Accounting for the microbial assembly of each process in wastewater treatment plants (WWTPs): study of four WWTPs receiving similar influent streams

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.IMPORTANCEThis 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 source-tracking the effluent from different wastewater treatment plants.

Quantifying Stochastic Processes in Shaping Dissolved Organic Matter Pool with High-Resolution Mass Spectrometry

Natural dissolved organic matter (DOM) represents a ubiquitous molecular mixture, progressively characterized by spatiotemporal resolution. However, an inadequate comprehension of DOM molecular dynamics, especially the stochastic processes involved, hinders carbon cycling predictions. This study employs ecological principles to introduce a neutral theory to elucidate the fundamental processes involving molecular generation, degradation, and migration. A neutral model is thus formulated to assess the probability distribution of DOM molecules, whose frequencies and abundances follow a β-distribution relationship. The neutral model is subsequently validated with high-resolution mass spectrometry (HRMS) data from various waterbodies, including lakes, rivers, and seas. The model fitting highlights the prevalence of molecular neutral distribution and quantifies the stochasticity within DOM molecular dynamics. Furthermore, the model identifies deviations of HRMS observations from neutral expectations in photochemical and microbial experiments, revealing nonrandom molecular transformations. The ecological null model further validates the neutral modeling results, demonstrating that photodegradation reduces molecular stochastic dynamics at the surface of an acidic pit lake, while random distribution intensifies at the river surface compared with the porewater. Taken together, the DOM molecular neutral model emphasizes the significance of stochastic processes in shaping a natural DOM pool, offering a potential theoretical framework for DOM molecular dynamics in aquatic and other ecosystems.

Seasonal assembly of skin microbiota driven by neutral and selective processes in the greater horseshoe bat

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.

Biofilm thickness controls the relative importance of stochastic and deterministic processes in microbial community assembly in moving bed biofilm reactors

Deterministic and stochastic processes are believed to play a combined role in microbial community assembly, though little is known about the factors determining their relative importance. We investigated the effect of biofilm thickness on community assembly in nitrifying moving bed biofilm reactors using biofilm carriers where maximum biofilm thickness is controlled. We examined the contribution of stochastic and deterministic processes to biofilm assembly in a steady state system using neutral community modelling and community diversity analysis with a null-modelling approach. Our results indicate that the formation of biofilms results in habitat filtration, causing selection for phylogenetically closely related community members, resulting in a substantial enrichment of Nitrospira spp. in the biofilm communities. Stochastic assembly processes were more prevalent in biofilms of 200 µm and thicker, while stronger selection in thinner (50 µm) biofilms could be driven by hydrodynamic and shear forces at the biofilm surface. Thicker biofilms exhibited greater phylogenetic beta-diversity, which may be driven by a variable selection regime caused by variation in environmental conditions between replicate carrier communities, or by drift combined with low migration rates resulting in stochastic historical contingency during community establishment. Our results indicate that assembly processes vary with biofilm thickness, contributing to our understanding of biofilm ecology and potentially paving the way towards strategies for microbial community management in biofilm systems.

Differential Oral Microbial Input Determines Two Microbiota Pneumo-Types Associated with Health Status

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.

Diversity patterns and speciation processes in a two-island system with continuous migration

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.

Neutral Processes Provide an Insight Into the Structure and Function of Gut Microbiota in the Cotton Bollworm

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.

Testing macroecological theories in cryptocurrency market: neutral models cannot describe diversity patterns and their variation

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.

Non-zero-sum neutrality test for the tropical rain forest community using long-term between-census data

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 (N sp) between observations. For the non-zero-sum neutrality test, the model distributed the expected N sp, as calculated by extensive simulations, which allowed us to investigate the neutrality of the observed community by comparing the observed N sp with distributions of the expected N sp derived from the simulations. For this comparison, we developed a new "non-zero-sum N sp test," which we validated by running multiple neutral simulations using different parameter settings. We found that the non-zero-sum N sp test rejected neutrality at a near-significance level, which justified the validity of our approach. For an empirical test, the non-zero-sum N sp test was applied to real tropical tree communities in Panama and Malaysia. The non-zero-sum N sp test rejected neutrality in both communities when the observation interval was long and N sp was large. Hence, the non-zero-sum N sp test is an effective way to examine neutrality and has reasonable statistical power to reject the neutral model, especially when the observed N sp 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.

Microbiome stability and structure is governed by host phylogeny over diet and geography in woodrats (Neotoma spp.)

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.

A neutral model for the loss of recombination on sex chromosomes

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)'.

Assembly processes lead to divergent soil fungal communities within and among 12 forest ecosystems along a latitudinal gradient

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.

Weak selection on synonymous codons substantially inflates dN/dS estimates in bacteria

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 [Formula: see text] substitution model that allows multiple classes of synonymous substitutions. Under this multiclass synonymous substitution (MSS) model, the denominator of [Formula: see text] includes only the strictly neutral class of synonymous substitutions. On average, the value of [Formula: see text] 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 [Formula: see text] 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, [Formula: see text].

Joint assessment of density correlations and fluctuations for analysing spatial tree patterns

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.

Fungal infection alters the selection, dispersal and drift processes structuring the amphibian skin microbiome

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.

Ecological drift and competitive interactions predict unique patterns in temporal fluctuations of population size

Recent studies have highlighted the importance of higher-order competitive interactions in stabilizing population dynamics in multi-species communities. But how does the structure of competitive hierarchies affect population dynamics and extinction processes? We tackled this important question by using spatially explicit simulations of ecological drift (10 species in a homogeneous landscape of 64 patches) in which birth rates were influenced by interspecific competition. Specifically, we examined how transitive (linear pecking orders) and intransitive (pecking orders with loops) competitive hierarchies affected extinction rates and population dynamics in simulated communities through time. In comparison to a pure neutral model, an ecological drift model including transitive competition increased extinction rates, caused synchronous density-dependent population fluctuations, and generated a white-noise distribution of population sizes. In contrast, the drift model with intransitive competitive interactions decreased extinctions rates, caused asynchronous (compensatory) density-dependent population fluctuations, and generated a brown noise distribution of population sizes. We also explored the effect on community stability of more complex patterns of competitive interactions in which pairwise competitive relationships were assigned probabilistically. These probabilistic competition models also generated density-dependent trajectories and a brown noise distribution of population sizes. However, extinction rates and the degree of population synchrony were comparable to those observed in purely neutral communities. Collectively, our results confirm that intransitive competition has a strong and stabilizing effect on local populations in species-poor communities. This effect wanes with increasing species richness. Empirical assemblages characterized by brown spectral noise, density-dependent regulation, and asynchronous (compensatory) population fluctuations may indicate a signature of intransitive competitive interactions.

Response of host-bacterial colonization in shrimp to developmental stage, environment and disease

The host-associated microbiota is increasingly recognized to facilitate host fitness, but the understanding of the underlying ecological processes that govern the host-bacterial colonization over development and, particularly, under disease remains scarce. Here, we tracked the gut microbiota of shrimp over developmental stages and in response to disease. The stage-specific gut microbiotas contributed parallel changes to the predicted functions, while shrimp disease decoupled this intimate association. After ruling out the age-discriminatory taxa, we identified key features indicative of shrimp health status. Structural equation modelling revealed that variations in rearing water led to significant changes in bacterioplankton communities, which subsequently affected the shrimp gut microbiota. However, shrimp gut microbiotas are not directly mirrored by the changes in rearing bacterioplankton communities. A neutral model analysis showed that the stochastic processes that govern gut microbiota tended to become more important as healthy shrimp aged, with 37.5% stochasticity in larvae linearly increasing to 60.4% in adults. However, this defined trend was skewed when disease occurred. This departure was attributed to the uncontrolled growth of two candidate pathogens (over-represented taxa). The co-occurrence patterns provided novel clues on how the gut commensals interact with candidate pathogens in sustaining shrimp health. Collectively, these findings offer updated insight into the ecological processes that govern the host-bacterial colonization in shrimp and provide a pathological understanding of polymicrobial infections.

Allometry and Ecology of the Bilaterian Gut Microbiome

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.

Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago

Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns.

Temporal effects of disturbance on community composition in simulated stage-structured plant communities

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.

Evolutionary dynamics of the cryptocurrency market

The cryptocurrency market surpassed the barrier of $100 billion market capitalization in June 2017, after months of steady growth. Despite its increasing relevance in the financial world, a comprehensive analysis of the whole system is still lacking, as most studies have focused exclusively on the behaviour of one (Bitcoin) or few cryptocurrencies. Here, we consider the history of the entire market and analyse the behaviour of 1469 cryptocurrencies introduced between April 2013 and May 2017. We reveal that, while new cryptocurrencies appear and disappear continuously and their market capitalization is increasing (super-)exponentially, several statistical properties of the market have been stable for years. These include the number of active cryptocurrencies, market share distribution and the turnover of cryptocurrencies. Adopting an ecological perspective, we show that the so-called neutral model of evolution is able to reproduce a number of key empirical observations, despite its simplicity and the assumption of no selective advantage of one cryptocurrency over another. Our results shed light on the properties of the cryptocurrency market and establish a first formal link between ecological modelling and the study of this growing system. We anticipate they will spark further research in this direction.

Patterns and Processes in Marine Microeukaryotic Community Biogeography from Xiamen Coastal Waters and Intertidal Sediments, Southeast China

Microeukaryotes play key roles in the structure and functioning of marine ecosystems. Little is known about the relative importance of the processes that drive planktonic and benthic microeukaryotic biogeography in subtropical offshore areas. This study compares the microeukaryotic community compositions (MCCs) from offshore waters (n = 12) and intertidal sediments (n = 12) around Xiamen Island, southern China, using high-throughput sequencing of 18S rDNA. This work further quantifies the relative contributions of spatial and environmental variables on the distribution of marine MCCs (including total, dominant, rare and conditionally rare taxa). Our results showed that planktonic and benthic MCCs were significantly different, and the benthic richness (6627 OTUs) was much higher than that for plankton (4044 OTUs) with the same sequencing effort. Further, we found that benthic MCCs exhibited a significant distance-decay relationship, whereas the planktonic communities did not. After removing two unique sites (N2 and N3), however, 72% variation in planktonic community was explained well by stochastic processes. More importantly, both the environmental and spatial factors played significant roles in influencing the biogeography of total and dominant planktonic and benthic microeukaryotic communities, although their relative effects on these community variations were different. However, a high proportion of unexplained variation in the rare taxa (78.1–97.4%) and conditionally rare taxa (49.0–81.0%) indicated that more complex mechanisms may influence the assembly of the rare subcommunity. These results demonstrate that patterns and processes in marine microeukaryotic community assembly differ among the different habitats (coastal water vs. intertidal sediment) and different communities (total, dominant, rare and conditionally rare microeukaryotes), and provide novel insight on the microeukaryotic biogeography and ecological mechanisms in coastal waters and intertidal sediments at local scale.

A Neutral Model for the Evolution of Diet Breadth

Variation in diet breadth among organisms is a pervasive feature of the natural world that has resisted general explanation. In particular, trade-offs in the ability to use one resource at the expense of another have been expected but rarely detected. We explore a spatial model for the evolution of specialization, motivated by studies of plant-feeding insects. The model is neutral with respect to the causes and consequences of diet breadth: the number of hosts utilized is not constrained by trade-offs, and specialization or generalization does not confer a direct advantage with respect to the persistence of populations or the probability of diversification. We find that diet breadth evolves in ways that resemble reports from natural communities. Simulated communities are dominated by specialized species, with a predictable but less species-rich component of generalized taxa. These results raise the possibility that specialization might be a consequence of stochastic diversification dynamics acting on spatially segregated consumer-resource associations rather than a trait either favored or constrained directly by natural selection. Finally, our model generates hypotheses for global patterns of herbivore diet breadth, including a positive effect of host richness and a negative effect of evenness in host plant abundance on the number of specialized taxa.

Wolf in sheep's clothing: Model misspecification undermines tests of the neutral theory for life histories

Understanding the processes behind change in reproductive state along life‐history trajectories is a salient research program in evolutionary ecology. Two processes, state dependence and heterogeneity, can drive the dynamics of change among states. Both processes can operate simultaneously, begging the difficult question of how to tease them apart in practice. The Neutral Theory for Life Histories (NTLH) holds that the bulk of variations in life‐history trajectories is due to state dependence and is hence neutral: Once previous (breeding) state is taken into account, variations are mostly random. Lifetime reproductive success (LRS), the number of descendants produced over an individual's reproductive life span, has been used to infer support for NTLH in natura. Support stemmed from accurate prediction of the population‐level distribution of LRS with parameters estimated from a state dependence model. We show with Monte Carlo simulations that the current reliance of NTLH on LRS prediction in a null hypothesis framework easily leads to selecting a misspecified model, biased estimates and flawed inferences. Support for the NTLH can be spurious because of a systematic positive bias in estimated state dependence when heterogeneity is present in the data but ignored in the analysis. This bias can lead to spurious positive covariance between fitness components when there is in fact an underlying trade‐off. Furthermore, neutrality implied by NTLH needs a clarification because of a probable disjunction between its common understanding by evolutionary ecologists and its translation into statistical models of life‐history trajectories. Irrespective of what neutrality entails, testing hypotheses about the dynamics of change among states in life histories requires a multimodel framework because state dependence and heterogeneity can easily be mistaken for each other.

Vertebrate Hosts as Islands: Dynamics of Selection, Immigration, Loss, Persistence, and Potential Function of Bacteria on Salamander Skin

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, <1% of bacteria that were consistent with random dispersal and none of the bacteria that were consistent under negative selection had a 97% or greater match to antifungal isolates. Additionally we performed an experiment where salamanders were either provided or denied a bacterial reservoir and estimated immigration and loss (emigration and local extinction) rates of bacteria on salamanders in both treatments. Loss was strongly related to bacterial richness, suggesting competition is important for structuring the community. Bacteria closely related to antifungal isolates were more likely to persist on salamanders with or without a bacterial reservoir, suggesting they had a competitive advantage. Furthermore, over-represented and under-represented operational taxonomic units (OTUs) had similar persistence on salamanders when a bacterial reservoir was present. However, under-represented OTUs were less likely to persist in the absence of a bacterial reservoir, suggesting that the over-represented and under-represented bacteria were selected against or for on salamanders through time. Our findings from the neutral model, migration and persistence analyses show that bacteria that exhibit a high similarity to antifungal isolates persist on salamanders, which likely protect hosts against pathogens and improve fitness. This research is one of the first to apply ecological theory to investigate assembly of host associated-bacterial communities, which can provide insights for probiotic bioaugmentation as a conservation strategy against disease.

Community assembly rules affect the diversity of expanding communities

Despite centuries of interest in species range limits, few studies have taken a whole community into consideration. Actually, multiple species may simultaneously respond to environmental changes, for example, global warming, leading a series of dynamical communities toward the advancing front. We investigated multiple species range expansions through the analysis of a two-species dispersion model and simulations of multiple species assemblages regulated by neutral and fecundity-survival trade-offs (FSTs), respectively, and found that species assemblages regulated by different mechanisms would initiate different expanding patterns in geographic ranges in response to environmental changes. The neutral model generally predicts a higher biodiversity near the core of an expanding range, and a lower community similarity compared with a FST model. Without considering the evolution of life history traits, an assortment of the reproduction ability happens at the advancing front under FSTs at the expense of a higher death rate or lower competitive ability. These results emphasize the importance of community assembly rules to the biodiversity maintenance of range expanding communities.

Strong species-environment feedback shapes plant community assembly along environmental gradients

An aim of community ecology is to understand the patterns of competing species assembly along environmental gradients. All species interact with their environments. However, theories of community assembly have seldom taken into account the effects of species that are able to engineer the environment. In this modeling study, we integrate the species' engineering trait together with processes of immigration and local dispersal into a theory of community assembly. We quantify the species' engineering trait as the degree to which it can move the local environment away from its baseline state towards the optimum state of the species (species-environment feedback). We find that, in the presence of immigration from a regional pool, strong feedback can increase local species richness; however, in the absence of continual immigration, species richness is a declining function of the strength of species-environment feedback. This shift from a negative effect of engineering strength on species richness to a positive effect, as immigration rate increases, is clearer when there is spatial heterogeneity in the form of a gradient in environmental conditions than when the environment is homogeneous or it is randomly heterogeneous. Increasing the scale over which local dispersal occurs can facilitate species richness when there is no species-environment feedback or when the feedback is weak. However, increases in the spatial scale of dispersal can reduce species richness when the species-environment feedback is strong. These results expand the theoretical basis for understanding the effects of the strength of species-environment feedback on community assembly.

Using landscape history to predict biodiversity patterns in fragmented landscapes

Landscape ecology plays a vital role in understanding the impacts of land-use change on biodiversity, but it is not a predictive discipline, lacking theoretical models that quantitatively predict biodiversity patterns from first principles. Here, we draw heavily on ideas from phylogenetics to fill this gap, basing our approach on the insight that habitat fragments have a shared history. We develop a landscape ‘terrageny’, which represents the historical spatial separation of habitat fragments in the same way that a phylogeny represents evolutionary divergence among species. Combining a random sampling model with a terrageny generates numerical predictions about the expected proportion of species shared between any two fragments, the locations of locally endemic species, and the number of species that have been driven locally extinct. The model predicts that community similarity declines with terragenetic distance, and that local endemics are more likely to be found in terragenetically distinctive fragments than in large fragments. We derive equations to quantify the variance around predictions, and show that ignoring the spatial structure of fragmented landscapes leads to over-estimates of local extinction rates at the landscape scale. We argue that ignoring the shared history of habitat fragments limits our ability to understand biodiversity changes in human-modified landscapes.

How do multiple testing correction and spatial autocorrelation affect areal boundary analysis?

This paper presents alternative implementations of boundary analysis to: (1) quantify rate changes across boundaries both in an absolute (rate difference) and relative (rate ratio) ways, (2) detect changes of a minimum magnitude by using a null hypothesis of non-uniform risk, (3) account for spatial patterns and population sizes in the randomization procedure, and (4) compute multi-edge p-values for use in multiple testing correction. Simulation studies demonstrate that accounting for spatial autocorrelation and population size in the randomization procedure improves the discriminant power of the statistic, leading to a higher agreement between target and detected edges according to van Rijsbergen’s F-measure. The increase in power and F-measure was strongest for the tests based on the null hypothesis of non-uniform risk across the edge. Multiple testing correction slightly decreases the classification accuracy, yet it reduces substantially the proportion of false positives that becomes very close to the significance level when using the new procedure based on multi-edge p-values.

A comprehensive analysis of gene expression evolution between humans and mice

Evolutionary changes in gene expression account for most phenotypic differences between species. Advances in microarray technology have made the systematic study of gene expression evolution possible. In this study, gene expression patterns were compared between human and mouse genomes using two published methods. Specifically, we studied how gene expression evolution was related to GO terms and tried to decode the relationship between promoter evolution and gene expression evolution. The results showed that (1) the significant enrichment of biological processes in orthologs of expression conservation reveals functional significance of gene expression conservation. The more conserved gene expression in some biological processes than is expected in a purely neutral model reveals negative selection on gene expression. However, fast evolving genes mainly support the neutrality of gene expression evolution, and (2) gene expression conservation is positively but only slightly correlated with promoter conservation based on a motif-count score of the promoter alignment. Our results suggest a neutral model with negative selection for gene expression evolution between humans and mice, and promoter evolution could have some effects on gene expression evolution.

Accounting for rate instability and spatial patterns in the boundary analysis of cancer mortality maps

Boundary analysis of cancer maps may highlight areas where causative exposures change through geographic space, the presence of local populations with distinct cancer incidences, or the impact of different cancer control methods. Too often, such analysis ignores the spatial pattern of incidence or mortality rates and overlooks the fact that rates computed from sparsely populated geographic entities can be very unreliable. This paper proposes a new methodology that accounts for the uncertainty and spatial correlation of rate data in the detection of significant edges between adjacent entities or polygons. Poisson kriging is first used to estimate the risk value and the associated standard error within each polygon, accounting for the population size and the risk semivariogram computed from raw rates. The boundary statistic is then defined as half the absolute difference between kriged risks. Its reference distribution, under the null hypothesis of no boundary, is derived through the generation of multiple realizations of the spatial distribution of cancer risk values. This paper presents three types of neutral models generated using methods of increasing complexity: the common random shuffle of estimated risk values, a spatial re-ordering of these risks, or p-field simulation that accounts for the population size within each polygon. The approach is illustrated using age-adjusted pancreatic cancer mortality rates for white females in 295 US counties of the Northeast (1970-1994). Simulation studies demonstrate that Poisson kriging yields more accurate estimates of the cancer risk and how its value changes between polygons (i.e. boundary statistic), relatively to the use of raw rates or local empirical Bayes smoother. When used in conjunction with spatial neutral models generated by p-field simulation, the boundary analysis based on Poisson kriging estimates minimizes the proportion of type I errors (i.e. edges wrongly declared significant) while the frequency of these errors is predicted well by the p-value of the statistical test.

Estimating the relative order of speciation or coalescence events on a given phylogeny

The reconstruction of large phylogenetic trees from data that violates clocklike evolution (or as a supertree constructed from any m input trees) raises a difficult question for biologists-how can one assign relative dates to the vertices of the tree? In this paper we investigate this problem, assuming a uniform distribution on the order of the inner vertices of the tree (which includes, but is more general than, the popular Yule distribution on trees). We derive fast algorithms for computing the probability that (i) any given vertex in the tree was the j-th speciation event (for each j), and (ii) any one given vertex is earlier in the tree than a second given vertex. We show how the first algorithm can be used to calculate the expected length of any given interior edge in any given tree that has been generated under either a constant-rate speciation model, or the coalescent model.

The Distribution of Abundance in Neutral Communities

The patterns of abundance generated by a simple stochastic birth-death-immigration model are described in order to characterize the diversity of neutral communities of ecologically equivalent species. Diversity is described by species number S and the variance of frequency or log abundance q∼. The frequency distribution of abundance is very generally lognormal, skewed to the left by immigration and resembling descriptions of natural communities. Increased immigration and community size always cause S to increase. Their effect on q∼ is more complicated, but given biologically reasonable assumptions, S and q∼ will be positively correlated in most circumstances. Larger samples contain more species; the graph of log S on log individuals, equivalent to a species-area curve, is generally convex upward but becomes linear with a slope of about +0.25 when immigration is low and births exceed deaths. When individuals invade a new, vacant environment, both S and q∼ increase through time. Thus, a positive correlation between S and q∼ will usually be generated when sites of differing size or age are surveyed. At equilibrium, communities maintain roughly constant levels of S and q∼ but change in composition through time; composition may remain similar, however, for many generations. Many prominent patterns observed in natural communities can therefore be generated by a strictly neutral model. This does not show that community structure is determined exclusively by demographic stochasticity, but rather demonstrates the necessity for an appropriate null model when functional hypotheses are being tested.