Journal of Geographical Sciences >
The response of vegetation growth to shifts in trend of temperature in China
Author: He Bin (1981-), Associate Professor, specialized in studies on impacts of climate extremes. E-mail: hebin@bnu.edu.cn
Received date: 2016-09-02
Accepted date: 2017-01-20
Online published: 2017-07-10
Supported by
National Natural Science Foundation of China, No.41671083, No.41301076
Copyright
Though many studies have focused on the causes of shifts in trend of temperature, whether the response of vegetation growth to temperature has changed is still not very clear. In this study, we analyzed the spatial features of the trend changes of temperature during the growing season and the response of vegetation growth in China based on observed climatic data and the normalized difference vegetation index (NDVI) from 1984 to 2011. An obvious warming to cooling shift during growing season from the period 1984-1997 to the period 1998-2011 was identified in the northern and northeastern regions of China, whereas a totally converse shift was observed in the southern and western regions, suggesting large spatial heterogeneity of changes of the trend of growing season temperature throughout China. China as a whole, a significant positive relationship between vegetation growth and temperature during 1984 to 1997 has been greatly weakened during 1998-2011. This change of response of vegetation growth to temperature has also been confirmed by Granger causality test. On regional scales, obvious shifts in relationship between vegetation growth and temperature were identified in temperate desert region and rainforest region. Furthermore, by comprehensively analyzing of the relationship between NDVI and climate variables, an overall reduction of impacts of climate factors on vegetation growth was identified over China during recent years, indicating enhanced influences from human associated activities.
Key words: vegetation growth; temperature; shift; response; NDVI; China
HE Bin , CHEN Aifang , JIANG Weiguo , CHEN Ziyue . The response of vegetation growth to shifts in trend of temperature in China[J]. Journal of Geographical Sciences, 2017 , 27(7) : 801 -816 . DOI: 10.1007/s11442-017-1407-3
Figure 1 Spatial distribution of studied sub-regions and selected climate stations across China: (1) coniferous forest region, (2) broadleaf-coniferous mixed forest region, (3) deciduous broadleaf forest region, (4) evergreen broadleaf forest region, (5) rainforest region, (6) temperate grassland region, (7) temperate desert region, and (8) Qinghai-Tibet Plateau alpine meadow region |
Figure 2 Changes in growing season annual surface air temperature during 1984-1997 (a) and 1998-2011(b). Red triangles indicate warming trends, and blue ones indicate cooling trends. |
Figure 3 Linear tends of growing season NDVI (a) and corresponding temperature during 1984 to 2011(b); variation of correlation coefficient between growing season NDVI and responding temperature during 1984 to 2011 with 14-year moving windows (c). Correlations with p-values<0.1, <0.05 and <0.01 are marked with asterisks. |
Figure 4 Spatial patterns of correlation coefficient between growing season NDVI and corresponding temperature from 1984 to 1997 (a) and 1998 to 2011 (b). Red triangles indicate positive relationships, and blue ones indicate negative relationships. |
Figure 5 Inter-annual variations of growing season NDVI (green line), mean temperature (red line) and mean precipitation (blue line) in eight sub-regions over the past 28 years. Trend lines denote linear time trends. “R1N-T”, “R1N-P”, “R2N-T” and “R2N-P” are the correlation coefficients between NDVI and temperature and NDVI and precipitation in 1984-1997 and 1998-2011, respectively. |
Figure 6 Variations of the relationship between NDVI and temperature with 14-year moving windows in eight sub-regions over the past 28 years. Correlations between NDVI and temperature are spatially heterogeneous. Correlations with p<0.1, <0.05 and <0.01 are marked with asterisks. |
Figure 7 Granger causality tests between growing season NDVI and responding temperature during periods of 1984-1997 and 1998-2011 on national (a) and regional scale (b-c). (a1) GS-T granger cause GS-NDVI and (a2) vice versa; (b1) GS-T granger cause GS-NDVI in 1984-1997 and (b2) vice versa; (c1) GS-T granger cause GS-NDVI in 1998-2011 and (c2) vice versa. Color-circles indicate the p-value below 0.1 which means a significant causal link between variables, and red color means a positive correlation between GS-NDVI and GS-T, while the blue one indicates a negative correlation. |
Figure 8 Granger causality tests between growing season NDVI and responding precipitation (a), radiation (b) and CO2 concentration (c) during the periods 1984-1997 and 1998-2011 on national scale. (a1) GS-P granger cause GS-NDVI and (a2) vice versa; (b1) GS-R granger cause GS-NDVI and (b2) vice versa; and (c1) GS-CO2 granger cause GS-NDVI and (c2) vice versa. Color-circles indicated the p-value below 0.1, and red color means a positive correlation between GS-NDVI and GS-climate variables, while the blue one indicates a negative correlation. |
Table 1 Results of Granger causality tests from GS-climate variables to GS-NDVI for whole China and eight vegetation type regions |
Regions | Periods | |
---|---|---|
1984-1997 | 1998-2011 | |
China as a whole | T(+), R(+) | T(-), P(-) |
R1 (Coniferous forest region) | P(-), C(+) | P(-) |
R2 (Broadleaf-coniferous mixed forest region) | ||
R3 (Deciduous broadleaf forest region) | R(+) | |
R4 (Evergreen broadleaf forest region) | ||
R5 (Rainforest region) | T(+), C(-) | T(-) |
R6 (Temperate grasslands region) | P(+), C(+) | |
R7 (Temperate desert region) | T(-) | |
R8 (Qinghai-Tibet Plateau alpine meadow region) | C(-) |
Figure S1 Variation of correlation coefficient between growing season NDVI and responding temperature during 1984 to 2011 with 10-year moving windows (a) 18-year moving windows (b). Correlations with p-values<0.1, <0.05 and <0.01 are marked with asterisks. |
Figure S2 Variation of the relationship between NDVI and temperature with 10-year moving windows in eight sub-regions over the past 28 years. The correlations between NDVI and temperature are spatially heterogeneous. Correlations with p-values<0.1, <0.05 and <0.01 are marked with asterisks. |
Figure S3 Variation of the relationship between NDVI and temperature with 18-year moving windows in eight sub-regions over the past 28 years. The correlations between NDVI and temperature are spatially heterogeneous. Correlations with p-values<0.1, <0.05 and <0.01 are marked with asterisks. |
Figure S4 Variation of the relationship between NDVI and precipitation with 14-year moving windows in eight sub-regions over the past 28 years. The correlations between NDVI and precipitation are spatially heterogeneous. Correlations with p-values<0.1, <0.05 and <0.01 are marked with asterisks. |
Figure S5 Granger causality tests between growing season NDVI and responding precipitation (a), radiation (b) and CO2 concentration (c) in 1984-1997 on regional scale. (a1) GS-P granger cause GS-NDVI and (a2) vice versa; (b1) GS-R granger cause GS-NDVI and (b2) vice versa; and (c1) GS-CO2 granger cause GS-NDVI and (c2) vice versa. Color-circles indicated the p-value below 0.1, and red color means a positive correlation between GS-NDVI and GS- climate variables, while the blue one indicates a negative correlation. |
Figure S6 Granger causality tests between growing season NDVI and responding precipitation (a), radiation (b) and CO2 concentration (c) in 1998-2011 on regional scale. (a1) GS-P granger cause GS-NDVI and (a2) vice versa; (b1) GS-R granger cause GS-NDVI and (b2) vice versa; and (c1) GS-CO2 granger cause GS-NDVI and (c2) vice versa. Color-circles indicated the p-value below 0.1, and red color means a positive correlation between GS-NDVI and GS- climate variables, while the blue one indicates a negative correlation. |
The authors have declared that no competing interests exist.
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