Chin J Plant Ecol ›› 2022, Vol. 46 ›› Issue (12): 1437-1447.DOI: 10.17521/cjpe.2021.0259
Special Issue: 生态学研究的方法和技术; 青藏高原植物生态学:生态系统生态学; 生态系统碳水能量通量
• Special feature: Ecosystem carbon and water fluxes in ecological vulnerable areas of China • Previous Articles Next Articles
LI Hong-Qin1, ZHANG Ya-Ru1, ZHANG Fa-Wei2,3,*(), MA Wen-Jing4,5, LUO Fang-Lin3, WANG Chun-Yu3, YANG Yong-Sheng2,3, ZHANG Lei-Ming6, LI Ying-Nian2,3
Received:
2021-07-13
Accepted:
2021-12-03
Online:
2022-12-20
Published:
2023-01-13
Contact:
*ZHANG Fa-Wei(Supported by:
LI Hong-Qin, ZHANG Ya-Ru, ZHANG Fa-Wei, MA Wen-Jing, LUO Fang-Lin, WANG Chun-Yu, YANG Yong-Sheng, ZHANG Lei-Ming, LI Ying-Nian. Application of boosted regression trees for the gap-filling to flux dataset in an alpine scrubland of Qingzang Plateau[J]. Chin J Plant Ecol, 2022, 46(12): 1437-1447.
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URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2021.0259
Fig. 1 A regression tree with 5 leaf nodes (Y1, Y2, Y3, Y4 and Y5) of 2 variables (X1 and X2). t1, t2, t3 and t4 are the splitting value of an optimal predictor.
Fig. 2 Interannual variations of 30-min net CO2 exchange (A), sensible heat flux (H)(B), latent heat flux (LE)(B), air temperature (Ta)(C), atmospheric water vapor (D), wind speed (Ws)(E), solar shortwave radiation (Swin)(F), topsoil temperature at 5 cm depth (Ts)(G), and topsoil water content at 10 cm depth (SWC)(H) during 2003 to 2005 in an alpine scrubland.
Fig. 3 Relationships between the observed data of 30-min net CO2 exchange (NEE)(A), sensible heat flux (H)(B) and latent heat flux (LE)(C) with the predicted data by the boosted regression trees for NEE during the growing season daytime and other periods (nighttime during growing season and the whole non-growing season), and for H and LE during growing and non-growing season in an alpine scrubland. MAE, mean absolute error; RMSE, root mean square error.
Fig. 4 Relative contributions of environmental factors to the variations of 30 min net CO2 exchange at daytime during growing season and other periods (nighttime during growing season and the whole non-growing season)(A), sensible heat flux (H), and latent heat flux (LE) during growing season and non-growing season in an alpine scrubland (B). SWC, topsoil water content at 10 cm depth; Swin, shortwave radiation; Ta, air temperature; Ts, topsoil temperature at 5 cm depth; Vapor, atmospheric water vapor pressure; Ws, wind speed.
Fig. 5 Relationships between fitted 30-min net CO2 exchange (A, B, daytime during growing season; C, nighttime during growing season and the whole non-growing season), sensible heat flux (D, growing season; E, non-growing season) and latent heat flux (F, growing season; G, non-growing season) from boosted regression trees with main environmental factors during the different stages in an alpine scrubland. H, sensible heat flux; LE, latent heat flux; Swin, solar shortwave radiation; Ts, topsoil temperature at 5 cm depth; Vapor, atmospheric water vapor pressure.
Fig. 6 Comparisons between the boosted regression trees (BRT) and Chinese flux observation and research network (ChinaFLUX) for gap-filled 30 min net CO2 exchange and during growing-season (NEE)(A) and other periods (nighttime during growing season and the whole non-growing season)(B), 30 min sensible heat flux (H) during growing season (C) and non-growing season (D), and latent heat flux (LE) during growing season (E) and non-growing season (F) in an alpine scrubland.
Fig. 7 Comparisons between the boosted regression trees (BRT) and Chinese flux observation and research network (ChinaFLUX) for daily CO2 fluxes (A), sensible heat flux (H)(B) and latent heat flux (LE)(C) in an alpine scrubland. GEE, gross ecosystem CO2 exchange; NEE, net ecosystem CO2 exchange; RES, ecosystem respiration.
Fig. 8 Comparisons between the boosted regression trees (BRT) and Chinese flux observation and research network (ChinaFLUX) for the modelled monthly CO2 fluxes (A) and heat fluxes (B) in an alpine scrubland. GEE, gross ecosystem CO2 exchange; H, sensible heat flux; LE, latent heat flux; NEE, net ecosystem CO2 exchange; RES, ecosystem respiration.
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