Distinct Assembly Processes and Determinants of Soil Microbial Communities between Farmland and Grassland in Arid and Semiarid Areas

Spatial Distribution Patterns and Assembly Processes of Abundant and Rare Fungal Communities in Pinus sylvestris var. mongolica Forests

Revealing the biogeography and community assembly mechanisms of soil microorganisms is crucial in comprehending the diversity and maintenance of Pinus sylvestris var. mongolica forests. Here, we used high-throughput sequencing techniques and null model analysis to explore the distribution patterns and assembly processes of abundant, rare, and total fungal communities in P. sylvestris var. mongolica forests based on a large-scale soil survey across northern China. Compared to the abundant and total taxa, the diversity and composition of rare taxa were found to be more strongly influenced by regional changes and environmental factors. At the level of class, abundant and total taxa were dominated by Agaricomycetes and Leotiomycetes, while Agaricomycetes and Sordariomycetes were dominant in the rare taxa. In the functional guilds, symbiotrophic fungi were advantaged in the abundant and total taxa, and saprotrophic fungi were advantaged in the rare taxa. The null model revealed that the abundant, rare, and total taxa were mainly governed by stochastic processes. However, rare taxa were more influenced by deterministic processes. Precipitation and temperature were the key drivers in regulating the balance between stochastic and deterministic processes. This study provides new insights into both the biogeographical patterns and assembly processes of soil fungi in P. sylvestris var. mongolica forests.

Effect of aridity on the β-diversity of alpine soil potential diazotrophs: insights into community assembly and co-occurrence patterns

Microbial diversity plays a vital role in the maintenance of ecosystem functions. However, the current understanding of mechanisms that shape microbial diversity along environmental gradients at broad spatial scales is relatively limited, especially for specific functional groups, such as potential diazotrophs. Here, we conducted an aridity-gradient transect survey from 60 sites across the Tibetan Plateau, the largest alpine ecosystem of the planet, to investigate the ecological processes (e.g., local species pools, community assembly processes, and co-occurrence patterns) that underlie the β-diversity of alpine soil potential diazotrophic communities. We found that aridity strongly and negatively affected the abundance, richness, and β-diversity of soil diazotrophs. Diazotrophs displayed a distance-decay pattern along the aridity gradient, with organisms living in lower aridity habitats having a stronger distance-decay pattern. Arid habitats had lower co-occurrence complexity, including the number of edges and vertices, the average degree, and the number of keystone taxa, as compared with humid habitats. Local species pools explained limited variations in potential diazotrophic β-diversity. In contrast, co-occurrence patterns and stochastic processes (e.g., dispersal limitation and ecological drift) played a significant role in regulating potential diazotrophic β-diversity. The relative importance of stochastic processes and co-occurrence patterns changed with increasing aridity, with stochastic processes weakening whereas that of co-occurrence patterns enhancing. The genera Geobacter and Paenibacillus were identified as keystone taxa of co-occurrence patterns that are associated with β-diversity. In summary, aridity affects the co-occurrence patterns and community assembly by regulating soil and vegetation characteristics and ultimately shapes the β-diversity of potential diazotrophs. These findings highlight the importance of co-occurrence patterns in structuring microbial diversity and advance the current understanding of mechanisms that drive belowground communities.IMPORTANCERecent studies have shown that community assembly processes and species pools are the main drivers of β-diversity in grassland microbial communities. However, co-occurrence patterns can also drive β-diversity formation by influencing the dispersal and migration of species, the importance of which has not been reported in previous studies. Assessing the impact of co-occurrence patterns on β-diversity is important for understanding the mechanisms of diversity formation. Our study highlights the influence of microbial co-occurrence patterns on β-diversity and combines the drivers of community β-diversity with drought variation, revealing that drought indirectly affects β-diversity by influencing diazotrophic co-occurrence patterns and community assembly.

Heterogeneous bacterial communities affected by phytoplankton community turnover and microcystins in plateau lakes of Southwestern China

Both phytoplankton and bacteria are fundamental organisms with key ecological functions in lake ecosystems. However, the mechanistic interactions through which phytoplankton community change and bacterial communities interact remain poorly understood. Here, the responses of bacterial communities to the community structure, resource-use efficiency (RUE), and community turnover of phytoplankton and microcystins (MCs) were investigated in Lake Dianchi, Lake Xingyun, and Lake Erhai of Southwestern China across two seasons (May and October 2020). Among phytoplankton, Cyanobacteria was the dominant species in all three lakes and attained greater dominance in October than in May due to variation in the RUE of nitrogen and phosphorus and environmental changes. The production of MCs, including MC_LR, MC_RR and MC_YR, was the result of the massive Cyanobacteria. Decreases in diversity and increases in heterogeneity were observed in the bacterial community structure. Nutrient levels, environmental factors and MCs (especially MC_YR) jointly affected the bacterial community in lakes, namely its diversity and community assembly. The cascading effects in lakes mediated by environmental conditions, phytoplankton community composition, RUE, community turnover, and MCs on bacterial communities were revealed in this study. These findings underscore the importance of relating phytoplankton community change and MCs to the bacterial community, which is fundamental for better understanding the lake ecosystem functioning and potential risks of MCs.

Weather-driven synergistic water-economy-environment regulation of farmland ecosystems

Farmland ecosystems (FEs) constitute the most important source of food production, and water is one of the most important factors influencing FEs. The amount of water can affect the yield and thus the economic efficiency. Water migration can generate environmental effects through the migration of fertilizers. Interlinkages and constraints exist between the water, economy and environment, which require synergistic regulation. Meteorological elements influence the reference crop uptake amount and thus the water cycle processes and are key drivers of regulation at the water-economy-environment nexus. However, the weather-driven, synergistic water-economy-environment regulation of FEs has not been sufficiently researched. As such, this paper employed a dynamic Bayesian prediction of the reference evapotranspiration (ET_o) and a quantitative characterization of the total nitrogen (TN) and total phosphorus (TP) contents in agricultural crops and soils via field monitoring and indoor experimental analysis. Consequently, multiobjective optimization modeling was conducted to weigh the mutual trade-offs and constraints between water, the economy and the environment. The proposed method was verified via an example involving the modern agricultural high-tech demonstration park in Harbin, Heilongjiang Province, China. The results indicated that (1) the effect of meteorological factors gradually decreased over time, but the prediction results were very accurate, and the higher the delay order of the dynamic Bayesian network (DBN) was, the more accurate the predictions; (2) ET_o was significantly driven by meteorological elements, and the most important meteorological factor influencing ET_o throughout the year was average temperature. When the average temperature was reduced by 10.0 %, ET_o was reduced by 1.4 %, the required amount of irrigation water was reduced by 4.9 %, and the economic benefits of a single cube of water increased by 6.3 %; (3) resource-economy-environment multidimensional synergy enabled a 12.8 % reduction in agricultural ecosystem pollutant emissions, while the economic benefits per unit of water increased by 8.2 % and the system synergy increased by 23.2 %.

Soil microbial community assembly model in response to heavy metal pollution

Heavy metal pollution affected the stability and function of soil ecosystem. The impact of heavy metals on soil microbial community and the interaction of microbial community has been widely studied, but little was known about the response of community assembly to the heavy metal pollution. In this study, we collected 30 soil samples from non (CON), moderately (CL) and severely (CH) contaminated fields. The prokaryotic community was studied using high-throughput Illumina sequencing of 16s rRNA gene amplicons, and community assembly were quantified using phylogenetic-bin-based null approach (iCAMP). Results showed that diversity and composition of both bacterial and archaeal community changed significantly in response to heavy metal pollution. The microbial community assembly tended to be more deterministic with the increase of heavy metal concentration. Among the assembly processes, the relative importance of homogeneous selection (deterministic process) increased significantly (increased by 16.2%), and the relative importance of drift and dispersal limitation (stochastic process) decreased significantly (decreased by 11.4% and 5.4%, respectively). The determinacy of bacterial and archaeal community assembly also increased with heavy metal stress, but the assembly models were different. The deterministic proportion of microorganisms tolerant to heavy metals, such as Thiobacillus, Euryarchaeota and Crenarchaeota (clustered in bin 32, bin59 and bin60, respectively) increased, while the stochastic proportion of microorganisms sensitive to heavy metals, such as Koribacteraceae (clustered in bin23) increased. Therefore, the heavy metal stress made the prokaryotic community be deterministic, however, the effects on the assembly process of different microbial groups differed obviously.