Bamboo forest is characterized by large carbon sequestration capability and it plays an important role in mitigating climate change and global carbon cycling. Previous studies have mostly focused on carbon cycling and carbon stocks in bamboo forest ecosystems, whereas the carbon footprints of bamboo products have not received attention. China is the largest exporting country of bamboo flooring in the world. Estimating the carbon footprint of bamboo flooring is of essential importance for the involved enterprises and consumers to evaluate their own carbon footprints. In this study, we investigated the production processes of bamboo scrimber flooring for outdoor use, a typical bamboo flooring in China. Based on business-to-business (B2B) evaluation method, we assessed CO₂ emission and carbon transfer ratio in each step of the production process, including transporting bamboo culms and producing and packing the products. We found that to produce 1 m³ of bamboo scrimber flooring, direct carbon emissions from fossil fuels during transporting raw materials/semi-finished products, from power consumptions during production, and indirect emissions from applying additives were 30.94 kg CO₂ eq, 143.37 kg CO₂ eq, and 78.34 kg CO₂ eq, respectively. After subtracting the 267.54 kg CO₂ eq carbon stocks in the product from the 252.65 kg CO₂ eq carbon emissions derived within the defined boundary, we found that the carbon footprint of 1 m³ bamboo scrimber flooring was −14.89 kg CO₂ eq. Our results indicated that the bamboo scrimber flooring is a negative carbon-emission product. Finally, we discussed factors that influence the carbon footprint of the bamboo flooring and gave suggestions on carbon emission reduction during production processes. This study provided a scientific basis for estimating carbon stocks and carbon footprints of bamboo products and further expanded knowledge on carbon cycling and lifespan of carbon in the bamboo forest ecosystem.

Soil organic carbon (SOC) strongly contributes to the operation of the global carbon cycling, and topographical factors largely influence its spatial distribution. However, SOC distribution and its leading topographical impact factors in subtropical forest ecosystems (e.g., the Zhejiang Province in China) have received relatively limited attention from researchers. In this study, 255 forest soil samples were collected from the Zhejiang Province to quantify the spatial variation in SOC and impact factors in subtropical forests. The SOC contents over soil profiles were 35.95 ± 22.58 g/kg, 20.98 ± 15.26 g/kg, and 13.77 ± 11.28 g/kg at depths of 0–10 cm, 10–30 cm, and 30–60 cm, respectively. The coefficient variations at different depths were 62.81% (0–10 cm), 72.74% (10–30 cm), and 81.92% (30–60 cm), respectively. SOC content shows a moderate intensity variation in the Zhejiang Province. The nugget coefficients of the SOC content for the three depths were 0.809 (0–10 cm), 0.846 (10–30 cm), and 0.977 (30–60 cm), respectively. Structural factors mainly influence SOC content. SOC content is positively correlated with elevation and slope, and negatively correlated with slope position (p < 0.05). However, the SOC content was negatively correlated with slope in mixed coniferous and broad-leaved forest. The distribution of the SOC content was relatively balanced between different slope positions. However, the differences became obvious when forest types were distinguished. Topographical factors affected the SOC content differently: elevation > slope > slope position. Slope becomes the main influencing factor in 30–60 cm soil. Forest type significantly influenced the SOC content but with a low statistical explanation compared to topographical factors. Topography has different effects on SOC of different forest types in subtropical forests. This reminds us that in future research, we should consider the combination of topography and forest types.

Moso bamboo (Phyllostachys pubescens) has high carbon sequestration potential and plays an important role in terrestrial carbon cycling. Quantifying the temporal change in Moso bamboo forest carbon stocks is important for understanding forest dynamics and global climate change feedback capacity. In 2009, 168 Moso bamboo forest sample plots were established in Zhejiang Province using National Forest Continuous Inventory protocols and enhanced measurements. These plots were revisited and remeasured in 2014. By comparing the two years, culms number in age classes 2 and 4 increased by 12.3% and 82.5%, respectively, while that in age classes 1 and 3 decreased by 14.7% and 0.03%, respectively. The total aboveground culms carbon stocks increased by 2.95 Mg C ha⁻¹ in the sample plots. On average, age classes 2 and 4 contributed 25.5% and 86.7% of the change in total carbon stocks, respectively. The carbon sequestrated by aboveground culms was 0.42 Tg C year⁻¹, accounting for 1.55 Tg CO₂ year⁻¹ in Moso bamboo over an area of 0.78 million hectares in Zhejiang Province. The change in Moso bamboo carbon stocks did not correlate with environmental factors, but significantly increased with increasing culms number and average diameter at breast height (DBH). Our study helps contribute to improvements in Moso bamboo forest management strategies and promote carbon sequestration capacity.

Soil is a crucial contributor to greenhouse gas (GHG) emissions from terrestrial ecosystems to the atmosphere. The reduction of GHG emissions in plantation management is crucial to combating and mitigating global climate change. A 12-month field trial was conducted to explore the effects of different fertilization treatments (control, without fertilizer (CK); biochar-based fertilizer treatment (BFT); chemical fertilizer treatment (CFT); and mixture of 50% BFT and 50% CFT (MFT)) on the soil GHG emissions of a typical bamboo (Pleioblastus amarus (Keng) Keng f.) plantation. The results demonstrated that compared with the CK, BFT reduced the annual cumulative soil N₂O emission by 16.3% (p < 0.01), while CFT and MFT significantly increased it by 31.0% and 23.3% (p < 0.01), respectively. Meanwhile, BFT and MFT increased the annual cumulative soil CH₄ uptake by 5.8% (p < 0.01) and 7.5% (p < 0.01), respectively, while there was no statistically significant difference between CFT and the control. In addition, BFT, CFT, and MFT significantly increased the annual cumulative soil CO₂ emission by 9.4% (p < 0.05), 13.0% (p < 0.01), and 26.5% (p < 0.01). The global warming potential (GWP) of BFT did not change significantly, while CFT and MFT increased the GWP by 13.7% (p < 0.05) and 28.6% (p < 0.05), respectively, compared with the control. Structural equation modeling revealed different treatments affected soil N₂O and CH₄ emission by changing soil labile carbon and labile nitrogen pools. This study suggests utilizing BFT new ideas and strategies for mitigating GHG emissions from soils in subtropical Pleioblastus amarus plantations.

Root system architecture (RSA) refers to the geometric features and topology of the root system. Ground-penetrating radar (GPR) is a possible method of RSA reconstruction. However, because the topology of the root system is not directly accessible by GPR, GPR-based reconstruction must be complemented by manual connection of root points, resulting in limited accuracy. In this study, we used both GPR and direct excavation to obtain 3D coordinates (XYZ coordinates) and diameters of moso bamboo rhizomes on an orthogonal grid. A score function for selecting the best-connected root points was developed using rhizome diameter, depth, extension angle, and measured line spacing, which was then used to recover the topology of discrete root points. Based on the recovered topology, the 3D RSA of the rhizomes was reconstructed using a smoothing function. Based on the excavation data, the reconstructed RSA was generally consistent with the measured RSA, with 78.13% of root points correctly connected. The reconstructed RSA based on GPR data thus provided a rough approximation of the measured RSA, with errors arising due to missing root points and rhizome displacement. The proposed algorithm for reconstructing 3D RSA further enriches the application of ground-penetrating radar to root detection.

The canopy is the direct receiver and receptor of external environmental variations, and affects the microclimate and energy exchange between the understory and external environment. After autumn leaf fall, the canopy structure of different forests shows remarkable variation, causes changes in the microclimate and is essential for understory vegetation growth. Moreover, the microclimate is influenced by the scale effect of the canopy. However, the difference in influence between different forests remains unclear on a small scale. In this study, we aimed to analyze the influence of the scale effect of canopy projection on understory microclimate in three subtropical broad-leaved forests. Three urban forests: evergreen broad-leaved forest (EBF), deciduous broad-leaved forest (DBF), and mixed evergreen and deciduous broad-leaved forest (MBF) were selected for this study. Sensors for environmental monitoring were used to capture the microclimate data (temperature (T), relative humidity (RH), and light intensity (LI)) for each forest. Terrestrial laser scanning was employed to obtain the canopy projection intensity (CPI) at each sensor location. The results indicate that the influence range of canopy projection on the microclimate was different from stand to stand (5.5, 5, and 3 m). Moreover, there was a strong negative correlation between T and RH, and the time for T and LI to reach a significant correlation in different urban forests was different, as well as the time for RH and LI during the day. Finally, the correlation between CPI and the microclimate showed that canopy projection had the greatest effect on T and RH in MBF, followed by DBF and EBF. In conclusion, our findings confirm that canopy projection can significantly affect understory microclimate. This study provides a reference for the conservation of environmentally sensitive organisms for urban forest management.