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.

Understanding the spatiotemporal patterns and variations in vapor pressure deficit (VPD) is essential for effective water resource management in the face of climate change. VPD serves as a fundamental indicator of atmospheric dryness, directly impacting plant evapotranspiration rates, thereby affecting overall ecosystem functioning. In this study, VPD changes in five subregions and four ecological types of land in Yunnan from 1980 to 2021 were investigated using data from 108 meteorological stations. We found increasing trends in annual VPD that were larger during warmer spring and summer seasons. Among the subregions, the highland subtropical southern broadleaved evergreen forest ecoregion exhibited the largest drying trend (0.04 kPa / decade), while the subtropical (eastern) humid broadleaved evergreen forest ecoregion had the smallest drying trend (0.01 kPa / decade). Among the ecological barriers, the dry-hot valleys had significantly higher increases in VPD compared to other Yunnan regions. Increases in VPD from 1990s to 2000s in several regions of Yunnan exceeded atmospheric drying trends reported elsewhere. Additionally, we documented smaller VPD declines at higher elevations. Across different ecological land types, Shrubland exhibited the largest VPD trend (0.07 kPa / decade), while Forest displayed the smallest (0.03 kPa / decade). Decreased relative humidity through time explained 65% of the increase in VPD in Yunnan, while increasing temperatures accounted for 25%. These findings provide valuable insights into climatic dynamics of Yunnan, with implications for ecological, hydrological, and atmospheric studies.

Earthworms are widely used as biological indicators of soil contamination and are often referred to as the ‘intestine of the soil’; however, their effectiveness can vary across regions and environmental conditions. The performance of earthworms as indicators of soil pollution may vary among regions, and there is a need to assess their reliability under specific environmental conditions. So, in this study, soil and earthworm samples were collected from 19 locations across Punjab, Pakistan, to assess heavy metal pollution and bioaccumulation using geoaccumulation indices (Igeo) and bioaccumulation factors (BAF). Soil and earthworm tissues were digested and analyzed for heavy metals such as Sr, Zn, Ca, Cu, Fe, Mn, Co, Cr, Pb, Cd and Ni using ICP-MS. According to Igeo, cadmium frequently classified soils as strongly to extremely polluted, with values up to 4.5 in Bahawalnagar, whereas most other metals fell within the unpolluted to moderately polluted classes. Earthworms showed clear bioaccumulation (BAF > 1) for several essential or poorly regulated elements, particularly Ca, Mn, Cu and Sr; the maximum BAF for Ca reached 8.18 in Faisalabad. In contrast, group-1 carcinogenic metals (Pb, Cd and Cr) generally did not exhibit strong bioaccumulation. Relationships between BAF and soil metal concentrations or abiotic properties (moisture, pH, electrical conductivity, total dissolved and suspended solids) were generally weak (R² typically ≤ 0.32), indicating that these factors explain only a modest fraction of the variation in metal uptake. Overall, the results highlight cadmium as the primary soil contamination risk in the surveyed areas. Because bioaccumulation showed weak relationships with soil metal concentrations and physicochemical parameters, earthworms in this study demonstrated limited effectiveness as bioindicators of toxic heavy metal accumulation. The limited internal accumulation of highly toxic metals suggests possible physiological regulation or tolerance, although the long-term ecological implications require further investigation. Further controlled studies are necessary to better evaluate their ecological role and potential applications in soil remediation, waste management, and vermicompost production.