Reviewer: Cernusak LA5
Measurable unit: ratio of heavy to light isotope in per mil (‰) relative to standard; Measurement scale: precipitation, soil, and/or plant tissue; Equipment costs: €€€; Running costs: €; Installation effort: medium; Maintenance effort: medium; Knowledge need: high; Measurement mode: manual and data logger
Stable isotopes of hydrogen and oxygen in water, as well as plant organic materials formed using such water, have become an important tool for determining plant functional responses to the environment. Stable isotopes of water vary naturally as a function of both physical and biophysical processes as they move through the ecohydrological cycle (Gat, 2005). These variations depend on differences in the rate of evaporation and condensation between water molecules containing the light and heavy isotopes. The measurement of the ratio of the heavy to light isotopes of a given element present in a sample (i.e. 18O/16O of leaf material, as interpreted relative to an international reference standard; Coplen, 2011) can be studied to trace the source and physical movement of those isotopes through plants, or as a record of the impact of plant biophysical processes on those isotopes (Dawson et al., 2002).
In particular, stable isotopes of water are powerful tools for interpreting how the sources of water taken up by roots vary across time and space among different plants (Brooks et al., 2010; Allen et al., 2019). Soil water reflects the isotopic composition of precipitation. In seasonal climates, winter precipitation generally is depleted in the heavy isotope and therefore has a more negative isotope ratio (Marshall et al., 2007). In turn, the isotopic composition of water taken up by plants into the xylem is altered when it reaches the evaporative sites within leaves through the process of leaf transpiration: these changes subsequently become recorded in plant organic matter (e.g. sugars) via photosynthesis. Given that transpiration is strongly controlled by plant water supply and demand (Cernusak et al., 2016), stable isotopes of hydrogen and oxygen in plant organic matter reflect the environmental conditions (particularly leaf-to-air vapour pressure deficit) in which metabolic processes occurred and the metabolic response to those conditions (Helliker & Richter, 2008; Kahmen et al., 2011; Song et al., 2011). Stable isotope ratios of hydrogen and oxygen recorded in leaf sugars, leaf tissue, phloem sap, and tree rings thus reflect plant biophysical responses recorded at different time scales (Roden et al., 2000; Cernusak et al., 2003; Gessler et al., 2009). In this respect, stable isotopes of hydrogen and oxygen are unique from instantaneous measurements. Moreover, because sample collection in the field can often be carried out relatively quickly, observations of hydrogen and oxygen isotopes can increase the breadth and depth of a study across time, space, and other variables of interest.
When used in combination with other measurements of stress physiology, stable isotopes represent a powerful means of understanding how environment affects water use among different plants and this is of particular interest for interpreting the effects of climate change in both experimental (e.g. Barbeta et al., 2015) and observational contexts (e.g. Treydte et al., 2007; Saurer et al., 2016; also see protocol 5.5 Leaf temperature). Similarly, the techniques described here can be applied to understand other global-change drivers, such as soil fertilisation (Brooks & Mitchell, 2011) and invasive species (Reynolds & Cooper, 2010).
5.13.1 What and how to measure?
δ18O and δ2H of water
Stable isotopes of water are frequently used as a means of inferring the source of water taken up by plants (Brooks et al., 2010; Goldsmith et al., 2012; West et al., 2012; Barbeta et al., 2015), as well as for inferring how plant water availability and demand (driven by environmental conditions) has affected the process of transpiration (Wang & Yakir, 1995; Ripullone et al., 2008; Kahmen et al., 2013). Given that water availability is frequently a limiting factor for plant function, there is considerable interest in understanding how plant water use will change given projected scenarios of global climate change.
Using water isotopes as a means of inferring plant function requires carefully constraining the different sources of water that can be used by plants. This begins with observing the isotope ratios of precipitation (e.g. rain, snow, fog, dew) at the study location. Where direct observations are not possible, data from monitoring networks (e.g. the Global Network of Isotopes in Precipitation – GNIP), or from geospatial interpolations of monitoring networks (e.g. waterisotopes.org), can also be used, but these data may be less accurate and precise depending on the temporal and spatial resolution of measurements upon which the estimations are based. Precipitation isotopes are generally collected at an open site using a collector designed to prevent any evaporation (and thus isotopic fractionation) – see Ingraham (1998) for details. However, it is important to note that the isotopic composition of throughfall (i.e. after passage through the plant canopy) is likely to differ from that of precipitation and will thus more accurately represent the water entering soil (Allen et al., 2017). Throughfall mixes into the existing soil and groundwater pools, where it then becomes available to serve as the primary source of water for plants (but see Lehmann et al., 2017).
Soil samples can be collected using either a soil corer, or by opening a soil pit and sampling into the face of the pit where soil water has not been subject to evaporative fractionation while the pit was prepared. Both methods have drawbacks. The soil corer is prone to compaction and thus makes it difficult to estimate the depth of the soil being sampled, while soil pits are time consuming to dig. Given the heterogeneity of soils, it may be better to use a soil corer and tradeoff the accuracy of knowing soil depth in favour of better constraining the range of possible soil waters being used by the plants of interest. Experimental designs that representatively sample both vertical and horizontal space are likely to yield the most accurate results. Where possible, it is also informative to sample groundwater from a monitoring bore, a well or a tap with a local source, discarding the initial water sample to avoid evaporative fractionation. Soil water isotopic signals reflect seasonal changes in the soil-water pool and should be sampled as frequently as possible.
Finally, water can be collected from plant xylem in either roots or woody stems. Fractionation associated with root water uptake is likely to be limited (but see Vargas et al., 2017), but it has been consistently reported from particularly dry and/or saline environments (Ellsworth & Williams, 2007; Zhao et al., 2016). Tissue that is not suberised (e.g. leaves or green stems, as compared to woody and brown stems) is subject to evaporative fractionation and thus does not represent the water being taken up by the plant (Dawson & Ehleringer, 1993; Martín-Gómez et al., 2017).
In all cases, samples must be collected in such a way as to prevent any possible evaporation (e.g. glass vial with screw-top lid), sealed immediately, and cooled (if possible) to reduce the possibility of isotopic fractionation ex post facto. With the exception of water from precipitation, water in matrices such as soil and plant tissue is generally extracted prior to analysis. The most common form of extraction is cryogenic vacuum distillation (West et al., 2006; Koeniger et al., 2011). In brief, the vial with the sample is connected to another empty vial. The sample is frozen under liquid nitrogen, lowering the water vapour pressure to nearly zero, and the air is then pumped away and evacuated from both connected vials. The vial with the sample is then heated while the empty vial is maintained in liquid nitrogen. The water vapour pressure rises in the heated tube and, because of the near vacuum, it diffuses rapidly to be condensed in the vial under liquid nitrogen. Ideally, the extraction continues until vacuum returns, at which point all the water has been extracted into the second vial. There are also other forms of extraction (e.g. microwave extraction; Munksgaard et al., 2014), as well as direct equilibration (Scrimgeour, 1995; Song & Barbour, 2016). Users are advised to validate their methods to improve confidence in their results.
Finally, the isotope ratios can then be measured by means of an isotope ratio mass spectrometer (IRMS). The IRMS is a specialised piece of lab equipment that requires significant resources – where instrumentation is not available locally, it is possible to identify other labs that will analyse samples at a reasonable cost. Quality control standards and data on the long-term accuracy and precision of the instrumentation are important for appropriate interpretation of the results.
δ18O of bulk leaf organic material
The incorporation of oxygen isotopes from water into plant organic material has emerged as an important means of tracking plant functional response to environment, particularly with respect to stomatal conductance (Barbour et al., 2000), leaf temperature (Helliker & Richter, 2008; also see protocol 5.5 Leaf temperature), and especially for understanding the ratio of leaf to air vapour pressure (Kahmen et al., 2011). This relies on the observation that the transpiration rate is coupled to the fractionation of leaf water, whereby light water isotopes are preferentially evaporated and the remaining pool of leaf water is thus enriched in heavy water isotopes. The extent of this enrichment is subsequently recorded in leaf organic materials through the incorporation of oxygen isotopes from water into photosynthetic products. The most common way to measure this is to observe the oxygen isotope ratios of bulk leaf organic material (δ18OBL).
Importantly, leaf water enrichment is often heterogeneous and sampling of leaves must account for this possibility. Enrichment can reflect a gradient from the bottom to the top of the leaf (e.g. grasses), from the veins to the margins (e.g. broad leaves), or alternatively, reflect multiple isotopically distinct pools of water within the leaf (Song et al., 2013; Roden et al., 2015; Cernusak et al., 2016). This enrichment is reflected in the leaf organic material and as such, it is critical to adapt sampling protocols for the leaf form of interest. For instance, some studies remove the primary vein(s) and only use the leaf lamina (Kimak et al., 2015). However, this can be difficult to achieve for leaf forms such as grasses or needles (Roden et al., 2015; Liu et al., 2017). Sampling is usually confined to mature leaves that do not show signs of senescence and the location of sample collection in the canopy (with accompanying differences in microclimate) should be carefully considered.
Freshly sampled leaf material should rapidly be cooled in order to stop any metabolic activity (e.g. by using dry ice or liquid nitrogen). Subsequently, the leaf material should be kept frozen at -20 °C and freeze-dried. This procedure is particularly important for δ18O in leaf material, as some compounds, such as sugars, can continue to exchange oxygen isotopes with the remaining leaf water, altering the original isotope ratio relative to the time of original sampling (Lehmann et al., 2017). After drying, the leaf material can be milled to a fine powder by a steel ball mill, transferred into silver capsules, and the δ18O value determined by TC/EA-IRMS. While isotope analysis of δ18OBL is straightforward, the analysis of δ2H in bulk leaf material is still problematic from a methodological perspective. Thus, most researchers studying hydrogen isotopes extract and purify individual compounds from leaves such as cellulose, fatty acids, or alkanes and determine their respective δ2H values.
δ18O and δ2H analysis of leaf cellulose
For δ18O, soluble sugars and starch may not yet have exchanged all of their oxygen atoms with local water, as occurs during synthesis of structural compounds such as cellulose. Thus, there exists the possibility that variation in non-structural carbohydrate concentrations among leaves may introduce some variability into the δ18OBL. For this reason, some authors have preferred to first extract cellulose from bulk tissue, which is then subject to δ18O analysis on the TC/EA-IRMS. In general, the difference between δ18O of bulk tissue and δ18O of cellulose extracted from it was shown to be less variable for wood than for leaves (Barbour et al., 2001; Cernusak et al., 2004). Thus, the decision as to whether or not cellulose extraction is necessary prior to δ18O analysis of organic material will likely be context-specific, depending on the tissue type (e.g. leaf v. wood), the number of different species analysed, and the treatments imposed on those species (e.g. less than a day v. years).
Leaf cellulose in particular functions as a record of the climatic conditions a plant has specifically experienced during leaf development and can be employed in an experimental context (Helliker & Ehleringer, 2002; Gamarra et al., 2016; Lehmann et al., 2017). Since leaf cellulose is a stable compound with a long lifetime and very low turnover, repeated measurements are generally not necessary (Kimak et al., 2015). More generally, the isotopic analysis of any dateable plant material, such as the cellulose of annual rings in stem tissues (i.e. tree-ring cellulose), can be valuable for reconstructing past plant physiological responses to climatic conditions or shifts in available water sources (Treydte et al., 2014; Saurer et al., 2016).
Several laboratory protocols have been established for isotope analysis of cellulose (Boettger et al., 2007). Many of them follow a similar procedure, in which small pieces of leaf or wood material are packed into small Teflon bags, then i) bleached using an acidic NaClO2 solution to remove lignin for several days, ii) purified with NaOH to remove fatty acids, oils, and hemicellulose, and iii) washed with deionized water and HCl solutions. The remaining cellulose is dried in an oven or freeze-dryer and stored in a dry place until measurement. Additionally, some protocols use an ultrasonicator to homogenise the cellulose material (Weigt et al., 2015). An alternative method has also been developed in which delignification and removal of non-cellulosic polysaccharides takes place within a single step through addition of a mixture of acetic and nitric acid to the plant material, which is located in screw-top vials with silicone O-ring seals (Brendel et al., 2000). Advantages of this method are that it is relatively fast and that it can be applied to small samples. In either case, the purity of the cellulose extraction can be tested against standards using infrared spectroscopy (Rinne et al., 2005).
The prepared cellulose material can then be transferred to silver capsules and the δ18O value determined by TC/EA-IRMS. This procedure is different for δ2H values. Due to a high proportion of oxygen-bound hydrogen in cellulose that constantly exchanges with atmospheric humidity or water, accurate δ2H values of the non-exchangeable carbon-bound hydrogen (holding useful information on plant physiology) cannot be easily inferred from unprepared cellulose. To overcome this problem, cellulose must be chemically converted to cellulose nitrate (DeNiro, 1981), or equilibrated with water vapour of a known isotopic ratio (Wassenaar et al., 2015).
δ18O and δ2H analysis of non-structural carbohydrates
Isotope analysis of non-structural carbohydrates, such as sugars or starch, have a higher turnover than cellulose and thus reflect the influence of short-term environmental effects on a daily or weekly time scale. Also, as noted above, the isotopic composition of these compounds may be more representative of the initial products of photosynthesis, as there will have been fewer opportunities for non-structural carbohydrates to have exchanged atoms with local water than the end products of biosynthetic pathways (e.g. cellulose and lignin). As such, the measurement of the isotope ratios of oxygen and hydrogen in non-structural carbohydrates may be of interest for understanding how trees respond to short-term environmental changes (Lehmann et al., 2018).
Recent methodological developments have made the measurement of δ18O and δ2H values of individual sugars, starches, and other compounds more readily accessible (Wassenaar et al., 2015; Lehmann et al., 2016). The water-soluble compounds can be easily extracted with water or methanol/chloroform/water (MCW) solutions for a short time with heating. This bulk fraction can then be freed from non-sugar compounds such as amino acids, organic, acids, and polyphenols by ion-exchange chromatography and the neutral bulk sugars collected in water (Rinne et al., 2012; Lehmann et al., 2015). For starch extraction and purification, the water insoluble material can be washed repeatedly with water or MCW and the starch extracted enzymatically (Wanek et al., 2001; Richter et al., 2009). The breakdown of starch results in a mix of sugars (e.g. glucose and maltose). Both bulk sugars and starch-derived sugars can then be pipetted into silver capsules, frozen, freeze-dried, and the δ18O values determined by TC/EA-IRMS. Importantly, the samples should remain frozen between analyses to reduce the possibility of oxygen isotope exchange (Lehmann et al., 2017). To determine the δ2H values of bulk sugars and starch-derived sugars, samples should be equilibrated with water vapour of a known isotopic ratio before analysis by TC/EA-IRMS (Wassenaar et al., 2015).
Where to start
Barbour (2007), Cernusak et al. (2016), Dawson & Ehleringer (1998), Gat (2005), Gessler et al. (2009), Roden et al. (2000), Werner et al. (2012)
δ18O and δ2H of water. At landscape scales, source water isotope ratios (e.g. snow and rainfall) vary as a function of a number of different factors. While the temperature at which the source water was formed is the primary control, there are additional effects imposed by latitude, continental landmasses, altitude, and storm event size (Dansgaard, 1964). On top of these are local effects of fractionation and mixing driven by canopy interception and transit into the soil, all of which can contribute to the formation of a distinct profile of soil water isotope composition as a function of depth below the surface (Sprenger et al., 2016). The variation in the isotopic composition of water available to plants in the soil is, in turn, used to interpret how the sources of water taken up by roots vary across time and space.
In particular, there are three primary methods used for inferring the relative proportion of water taken up by plants from different sources within the ground using stable isotopes. The first is graphical inference carried out by matching the isotope composition of the water in xylem with that of the soil using either one or both isotopes (Brunel et al., 1995). The second is the use of a two-source (Dawson & Pate, 1996) or multi-source mixing model (Phillips & Gregg, 2003; Parnell et al., 2013) that statistically solves the relative contributions of the different possible soil-water sources to the xylem water. The third is the use of an analytical and physically based model (Ogle et al., 2004) that incorporates additional information on the plant–soil interface. For all of these methods, the ability to resolve the sources of water observed in the plant xylem increases with the sampling resolution of the potential soil-water sources, as well as with the magnitude of differences among those soil-water sources. Rothfuss & Javaux (2017) provide a detailed review and comparison of these methods.
Finally, vertical profiles of water isotope values are sometimes flat or bimodal, which complicates inferences of depth of water uptake. In these instances, addition of isotopically labelled water to the soil surface, or below it (Beyer et al., 2016), may be of value (Koeniger et al., 2010). D2O is a common choice and relatively inexpensive. Changes in deuterium excess (D-excess = δ2H/8 – δ18O) provide a high signal-to-noise ratio and can be a useful metric for interpretation (Lai & Ehleringer, 2011).
As noted above, the isotopic composition of water in leaves differs from the xylem due to the effects of transpiration. Evaporation of water from the leaf enriches the isotopic composition of the remaining leaf water due to i) an equilibrium fractionation associated with phase change from liquid to vapour and ii) a kinetic fractionation associated with diffusion through the stomata and boundary layer. The magnitude of this fractionation depends on the isotopic composition of both the source water and the atmospheric water vapour, as well as on the ratio of ambient air vapour pressure to leaf intracellular vapour pressure. This enrichment can be modelled using an approach originally developed for well-mixed surface waters and subsequently modified expressly for transpiration (Craig & Gordon, 1965; Dongmann et al., 1974). Cernusak et al. (2016) provide a detailed review of leaf water isotopes.
δ18O of organic material. The δ18O of organic material reflects the effects of evaporative enrichment on leaf water isotopes used for photosynthesis. However, the δ18O of organic material differs from that of leaf water due to fractionation that occurs when oxygen is incorporated into organic molecules. This “biosynthetic” isotope fractionation factor (ℇO) results in a c. 27 ‰ enrichment of organic material (including bulk organic matter, cellulose, and non-structural carbohydrates) compared to the water used for synthesis. The ℇO reflects a reversible hydration reaction on carbonyl groups during photosynthetic carbohydrate biosynthesis (DeNiro & Epstein, 1981; Sternberg & DeNiro, 1983). There is evidence for a temperature dependency of ℇO (Sternberg & Ellsworth, 2011) and it may be important to account for this in some cases. For cellulose from tree rings, enrichment of 27 ‰ above source water is often observed (Saurer et al., 1997; Treydte et al., 2007). However, it has recently been observed that the ℇO of sucrose in grass and tree species can be higher than 27 ‰ (Lehmann et al., 2017).
The δ18O of organic material is further altered by oxygen isotope-exchange reactions occurring between carbohydrate carbonyl groups and water after photosynthesis (Hill et al., 1995; Lehmann et al., 2017). These isotopic exchange processes occur in leaves, but also during translocation of sugars (i.e. from leaves to the stem or roots). Such isotopic exchange dampens the leaf water signal that is imprinted on the organic material by partially incorporating the un-enriched source water signal (Farquhar et al., 1998; Barbour & Farquhar, 2000). Some studies, which use the isotopic composition of tree-ring cellulose to model environmental conditions and plant responses, have found that these post-photosynthetic isotope-exchange processes are relatively constant and that this parameter can be easily implemented into models (Roden et al., 2000; Sternberg, 2009). Other studies have found that these isotopic exchange processes are much more variable and change with tree species, soil moisture conditions, and precipitation amount (Gessler et al., 2013; Pflug et al., 2015; Cheesman & Cernusak, 2017). Recognition of these processes is critical for the accurate interpretation of oxygen isotopes in plant tissues.
δ2H of organic material. The δ2H values in plants are influenced by several isotope fractionations that can be separated into photoautotrophic and heterotrophic processes (Yakir & DeNiro, 1990). Photoautotrophic isotope fractionations (ℇHA) are assumed to cause a partial 2H-depletion in carbohydrates. The mechanism for ℇHA is most likely related to incorporation of 2H-depleted hydrogen derived from water photolysis processes, which is then transferred in the Calvin cycle to carbohydrates via NADPH (Estep & Hoering, 1981; Yakir & DeNiro, 1990). The triose phosphates from the Calvin cycle and their descendants experience an additional set of heterotrophic isotopic fractionations (ℇHH) during hexose and sucrose biosynthesis, causing a 2H-enrichment in non-structural carbohydrates (Yakir & DeNiro, 1990; Zhang et al., 2009). ℇHH can occur in both photoautotrophic (leaves) and heterotrophic tissues (phloem, roots) and is able to affect carbon-bound hydrogen. Although the carbon-bound hydrogen is non-exchangeable from a chemical point of view, the mechanism for ℇHH can be partially explained by hydrogen isotope exchange reactions with (leaf) water in enzymatic catalysed reactions by aldolases or isomerases (Yakir, 1992; Schleucher et al., 1999; Augusti et al., 2006). In heterotrophic tissues, 2H-enriched hydrogen in carbohydrates and cellulose can also derive from NADPH originating from enzymatic reactions of the oxidative pentose phosphate pathway and tricarboxylic acid cycle (Zhang et al., 2009).
The δ2H values of non-structural carbohydrates and cellulose are known to be lower than those of the leaf water used for synthesis and to vary largely among tissues and species (Luo & Sternberg, 1992; Loader et al., 2014). For instance, δ2H values of cellulose derived from photosynthetic tissues have been found to be higher in CAM plants than those of C3 plants (Sternberg et al., 1984). Also, the δ2H values among compounds of different functional groups (i.e. lipids, carbohydrates, proteins) show a very high variability in plants, making hydrogen isotopes an ideal tool to investigate biochemical processes within plants that cannot be inferred from oxygen or other isotopes (Schmidt et al., 2007; Sachse et al., 2012). However, the interpretation of δ2H variations in plant material remains difficult and additional studies will be necessary to realise the full utility of this approach.
5.13.2 Special cases, emerging issues, and challenges
The paired study of stable isotopes of oxygen and carbon in plant organic material (particularly with respect to leaves) can be a particularly powerful approach for providing insights not available from oxygen or carbon isotopes alone (Scheidegger et al., 2000). Additional details are provided in protocol 5.15 Water-use efficiency.
While isotope ratio mass spectrometry has long been considered the gold standard for the measurement of hydrogen and oxygen isotope ratios of water and remains the only means of measuring organic samples, isotope ratio infrared spectroscopy (IRIS) has emerged as a rapid, economical, and low maintenance method for making measurements of both discrete liquid water samples and continuous measurements of water vapour in real time (Wen et al., 2012). It is now well established that these laser-based instruments are vulnerable to interference with the absorption spectra associated with the presence of volatile organic compounds (e.g. alpha-pinene) that are often found in water extracted from plants (West et al., 2010, 2011). Such effects appear to be more limited in the context of soil water, although they may still be present. Both pre- and post-measurement methods have been developed to mitigate these effects (Martín-Gómez et al., 2015; Chang et al., 2016; Johnson et al., 2017), but so far, these methods have not completely resolved the problem and it remains critical to validate the IRIS measurements on IRMS. Nevertheless, the development of this technology has facilitated exciting advances in our ability to understand how water moves through the soil–plant–atmosphere continuum in real time. This includes continuous in situ monitoring of soil and plant xylem water isotopes that is likely to provide compelling new insights into plant water use in response to changing plant water supply and demand (Volkmann & Weiler, 2014; Volkmann et al., 2016; Oerter et al., 2017).
In addition to IRIS, advances in IRMS are also opening new doors for research. Plant metabolic processes or isotopic exchange can alter the isotopic signal before it is ultimately transferred to a stable compound that is functioning as a biomarker (Lehmann et al., 2017). Identifying and understanding these hidden isotope fractionation processes and how they respond to changing climatic signals is often not straightforward, but it is necessary to improve the precision and accuracy of their application. To open this black box, compound-specific isotope analysis (CSIA) by gas chromatography/pyrolysis-IRMS (GC/Pyr-IRMS) is emerging as a useful tool for determining δ18O or δ2H of particular biomarkers and their precursors, including specific carbohydrates (Lehmann et al., 2016), hemicellulose (Zech & Glaser, 2009), n-alkanes (Sachse et al., 2012), and levoglucosan (Blees et al., 2017). While much of this work remains in development, CSIA holds significant promise for becoming a means of directly tracking plant functional response to environment from source to sink, as well as for improving our existing use of stable isotopes of water.
The use of stable isotopes of hydrogen and oxygen as a means of answering questions regarding plant function is currently an active field of research. This includes innovations in methods development (e.g. continuous in situ monitoring of water isotopes; Volkmann & Weiler, 2014), as well as cautions regarding the use of existing methods (e.g. differences among methods used for extracting water from matrices; Orlowski et al., 2016). It also includes advances in our understanding of how hydrogen and oxygen isotopes fractionate and mix in the soil (e.g. Gaj et al., 2017), upon uptake (Vargas et al., 2017), and in plants (e.g. Goldsmith et al., 2017) and, as such, there will remain a premium on the careful design, implementation, and interpretation of hydrogen and oxygen isotopes based on the latest research.
Theory, significance, and large datasets
Barbour (2007), Cernusak et al. (2016), Evaristo et al. (2015), Gat (2005), Scheiddiger et al. (2000)
More on methods and existing protocols
Lehmann et al. (2016), Loader et al. (2014), Martín‐Gómez et al. (2015), Rothfuss & Javaux (2017), West et al. (2006)
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Cheesman, A. W., & Cernusak, L. A. (2017). Infidelity in the outback: climate signal recorded in Δ18O of leaf but not branch cellulose of eucalypts across an Australian aridity gradient. Tree Physiology, 37(5), 554-564.
Coplen, T. B. (2011). Guidelines and recommended terms for expression of stable‐isotope‐ratio and gas‐ratio measurement results. Rapid Communications in Mass Spectrometry, 25(17), 2538-2560.
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Authors: Goldsmith GR1, Marshall JD2, Barbeta A3, Lehmann MM4
Reviewer: Cernusak LA5
1 Schmid College of Science and Technology, Chapman University, Orange, USA
2 Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Umeå, Sweden
3 INRA, UMR ISPA, Villenave d’Ornon, France
4 Forest Dynamics, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland
5 College of Science and Engineering, James Cook University, Cairns, Australia