TY - JOUR
T1 - Greening and browning of the coastal areas in mainland China
T2 - Spatial heterogeneity, seasonal variation and its influential factors
AU - Meng, Ziqi
AU - Liu, Min
AU - Gao, Chanchan
AU - Zhang, Yang
AU - She, Qiannan
AU - Long, Lingbo
AU - Tu, Yue
AU - Yang, Yixuan
N1 - Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2020/3
Y1 - 2020/3
N2 - Reliable detection and attribution of vegetation variations is a prerequisite for the development of sustainable ecosystem management strategies. Vegetation in coastal areas plays an important role in stabilizing the surface against wind erosion and provides habitat for wildlife. In this study, we analyzed the spatial heterogeneity and seasonal variation trend of greening or browning in coastal areas of mainland China (CAMC) during 1982–2015. Socioeconomic and climate factors were included to screen the driving forces for vegetation change in CAMC at the pixel scale. Based on the Normalized Difference Vegetation Index (NDVI) dataset from Global Inventory Modeling and Mapping Study (GIMMS), Mann-Kendall (M-K) trend test indicated that 33.71% of the study area was significantly greening (restoration) and 8.88% showed significant browning (degradation) with great seasonal variation. Compared to annual NDVI greened with a rate of 0.0006/a (p < 0.01), the vegetation in the spring presented a high rate of 0.0021/a (p < 0.01). It could be an interesting result for the earlier onset of the growing season that may stimulate photosynthetic rate and the intensification of agricultural activities. However, the greening trend rate in summer was the minimum (0.0006/a (p < 0.01)), implying that NDVI dataset calculated by maximum value composite (MVC) method may be insufficient to reflect and may underestimate the vegetation growth. In addition, greening was dominant at lower and middle elevations as the accelerated nitrogen deposition driven in cultivated plants enhanced vegetation growth. However, browning mainly occurred at high elevation with the warming temperature that may exacerbate moisture stress to plants. Socioeconomic factors, such as economic production and human populations, were the most important factors for vegetation changes. In addition, the agricultural intensity and land use/cover change also had influence on vegetation variations. The contribution of climate conditions to the vegetation browning or greening in CAMC was limited.
AB - Reliable detection and attribution of vegetation variations is a prerequisite for the development of sustainable ecosystem management strategies. Vegetation in coastal areas plays an important role in stabilizing the surface against wind erosion and provides habitat for wildlife. In this study, we analyzed the spatial heterogeneity and seasonal variation trend of greening or browning in coastal areas of mainland China (CAMC) during 1982–2015. Socioeconomic and climate factors were included to screen the driving forces for vegetation change in CAMC at the pixel scale. Based on the Normalized Difference Vegetation Index (NDVI) dataset from Global Inventory Modeling and Mapping Study (GIMMS), Mann-Kendall (M-K) trend test indicated that 33.71% of the study area was significantly greening (restoration) and 8.88% showed significant browning (degradation) with great seasonal variation. Compared to annual NDVI greened with a rate of 0.0006/a (p < 0.01), the vegetation in the spring presented a high rate of 0.0021/a (p < 0.01). It could be an interesting result for the earlier onset of the growing season that may stimulate photosynthetic rate and the intensification of agricultural activities. However, the greening trend rate in summer was the minimum (0.0006/a (p < 0.01)), implying that NDVI dataset calculated by maximum value composite (MVC) method may be insufficient to reflect and may underestimate the vegetation growth. In addition, greening was dominant at lower and middle elevations as the accelerated nitrogen deposition driven in cultivated plants enhanced vegetation growth. However, browning mainly occurred at high elevation with the warming temperature that may exacerbate moisture stress to plants. Socioeconomic factors, such as economic production and human populations, were the most important factors for vegetation changes. In addition, the agricultural intensity and land use/cover change also had influence on vegetation variations. The contribution of climate conditions to the vegetation browning or greening in CAMC was limited.
KW - Browning
KW - Climate change
KW - Coastal areas of mainland China
KW - Greening
KW - Human activities
KW - NDVI
UR - https://www.scopus.com/pages/publications/85074567945
U2 - 10.1016/j.ecolind.2019.105888
DO - 10.1016/j.ecolind.2019.105888
M3 - 文章
AN - SCOPUS:85074567945
SN - 1470-160X
VL - 110
JO - Ecological Indicators
JF - Ecological Indicators
M1 - 105888
ER -
