Results
Under a common environment of the tree plantations, the seven pine
species exhibited relatively large variations in trunk radial growth
rate. Across a cambial age sequence of 15 years, the cumulative basal
area of all the seven pine species exhibited linear relationships with
age but the rate of increment showed relatively large interspecific
differences (Fig. 2). The cumulative basal area at cambial age of 15
years (CBA15) varied more than two folds among the
studied species, i.e. ranged from 83.9 cm2 in P.
tabuliformis to 209.1 cm2 in P.
sylverstriformis . Similarly, the standardized tree-ring width
chronologies of the seven studied species showed that there were
relatively large variations in climate sensitivity of the annual
tree-ring growth with the mean sensitivity ranged from 0.21 in P.
koraiensis to 0.33 in P. tabuliformis (Table 1). Moreover, our
tree-ring analyses showed that radial growth of the seven species showed
substantial interspecific differences in responding to the extreme
drought event happened in 2015, i.e. with values of the drought
resistance index ranged from 0.54 in P. densiflora to 1.33 inP. koraiensis and the drought resilience index ranged from 0.51
in P. densiflora to 1.30 in P. koraiensis . All the studied
species showed relatively low recovering ability after the extreme
drought stress with the recovery index mostly lower than 1.25 (Table 1;
Fig. 3).
The leaf mass based maximum photosynthetic rate
(A m) ranged from 0.0124 μmol
g-1 s-1 in P. koraiensis to
0.0194 μmol g-1 s-1 in P.
sylvestriformis (Table S1; Fig. 4a), sapwood-specific hydraulic
conductivity (K s) and leaf-specific hydraulic
conductivity (K l) ranged from 0.92 kg
m-1 s-1 MPa-1 and
1.05×10-4 kg m-1s-1 MPa-1 in P. koraiensis to
1.32 kg m-1 s-1MPa-1 and
3.73×10-4kg m-1 s-1 MPa-1in P. densiflora , respectively (Fig. 4b). There is a significant
positive correlation between K s andA m across the seven studied pine species
(P < 0.05, Table S2; Pearson correlation). All the
studied species showed relatively large hydraulic safety margins (HSM)
ranging from 0.88 MPa in P. densiflora var. zhangwuensisto 1.29 MPa in P. koraiensis (Fig. 5a). Interspecific variation
in wood density (WD) among the studied species overall showed a
consistent order with that of HSM (Fig. 5a, b) that leads to a
significant positive correlation between the two parameters (P< 0.05, Table S2; Pearson correlation). The order of
interspecific variation in leaf level traits related to drought
tolerance, as measured by leaf turgor loss point
(π 0), showed different patterns with that of
stem traits related to hydraulic tolerance to drought (Fig. 5a-c), which
resulted in non-significant correlations across species between leaf and
stem traits relevant to drought tolerance (Table S2).
Our results showed that tree drought resistance and resilience indices
calculated from tree-ring analyses overall exhibited strong coordination
with stem and leaf physiological traits related to drought tolerance
(Fig. 6a-f). RT and RS were both positively correlated with WD (P< 0.01; Fig. 6a, d), HSM (P < 0.05, P= 0.115; Fig. 6b, e), and π 0 (P = 0.069
and 0.038; Fig. 6c, f). Contrastingly, both RT and RS showed significant
negative correlations with functional traits pertinent to xylem
hydraulic efficiency and leaf photosynthetic carbon assimilation (Fig.
7a-d). We found that tree radial growth rate as reflected by
CBA15 has a strong negative correlation with growth
sensitivity to inter-annual climate variability calculated from
tree-ring analysis (P < 0.05; Fig. 8).