Results
3.1 Underlying growth pattern of
trees
We revealed the growth trajectories of trees on the century scale, at
the aggregate, and individual levels. With DBH as the gradient, the
maximum tree ring increment of fir communities at different altitudes
was determined and the results are presented in Fig. 2, which reflects
the inherent or ideal growth law independent of the environment. The
radial growth of ideal trees at altitude of 2,900m, 3,100m and 3,300m
exhibit unimodal (Figs. 2b and c) or bimodal (Fig. 2a) characteristics.
For a range of DBH less than 80 cm, the fir radial growth at all
altitudes except at the treeline exhibit a unimodal curve extended by
Gompertz pattern (Eq. 1b) (Tab. S2). We also directly observed a
unimodal curve based on logistic pattern in the larger DBH interval
(>80 cm) (Tab. S2). The growth also shows an initial
increase and then a linear decreasing pattern, as shown in Fig. 2d.
Trees at the altitude of the treeline are subjected to a harsher
environment, and the observed linear growth pattern may indicate the
incomplete expression of a unimodal pattern.
The aboveground biomass measurements also reveal the unimodal growth of
ideal trees, as shown in Fig. 3. These unimodal curves are as obvious as
those corresponding to radial growth. The unimodal parts are still well
explained by Eqs. 3 and 2 (R2>0.7,
P<0.01. Tab. S3). From a more complete growth curve, it can be
seen that the growth trajectory of trees can transit from one smaller
unimodal curve to a larger one, as shown in Fig. 3a. Not only that, the
average increment dynamics may be unimodal or multimodal because of the
covariant relationship with the ideal increment dynamics (Fig. S2). For
the same reason, the biomass dynamic near the forest line (Fig. 3d) was
similar to that of DBH (Fig. 2d). To a large extent, these results
directly support H1.
The growth trajectories of selected trees were determined and are shown
in Fig. 4. Clearly, these unimodal curves vary in size and do not fully
cover the entire growth process, as some independent growth changes
occur before and after the unimodal curve. In fact, there may be more
than one unimodal curve, as shown in Fig. 4e. The maximum heights and
lengths of the unimodal curves increase with tree size. For example, the
lengths of unimodal trajectories of trees with biomass 1412 kg and 4855
kg are 510 kg and 2053 kg respectively, and the heights of those are 115
kg and 180 kg respectively (Figs. 4h and i). These trajectories driven
by radial and tree height growth conform to the Gompertz curve. See Tab.
S4 for fitting results.These results support H2.
3.2 Change of functional traits with
growth
Due to the lack of significant difference in module traits (i.e., leaf
and stem economics) of individual trees, here, we only presented the
traits corresponding to different size intervals (Ⅰ, Ⅱ, and Ⅲ), as shown
in Figs. 5 and 6. However, structural indicators (canopy/size and
SWA/SHA) are not stable. Except for trees located at the treeline (Fig.
7d), the canopy/size and size of other trees at other elevations should
conform to the logistic relationship. The SWA/SHA and sizes of all trees
show an obvious inverse relationship (see Tab. S5 for fitting results).
According to our hypothesis, increasing canopy/size and decreasing
SWA/SHA would result in a greater growth increment and maximum biomass
(Fig.1 and Tab. 1).
Thus,
these two traits may be related to cascading growth. In practice, in
accordance with the actual biomass intervals in Figs. 3a and c where the
Gompertz curves are located (i.e., left side of vertical solid line in
Figs. 3a and c), the SWA/SHA and
canopy/size of ideal trees can be
estimated by the size of ideal trees (dotted line in Fig. 7) and the
size-traits function. The calculated SWA/SHA and canopy/size are 0.28
and 0.75 (2,900m), 0.30 and 0.79 (3,100m) and 0.47 and 0.70 (3,300m).
3.3 Changes in canopy and sapwood
relative to size are the main causes of cascading
growth
With
very stable leaf and stem economics, we next tested whether canopy /size
and SWA/HWA can affect the formation of unimodal curve. According to
Fig. 1 and Tab. 1, we tested canopy /size ∝
maximum growth rate (∝cM ), SWA/HWA ∝ mr and
SWA/HWA∝ 1/maximum growth rate (∝
1/cM ). In
addition to individual trees at an elevation of 3,100m, these analyses
also included ideal trees at different altitudes (black dots). All
relationships are confirmed well
(R2>0.56, p<0.01), as shown in
Figs. 8a, b and c. Due toM max∝cM /mr (Fig. S3), we
expected a positive correlation between canopy /size ×HWA/SWA andM amax. WhenM amax is less than 2100kg, this correlation tends
to be linear (R2=
0.93, p<0.01), as shown in Fig. 8d. Overall, this relationship
is closer to power function (R2= 0.93,
p<0.01). Obviously, the the height and length of the growth
curve can be largely explained by the morphological traits, consistent
with H3.