Kai Jin, Yidong Wu, Fei Wang, Cuijin Li, Quanli Zong, Chunxia Liu
{"title":"评估气候和人为因素对中国植被动态的影响:考虑气候时滞和累积效应。","authors":"Kai Jin, Yidong Wu, Fei Wang, Cuijin Li, Quanli Zong, Chunxia Liu","doi":"10.1007/s00484-024-02794-3","DOIUrl":null,"url":null,"abstract":"<p><p>Determining the factors that drive vegetation variation is complicated by the intricate interactions between climatic and anthropogenic influences. Neglecting the short-term time-lag and cumulative effects of climate on vegetation growth (i.e., temporal effects) exacerbates the uncertainty in attributing long-term vegetation dynamics. This study evaluated the climatic and anthropogenic influences on vegetation dynamics in China from 2000 to 2019 by analyzing normalized difference vegetation index (NDVI), temperature, precipitation, solar radiation, and ten anthropogenic indicators through linear regression, correlation, multiple linear regression (MLR), residual, and principal component analyses. Across most regions, growing season NDVI (G-NDVI) exhibited heightened sensitivity to climatic variables from earlier periods or from both earlier and current periods, signaling extensive temporal climatic effects. Constructing new time series for temperature, precipitation, and solar radiation from 2000 to 2019, based on the optimal vegetation response timing to each climatic variable, revealed significant correlations with G-NDVI across 27.9%, 26.7%, and 23.3% of the study area, respectively. Climate variability and anthropogenic activities contributed 45% and 55% to the G-NDVI increase in China, respectively. Afforestation significantly promoted vegetation greening, while agricultural development had a marginally positive influence. In contrast, urbanization negatively impacted vegetation, particularly in eastern China, where farmland conversion to constructed land has been prevalent over the past two decades. Neglecting temporal effects would significantly reduce the areas with robust MLR models linking G-NDVI to climatic variables, thereby increasing uncertainty in attributing vegetation changes. The findings highlight the necessity of integrating multiple anthropogenic factors and climatic temporal effects in evaluating vegetation dynamics and ecological restoration.</p>","PeriodicalId":588,"journal":{"name":"International Journal of Biometeorology","volume":" ","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessment of climatic and anthropogenic influences on vegetation dynamics in China: a consideration of climate time-lag and cumulative effects.\",\"authors\":\"Kai Jin, Yidong Wu, Fei Wang, Cuijin Li, Quanli Zong, Chunxia Liu\",\"doi\":\"10.1007/s00484-024-02794-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Determining the factors that drive vegetation variation is complicated by the intricate interactions between climatic and anthropogenic influences. Neglecting the short-term time-lag and cumulative effects of climate on vegetation growth (i.e., temporal effects) exacerbates the uncertainty in attributing long-term vegetation dynamics. This study evaluated the climatic and anthropogenic influences on vegetation dynamics in China from 2000 to 2019 by analyzing normalized difference vegetation index (NDVI), temperature, precipitation, solar radiation, and ten anthropogenic indicators through linear regression, correlation, multiple linear regression (MLR), residual, and principal component analyses. Across most regions, growing season NDVI (G-NDVI) exhibited heightened sensitivity to climatic variables from earlier periods or from both earlier and current periods, signaling extensive temporal climatic effects. Constructing new time series for temperature, precipitation, and solar radiation from 2000 to 2019, based on the optimal vegetation response timing to each climatic variable, revealed significant correlations with G-NDVI across 27.9%, 26.7%, and 23.3% of the study area, respectively. Climate variability and anthropogenic activities contributed 45% and 55% to the G-NDVI increase in China, respectively. Afforestation significantly promoted vegetation greening, while agricultural development had a marginally positive influence. In contrast, urbanization negatively impacted vegetation, particularly in eastern China, where farmland conversion to constructed land has been prevalent over the past two decades. Neglecting temporal effects would significantly reduce the areas with robust MLR models linking G-NDVI to climatic variables, thereby increasing uncertainty in attributing vegetation changes. 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Assessment of climatic and anthropogenic influences on vegetation dynamics in China: a consideration of climate time-lag and cumulative effects.
Determining the factors that drive vegetation variation is complicated by the intricate interactions between climatic and anthropogenic influences. Neglecting the short-term time-lag and cumulative effects of climate on vegetation growth (i.e., temporal effects) exacerbates the uncertainty in attributing long-term vegetation dynamics. This study evaluated the climatic and anthropogenic influences on vegetation dynamics in China from 2000 to 2019 by analyzing normalized difference vegetation index (NDVI), temperature, precipitation, solar radiation, and ten anthropogenic indicators through linear regression, correlation, multiple linear regression (MLR), residual, and principal component analyses. Across most regions, growing season NDVI (G-NDVI) exhibited heightened sensitivity to climatic variables from earlier periods or from both earlier and current periods, signaling extensive temporal climatic effects. Constructing new time series for temperature, precipitation, and solar radiation from 2000 to 2019, based on the optimal vegetation response timing to each climatic variable, revealed significant correlations with G-NDVI across 27.9%, 26.7%, and 23.3% of the study area, respectively. Climate variability and anthropogenic activities contributed 45% and 55% to the G-NDVI increase in China, respectively. Afforestation significantly promoted vegetation greening, while agricultural development had a marginally positive influence. In contrast, urbanization negatively impacted vegetation, particularly in eastern China, where farmland conversion to constructed land has been prevalent over the past two decades. Neglecting temporal effects would significantly reduce the areas with robust MLR models linking G-NDVI to climatic variables, thereby increasing uncertainty in attributing vegetation changes. The findings highlight the necessity of integrating multiple anthropogenic factors and climatic temporal effects in evaluating vegetation dynamics and ecological restoration.
期刊介绍:
The Journal publishes original research papers, review articles and short communications on studies examining the interactions between living organisms and factors of the natural and artificial atmospheric environment.
Living organisms extend from single cell organisms, to plants and animals, including humans. The atmospheric environment includes climate and weather, electromagnetic radiation, and chemical and biological pollutants. The journal embraces basic and applied research and practical aspects such as living conditions, agriculture, forestry, and health.
The journal is published for the International Society of Biometeorology, and most membership categories include a subscription to the Journal.