An in-depth understanding of the dominant factors controlling soil respiration is important to accurately estimate carbon cycling in forest ecosystems. However, information on variations in soil respiration at different soil depths and the influencing factors in forest is limited. This study examined the variations in soil respiration at two soil depths (0–10 and 10–20 cm) as well as the effects of soil temperature, soil water content, litter removal, and root cutting on soil respiration in three typical forest types (i.e., Pinus tabulaeformis Carrière, Platycladus orientalis (L.) Franco, and Quercus variabilis Bl.) in the mountainous area of north China from March 2013 to October 2014. The obtained results show that soil respiration exhibited strong seasonal variation and decreased with soil depth. Soil respiration was exponentially correlated to soil temperature, and soil respiration increased with soil water content until reaching threshold values (19.97% for P. tabulaeformis, 16.65% for P. orientalis, and 16.90% for Q. variabilis), followed by a decrease. Furthermore, interactions of soil temperature and water content significantly affected soil respiration at different soil depths of forest types, accounting for 68.9% to 82.6% of the seasonal variation in soil respiration. In addition to soil temperature and water content, aboveground litter and plant roots affected soil respiration differently. In the three forest types, soil respiration at two soil depths decreased by 22.97% to 29.76% after litter removal, and by 44.84% to 53.76% after root cutting. The differences in soil respiration reduction between the two soil depths are largely attributed to variations in substrate availability (e.g., soil organic content) and soil carbon input (e.g., litter and fine root biomass). The obtained findings indicate that soil respiration varies at different soil depths, and suggest that in addition to soil temperature and water content, soil carbon input and dissolved organic substances may exert a strong effect on forest soil respiration.

Concern for the offsite impact of eroded sediment and the need to develop effective catchment sediment management strategies has directed attention to the need for an improved understanding of the primary sediment sources within catchments and the potential of sediment source fingerprinting techniques to provide such information. The study reported here was undertaken in the black soil region of Northeast China, where soil erosion is seen as a serious threat to the sustainable use of soil resources and offsite impacts of eroded soil are also concerned. The study applies source fingerprinting techniques to the evaluation of sediment sources in a small (3.46 km²) agricultural catchment. Sediment sources from five snowmelt and five rainfall events of varying magnitude were contrasted. Three key potential sediment sources were identified within the study catchment: gullies, cultivated topsoil and uncultivated topsoil. Geochemical properties of the source materials (Ti, Ga, Br and Ba) were used as composite fingerprints capable of discriminating between the three potential sources. A mixing model, optimized using a genetic algorithm and coupled with a Monte Carlo procedure to quantify the uncertainty associated with the resulting estimates, was used for source apportionment. The results indicated mean source contributions for the set of 10 events for cultivated topsoil, uncultivated topsoil and the gullies of ~30%, ~10% and ~60%, respectively. In general, snowmelt and rainfall events were characterized by increased contributions from gully sources and cultivated topsoil, respectively. The study is seen as demonstrating the potential for using source tracing techniques to investigate sediment sources in environments where strong seasonal contrasts between snowmelt and rainfall events exist.

Land-use systems (LUSs) and soil types (STs) are strongly related to factors that influence soil degradation and carbon (C) loss. However, the way in which land use and soil type affects the soil organic C (SOC) pools, and soil aggregation in the Sanjiang Plain, has not been thoroughly investigated. Therefore, this study aimed to investigate soil physic–ochemical properties, soil aggregates, and C management index (CMI) in three different LUSs (grassland, dryland, and paddy field) under two STs (meadow soil and albic soil) of the Sanjiang Plain in northeast China. A total of 60 composite soil samples were collected for laboratory analyses. The results were as follows: soil properties were affected by LUS and ST, especially soil chemical properties; ST had no significant effect on soil aggregates but significantly affected its SOC content, while LUS had a significant effect on soil aggregates (p < 0.01), except for small macro-aggregates (2–0.25 mm); the mean weight diameter (MWD) and SOC in meadow soil was significantly different under different land uses, with grassland being the highest and dryland the lowest. However, there was no significant difference in albic soil. The heterogeneity of grassland, dryland, and paddy field showed that different LUSs had particular effects on SOC and its active components because LUS had significant effects on C pool index (CPI) and CMI, but ST and its interaction had no significant effects on CPI and CMI. Overall, the results showed that LUS was an important factor affecting CMI in the Sanjiang Plain, rather than ST, and the paddy field CMI was optimal in the Sanjiang Plain.

Non-homogeneous soil’s high gravel content (also known as the “soil-rock dual structure”) may render it more prone to erosion and the significant development of gullies. In order to reveal the morphological characteristics and erosion rate of gullies in “soil-rock dual structure” areas, this study focused on the Shagou Reservoir basin in the Yimeng mountain area as the study area. Based on a complete digital orthophoto map (DOM, 0.03 m) and a digital elevation model (DEM, 0.03 m) acquired by an unmanned aerial vehicle (UAV), the researchers calculated the length (L), top width (TW), depth (D), area (A) and volume (V) of 19 gullies and built and optimized the volume estimation model. The DOM and the DEM were used to modify the morphological parameters of 43 gullies extracted from high-resolution remote sensing (RS) stereopair images (Worldview, 0.5 m), and the development and evolution of gully erosion were evaluated in large scale. The results showed that: (1) after correction, the average relative errors of parameters L, TW, D and A computed from the UAV data and the high-resolution RS stereopair image data fell below 0.005%; (2) the mean of TW/D was 5.20, i.e., the lateral erosion development of gullies far outweighed the downcutting erosion. The retrogressive erosion, lateral erosion and downcutting erosion rates of gullies were 0.01~0.83 m/a (averaged at 0.23 m/a), 0.01~0.68 m/a (averaged at 0.25 m/a) and 0.01~0.19 m/a (averaged at 0.09 m/a), respectively, between 2014 and 2021; (3) the volume-area (V-A) model for gullies is the optimal one (p < 0.01, R² = 0.944).A total of 90.7% of the gully volume was growing at an erosion rate of 0.42~399.39 m³/a and the total erosion rate of the gullies was 3181.56 m³/a from 2014 to 2021. These research findings can serve as a basis for the quantitative modeling of gully erosion in water-eroded locations with a large-dimension “soil-rock dual structure”.