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As an emerging contaminant, microplastics (MPs) have received considerable attention for their potential threat to the soil environment. However, the response of soil bacterial and fungal communities to MPs exposure remains unclear. In this study, we conducted a global meta-analysis of 95 publications and 2317 observations to assess the effects of nonbiodegradable MP properties and exposure conditions on soil microbial biomass, alpha and beta diversity, and community structure. Our results indicate that MPs increased (p < 0.05) soil active microbial biomass by 42%, with the effect varying with MPs type, exposure concentration, exposure time and soil pH. MPs concentration was identified as the most important factor controlling the response of soil microbial biomass to MPs. MPs addition decreased (p < 0.05) the soil bacterial Shannon and Chao1 indices by 2% and 3%, respectively, but had limited effects (p > 0.05) on soil fungal Shannon and Chao1 indices. The type of MPs and exposure time determined the effects of MPs on bacterial Shannon and Chao1 indices, while the type of MPs and soil pH controlled the response ratios of fungal Shannon and Chao1 indices to MPs. Specifically, soil organic carbon (SOC) was the major factor regulating the response ratio of bacterial alpha diversity index to MPs. The presence of MPs did not affect soil bacterial community structure and beta diversity. Our results highlight that MPs reduced bacterial diversity and richness but increased the soil active microbial biomass, suggesting that MPs could disrupt biogeochemical cycles by promoting the growth of specific microorganisms. • Microplastics (MPs) significantly increased soil active microbial biomass. • MPs increased bacterial Shannon index but had limited effect on fungi. • The effects of MPs on microbial Chao1 index varied depending on MP types. • MPs did not change soil community structure and beta diversity. [ABSTRACT FROM AUTHOR]

The diseases caused by Vibrio during shrimp breeding program have the risk of spreading in different aquatic areas through larvae transportation between different regions. Therefore, the population distribution and the virulence and antibiotic resistance risk of 5 pathogenic Vibrio in shrimp (Penaeus vannamei) breeding system in China were evaluated for the first time. A total of 418 isolates were recovered from shrimp, breeding water and biological baits samples, and 312 isolates were identified as Vibrio genus based on 16s rDNA, among which V. alginolyticus , V. harveyi , V. parahaemolyticus , V. cholerae and V. campbellii were the dominant species. And 10/20 kinds of virulence genes (chiA , luxR , vhh , tlh , chxA , sepro , flaA , vch , VAC and rpoS) were detected among the 5 Vibrio species. Multiple antibiotic resistance (MAR) index of the 5 dominant Vibrio isolates were 0.13–0.88 %, and 36.5 % isolates with MAR < 0.2. But the antibiotic resistance pattern abundance (ARPA) index ranged from 0.25 to 0.56, which indicated the antibiotic phenotypes of Vibrio species in the shrimp breeding system in China were homogeneity. Furthermore, resistance quotients (RQs) calculation results displayed that the dominant Vibrio species in the shrimp breeding system in China showed no or low selection pressure for resistance to cefoperazone/sulbactam, enrofloxacin, ciprofloxacin, fluoroquine, florfenicol, tetracycline and doxycycline. But only 5 resistance genes were detected, which were strA (43.8 %), strB (11.7 %), QnrVC (2.9 %), sul2 (8.8 %) and Int4 (8.8 %), respectively, and the antimicrobial resistance genotypes were not previously correlated with their phenotypes. The relevant research results provide theoretical basis for epizootic tracking in aquatic system in China, and targeting its final risk in aquatic ecosystem and public health perspectives. • The population distribution, virulence and antibiotic resistance risk of Vibrio in shrimp breeding system in China were evaluated for the first time. • Vibrio isolated from shrimp breeding system were representative with typical genetic and metabolic diversity. • Risk assessment of Vibrio in aquatic system revealing its final risk in aquatic ecosystem and public health perspectives. [ABSTRACT FROM AUTHOR]

Understanding and quantifying the impact of elevated tropospheric carbon dioxide concentration (e [CO 2 ]) on methane (CH 4) globally is important for effectively assessing and mitigating climate warming. Paddies and wetlands are the two important sources of CH 4 emissions. Yet, a quantitative synthetic investigation of the effects of e [CO 2 ] on CH 4 emissions from paddies and wetlands on a global scale has not been conducted. Here, we conducted a meta-analysis of 488 observation cases from 40 studies to assess the long-term effects of e [CO 2 ] (ambient [CO 2 ]+ 53–400 μmol mol−1) on CH 4 emissions and to identify the relevant key drivers. On aggregate, e [CO 2 ] increased CH 4 emissions by 25.7% (p < 0.05) from paddies but did not affect CH 4 emissions from wetlands (−3.29%; p > 0.05). The e [CO 2 ] effects on paddy CH 4 emissions were positively related to that on belowground biomass and soil-dissolved CH 4 content. However, these factors under e [CO 2 ] resulted in no significant change in CH 4 emissions in wetlands. Particularly, the e [CO 2 ]-induced abundance of methanogens increased in paddies but decreased in wetlands. In addition, tillering number of rice and water table levels affected e [CO 2 ]-induced CH 4 emissions in paddies and wetlands, respectively. On a global scale, CH 4 emissions changed from an increase (+0.13 and + 0.86 Pg CO 2 -eq yr−1) under short-term e [CO 2 ] into a decrease and no changes (−0.22 and + 0.03 Pg CO 2 -eq yr−1) under long-term e [CO 2 ] in paddies and wetlands, respectively. This suggested that e [CO 2 ]-induced CH 4 emissions from paddies and wetlands changed over time. Our results not only shed light on the different stimulative responses of CH 4 emissions to e [CO 2 ] from paddy and wetland ecosystems but also suggest that estimates of e [CO 2 ]-induced CH 4 emissions from global paddies and wetlands need to account for long-term changes in various regions. • e [CO 2 ] increased paddy CH 4 emissions but did not affect wetland CH 4 emissions. • e [CO 2 ] effects on paddy CH 4 emissions were positively related to that on belowground biomass, methanogens. • Rice tillering numbers affect e [CO 2 ]-induced CH 4 emissions in paddies. • Water table levels affect e [CO 2 ]-induced CH 4 emissions in wetlands. • e [CO 2 ]-induced CH 4 emissions from paddies and wetlands changed over time. [ABSTRACT FROM AUTHOR]