Discussion
Xylem water matches source water, but bulk stem water
doesn’t
Our data show that the Cavitron-extracted xylem water had δD signatures
that closely aligned with source water (mean of δD offsets not
significantly different from zero), with virtually identical trend lines
between these two groups. This result corroborates the findings of
recent studies that used a Cavitron for xylem water extraction (Barbeta
et al., 2022; He et al., 2023; Wen et al., 2023). Similar centrifugation
methods relying on smaller stem segments have also resulted in
relatively good alignments with source water (Sánchez-Murillo et al.,
2023). While not directly tested against source water measurements,
other techniques targeting mobile xylem water, such as direct vapour
equilibration (Millar et al., 2018) and pressure chamber extraction
(Bowers & Williams, 2022; Zuecco et al., 2022), have also produced δD
signatures likely reflective of source water.
We found that unlike xylem water, bulk CVD-extracted water was strongly
depleted in δD relative to both source water (median δD offset –15.5\($\textperthousand$\))
and Cavitron-extracted water (median δD bias –14.9\($\textperthousand$\)). The tendency of
CVD extraction to introduce systematic isotopic biases is now well-known
and has been thoroughly described through recent experimental work by
Wen et al. (2022). These authors have shown that CVD-induced bias is
caused by both within-stem isotopic differences between xylem and tissue
(as per Barbeta et al., 2022) and hydrogen exchange with organics (as
per Chen et al., 2020), with hydrogen exchange being the dominant
process. Diao et al. (2022) propose an alternative perspective,
suggesting that while hydrogen exchange does occur, CVD-induced biases
are mostly related to isotopic fractionation during CVD extraction, and
that extracting larger volumes of plant water through CVD can reduce
these biases. In our case, the exact CVD-extracted volumes were not
recorded, but were on average 0.25 mL. According to Diao et al. (2022),
this small sample volume size could lead to a δD bias roughly ranging
from –10 to –35\($\textperthousand$\), consistent with our observations – although we note
that the volume effect would be specific to the CVD setup used.
Overall, our results add to the growing empirical evidence that sampling
xylem water yields more reliable estimates of plant water sources,
compared to methods analysing bulk stem water.
Cryogenic bias is species-specific, but independent of stem
water content and
status
Our data indicate that while the CVD-induced δD bias was apparent across
seven tree species, it affected each species differently, with mean
biases ranging from –19.3\($\textperthousand$\) (C. bella) to –9.1\($\textperthousand$\) (M.
argentea). These results support the findings of Chen et al. (2020),
who showed via rehydration experiments that CVD-induced biases differed
in the range –5 to –11\($\textperthousand$\) across nine species, and those of Barbeta et
al. (2022) who observed significant inter-specific differences in the
range –12.7 to –22.3\($\textperthousand$\) across three species. More broadly, the global
synthesis by de la Casa et al. (2022) suggests considerable variations
in δD biases across different species – although this study inferred
biases based on δD offset calculations using source water, rather than
through direct measurements.
Variability in δD biases within single species was relatively low,
although the small number of replicate trees was a limitation of our
study – except for H. arborescens for which we have data for
seven individual trees. For this species, the measured δD biases varied
between –20.4 and –13.6\($\textperthousand$\). Limited within-species variation was also
reported by Barbeta et al. (2022) for Fagus sylvatica and by
Bowers and Williams (2022) for a range of conifer species. Wen et al.
(2022) found large variations in the δD of xylem water between apple
trees of the same species (and even within single individuals), but
their δD biases were less variable, similar to our findings.
CVD-induced δD biases were not correlated with RSWC or stem water
isotopic composition. This is at odds with recent laboratory studies
where stem water content emerged as a key driver of the CVD δD bias.
Chen et al. (2020) and Wen et al. (2022) showed that a higher stem
content resulted in a lower bias, and Wen et al. (2022) showed that more
δD-depleted stem water resulted in lower biases. However, these two
studies were rehydration experiments so may not be reflective of natural
conditions. Our results are more in line with those of Barbeta et al.
(2022), Bowers and Williams (2022) and He et al. (2023) who found, under
field conditions, non-significant or weakly significant relationships
between RSWC and δD bias.
CVD-induced δD biases were not correlated with pre-dawn LWP either. This
lack of a relationship between δD biases and water availability suggests
that the extent of tree water stress may not affect the CVD bias. Bowers
and Williams (2022) observed a negative correlation between
species-specific xylem vulnerability to cavitation and δD bias, and
hypothesised that less vulnerable species might have less well-mixed
xylem conduits, potentially leading to higher δD biases. While our data
do not allow us to test this hypothesis, it is plausible that the
observed inter-specific differences may be related to anatomical
differences between species, rather than to point-in-time water stress
conditions (e.g. differences in connectivity of xylem conduits, variable
xylem residence times; Bowers and Williams (2022)). The wide range of
observed LWPs (–1.97 to –0.18 MPa) suggests that the sampled species
may represent a spectrum of anatomical adaptations to aridity, given
this is a strong driver shaping stem hydraulic traits in Australian
trees (Peters et al., 2021). Overall, there is a clear need for research
that further untangle the respective roles of anatomical and functional
tree properties in CVD-induced δD biases.
Concluding remarks
Our dataset provides robust evidence of (1) a strong δD bias in
CVD-extracted bulk stem water relative to xylem water and source water,
(2) significant differences in the magnitude of these biases among tree
species, and (3) the limited influence of RSWC and LWP in explaining
variations in δD bias. However, our inability to extract sufficient
water from some stem samples resulted in a low number of replicates per
species. These low numbers might have hindered the detection of any
species-specific patterns in the data, suggesting that our third
conclusion might not hold for individual species. To improve water
extraction yields, particularly for trees in seasonally dry
environments, we recommend using a larger version of the Cavitron
(500-mm diameter), which can host longer stems hence yield higher water
volumes.
In the context of future plant water sourcing studies, we recommend that
non-destructive extraction techniques that target xylem water, such as
Cavitron centrifugation (e.g. Barbeta et al., 2022; He et al., 2023),
pressure chamber (e.g. Wen et al., 2023; Zuecco et al., 2022) or in-situ techniques (e.g. Kübert et al., 2023; Kühnhammer et al.,
2022), be preferred over CVD extraction. Should no alternative be
available, one should ensure that large volumes (specific to each
experimental setup) are extracted via CVD (Diao et al., 2022). In any
case, the similarities we found between average δD biases and average δD
offsets lead us to the conclusion that CVD-derived bulk stem water
isotopic signatures can potentially be corrected to provide a reasonable
approximation of xylem water isotopic signatures. Yet this adjustment
can only be done using a site-specific δD offset, a step that requires
the local source water line to be known.
Unlike Chen et al. (2020), we discourage the indiscriminate use of a
uniform offset correction for all sites, because δD offsets may be
highly site- and method-dependent (Diao et al., 2022; Millar et al.,
2018). We also recommend using an average, site-specific δD offset for
the correction of CVD data (Duvert et al., 2022) rather than individual
offsets (Barbeta et al., 2019; He et al., 2023), as using individual
offsets for each sample eliminates the natural variability in δD among
samples. In turn, this can introduce additional uncertainties to plant
water source identification. Until a complete understanding of the
mechanisms generating δD offsets is achieved, corrections of CVD data
should be made with a high degree of caution, and researchers should
consider assessing plant water sources based on δ18O
data alone.
Our work emphasises how considering an appropriate methodology when
seeking to characterise plant water uptake is key to advancing our
understanding of the role of vegetation in partitioning rainfall into
evapotranspiration and recharge. From a water resource management
perspective, this field of research is also becoming increasingly
relevant, particularly in areas where exploited groundwater systems
support groundwater-dependent ecosystems of ecological and cultural
significance.