Satellite-derived Normalized Difference Vegetation Index (NDVI), a proxy of vegetation productivity, is known to be correlated with temperature in northern ecosystems. This relationship, however, may change over time following alternations in other environmental factors. Here we show that above 30°N, the strength of the relationship between the interannual variability of growing season NDVI and temperature (partial correlation coefficient RNDVI-GT) declined substantially between 1982 and 2011. This decrease in RNDVI-GT is mainly observed in temperate and arctic ecosystems, and is also partly reproduced by process-based ecosystem model results. In the temperate ecosystem, the decrease in RNDVI-GT coincides with an increase in drought. In the arctic ecosystem, it may be related to a nonlinear response of photosynthesis to temperature, increase of hot extreme days and shrub expansion over grass-dominated tundra. Our results caution the use of results from interannual time scales to constrain the decadal response of plants to ongoing warming.

Evidence for A Weakening Relationship between Interannual Temperature Variability and Northern Vegetation Activity

The research of soil and water conservation biological measures is summarized and analyzed, including the estimate and choice of soil and water conservation vegetation breed, the anti erosion mechanism of soil and water conservation vegetation breed, the collocation of soil and water conservation vegetation measures and the building technology of soil and water conservation vegetation, and the content of four aspects is summarized and analyzed at length

Research of Soil and Water Conservation Biological Measures

Geographic detector-based quantitative assessment enhances attribution analysis of climate and topography factors to vegetation variation for spatial heterogeneity and coupling

This study used both temperature-humidity and wind efficiency indices at three time-scale resolutions (year, season, and month) for the first time, to analyze the spatio–temporal evolution of urban climate comfort in the Guangdong–Hong Kong–Macau Greater Bay Area (GBA). The main factors affecting human-settlement climate comfort were elucidated and the annual changes in both indices used in the study area exhibited fluctuating growth from 2005 to 2020. Moreover, the annual growth of the temperature-humidity and wind efficiency indices in the southern cities of the GBA was relatively fast. In contrast, the annual growth of these indices in the northern cities of the GBA was relatively slow. Overall, the climate of the human-settlement environments in the GBA was the most comfortable in spring and autumn, and summer and winter were characterized by hot and cold climate conditions, respectively. We did not identify any prominent change in the climate comfort of spring and autumn from 2005 to 2020; however, the climate comfort degree deteriorated in summer and ameliorated in winter. On a monthly scale, the human-settlement environments in the GBA were the coldest in December and the hottest in July. The urban human settlements were cold in January and February, hot in May, June, August, and September, and the most comfortable in March, April, October, and November in 2020. We analyzed the factors affecting the climate comfort of human-settlement environments in the study area and found that elevation, gross industrial production, population scale, and construction land area were the most influential parameters. Notably, the impact of natural factors on the climate comfort of human-settlement environments was more significant than that of anthropogenic factors. Moreover, the related factors affected the temperature-humidity index more strongly than the wind efficiency index. Overall, our results provide data-driven guidelines for improving the climate comfort of urban human settlements in the GBA.

/pdf/spatio-temporal-evolution-and-factors-of-climate-comfort-for-3cn2glnw.pdf

Spatio–temporal evolution and factors of climate comfort for urban human settlements in the Guangdong–Hong Kong–Macau Greater Bay Area

Vegetation growth is sensitive to climate change. The complex climate types of China pose great challenges to the sustainable management of vegetation on global change. Therefore, this study used Enhanced Vegetation Index (EVI) as an indicator to explore the spatiotemporal dynamics of vegetation and their driving factors in different climatic zones of China to provide theoretical support for sustainable vegetation management in different climate zones in the future. The results showed that vegetation exhibited considerable clustering patterns in the country, with high and low values concentrated in the eastern and western regions, respectively. From 2001 to 2020, both at regional and pixel scales, vegetation in China showed a significant greening trend. EVI displayed a noticeable increase within temperate and subtropical areas. The only exception is observed in the eastern coastal area of the North China Plain and Yangtze River Delta region, which experienced evident degradation trend. During this period, China's climate showed an overall trend towards warming and humidification with drying trends observed mainly over the western regions. The impact of climate changes resulted in EVI dynamics that vary over time and space. The vegetation change in China was mainly derived by changes in precipitation and radiation rather than temperature, especially in temperate and subfrigid regions. Precipitation was the main driving factor for vegetation greening in tropical and temperate regions, while radiation and temperature were the dominant climate factor for vegetation greening in subfrigid and subtropical regions, respectively. When precipitation was no longer a limiting factor for vegetation growth, the effect of temperature or radiation increases. In addition, the positive impact of precipitation on plant growth in temperate regions was much greater than that of radiation and temperature, and this difference was much greater than in tropical, subtropical, and subfrigid regions. 

Vegetation response to changes in climate across different climate zones in China

Relationship between extreme climate indices and spatiotemporal changes of vegetation on Yunnan Plateau from 1982 to 2019

How does the Net primary productivity respond to the extreme climate under elevation constraints in mountainous areas of Yunnan, China?

/pdf/impact-of-climate-change-on-potential-distribution-patterns-mijz5b7x1g.pdf

Impact of Climate Change on Potential Distribution Patterns of Alpine Vegetation in the Hengduan Mountains Region, China

Based on MODIS data and CASA (Camegie Ames Stanford Approach) model to estimate the net primary productivity (NPP) of farmland ecosystem in the Central Yunnan Plateau from 1982 to 2019, the spatial autocorrelation method and Sen’ s trend analysis were used to analyze the spatial-temporal variation characteristics of farmland NPP and the influence of climate factors for the last 38 years. The results indicated: The annual NPP of farmland varied from 772.43 to 993.72 g C/(m2⋅a) during 1982 - 2019, with the total mean value of 897.50 g C/(m2⋅a), which had the decrease trend during 1982 - 2000 but showed the increase fluctuation from 2001 to 2019. The total values of NPP tended to stabilize during 1982 - 2019. As for the spatial distribution, the farmland NPP in the southwest low-altitude areas were relatively high (>1500 g C/(m2⋅a)), whereas the farmland NPP in the northeast high-altitude regions had the lower values, especially in Kunming and urbans in central Yunnan (<200 g C/(m2⋅a). From the variation trend, the farmland NPP significantly increased in 31.7% of the agricultural area in the Central Yunnan Plateau, with no obvious change and significant decrease in 37.1% and 31.2%, which was observed for obvious increase tendency in the northeast area. The significant positive relationships were observed for 30.0%, 28.2% and 73.0% of mean pixel NPP with precipitation, temperature and SPEI drought index respectively, which indicated that the farmland ecosystem was largely influenced by drought to a certain extent.

Spatio-temporal Variation of Net Primary Productivity of Farmland Ecosystem in Central Yunnan Plateau

Global warming is increasing the frequency and intensity of extreme weather events around the world. The extreme climate in plateau and mountainous areas is sensitive and fragile. Based on the software Rclimdex 1.0, the spatio-temporal variation characteristics of 27 extreme climate indices at 120 meteorological stations were calculated in Yunnan from 1960 to 2019. The results show that the extreme temperature is rising, and the warming rate at night is higher than that in the daytime. It showed a trend of warming and drying, and precipitation was concentrated into more intense bursts. Extreme temperature cold indices (TX10p, TN10p, FD0, ID0, and CSDI) were negatively correlated with extreme precipitation indices (R × 5 day, PRCPTOT, R10 mm, R20 mm, and R25 mm). Extreme temperature warmth indices (TX90p and TN90p) were positively correlated with extreme precipitation indices (R × 5 day, CWD, PRCPTOT, R10 mm, R20 mm, and R25 mm). The change rate of extreme temperature does not increase linearly with altitude. The increase in middle-altitude and high-altitude areas is higher than that in low-altitude areas. Compared with ENSO and AO, NAO is a vital circulation pattern affecting the extreme climate in Yunnan. The influence of NAO on Yunnan’s extreme climate indices is most significant in the current month and the second month that follows. NAO was negatively correlated with extreme temperature warm indices (TN90p, TX90p, SU25, and TR20). NAO positively correlates with the extreme cold temperature indices (TN10p and TX10p). Except that ENSO has a significant effect on CDD, the effect of the general circulation patterns on the extreme temperature indices was more significant than that on the extreme precipitation indices in Yunnan. The results of this study are helpful to further understand and predict the characteristics of extreme climatic events and the factors affecting their geographical locations and atmospheric circulation patterns in Yunnan.

Analysis of Spatiotemporal Variability in Extreme Climate and Potential Driving Factors on the Yunnan Plateau (Southwest China) during 1960–2019

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