scholarly journals EFFECTS OF OZONE POLLUTION ON TERRESTRIAL ECOSYSTEM PRODUCTIVITY

2007 ◽  
Vol 31 (2) ◽  
pp. 219-230 ◽  
Author(s):  
REN Wei ◽  
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TIAN Han-Qin
2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jianguo Li ◽  
Chenxin Zou ◽  
Qiang Li ◽  
Xinyue Xu ◽  
Yanqing Zhao ◽  
...  

AbstractThe terrestrial ecosystem productivity and foundation of regional ecosystem services have been significantly influenced by recent urbanization processes. This study assesses the changes in terrestrial ecosystem productivity in Jiangsu from the years of 2000 to 2015 in response to the urbanization. A linear model that incorporates the traditional equalization method is proposed to improve the estimation accuracy of net primary productivity (NPP) loss. Results revealed that the land area of urban construction expanded rapidly during the research period to encompass an area of 8672.8 km2. The rate of expansion was highest during 2005–2010. Additionally, the expansion rate of urban construction land was considerably higher in southern Jiangsu compared to the northern areas. The NPP exhibited a rising tendency from the year of 2000 to 2015, and varied from 33.30 to 40.23 Tg C/y. It was higher in the central parts, which include the cities of Yancheng and Nantong. The increase in urban construction land has resulted in a significant reduction in the terrestrial ecosystem productivity, i.e. a cumulative NPP loss of 2.55–2.88 Tg C during the research period. The NPP losses due to the conversion from cropland to constrction land were the highest, followed by the wetland. The work in this paper indicates that the rate of future productivity losses in terrestrial ecosystem in northern Jiangsu would be faster than the southern areas.


2018 ◽  
Vol 10 (3) ◽  
pp. 1217-1226 ◽  
Author(s):  
Xiaoli Ren ◽  
Honglin He ◽  
Li Zhang ◽  
Guirui Yu

Abstract. Solar radiation, especially photosynthetically active radiation (PAR), is the main energy source of plant photosynthesis, and the diffuse component can enhance canopy light use efficiency, thus increasing ecosystem productivity. In order to predict the terrestrial ecosystem productivity precisely, we not only need global radiation and PAR as driving variables, but also need to treat diffuse radiation and diffuse PAR explicitly in ecosystem models. Therefore, we generated a series of radiation datasets, including global radiation, diffuse radiation, PAR, and diffuse PAR of China from 1981 to 2010, based on the observations of the China Meteorology Administration (CMA) and the Chinese Ecosystem Research Network (CERN). The dataset should be useful for the analysis of the spatiotemporal variations of solar radiation in China and the impact of diffuse radiation on terrestrial ecosystem productivity based on ecosystem models. The dataset is freely available from Zenodo on the following website: https://zenodo.org/record/1198894#.Wx6–C_MwWo (https://doi.org/10.11922/sciencedb.555, Ren et al., 2018).


2018 ◽  
Author(s):  
Xiaoli Ren ◽  
Honglin He ◽  
Li Zhang ◽  
Guirui Yu

Abstract. Solar radiation, especially photosynthetically active radiation (PAR), is the main energy source of plant photosynthesis; and the diffuse component can enhance canopy light use efficiency, thus increasing ecosystem productivity. In order to predict the terrestrial ecosystem productivity precisely, we not only need global radiation and PAR as driving variables, but also need to treat diffuse radiation and diffuse PAR explicitly in ecosystem models. Therefore, we generated a series of radiation datasets, including global radiation, diffuse radiation, PAR, and diffuse PAR of China from 1981 to 2010, based on the observations of China Meteorology Administration (CMA) and Chinese Ecosystem Research Network (CERN). The dataset should be useful for the analysis of the spatio-temporal variations of solar radiation in China and the impact of diffuse radiation on terrestrial ecosystem productivity based on ecosystem models. The dataset is freely available from the Zenodo at the website of https://zenodo.org/record/1198894 (DOI: 10.11922/sciencedb.555).


2018 ◽  
Vol 28 (5) ◽  
pp. 1313-1324 ◽  
Author(s):  
Sean DuBois ◽  
Ankur R. Desai ◽  
Aditya Singh ◽  
Shawn P. Serbin ◽  
Michael L. Goulden ◽  
...  

2002 ◽  
Vol 107 (D6) ◽  
pp. ACL 2-1-ACL 2-23 ◽  
Author(s):  
Lianhong Gu ◽  
Dennis Baldocchi ◽  
Shashi B. Verma ◽  
T. A. Black ◽  
Timo Vesala ◽  
...  

2020 ◽  
Vol 54 (8) ◽  
pp. 4984-4994
Author(s):  
Peggy A. O’Day ◽  
Ugwumsinachi G. Nwosu ◽  
Morgan E. Barnes ◽  
Stephen C. Hart ◽  
Asmeret Asefaw Berhe ◽  
...  

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