Cunninghamia lanceolata (Lamb.) Hook. (Chinese fir) is one of the main timber species in Southern China, which has a wide planting range that accounts for 25% of the overall afforested area. Moreover, it plays a critical role in soil and water conservation; however, its suitability is subject to climate change. For this study, the appropriate distribution area of C. lanceolata was analyzed using the MaxEnt model based on CMIP6 data, spanning 2041–2060. The results revealed that (1) the minimum temperature of the coldest month (bio6), and the mean diurnal range (bio2) were the most important environmental variables that affected the distribution of C. lanceolata; (2) the currently suitable areas of C. lanceolata were primarily distributed along the southern coastal areas of China, of which 55% were moderately so, while only 18% were highly suitable; (3) the projected suitable area of C. lanceolata would likely expand based on the BCC-CSM2-MR, CanESM5, and MRI-ESM2-0 under different SSPs spanning 2041–2060. The increased area estimated for the future ranged from 0.18 to 0.29 million km², where the total suitable area of C. lanceolata attained a maximum value of 2.50 million km² under the SSP3-7.0 scenario, with a lowest value of 2.39 million km² under the SSP5-8.5 scenario; (4) in combination with land use and farmland protection policies of China, it is estimated that more than 60% of suitable land area could be utilized for C. lanceolata planting from 2041–2060 under different SSP scenarios. Although climate change is having an increasing influence on species distribution, the deleterious impacts of anthropogenic activities cannot be ignored. In the future, further attention should be paid to the investigation of species distribution under the combined impacts of climate change and human activities.

Shear strength is an important mechanical property of soil, as its mechanical function plays critical roles in reducing land degradation and preventing soil erosion. However, shear strength may be affected by vegetation type through changes in the soil and root patterns. To understand the influences of different types of vegetation on shear strength, the soil shear indices of three typical vegetation types (broad-leaved forest, coniferous broad-leaved mixed forest, and grassland) were studied and evaluated at the Fengyang Mountain Nature Reserve, China. We employed a direct shear apparatus to measure the soil shear resistance index. We quantified the soil porosity, moisture content, and composition of particle size to determine the properties of the soil, and a root scanner was used to quantify the root index. The results revealed that there were significant differences in shear resistance indices at the stand level. Between the three vegetation types, the internal friction angle of the broad-leaved forest was the largest and the cohesion was the smallest. The soil moisture content and porosity of the coniferous broad-leaved mixed forest were higher than those of the broad-leaved forest, and the root volume density (RVD/cm³) of the broad-leaved forest was higher than that of the coniferous and broad-leaved mixed forest and grassland. Structural equation modeling results show that the soil particle size and root characteristics indirectly impacted the soil water content by affecting porosity, which finally affected shear strength. In general, there were significant differences in soil properties and plant root indices between the different stands, which had an impact on soil shear strength.

Aims: Changes in root system architecture (RSA) and soil depth affect the root decomposition rate. However, due to soil opacity, many variables of RSA have not been well studied or even measured. Methods: To investigate the effects of soil depth and the characteristics of RSA on the root decomposition rate, soil samples (Soil cores were collected in October 2020 from Cunninghamia lanceolata and Pinus taeda plantations, which were 40 years old) were obtained using a soil auger and had a diameter of 10 cm and a length of 60 cm. Samples were taken from six different soil depths, ranging from 0 to 60 cm with a 10 cm interval between each depth. The RSA in the in-situ soil cores was analyzed using computed tomography scans and Avizo. Results: Root volume and the number of root throats were significantly higher at the 0–10 cm soil depth than at the 10–60 cm soil depth, but root length was significantly lower at the 50–60 cm soil depth (p < 0.05). Structural equation modeling showed that different stand types influenced root biomass and thus the root decomposition rate directly or indirectly through the characteristics of the stand types. RSA, i.e., root thickness and breadth, affected root biomass indirectly and then affected the root decomposition rate. Root biomass contributed the most to the root decomposition rate in the Cunninghamia lanceolata (20.19%) and Pinus taeda (32.26%) plantations. The contribution of the RSA variables to the root decomposition rate exceeded 50% at the 20–30 cm and 40–50 cm soil depths. Conclusions: Our findings suggested that the influence of the RSA variables on the root decomposition rate varies with soil depth. This deserves more consideration in our future studies on root decomposition and RSA.

Fine root decomposition plays a vital role in driving the carbon cycle in terrestrial ecosystems, as it constitutes a substantial part of annual net primary production and, as transient tissues, returns to the soil within relatively short timescales. Soil fungal communities and enzyme activities strongly influence this process. In this study, we used an in situ soil core decomposition method to compare the fine root decomposition rates of Liriodendron chinense (Hemsl.) Sargent, Cunninghamia lanceolata (Lamb.) Hook, and Phyllostachys edulis (Carrière) J.Houz forests over a 1-year period (March 2021–March 2022). We quantified the chemical attributes of fine roots and soil enzymatic activities across different forests, detected fungal communities via ITS rRNA gene sequencing, and forecasted fungal functional groups using the FUNGuild database. The results showed that fine root decomposition was fastest in the Liriodendron chinense (Hemsl.) Sargent forest (77.2%) and the slowest for Cunninghamia lanceolata (Lamb.) Hook (59.2%). Structural equation modeling (SEM) results indicated that the carbon content of fine roots and the functional groups of soil fungi are crucial to fine root decomposition. They not only directly influence fine root decomposition but also promote it through soil enzymatic activities, clearly suggesting that changes in soil enzymatic activities can be employed to explain the ecological effects of the root decomposition process. This study illuminates significant differences in the chemical characteristics of fine roots, soil enzymatic activities, and soil fungal communities among different forest types, all of which significantly affect fine root decomposition.