3.1 Stability and productivity in planted and natural forest
Natural forests showed greater temporal stability in AGB than planted
forests over the last four decades (T value=5.19, P<0.0001)
(Fig. 2a). Despite the low diversity of planted forest (often with a
single tree species), the AGB stocks of planted forest (0.028±0.027 Tg
ha-1) was similar to that of natural forest
(0.029±0.028 Tg
ha-1); however, the productivity of planted forest was
much higher compared with natural forest (T value=4.65,
P<0.001) (Fig. 2b). AGB stability significantly decreased at a
rate of -0.013 yr-1 (T value=-9.06, df=4893,
P<0.0001) in natural forest and
-0.011
yr-1 (T value=-3.53, df=546, P<0.0001) in
planted forests (Fig. 3a). There was a significant decrease in
productivity (T value=-4.76, df=4893, P<0.0001) in natural
forest, with a slope of -0.0065 Mg
ha-1 year-1 per calendar year;
productivity in planted forest did not change significantly (Fig. 3b).
3.2 Environmental and forest structure predictors of
productivity and AGB stability in planted and natural forests
In natural forest, annual precipitation (Z value=3.47, P=0.00053) and
latitude (Z value=2.04, P=0.042) had a negative effect on AGB stability
in the conditional average models after accounting for spatial
autocorrelation (Fig. 4a). AGB stability was higher in natural forest
plots with older stand age and higher altitude (Fig. 4a). However,
richness (Z value=1.95, P=0.055) and stand age (Z value=1.71, P=0.087)
were not significantly related to AGB stability in planted forest in the
conditional average models (Fig. 4a). Based on the GAMM model, there was
a significant non-linear relationship of tree density (F value=6.12, P
<0.0001) and stand age (F value=8.64, P <0.0001)
with stability in natural forest (Fig. S3 a and c). And, there was no
significant association between richness and stability in natural forest
(F value=0.97, P =0.34) and planted forest (F value=3.81, P =0.053)
(Fig. S3b) in GAMM model. In addition, density (F value=0.26, P =0.61)
and stand age (F value=2.80, P =0.11) did not significantly affect
stability in planted forest (Fig. S3 a and c)
The conditional average models for natural forest productivity change
included precipitation, stand age, latitude, soil depth, and tree
density (Fig. 4b). Annual precipitation (Z value=3.73, P=0.0002), soil
depth (Z value=5.51, P<0.0001), and latitude (Z value=5.68,
P<0.0001) played a significant positive role in productivity
in natural forest (Fig. 4b). Productivity decreased with Stand age was
in natural forest (Z value=5.87, P<0.0001) (Fig. 4b). No
significant effect of tree density on productivity in natural forest was
observed (Z value=0.16, P=0.87) (Fig. 4b). The change in productivity in
planted forest was most strongly affected by stand age, tree density,
richness, and altitude. Productivity increased significantly with
richness (Z value=4.42, P<0.0001) and tree density (Z
value=3.38 P=0.00072) (Fig. 4b), and decreased significantly with stand
age (Z value=3.71, P=0.00021) (Fig. 4b). Productivity of planted forests
was higher at higher altitudes (Z value=2.25, P=0.025) (Fig. 3b). Based
on the GAMM models, the productivity of natural (F value=25.95, P
<0.0001) and planted forest (F value=4.49, P =0.011) increased
logarithmically with tree density (Fig. S2 d) but displayed contrasting
patterns with tree density. Productivity also increased
near-logarithmically with stand age (F value=5.80, P <0.0001)
in natural forest (Fig. S3 f), and stand age had negative and linear
effects on the present-day productivity of planted forest (F value
=-1.96, P =0.050). Richness played a positive role in productivity in
planted forest (F value=17.72, P <0.0001) but not in natural
forest (F value=0.64, P =0.43) (Fig. S3 e). In general, the results of
the GAMM models and GLS models were consistent.