Root-shoot ratio varied between two origins
The re-complied dataset covered a large range of environmental variations, e.g., annual mean temperature ranged from -5.7 ℃ to 24.9℃, and annual precipitation ranged from 25 mm to 3354 mm (Table S1). The root-shoot ratios varied between forest origins (Fig.S1), as the ratios of the natural forests (mean±se, 0.243 ± 0.003, n = 653) was marginally significantly higher than that of planted forests (0.236 ± 0.002, n =1278) (p = 0.073). For the natural forests, root-shoot ratio ranged from 0.057 to 0.620 with median value as 0.237; while for the planted forests, it ranged from 0.033 to 0.588 with median value as 0.225.
Relative importance of variables on root-shoot ratio
The six variables (forest age, forest density, BIO4, BIO8, BIO15 and BIO18) were finally identified as most important factors affecting the root-shoot ratio of forest ecosystems in China. With these variables, RF models performed moderately well on variations of the root-shoot ratio, e.g., they explained 28.35 % (RMSE = 1.87%, MAE = 1.11%), 33.18 % (RMSE = 1.59%, MAE = 0.76%) and 33.42 % (RMSE = 1.34%, MAE = 0.68%) variations of the root-shoot ratio in the natural, planted and full forest stands, respectively (Table 2, Fig. 2). Relative importance value (VIMP) and order of the selected environmental factors on the root-shoot ratio varied with forest origins (Table 2, Fig. S2), but forest age or forest density was generally contributed to the most importance in the root-shoot ratio variations regardless of forest origins. For the full dataset, the forest age (133.80%), BIO18 (108.74%) and forest density (102.31%) accounted for the top three important variables on the root-shoot ratios (Table 2, Fig. 2a). For the natural forests, VIMP with the decreasing order was forest density (54.42 %), forest age (51.05%), BIO4 (48.97%), BIO8 (48.95%), BIO18 (47.05%), BIO15 (38.95%) (Table 2, Fig. 2b); for the planted forests, the largest VIMP was forest age (117.27 %), followed by BIO18 (99.45%), BIO4 (79.54%), BIO15(77.21%), BIO8 (75.35%) and forest density (74.61%) (Table 2, Fig. 2c). Significantly linear relationship occurred between the RF-based predicted root-shoot ratio (RS) and the field observed RS across forest origins (Fig.2 d-f).
Table 2 Relative importance of the variables selected by the VSURF function on the root-shoot ratios in forest ecosystems of China. R2pseudo and MSEfitted were calculated from model predicted against observed values; RMSE and MAE derived from media cross-validation; R2pseudo-median was median permuted percent variance explained.
Variables
|
Full data
|
Natural forest
|
Planted forest
|
|
%IncMSE
|
P
|
%IncMSE
|
P
|
%IncMSE
|
P
|
Forest age
|
133.80
|
0.020
|
51.05
|
0.020
|
117.27
|
0.020
|
Forest density
|
102.31
|
0.020
|
54.42
|
0.020
|
74.61
|
0.020
|
BIO4
|
90.49
|
0.020
|
48.97
|
0.020
|
79.54
|
0.020
|
BIO8
|
91.22
|
0.020
|
48.95
|
0.020
|
75.35
|
0.020
|
BIO15
|
86.80
|
0.020
|
38.95
|
0.020
|
77.21
|
0.020
|
BIO18
|
108.74
|
0.020
|
47.05
|
0.020
|
99.45
|
0.020
|
Model performance
|
R2pseudo, %
|
34.42
|
28.35
|
33.18
|
MSEfitted, %
|
0. 44
|
0. 57
|
0. 41
|
RMSE, %
|
1.34
|
1.87
|
1.59
|
MAE, %
|
0. 68
|
1.11
|
0. 76
|
Pvalue
|
<0.001
|
<0.001
|
<0.001
|
R2pseudo-median, %
|
97.12
|
94.30
|
95.97
|
Partial dependent of root-shoot ratio on environmental variables
Overall, root-shoot ratio decreased with increase of forest age for both forest origins. However, after initial decrease it turned to increase to a relative stable level (the turning point, e.g., ca. 150yr occurring for natural forests and ca.30yr for planted forests) (Fig.3-a, g). The root-shoot ratio increased nonlinearly with forest density in both forest origins (Fig.3). The ratios decreased with temperature seasonality (BIO4) until to ~50℃ (natural) and ~70℃ (planted), and then increased. The ratios responding to mean temperature of wettest quarter (BIO8) was opposite between two origins when BIO8 < 15℃, as presenting increasing trend for natural forest while with decreasing trends for planted forests. Interestingly, root-shoot ratios responded to precipitation seasonality (BIO15) with cosine-like trend in the natural forest, while with inverse parabolic trend in the planted forest. Specially, both origins initially decreased with BIO15 toward the bottoms (~ 60 mm for natural and ~75mm for planted forest) and then rebound, but only descend again in the natural forest (vertex value: ~ 90 mm). Finally, consistent trends were also observed in the response of root-shoot ratio to precipitation of warmest quarter (BIO18) for two forest origins, as initially sharply decreasing but after BIO18≈500mm, both turning to slightly increase afterwards.
Direct and indirect effects of environmental factors on root-shoot ratio
SEMs explained a few variations of root-shoot ratio (Fig.4), e.g., 16.5% for natural forest and 4.9% for planted forest, which maybe contributed mostly by strongly non-linear correlation between dependent and independent variable as revealed by above partial analysis (Fig.3), but still providing to some extent information about the direct and indirect effects of variables on the root-shoot ratio studied. Consistently, four variables (forest age, BIO4, BIO8 and BIO18) had direct negative effects on root-shoot ratio of both origins, and their standardized direct effects were -0.108, -0.094,-0.092 and -0.229 in the natural forests, and -0.080, -0.015,-0.099 and -0.092 in the planted forests, respectively (Table S2). Two variables (forest density and BIO15) had direct positive effects on root-shoot ratio, and their standardized direct effects were 0.177 and 0.165 in the natural forests, and 0.096 and 0.099 in the planted forests. Meanwhile, only two variables (forest age and BIO15) exerted significantly indirect negative effects on root-shoot ratio through forest density, and their indirect effects were -0.080 and -0.014 in the natural forests, and -0.033 and -0.011 in the planted forests (Fig.4, Table S2).