Journal of Geographical Sciences ›› 2017, Vol. 27 ›› Issue (7): 801-816.doi: 10.1007/s11442-017-1407-3
• Orginal Article • Previous Articles Next Articles
Bin HE1(
), Aifang CHEN2, Weiguo JIANG3, Ziyue CHEN1
Received:2016-09-02
Accepted:2017-01-20
Online:2017-07-10
Published:2017-07-10
About author:Author: He Bin (1981-), Associate Professor, specialized in studies on impacts of climate extremes. E-mail:
Supported by:Bin HE, Aifang CHEN, Weiguo JIANG, Ziyue CHEN. The response of vegetation growth to shifts in trend of temperature in China[J].Journal of Geographical Sciences, 2017, 27(7): 801-816.
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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."
| [1] | Bhatt U S, Walker D A, Raynolds M Ket al., 2010. Circumpolar Arctic tundra vegetation change is linked to sea ice decline.Earth Interactions, 14(8): 1-20. |
| [2] |
Bhatt U S, Walker D A, Raynolds M Ket al., 2013. Recent declines in warming and vegetation greening trends over Pan-Arctic Tundra.Remote Sensing, 5(9): 4229-4254.
doi: 10.3390/rs5094229 |
| [3] |
Boykoff M T, 2014. Media discourse on the climate slowdown.Nature Climate Change, 4(3): 156-158.
doi: 10.1038/nclimate2156 |
| [4] |
Brown M T, Pinzón J E, Didan Ket al., 2006. Evaluation of the consistency of long-term NDVI time series derived from AVHRR, SPOT-vegetation, SeaWiFS, MODIS, and Landsat ETM+ sensors.IEEE Transactions on Geoscience and Remote Sensing, 44(7): 1787-1793.
doi: 10.1109/TGRS.2005.860205 |
| [5] |
Chen X Y, Tung K K, 2014. Varying planetary heat sink led to global-warming slowdown and acceleration.Science, 345(6199): 897-903.
doi: 10.1126/science.1254937 pmid: 25146282 |
| [6] |
Ding M J, Li L H, Zhang Y Let al., 2015. Start of vegetation growing season on the Tibetan Plateau inferred from multiple methods based on GIMMS and SPOT NDVI data.Journal of Geographical Sciences, 25(2): 131-148.
doi: 10.1007/s11442-015-1158-y |
| [7] |
Ding M J, Zhang Y L, Liu L Set al., 2007. The relationship between NDVI and precipitation on the Tibetan Plateau.Journal of Geographical Sciences, 17(3): 259-268.
doi: 10.1007/s11442-007-0259-7 |
| [8] |
Dong L, Zhang M, Wang S, et al., 2015. The freezing level height in the Qilian Mountains, northeast Tibetan Plateau based on reanalysis data and observations, 1979-2012.Quaternary International, 380: 60-67.
doi: 10.1016/j.quaint.2014.08.049 |
| [9] |
Fang J Y, Piao S L, He J Set al., 2004. Increasing terrestrial vegetation activity in China, 1982-1999. Science in China Series C: Life Sciences, 47(3): 229-240.
doi: 10.1007/BF03182768 pmid: 15524280 |
| [10] |
Ge Q S, Wang H J, Dai J H, 2015. Phenological response to climate change in China: A meta-analysis.Global Change Biology, 21(1): 265-274.
doi: 10.1111/gcb.12648 pmid: 24895088 |
| [11] |
Granger C W J, 1969. Investigating causal relations by econometric models and crossspectral methods.Econometrica, 37(3): 424-438.
doi: 10.2307/1912791 |
| [12] |
Holben B N, 1986. Characteristics of maximum-value composite images from temporal AVHRR data.International Journal of Remote Sensing, 7(11): 1417-1434.
doi: 10.1080/01431168608948945 |
| [13] |
Hou M T, Hu Y H, He Y T, 2014. Modifications in vegetation cover and surface albedo during rapid urbanization: A case study from South China.Environmental Earth Sciences, 72(5): 1659-1666.
doi: 10.1007/s12665-014-3070-7 |
| [14] |
Jiang B, Liang S L, Yuan W P, 2015. Observational evidence for impacts of vegetation change on local surface climate over northern China using the Granger causality test. Journal of Geophysical Research: Biogeosciences, 120(1): 1-12.
doi: 10.1002/2014JG002741 |
| [15] |
Jiang N, Zhu W Q, Zheng Z Tet al., 2013. A comparative analysis between GIMSS NDVIg and NDVI3g for monitoring vegetation activity change in the Northern Hemisphere during 1982-2008.Remote Sensing, 5(8): 4031-4044.
doi: 10.3390/rs5084031 |
| [16] |
Kaufmann R K, Zhou L, Myneni Ret al., 2003. The effect of vegetation on surface temperature: A statistical analysis of NDVI and climate data.Geophysical Research Letters, 30(22): 2147.
doi: 10.1029/2003GL018251 |
| [17] | Kendall M G, 1948. Rank Correlation Methods. London, UK: Charles Griffin, 108. |
| [18] |
Kosaka K, Xie S P, 2013. Recent global-warming hiatus tied to equatorial Pacific surface cooling.Nature, 501(7467): 403-407.
doi: 10.1038/nature12534 pmid: 23995690 |
| [19] | Lü Y H, Zhang L W, Feng X Met al., 2015. Recent ecological transitions in China: Greening, browning, and influential factors. Scientific Reports, 5. |
| [20] |
Li Q X, Yang S, Xu W Het al., 2015. China experiences the recent warming hiatus.Geophysical Research Letters, 42(3): 889-898.
doi: 10.1002/2014GL062773 |
| [21] |
Li S S, Yan J P, Liu X Yet al., 2013. Response of vegetation restoration to climate change and human activities in Shaanxi-Gansu-Ningxia Region.Journal of Geographical Sciences, 23(1): 98-112.
doi: 10.1007/s11442-013-0996-8 |
| [22] |
Liu X F, Zhang J S, Zhu X Fet al., 2014. Spatiotemporal changes in vegetation coverage and its driving factors in the Three-River Headwaters Region during 2000-2011.Journal of Geographical Sciences, 24(2): 288-302.
doi: 10.1007/s11442-014-1088-0 |
| [23] |
Loarie S R, Lobell D B, Asner G Pet al., 2011. Direct impacts on local climate of sugar-cane expansion in Brazil. Nature Climate Change, 1(2): 105-109.
doi: 10.1038/nclimate1067 |
| [24] |
Meehl G A, Teng H, Arblaster J M, 2014. Climate model simulations of the observed early-2000s hiatus of global warming.Nature Climate Change, 4(10): 898-902.
doi: 10.1038/nclimate2357 |
| [25] |
Mosedale J T, Stephenson B D, 2005. Granger causality of coupled climate processes ocean feedback on the North Atlantic Oscillation. Journal of Climate (Special Section), 19: 1182-1194.
doi: 10.1175/JCLI3653.1 |
| [26] |
Nemani R R, Keeling C D, Hashimoto Het al., 2003. Climate-driven increases in global terrestrial net primary production from 1982 to 1999.Science, 300(5625): 1560-1563.
doi: 10.1126/science.1082750 |
| [27] |
Peng S S, Chen A P, Xu Let al., 2011. Recent change of vegetation growth trend in China.Environmental Research Letters, 6(4): 044027.
doi: 10.1088/1748-9326/6/4/044027 |
| [28] |
Piao S L, Cui M D, Chen A Pet al., 2011. Altitude and temperature dependence of change in the spring vegetation green-up date from 1982 to 2006 in the Qinghai-Xizang Plateau.Agricultural and Forest Meteorology, 151(12): 1599-1608.
doi: 10.1016/j.agrformet.2011.06.016 |
| [29] |
Piao S L, Fang J Y, Liu H Yet al., 2005. NDVI-indicated decline in desertification in China in the past two decades. Geophysical Research Letters, 32: L06402. doi: 10.1029/2004GL021764.
doi: 10.1029/2004GL021764 |
| [30] |
Piao S L, Nan H J, Huntingford Cet al., 2014. Evidence for a weakening relationship between interannual temperature variability and northern vegetation activity.Nature Communications, 5: 5018. doi:10.1038/ncomms6018
doi: 10.1038/ncomms6018 pmid: 25318638 |
| [31] |
Qi L,Wang Y, 2012. Changes in the observed trends in extreme temperatures over China around 1990.Journal of Climate, 25(15): 5208-5222.
doi: 10.1175/JCLI-D-11-00437.1 |
| [32] | Pinzon J E, Tucker C J, 2010. GIMMS 3g NDVI set and global NDVI trends. Second Yamal Land-Cover Land-Use Change Workshop Arctic Centre (Rovaniemi, March). |
| [33] |
Sen P K, 1968. Estimates of the regression coefficient based on Kendall's tau.Journal of the American Statistical Association, 63(324): 1379-1389.
doi: 10.1080/01621459.1968.10480934 |
| [34] |
Shaver G R, Canadell J, Chapin F Set al., 2000. Global warming and terrestrial ecosystems.BioScience, 50(10): 871-882.
doi: 10.1016/j.msec.2003.09.147 |
| [35] |
Shen M, Piao S, Jeong S J, et al., 2015. Evaporative cooling over the Tibetan Plateau induced by vegetation growth.Proceedings of the National Academy of Sciences, 112(30): 9299-9304.
doi: 10.1073/pnas.1504418112 pmid: 26170316 |
| [36] |
Sillitto G, 1947. The distribution of Kendall's τ coefficient of rank correlation in rankings containing tie.Biometrika, 36-40.
doi: 10.2307/2332511 pmid: 20287820 |
| [37] |
Sun J Y, Wang X H, Chen A Pet al., 2011. NDVI indicated characteristics of vegetation cover change in China’s metropolises over the last three decades.Environmental Monitoring and Assessment, 179(1-4): 1-14.
doi: 10.1007/s10661-010-1715-x pmid: 20853187 |
| [38] |
Thompson D M, Cole J E, Shen G Tet al., 2014. Early twentieth-century warming linked to tropical Pacific wind strength.Nature Geoscience, 8(2): 117-121.
doi: 10.1038/NGEO2321 |
| [39] |
Tucker C, Pinzon J, Brown Met al., 2005. An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data.International Journal of Remote Sensing, 26(20): 4485-4498.
doi: 10.1080/01431160500168686 |
| [40] |
Ukkola A M, Prentice I C, Keenan T Fet al., 2015. Reduced streamflow in water-stressed climates consistent with CO2 effects on vegetation.Nature Climate Change, 6: 75-78. doi: 10.1038/nclimate2831.
doi: 10.1038/NCLIMATE2831 |
| [41] |
Wang L, Li C C, Ying Qet al., 2012. China’s urban expansion from 1990 to 2010 determined with satellite remote sensing.Chinese Science Bulletin, 57(22): 2802-2812.
doi: 10.1007/s11434-012-5235-7 |
| [42] |
Wang S W, Wen X Y, Luo Yet al., 2010. Does the global warming pause in the last decade: 1999-2008.Advances in Climate Change Research, 6: 95-99.
doi: 10.3724/SP.J.1248.2010.00049 |
| [43] |
Wang W, Anderson B T, Kaufmann R Ket al., 2004. The relation between the North Atlantic Oscillation and SSTs in the North Atlantic Basin.Journal of Climate, 17: 4752-4759.
doi: 10.1175/JCLI-3186.1 |
| [44] |
Wang X H, Piao S L, Ciais Pet al., 2014. A two-fold increase of carbon cycle sensitivity to tropical temperature variations.Nature, 506(7487): 212-215.
doi: 10.1038/nature12915 pmid: 24463514 |
| [45] |
Wu D H, Zhao X, Liang S Let al., 2015. Time-lag effects of global vegetation responses to climate change.Global Change Biology, 21(9): 3520-3531.
doi: 10.1111/gcb.12945 pmid: 25858027 |
| [46] |
Wu R, Kinter III J, Kirtman B P, 2005. Discrepancy of interdecadal changes in the Asian region among the NCEP-NCAR reanalysis, objective analyses, and observations.Journal of Climate, 18(15): 3048-3067.
doi: 10.1175/JCLI3465.1 |
| [47] |
Wu R, Yang S, Liu S, et al., 2010. Changes in the relationship between Northeast China summer temperature and ENSO. Journal of Geophysical Research: Atmospheres, 115(D21).
doi: 10.1029/2010JD014422 |
| [48] |
Wu Z, Dijkstra P, Koch G Wet al., 2012. Biogeochemical and ecological feedbacks in grassland responses to warming.Nature Climate Change, 2(6): 458-461.
doi: 10.1038/nclimate1486 |
| [49] |
Xiao J F, 2014. Satellite evidence for significant biophysical consequences of the “Grain for Green” Program on the Loess Plateau in China. Journal of Geophysical Research: Biogeosciences, 119(12): 2261-2275.
doi: 10.1002/2014JG002820 |
| [50] |
Xu X T, Piao S L, Wang X Het al., 2012. Spatio-temporal patterns of the area experiencing negative vegetation growth anomalies in China over the last three decades.Environmental Research Letters, 7(3): 035701.
doi: 10.1088/1748-9326/7/3/035701 |
| [51] |
Yin G, Hu Z Y, Chen Xet al., 2016. Vegetation dynamics and its response to climate change in Central Asia.Journal of Arid Land, 8(3): 375-388.
doi: 10.1007/s40333-016-0043-6 |
| [52] |
Zeng F W, Collatz G J, Pinzon J Eet al., 2013. Evaluating and quantifying the climate-driven interannual variability in Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) at global scales.Remote Sensing, 5(8): 3918-3950.
doi: 10.3390/rs5083918 |
| [53] |
Zhang L, Xiao J F, Li Jet al., 2012. The 2010 spring drought reduced primary productivity in southwestern China.Environmental Research Letters, 7(4): 045706.
doi: 10.1088/1748-9326/7/4/045706 |
| [54] |
Zhang X Y, Hu Y F, Zhuang D Fet al., 2009. NDVI spatial pattern and its differentiation on the Mongolian Plateau.Journal of Geographical Sciences, 19(4): 403-415.
doi: 10.1007/s11442-009-0403-7 |
| [55] |
Zhang X Z, Dai J H, Ge Q S, 2013. Variation in vegetation greenness in spring across eastern China during 1982-2006. Journal of Geographical Sciences, 23(1): 45-56.
doi: 10.1007/s11442-013-0992-z |
| [56] |
Zhao X, Tan K, Zhao Set al., 2011. Changing climate affects vegetation growth in the arid region of the northwestern China.Journal of Arid Environments, 75(10): 946-952.
doi: 10.1016/j.jaridenv.2011.05.007 |
| [57] |
Zhou L M, Tucker C J, Kaufmann R Ket al., 2001. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. Journal of Geophysical Research: Atmospheres, 106(D17): 20069-20083.
doi: 10.1029/2000JD000115 |
| [58] |
Zhou W, Gang C C, Chen Y Zet al., 2014. Grassland coverage inter-annual variation and its coupling relation with hydrothermal factors in China during 1982-2010.Journal of Geographical Sciences, 24(4): 593-611.
doi: 10.1007/s11442-014-1108-0 |
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