Snow amounts and duration are susceptible to climate change and may significantly affect plant diversity and biomass in grassland ecosystems. Yet, the combined effects of grassland use (type and intensity) and snow depth on plant diversity and productivity remain poorly understood. We established two complementary field experiments to explore the mechanisms driving the effects of grassland use (type and intensity) and snow manipulation on plant diversity and productivity in the meadow steppe. An experiment on grassland use type and snow manipulation showed that lower snow cover in winter reduced soil moisture in the snowmelt period, significantly increased the abundance of ammonia-oxidizing archaea and ammonia-oxidizing bacteria, and initiated nitrification earlier, resulting in the loss of soil available nitrogen, and then reduced the aboveground biomass of early grasses. An experiment on grassland mowing intensity and snow manipulation showed that moderate mowing intensity can restrain the loss of grass biomass and soil nutrients and maintain grassland sustainability in winters with less snow. Stochasticity has played a more important role in plant community assembly in higher intensity of grassland use. Based on our results, we recommend that optimal defoliation height can restrain the loss of grass biomass and soil nutrients and maintain grassland sustainability in winters with less snow. This study has potential benefits for optimizing sustainable production and maintaining ecosystem function under winter snowfall changes in the future across large regions of arid and semiarid grasslands. (c) 2024 The Society for Range Management. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Permafrost active layer soils are harsh environments with thaw/freeze cycles and sub-zero temperatures, harboring diverse microorganisms. However, the distribution patterns, assembly mechanism, and driving forces of soil microeukaryotes in permafrost remain largely unknown. In this study, we investigated microeukaryotes in permafrost active layer across the Qinghai-Tibet Plateau (QTP) using 18S rRNA gene sequencing. The results showed that the microbial eukaryotic communities were dominated by Nematozoa, Ciliophora, Ascomycota, Cercozoa, Arthropoda, and Basidiomycota in terms of relative abundance and operational taxonomic unit (OTU) richness. Nematozoa had the highest relative abundance, while Ciliophora had the highest OTU richness. These phyla had strong interactions between each other. Their alpha diversity and community structure were differently influenced by the factors associated to location, climate, and soil properties, particularly the soil properties. Significant but weak distance-decay relationships with different slopes were established for the communities of these dominant phyla, except for Basidiomycota. According to the null model, community assemblies of Nematozoa and Cercozoa were dominated by heterogeneous selection, Ciliophora and Ascomycota were dominated by dispersal limitation, while Arthropoda and Basidiomycota were highly dominated by non-dominant processes. The assembly mechanisms can be jointly explained by biotic interactions, organism treats, and environmental influences. Modules in the co-occurrence network of the microeukaryotes were composed by members from different taxonomic groups. These modules also had interactions and responded to different environmental factors, within which, soil properties had strong influences on these modules. The results suggested the importance of biological interactions and soil properties in structuring microbial eukaryotic communities in permafrost active layer soil across the QTP.

Glaciers, which constitute the world's largest global freshwater reservoir, are also natural microbial repositories. The frequent pandemic in recent years underscored the potential biosafety risks associated with the release of microorganisms from the accelerated melting of glaciers due to global warming. However, the characteristics of pathogenic microorganisms in glaciers are not well understood. The glacier surface is the primary area where glacier melting occurs that is often the main subject of research on the dynamics of pathogenic microbial communities in efforts to assess glacier biosafety risks and devise preventive measures. In this study, high-throughput sequencing and quantitative polymerase chain reaction methods were employed in analyses of the composition and quantities of potential pathogenic bacteria on the surfaces of glaciers in the southeastern Tibetan Plateau. The study identified 441 potential pathogenic species ranging from 215 to 4.39 x 10(11) copies/g, with notable seasonal and environmental variations being found in the composition and quantity of potential pathogens. The highest level of diversity was observed in April and snow, while the highest quantities were observed in October and cryoconite. Host analysis revealed that >70 % of the species were pathogens affecting animals, with the highest proportion of zoonotic pathogens being observed in April. Analysis of aerosols and glacial meltwater dispersion suggested that these microbes originated from West Asia, primarily affecting the central and southern regions of China. Null model analysis indicated that the assembly of potential pathogenic microbial communities on glacier surfaces was largely governed by deterministic processes. In conclusion, potential pathogenic bacteria on glacier surfaces mainly originated from the snow and exhibited significant temporal and spatial variation patterns. These findings can be used to enhance researchers' ability to predict potential biosafety risks associated with pathogenic bacteria in glaciers and to prevent their negative impact on populations and ecological systems.

Plant-associated microbiomes are structured by environmental conditions and plant associates, both of which are being altered by climate change. The future structure of plant microbiomes will depend on the, largely unknown, relative importance of each. This uncertainty is particularly relevant for arctic peatlands, which are undergoing large shifts in plant communities and soil microbiomes as permafrost thaws, and are potentially appreciable sources of climate change feedbacks due to their soil carbon (C) storage. We characterized phyllosphere and rhizosphere microbiomes of six plant species, and bulk peat, across a permafrost thaw progression (from intact permafrost, to partially- and fully-thawed stages) via 16S rRNA gene amplicon sequencing. We tested the hypothesis that the relative influence of biotic versus environmental filtering (the role of plant species versus thaw-defined habitat) in structuring microbial communities would differ among phyllosphere, rhizosphere, and bulk peat. Using both abundance- and phylogenetic-based approaches, we found that phyllosphere microbial composition was more strongly explained by plant associate, with little influence of habitat, whereas in the rhizosphere, plant and habitat had similar influence. Network-based community analyses showed that keystone taxa exhibited similar patterns with stronger responses to drivers. However, plant associates appeared to have a larger influence on organisms belonging to families associated with methane-cycling than the bulk community. Putative methanogens were more strongly influenced by plant than habitat in the rhizosphere, and in the phyllosphere putative methanotrophs were more strongly influenced by plant than was the community at large. We conclude that biotic effects can be stronger than environmental filtering, but their relative importance varies among microbial groups. For most microbes in this system, biotic filtering was stronger aboveground than belowground. However, for putative methane-cyclers, plant associations have a stronger influence on community composition than environment despite major hydrological changes with thaw. This suggests that plant successional dynamics may be as important as hydrological changes in determining microbial relevance to C-cycling climate feedbacks. By partitioning the degree that plant versus environmental filtering drives microbiome composition and function we can improve our ability to predict the consequences of warming for C-cycling in other arctic areas undergoing similar permafrost thaw transitions.

It is generally believed that there is a vegetation succession sequence from alpine marsh meadow to desert in the alpine ecosystem of the Qinghai-Tibet Plateau. However, we still have a limited understanding about distribution patterns and community assemblies of microorganisms' response to such vegetation changes. Hence, across a gradient represented by three types of alpine vegetation from swamp meadow to meadow to steppe, the soil bacterial, fungal and archaeal diversity was evaluated and then associated with their assembly processes, and glacier foreland vegetation was also surveyed as a case out of this gradient. Vegetation biomass was found to decrease significantly along the vegetation gradient. In contrast to irregular shifts in alpha diversity, bacterial and fungal beta diversities that were dominated by species replacement components (71.07-9.08%) significantly increased with the decreasing gradient in vegetation biomass (P < 0.05). These trends of increase were also found in the extent of stochastic bacterial and fungal assembly. Moreover, an increase in microbial beta diversity but a decrease in beta nearest taxon index were observed along with increased discrepancy in vegetation biomass (P < 0.001). Stepwise regression analyses and structural equation models suggested that vegetation biomass was the major variable that was related to microbial distribution and community assembly, and there might be associations between the dominance of species replacements and stochastic assembly. These findings enhanced our recognition of the relationship between vegetation and soil microorganisms and would facilitate the development of vegetation-microbe feedback models in alpine ecosystems.

Understanding drivers of permafrost microbial community composition is critical for understanding permafrost microbiology and predicting ecosystem responses to thaw. We hypothesize that permafrost communities are shaped by physical constraints imposed by prolonged freezing, and exhibit spatial distributions that reflect dispersal limitation and selective pressures associated with these physical constraints. To test this, we characterized patterns of environmental variation and microbial community composition in permafrost across an Alaskan boreal forest landscape. We used null modeling to estimate the importance of selective and neutral assembly processes on community composition, and identified environmental factors influencing ecological selection through regression and structural equation modeling (SEM). Proportionally, the strongest process influencing community composition was dispersal limitation (0.36), exceeding the influence of homogenous selection (0.21), variable selection (0.16) and homogenizing dispersal (0.05) Fe(II) content was the most important factor explaining variable selection, and was significantly associated with total selection by univariate regression (R-2 = 0.14, P = 0.003). SEM supported a model in which Fe(II) content mediated influences of the Gibbs free energy of the organic matter pool and organic acid concentration on total selection. These findings suggest that the dominant processes shaping microbial communities in permafrost result from the stability of the permafrost environment, which imposes dispersal and thermodynamic constraints.