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Sciences in Cold and Arid Regions ›› 2018, Vol. 10 ›› Issue (6): 482-492.doi: 10.3724/SP.J.1226.2018.00482

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Contrasting vegetation changes in dry and humid regions of the Tibetan Plateau over recent decades

RuiQing Li1,2,YanHong Gao1,*(),DeLiang Chen3,4,YongXin Zhang5,SuoSuo Li1   

  1. 1 Key Laboratory of Land-surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
    2 Inner Mongolia Autonomous Regional Meteorological Observatory, Hohhot, Inner Mongolia 010051, China
    3 Regional Climate Group, Department of Earth Sciences, University of Gothenburg, Gothenburg, Sweden
    4 Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
    5 National Center for Atmospheric Research, Boulder, Colorado, U.S.A.
  • Received:2017-12-25 Accepted:2018-10-08 Online:2018-12-01 Published:2018-12-29
  • Contact: YanHong Gao E-mail:gaoyh@lzb.ac.cn
  • Supported by:
    We thank the Center for Global Change Data Processing and Analysis of Beijing Normal University for the GLASS LAI dataset. This work is jointly supported by National Natural Science Foundation of China (91537105, 91537211, 41322033), the Opening Research Foundation of Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, and the Chinese Academy of Sciences (LPCC201504). D. Chen is supported by Swedish VR, STINT, BECC and MERGE, as well as SNIC through S-CMIP.

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Abstract:

An overall greening over the Tibetan Plateau (TP) in recent decades has been established through analyses of remotely sensed Normalized Difference Vegetation Index (NDVI), though the regional pattern of the changes and associated drivers remain to be explored. This study used a satellite Leaf Area Index (LAI) dataset (the GLASS LAI dataset) and examined vegetation changes in humid and arid regions of the TP during 1982–2012. Based on distributions of the major vegetation types, the TP was divided roughly into a humid southeastern region dominated by meadow and a dry northwestern region covered mainly by steppe. It was found that the dividing line between the two regions corresponded well with the lines of mean annual precipitation of 400 mm and the mean LAI of 0.3. LAI=0.3 was subsequently used as a threshold for investigating vegetation type changes at the interanual and decadal time scales: if LAI increased from less than 0.3 to greater than 0.3 from one time period to the next, it was regarded as a change from steppe to meadow, and vice versa. The analysis shows that changes in vegetation types occurred primarily around the dividing line of the two regions, with clear growth (reduction) of the area covered by meadow (steppe), in consistency with the findings from using another independent satellite product. Surface air temperature and precipitation (diurnal temperature range) appeared to contribute positively (negatively) to this change though climate variables displayed varying correlation with LAI for different time periods and different regions.

Key words: Tibetan Plateau, vegetation change, leaf area index, climate change

Table 1

Percentage of vegetation covers (coincidence rate) as a function of the GS LAI intervals"

LAI Steppe Meadow Forest Shrub-land Crop
0.0–0.1 86.00 11.88 0.09 1.47 0.57
0.1–0.2 71.45 24.96 0.22 2.99 0.39
0.2–0.3 51.62 42.67 0.35 4.77 0.59
0.3–0.4 36.73 50.99 1.26 10.38 0.65
0.4–0.5 24.10 57.77 2.79 14.27 1.08
0.5–0.6 17.79 60.98 3.39 16.38 1.46
0.6–0.7 16.45 62.93 3.72 15.77 1.13
0.7–0.8 10.94 65.32 4.96 18.34 0.44
0.8–0.9 9.13 66.58 5.15 18.52 0.61
0.9–1.0 7.51 64.01 6.92 21.25 0.32
1.0–1.1 5.44 62.51 9.37 22.24 0.44
1.1–1.2 6.31 55.38 11.50 26.38 0.44
1.2–1.3 5.84 47.61 15.75 30.24 0.56
1.3–1.4 4.11 46.12 19.62 28.73 1.42
1.4–1.5 3.29 40.78 19.25 35.80 0.88
1.5–1.6 3.14 41.39 19.30 35.12 1.05
1.6–1.7 2.74 37.61 22.11 36.80 0.74
1.7–1.8 2.44 37.36 22.56 37.14 0.50
1.8–1.9 1.67 40.33 20.42 36.70 0.87
1.9–2.0 1.22 38.32 23.13 36.41 0.92
2.0–2.1 1.90 38.81 27.54 30.79 0.95
2.1–2.2 1.60 38.87 26.31 31.45 1.77
2.2–2.3 1.39 38.56 28.94 29.64 1.47
2.3–2.4 1.06 46.26 26.47 25.42 0.79
2.4–2.5 1.16 35.65 36.08 25.63 1.48
2.5–2.6 2.27 23.82 47.16 24.96 1.78
2.6–2.7 0.25 10.43 60.05 27.23 2.04
2.7–2.8 0.00 7.69 62.39 27.07 2.85
2.8–2.9 0.00 5.90 60.87 30.43 2.80
2.9–3.0 0.00 3.90 58.16 34.75 3.19
3.0–7.0 0.00 1.86 79.45 11.79 6.89

Table 2

Percentage of areas covered by each vegetation type in GS over ROI1 and ROI2 (Unit: %)"

LAI-VEG Steppe Meadow Forest Shrub-land Crop Sum
ROI1 33.70 10.01 0.08 1.18 0.23 45.21
ROI2 4.72 25.26 10.83 13.26 0.71 54.79
SUM 38.43 35.28 10.91 14.44 0.94 100.00

Figure 1

Spatial distributions of (a) annual mean precipitation (mm) during 1982–2012 and the 400 mm dividing line, (b) major vegetation cover types and the dividing line between steppe- and meadow-dominated regions, (c) GS LAI during 1982–2012 and the LAI=0.3 dividing line, and (d) the dividing lines from (a) (blue), (b) (red) and (c) (green). The vegetation cover types map was released in 2001 as an average since 1950"

Figure 2

Yearly locations of the dividing lines determined by (a) annual precipitation of 400 mm and (b) LAI of 0.3. Time series and linear trends of the areal coverage percentage of the humid region ROI2 in relation to the entire TP as determined by LAI (red lines) and precipitation (Precip, blue lines) are presented in (c). The time period is 1982–2012 and for the growing season. In (a) and (b), the yellow lines represent the earlier years while the green lines represent more recent years. In (c), coefficient of determination R2, statistical significance p-value, regression coefficient and correlation are indicated "

Table 3

Temporal correlation of annual LAI with annual mean surface air temperature (Tmean), precipitation (Precip), and diurnal temperature ranger (DTR) in the three decades (1982–2012), the first two decades (1982–2001) and the last two decades (1993–2012). Correlation coefficients that are statistically significant at the 0.001 level based on the two-tailed t-test are marked with a"

CORR Tmean Precip DTR
1982–2012 0.59a 0.62a ?0.53a
1982–2001 0.43 0.40 ?0.21
1993–2012 0.23 0.65a ?0.69a

Figure 3

Decadal locations of the dividing lines determined by (a) annual precipitation of 400 mm and (b) LAI of 0.3. Decadal means of Tmean, Precip, DTR and LAI over the intersection of ROI1 and ROI2 are presented in (c). The time period in 1982–2012 and the three decades are 1982–1991, 1992–2001, 2002–2012. In (a) and (b), the light gray, the light black, and the dark black lines represent the first, second, and third decade, respectively"

Table 4

Means before and after 1997/1998 (i.e., 1982–1997 and 1998–2012) of GS LAI and three climate variables over the two subregions and the entire TP (Precip: precipitation; Tmean: mean surface air temperature; DTR: diurnal temperature range. Unit for Precip is mm, unit for Tmean and DTR is °C) "

Mean Arid sub-region Humid sub-region Whole TP
before after before after before After
LAI 0.13 0.18 1.38 1.51 0.76 0.85
Precip 31.6 38.1 92.6 94.3 62.1 66.2
Tmean 3.4 4.2 6.3 7.0 4.8 5.6
DTR 13.0 12.4 11.8 11.6 12.4 12.0

Figure 4

Time series of the yearly areas of arid and humid regions during 1982–2012 (a, c) and spatial distributions of the shift between steppe and meadow in the last decade (2003–2012) compared to the first decade (1982–1991) for GLASS LAI (a, b) and GeoLand2 LAI (c, d). Coefficient of determination R2, statistical significance p-value, and regression coefficient for the arid region are indicated in (a) and (c). Green shadings in (b) and (d) denote the locations where steppe was replaced by meadow and red shadings denote the locations where meadow was replaced by steppe "

Table 5

Same as Table 4 except for the linear trends of the variables for 1982–1997 and 1998–2012 (Unit for Precip is mm/10a, unit for Tmean and DTR is °C/10a)"

Trend Arid sub-region Humid sub-region Whole TP
before after before after before after
LAI 0.01 0.01 0.06 ?0.02 0.04 ?0.01
Precip 0.9 7.4 ?2.6 ?0.8 ?0.9 3.3
Tmean 0.5 0.1 0.2 0.5 0.3 0.3
DTR 0.02 ?0.50 ?0.13 0.05 ?0.06 ?0.23
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