Studies have documented many biophysical factors that are correlated with urban forest carbon storage. This urban forest function is also increasingly being promoted as a nature-based solution for cities. While urbanization affects both the structure and function of urban forest ecosystems, quantitative analyses of specific casual drivers of carbon storage in urban versus peri-urban forests are scarce. To address this lack of information, we used field data of random plots located along an urban to rural gradient in Shanghai, China, region-specific biomass equations, and path analysis of commonly studied urban forest socioeconomic and ecological drivers to analyze their effects on above ground tree carbon storage. An urbanization index was also developed to quantitatively differentiate urban from peri-urban sites along the transect. Results show that in both urban and peri-urban forests, percent tree and shrub cover had a significant and positive effect on tree and shrub carbon, but tree and shrub density had an even greater effect. Further, tree and shrub species diversity had no effects on carbon storage, while the effects of species composition on tree and shrub carbon in urban forests was different from those in peri-urban areas. Peri-urban forests also exhibited a significant effect of percent tree and shrub cover on tree and shrub species diversity. This approach, using a path analysis of field and plot data and site-specific dendrometric and urbanization information, can be used to quantitatively identify little explored causal dependences between drivers and ecosystem services without relying exclusively on spatial land cover data often not available in developing countries.

The multi-scale carbon-carbon dioxide (C-CO₂) dynamics of subtropical urban forests and other green and grey infrastructure types were explored in an urbanized campus near Shanghai, China. We integrated eddy covariance (EC) C-CO₂ flux measurements and the Agroscope Reckenholz-Tänikon footprint tool to analyze C-CO₂ dynamics at the landscape-scale as well as in local-scale urban forest patches during one year. The approach measured the C-CO₂ flux from different contributing areas depending on wind directions and atmospheric stability. Although the study landscape was a net carbon source (2.98 Mg C ha⁻¹ yr⁻¹), we found the mean CO₂ flux in urban forest patches was −1.32 μmol m⁻²s⁻¹, indicating that these patches function as a carbon sink with an annual carbon balance of −5.00 Mg C ha⁻¹. These results indicate that urban forest patches and vegetation (i.e., green infrastructure) composition can be designed to maximize the sequestration of CO₂. This novel integrated modeling approach can be used to facilitate the study of the multi-scale effects of urban forests and green infrastructure on CO₂ and to establish low-carbon emitting planning and planting designs in the subtropics.

Shanghai, China, is a city that is relatively representative of various cities in China due to its geographical location and socio-economic dynamics. The role of urban vegetation in the carbon cycle of urban developments in these types of cities is now being studied. We focus on identifying which urban plant community types have a greater influence on CO₂ flux in cities, thus providing a scientific basis for low-carbon urban greening. Based on the eddy covariance (EC) observation system, ART Footprint Tool, plant inventory, and ecological community classification, we show that the CO₂ flux characteristics of different plant communities vary temporally. The carbon sink duration during summer was the longest (up to 10 h) and the carbon sink duration was the shortest during winter (7.5 h). In addition, we discovered that the CO₂ flux contribution rates of different plant community types are distinct. The annual average CO₂ contribution rates of the Cinnamomum camphora-Trachycarpus fortunei community and the Metasequoia glyptostroboides+Sabina chinensis community are 11.88% and 0.93%, respectively. The CO₂ flux contribution rate of the same plant community differs according to season. The CO₂ contribution rate of the Cinnamomum camphora-Trachycarpus fortunei community exhibits local maxima during winter and summer, with a maximum difference of 11.16%. In contrast, the Metasequoia glyptostroboides+Sabina chinensis community has a CO₂ contribution rate of 0.35% during the same period. In general, summer is the season with the lowest CO₂ flux contribution rate of plant communities, and winter is the season with the highest CO₂ flux contribution rate. However, the Cinnamomum camphora+Salix babylonica community and the Cinnamomum camphora+Sabina chinensis community present the opposite pattern. Finally, the diurnal variation characteristics of CO₂ flux in different communities have the same trend, but the peak values differ significantly. Overall, daily CO₂ flux peak value of the Metasequoia glyptostroboides community and the Cinnamomum camphora-Trachycarpus fortunei community indicate that these two plant communities exhibit a strong capacity for CO₂ absorption in the study area. According to these research results, urban greening efforts in subtropical climates can increase the green space covered by the Cinnamomum camphora-Trachycarpus fortunei and the Metasequoia glyptostroboides community types when urban greening, so as to appropriately reduce the CO₂ emitted into the atmosphere.

Carbon storage of urban woody vegetation is crucial for climate change mitigation. Biomass structure and species composition have been shown to be important determinants of carbon storage in woody vegetation. In this study, allometric equations were used to estimate the aboveground carbon storage of urban woody vegetation along an urban–rural transect in Shanghai. A random forest model was developed to evaluate the importance scores and influence of species diversity, canopy cover, species evenness, and tree density on aboveground carbon storage. The results showed that tree density, canopy cover, species diversity, species evenness, and aboveground carbon storage of urban woody vegetation vary with the degree of urbanization and urban–rural environment. In addition, the Bayesian optimization algorithm optimized the random forest model parameters to enhance model accuracy, and good modeling results were demonstrated in the study. The R² was at 0.61 in the testing phase and 0.78 in the training phase. The root mean square errors (RMSEs) were 0.84 Mg/ha of carbon in the testing phase and 0.57 Mg/ha in the training phase, which is indicative of a low error of the optimized model. Tree species diversity, canopy cover, species evenness, and tree density were found to correlate with aboveground carbon storage. Tree density was the most important contributor, followed by species diversity and canopy cover, and species evenness was the least effective for aboveground carbon storage. Meanwhile, the results of the partial dependence analysis indicated the combination of factors most conducive to aboveground carbon storage at a tree density of 2200 trees/ha, canopy cover of 50%, species diversity of 1.2, and species evenness of 0.8 in the transect. The findings provided practical recommendations for urban forest managers to adjust the structure and composition of woody vegetation to increase carbon storage capacity and reduce greenhouse gas emissions.

Methane (CH₄) emissions exert large effects on the global climate. Tree stems are vital sources of emissions in ecosystem CH₄ budgets. This paper reviewed the number of publications, journals, authors, keywords, research hotspots, and challenges. A total of 990 articles from 2006 to 2022 were collected based on the Web of Science database. The intellectual base was analyzed using CiteSpace 6.3.1 and VOSviewer 1.6.20 softwares. The results illustrated a growing trend in the study of tree stem methane emissions. The United States was the most research-active country; however, the most active institution was the Chinese Academy of Sciences in China. The research on stem methane emission by Vincent Gauci, Katerina Machacova, Zhi-Ping Wang, Kazuhiko Terazawa, Kristofer R. Covey, and Sunitha R. Pangala has had a significant impact. Current research indicates that stem CH₄ emissions significantly vary among different tree species and are influenced by leaf type, forest type, tree height, whether the trees are alive or dead, and other environmental conditions (such as soil water content, air temperature, CO₂ fluxes, and specific density). Soil CH₄ fluxes and production by methanogens in heartwood were the primary sources of tree stem methane. Some pectin or cellulose from trees may also be converted into methane. Moreover, methane can be produced and released during the decomposition of deadwood by basidiomycetes. Furthermore, there are some trends and challenges for the future: (1) distinguishing and quantifying emissions from various sources; (2) accurately assessing the impact of floods on methane emissions is crucial, as the water level is the main factor affecting CH₄ emissions; and (3) addressing the limited understanding of the microbial mechanisms of methane production in different tree species and investigating how microbial communities affect the production and emission of methane is vital. These advances will contribute to the accurate assessment of methane emissions from global ecosystems.