Potential landslides in the mountainous areas of southwest China pose a serious threat to the lives and property of local residents. Synthetic aperture radar interferometry (InSAR) technology has the advantages of wide coverage, all weather applicability, and low cost and can quickly and accurately identify large range of active landslides, making it a useful geodetic tool for the early identification and prevention of landslides. This paper employed small baseline subset InSAR (SBAS−InSAR) technology and ascending and descending Sentinel−1 data from January 2019 to December 2021 to early identify active landslides in the Maoxian County to Li County National Highway (G317 and G213). The InSAR deformation results were verified by geometric distortion analysis, optical remote sensing interpretation, and field investigation, and 115 active landslides were successfully determined, among which 23 active landslides were identified by ascending and descending Sentinel−1 data together. In addition, InSAR deformation results show that fault, stratigraphic lithology, and rainfall are the three main factors that accelerate the deformation of active landslides and can trigger new active landslides. This study can provide an important reference for the early identification and prevention of landslides in mountainous areas.

Nitrogen (N) deposition has been well documented to cause substantial impacts on ecosystem carbon cycling. However, the majority studies of stimulating N deposition by direct N addition to forest floor have neglected some key ecological processes in forest canopy (e.g., N retention and absorption) and might not fully represent realistic atmospheric N deposition and its effects on ecosystem carbon cycling. In this study, we stimulated both canopy and understory N deposition (50 and 100 kg N ha⁻¹ year⁻¹) with a local atmospheric NH_x:NO_y ratio of 2.08:1, aiming to assess whether canopy and understory N deposition had similar effects on soil respiration (RS) and net ecosystem production (NEP) in Moso bamboo forests. Results showed that RS, soil autotrophic (RA), and heterotrophic respiration (RH) were 2971 ± 597, 1472 ± 579, and 1499 ± 56 g CO₂ m⁻² year⁻¹ for sites without N deposition (CN0), respectively. Canopy and understory N deposition did not significantly affect RS, RA, and RH, and the effects of canopy and understory N deposition on these soil fluxes were similar. NEP was 1940 ± 826 g CO₂ m⁻² year⁻¹ for CN0, which was a carbon sink, indicating that Moso bamboo forest the potential to play an important role alleviating global climate change. Meanwhile, the effects of canopy and understory N deposition on NEP were similar. These findings did not support the previous predictions postulating that understory N deposition would overestimate the effects of N deposition on carbon cycling. However, due to the limitation of short duration of N deposition, an increase in the duration of N deposition manipulation is urgent and essential to enhance our understanding of the role of canopy processes in ecosystem carbon fluxes in the future.

Elevated nitrogen (N) and phosphorus (P) depositions have greatly affected belowground carbon processes in forest ecosystems. However, open questions still remained on the effects of N and P depositions on belowground carbon processes, including soil respiration (RS), its source components—autotrophic respiration (RA) and heterotrophic respiration (RH), and total belowground carbon allocation (TBCA) in Moso bamboo forests—one of the most important forest types with wide distributions in subtropical China. To fill this knowledge gap, a two-year N, P, and NP experiment was conducted in Moso bamboo forests. Results showed that RS, RA, and RH had a strong seasonal variability and were exponentially correlated with soil temperature. N and P depositions did not change RS and RA. However, P deposition increased RH due to the stimulation of microbial activities, indicating a significant soil carbon loss under P deposition. N and P depositions did not affect TBCA. However, NP deposition significantly increased root carbon-use efficiency. Net ecosystem production (NEP) varied from 198 ± 104 to 529 ± 225 g C m⁻² year⁻¹, indicating that Moso bamboo is an important carbon sink. P deposition marginally decreased NEP, while N and NP depositions did not affect NEP, which indicates that N deposition alleviated the suppression of P deposition on NEP. These findings highlight the inconsistent responses of RA, RH, and NEP to N, P, and NP depositions, which should be differently considered to increase the accuracy of predicting belowground carbon dynamics.

Aboveground plant water storage (APWS), the total of water storing in aboveground parts of plant, has the function of sustaining the balance between water loss by transpiration and water gain of root uptake. APWS is also essential for plants and hydrological cycle, particularly for semi-arid areas, where water availability is limited. However, APWS varies spatially due to the heterogeneity of natural areas that are composed of a large variety of vegetation types, and studies on the spatial variability of APWS are quite limited in semi-arid areas. To fill this knowledge gap, we established 55 inventory plots with 36 plots in forests and 19 plots in shrubs to detect the spatial variability of APWS using a Random Forest (RF) algorithm and Sentinel-2 images in Mao County, China. Field observations indicated that APWS varied significantly with ecosystems, with the highest APWS in forests. Regardless of ecosystem type, mean APWS in Mao Country was 117.63 Mg ha-1. 10-fold cross-validation suggested that the RF model could reasonably predict APWS (model efficiency = 0.68, root mean square error = 54 Mg ha-1), enabling to capture the spatial variability of APWS. A robust spatial variability of APWS was observed with the highest APWS in forests located high altitude areas, while the lowest APWS was found in shrubs located in low altitude areas. Total APWS was 3.39×107 Mg across the whole study area, which could be used as a valuable natural resource for the semi-arid area. Our study successfully explored the spatial variability of APWS, suggesting the capability of detecting APWS using Sentinel-2 and providing essential data evidence for environmental protection for semi-arid areas.