5.3 Characterizing midday ΨL regulation
Periodic
midday ΨL measurements (10:00–16:00 local time) were
compiled from a dataset of over 1600 observations collected throughout
the growing seasons of 2011–2017. On each measurement day, one to five
samples were collected from one to three trees per species from the
upper third of the canopy. Leaves were bagged for ~15
minutes prior to excision to allow Ψ of the leaf cells and stem xylem to
reach equilibrium (Leach et al. , 1982; Roman et al. ,
2015); this approach was conducted in every site except for IN 35yo
where canopies were inaccessible from the ground or by cherry picker.
After excision, ΨL was measured using a pressure chamber
(PMS Instruments, Corvallis, OR, USA) (Turner, 1988) immediately in the
field, or after leaves were transferred to the lab in humidified bags
stored in a cooler. All together, we made 704, 178, and 757
ΨL observations of L. tulipifera , A.
saccharum , and Q. alba , respectively. The number of
ΨL observations and sampling days varied across regions,
but ΨL was measured on 4–51 different days at each
stand, including sampling at the beginning (June) and end (September) of
the growing season to permit observation throughout dynamic seasonal
changes of moisture conditions.
While regulation of plant water status is frequently characterized as
the sensitivity of ΨL to declining ΨS(McDowell et al ., 2008; Klein, 2014; Martínez-Vilalta et
al ., 2014; Matheny et al., 2015; Meinzer et al.,2017), this metric of isohydricity can change temporally
as drought evolves (Hochberg et al., 2018; Wu et al.,2021), and is often inconsistent for the same species from one stand to
the next (Martínez-Vilalta & Garcia-Forner, 2017). These
inconsistencies likely reflect the fact that the degree of isohydricity,
when defined as\(\ \partial\Psi_{L}/\partial\Psi_{S}\), is complicated
by environmental interactions (Hochberg et al ., 2018), including
variability in D which can also affect ΨL (Domec
& Johnson, 2012; Novick et al ., 2019), or when the magnitude of
soil water deficit during the sampling period is insufficient to capture
stress responses (Martínez-Vilatla & Garcia-Forner, 2017).
Another proposed metric – the “hydroscape” concept (Meinzer et
al., 2016; Li et al., 2019) based on the integrated area between
the observed \(\Psi_{L}-\Psi_{S}\) curve – can overcome some of the
conceptual difficulties associated with\(\partial\Psi_{L}/\partial\Psi_{S}\). However, the hydroscape is still
fundmentally informed by the relationship between \(\Psi_{L}\ \)and\(\Psi_{S}\). Thus, the hydroscape does not directly account for
variability in ΨL driven by D and can be hard to
quantify in mesic sites where \(\Psi_{S}\) may be relatively stationary
even while temperature-driven variation in D may be large.
Negative excursions in \(\Psi_{L}\ \)driven by D may be
especially important in eastern US forests, where limitations to
stomatal conductance from D have been shown to dominate over soil
water limitations, at both the stand (Novick et al ., 2016) and
tree-scale (Yi et al., 2019; Denham et al ., 2021). While
substantial soil water deficits occurred in some of our sites (e.g., MO,
NC_E, IN), the more mesic NC_W stands rarely experience soil water
limitations, and soil water deficits were not observed during the study
period (Fig. S1); however, ΨL reductions during periods
of elevated D occurred routinely (Fig. S2). For these reasons, we
quantified isohydricity as the variability in seasonal midday
ΨL to capture ΨL sensitivity to both
declining soil moisture and increasing D (See SI.1 for further
discussion). To minimize error associated with uncharacteristic behavior
during spring leaf out and fall senescence, ΨL data used
for this analysis were constrained to a period of relatively stationary
leaf area index (days of year 150–270).