The modeling and partitioning of regional evapotranspiration (ET) are key issues in global hydrological and ecological research. We incorporated a stomatal conductance model and a light-use efficiency-based gross primary productivity (GPP) model into the Shuttleworth–Wallace model to develop a simplified carbon-water coupling model, SWH, for estimating ET using meteorological and remote sensing data. To enable regional application of the SWH model, we optimized key parameters with measurements from global eddy covariance (EC) tower sites. In addition, we estimated soil water content with the principle of the bucket system. The model prediction of ET agreed well with the estimates obtained with the EC measurements, with an average R² of 0.77 and a root mean square error of 0.72 mm·day⁻¹. The model performance was generally better for woody ecosystems than herbaceous ecosystems. Finally, the spatial patterns of ET and relevant model outputs (i.e., GPP, water-use efficiency and the ratio of soil water evaporation to ET) in China with the model simulations were assessed.

Solar radiation significantly affects terrestrial gross primary productivity (GPP). However, the relationship between GPP and solar radiation is nonlinear because it is affected by diffuse radiation. Solar radiation has undergone a shift from darker to brighter values over the past 30 years in China. However, the effects on GPP of variation in solar radiation because of changes in diffuse radiation are unclear. In this study, national global radiation in conjunction with other meteorological data and remotely sensed data were used as input into a two-leaf light use efficiency model (TL-LUE) that simulated GPP separately for sunlit and shaded leaves for the period from 1981 to 2012. The results showed that the nationwide annual global radiation experienced a significant reduction (2.18 MJ m⁻² y⁻¹; p < 0.05) from 1981 to 2012, decreasing by 1.3% over this 32-year interval. However, the nationwide annual diffuse radiation increased significantly (p < 0.05). The reduction in global radiation from 1981 to 2012 decreased the average annual GPP of terrestrial ecosystems in China by 0.09 Pg C y⁻¹, whereas the gain in diffuse radiation from 1981 to 2012 increased the average annual GPP in China by about 50%. Therefore, the increase in canopy light use efficiency under higher diffuse radiation only partially offsets the loss of GPP caused by lower global radiation.

Soils in mid-high latitudes are under the great impact of freeze–thaw cycling. However, insufficient research on soil CO₂, CH₄, and N₂O fluxes during the spring freeze–thaw (SFT) period has led to great uncertainties in estimating soil greenhouse gas (GHG) fluxes. The present study was conducted in a temperate broad-leaved Korean pine mixed forest in Northeastern China, where soils experience an apparent freeze–thaw effect in spring. The temporal variations and impact factors of soil GHG fluxes were measured during the SFT period and growing season (GS) using the static-chamber method. The results show that the soil acted as a source of atmospheric CO₂ and N₂O and a sink of atmospheric CH₄ during the whole observation period. Soil CO₂ emission and CH₄ uptake were lower during the SFT period than those during the GS, whereas N₂O emissions were more than six times higher during the SFT period than that during the GS. The responses of soil GHG fluxes to soil temperature (T_s) and soil moisture during the SFT and GS periods differed. During the SFT period, soil CO₂ and CH₄ fluxes were mainly affected by the volumetric water content (VWC) and T_s, respectively, whereas soil N₂O flux was influenced jointly by T_s and VWC. The dominant controlling factor for CO₂ was T_s during the GS, whereas CH₄ and N₂O were mainly regulated by VWC. Soil CO₂ and N₂O fluxes accounted for 97.3% and 3.1% of the total 100-year global warming potential (GWP₁₀₀) respectively, with CH₄ flux offsetting 0.4% of the total GWP₁₀₀. The results highlight the importance of environmental variations to soil N₂O pulse during the SFT period and the difference of soil GHG fluxes between the SFT and GS periods, which contribute to predicting the forest soil GHG fluxes and their global warming potential under global climate change.

As one of the most important renewable and sustainable energy sources, the forest biomass energy resource has always been the focus of attention of scholars and policy makers. However, its potential is still uncertain in China, especially with respect to its spatial distribution. In this paper, the quantity and distribution of Chinese forest biomass energy resources are explored based mainly on forestry statistics data rather than forest resource inventory data used by most previous studies. The results show that the forest biomass energy resource in China was 169 million tons in 2010, of which wood felling and bucking residue (WFBR),wood processing residue (WPR), bamboo processing residue, fuel wood and firewood used by farmers accounted for 38%, 37%, 6%, 4% and 15%, respectively. The highest resource was located in East China, accounting for nearly 39.0% of the national amount, followed by the Southwest and South China regions, which accounted for 17.4% and 16.3%, respectively. At the provincial scale, Shandong has the highest distribution, accounting for 11.9% of total resources, followed by Guangxi and Fujian accounting for 10.3% and 10.2%, respectively. The actual wood-processing residue (AWPR) estimated from the actual production of different wood products (considering the wood transferred between regions) showed apparent differences from the local wood processing residue (LWPR), which assumes that no wood has been transferredbetween regions. Due to the large contribution of WPR to total forestry bioenergy resources, the estimation of AWPR will provide a more accurate evaluation of the total amount and the spatial distribution of forest biomass energy resources in China.

Light use efficiency (LUE) is a key indicator of vegetation photosynthesis, which provides important insights into how vegetation productivity responds to environmental conditions. The photochemical reflectance index (PRI) is based on reflectance at 531 and 570 nm, which reflects the xanthophyll cycle process of plants under different radiation conditions, and makes LUE related to plant optical characteristics. In this study, tower-based PRI and eddy covariance (EC) based LUEs were used to explore the ability of PRI to track LUE variations in a subtropical, evergreen mixed forest in South China. The results indicate that there is a stronger relationship between PRI and LUE, corrected by the bidirectional reflectance distribution function (BRDF), where R² = 0.46 before correction and R² = 0.60 after correction. Generally, PRI is able to capture diurnal and seasonal changes in LUE. Simultaneously, this study highlights a significant correlation between LUE and PRI, but there is also a large seasonal difference in its correlation. The correlation in winter was significantly stronger than summer. The strongest correlation is found in November (R² = 0.91) and the weakest is in July (R² = 0.34). Photosynthetically active radiation (PAR) had a strong influence on the LUE-PRI relationship, while vapor pressure deficit (VPD) and air temperature (Ta) had negative influences on the relationship between LUE and PRI. Terrestrial laser scanning is used to retrieve the vertical structure of forest crown. Our results show that the vegetation canopy structure (i.e., effective leaf area index, LAI_e), extracted from terrestrial laser scanning (TLS) point data in subtropical mixed forests, had a weak influence on LUE. Our research suggests that environmental factors and vegetation canopy structures should be considered when using PRI to accurately estimate LUE.