δ13C, Grams et al. 2007) is plotted on the Y axis and δ18O or Δ18O on the X with an arrow indicating the change in both isotopes between organisms of different species or treatments or sites, etc. being compared (Fig. 16.1). These plots must not be interpreted as plots of dependent and independent variables as one isotope’s variation is not a causal factor for the other. These plots only represent how both isotopes vary in tandem. The slope and direction of the arrow is then used to imply the impact on net photosynthesis (Anet) or gs and consequently on δ13C variation between comparator organisms (Fig. 16.1).

Fig. 16.1
figure 1

Adapted from Scheidegger et al. (2000). The alternate interpretation for scenario B (dashed line) is given by Grams et al. (2007)

A subset of potential scenarios on how the dual-isotope conceptual model is used to interpret δ13C variation.

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The basic assumption is that changes in δ13C result from changes in Anet (the demand) or gs (supply function) or both, which are driven by temperature, VPD, light, CO2 etc., while δ18O varies independently of carbon isotope fractionation during photosynthesis. Based on Farquhar and Lloyd (1993) and Barbour et al. (2000, 2004), δ18O and gs are negatively correlated. Therefore any variable (VPD, soil water content, light, CO2 etc.) that reduces gs will result in an increase of δ18O or vice versa. With this additional value, we can determine whether a change in δ13C was predominantly influenced by Anet or gs. For example, in scenario A of Fig. 16.1, an increase in both δ18O and δ13C would imply both a reduction in gs, (inverse relationship with δ18O) and ci/ca (leading to reduced discrimination of 13C by Rubisco), implying that photosynthetic rates remained unchanged. If Anet also declined with gs then ci/ca might remain unchanged and δ13C values should be similar between conditions (scenario C in Fig. 16.1).

Another premise is that these changes are sufficiently large since uncertainty increases with decreasing signal strength. The dual-isotope methodology can be used to study treatment and species differences or changes in the environment over time, provided that the assumptions of similar δ18O of source water and water vapor hold. Some studies try to account for source water δ18O variation between treatments or species etc. by plotting Δ18O (enrichment above source water). In situations with high relative humidity, the δ18O of vapor can contribute to the uncertainty in leaf δ18O because of the bidirectional diffusion of the H2O molecules (Lehmann et al. 2018, see also Fiorella et al. 2019 for related processes from an atmospheric perspective). In cases where the δ18O of source water or water vapor cannot be measured, they may be estimated from models though interpretations must be tempered as uncertainties compound when models are nested within models.

5 Testing the Model

Scheidegger et al. (2000) tested this conceptual model using leaf organic matter from three herbaceous species growing in fields with differences in land management (mowed and fertilized fields or those abandoned from agricultural manipulations for an extended period). The experiment produced two distinct microclimatic scenarios impacting plant physiology, which was reflected in C and O isotope ratios. The predictions from the conceptual model for Anet and gs agreed qualitatively with gas exchange measurements from the same plots. Yet in their paper, Scheidegger et al. (2000) indicated that controlled experiments would be the next step to clarify the viability of the model for other systems and scenarios and to what extent it could be used to interpret C and O isotope variations in terms of physiology with confidence. Since then, more than 330 studies (controlled and field) have applied the dual-isotope approach (see Siegwolf et al. 2022).

Grams et al. (2007) tested this approach on trees, using leaf cellulose from beech and spruce trees from field sites or grown in controlled environments and exposed to treatments that influenced AMAX and gs (ozone, elevated CO2 and light). They too validated model output with gas exchange data and went a step further by comparing simulated C and O isotope values with measured data. They found that leaf cellulose δ18O can be related to stomatal conductance and by using C and O simulations they could improve the correlation between gs and δ18O via additional adjustments of fractionation model parameters such as kinetic fractionation, leaf temperature (and ea/ei) associated with transpirational cooling, and the Péclet correction (associated with transpiration rate, E and effective pathlength, L, a scaling factor assumed to be associated with leaf anatomy and hydraulic resistance). They concluded that the dual-isotope approach can help delineate the effects of their treatments on stomatal conductance and carbon assimilation.

6 Testing the Model Using Tree Rings

The expansion of the dual-isotope approach from leaf cellulose to tree-ring cellulose is a critical issue for those who wish to interpret historical changes in tree physiology (the topic of this volume). While it may seem likely that all organic matter should follow the same general rules for isotope fractionation, tree rings have a number of unique attributes due to their temporal and physical separation from the sites of photosynthetic carbon assimilation (see Chaps. 13 and 15 in this compilation). And so, the application of the Scheidegger et al. (2000) model to δ13C and δ18O variation using tree-ring cellulose time series requires further validation.

Roden and Farquhar (2012), tested the dual-isotope approach for wood cellulose in a control experiment (growth chambers) on pine and eucalypt seedlings grown under a variety of conditions designed to alter stomatal conductance (VPD, drought, and temperature) and/or photosynthetic rates (light levels and nitrogen nutrition). While humidity treatments (46 versus 65%) produced significant effects on leaf transpiration, leaf water evaporative enrichment in 18O, and wood cellulose δ18O (from 2 to 3‰), they produced only minor changes in gs (Roden and Farquhar 2012). Non-significant differences in stomatal behavior was partly due to highly variable measurements of gs and as well as humidity treatments that may not have limited plant function and water status. Within a humidity treatment, the dual-isotope approach accurately predicted A:gs relationships for some of the other treatments (Fig. 16.2, only the low humidity treatment is shown for clarity as both humidity treatments showed similar patterns, see Roden and Farquhar 2012 and stomata should be most responsive at high VPD, see below). Both the low light and low nitrogen treatments produced reductions in photosynthetic carbon assimilation with little change in stomatal conductance, while both the elevated temperature and drought treatments produced reductions in both A and gs (Fig. 16.2). For both species, the dual-isotope approach accurately predicted the response to increased temperature but not the response to reduced nitrogen nutrition (Fig. 16.2a). The dual-isotope approach accurately predicted the response to low light and drought for the eucalypt but not for the pine (Fig. 16.2b). It should be noted that this was a seedling study and impacts related to long-distance transport of assimilates through the bole were not captured. Another difficulty in this technique is choosing which interpretation should be used if the dual-isotope plot produces an arrow between two options (e.g. part way between angled and vertical). This study provides a cautionary note that dual-isotope interpretations of C and O isotope variation in tree-ring cellulose may not be able to clearly delineate all hypothetical variations in the A:gs relationship as often assumed. The results of this study demonstrated that the dual-isotope model works better for some environmental effects and for some species than for others.

Fig. 16.2
figure 2

Measured physiological response (see Roden and Farquhar 2012 for details) of Eucalyptus globulus and Pinus radiata grown in chambers controlled for temperature (21 °C), humidity (46%), light level (1000 mol photons m−2 s−1), source water δ18O (−6‰) and atmospheric vapor δ18O (−17‰). Compared to standard (control) conditions, separate treatments were increased temperature (+3 °C), reduced nitrogen nutrition (½ the N inputs, low N), reduced moisture inputs (drought) and reduced light inputs (50% of ambient, low light). All arrows extend from the mean physiological measurements of control plants to the mean for plants exposed to each indicated treatment (separated into 2 panels, a and b to reduce clutter). Inset plots are predicted responses derived from dual-isotope plots (data not shown, but see Roden and Farquhar 2012) for each treatment

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7 Utilization of the Dual-Isotope Conceptual Model

A number of studies have utilized the dual-isotope approach to probe a variety of questions. Sullivan and Welker (2007) found the approach useful to qualitatively differentiate the contributions of gs and A on site differences in 13C discrimination for willows in Greenland. Keitel et al. (2006) applied the conceptual model to phloem sap and leaf organic matter for European beech along a continental scale transect and argue that organic matter Δ18O reflects canopy level conductance (estimated not measured). Since neither study utilized a common garden experimental design, some assumptions of the dual-isotope model may have been violated, but they claim that with environmental quantification and reasonable assumptions their analysis could produce valid conclusions. Moreno-Gutiérrez et al. (2011) applied the dual-isotope approach to needle organic matter from a pine plantation and assert that the model provided insights into tree physiological changes after forest thinning treatments. For a grassland ecosystem, Flanagan and Farquhar (2014) interpreted their variation in dual-isotope space as indicating stomatal control as the principle effect on photosynthetic rates and 13C discrimination during periods of water stress. Prieto et al. (2018) measured leaf δ13C, δ18O, and morphological traits on 15 herbaceous species in a rangeland common garden to investigate diversity in leaf functional traits including water use efficiency and nutrient economies. They conclude that the dual-isotope approach can be used to probe water use strategies among species and broad-scale studies on ecological adaptations. While more examples could be included, these diverse studies show that the dual-isotope model has gained traction in the plant physiological community as a way to constrain the interpretation of δ13C variation, stomatal conductance and water use strategies in leaf organic matter.

While the dual-isotope model was developed for leaf tissues, numerous studies expanded its use to tree-ring cellulose exploring how environmental changes affect physiological properties over time. Sidorova et al. (2009) noted a change in correlation between C and O isotopes in Siberian larch over time and used the dual-isotope model to infer changes in stomatal conductance and carbon assimilation associated with water stress. Brooks and Mitchell (2011) used δ13C and δ18O variation in Douglas-fir tree-ring cellulose to probe intrinsic water-use efficiency and changes in stomatal conductance from before and after fertilization and thinning treatments. Similarly, Barnard et al. (2012) utilized the dual-isotope approach to infer physiological changes in Douglas-fir trees differing in canopy position. Voltas et al. (2013) studied winter dieback, and hydraulic limitations for Scots pine trees in marginal habitats. In their system, oxygen isotope variation indicated greater stomatal control of water loss in declining trees. Giuggiola et al. (2016) combined the dual-isotope approach with a canopy-level mechanistic model (MuSICA, Ogée et al. 2003) to clarify the effects on stomatal conductance and carbon assimilation on thinning induced growth enhancement in a xeric Scots pine plantation. While the studies highlighted above have provided valuable insights, as the complexity of the system tested increases, the application of the dual-isotope model may become problematic as the number of untested assumptions and unmeasured variables expand (similar source water and atmospheric vapor δ18O inputs, common humidity between treatments in complex canopies, etc.).

8 Points of Caution

Before tree physiologists and dendro-climatologists consider using the dual-isotope approach in tree rings to interpret historic variation in δ13C, they need to pay special attention to model assumptions and constraints. The most obvious pitfall of this approach is accurate determination of source water and water vapor δ18O values as both can mimic stomatal impacts. The greater the fractionation events that could be attributed to factors other than stomatal conductance, the less useful the model output becomes for constraining the interpretation of carbon isotope variation (see also Chap. 18). In addition, we must consider for the interpretation of tree-ring isotope values that CO2 assimilation and growth are different processes, which are not as tightly linked as usually assumed (Körner 2018). Tree growth can be fueled from carbohydrate reserves as well as directly from fresh leaf assimilates depending on phenological stage and dampening isotope signals. Furthermore, there can be considerable time gaps between the synthesis of carbohydrates and its use for cellulose production in the stem (Gessler et al. 2009, 2014; Offermann et al. 2011). This can be problematic, as the isotopic signal in tree rings is not synchronized with the time of the climatic event. An extreme case of this phenomenon is the complete isotopic decoupling between leaf organic matter production and cambial activity in the stem. Sarris et al. (2013) and Pflug et al. (2015) described this for trees exposed to severe and chronic drought. A similar effect has been observed at low temperatures (5–7 °C) where growth is severely limited, potentially making summer conditions a disproportionally greater influence on whole tree ring isotope signals (Körner 2018, See also Chap. 14). Using specific portions of the tree ring (earlywood, latewood etc.) may be important to connect isotope variation to relevant periods of interest. Studies with air pollutants and isotopes show that some principles for carbon isotope fractionation in C3 plants were violated (Chap. 24). This was observed for ozone, which caused an increase in δ13C due to enhanced PEP carboxylase activity, although ci/ca was elevated in damaged leaves (Saurer et al. 1995a). A similar effect was observed with SO2. In such situations the C and O isotope model will yield physiologically non-plausible results.

Roden and Siegwolf (2012) highlighted ten areas of caution for this conceptual model and encouraged research that could reduce model uncertainties. Some issues they discuss have been mentioned above (e.g. common environmental inputs and evaluation of the humidity/gs relationship for a species), but they also highlight areas of caution specific to tree-ring studies. For example, tree-ring cellulose has a dampened signal as compared to leaf cellulose due to isotope exchange with medium water in the vascular cambium (unenriched compared to leaf water, Roden et al. 2000, Barbour et al. 2004, but see also Treydte et al. 2014, for complications with relative contributions) and dilution of signal when utilizing stored carbohydrate reserves (Roden and Siegwolf 2012). They also indicate that site ambient humidity may determine if tree ring δ18O variation can detect changes in gs. At high humidity, mechanistic models that describe 18O fraction in cellulose (Roden et al. 2000; Barbour et al. 2004) predict that δ18O variation in organic matter will be insensitive to variation in stomatal conductance. In addition, while the dual-isotope model predicts that changes in gs will modify organic matter δ18O via differences in kinetic fractionation and transpiration (through the Péclet effect, Farquhar and Lloyd 1993), they rarely consider the influence of gs on bidirectional flow of isotopically distinct water vapor (Roden and Siegwolf 2012; Lehmann et al. 2018). Most studies assume δ18O of water vapor in the atmosphere is in equilibrium with tree source water, which may rarely be the case (White and Gedzelman 1984; Fiorella et al. 2019). In addition, atmospheric turbulences as they occur throughout the day in most forests disturb steady state conditions and this can impair this assumption as well.

Many researchers (Keitel et al. 2006; Sidorova et al. 2009; Moreno-Gutiérrez et al. 2011; Barnard et al. 2012; Flanagan and Farquhar 2014; Prieto et al. 2018) utilize regression analysis of δ18O and δ13C data sets to provide some statistical confidence regarding trends in highly variable data sets and time series rather than directional arrows (as in Fig. 16.1). However, Roden and Siegwolf (2012) argue that regression analysis cannot be used exclusively because non-significant relationships (vertical or horizontal slopes) have meaningful interpretations in the Scheidegger et al. (2000) and Grams et al. (2007) conceptual models. They also argue against the use of AMAX to interpret changes in assimilation because it is not the photosynthetic capacity (which can be defined in a variety of ways) that sets the demand side of the A:gs relationship that sets chloroplast CO2 concentrations which influences 13C discrimination, but rather integrated or average assimilation (Anet). There are numerous environmental factors that affect integrated assimilation without altering photosynthetic capacity such as light, water status, CO2, and temperature variation.

9 Alternative Dual-Isotope Approaches

Utilizing information from both C and O isotopes in organic matter can be approached in a number of ways other than that proposed by Scheidegger et al. (2000), making it possible to derive information beyond the influence of A and gs on δ13C variation. Recently, another take on the dual-isotope approach was made by Goud et al. (2019) where they introduced a way to quantify the relationship between δ13C and Δ18O in leaf cellulose they termed integrated metabolic strategy (IMS). Instead of visualizing δ13C and δ18O together in isotope space (as in Fig. 16.1), they calculate a ratio between the two isotopes that reflect leaf-level metabolic efficiency. Their equation scales both isotopes such that an increasing IMS implies more carbon gain per unit water loss (water-use efficiency) rather than using δ13C alone to infer ci/ca and iWUE. They tested the concept of IMS on 20 milkweed (Asclepias) species with different leaf attributes associated with ecological and evolutionary diversity and found that IMS has the potential to provide valuable insights on phylogenetic relationships and phenotypic plasticity regarding tradeoffs between CO2 uptake and water loss (Goud et al. 2019). In another example, Saurer et al. (1997) utilized combined δ13C and δ18O information to derive the sensitivity of ci/ca of different tree species to changing humidity. Approaches that combine mechanistic models, like MuSICA (Guiggiola et al. 2016) can improve model predictive power and physiological interpretations. Even if δ18O cannot be directly related to changes in stomatal conductance, but say, rooting depths, plots of δ18O versus δ13C could be useful to see if different species having different source water access have different δ13C and thus iWUE.

9.1 Conclusions

The theoretical framework of the dual-isotope model introduced by Scheidegger et al. (2000) is valid and can be used to probe the degree of carbon isotope variation in plant organic matter that is determined by the supply side (stomatal conductance) drivers of internal CO2 concentrations (ci/ca). As the model is rather simple at first sight it is tempting to apply it like a “plug and play tool”. However, applying the dual-isotope approach, particularly for stable isotope variation in tree-ring cellulose, and linking it with the principles of gas exchange, requires special attention to keep the physiological mechanistic context in mind and to ensure that the assumptions of the conceptual model are not violated. Nevertheless, considering the myriad of plant responses to the environment in a multi-species ecosystem context, it is very useful to have a tool available that helps guiding the physiological interpretation. Despite issues of applicability, measuring more than one stable isotope on a single sample will generally provide added information and allow for better characterization of environmental variation and physiological attributes.