Insights into tolerance mechanisms of earthworms (Eisenia fetida) in copper-contaminated soils by integrating multi-omics analyses.

Earthworms can resist high levels of soil copper (Cu) contamination and play an essential role in absorbing them effectively. However, the molecular mechanisms underlying Cu tolerance in earthworms are poorly understood. To address this research gap, we studied alterations of Eisenia fetida in antioxidant enzymes, gut microbiota, metabolites, and genes under varying levels of Cu exposure soils (0, 67.58, 168.96, 337.92 mg/kg). Our results revealed a reduction in antioxidant enzyme activities across all treatment groups, indicating an adaptive response to alleviate Cu-induced oxidative stress. Analysis of gut microbiota revealed a significant increase in the abundance of bacteria associated with nutrient uptake and Cu2+ excretion under Cu stress. Furthermore, metabolomic analysis discovered an increase in certain metabolites associated with energy metabolism, such as pyruvic acid, L-malic acid, and fumaric acid, as Cu concentration escalated. These results suggested that enhanced energy supply contributes to the elevated tolerance of E. fetida towards Cu. Additionally, transcriptome analysis not only identified crucial detoxification genes (Hsp70, CTSL, GST, CHAC, and GCLC), but also confirmed the critical role of glutathione metabolism as a key pathway in E. fetida Cu detoxification processes. These findings provide a new perspective on the molecular mechanisms of Cu tolerance in earthworms.

Investigating the effects of species niche shifts on the potential distribution of Tuta absoluta (Lepidoptera: Gelechiidae) by using global occurrence data.

Invasive species may occupy quite different environments in their invaded areas to native ones, which may intensively interfere with predicting potential distribution through ecological niche modeling (ENM). Here, we take the tomato leafminer Tuta absoluta Meyrick (Lepidoptera: Gelechiidae), a tomato pest, as an example to investigate this topic. We analyzed niche expansion, stability, unfilling, and Schoener's D by principal component analysis (PCA) ordination method to examine its realized niche shifts and to explore how ENM approaches are affected by niche shifts. We used 5 datasets: Asian, African, European, South American, and global occurrence records in this study. Results showed that high niche unfilling for the species' invaded areas in Asia (20%), Africa (12%), and Europe (37%), possibly due to T. absoluta being in the early stages of invasion. High niche expansion was observed in Asia (38%) and Europe (19%), implying that some European and Asian populations had reached new climatic areas. African niche had the most niche stability (94%) and was equivalent to the native one in climate space (PCA ordination method), but the n-dimensional climate space framework showed that they were different. When projecting the native model to Asia and Europe, the native model performed poorly, implying that the niche shifts affected the transferability of the native model. ENM based on global data outperformed than other models, and our results suggested that T. absoluta has a large potential distribution in Asia, Mexico, South Europe, the United States, and Australia. Meanwhile, we recommend updating ENMs based on the species' invasion stage.

Spatial Distribution and Sustainable Development of Living Woody and Coarse Woody Debris in Warm-Temperate Deciduous Broadleaved Secondary Forests in China.

The investigation into the spatial patterns of living woody (LWD) and coarse woody debris (CWD) in warm-temperate deciduous broadleaved secondary forests serves as a foundational exploration of the mechanisms governing coexistence and mortality in forest ecosystems. The complete spatial randomness null model (CSR) was employed to analyze spatial distribution patterns, with the independent component null model (IC) and canonical correspondence analysis (CCA) utilized to elucidate spatial correlations and topographic influences. All three models were applied to LWD and CWD across various size classes within a 20-hectare plot in the Dongling Mountains. The study's findings indicate that both LWD and CWD predominantly exhibited aggregated patterns, transitioning to a random distribution as the size class increased. Both increasing abundance and maximum diameter at breast height (DBH) also have a significant influence on the distribution of species. Notably, rare species exhibited higher aggregation compared to common and abundant species. The spatial correlation results between LWD and CWD across various size classes predominantly showed positive correlations and uncorrelated patterns within the sampled plots. CCA analysis further revealed that elevation, convexity, slope, and aspect significantly influenced the spatial patterns of LWD and CWD across different size classes. Within the sample site, trees display a tendency to grow and die in clusters. Biotic factors have a more significant influence on species distribution than abiotic factors.