Trends in vegetation productivity related to climate change in China’s Pearl River Delta

for China between 1960–1990 [44] was found to be greater over urban areas. The loess graphs also show increased winter and spring temperatures in the 1995–2004 period, and this is usu- ally consistent with increased cloud cover due to the insulating effects of clouds in cold weather. Response of vegetation to seasonal and annual changes in precipitation and temperature As the NDVI is expected to be related to both temperature and rainfall, we performed partial correlation analysis to control the confounding effects. As most of the mapped variables were not significant (S6 and S7 Figs), only significant variables are shown in Fig 6. It is interesting that the MGS shows a moderate (r = ~-0.6) negative correlation with temperature, especially, but not confined to, crop-growing areas, for all seasons of the year. Peak NDVI also shows a negative correlation with temperature (r = ~-0.6) over cropland as well as over some forested regions for all seasons. On the other hand, Trough (NDVI in February) in both forest and Fig 4. Trends in phenometrics of different LCLU classes with loess fitting and confidence intervals. Only the metrics showing significant trends in most land cover classes; correlation coefficient (r), slope, significance (p) and total change (TC) is obtained by linear regression analysis of the variables over time. https://doi.org/10.1371/journal.pone.0245467.g004 PLOS ONE Climate and vegetation trends in the Pearl River Delta PLOS ONE | https://doi.org/10.1371/journal.pone.0245467 February 24, 2021 9 / 20