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Soil microorganisms play a crucial role in suppressing soil-borne diseases. Although the composition of microbial communities in healthy versus diseased soils is somewhat understood, the interplay between microbial interactions and disease incidence remains unclear. This study used 16S rRNA and fungal internal transcribed spacer (ITS) sequencing to investigate the bacterial and fungal community composition in three soil types: forest soil (Z), soil from healthy banana plantations (H), and soil from diseased banana plantations (D). Principal coordinate analysis revealed significant differences among the bacterial and fungal community structures of the three soil types. Compared with those in forest soil, bacterial and fungal diversities significant ly decreased in diseased banana soil. Key microorganisms, including the bacteria Chloroflexi and Pseudonocardia and the fungi Mortierellomycota and Moesziomyces, were significantly increased in soil from diseased banana plantations. Redundancy analysis revealed that total nitrogen and available phosphorus were the primary drivers of the soil microbial community structure. The neutral community model posited that the bacterial community assembly in banana plantations is predominantly governed by stochastic processes, whereas the fungal community assembly in banana plantations is primarily driven by deterministic processes. Furthermore, co-occurrence network analysis revealed that the proportion of positive edges in the fungal network of soil from diseased banana plantations was 5.92 times lower than that in soil from healthy banana plantations, and its fungal network structure was sparse and simple. In conclusion, reduced interactions within the fungal network were significantly linked to the epidemiology of Fusarium wilt. These findings underscore the critical role of soil fungal communities in modulating pathogens. [ABSTRACT FROM AUTHOR]

Anthropogenic perturbations make negative effects on wetland ecosystems, such as increasing levels of eutrophication. Under variable environmental conditions, studying the processes and mechanisms underlying their spatial distribution is critical to biogeochemical significance of microorganisms. In order to understand the changes in sediment bacterial community and their assembly with long-term eutrophication of the Baiyangdian Lake of China, we explored the microbial communities for 24 surface sediment samples using high throughput sequencing of V3-V4 region of 16S rRNA gene, meanwhile we employed Neutral community model (NCM) to characterize the community assembly processes. Then, the β-nearest taxon index (βNTI) based on a null model was used to provide a quantitative description of the assembly processes of the bacterial community. Dispersal limitation, quantified by βNTI, accounted for ∼64.6% of all assembly processes. As the increasing levels of eutrophication, deterministic processes of bacterial community assembly may be enhanced. Moreover, the significant correlation between the βNTI and change in water NO 3 − or sediment pH might lead to deterministic processes. There was some selection pressure acting within the Baiyangdian lake sediments. The neutral community model properly explained bacterial community assembly. The NO 3 −, NH 4 +, pH and EC were main influencing factors on the composition of the bacterial community. The overlying water NO 3 −, surface water NO 3 − and sediment pH were the three most crucial environmental factors to drive bacterial assembly. The findings revealed that Group 4 with relatively stronger deterministic processes as a more eutrophic area should be monitored as an indicator for eutrophication governance. [ABSTRACT FROM AUTHOR]

Disentangling the assembly mechanisms controlling community composition, structure, distribution, functions, and dynamics is a central issue in ecology. Although various approaches have been proposed to examine community assembly mechanisms, quantitative characterization is challenging, particularly in microbial ecology. Here, we present a novel approach for quantitatively delineating community assembly mechanisms by combining the consumer-resource model with a neutral model in stochastic differential equations. Using time-series data from anaerobic bioreactors that target microbial 16S rRNA genes, we tested the applicability of three ecological models: the consumer-resource model, the neutral model, and the combined model. Our results revealed that model performances varied substantially as a function of population abundance and/or process conditions. The combined model performed best for abundant taxa in the treatment bioreactors where process conditions were manipulated. In contrast, the neutral model showed the best performance for rare taxa. Our analysis further indicated that immigration rates decreased with taxa abundance and competitions between taxa were strongly correlated with phylogeny, but within a certain phylogenetic distance only. The determinism underlying taxa and community dynamics were quantitatively assessed, showing greater determinism in the treatment bioreactors that aligned with the subsequent abnormal system functioning. Given its mechanistic basis, the framework developed here is expected to be potentially applicable beyond microbial ecology.

The assembly of rhizosphere microbial communities is essential for maintaining plant health, yet it is influenced by a wide range of biotic and abiotic factors. The key drivers shaping the composition of these communities, however, remain poorly understood. In this study, we analyzed 108 plant samples and evaluated root traits, plant growth characteristics, soil enzyme activities, rhizosphere metabolites, and soil chemical properties to identify the primary determinants of rhizosphere community assembly. Across 36 soil samples, we obtained 969,634 high-quality sequences, clustering into 6,284 ASVs predominantly classified into Proteobacteria (57.99%), Actinobacteria (30%), and Bacteroidetes (5.13%). Our findings revealed that rhizosphere metabolites accounted for more variance in microbial community composition compared to chemical properties (ANOVA, F = 1.53, p = 0.04), enzyme activities, or root traits (ANOVA, F = 1.04, p = 0.001). Seven small molecule metabolites, including glycerol, sorbitol, phytol, and alpha-ketoglutaric acid, were significantly correlated with βNTI, underscoring their role as critical drivers of microbial community assembly. The genus Rhizobium, significantly associated with βNTI (R = 0.25, p = 0.009), emerged as a keystone taxon shaping community structure. Soil culture experiments further validated that small molecule metabolites can modulate microbial community assembly. The ST treatment, enriched with these metabolites, produced 1,032,205 high-quality sequences and exhibited significant shifts in community composition (Adonis, p = 0.001, R = 0.463), with Rhizobium showing higher abundance compared to the control (CK). Variable selection (βNTI >2) drove phylogenetic turnover in ST, while stochastic processes (|βNTI|

Environmental heterogeneity partly drives microbial succession in arthropods, while the microbial assembly mechanisms during environmental changes remain largely unknown. Here, we explored the temporal dynamics and assembly mechanisms within both bacterial and fungal communities in Liriomyza huidobrensis (Blanchard) during the transition from field to laboratory conditions. We observed a decrease in bacterial diversity and complexity of bacterial-fungal co-occurrence networks in leaf miners transitioning from wild to captive environments. Both neutral and null models revealed that stochastic processes, particularly drift (contributing over 70%), play a crucial role in governing bacterial and fungal community assembly. The relative contribution of ecological processes such as dispersal, drift, and selection varied among leaf miners transitioning from wild to captive states. Furthermore, we propose a hypothetical scenario for the assembly and succession of microbial communities in the leaf miner during the short- and long-term transition from the wild to captivity. Our findings suggest that environmental heterogeneity determines the ecological processes governing bacterial and fungal community assembly in leaf miners, offering new insights into microbiome and mycobiome assembly mechanisms in invasive pests amidst environmental change. [ABSTRACT FROM AUTHOR]

We evaluated a unique model in which four full-scale wastewater treatment plants (WWTPs) with the same treatment schematic and fed with similar influent wastewater were tracked over an 8-month period to determine whether the community assembly would differ in the activated sludge (AS) and sand filtration (SF) stages. For each WWTP, AS and SF achieved an average of 1-log10 (90%) and <0.02-log10 (5%) reduction of total cells, respectively. Despite the removal of cells, both AS and SF had a higher alpha and beta diversity compared to the influent microbial community. Using the Sloan neutral model, it was observed that AS and SF were individually dominated by different assembly processes. Specifically, microorganisms from influent to AS were predominantly determined by the selective niche process for all WWTPs, while the microbial community in the SF was relatively favored by a stochastic, random migration process, except two WWTPs. AS also contributed more to the final effluent microbial community compared with the SF. Given that each WWTP operates the AS independently and that there is a niche selection process driven mainly by the chemical oxygen demand concentration, operational taxonomic units unique to each of the WWTPs were also identified. The findings from this study indicate that each WWTP has its distinct microbial signature and could be used for source-tracking purposes. IMPORTANCE This study provided a novel concept that microorganisms follow a niche assembly in the activated sludge (AS) tank and that the AS contributed more than the sand filtration process toward the final microbial signature that is unique to each treatment plant. This observation highlights the importance of understanding the microbial community selected by the AS stage, which could contribute toward sourcetracking the effluent from different wastewater treatment plants. [ABSTRACT FROM AUTHOR]

Abstract Disentangling the assembly mechanisms controlling community composition, structure, distribution, functions, and dynamics is a central issue in ecology. Although various approaches have been proposed to examine community assembly mechanisms, quantitative characterization is challenging, particularly in microbial ecology. Here, we present a novel approach for quantitatively delineating community assembly mechanisms by combining the consumer–resource model with a neutral model in stochastic differential equations. Using time‐series data from anaerobic bioreactors that target microbial 16S rRNA genes, we tested the applicability of three ecological models: the consumer–resource model, the neutral model, and the combined model. Our results revealed that model performances varied substantially as a function of population abundance and/or process conditions. The combined model performed best for abundant taxa in the treatment bioreactors where process conditions were manipulated. In contrast, the neutral model showed the best performance for rare taxa. Our analysis further indicated that immigration rates decreased with taxa abundance and competitions between taxa were strongly correlated with phylogeny, but within a certain phylogenetic distance only. The determinism underlying taxa and community dynamics were quantitatively assessed, showing greater determinism in the treatment bioreactors that aligned with the subsequent abnormal system functioning. Given its mechanistic basis, the framework developed here is expected to be potentially applicable beyond microbial ecology.

Skin microbiota play an important role in protecting bat hosts from the fungal pathogen Pseudogymnoascus destructans, which has caused dramatic bat population declines and extinctions. Recent studies have provided insights into the bacterial communities of bat skin, but variation in skin bacterial community structure in the context of the seasonal dynamics of fungal invasion, as well as the processes that drive such variation, remain largely unexplored. In this study, we characterized bat skin microbiota over the course of the bat hibernation and active season stages and used a neutral model of community ecology to determine the relative roles of neutral and selective processes in driving microbial community variation. Our results showed significant seasonal shifts in skin community structure, as well as less diverse microbiota in hibernation than in the active season. Skin microbiota were influenced by the environmental bacterial reservoir. During both the hibernation and active season stages, more than 78% of ASVs in bat skin microbiota were consistent with neutral distribution, implying that neutral processes, that is, dispersal or ecological drift contributing the most to shifts in skin microbiota. In addition, the neutral model showed that some ASVs were actively selected by the bats from the environmental bacterial reservoir, accounting for approximately 20% and 31% of the total community during hibernation and active season stages, respectively. Overall, this research provides insights into the assemblage of bat‐associated bacterial communities and will aid in the development of conservation strategies against fungal disease. [ABSTRACT FROM AUTHOR]

Models for the evolution of various phenotypes are sometimes constructed with an assumption that mutational effects will be symmetrically distributed about a static mean. This model produces a memory effect that over long evolutionary times results in an expectation that randomized sequences underlying the genetic architecture of the trait will on average retain the ancestral phenotype. This expectation is unrealistic and also inconsistent with our current understanding of processes of molecular evolution. [ABSTRACT FROM AUTHOR]

Neutral models in ecology assume that all species are demographically equivalent, such that their abundances differ ultimately because of demographic stochasticity rather than selection. In spite of their simplicity, neutral models have been found to accurately reproduce static patterns of biodiversity for diverse communities. However, the same neutral models have been found to exhibit species abundance dynamics that are far too slow compared to reality, resulting in poor fits to temporally dynamic patterns of biodiversity. Here, we show that one of the root causes of these slow dynamics is the additional assumption that a community has reached an equilibrium with a fixed community size, with species that have a net growth rate close to zero. We removed this additional assumption by constructing and analyzing a neutral model with an expected community size that can change over time and is not necessarily at equilibrium, which thus allows the historical formation of a community to be represented explicitly. Our analysis demonstrated that for the general scenario where a small community rapidly grows in size to a carrying capacity, representing recovery from ecological disturbance or assembly of a new community, the model produced much larger changes in species abundances and much shorter species ages than a neutral model at an equilibrium with fixed community size. In addition, the species abundance distribution was biphasic with a subset of abundant species arising from a founder effect. We confirmed these new results in applications of the new model to the specific scenario of recovery of the Amazon tree community after the end-Cretaceous bolide impact, which involved periods of increasing and decreasing community size. We conclude that incorporating transient dynamics in neutral models improves realism by allowing explicit consideration of how a community is formed over realistic time-scales. • Transient dynamics of a neutral model with varying community size are analyzed. • Formulae are derived specifying expected species richness and species age. • Formulae are derived specifying the species-abundance distribution. • Model gives a biphasic SAD with common species arising from a founder effect. • Model also gives realistic species ages for a tree community at an Amazon scale. [ABSTRACT FROM AUTHOR]

What causes turnover on the Billboard charts? The neutral model of cultural evolution, which assumes that taste is transmitted via an unbiased copying process, provides precise predictions regarding expected popularity distributions and turnover within a popularity-ranked list. Recent advances in this line make it possible to characterize the likelihood of music taste transmission mechanisms by investigating departures of observed turnover rates from neutral model predictions. Here, I bias the neutral model to investigate four alternative conceptions of individual music taste transmission (song quality, individual status, social network, and anticonformist) and use agent-based simulations to examine the impact on turnover. I then compare modeled with empirical turnover data from the Billboard Hot 100 over the period from 1958 to 2021 and find that observed turnover patterns are reproduced only in an anticonformist model simulating the systematic rejection of the most popular songs. This finding was unexpected and challenges the notion of a generalized "preference for the popular." Overall, this study contributes to ongoing debates regarding the mechanisms involved in the transmission of taste and the mechanics of fashion change. [ABSTRACT FROM AUTHOR]

Periphytic algae is an important primary producer in the river ecosystem, and it is one of the important indicators for the monitoring and evaluation of river water ecology. As a typical plateau river, the assembly process of the algae community in the Yarlung Zangbo River is still unclear. In May 2022 and July and September 2023, algae samples were collected, and water environmental factors were determined in the lower reaches of the Yarlung Zangbo River. The algal species were identified, and cell abundance and biomass were calculated using in vivo observation and fixed staining techniques to explore the diversity pattern of algae communities in the lower reaches of the Yarlung Zangbo River, to clarify the relative importance of deterministic and random processes in the assembly of algal communities, and to reveal the influencing factors driving the assembly process. The results showed that there were significant differences in the time of water environmental factors, mainly concentrated between spring, summer, summer, and autumn. A total of 274 species of algae were identified in the three seasons, belonging to 7 phyla, 9 classes, 18 orders, 31 families, and 63 genera, and the community differences between seasons were significant （ P =0.001）. They all showed Bacillariophyta-Chlorophyta-Cyanophyta, and the community assembly process of algae was affected by both a deterministic process and random process but was dominated by the deterministic process. The interspecific relationship was mainly cooperative, and the co-occurrence network in autumn showed stronger network complexity and connectivity. The pH and turbidity were important water environmental factors affecting the community structure of algae, which could indirectly affect the community assembly process of algae by driving the metabolic rate and ecological adaptability of algae species.

Recent work highlighted the role of motility genes in dispersing fly-associated microbes and their spread between hosts. We investigated whether bacterial genes encoding motility are associated with the occurrence of bacteria above passive dispersal levels in the gut of wild Drosophila melanogaster . We revisited 16S amplicon and shotgun metagenome data of wild flies and correlated four genera of bacteria ( Commensalibacter , Gluconobacter , Lactobacillus , and Tatumella ) with motility genes. We plotted the microbes against neutral models of ecological drift and passive dispersal. Microbes with positive correlations to motility were exclusively found at or above neutral model predictions, suggesting motility genes are crucial for fly microbiota spread and colonization. This information is crucial for understanding how specific gene functions contribute to microbial community dispersal and colonization within the fly host. Moreover, this study's findings serve as a proof of concept for using the neutral model to predict microbial functions essential for survival and dissemination in diverse hosts., Competing Interests: The authors declare no conflicts of interest for this manuscript., (Published by Oxford University Press on behalf of the International Society for Microbial Ecology 2025.)

The oral and upper respiratory tracts are closely linked anatomically and physiologically with the lower respiratory tract and lungs, and the influence of oral and upper respiratory microbes on the lung microbiota is increasingly being recognized. However, the ecological process and individual heterogeneity of the oral and upper respiratory tract microbes shaping the lung microbiota remain unclear owing to the lack of controlled analyses with sufficient sample sizes. Here, the microbiomes of saliva, nasal cavity, oropharyngeal area, and bronchoalveolar lavage samples are profiled and the shaping process of multisource microbes on the lung microbiota is measured. It is found that oral and nasal microbial inputs jointly shape the lung microbiota by occupying different ecological niches. It is also observed that the spread of oral microbes to the lungs is heterogeneous, with more oral microbes entering the lungs being associated with decreased lung function and increased lung proinflammatory cytokines. These results depict the external shaping process of lung microbiota and indicate the great value of oral samples, such as saliva, in monitoring and assessing lung microbiota status in clinical settings. [ABSTRACT FROM AUTHOR]

Geographic isolation is a central mechanism of speciation, but perfect isolation of populations is rare. Although speciation can be hindered if gene flow is large, intermediate levels of migration can enhance speciation by introducing genetic novelty in the semi‐isolated populations or founding small communities of migrants. Here, we consider a two‐island neutral model of speciation with continuous migration and study diversity patterns as a function of the migration probability, population size, and number of genes involved in reproductive isolation (dubbed as genome size). For small genomes, low levels of migration induce speciation on the islands that otherwise would not occur. Diversity, however, drops sharply to a single species inhabiting both islands as the migration probability increases. For large genomes, sympatric speciation occurs even when the islands are strictly isolated. Then species richness per island increases with the probability of migration, but the total number of species decreases as they become cosmopolitan. For each genome size, there is an optimal migration intensity for each population size that maximizes the number of species. We discuss the observed modes of speciation induced by migration and how they increase species richness in the insular system while promoting asymmetry between the islands and hindering endemism. [ABSTRACT FROM AUTHOR]

Macroinvertebrate community in the intertidal setup plays an important role in coastal ecosystem functions and biogeochemical cycle. However, different land use pattern may influence on their community structure, diversity, and composition in the coastal ecosystems. Using Van-Veen grab sampler, 60 sediment samples were seasonally collected from mangroves-dominated, aquaculture-dominated, and anthropogenically affected area in the lower intertidal zone of the Kohelia channel of Bangladesh, the Northern Bay of Bengal. We have tasted the variation in sediment properties across three land-use types in this intertidal habitat. To understand the patterns of benthic macroinvertebrate distribution, a neutral community model was applied. Our results showed that community composition and biodiversity of the benthic macroinvertebrate communities varied significantly between mangrove-dominated area with anthropogenically affected areas among the four seasons. The neutral community model revealed that community assembly of benthic macroinvertebrates in the lower intertidal habitats is structured by stochastic processes while sediment properties have significant influence on species distribution and interactions. Results suggested that land-use changes altered sediment properties and could change the diversity and distribution of the macroinvertebrate communities in the lower intertidal habitats. [ABSTRACT FROM AUTHOR]

As the water source for the Middle Route Project of the South-to-North Water Diversion Project (MR-SNWD) of China, the Danjiangkou Reservoir (DJR) is in the process of ecosystem reassembly, but the composition, function, and assembly mechanisms of bacterioplankton communities are not yet clear. In this study, the composition, distribution characteristics and influencing factors of bacterioplankton communities were analyzed by high-throughput sequencing (HTS); PICRUSt2 was used to predict community function; a molecular ecological network was used to analyze bacterioplankton interactions; and the assembly process of bacterioplankton communities was estimated with a neutral model. The results indicated that the communities, function and interaction of bacterioplankton in the DJR had significant annual and seasonal variations and that the seasonal differences were greater than that the annual differences. Excessive nitrogen (N) and phosphorus (P) nutrients in the DJR are the most important factors affecting water quality in the reservoir, N and P nutrients are the main factors affecting bacterial communities. Season is the most important factor affecting bacterioplankton N and P cycle functions. Ecological network analysis indicated that the average clustering coefficient and average connectivity of the spring samples were lower than those of the autumn samples, while the number of modules for the spring samples was higher than that for the autumn samples. The neutral model explained 66.3%, 63.0%, 63.0%, and 70.9% of the bacterioplankton community variations in samples in the spring of 2018, the autumn of 2018, the spring of 2019, and the autumn of 2019, respectively. Stochastic processes dominate bacterioplankton community assembly in the DJR. This study revealed the composition, function, interaction, and assembly of bacterioplankton communities in the DJR, providing a reference for the protection of water quality and the ecological functions of DJR bacterioplankton. [ABSTRACT FROM AUTHOR]

As the water source for the Middle Route Project of the South-to-North Water Diversion Project (MR-SNWD) of China, the Danjiangkou Reservoir (DJR) is in the process of ecosystem reassembly, but the composition, function, and assembly mechanisms of bacterioplankton communities are not yet clear. In this study, the composition, distribution characteristics and influencing factors of bacterioplankton communities were analyzed by high-throughput sequencing (HTS); PICRUSt2 was used to predict community function; a molecular ecological network was used to analyze bacterioplankton interactions; and the assembly process of bacterioplankton communities was estimated with a neutral model. The results indicated that the communities, function and interaction of bacterioplankton in the DJR had significant annual and seasonal variations and that the seasonal differences were greater than that the annual differences. Excessive nitrogen (N) and phosphorus (P) nutrients in the DJR are the most important factors affecting water quality in the reservoir, N and P nutrients are the main factors affecting bacterial communities. Season is the most important factor affecting bacterioplankton N and P cycle functions. Ecological network analysis indicated that the average clustering coefficient and average connectivity of the spring samples were lower than those of the autumn samples, while the number of modules for the spring samples was higher than that for the autumn samples. The neutral model explained 66.3%, 63.0%, 63.0%, and 70.9% of the bacterioplankton community variations in samples in the spring of 2018, the autumn of 2018, the spring of 2019, and the autumn of 2019, respectively. Stochastic processes dominate bacterioplankton community assembly in the DJR. This study revealed the composition, function, interaction, and assembly of bacterioplankton communities in the DJR, providing a reference for the protection of water quality and the ecological functions of DJR bacterioplankton.

Economy and ecology are two main aspects of human sustainable development. However, a comprehensive analysis of the status and trends of economic and ecological cognition is still lacking. Here, we defined economic and ecological concepts as cultural traits that constitute a complex system representing sustainability ideas. Adopting a linguistic ecology perspective, we analysed the frequency distribution, turnover and innovation rates of 3713 concepts appearing in China's mainstream newspaper, People's Daily, from 1946 to 2015. Results reveal that: (1) In the whole historical period, there were more economic concepts than ecological concepts both in amount and category. Economic concepts experienced stronger cultural drift than ecological concepts tested by the neutral model of cultural evolution; (2) popular economic concepts became more diversified, but popular ecological concepts became more uniform; (3) both economic concepts and ecological concepts attained more variation in their own disciplinary domains than in cross-disciplinary domains; and (4) as a platform of both giving information and opinion, a newspaper is subjected to cultural selection, especially reflected in the change in ecological concepts under the context of Chinese ecological civilization construction. We concluded with a discussion of promoting vibrant and resilient ecological knowledge in fostering sustainability activities and behaviours. [ABSTRACT FROM AUTHOR]

Gut-associated microbes can influence insect health and fitness. Understanding the structure of bacterial communities provides valuable insights on how different species may be selected and their functional characteristics in their hosts. The neutral model is powerful in predicting the structure of microbial communities, but its application in insects remains rare. Here, we examined the contribution of neutral processes to the gut-associated bacterial communities in Helicoverpa armigera caterpillars collected from different maize varieties at four locations. The gut-associated bacteria can be assigned to 37 Phyla, 119 orders, and 515 genera, with each individual gut containing 17–75% of the OTUs and 19–79% of the genera in the pooled samples of each population. The distribution patterns of most (75.59–83.74%) bacterial taxa were in good agreement with the neutral expectations. Of the remaining OTUs, some were detected in more individual hosts than would be predicted by the neutral model (i.e., above-partition), and others were detected in fewer individual hosts than predicted by the neutral model (i.e., below-partition). The bacterial taxa in the above-partitions were potentially selected by the caterpillar hosts, while the bacteria in the below-partitions may be preferentially eliminated by the hosts. Moreover, the gut-associated microbiota seemed to vary between maize varieties and locations, so ecological parameters outside hosts can affect the bacterial communities. Therefore, the structure of gut microbiota in the H. armigera caterpillar was mainly determined by stochastic processes, and the bacteria in the above-partition warrant further investigation for their potential roles in the caterpillar host. [ABSTRACT FROM AUTHOR]

Gut-associated microbes can influence insect health and fitness. Understanding the structure of bacterial communities provides valuable insights on how different species may be selected and their functional characteristics in their hosts. The neutral model is powerful in predicting the structure of microbial communities, but its application in insects remains rare. Here, we examined the contribution of neutral processes to the gut-associated bacterial communities in Helicoverpa armigera caterpillars collected from different maize varieties at four locations. The gut-associated bacteria can be assigned to 37 Phyla, 119 orders, and 515 genera, with each individual gut containing 17–75% of the OTUs and 19–79% of the genera in the pooled samples of each population. The distribution patterns of most (75.59–83.74%) bacterial taxa were in good agreement with the neutral expectations. Of the remaining OTUs, some were detected in more individual hosts than would be predicted by the neutral model (i.e., above-partition), and others were detected in fewer individual hosts than predicted by the neutral model (i.e., below-partition). The bacterial taxa in the above-partitions were potentially selected by the caterpillar hosts, while the bacteria in the below-partitions may be preferentially eliminated by the hosts. Moreover, the gut-associated microbiota seemed to vary between maize varieties and locations, so ecological parameters outside hosts can affect the bacterial communities. Therefore, the structure of gut microbiota in the H. armigera caterpillar was mainly determined by stochastic processes, and the bacteria in the above-partition warrant further investigation for their potential roles in the caterpillar host.

We develop an analysis of the cryptocurrency market borrowing methods and concepts from ecology. This approach makes it possible to identify specific diversity patterns and their variation, in close analogy with ecological systems, and to characterize the cryptocurrency market in an effective way. At the same time, it shows how non-biological systems can have an important role in contrasting different ecological theories and in testing the use of neutral models. The study of the cryptocurrencies abundance distribution and the evolution of the community structure strongly indicates that these statistical patterns are not consistent with neutrality. In particular, the necessity to increase the temporal change in community composition when the number of cryptocurrencies grows, suggests that their interactions are not necessarily weak. The analysis of the intraspecific and interspecific interdependency supports this fact and demonstrates the presence of a market sector influenced by mutualistic relations. These latest findings challenge the hypothesis of weakly interacting symmetric species, the postulate at the heart of neutral models.

Skin bacterial communities can protect amphibians from a fungal pathogen; however, little is known about how these communities are maintained. We used a neutral model of community ecology to identify bacteria that are maintained on salamanders by selection or by dispersal from a bacterial reservoir (soil) and ecological drift. We found that 75% (9/12) of bacteria that were consistent with positive selection,

Abstract For community ecologists, “neutral or not?” is a fundamental question, and thus, rejecting neutrality is an important first step before investigating the deterministic processes underlying community dynamics. Hubbell's neutral model is an important contribution to the exploration of community dynamics, both technically and philosophically. However, the neutrality tests for this model are limited by a lack of statistical power, partly because the zero‐sum assumption of the model is unrealistic. In this study, we developed a neutrality test for local communities that implements non‐zero‐sum community dynamics and determines the number of new species (Nsp) between observations. For the non‐zero‐sum neutrality test, the model distributed the expected Nsp, as calculated by extensive simulations, which allowed us to investigate the neutrality of the observed community by comparing the observed Nsp with distributions of the expected Nsp derived from the simulations. For this comparison, we developed a new “non‐zero‐sum Nsp test,” which we validated by running multiple neutral simulations using different parameter settings. We found that the non‐zero‐sum Nsp test rejected neutrality at a near‐significance level, which justified the validity of our approach. For an empirical test, the non‐zero‐sum Nsp test was applied to real tropical tree communities in Panama and Malaysia. The non‐zero‐sum Nsp test rejected neutrality in both communities when the observation interval was long and Nsp was large. Hence, the non‐zero‐sum Nsp test is an effective way to examine neutrality and has reasonable statistical power to reject the neutral model, especially when the observed Nsp is large. This unique and simple approach is statistically powerful, even though it only employs two temporal sequences of community data. Thus, this test can be easily applied to existing datasets. In addition, application of the test will provide significant benefits for detecting changing biodiversity under climate change and anthropogenic disturbance.

For community ecologists, "neutral or not?" is a fundamental question, and thus, rejecting neutrality is an important first step before investigating the deterministic processes underlying community dynamics. Hubbell's neutral model is an important contribution to the exploration of community dynamics, both technically and philosophically. However, the neutrality tests for this model are limited by a lack of statistical power, partly because the zero‐sum assumption of the model is unrealistic. In this study, we developed a neutrality test for local communities that implements non‐zero‐sum community dynamics and determines the number of new species (Nsp) between observations. For the non‐zero‐sum neutrality test, the model distributed the expected Nsp, as calculated by extensive simulations, which allowed us to investigate the neutrality of the observed community by comparing the observed Nsp with distributions of the expected Nsp derived from the simulations. For this comparison, we developed a new "non‐zero‐sum Nsp test," which we validated by running multiple neutral simulations using different parameter settings. We found that the non‐zero‐sum Nsp test rejected neutrality at a near‐significance level, which justified the validity of our approach. For an empirical test, the non‐zero‐sum Nsp test was applied to real tropical tree communities in Panama and Malaysia. The non‐zero‐sum Nsp test rejected neutrality in both communities when the observation interval was long and Nsp was large. Hence, the non‐zero‐sum Nsp test is an effective way to examine neutrality and has reasonable statistical power to reject the neutral model, especially when the observed Nsp is large. This unique and simple approach is statistically powerful, even though it only employs two temporal sequences of community data. Thus, this test can be easily applied to existing datasets. In addition, application of the test will provide significant benefits for detecting changing biodiversity under climate change and anthropogenic disturbance. [ABSTRACT FROM AUTHOR]

The mammal gut is a rich reservoir of antibiotic resistance genes (ARGs), and the relationship between bacterial communities and ARGs has been widely studied. Despite ecological significance of microeukaryotes (fungi and protists), our understanding of their roles in the mammal gut microbiome and antibiotic resistome is still limited. Here, we used amplicon sequencing, metagenomic sequencing and high-throughput quantitative PCR to examine microbiomes and antibiotic resistomes of 41 giant panda fecal samples from individuals with different genders, ages, sampling sites and diet. Our results show that diverse protists inhabit in the giant panda gut ecosystem, dominated by consumers. Higher abundance of protistan consumers was detected in the elder compared to sub-adult and adult giant pandas. Diet is the main driving factor of variation in ARGs in the giant panda gut microbiome. Weighted correlation network analysis identified two key microbial modules from multitrophic communities, which all contributed to the variation in ARGs in the giant panda gut. Protists occupied an important position in the two modules which were dominated by fungal taxa. Deterministic processes made a more important contribution to microbial community assembly of the two modules than to bacterial, fungal and protistan communities. This study sheds new light on how key microbial modules contribute to the variation in ARGs, which is crucial in understanding dynamics of antibiotic resistome in the mammal gut, particularly endangered species.

The microbiome is critical for host survival and fitness, but gaps remain in our understanding of how this symbiotic community is structured. Despite evidence that related hosts often harbor similar bacterial communities, it is unclear whether this pattern is due to genetic similarities between hosts or to common ecological selection pressures. Here, using herbivorous rodents in the genus Neotoma, we quantify how geography, diet, and host genetics, alongside neutral processes, influence microbiome structure and stability under natural and captive conditions. Using bacterial and plant metabarcoding, we first characterized dietary and microbiome compositions for animals from 25 populations, representing seven species from 19 sites across the southwestern United States. We then brought wild animals into captivity, reducing the influence of environmental variation. In nature, geography, diet, and phylogeny collectively explained ~50% of observed microbiome variation. Diet and microbiome diversity were correlated, with different toxin-enriched diets selecting for distinct microbial symbionts. Although diet and geography influenced natural microbiome structure, the effects of host phylogeny were stronger for both wild and captive animals. In captivity, gut microbiomes were altered; however, responses were species specific, indicating again that host genetic background is the most significant predictor of microbiome composition and stability. In captivity, diet effects declined and the effects of host genetic similarity increased. By bridging a critical divide between studies in wild and captive animals, this work underscores the extent to which genetics shape microbiome structure and stability in closely related hosts. [ABSTRACT FROM AUTHOR]

Theoretical ecologists have analysed a range of neutral models but few including stage structure. Here we introduce a stage‐structured neutral model, by extending the standard spatial neutral model to have two‐stage classes: a juvenile stage and a reproductive stage. We find that formulas for biodiversity patterns (e.g. species–area relationships and species abundance distributions) of reproductives in the stage‐structured model can be obtained from the corresponding standard formulas via a parameter rescaling, which involves calculating an effective speciation rate parameter and an effective dispersal parameter. This is useful because it means existing knowledge about the non‐stage‐structured model can be transferred to the stage‐structured model, providing that applications focus exclusively on the reproductive stage. One surprising implication is that the presence of a juvenile stage can substantially increase the species richness of reproductive individuals: a juvenile stage with a length fraction k that of the reproductive stage increases reproductive species richness by roughly the same factor. We apply our new formulas to a case study of tropical forest trees in Panama and find that while the stage‐structured model makes different predictions than the standard model, it does not fix known problems with cross‐scale predictions. We speculate that some of our results, in particular the result that the presence of a juvenile stage increases community diversity, likely apply to non‐neutral systems as well. [ABSTRACT FROM AUTHOR]

The loss of recombination between sex chromosomes has occurred repeatedly throughout nature, with important implications for their subsequent evolution. Explanations for this remarkable convergence have generally invoked only adaptive processes (e.g. sexually antagonistic selection); however, there is still little evidence for these hypotheses. Here we propose a model in which recombination on sex chromosomes is lost due to the neutral accumulation of sequence divergence adjacent to (and thus, in linkage disequilibrium with) the sex determiner. Importantly, we include in our model the fact that sequence divergence, in any form, reduces the probability of recombination between any two sequences. Using simulations, we show that, under certain conditions, a region of suppressed recombination arises and expands outwards from the sex-determining locus, under purely neutral processes. Further, we show that the rate and pattern of recombination loss are sensitive to the pre-existing recombination landscape of the genome and to sex differences in recombination rates, with patterns consistent with evolutionary strata emerging under some conditions. We discuss the applicability of these results to natural systems. This article is part of the theme issue 'Challenging the paradigm in sex chromosome evolution: empirical and theoretical insights with a focus on vertebrates (Part I)'. [ABSTRACT FROM AUTHOR]

Summary: Latitudinal gradients provide opportunities to better understand soil fungal community assembly and its relationship with vegetation, climate, soil and ecosystem function. Understanding the mechanisms underlying community assembly is essential for predicting compositional responses to changing environments.We quantified the relative importance of stochastic and deterministic processes in structuring soil fungal communities using patterns of community dissimilarity observed within and between 12 natural forests and related these to environmental variation within and among sites.The results revealed that whole fungal communities and communities of arbuscular and ectomycorrhizal fungi consistently exhibited divergent patterns but with less divergence for ectomycorrhizal fungi at most sites. Within those forests, no clear relationships were observed between the degree of divergence within fungal and plant communities. When comparing communities at larger spatial scales, among the 12 forests, we observed distinct separation in all three fungal groups among tropical, subtropical and temperate climatic zones. Soil fungal β‐diversity patterns between forests were also greater when comparing forests exhibiting high environmental heterogeneity.Taken together, although large‐scale community turnover could be attributed to specific environmental drivers, the differences among fungal communities in soils within forests was high even at local scales. [ABSTRACT FROM AUTHOR]

The three-dimensional (3D) design data employed in a process plant construction project are generated during both the basic design and detailed design stages and are used for various purposes throughout the life cycle of the project. After the design stage, 3D design data are converted to a lightweight 3D format and utilized to support procurement, construction, and audit work in a collaborative project management system. However, significant time and cost are incurred when separate interfaces to convert design data are developed for each plant 3D computer-aided design (CAD) system. As an alternative, a method exists to integrate an interface using a neutral model. After translating the 3D input design data for the plant 3D CAD system to a neutral format, this study proposes an interface for use in collaborative project management by converting the data into a lightweight 3D model. In addition, detailed techniques for implementing the proposed interface are described. To verify the validity of the proposed neutral model-based 3D design data interface, translation, inspection, and lightweighting experiments are performed using 3D design data for a synthesized natural gas production plant project. [ABSTRACT FROM AUTHOR]

Synonymous codon substitutions are not always selectively neutral as revealed by several types of analyses, including studies of codon usage patterns among genes. We analyzed codon usage in 13 bacterial genomes sampled from across a large order of bacteria, Enterobacterales, and identified presumptively neutral and selected classes of synonymous substitutions. To estimate substitution rates, given a neutral/selected classification of synonymous substitutions, we developed a flexible dN=dS substitution model that allows multiple classes of synonymous substitutions. Under this multiclass synonymous substitution (MSS) model, the denominator of dN=dS includes only the strictly neutral class of synonymous substitutions. On average, the value of dN=dS under the MSS model was 80% of that under the standard codon model in which all synonymous substitutions are assumed to be neutral. The indication is that conventional dN=dS analyses overestimate these values and thus overestimate the frequency of positive diversifying selection and underestimate the strength of purifying selection. To quantify the strength of selection necessary to explain this reduction, we developed a model of selected compensatory codon substitutions. The reduction in synonymous substitution rate, and thus the contribution that selection makes to codon bias variation among genes, can be adequately explained by very weak selection, with a mean product of population size and selection coefficient, Ns = 0.8. [ABSTRACT FROM AUTHOR]

Inferring the processes underlying the emergence of observed patterns is a key challenge in theoretical ecology. Much effort has been made in the past decades to collect extensive and detailed information about the spatial distribution of tropical rainforests, as demonstrated, e.g. in the 50 ha tropical forest plot on Barro Colorado Island, Panama. These kinds of plots have been crucial to shed light on diverse qualitative features, emerging both at the single-species or the community level, like the spatial aggregation or clustering at short scales. Here, we build on the progress made in the study of the density correlation functions applied to biological systems, focusing on the importance of accurately defining the borders of the set of trees, and removing the induced biases. We also pinpoint the importance of combining the study of correlations with the scale dependence of fluctuations in density, which are linked to the well-known empirical Taylor’s power law. Density correlations and fluctuations, in conjunction, provide a unique opportunity to interpret the behaviours and, possibly, to allow comparisons between data and models. We also study such quantities in models of spatial patterns and, in particular, we find that a spatially explicit neutral model generates patterns with many qualitative features in common with the empirical ones.

Stochastic modeling of phylogenies raises five questions that have received varying levels of attention from quantitatively inclined biologists. 1) How large do we expect (from the model) the ratio of maximum historical diversity to current diversity to be? 2) From a correct phylogeny of the extant species of a clade, what can we deduce about past speciation and extinction rates? 3) What proportion of extant species are in fact descendants of still-extant ancestral species, and how does this compare with predictions of models? 4) When one moves from trees on species to trees on sets of species (whether traditional higher order taxa or clades within PhyloCode), does one expect trees to become more unbalanced as a purely logical consequence of tree structure, without signifying any real biological phenomenon? 5) How do we expect that fluctuation rates for counts of higher order taxa should compare with fluctuation rates for number of species? We present a mathematician's view based on an oversimplified modeling framework in which all these questions can be studied coherently.

The concept of potential natural vegetation (PNV) refers to self-sustaining mature vegetation matching the environmental conditions a site offers. Despite its widespread use, the applicability of the concept under the current level of human impacts on the environment has been criticised. We re-examine the original publication of the PNV concept and its development over time to identify the sources of tension between theory and application and to direct the discourse onto a common ground of understanding. Our focus is on the relationship between human impacts and PNV. Based on extended excerpts and detailed interpretation, we affirm that PNV applies to a specific point in time. Consequently, PNV is independent of any realised vegetation including past undisturbed (pre-human) vegetation. We track possible routes and reasons for alternative interpretations. We identify PNV as a mental concept, or a neutral model, that represents baseline vegetation potential that excludes contemporary human management but includes past environment-modifying impacts. We address how a concept reflecting unmanaged vegetation can be important for application in a world transformed by humans. Rather than abandoning the concept, we advocate adhering to using it in the original sense of its definition. This way PNV can serve research as a neutral model and support sustainable land use planning. [ABSTRACT FROM AUTHOR]

The relationship between species richness and productivity changes with spatial scale, but the way in which it changes and the underlying mechanisms remain unclear. We address this critical knowledge gap using a new mechanistic model of the spatial scaling of species richness–productivity (SP) relationships for a local community. Our model is neutral and hence assumes that species dynamics are driven by dispersal limitation and demographic stochasticity. We showed analytically that SP relationships predicted by our model are typically unimodal. Consistent with previous simulation-based studies, the positive phase of our unimodal SP relationship was driven by a sampling effect ("more-individuals effect") whereas the negative phase was driven by relatively more propagules being of local as opposed to external origin ("dilution effect"). Our main novel finding related to the spatial scaling of the unimodal SP relationship: the peak shifted to the left with increasing spatial scale, such that the decreasing phase covered a greater range of productivity. This was driven by an increase in the strength of the dilution effect relative to the more-individuals effect, reflecting higher area/perimeter ratios at larger spatial scales. Our theoretical predictions are qualitatively consistent with the spatial scaling of SP relationships documented for trees in localized forest communities across the world. [ABSTRACT FROM AUTHOR]

Neutral community models embody the idea that individuals are ecologically equivalent, having equal fitness over all environmental conditions, and describe how the spatial dynamics and speciation of such individuals can produce a wide range of patterns of distribution, diversity, and abundance. Neutral models have been controversial, provoking a rush of tests and comments. The debate has been spurred by the suggestion that we should test mechanisms. However, the mechanisms and the spatial scales of interest have never clearly been described, and consequently, the tests have often been only peripherally relevant. At least two mechanisms are present in spatially structured neutral models. Dispersal limitation causes clumping of a species, which increases the strength of intraspecific competition and reduces the strength of interspecific competition. This may prolong coexistence and enhance local and regional diversity. Speciation is present in some neutral models and gives a donor-controlled input of new species, many of which remain rare or are short lived, but which directly add to species diversity. Spatial scale is an important consideration in neutral models. Ecological equivalence and equal fitness have implicit spatial scales because dispersal limitation and its emergent effects operate at population levels, and populations and communities are defined at a chosen spatial scale in recent neutral models; equality is measured relative to a metacommunity, and this necessitates de. ning the spatial scale of that metacommunity. Furthermore, dispersal has its own scales. Thorough empirical tests of neutral models will require both tests of mechanisms and pattern-producing ability, and will involve coupling theoretical models and experiments.

Abstract In an era of global environmental change, understanding how disturbance affects the dynamics of ecological communities is crucial. However, few studies have theoretically explored the potential influence of disturbance including both intensity and frequency on compositional change over time in communities with stage structure. A spatially explicit, individual‐based model was constructed incorporating the various demographic responses to disturbance of plants at two different growth stages: seedlings and adults. In the model, we assumed that individuals within each stage were demographically equivalent (neutral) but differed between stages. We simulated a common phenomenon that seedlings suffered more from disturbance such as grazing and fire than adults. We showed how stage‐structured communities of seedlings and adults responded to disturbance with various levels of disturbance frequency and intensity. In “undisturbed” simulations, the relationship between average species abundance (defined here as the total number of individuals divided by species richness) and community composition turnover (measured by the Bray–Curtis similarity index) was asymptotic. However, in strongly “disturbed” simulations with the between‐disturbance intervals greater than one, this relationship became unimodal. Stage‐dependent response to disturbance underlay the above discrepancy between undisturbed and disturbed communities.

Symbiotic microbial communities are important for host health, but the processes shaping these communities are poorly understood. Understanding how community assembly processes jointly affect microbial community composition is limited because inflexible community models rely on rejecting dispersal and drift before considering selection. We developed a flexible community assembly model based on neutral theory to ask: How do dispersal, drift and selection concurrently affect the microbiome across environmental gradients? We applied this approach to examine how a fungal pathogen affected the assembly processes structuring the amphibian skin microbiome. We found that the rejection of neutrality for the amphibian microbiome across a fungal gradient was not strictly due to selection processes, but was also a result of species‐specific changes in dispersal and drift. Our modelling framework brings the qualitative recognition that niche and neutral processes jointly structure microbiomes into quantitative focus, allowing for improved predictions of microbial community turnover across environmental gradients. [ABSTRACT FROM AUTHOR]

• Sea-level rise (SLR) thresholds for salt marsh stability vary by spatial patterns. • PC1 of landscape metrics yields smaller SLR threshold than from total area alone. • How spatial resolution impacts SLR thresholds differs by landscape metrics used. • Spatial configuration's effect on SLR thresholds is smaller with smaller salt marsh areas. • Spatial patterns should be comprehensibly accounted for to derive SLR thresholds. Ecological threshold is an important concept to indicate the boundary of alternate states of ecosystems driven by environmental conditions and to facilitate evaluation of ecosystem resilience. Sea-level rise (SLR) thresholds for the stability of salt marshes, if studied in two dimensions, are generally derived based on total areas without systematic accounting for spatial patterns related to edges, shapes, and contagions of patches. As these spatial patterns are potentially important for functions and ecosystem services of salt marshes and they are likely to be impacted by SLR in a different way from the total areas, it is necessary to study SLR thresholds based on these spatial patterns to obtain a more comprehensive understanding of salt marsh resilience to SLR. This research compares the SLR thresholds based on these spatial patterns of salt marshes to those based on total areas alone across different spatial resolutions. The spatial patterns of salt marshes were quantified by 26 commonly used landscape metrics, predicted from a mechanistic wetland change model. At spatial resolutions of 2–100 m, SLR thresholds were first derived using individual landscape metrics and then the first principal component that explained >80% of total variance of these metrics showing threshold responses to SLR. In order to separate the effect of spatial configuration from composition, a neutral model which simulated the same amount of salt marsh change as the mechanistic model but at the random locations was applied. The SLR thresholds were derived based on the simulations from the neutral model and compared to those from the mechanistic model. The results show that total area-based SLR thresholds do not comprehensively represent salt marshes' resilience to SLR. Particularly, I find 1) the derived SLR thresholds vary from 7.29 to 11.12 mm/yr for 2100 based on landscape metrics used, 2) the SLR threshold based on the first principal components (7.99 mm/yr) is smaller than that based on the total area only (8.40 mm/yr), 3) the SLR thresholds are scale dependent, and 4) the spatial configuration' effect on SLR thresholds is smaller for smaller salt marsh areas compared to larger salt marsh areas. This study highlights the need to account for different spatial patterns of salt marshes and apply wetland maps with a spatial resolutions of 30 m or finer in deriving SLR thresholds, as using total areas alone or coarser-resolution maps may provide a biased interpretation that salt marshes are more resilient to SLR than they actually are. [ABSTRACT FROM AUTHOR]

Questions: What is the relative influence of: (a) traits related to dispersal (seed size) and growth (specific leaf area [SLA]), and; (b) regional species abundances, on the structure of local sapling communities? Which metacommunity models best explain the process of forest nucleation in grasslands? Location: Woody vegetation patches originating from nucleation and the continuous forest that neighbors native grasslands, in the southern Brazilian plateau (29°28′58.00″ S, 50°12′26.00″ W). Methods: We calculated community‐weighted trait means (CWM) and functional diversity for woody saplings, considering species occurrences (FD) and abundances (FDis) separately for both seed size and SLA, in woody vegetation patches of different sizes and in the continuous forest. We tested whether mean SLA and mean seed size differed between habitat types, and whether values of FD and FDis were lower than expected by chance. We also evaluated whether the relative abundances of species in woody vegetation patches were determined by their abundances in the continuous forest, using CATS models (Community Assembly by Trait Selection). The results were then compared to the expectations from each metacommunity model. Results: Functional diversity of SLA and seed size did not differ from what was expected by chance in most sites. Species in communities of different habitat types did not differ in their mean SLA values, but we observed differences in mean seed size, with large‐seeded species being typical of areas with more shade. Species abundances in the regional species pool were more important factors than species traits for determining species abundances in the local communities. Conclusions: The analytical framework employed in this study enables a straightforward test of different metacommunity structuring models. Mass effects were the metacommunity model that best explained the process of forest nucleation in the southern Brazilian plateau, which highlights the importance of dispersal for the structure of local communities. [ABSTRACT FROM AUTHOR]

Aim: The great variation in range sizes among species has fascinated ecologists for decades. Reef‐associated fish species live in highly spatially structured habitats and adopt a wide range of dispersal strategies. We consequently expect species with greater dispersal ability to occupy larger ranges. However, empirical evidence for such a positive relationship between dispersal and range size remains scarce. Here, we unveil the role of dispersal on the range size distribution of reef‐associated fishes using empirical data and a novel spatially explicit model. Location: Tropical Eastern Pacific. Major taxa studied: Reef‐associated fishes. Time period: Underlying records are from the 20th and 21st centuries. Methods: We estimated range size distributions for all reef‐associated fishes separated into six guilds, each with different dispersal abilities. We used a one‐dimensional spatially explicit neutral model, which simulates the distribution of species along a linear and contiguous coastline, to explore the effect of dispersal, speciation and sampling on the distribution of range sizes. Our model incorporates biologically important long‐distance dispersal events with a fat‐tailed dispersal kernel and also adopts a more realistic gradual "protracted" speciation process than originally used in neutral theory. We fitted the model to the empirical data using an approximate Bayesian computation approach, with a sequential Monte Carlo algorithm. Results: Stochastic birth, death, speciation and dispersal events alone can accurately explain empirical range size distributions for six different guilds of tropical, reef‐associated fishes. Variation in range size distributions among guilds are explained purely by differences in dispersal ability with the best dispersers being distributed over larger ranges. Main conclusions: Neutral processes and guild‐specific dispersal ability provide a general explanation for both within‐ and across‐guild range size variation. Our results support the theoretically expected, but empirically much debated, hypothesis that high dispersal capacity promotes the establishment of large range size. [ABSTRACT FROM AUTHOR]

• Using a new approach, we estimate conformity (context) and information transparency (content) from archaeological data. • The model, which we have developed over the last decade, has until now never been successfully applied to real data. • Our case study is decorative motifs on several centuries of pottery from Early Neolithic Europe, ca. 5400–5000 BCE. • Our computational approach, Approximate Bayesian Computation with Random Forest algorithm, reconciles two views that figure prominently in cultural-evolutionary studies—adaptionist versus "stylistic"—through an empirical test. • The computational modeling confirms that cultural transmission of pottery motifs was a process of unbiased social learning with little content bias. Cultural-evolutionary modeling of archaeological data faces numerous challenges, perhaps the most significant being the mismatch between models of microscale activities and the macroevolutionary scale of the archaeological record. This is especially the case with identifying different kinds of social learning reflected in the record. Here we present a computational approach to social learning using a new model that compares frequencies of stylistic traits through time to an evolutionary model of social learning. Two dimensions of cultural evolution—popularity bias and information transparency—help unify a range of hitherto competing models of social learning. This model has never successfully been calibrated to real-world data, with the sparseness of archaeological data presenting an even further challenge. By calibrating the model to archaeological data, we confirm that it can be used successfully to characterize cultural transmission in the past. Our case study consists of decorative motifs on pottery from Early Neolithic Europe, ca. 5400–5000 BCE. The comparison of data to model is highly computational, involving seven different metrics and hundreds of simulations and re-samplings. Inferences are made using approximate Bayesian computation and a random-forest algorithm to estimate the best solution using a combination of all metrics. The computational modeling confirms that cultural transmission of the Neolithic pottery motifs was a process of unbiased social learning and opens the way for the exploration of a wide range of frequency data. [ABSTRACT FROM AUTHOR]

ABSTRACT Classical ecology provides principles for construction and function of biological communities, but to what extent these apply to the animal-associated microbiota is just beginning to be assessed. Here, we investigated the influence of several well-known ecological principles on animal-associated microbiota by characterizing gut microbial specimens from bilaterally symmetrical animals (Bilateria) ranging from flies to whales. A rigorously vetted sample set containing 265 specimens from 64 species was assembled. Bacterial lineages were characterized by 16S rRNA gene sequencing. Previously published samples were also compared, allowing analysis of over 1,098 samples in total. A restricted number of bacterial phyla was found to account for the great majority of gut colonists. Gut microbial composition was associated with host phylogeny and diet. We identified numerous gut bacterial 16S rRNA gene sequences that diverged deeply from previously studied taxa, identifying opportunities to discover new bacterial types. The number of bacterial lineages per gut sample was positively associated with animal mass, paralleling known species-area relationships from island biogeography and implicating body size as a determinant of community stability and niche complexity. Samples from larger animals harbored greater numbers of anaerobic communities, specifying a mechanism for generating more-complex microbial environments. Predictions for species/abundance relationships from models of neutral colonization did not match the data set, pointing to alternative mechanisms such as selection of specific colonists by environmental niche. Taken together, the data suggest that niche complexity increases with gut size and that niche selection forces dominate gut community construction. IMPORTANCE The intestinal microbiome of animals is essential for health, contributing to digestion of foods, proper immune development, inhibition of pathogen colonization, and catabolism of xenobiotic compounds. How these communities assemble and persist is just beginning to be investigated. Here we interrogated a set of gut samples from a wide range of animals to investigate the roles of selection and random processes in microbial community construction. We show that the numbers of bacterial species increased with the weight of host organisms, paralleling findings from studies of island biogeography. Communities in larger organisms tended to be more anaerobic, suggesting one mechanism for niche diversification. Nonselective processes enable specific predictions for community structure, but our samples did not match the predictions of the neutral model. Thus, these findings highlight the importance of niche selection in community construction and suggest mechanisms of niche diversification.