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Charles Darwin posited two alternative hypotheses to explain the success of nonnative species based on their relatedness to natives: nonnative species that are closely related to native species could experience (1) higher invasion success because of an increased probability of habitat suitability (conferred by trait similarity) or (2) lower invasion success due to biotic interference, such as competition and limiting similarity. The paradox raised by the opposing predictions of these two hypotheses has been termed \"Darwin's naturalization conundrum\" (DNC). Using plant communities measured repeatedly across an experimental fire gradient in an oak savanna (Minnesota, USA) over 31 yr, we evaluated the DNC by incorporating taxonomic, functional, and phylogenetic information. We used a \"focal-species\" approach, in which the taxonomic, functional, and phylogenetic structure of species co-occurring with a given nonnative (focal) species in local communities was quantified. We found three main results: first, nonnative species tended to co-occur most with closely related natives, except at the extreme ends of the fire gradient (i.e., in communities with no fire and those subjected to high fire frequencies); second, with increasing fire frequency, nonnative species were functionally more similar to native species in recipient communities; third, functional similarity between co-occurring nonnatives and natives was stable over time, but their phylogenetic similarity was not, suggesting that dynamic external forces (e.g., climate variability) influenced the phylogenetic relatedness of nonnatives to natives. Our results provide insights for understanding invasion dynamics across environmental gradients and highlight the importance of evaluating different dimensions of biodiversity in order to draw stronger inferences regarding species co-occurrence at different spatial and temporal scales.

Fermentation, also known as aging, is vital for enhancing the quality of flue‐cured tobacco leaves (FTLs). Aged FTLs demonstrate high‐quality sensory characteristics, while unaged FTLs do not. Microbes play important roles in the FTL fermentation process. However, the eukaryotic microbial community diversity is poorly understood, as are microbial associations within FTLs. We aimed to characterize and compare the microbiota associated with two important categories, fresh and strong flavor style FTLs, and to reveal correlations between the microbial taxa within them. Based on 16S and 18S rRNA Illumina MiSeq sequencing, the community richness and diversity of prokaryotes were almost as high as that of eukaryotes. The dominant microbes of FTLs belonged to seven genera, including Pseudomonas, Bacillus, Methylobacterium, Acinetobacter, Sphingomonas, Neophaeosphaeria, and Cladosporium, of the Proteobacteria, Firmicutes, and Ascomycota phyla. According to partial least square discriminant analysis (PLS‐DA), Xanthomonas, Franconibacter, Massilia, Quadrisphaera, Staphylococcus, Cladosporium, Lodderomyces, Symmetrospora, Golovinomyces, and Dioszegia were significantly positively correlated with fresh flavor style FTLs, while Xenophilus, Fusarium, unclassified Ustilaginaceae, Tilletiopsis, Cryphonectria, Colletotrichum, and Cyanodermella were significantly positively correlated with strong flavor style FTLs. Network analysis identified seven hubs, Aureimonas, Kocuria, Massilia, Brachybacterium, Clostridium, Dietzia, and Vishniacozyma, that may play important roles in FTL ecosystem stability, which may be destroyed by Myrmecridium. FTL microbiota was found to be correlated with flavor style. Species present in lower numbers than the dominant microbes might be used as microbial markers to discriminate different flavor style samples and to stabilize FTL microbial communities. This research advances our understanding of FTL microbiota and describes a means of discriminating between fresh and strong flavor FTLs based on their respective stable microbiota. In this study, we use 16S and 18S rRNA Illumina MiSeq sequencing data to characterize and compare the microbiota associated with fresh and strong flavor style flue‐cured tobacco leaves and reveal correlations between the microbial taxa within them. Flue‐cured tobacco leaf microbiota are correlated with flavor style, and species present at low numbers within the microbial communities can be used as microbial markers to discriminate between samples of different flavor styles and to stabilize flue‐cured tobacco leaf microbial communities.

Edge disturbance can drive liana community changes and alter liana‐tree interaction networks, with ramifications for forest functioning. Understanding edge effects on liana community structure and liana‐tree interactions is therefore essential for forest management and conservation. We evaluated the response patterns of liana community structure and liana‐tree interaction structure to forest edge in two moist semi‐deciduous forests in Ghana (Asenanyo and Suhuma Forest Reserves: AFR and SFR, respectively). Liana community structure and liana‐tree interactions were assessed in 24 50 × 50 m randomly located plots in three forest sites (edge, interior and deep‐interior) established at 0–50 m, 200 m and 400 m from edge. Edge effects positively and negatively influenced liana diversity in forest edges of AFR and SFR, respectively. There was a positive influence of edge disturbance on liana abundance in both forests. We observed anti‐nested structure in all the liana‐tree networks in AFR, while no nestedness was observed in the networks in SFR. The networks in both forests were less connected, and thus more modular and specialised than their null models. Many liana and tree species were specialised, with specialisation tending to be symmetrical. The plant species played different roles in relation to modularity. Most of the species acted as peripherals (specialists), with only a few species having structural importance to the networks. The latter species group consisted of connectors (generalists) and hubs (highly connected generalists). Some of the species showed consistency in their roles across the sites, while the roles of other species changed. Generally, liana species co‐occurred randomly on tree species in all the forest sites, except edge site in AFR where lianas showed positive co‐occurrence. Our findings deepen our understanding of the response of liana communities and liana‐tree interactions to forest edge disturbance, which are useful for managing forest edge. Edge effects positively and negatively influenced liana diversity in the two forests, and also enhanced liana abundance. Liana‐tree networks were non‐nested, less connected and more specialised and modular, irrespective of edge disturbance. Edge disturbance did not shift the topological roles of most of the lianas, but a few species had their roles changed.

Macroinvertebrates play a vital role in coastal ecosystems and are an important indicator of ecosystem quality. Both anthropogenic activity and environmental changes may lead to significant changes in the marine macroinvertebrate community. However, the assembly process of benthic biodiversity and its mechanism driven by environmental factors at large scales remains unclear. Here, using the benthic field survey data of 15 years at large spatial and temporal scales from the Yellow Sea Large Marine Ecosystem, we investigated the relative importance of environmental selection, dispersal processes, random‐deterministic processes of macroinvertebrates community diversity assembly, and the responses of this relative importance driven by temperature and nutrients. Results showed that the macroinvertebrates community diversity is mainly affected by dispersal. Nitrogen and phosphorus are the most important negative factors among environmental variables, while geographical distance is the main limiting factor of β diversity. Within the range of 0.35–0.70 mg/L of nutrients, increasing nutrient concentration can significantly facilitate the contribution of the decay effect to β diversity. Within the temperature range studied (15.0–18.0°C), both warming and cooling can lead to a greater tendency for species diversity assembly processes to be dominated by deterministic processes. The analysis contributes to a better understanding of the assembly process of the diversity of coastal marine macroinvertebrates communities and how they adapt to global biogeochemical processes. The assembly mechanism of macroinvertebrates diversity in offshore waters is dominated by the dispersal process and random model, and this trend is maintained on a long‐time scale.

Microorganisms dominate marine environments in the polar oceans and are known to harbor greater diversity and abundance than was once thought, and yet, little is known about their biogeographic distribution patterns in marine sediments at a broad spatial scale. In this study, we conducted extensive sampling of marine sediments along a latitudinal transect spanning 2500 km from the Bering Sea to the Arctic Ocean to investigate the geographical distribution patterns of bacteria, archaea, and fungi. Our findings revealed that the community similarities of bacteria and fungi decay at similar rates with increasing geographical distance (slope: −0.005 and −0.002), which are much lower than the decay rate of archaeal communities (slope: −0.012). Notably, microbial richness and community composition showed significant differences in the region of 75−80°N compared to other regions in 60−75°N. Salinity, temperature, pH, ammonium nitrogen, and total organic carbon are key factors that significantly affect microbial community variations. Furthermore, bacterial co‐occurrence networks showed more complex interactions but lower modularity than fungal counterparts. This study provides crucial insights into the spatial distribution patterns of bacteria, archaea, and fungi in the Arctic marine sediments and will be critical for a better understanding of microbial global distribution and ecological functions. Impact statement Understanding the biogeography of marine microbes is essential for grasping biogeochemical cycling and climate regulation. This study on the Arctic marine sediments revealed distinct geographic distribution patterns of bacteria, archaea, and fungi. Archaea showed the strongest distance–decay pattern, while bacteria and fungi showed similar distributions. These findings advance our understanding of benthic microbial biogeography and the mechanisms driving microbial distribution. This knowledge is crucial for predicting microbial responses to rapid Arctic warming and developing strategies to preserve biodiversity and ecological functions, thereby ensuring the stability of marine environments globally.

Disentangling the different processes structuring ecological communities is a long‐standing challenge. In species‐rich ecosystems, most emphasis has so far been given to environmental filtering and competition processes, while facilitative interactions between species remain insufficiently studied. Here, we propose an analysis framework that not only allows for identifying pairs of facilitating and facilitated species, but also estimates the strength of facilitation and its variation along environmental gradients. Our framework combines the analysis of both co‐occurrence and co‐abundance patterns using a moving window approach along environmental gradients to control for potentially confounding effects of environmental filtering in the co‐abundance analysis. We first validate our new approach against community assembly simulations, and exemplify its potential on a large 1,134 plant community plots dataset. Our results generally show that facilitation intensity was strongest under cold stress, whereas the proportion of facilitating and facilitated species was higher under drought stress. Moreover, the functional distance between individual facilitated species and their facilitating species significantly changed along the temperature–moisture gradient, and seemed to influence facilitation intensity, although no general positive or general negative trend was discernible among species. The main advantages of our robust framework are as follows: It enables detecting facilitating and facilitated species in species‐rich systems, and it allows identifying the directionality and intensity of facilitation in species pairs as well as its variation across long environmental gradients. It thus opens numerous opportunities for incorporating functional (and phylogenetic) information in the analysis of facilitation patterns. Our case study indicated high complexity in facilitative interactions across the stress gradient and revealed new evidence that facilitation, similarly to competition, can operate between functionally similar and dissimilar species. Extending the analyses to other taxa and ecosystems will foster our understanding how complex interspecific interactions promote biodiversity. Identifying facilitative interactions in species‐rich systems is a long‐standing challenge. Here, we propose a simple analysis framework that allows identifying pairs of facilitating and facilitated species, estimating the strength of their interaction and its variation along environmental gradients. We validate our approach against community assembly simulations and exemplify its potential on a large plant community dataset. Our results show that although facilitation intensity is strongest under cold stress, the proportion of facilitating and facilitated species is higher under drought stress.

Background Microbial interactions shape the structure and function of microbial communities; microbial co-occurrence networks in specific environments have been widely developed to explore these complex systems, but their interconnection pattern across microbiomes in various environments at the global scale remains unexplored. Here, we have inferred an Earth microbial co-occurrence network from a communal catalog with 23,595 samples and 12,646 exact sequence variants from 14 environments in the Earth Microbiome Project dataset. Results This non-random scale-free Earth microbial co-occurrence network consisted of 8 taxonomy distinct modules linked with different environments, which featured environment specific microbial co-occurrence relationships. Different topological features of subnetworks inferred from datasets trimmed into uniform size indicate distinct co-occurrence patterns in the microbiomes of various environments. The high number of specialist edges highlights that environmental specific co-occurrence relationships are essential features across microbiomes. The microbiomes of various environments were clustered into two groups, which were mainly bridged by the microbiomes of plant and animal surface. Acidobacteria Gp2 and Nisaea were identified as hubs in most of subnetworks. Negative edges proportions ranged from 1.9% in the soil subnetwork to 48.9% the non-saline surface subnetwork, suggesting various environments experience distinct intensities of competition or niche differentiation. 2NmSq7Q5noeLTtkrbKwa4L Video abstract Conclusion This investigation highlights the interconnection patterns across microbiomes in various environments and emphasizes the importance of understanding co-occurrence feature of microbiomes from a network perspective.

Discovering patterns from a set of text or, more generally, categorical data is an important problem in many disciplines such as biomedical research, linguistics, artificial intelligence and sociology. We consider here the well‐known ‘market basket’ problem that is often discussed in the data mining community, and is also quite ubiquitous in biomedical research. The data under consideration are a set of ‘baskets’, where each basket contains a list of ‘items’. Our goal is to discover ‘themes’, which are defined as subsets of items that tend to co‐occur in a basket. We describe a generative model, i.e. the theme dictionary model, for such data structures and describe two likelihood‐based methods to infer themes that are hidden in a collection of baskets. We also propose a novel sequential Monte Carlo method to overcome computational challenges. Using both simulation studies and real applications, we demonstrate that the new approach proposed is significantly more powerful than existing methods, such as association rule mining and topic modelling, in detecting weak and subtle interactions in the data.

Unraveling the dynamics and driving forces of abundant and rare bacteria in response to glacial retreat is essential for a deep understanding of their ecological and evolutionary processes. Here, we used Illumina sequencing datasets to investigate ecological abundance, successional dynamics, and the co-occurrence patterns of abundant and rare bacteria associated with different stages of soil development in the Hailuogou Glacier Chronosequence. Abundant taxa exhibited ubiquitous distribution and tight clustering, while rare taxa showed uneven distribution and loose clustering along the successional stages. Both abundant and rare subcommunities were driven by different factors during assembly: the interactions of biotic and edaphic factors were the main driving forces, although less important for rare taxa than for the abundant ones. In particular, the redundancy analysis and structural equation modeling showed that soil organic C, pH, and plant richness primarily affected abundant subcommunities, while soil N and pH were most influential for rare subcommunities. More importantly, variation partitioning showed that edaphic factors exhibited a slightly greater influence on both abundant (7.8%) and rare (4.5%) subcommunities compared to biotic factors. Both abundant and rare bacteria exhibited a more compact network topology at the middle than at the other chronosequence stages. The overlapping nodes mainly belonged to Proteobacteria and Acidobacteria in abundant taxa and Planctomycetia, Sphingobacteriia, and Phycisphaerae in rare taxa. In addition, the network analysis showed that the abundant taxa exhibited closer relationships and more influence on other co-occurrences in the community when compared to rare taxa. These findings collectively reveal divergent co-occurrence patterns and driving forces for abundant and rare subcommunities along a glacier forefield chronosequence in the eastern Tibetan Plateau.

Soil microorganisms play an important role in maintaining soil quality and function, although the response of soil microbial biodiversity to heavy metals has been extensively investigated, the microbe-microbe associations under the influence of both native plant species and extremely high heavy metal contamination are not well documented. We examined the diversity and composition of microbial communities and the physicochemical properties in the rhizosphere of three native plant species, Carex breviculmis , Buddleja davidii , and Artemisia annua growing on and around a Pb-Zn waste heap with a nearly 100-year history of natural recovery. Both plant species and heavy metals influence soil microbial diversity and composition. C. breviculmis and A. annua showed a prominent advantage in increasing rhizosphere microbial diversity and richness as well as network complexity compared with plant Buddleja davidii at severely contaminated soil, which was mainly related to the accumulation of soil nutrients such as soil organic carbon (SOC), total nitrogen ammonium nitrogen and nitrate nitrogen rather than a reduction in heavy metal concentrations. Moreover, the heavy metal concentration and soil nutrient levels significantly affected the microbial groups affiliated with Proteobacteria, Chloroflexi, Ascomycota, and Basidiomycota, in which those affiliated with Chloroflexi and Ascomycota were positively associated with heavy metals. Soil microbial network on the Pb-Zn waste heap exhibited higher average degree and a higher proportion of positive links than those around the waste heap, and thus soil microbial structure became more complexity and unstable with increasing heavy metal pollution.