Sciences in Cold and Arid Regions ›› 2019, Vol. 11 ›› Issue (3): 226-238.doi: 10.3724/SP.J.1226.2019.00226.

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Stem radial growth indicate the options of species, topography and stand management for artificial forests in the western Loess Plateau, China

ShengChun Xiao1(),XiaoMei Peng1,QuanYan Tian1,2,Gong Zhu3   

  1. 1. Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou, Gansu 730000, China
    2. University of the Chinese Academy of Sciences, Beijing 100049, China
    3. Landscape Engineering Department of South-North Mountain of Lanzhou City, Lanzhou, Gansu 730000, China
  • Received:2018-12-07 Revised:2019-04-10 Online:2019-06-30 Published:2019-07-01
  • Contact: ShengChun Xiao
  • Supported by:
    Our research was funded by the National Natural Science Foundation of China(Grant No. 41471082)


An understanding of the differences in artificial forest between tree species, slope aspects, and management options in arid environments is fundamentally important for efficient management of these artificial systems; however, few studies have quantified the spatial and temporal differences in stem radial growth of trees in the arid western Loess Plateau of China. Using dendrochronology, we assessed the growth of three woody species (the native shrub Reaumuria soongorica, the exotic shrub Tamarix ramosissima and tree Platycladus orientalis) by measuring the annual stem radial increment. We also describe the long-term growth trends and responses to climatic factors on slopes with different aspects during periods with and without irrigation. We found that precipitation during the main growing season was significantly positively correlated with ring growth for all three species and both slope aspects. In addition, supplemental water (e.g., irrigation, rainwater harvesting) greatly relieved drought stress and promoted radial growth. Our results suggest that as the main afforestation species in the Loess Plateau used for soil and water conservation, P. orientalis is more suitable than T. ramosissima under rain-fed conditions. However, a landscape that combined a tree (P. orientalis) with a shrub (R. soongorica) and grassland appears likely to represent the best means of ecological restoration in the arid western Loess Plateau.

Key words: dendroecology, tree-ring, artificial forest, Loess Plateau

Figure 1

Location of the study area and sampling sites on the western Loess Plateau, China"

Table 1

Characteristics of the sampling sites"

Sampling site (code) Plant species Slope aspect Location


(m a.s.l.)

Sample types Management options
G (GNP) Platycladus orientalis N



1,726 Disc at the soil surface Broadcast irrigation before 1988; only rain-fed thereafter
G (GNT) Tamarix ramosissima N
L (L0R) Reaumuria soongorica Flat area on hill top



1,836 Rain-fed, natural vegetation
X (X0P) Platycladus orientalis



1,673 Core at 40 cm above the ground Furrow irrigation

Figure 2

Mean stem radial growth curves for the three woody species at the sampling sites. A: P. orientalis on GNP and GSP site; B: T. ramosissima on GNT and GST site; C: P. orientalis on X0P site and R. soongorica on L0P site"

Figure 3

Average ring width of (a) the three species at the six sampling sites in GNP, GSP, GNT, GST, X0P and L0P, and (b) of T. ramosissima during the periods with (GNTi and GSTi) and without irrigation (GNTn and GSTn) at the GNT and GST sites. Values are mean ± SD. Bars for a given parameter labeled with different letters differ significantly between the species, sampling sites, slope aspects and management options (P <0.05)"

Figure 4

Ring-width standard chronologies and the sample size (n + sample code) for the six sampling sites. (a): GNP (Gray- and dotted curve) and GSP (Black- and dotted curve); (b): GNT (Gray- and dotted curve) and GST (Black- and dotted curve); (c): X0P (Gray- and dotted curve) and L0R (Black- and dotted curve). SSS, subsample signal strength (the vertical bar, the same color as the same curve in a, b and c)"

Table 2

Statistical characteristics of the six standardized chronologies at the sampling sites"

Item Sampling sites
Ring width (mean±SD) 0.57±0.18 0.58±0.22 1.08±0.50 0.80±0.41 0.34±0.09 2.28±0.84
No. of radii /stems or cores 41/22 33/18 29/23 23/23 54/29 25/25
Chronology period (No. of series and starting year with SSS >0.85)













Mean serial correlation 0.182 0.697 0.592 0.419 0.145 0.372
PC1 (% of variation) 38.6 54.1 43.5 53.2 42.2 41.2
Mean Sensitivity 0.254 0.249 0.309 0.335 0.283 0.322
Common period 1989-2003 1987-2013 1984-2011 1986-2011 1998-2013 1975-2013
EPS 0.943 0.969 0.922 0.950 0.970 0.919
R bar 0.322 0.503 0.360 0.490 0.392 0.352

Table 3

Correlations (Pearson's r) between the chronologies at the six sampling sites"

Item Sampling sites
GNT r 0.604**
P (2-tailed) <0.001
N 31
GSP r 0.755** 0.427*
P (2-tailed) 0.000 0.015
N 31 32
GST r 0.595** 0.754** 0.630**
P (2-tailed) 0.000 0.000 0.000
N 31 35 32
L0R r -0.065 0.174 0.038 0.068
P (2-tailed) 0.747 0.386 0.851 0.735
N 27 27 27 27
X0P r 0.243 -0.098 0.384* 0.213 -0.177
P (2-tailed) 0.188 0.516 0.030 0.219 0.376
N 31 46 32 35 27

Figure 5

Correlation coefficients (Pearson's r) between the ring-width chronologies at the six sampling sites and precipitation in various months and periods (MJ, May to June; MJJ, May, June, and July; MJJA, May, June, July, and August). Significance: * and **: P <0.05 and P <0.01, respectively. (a): GNP; (b): GNT; (c): GSP; (d): GST; (e): X0P; (f): L0P (Site code + i, with irrigation; site code + n, without irrigation; n = sample size; site code + i1 or i2: with furrow irrigation before or after the year of 1988)"

Figure 6

Correlation coefficients (Pearson's r) between mean monthly air temperature from April to October of the current year"

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