5.6 Data processing and analysis
We investigated differences in P12 and P50 across species and stands
(hypotheses 1 and 2) with a two-way ANOVA, where species and stand age
were fixed factors and region was a blocking factor.
We compared vessel density and
lumen area with a two-way ANOVA, where species and stand age were fixed
factors. We removed region as a blocking factor because there was no
significant region or region interaction effect at p = 0.05. The
relationships between xylem anatomy (e.g., vessel density and vessel
lumen area) and embolism thresholds (e.g., P12 and P50) were assessed
with a least squares linear regression within and across species. All
ANOVA analyses were performed at the α = 0.05 level and were followed by
a Tukey post-hoc test for significant main effects. Significant
interaction terms were assessed by pairwise comparison of least square
means.
We analyzed the relationship between embolism thresholds and degree of
isohydricity (hypothesis 3) in two ways. First, we used in-situΨL observations and laboratory generated xylem embolism
curves to estimate the percent of native embolism across species and
stands during the study period. Specifically, we used the minimum
ΨL observation (ΨL,min) of a
non-transpiring (bagged) leaf for each species in each stand as an
approximation of equilibrated Ψx (Williams & Araujo,
2002; Zhang et al., 2013). While this approach is common (Choatet al., 2010; Zhang et al., 2013; Johnson et al.,2016), a gradient often exists between stem xylem and distal tissues
such that ΨL and Ψx are not always equal
(Simonin et al., 2015; Johnson et al., 2016; Holtzmanet al ., 2021). However, ΨL and Ψxare often correlated and most similar when hydrologic stress forces
stomatal closure (Holtzman et al., 2021). Thus,
ΨL,min as determined from bagged leaves is likely a
close approximation of Ψx. but may over-estimate true
extent of embolism propagation if equilibration between
ΨL and Ψx was not achieved during
bagging. Nevertheless, estimating native embolism in this manner yielded
similar values to those reported in the literature for L.
tulipifera (Johnson et al., 2016), A. saccharum (Wheeleret al., 2013), and Quercus species (Sperry & Sullivan
1992; Taneda & Sperry, 2008; Peguero-Pina et al., 2018). We
assessed differences in estimated native embolisms across species and
stands with a two-way ANOVA, where species and stand age were fixed
factors and region was a blocking factor. The relationship between
native embolism and degree of isohydricity was then assessed with a
least square linear regression between mean estimated native embolism
and interquartile range of ΨL of each species in each
stand. We excluded IN 35yo data from this analysis because leaf bagging
was not possible in this site (see section 5.3).
Second, we investigated hypothesis 3 in the context of a hydraulic
safety margin (Ψsafety) (MPa). Safety margins from P12
(Ψsafety, P12) (MPa) and P50 (Ψsafety,
P50) (MPa) were calculated as (Domec & Gartner, 2001; Delzon &
Cochard, 2014):
\(\Psi_{\text{safety}}=\ \Psi_{L,min}-\Psi_{\text{thresh}}\) (3)
where Ψthresh,(MPa) is mean embolism threshold (e.g.,
P12 or P50) for the same species in the same stand. A negative
Ψsafety suggests a high level of xylem embolism, while a
positive Ψsafety suggests a window of safety from
critical levels of xylem damage (Johnson et al ., 2016). We then
performed a least square linear regression between
Ψsafety and the ΨL interquartile range
across species and stands. Ψsafety should characterize
the difference between the largest xylem water tensions experienced by
the plant and the level of water stress leading to a threshold of
hydraulic failure (Domec & Gartner, 2001; Delzon & Cochard, 2014).
Therefore, we considered whether these analyses were sensitive to
hydrologic conditions during the study period, since the observed
ΨL, min may underestimate ΨL during
extreme exposure to drought (Bhaskar & Ackerly, 2006). We used
parametric bootstrapping to quantify a range of slopes of the
relationship between ΨL interquartile range and
Ψsafety and ΨL interquartile range and
estimated native embolism. Specifically,
for each unique site-species
combination, we created normal
distributions of each variable using the observed mean and standard
deviation of each metric for each site-species. We then drew 100
estimates of ΨL from the lowest 10% quantile of 50,000
data points drawn from the normal ΨL distribution, and
100 estimates of Ψthresh from the middle 60% of 50,000
data points drawn from the normal Ψthresh distribution.
We experimented with a range of thresholds for the ΨLquantile, ultimately selecting 10% as it produced estimates of
ΨL that were at least occasionally lower than the
observed minimum ΨL for each site-species. However, most
of the simulated ΨL within this quantile were greater
than the observed minimum ΨL, such that this is a
relatively conservative approach that underestimates the minimum
ΨL more than it overestimates it. In future work, other
probability distributions, including extreme value distributions
(Martínez-Vilatla et al., 2021) could be used instead. Together,
these simulated data gave us 100 estimates of Ψsafetythat accommodated uncertainty in both ΨL and
Ψthresh and allowed us to estimate 100 unique slopes of
the relationship between Ψsafety and the
ΨL interquartile range. Again, we excluded data from the
IN 35yo site in this analysis.