Characteristics and influencing factors of energy fluxes in the coniferous and broadleaf forests in Jinyun Mountains at different temporal scales

doi:10.17521/cjpe.2024.0276

Abstract

Abstract:

Aims Under the background of global climate change, this study investigated the dynamic characteristics of energy fluxes in Jinyun Mountain’s coniferous-broadleaf mixed forest across different temporal scales and their responses to environmental factors.

Methods We selected the mixed coniferous and broadleaf forests in Jinyun Mountains as the study area, and analyzed the long time series flux data of the mixed coniferous and broadleaf forests in Jinyun Mountains for the years 2020, 2021, and 2023 (data for 2022 are missing) using correlation factor analysis and structural equation modeling based on the data measured by eddy correlation technique.

Important findings (1) At the diurnal scale, net radiation (Rn), sensible heat flux (H), and latent heat flux (LE) exhibited unimodal trends, with their peak values occurring at 14:00 local time, and approaching near-zero values after 19:00. In contrast, soil heat flux (G) displayed a bimodal pattern, reaching its daily minimum prior to sunrise and attaining its daily maximum at 14:00 local time. (2) At the monthly scale, the influence of Rn on energy fluxes increased from April, reached its maximum in July and August, then gradually decreased. The influence of canopy conductance (Gs) on LE followed the same trend. (3) At the growing season scale, Rn was the primary influencing factor for energy flux variations. Correlation factor analysis indicated that Gs had a slight limiting effect on H but a significant limiting effect on LE. However, the plant water balance mechanism exerted the strongest influence. (4) The annual mean Bowen ratios (β) for the three years were 0.69, 0.63, and 0.76, respectively. (5) Influenced by extreme drought, the sensible heat flux at the annual scale exhibited a bimodal trend. This study analyzed the characteristics and influencing factors of energy fluxes in the Jinyun Mountain coniferous-broadleaf mixed forests, revealing the dynamic processes of energy fluxes, quantifying the impacts of environmental factors, and providing a scientific basis for assessing the response of subtropical forest ecosystems to climate change and forest conservation.

Key words: coniferous and broadleaf mixed forest, energy flux, latent heat flux, sensible heat flux, energy flows

ZHAO Kun, WANG Yun-Qi, LIANG Jun, ZHOU Xiao-Zhou, FENG Yin-Cheng, QI Zi-Han, LI Jun-Jie, CUI Xin-Rui, LIU Xuan-Wo, MAO Wei. Characteristics and influencing factors of energy fluxes in the coniferous and broadleaf forests in Jinyun Mountains at different temporal scales[J]. Chin J Plant Ecol, 2026, 50(1): 70-81.

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URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2024.0276

https://www.plant-ecology.com/EN/Y2026/V50/I1/70

Figures/Tables 8

Fig. 1 Location of the Jinyun Mountain Research Area and pictures of the flux tower in Chongqing.

Fig. 2 Energy closure of the coniferous and broadleaf mixed forest in Jinyun Mountains. G, soil heat flux; H, sensible heat flux; LE, latent heat flux; Rn, net radiation.

Fig. 3 Diurnal variation of energy flux in coniferous and broadleaf mixed forest ecosystems in Jinyun Mountains. A, 24-h flux trend chart in 2020. B, 24-h flux trend chart in 2021. C, 24-h flux trend chart in 2023. D, 24-h trend graph of soil heat flux on a year-by-year basis. G, soil heat flux; H, sensible heat flux; LE, latent heat flux; Rn, net radiation.

Fig. 4 Seasonal variations of daily mean energy fluxes in coniferous-broadleaved mixed forest ecosystems in Jinyun Mountains. A, Sensible heat flux (H). B, Latent heat flux (LE). C, Bowen ratio (β).

Fig. 5 Diurnal variation distribution of environmental factors in the coniferous and broadleaf mixed forest ecosystems in Jinyun Mountains. Gs, canopy conductance; P, precipitation; RH, relative humidity; TA, air temperature; VPD, vapor pressure deficit; WS, wind speed.

Fig. 6 Correlation coefficients between sensible heat flux (H) and net radiation (Rn), relative humidity (RH), air temperature (TA), wind speed (WS), saturated water vapor pressure difference (VPD), canopy conductance (Gs) and precipitation (P) in coniferous and broadleaf mixed forest ecosystems in Jinyun Mountains. A, Monthly correlation coefficient of sensible heat flux in 2020. B, Monthly correlation coefficient of sensible heat flux in 2021. C, Monthly correlation coefficient of sensible heat flux in 2023. D, Correlation coefficient of sensible heat flux in the growing season is year-by-year.

Fig. 7 Correlation coefficients between latent heat flux (LE) and net radiation (Rn), relative humidity (RH), air temperature (TA), wind speed (WS), saturated water vapor pressure difference (VPD), canopy conductance (Gs) and precipitation (P) in coniferous and broadleaf mixed forest ecosystems in Jinyun Mountains. A, Month-by-month correlation coefficient of latent heat flux in 2020. B, Month-by-month correlation coefficient of latent heat flux in 2021. C, Month-by-month correlation coefficient of latent heat flux in 2023. D, Year-by-year correlation coefficient of latent heat flux growing season.

Fig. 8 Direct and indirect effects of environmental factors on energy flux. A, Structural equation model path analysis of environmental factors and sensible heat fluxes. B, Structural equation model path analysis of environmental factors and latent heat fluxes. Standardized path coefficients (ρ: -1-1) are shown along with path arrows, where ρ < 0 and ρ > 0 indicate negative and positive correlations, respectively. The goodness-of-fit index (GFI) and root-mean-square error of approximation (RMSEA) for all path models were >0.80 and <0.06, respectively. Gs, canopy conductance; H, sensible heat flux; LE, latent heat flux; P, precipitation; RH, relative humidity; Rn, net radiation; TA, air temperature; VPD, saturated water vapour pressure difference; WS, wind speed.

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