The aboveground biomass (AGB) of a forest is an important indicator of the forest’s terrestrial carbon storage and its relation to climate change. Due to the advantage of extensive spatial coverage and low cost, coarse-resolution remote sensing data is the main data source for wall-to-wall mapping of forest AGB at the regional scale. Despite this, improving the accuracy and efficiency of forest AGB estimation is a major challenge. In this study, two optical imageries, Moderate Resolution Imaging Spectroradiometer (MODIS) 500 m imagery and Fengyun-3C Visible and Infrared Radiometer (FY-3C VIRR) 1000 m imagery, were used and compared for forest AGB estimation in Yunnan Province, southwest China. One parametric approach, multiple linear regression (MLR), and two nonparametric approaches, k-nearest neighbor (KNN) and random forest (RF), were applied for the two imagery datasets, respectively. We evaluated the performance of the combination of remote sensing data and modeling approaches by comparing the accuracies and also explored the potential of FY-3C imagery data in forest AGB estimation at the regional scale as it was used for this purpose for the first time. We found that the machine learning models KNN and RF provided better results than MLR. From the three approaches for both MODIS and FY-3C imagery, RF performed best with R² values of 0.84 and 0.81 and RMSE of 23.18 and 23.43, respectively. Estimation of forest AGB based on MODIS was marginally better than the estimation based on FY-3C. FY-3C imagery could therefore be an additional optical remote sensing data source of coarse spatial resolution, comparable to MODIS data which has been widely used for regional forest AGB estimation. Indices related to forest canopy moisture levels from both types of imagery were sensitive to forest AGB. The RF model and MODIS imagery were then applied to map the spatial variation of forest AGB of Yunnan Province. As a result of our study, we determined that Yunnan Province has a total forest AGB of 2123.22 Mt, with a mean value of 58.05 t/ha for forestland in 2016.

The Honghe Hani Rice Terraces represent the coexistence between natural and cultural systems. Despite being listed as a World Heritage Site in 2013, certain natural and anthropogenic factors have changed land use/land cover, which has led to a reduction in the size of the paddy rice area. It is difficult to accurately assess these changes due to the lack of historical maps of paddy rice croplands with fine spatial resolution. Therefore, we integrated a random forest classifier and phenological information to improve mapping accuracy and stability. We then mapped the historical distribution of land use/land cover in the Honghe Hani Rice Terraces from 1989–1991 to 2019–2021 using the Google Earth Engine. Finally, we analyzed the driving forces of land use types in the Honghe Hani Rice Terraces. We found that: (1) forests, shrubs or grasslands, and other croplands could be discriminated from paddy rice during the flooding and transplanting period, and water bodies and buildings could also be discriminated from paddy rice during the growing and harvesting period. (2) Inputting phenological feature data improved mapping accuracy and stability compared with single phenological periods. (3) In the past thirty years, 10.651%, 8.810%, and 5.711% of paddy rice were respectively converted to forests, shrubs or grasslands, and other croplands in the Honghe Hani Rice Terraces. (4) Lower agricultural profits and drought led to problems in identifying the driving mechanisms behind paddy rice distribution changes. This study demonstrates that phenological information can improve the mapping accuracy of rice terraces. It also provides evidence for the change in the size of the rice terrace area and associated driving forces in Southwest China.

Gamma-aminobutyric acid (GABA) significantly affects plant responses to heavy metals in hydroponics or culture media, but its corresponding effects in plant–soil systems remain unknown. In this study, different GABA dosages (0–8 g kg⁻¹) were added to the rhizosphere of Coreopsis grandiflora grown in Cd-contaminated soils. Cd accumulation in the shoots of C. grandiflora was enhanced by 38.9–159.5% by GABA in a dose-dependent approach because of accelerated Cd absorption and transport. The increase in exchangeable Cd transformed from Fe-Mn oxide and carbonate-bound Cd, which may be mainly driven by decreased soil pH rather than GABA itself, could be a determining factor responsible for this phenomenon. The N, P, and K availability was affected by multiple factors under GABA treatment, which may regulate Cd accommodation and accumulation in C. grandiflora. The rhizospheric environment dynamics remodeled the bacterial community composition, resulting in a decline in overall bacterial diversity and richness. However, several important plant growth-promoting rhizobacteria, especially Pseudomonas and Sphingomonas, were recruited under GABA treatment to assist Cd phytoextraction in C. grandiflora. This study reveals that GABA as a soil amendment remodels the rhizospheric environment (e.g., soil pH and rhizobacteria) to enhance Cd phytoextraction in plant–soil systems.

Yunnan Province, as a critical ecological security barrier in China, has long been highly susceptible to drought events. Characterizing the spatiotemporal distributions of drought and identifying its driving factors is crucial. Due to the complexity of drought occurrence, linear correlation analysis alone is insufficient to quantify drought drivers and their interactions. This study used the Standardized Precipitation Evapotranspiration Index (SPEI) as a drought indicator to analyze the spatiotemporal trends of drought across Yunnan and its six major river basins. The geographic detector model (GDM) and random forest (RF) were utilized to quantify the impacts of meteorological, topographical, soil, and human activities on drought, as well as the interactions among these factors. The results showed that 63.61% of the study area exhibits a significant drying trend (p-value < 0.05), with the Jinsha River Basin (JSRB) experiencing the highest frequency of extreme drought events. Precipitation (PRE), temperature, potential evapotranspiration (PET), vapor pressure deficit (VPD), and relative humidity (RH) were identified as the primary controlling factors of drought, with factor interactions displaying nonlinear enhancement effects. PRE plays a dominant role in driving drought across Yunnan, whereas elevation primarily influenced drought severity in the JSRB, Lancang River Basin (LCRB), and Nujiang River Basin (NJRB). The RF-based SPEI prediction model demonstrated superior performance in simulating short-term drought (SPEI_1, R² > 0.931, RMSE < 0.279), particularly in the JSRB (R² = 0.947 RMSE = 0.228). These findings provide a scientific basis for regional water resource management applications and drought early warning systems, offering a robust framework for understanding and mitigating drought impacts in ecologically sensitive regions.

Amid ongoing socio–economic development and natural environmental changes, the paddy rice area within the Honghe Hani Rice Terraces has undergone substantial decline, resulting in significant imbalances within the agroecosystem. This study employs land use change mapping and ecosystem service evaluation models to assess the ecological impacts of land use changes on the agricultural system from 1990 to 2020. The findings reveal that the area of paddy rice decreased by a net total of 36.35 km², representing a 24.83% reduction, with most of this area being converted into forest and cropland. Although forest expansion led to a 16.61% increase in carbon storage, the habitat quality declined overall due to the reduction in paddy rice areas. Specifically, the extent of lower-quality habitat areas expanded by 134.71 km² (30.02%), while soil retention and water yield ecosystem services decreased by 14.43% and 11.74%, respectively. Areas exhibiting extremely high sensitivity to habitat degradation (32.71%), and geological hazards (38.82%) increased markedly, thereby posing substantial risks to the resilience of the terrace system. Conversely, the total area sensitive to soil erosion declined by 48.84%. These results demonstrate that land use change has adversely affected the traditional agroecosystem services of the Honghe Hani Rice Terraces. The study further proposes pathways for the optimization and conservation of traditional agroecosystem functions.