Identifying the mechanisms that shape fungal community and metacommunity patterns in Yunnan, China

Characterization of Microbial Carbon Metabolism in Karst Soils from Citrus Orchards and Analysis of Its Environmental Drivers

Karst regions (KRs) have created significant karst carbon sinks globally through the carbon cycling process involving "water-carbon dioxide-carbonate rock-biota". Soil organic carbon (SOC) represents a crucial component of these carbon sinks. Microorganisms play a vital role in the soil carbon cycle, influencing the formation and preservation of SOC. Therefore, investigating the carbon metabolism of soil microorganisms in KRs is essential for clarifying the unique biogeochemical cycling mechanisms within these regions. In this paper, soils from karst regions (KRs), mixed regions (MRs) and non-karst regions (NKRs) were collected from citrus orchards in Mao Village, Karst Experimental Field, Guilin City, Guangxi Zhuang Autonomous Region, China. The ability to use different carbon sources was analyzed by Biolog-Eco microtiter plate technique; the number of microorganisms was detected by the plate colony counting method, and the microbial biomass was determined by the chloroform fumigation method. The results showed that the soil bacterial number (5.69 ± 0.39 × 106 CFU/g), microbial biomass carbon (MBC) (608.24 ± 63.80 mg/kg), microbial quotient (SMQ) (3.45 ± 0.18%), and Shannon's index (H') (3.28 ± 0.05) of the KR were significantly higher than those of the NKR. The pH showed a significant positive correlation (p < 0.05) with the bacterial number and H' (p < 0.05); SOC showed a highly significant positive correlation with bacterial number (p < 0.01), and a significant positive correlation with MBC, H', and average well change development (AWCD) (p < 0.05). Total nitrogen (TN) showed a significant positive correlation with MBC (p < 0.05); available potassium (AK) showed a significant positive correlation with bacterial number and MBC (p < 0.05). Exchangeable calcium (Ca2+) demonstrated significant positive correlations with bacterial number, MBC, and H' (p < 0.05). The above results indicate that soil bacterial number, carbon metabolic ability and diversity were highest in the KR. pH, SOC and exchangeable Ca2+ were the main influencing factors for the differentiation of soil microbial carbon metabolic diversity between the KR and NKR.

Comparative analyses of sooty mould communities from Brazil and Central Europe

To gain an insight into fungal sooty mould communities on leaves of trees and shrubs in the tropics and in temperate regions, 47 biofilms of the Mata Atlântica rainforest relic and the Caatinga vegetation in the state of Sergipe, Northeast Brazil, and from Central European colline and alpine zones were compared. The four sampling sites clearly differed in composition of their epiphyllous fungal communities. The fungal OTUs from all sites belonged mainly to the Ascomycota, with Dothideomycetes being the dominant class. The core community group consisted of a few site-specific representatives in co-occurrence with the ubiquitous Mycosphaerella tassiana and Aureobasidium pullulans. Most species of the core community were dark pigmented and were accompanied by facultative unpigmented or lightly pigmented species. Among the cultivable fungal species, the proportion of melanised species was significantly more abundant in samples from the two European sites, which supports the theory of thermal melanism. The identity of the host plant had a stronger impact on fungal community composition than the presence of sap-feeding insects.

How Mycorrhizal Associations Influence Orchid Distribution and Population Dynamics

Orchid distribution and population dynamics are influenced by a variety of ecological factors and the formation of holobionts, which play key roles in colonization and ecological community construction. Seed germination, seedling establishment, reproduction, and survival of orchid species are strongly dependent on orchid mycorrhizal fungi (OMF), with mycorrhizal cheating increasingly observed in photosynthetic orchids. Therefore, changes in the composition and abundance of OMF can have profound effects on orchid distribution and fitness. Network analysis is an important tool for the study of interactions between plants, microbes, and the environment, because of the insights that it can provide into the interactions and coexistence patterns among species. Here, we provide a comprehensive overview, systematically describing the current research status of the effects of OMF on orchid distribution and dynamics, phylogenetic signals in orchid-OMF interactions, and OMF networks. We argue that orchid-OMF associations exhibit complementary and specific effects that are highly adapted to their environment. Such specificity of associations may affect the niche breadth of orchid species and act as a stabilizing force in plant-microbe coevolution. We postulate that network analysis is required to elucidate the functions of fungal partners beyond their effects on germination and growth. Such studies may lend insight into the microbial ecology of orchids and provide a scientific basis for the protection of orchids under natural conditions in an efficient and cost-effective manner.

Amplicon sequencing dataset of soil fungi and associated environmental variables collected in karst and non-karst sites across Yunnan province, southwest China

Fungi are among the most widely distributed organisms on Earth, performing key roles in nutrient cycling, disease, and the global carbon cycle. However, studies on regional-scale fungal assemblage patterns and the underlying drivers, are scarce. The aim of this research was to determine the relative importance of environmental heterogeneity and spatial distance on the metacommunity structure of soil fungi in Yunnan province, southwest China. This dataset is supplementary to research by [1] and presents 12,843 fungal operational taxonomic unit (OTU) sequences, OTU distribution and abundance across 220 samples, OTU taxonomic and ecological annotations, and environmental characteristics of the sites where the samples were collected. Differences in fungal alpha and beta diversity indices between karst and non-karst soils for the full dataset, six class-level (Agaricomycetes, Dothideomycetes, Sordariomycetes, Leotiomycetes, Tremellomycetes, and Eurotiomycetes) and four functional-level (symbiotrophs, pathotrophs, saprotrophs, and ectomycorrhizal fungi) datasets are presented.