Zhihong Lu

The synergistic effects of soil acidification and heavy metal pollution present major challenges for global agroecosystems. To systematically trace the evolution of research and identify key topics in this field, this study employed CiteSpace to visualize and analyze 691 records from the China National Knowledge Infrastructure (CNKI) and 6747 highly relevant articles or reviews from the Web of Science (WOS) Core Collection database from 2005 to 2025. The results indicate a steady to rapid rise in global publications, with China contributing the largest share, at 2468 publications. This has produced a research cluster centered around the Chinese Academy of Sciences (CAS); however, the centrality of its international cooperation remains limited. Studies in the CNKI database are driven by agricultural needs, focusing on national food security, rice yield stability, improvement of arable land, and heavy metal passivation and remediation, with a concentration on basic agricultural science. By contrast, research in the WOS database emphasizes fundamental mechanisms and interdisciplinary integration, addressing aluminum toxicity, microbial communities, the nitrogen cycle, and global climate change, intersecting fields such as environmental science, soil science, ecology, and microbiology. The evolution of research hotspots shows a clear trajectory: from acidity regulation and chemical speciation analysis of heavy metals (2005–2013), to heavy metal passivation, remediation, and phytoremediation (2014–2018), and then to biochar materials, microbiome analysis, and the synergistic role of carbon sequestration (2019–2025). This study argues that future research should move beyond single remediation measures and adopt integrated strategic management to jointly improve bioremediation efficiency, promote soil carbon sequestration and soil health, and enhance microbial adaptation to global climate change.

Rice grain is a primary dietary source of cadmium (Cd), a heavy metal toxic to humans. Reducing Cd accumulation in rice through selecting and breeding low-Cd-accumulating cultivars is very important. However, field-based screening for low-Cd rice cultivars remains labor-intensive and time-consuming. In this study, we identified molecular marker genotypes that can distinguish high- and low-Cd-accumulating rice cultivars. We developed corresponding genotypes for marker-assisted selection of low-Cd cultivars in both early and late rice varieties. Fifty-nine locally adapted, high-yielding early rice cultivars and thirty-seven locally adapted, high-yielding late rice cultivars were grown in two fields with different soil Cd levels and genotyped using molecular markers associated with grain Cd accumulation. We identified five early rice cultivars that consistently showed low Cd accumulation, with grain Cd concentrations below the food safety threshold of 0.2 mg kg⁻¹ across two paddy fields. For early rice, we developed two low-Cd combined molecular marker genotypes (Multi-LCL1 and Multi-LCL2) that had significantly lower grain Cd content compared to Multi-LCL3 and Multi-LCL4. For late rice, the low-Cd combined molecular marker genotype Multi-CL1 showed substantially reduced grain Cd levels relative to Multi-CL2-CL5. These findings suggest that the combined molecular marker genotypes Multi-LCL1/LCL2 for early rice and Multi-CL1 for late rice are practical tools for quickly identifying cultivars with low Cd accumulation potential.

With irrigation using waste water, application of sewage sludge, and development of mine exploration, copper (Cu) contamination in some paddy fields has become increasingly serious. A greenhouse pot experiment was conducted using a factorial design with three sulfur (S) application rates (i.e., 0, 0.013, and 0.026 g S kg⁻¹ soil) and three silicon (Si) application rates (i.e., 0, 0.05, and 0.1 g Si kg⁻¹ soil) to test the effect of co-amendment of S and Si on alleviating Cu contamination in paddy soil. There were significant interaction effects between S and Si on soil Cu speciation and Cu uptake by rice plants (except brown rice). Sulfur addition decreased the content of soil-exchangeable Cu, whereas Si addition decreased the content of soil-reducible Cu, suggesting that co-amendment of S and Si generally reduced Cu availability. Copper was biominimized in the soil-rice plant system and rice root had the greatest Cu concentration (163–285 mg kg⁻¹). Co-amendment of S and Si decreased the translocation of Cu from soil to rice root, possibly due to decreased soil Cu mobility and enhancement of the formation of iron plaque on rice root. Co-amendment of S-Si at a rate of 0.013 (S)–0.1 (Si) g kg⁻¹ soil, respectively, was the optimal among all treatments.

Quantifying the impacts of multiple factors on surface runoff and base flow is essential for understanding the mechanism of hydrological response and local water resources management as well as preventing floods and droughts. Despite previous studies on quantitative impacts of multiple factors on runoff, there is still a need for assessment of the influence of these factors on both surface runoff and base flow in different temporal scales at the watershed level. The main objective of this paper was to quantify the influence of precipitation variation, evapotranspiration (ET) and vegetation restoration on surface runoff and base flow using empirical statistics and slope change ratio of cumulative quantities (SCRCQ) methods in Pengchongjian small watershed (116°25′48″–116°27′7″ E, 29°31′44″–29°32′56″ N, 2.9 km²), China. The results indicated that, the contribution rates of precipitation variation, ET and vegetation restoration to surface runoff were 42.1%, 28.5%, 29.4% in spring; 45.0%, 37.1%, 17.9% in summer; 30.1%, 29.4%, 40.5% in autumn; 16.7%, 35.1%, 48.2% in winter; and 35.0%, 38.7%, 26.3% in annual scale, respectively. For base flow they were 33.1%, 41.9%, 25.0% in spring; 39.3%, 51.9%, 8.8% in summer; 40.2%, 38.2%, 21.6% in autumn; 24.3%, 39.4%, 36.3% in winter; and 24.4%, 47.9%, 27.7% in annual scale, respectively. Overall, climatic factors, including precipitation and ET change, affect surface runoff generation the most, while ET affects the dynamic change of annual base flowthe most. This study highlights the importance of optimizing forest management to protect the water resource.