Abstract

Understanding how the dynamics of vegetation growth respond to climate change at different temporal and spatial scales is critical to projecting future ecosystem dynamics and the adaptation of ecosystems to global change. In this study, we investigated vegetated growth dynamics (annual productivity, seasonality and the minimum amount of vegetated cover) in China and their relations with climatic factors during 1982–2011, using the updated Global Inventory Modeling and Mapping Studies (GIMMS) third generation global satellite Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) dataset and climate data acquired from the National Centers for Environmental Prediction (NCEP). Major findings are as follows: (1) annual mean NDVI over China significantly increased by about 0.0006 per year from 1982 to 2011; (2) of the vegetated area in China, over 33% experienced a significant positive trend in vegetation growth, mostly located in central and southern China; about 21% experienced a significant positive trend in growth seasonality, most of which occurred in northern China (>35°N); (3) changes in vegetation growth dynamics were significantly correlated with air temperature and precipitation (p < 0.001) at a region scale; (4) at the country scale, changes in NDVI was significantly and positively correlated with annual air temperature (r = 0.52, p < 0.01) and not associated with annual precipitation (p > 0.1); (5) of the vegetated area, about 24% showed significant correlations between annual mean NDVI and air temperature (93% positive and remainder negative), and 12% showed significant correlations of annual mean NDVI with annual precipitation (65% positive and 35% negative). The spatiotemporal variations in vegetation growth dynamics were controlled primarily by temperature and secondly by precipitation. Vegetation growth was also affected by human activities; and (6) monthly NDVI was significantly correlated with the preceding month’s temperature and precipitation in western, central and northern China. The effects of a climate lag of more than two months in southern China may be caused mainly by the abundance of precipitation. These findings suggest that continuing efforts to monitor vegetation changes (in situ and satellite observations) over time and at broad scales are greatly needed, and are critical for the management of ecosystems and adapting to global climatic changes. It is likewise difficult to predict well future vegetation growth without linking these observations to mechanistic terrestrial ecosystem processes models that integrate all the satellite and in situ observations.

Highlights

  • As part of the biosphere, vegetation plays an important role in regulating the global carbon cycle [1,2,3,4].Vegetation helps maintain climatic stability in many ways, including photosynthesis, evapotranspiration, modifying surface albedo and roughness [5,6]

  • The normalized difference vegetation index (NDVI) exploits the contrast in reflectance between the infrared and red portions of the electromagnetic spectrum and is well correlated to leaf area index (LAI), chlorophyll abundance, absorption of photosynthetically active radiation and gross primary production (GPP)

  • We explored the relationship between changes in NDVI and the climatic factors to gain further insight into the contributions of climate to changes in vegetation

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Summary

Introduction

As part of the biosphere, vegetation plays an important role in regulating the global carbon cycle [1,2,3,4].Vegetation helps maintain climatic stability in many ways, including photosynthesis, evapotranspiration, modifying surface albedo and roughness [5,6]. There has been increasing realization of the importance of vegetation and its sensitivity to climate change [7,8,9,10]. Variations in vegetation and the relationship and interaction of vegetation with climate have become important issues in global change research [11,12,13,14,15,16,17]. Field surveys and remote sensing technology are commonly and widely used approaches to monitoring changes in vegetation dynamics. Field surveys can generate accurate information related to vegetation dynamics, but they are time-consuming and spatially limited [18,19]. In areas of high vegetation cover, measurements of this index will increase without limit. Tucker [22] proposed a normalized difference vegetation index (NDVI) that varies between −1 and 1. The NDVI exploits the contrast in reflectance between the infrared and red portions of the electromagnetic spectrum and is well correlated to leaf area index (LAI), chlorophyll abundance, absorption of photosynthetically active radiation (fPAR) and gross primary production (GPP)

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