Vegetation dynamics and its response to driving factors in typical karst regions, Guizhou Province, China

doi:10.1007/s11707-020-0842-0

Front. Earth Sci.

2021, Vol. 15

Issue (1) : 167-183 https://doi.org/10.1007/s11707-020-0842-0

RESEARCH ARTICLE

Vegetation dynamics and its response to driving factors in typical karst regions, Guizhou Province, China

Xiaocha WEI¹, Qiuwen ZHOU¹(

), Ya LUO¹, Mingyong CAI², Xu ZHOU¹, Weihong YAN¹, Dawei PENG¹, Ji ZHANG¹

¹. School of Geography and Environmental Science, Guizhou Normal University, Guiyang 550025, China
². Satellite Environment Center of MEP, Beijing 100094, China

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Abstract

Analyzing the vegetation dynamics and its response to driving factors provides a vital reference for understanding regional ecological processes and ecosystem services. However, this issue has been poorly understood in karst areas. Taking Guizhou Province as a case study, based on the Normalized-Difference Vegetation Index of the Global Inventory Modeling and Mapping Studies and on meteorological data sets during 1982–2015, we evaluated vegetation dynamics and its response to climatic factors and human activities. We used several methods: the Mann–Kendall test, rescaled range analysis, partial correlation analysis, and residual analysis. The results are as follows: 1) the mean annual Normalized-Difference Vegetation Index was 0.46 and exhibited a significant increasing trend with a variation rate of 0.01/10a during 1982–2015 in Guizhou Province. The vegetation cover showed was spatially heterogeneous: High vegetation cover was distributed mainly in the center and western margin of the study area, while the other parts of the study area mainly distributed with low vegetation cover, although the vegetation cover was higher in the non-karst areas than in the karst areas; 2) in general, the climate was getting warmer and drier in Guizhou Province during 1982–2015. Vegetation cover was positively correlated with temperature and negatively correlated with precipitation. Compared to precipitation, temperature was the dominant climatic factor impacting vegetation dynamics; 3) large-scale ecological restoration projects have obviously increased vegetation cover in Guizhou Province in recent years. The contribution of human activities to vegetation changes was 76%, while the contribution of climatic factors was 24%. In summary, compared to natural forces such as climatic factors and geographic parameters, human activities were the main factor driving the vegetation dynamics in Guizhou Province.

Keywords vegetation dynamics climate change human activities karst area

Corresponding Author(s): Qiuwen ZHOU

Online First Date: 29 March 2021 Issue Date: 19 April 2021

Cite this article:

Xiaocha WEI,Qiuwen ZHOU,Ya LUO, et al. Vegetation dynamics and its response to driving factors in typical karst regions, Guizhou Province, China[J]. Front. Earth Sci., 2021, 15(1): 167-183.

URL:

https://academic.hep.com.cn/fesci/EN/10.1007/s11707-020-0842-0
https://academic.hep.com.cn/fesci/EN/Y2021/V15/I1/167

Fig.1 Study-area location, altitudes, landform regions, and weather-station distribution.

Fig.2 Temporal variation of annual NDVI for entire study area (a) and for each landform region (b) in Guizhou Province during 1982–2015. (KB—Karst Basin; KG—Karst Gorge; KP—Karst Plateau; KT—Karst Trough Valley; NDVI—Normalized-Difference Vegetation Index; NK—Non-Karst Area; PCD—Peak Cluster Depression)

Fig.3 Monthly Normalized-Difference Vegetation Index (NDVI) for Guizhou Province during 1982–2015.

Fig.4 Spatial distributions of vegetation cover in Guizhou Province and statistics of vegetation cover in each landform region. (KB—Karst Basin; KG—Karst Gorge; KP—Karst Plateau; KT—Karst Trough Valley; NDVI—Normalized-Difference Vegetation Index; NK—Non-Karst Area; PCD—Peak Cluster Depression)

Fig.5 Variation trends for different landform regions in Guizhou Province: (a) 1982–2001 vegetation cover and (b) area ratio; (c) 2002–2015 vegetation cover and (d) area ratio. Definitions of trends: severely degraded, slope<–0.0015; moderately degraded, –0.0015<slope<–0.0005; slightly degraded, –0.0005<slope<0.001; stable, 0.001<slope<0.002; slightly improved, 0.002<slope<0.003; moderately improved, 0.003<slope<0.004; highly improved, slope>0.004. (KB—Karst Basin; KG—Karst Gorge; KP—Karst Plateau; KT—Karst Trough Valley; NK—Non-Karst Area; PCD—Peak Cluster Depression)

Fig.6 (a) Mann–Kendall test of Normalized-Difference Vegetation Index for Guizhou Province during 1982–2015. (b) Expected future vegetation-variation trend (according to Hurst index) for each landform region in Guizhou Province. (KB—Karst Basin; KG—Karst Gorge; KP—Karst Plateau; KT—Karst Trough Valley; NK—Non-Karst Area; PCD—Peak Cluster Depression)

Fig.7 Mean annual temperatures (a) for entire study area and (b) for each landform region in Guizhou Province, 1982–2015. (KB—Karst Basin; KG, Karst Gorge; KP, Karst Plateau; KT, Karst Trough Valley; NK, Non-Karst Area; PCD, Peak Cluster Depression)

Fig.8 Mean annual precipitation (a) for Guizhou Province and (b) for each landform region, 1982–2015. (KB—Karst Basin; KG—Karst Gorge; KP—Karst Plateau; KT—Karst Trough Valley; NK—Non-Karst Area; PCD—Peak Cluster Depression)

Fig.9 Mean annual (a) temperature (°C) and (b) precipitation (mm) for Guizhou Province, 1982–2015. (KB—Karst Basin; KG—Karst Gorge; KP—Karst Plateau; KT—Karst Trough Valley; NK—Non-Karst Area; PCD—Peak Cluster Depression)

Fig.10 Change in (a) mean annual temperature and (b) precipitation, Guizhou Province, 1982–2015.

Fig.11 Monthly temperatures (a) and precipitation (b), Guizhou Province, 1982–2015.

Tab.1 Pearson correlation coefficients between NDVI and temperature and between NDVI and precipitation.

Fig.12 Correlation coefficients between monthly (a) NDVI and temperature and (b) NDVI and precipitation at each meteorological station in Guizhou Province, 1982–2015. (KB—Karst Basin; KG—Karst Gorge; KP—Karst Plateau; KT—Karst Trough Valley; NDVI—Normalized-Difference Vegetation Index; NK—Non-Karst Area; PCD—Peak Cluster Depression)

Tab.2 Multiple correlation regressions of Normalized-Difference Vegetation Index (NDVI) and climatic factors.

Fig.13 Spatial distribution of (a) predicted NDVI and (b) residual NDVI; average observed, predicted, and (c) residual NDVI; and contribution of human activities and climatic factors to vegetation dynamics (d) for entire study area and each landform region in Guizhou Province during 2002–2015. (Ch—contribution of human activities; Cc—contribution of climatic factors; Cvd—contribution to vegetation dynamics; KB—Karst Basin; KG—Karst Gorge; KP—Karst Plateau; KT—Karst Trough Valley; NDVI—Normalized-Difference Vegetation Index; NK—Non-Karst Area; PCD—Peak Cluster Depression)

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