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.

February–May temperature strongly affects ecological processes and socio-economics in central China, yet its long-term variability has not been thoroughly assessed due to the shortness of instrumental records. In order to improve the understanding of the regularities of temperature variability in central China, in this study, we present a new tree-ring chronology from the Shengnongjia Mountains in central China which provides a valuable 245-year record of temperature variability. The reconstructed temperature correlated strongly with February–May mean temperature records of the Fangxian meteorological station from AD 1958 to AD 2011, and the derived reconstruction explained 44.5 % of the instrumental temperature variation during this period. The study shows that this region experienced three warm periods and two cool periods, i.e., the major warm periods occurred in AD 1783–1806, AD 1879–1909, and AD 1975 to the present, whereas the cool intervals occurred in AD 1807–1878 and AD 1910–1974. This reconstruction could aid in the evaluation of regional climate variability in subtropical China.

Tree-ring blue intensity (BI) has the potential to provide information on past summer temperatures of a similar quality to that of tree-ring maximum latewood density and at a substantially reduced cost. To explore the applicability of BI in subtropical regions, the inverted BI for the earlywood, latewood, and the delta BI (DBI) parameters, together with tree-ring width of subalpine fir (Abies fargesii Franch.) in the Shennongjia area of China, were measured, and the corresponding chronologies were developed. The relationships between these chronologies and monthly precipitation, monthly mean minimum temperature, monthly mean temperature, and monthly mean maximum temperature were explored through correlation analysis. Results show that the DBI chronology is closely related to the temperature in August of the current year, indicating that BI, specifically delta BI, data are suitable for use in dendroclimatology studies in subtropical areas. The resultant mean temperature reconstruction for August, based on DBI, explains 40.8% of the temperature variance and is robustly validated using independent periods from the calibration. This pilot study not only highlights the potential of DBI for temperature reconstruction in China but also offers valuable insights into historical climate variations in the Shennongjia region. Moreover, it shows the potential for utilizing such tree-ring data from low-latitude regions to derive past climate data in subtropical warm-humid zones.

This paper reported the structure rule and the signal processing technique of the sensor that utilizes the gas pendulum property of natural convection in the hermetic chamber to sense carrier obliquity. The sensor organ design, signal processing technique and software compensation effect of one dimension, two dimensions and omnidirectional tilt sensors were presented