## 4 Conclusions and Implications  
The spatiotemporal variations in vegetation growth dynamics (three indicators) and their relations with climatic factors in China were investigated using the AVHRR NDVI data and NCEP air temperature and precipitation data during 1982-2011. The following conclusions were drawn:  
(1) The overall annual NDVI in China showed a significant positive trend from 1982 to 2011 (\(\approx\)0.0006 yr\({}^{-1}\) or 0.14% yr\({}^{-1}\), \(p=0.002\)). Figure 7: Map of lagged months of (**a**) temperature and (**b**) precipitation. White area represents pixels with no data, light gray pixels represent insignificant trends, and dark gray pixels are masked with threshold of 30-year mean NDVI \(<0.1\). (2) The monthly mean NDVI in June, July and August had a significant TP in1984, 1988 and 2007, respectively. The monthly mean NDVI increased rapidly in June and July prior to the TPs and decreased for June and mostly stalled in July after the TPs; while in August the annual mean NDVI stabilized prior to the TP and rapidly increased after the TP at a rate of 0.011 NDVI\(\cdot\)yr\({}^{-1}\) (1.71% yr\({}^{-1}\)). (3) Of the vegetated area in China, about 33% showed a significant positive trend in annual mean NDVI, being mostly located in central to southern China; about 21% showed a significant positive trend in seasonality (s.d. NDVI), being most located in northern China (\(>\)35 \(\mathrm{\SIUnitSymbolMicro N}\)); a small proportion (\(<\)9%) had a significant trend in minimum vegetation coverage, with about half positive (in Jiangxi, Hunan and Hubei provinces, mainly caused by tree plantations) and half negative (in southwestern China, mainly caused by drought in the 2000s). (4) At the vegetation region scales, changes in vegetation growth dynamics were significantly correlated with air temperature (\(p<0.001\)); at the country scale, changes in NDVI was significantly and positively correlated with annual air temperature (\(r=0.52\), \(p<0.01\)) and insignificantly correlated with annual precipitation (\(p>0.1\)). (5) In about 24% of the vegetated area, annual mean NDVI was correlated significantly with air temperature (93% positive and remainder negative); and in 12% of the vegetated area, annual mean NDVI was correlated significantly 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, such as plantations, urbanization and agricultural practices in some regions. (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 mainly be caused by the abundance of precipitation. The results presented in this study demonstrate that annual vegetation productivity and seasonality in China vary among different vegetation regions. These different spatial patterns of gradual changes and TPs indicate complexity in vegetation growth dynamics and a nonlinear response of vegetation to global climatic changes and other drivers. The mechanisms behind the temporal and spatial dynamics of vegetation productivity in the context of accelerated global environmental change are not well understood. Divergence between the findings and those of previous researchers using different lengths of NDVI data series at different scales, suggests that continuing efforts to monitor vegetation changes (_in situ_ and satellite observations) over time and at broad scales are greatly needed and critical for the management of ecosystems, biodiversity, and for diagnosing and adapting to global climatic changes. Moving forward it is difficult to understand vegetation dynamics and its interaction with global climatic change.