The effects of air temperature and precipitation on the net primary productivity in China during the early 21st century

Wang, Qianfeng; Zeng, Jiali; Leng, Song; Fan, Bingxiong; Tang, Jia; Cong, Jiajia; Huang, Yi; Zhang, Qing; Qu, Yanping; Wang, Wulin; Shui, Wei

doi:10.1007/s11707-018-0697-9

“…where, NPP The potential and actual NPPs were calculated using our improved CASA model, which was further calibrated by field observed data in China (Zhu et al 2007), and considered the land cover change (Wang et al 2018). The improved CASA model thought that the NPP comprised absorbed photosynthetically active radiation (APAR) and light utilization efficiency (  ).…”

Section: Hanpp Frameworkmentioning

confidence: 99%

“…where, on the previous study (Wang et al 2018). Meanwhile, considering the human interference on cropland and built-up land, we adjusted the CASA model parameters for these two land cover types to calculate the potential NPP according to Hua's research (Hua 2009).…”

Section: Hanpp Frameworkmentioning

confidence: 99%

Assessing Human Appropriation of Net Primary Production in Various Vegetation Types Based on the Spatio-Temporal Fusion Model in Xiong'an New Area During 2000-2018

Tang

¹

,

Zhang

²

,

Zeng

³

et al. 2020

Preprint

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0

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Background: Humans have induced great changes in terrestrial ecosystems. The human appropriation of net primary production (HANPP) quantifying the intensity of anthropogenic extraction from ecosystem has been widely used to evaluate ecological sustainable development. However, the coarse-resolution of calculating data for the HANPP leads to biased results in a small scale. Furthermore, the spatio-temporal patterns and dynamics of the HANPP in a human-dominated heterogeneous region are still unclear. Methods: This study investigates the state-level new area Xiong'an New Area and applies the spatial and temporal nonlocal filter-based fusion model (STNLFFM) to generated new datasets, which is combined with our previously improved Carnegie–Ames–Stanford approach (CASA) to estimate HANPP. Spatio-temporal variations of HANPP are mapped and assessed using Mann–Kendall (M–K) trend analysis approach from 2000 to 2018 with a high resolution. The relationship among the HANPP, subcomponents, and natural–social–economic-driven factors is discussed herein. Results: The results show that the STNLFFM-derived fusion images fitted well with the observed images having the superior correlation coefficient (r), structural similarity index, root mean square error, and mean absolute deviation of 0.75, 0.76, 0.035, and 0.026, respectively, and the normalized difference vegetation index (NDVI) differences are mainly concentrated on the range of 0–0.15 for all months. The HANPP derived by the fusion-based images, above 60% of potential NPP, varied across the whole area, especially between various vegetation types. The HANPP exhibited a significant positive correlation (r > 0.46, P < 0.05) with precipitation and held an uptrend because of the increase of the harvested HANPP which related with the socio-economic conditions having the determination coefficients above 0.76.Conclusions: The spatio-temporal fusion contributed to fine spatial patterns and trends of HANPP among various vegetation types. Though the harvested HANPP increased from 2000 to 2018, the agricultural and socio-economic developments did not bring extensive HANPP growth, indicating that the expansion has not violated its sustainable development goal. The results provide a deep insight of the background characteristics in Xiong'an New Area, which has great potential in supporting the future scientific construction of the new area.

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“…-NPP + The potential and actual NPPs were calculated using our improved CASA model, which was further calibrated by field observed data in China (Zhu et al 2007), and considered the land cover change (Wang et al 2018). The improved CASA model thought that the NPP comprised absorbed photosynthetically active radiation (APAR) and light utilization efficiency (  ).…”

Section: Hanpp Frameworkmentioning

confidence: 99%

“…xt  can be further calculated based on the previous study (Wang et al 2018). Meanwhile, considering the human interference on cropland and built-up land, we adjusted the CASA model parameters for these two land cover types to calculate the potential NPP according to Hua's research (Hua 2009).…”

Section: Hanpp Frameworkmentioning

confidence: 99%

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Assessing Human Appropriation of Net Primary Production in Various Vegetation Types Based on the Spatio-Temporal Fusion Model in Xiong'an New Area During 2000-2018

Tang

¹

,

Zhang

²

,

Zeng

³

et al. 2020

Preprint

Self Cite

0

View full text Add to dashboard Cite

Background: Humans have induced great changes in terrestrial ecosystems. The human appropriation of net primary production (HANPP) quantifying the intensity of anthropogenic extraction from ecosystem has been widely used to evaluate ecological sustainable development. However, the coarse-resolution of calculating data for the HANPP leads to biased results in a small scale. Furthermore, the spatio-temporal patterns and dynamics of the HANPP in a human-dominated heterogeneous region are still unclear. Methods: This study investigates the state-level new area Xiong'an New Area and applies the spatial and temporal nonlocal filter-based fusion model (STNLFFM) to generated new datasets, which is combined with our previously improved Carnegie–Ames–Stanford approach (CASA) to estimate HANPP. Spatio-temporal variations of HANPP are mapped and assessed using Mann–Kendall (M–K) trend analysis approach from 2000 to 2018 with a high resolution. The relationship among the HANPP, subcomponents, and natural–social–economic-driven factors is discussed herein. Results: The results show that the STNLFFM-derived fusion images fitted well with the observed images having the superior correlation coefficient (r), structural similarity index, root mean square error, and mean absolute deviation of 0.75, 0.76, 0.035, and 0.026, respectively, and the normalized difference vegetation index (NDVI) differences are mainly concentrated on the range of 0–0.15 for all months. The HANPP derived by the fusion-based images, above 60% of potential NPP, varied across the whole area, especially between various vegetation types. The HANPP exhibited a significant positive correlation (r > 0.46, P < 0.05) with precipitation and held an uptrend because of the increase of the harvested HANPP which related with the socio-economic conditions having the determination coefficients above 0.76.Conclusions: The spatio-temporal fusion contributed to fine spatial patterns and trends of HANPP among various vegetation types. Though the harvested HANPP increased from 2000 to 2018, the agricultural and socio-economic developments did not bring extensive HANPP growth, indicating that the expansion has not violated its sustainable development goal. The results provide a deep insight of the background characteristics in Xiong'an New Area, which has great potential in supporting the future scientific construction of the new area.

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The influence of temperature and precipitation on the vegetation dynamics of the tropical island of Hainan

Guo

¹

,

Zhao

²

,

Jian

³

et al. 2020

Theor Appl Climatol

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The effects of air temperature and precipitation on the net primary productivity in China during the early 21st century

Cited by 51 publications

References 43 publications

Assessing Human Appropriation of Net Primary Production in Various Vegetation Types Based on the Spatio-Temporal Fusion Model in Xiong'an New Area During 2000-2018

Assessing Human Appropriation of Net Primary Production in Various Vegetation Types Based on the Spatio-Temporal Fusion Model in Xiong'an New Area During 2000-2018

Assessing Human Appropriation of Net Primary Production in Various Vegetation Types Based on the Spatio-Temporal Fusion Model in Xiong'an New Area During 2000-2018

The influence of temperature and precipitation on the vegetation dynamics of the tropical island of Hainan

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