The transition between the niche and neutral regimes in ecology

Microbial community assembly in engineered bioreactors

Microbial community assembly (MCA) processes that shape microbial communities in environments are being used to analyze engineered bioreactors such as activated sludge systems and anaerobic digesters. The goal of studying MCA is to be able to understand and predict the effect of design and operation procedures on bioreactor microbial composition and function. Ultimately, this can lead to bioreactors that are more efficient, resilient, or resistant to perturbations. This review summarizes the ecological theories underpinning MCA, evaluates MCA analysis methods, analyzes how these MCA-based methods are applied to engineered bioreactors, and extracts lessons from case studies. Furthermore, we suggest future directions in MCA research in engineered bioreactor systems. The review aims to provide insights and guidance to the growing number of environmental engineers who wish to design and understand bioreactors through the lens of MCA.

Phase Transition to Chaos in Complex Ecosystems with Nonreciprocal Species-Resource Interactions

Nonreciprocal interactions between microscopic constituents can profoundly shape the large-scale properties of complex systems. Here, we investigate the effects of nonreciprocity in the context of theoretical ecology by analyzing a generalization of MacArthur's consumer-resource model with asymmetric interactions between species and resources. Using a mixture of analytic cavity calculations and numerical simulations, we show that such ecosystems generically undergo a phase transition to chaotic dynamics as the amount of nonreciprocity is increased. We analytically construct the phase diagram for this model and show that the emergence of chaos is controlled by a single quantity: the ratio of surviving species to surviving resources. We also numerically calculate the Lyapunov exponents in the chaotic phase and carefully analyze finite-size effects. Our findings show how nonreciprocal interactions can give rise to complex and unpredictable dynamical behaviors even in the simplest ecological consumer-resource models.

Les Houches Lectures on Community Ecology: From Niche Theory to Statistical Mechanics

Ecosystems are among the most interesting and well-studied examples of self-organized complex systems. Community ecology, the study of how species interact with each other and the environment, has a rich tradition. Over the last few years, there has been a growing theoretical and experimental interest in these problems from the physics and quantitative biology communities. Here, we give an overview of community ecology, highlighting the deep connections between ecology and statistical physics. We start by introducing the two classes of mathematical models that have served as the workhorses of community ecology: Consumer Resource Models (CRM) and the generalized Lotka-Volterra models (GLV). We place a special emphasis on graphical methods and general principles. We then review recent works showing a deep and surprising connection between ecological dynamics and constrained optimization. We then shift our focus by analyzing these same models in "high-dimensions" (i.e. in the limit where the number of species and resources in the ecosystem becomes large) and discuss how such complex ecosystems can be analyzed using methods from the statistical physics of disordered systems such as the cavity method and Random Matrix Theory.

Phase transition to chaos in complex ecosystems with non-reciprocal species-resource interactions

Non-reciprocal interactions between microscopic constituents can profoundly shape the large-scale properties of complex systems. Here, we investigate the effects of non-reciprocity in the context of theoretical ecology by analyzing a generalization of MacArthur's consumer-resource model with asymmetric interactions between species and resources. Using a mixture of analytic cavity calculations and numerical simulations, we show that such ecosystems generically undergo a phase transition to chaotic dynamics as the amount of non-reciprocity is increased. We analytically construct the phase diagram for this model and show that the emergence of chaos is controlled by a single quantity: the ratio of surviving species to surviving resources. We also numerically calculate the Lyapunov exponents in the chaotic phase and carefully analyze finite-size effects. Our findings show how non-reciprocal interactions can give rise to complex and unpredictable dynamical behaviors even in the simplest ecological consumer-resource models.

Emergent competition shapes top-down versus bottom-up control in multi-trophic ecosystems

Ecosystems are commonly organized into trophic levels-organisms that occupy the same level in a food chain (e.g., plants, herbivores, carnivores). A fundamental question in theoretical ecology is how the interplay between trophic structure, diversity, and competition shapes the properties of ecosystems. To address this problem, we analyze a generalized Consumer Resource Model with three trophic levels using the zero-temperature cavity method and numerical simulations. We derive the corresponding mean-field cavity equations and show that intra-trophic diversity gives rise to an effective "emergent competition" term between species within a trophic level due to feedbacks mediated by other trophic levels. This emergent competition gives rise to a crossover from a regime of top-down control (populations are limited by predators) to a regime of bottom-up control (populations are limited by primary producers) and is captured by a simple order parameter related to the ratio of surviving species in different trophic levels. We show that our theoretical results agree with empirical observations, suggesting that the theoretical approach outlined here can be used to understand complex ecosystems with multiple trophic levels.

Spatial exclusion leads to "tug-of-war" ecological dynamics between competing species within microchannels

Competition is ubiquitous in microbial communities, shaping both their spatial and temporal structure and composition. Classical minimal models of competition, such as the Moran model, have been employed in ecology and evolutionary biology to understand the role of fixation and invasion in the maintenance of population diversity. Informed by recent experimental studies of cellular competition in confined spaces, we extend the Moran model to incorporate mechanical interactions between cells that divide within the limited space of a one-dimensional open microchannel. The model characterizes the skewed collective growth of the cells dividing within the channel, causing cells to be expelled at the channel ends. The results of this spatial exclusion model differ significantly from those of its classical well-mixed counterpart. The mean time to fixation of a species is greatly accelerated, scaling logarithmically, rather than algebraically, with the system size, and fixation/extinction probability sharply depends on the species' initial fractional abundance. By contrast, successful takeovers by invasive species, whether through mutation or immigration, are substantially less likely than in the Moran model. We also find that the spatial exclusion tends to attenuate the effects of fitness differences on the fixation times and probabilities. We find that these effects arise from the combination of the quasi-neutral "tug-of-war" diffusion dynamics of the inter-species boundary around an unstable equipoise point and the quasi-deterministic avalanche dynamics away from the fixed point. These results, which can be tested in microfluidic monolayer devices, have implications for the maintenance of species diversity in dense bacterial and cellular ecosystems where spatial exclusion is central to the competition, such as in organized biofilms or intestinal crypts.

The rate of species extinction in declining or fragmented ecological communities

Loss of habitat can take many forms, ranging from the fragmentation of once-continuous habitat to the slow erosion of populations across continents. Usually, the harm leading to biodiversity loss is not immediately obvious: there is an extinction debt. Most modelling research of extinction debt has focussed on relatively rapid losses of habitat with species loss happening in response afterwards. In this paper, using a niche-orientated community model we compare and contrast two different mechanisms and find contrasting patterns of extinction debt. From small fragments, we typically see the rapid initial loss of many species, followed by a slower loss of species on larger timescales. When we consider slow incremental declines of population sizes, we find initially a slow rate of extinction which subsequently increases exponentially. In such cases, the delayed extinctions may go undetected initially both because the extinctions may be small relative to background randomness and because rate itself is not constant and takes time to reach its maximum.

Life history complementarity and the maintenance of biodiversity

Life history, the schedule of when and how fast organisms grow, die and reproduce, is a critical axis along which species differ from each other^1-4. In parallel, competition is a fundamental mechanism that determines the potential for species coexistence^5-8. Previous models of stochastic competition have demonstrated that large numbers of species can persist over long timescales, even when competing for a single common resource^9-12, but how life history differences between species increase or decrease the possibility of coexistence and, conversely, whether competition constrains what combinations of life history strategies complement each other remain open questions. Here we show that specific combinations of life history strategy optimize the persistence times of species competing for a single resource before one species overtakes its competitors. This suggests that co-occurring species would tend to have such complementary life history strategies, which we demonstrate using empirical data for perennial plants.

The Elevational Gradient of Bird Beta Diversity in the Meili Snow Mountains, Yunnan Province, China

Understanding the elevational patterns of beta diversity in mountain regions is a long-standing problem in biogeography and ecology. Previous research has generally focused on the taxonomy facet on a large scale, but was limited with regard to multi-facet beta diversity. Accordingly, we constructed a multi-dimensional (taxonomic/phylogenetic/functional) framework to analyze the underlying mechanisms of beta diversity. Within an approximately 2000 m altitudinal range (from 2027 m to 3944 m) along the eastern slope of the Meili Snow Mountains in Deqin County, Yunnan Province, China, we performed field surveys of breeding and non-breeding birds in September/2011 and May/2012, respectively. In total, 132 bird species were recorded during the fieldwork. The results indicated that taxonomic beta diversity contributed 56% of the bird species diversity, and its turnover process dominated the altitudinal pattern of taxon beta diversity; beta phylogenetic diversity contributed 42% of the bird phylogenetic diversity, and its turnover process also appeared to be stronger than the nestedness. For both taxonomy and phylogeny, the null models standardized measures (SES.β_sim/SES.β_sne/SES.β_sor) of paired dissimilarities between elevation zones all showed statistically significant differences (p ≤ 0.05) and were higher than expected (SES.β > 0). However, standardized functional beta diversity showed convergence along the elevational gradient with no significant change. Moreover, the functional beta diversity contributed 50% of the bird functional diversity; there was no significant difference between the turnover and the nestedness-resultant component. Based on these results, we discerned that taxonomic and phylogenetic beta diversity patterns among the elevational zone were overdispersed, which indicated that limiting similarity dominated the turnover process among the bird species and phylogenetic communities in the Meili Snow Mountains.

Plant community phylogeny responses to protections and its main drivers in boreal forests, China: General pattern and implications

Patterns of the phylogenetic structure have been broadly applied to predict community assembly processes. However, the distribution pattern of evolutionary diversity and its drivers under nature conservation are still poorly understood in boreal forests. Here, we investigated 1738 sampling plots and subplots from distinct protection intensities (PIs) zones in five representative National Nature Reserves (NNRs). Multiple comparisons, redundancy analysis, and linear mixed model were performed to identify the changes in community phylogeny across different PIs and NNRs and the drivers for these variations. Our results showed considerable plant community phylogeny variations in different NNRs. As indicated by SesMPD (standardized mean pairwise distance) and SesMNTD (standardized the mean nearest taxon distance), trees, shrubs, and herbs presented overdispersed, clustered, and random distribution patterns, respectively, in different PIs. Protection resulted in the phylogenetic structure between the nearest species of trees showing a more overdispersed pattern (p < 0.05). Protection decreased the phylogenetically clustered degree between the nearest species of shrubs (p > 0.05), while the herbs still maintained a random pattern. Community traits explained the most to phylogeny variation of different communities (24 %-71 %, p < 0.01), followed by geoclimatic factors (2 %-24 %) and conservation processes (1 %-21 %). The higher mean annual precipitation and under branch height at the lower latitude area accompanied the higher SesMPD and SesMNTD. The higher PIs attended with higher tree SesMPD, and the longer protection time resulted in higher shrub PSR (phylogenetic species richness) and PSV (phylogenetic species variability). Including the location of NNRs, community traits, and years of protection, rather than only emphasizing PI itself, could optimize community phylogenetic structure and preserve the evolutionary potential of biodiversity.

A basic community dynamics experiment: Disentangling deterministic and stochastic processes in structuring ecological communities

Community dynamics are governed by two opposed processes: species sorting, which produces deterministic dynamics leading to an equilibrium state, and ecological drift, which produces stochastic dynamics. Despite a great deal of theoretical and empirical work aiming to demonstrate the predominance of one or the other of these processes, the importance of drift in structuring communities and maintaining species diversity remains contested. Here, we present the results of a basic community dynamics experiment using floating aquatic plants, designed to measure the relative contributions of species sorting and ecological drift to community change over about a dozen generations. We found that species sorting became overwhelmingly dominant as the experiment progressed, and directed communities toward a stable equilibrium state maintained by negative frequency-dependent selection. The dynamics of any particular species depended on how far its initial frequency was from its equilibrium frequency, however, and consequently the balance of sorting and drift varied among species.

Phenomenology and dynamics of competitive ecosystems beyond the niche-neutral regimes

Structure, composition, and stability of ecological populations are shaped by the inter- and intraspecies interactions within their communities. It remains to be fully understood how the interplay of these interactions with other factors, such as immigration, controls the structure, the diversity, and the long-term stability of ecological systems in the presence of noise and fluctuations. We address this problem using a minimal model of interacting multispecies ecological communities that incorporates competition, immigration, and demographic noise. We find that a complete phase diagram exhibits rich behavior with multiple regimes that go beyond the classical "niche" and "neutral" regimes, extending and modifying the "rare biosphere" or "niche-like" dichotomy. In particular, we observe regimes that cannot be characterized as either niche or neutral where a multimodal species abundance distribution is observed. We characterize the transitions between the different regimes and show how these arise from the underlying kinetics of the species turnover, extinction, and invasion. Our model serves as a minimal null model of noisy competitive ecological systems, against which more complex models that include factors such as mutations and environmental noise can be compared.

Random sampling associated with microbial profiling leads to overestimated stochasticity inference in community assembly

Revealing the mechanisms governing the complex community assembly over space and time is a central issue in ecology. Null models have been developed to quantitatively disentangle the relative importance of deterministic vs. stochastic processes in structuring the compositional variations of biological communities. Similar approaches have been recently extended to the field of microbial ecology. However, the profiling of highly diverse biological communities (e.g., microbial communities) is severely influenced by random sampling issues, leading to undersampled community profiles and overestimated β-diversity, which may further affect stochasticity inference in community assembly. By implementing simulated datasets, this study demonstrate that microbial stochasticity inference is also affected due to random sampling issues associated with microbial profiling. The effects on microbial stochasticity inference for the whole community and the abundant subcommunities were different using different randomization methods in generating null communities. The stochasticity of rare subcommunities, however, was persistently overestimated irrespective of which randomization method was used. Comparatively, the stochastic ratio approach was more sensitive to random sampling issues, whereas the Raup–Crick metric was more affected by randomization methods. As more studies begin to focus on the mechanisms governing abundant and rare subcommunities, we urge cautions be taken for microbial stochasticity inference based on β-diversity, especially for rare subcommunities. Randomization methods to generate null communities shall also be carefully selected. When necessary, the cutoff used for judging the relative importance of deterministic vs. stochastic processes shall be redefined.

Ternary network models for disturbed ecosystems

The complex network of interactions between species makes understanding the response of ecosystems to disturbances an enduring challenge. One commonplace way to deal with this complexity is to reduce the description of a species to a binary presence-absence variable. Though convenient, this limits the patterns of behaviours representable within such models. We address these shortcomings by considering discrete population models that expand species descriptions beyond the binary setting. Specifically, we focus on ternary (three-state) models which, alongside presence and absence, additionally permit species to become overabundant. We apply this ternary framework to the robustness analysis of model ecosystems and show that this expanded description permits the modelling of top-down extinction cascades emerging from consumer pressure or mesopredator release. Results therefore differ significantly from those seen in binary models, where such effects are absent. We also illustrate how this method opens up the modelling of ecosystem disturbances outside the scope of binary models, namely those in which species are externally raised to overabundance. Our method therefore has the potential to provide a richer description of ecosystem dynamics and their disturbances, while at the same time preserving the conceptual simplicity of familiar binary approaches.

Deterministic mechanisms drive bacterial communities assembly in industrial wastewater treatment system

Microbial communities are responsible for biological treatment of many industrial wastewater, but our knowledge of their diversity, assembly patterns, and function is still poor. Here, we analyzed the bacterial communities of wastewater and activated sludge samples taken from 11 full-scale industrial wastewater treatment plants (IWWTPs) characterized by the same process design but different wastewater types and WWTP compartments. We found significantly different diversity and compositions of bacterial assemblages among distinct wastewater types and IWWTPs compartments. IWWTPs bacterial communities exhibited a clear species abundance distribution. The dispersal-driven process was weak in shaping IWWTP communities. Meanwhile, environmental and operating conditions were important factors in regulating the structure of the activated sludge community and pollutants removal, indicating that bacterial community was largely driven by deterministic mechanisms. The core microbial community in IWWTPs was different from that in municipal wastewater treatment plants (MWWTPs), and many taxa (e.g. the genus Citreitalea) rarely were detected before, indicating IWWTPs harbored unique core bacterial communities. Furthermore, we found that bacterial community compositions were strongly linked to activated sludge function. These findings are important to both microbial ecologists and environmental engineers, who may optimize the operation strategies jointly for maintaining biodiversity, which in turn may promote a more stable performance of the IWWTP. Overall, our study enhances the mechanistic understanding of the IWWTP microbial community diversity, assembly patterns, and function, and provides important implications for microbial ecology and wastewater treatment processes.

Stability criteria for the consumption and exchange of essential resources

Models of consumer effects on a shared resource environment have helped clarify how the interplay of consumer traits and resource supply impact stable coexistence. Recent models generalize this picture to include the exchange of resources alongside resource competition. These models exemplify the fact that although consumers shape the resource environment, the outcome of consumer interactions is context-dependent: such models can have either stable or unstable equilibria, depending on the resource supply. However, these recent models focus on a simplified version of microbial metabolism where the depletion of resources always leads to consumer growth. Here, we model an arbitrarily large system of consumers governed by Liebig’s law, where species require and deplete multiple resources, but each consumer’s growth rate is only limited by a single one of these resources. Resources that are taken up but not incorporated into new biomass are leaked back into the environment, possibly transformed by intracellular reactions, thereby tying the mismatch between depletion and growth to cross-feeding. For this set of dynamics, we show that feasible equilibria can be either stable or unstable, again depending on the resource environment. We identify special consumption and production networks which protect the community from instability when resources are scarce. Using simulations, we demonstrate that the qualitative stability patterns derived analytically apply to a broader class of network structures and resource inflow profiles, including cases where multiple species coexist on only one externally supplied resource. Our stability criteria bear some resemblance to classic stability results for pairwise interactions, but also demonstrate how environmental context can shape coexistence patterns when resource limitation and exchange are modeled directly.

The emergence of interstellar molecular complexity explained by interacting networks

Recent years have witnessed the detection of an increasing number of complex organic molecules in interstellar space, some of them being of prebiotic interest. Disentangling the origin of interstellar prebiotic chemistry and its connection to biochemistry and ultimately, to biology is an enormously challenging scientific goal where the application of complexity theory and network science has not been fully exploited. Encouraged by this idea, we present a theoretical and computational framework to model the evolution of simple networked structures toward complexity. In our environment, complex networks represent simplified chemical compounds and interact optimizing the dynamical importance of their nodes. We describe the emergence of a transition from simple networks toward complexity when the parameter representing the environment reaches a critical value. Notably, although our system does not attempt to model the rules of real chemistry nor is dependent on external input data, the results describe the emergence of complexity in the evolution of chemical diversity in the interstellar medium. Furthermore, they reveal an as yet unknown relationship between the abundances of molecules in dark clouds and the potential number of chemical reactions that yield them as products, supporting the ability of the conceptual framework presented here to shed light on real scenarios. Our work reinforces the notion that some of the properties that condition the extremely complex journey from the chemistry in space to prebiotic chemistry and finally, to life could show relatively simple and universal patterns.

Niche-Neutral Continuum Seems to Explain the Global Niche Differentiation and Local Drift of the Human Digestive Tract Microbiome

The human digestive tract (DT) is differentiated into diverse niches and harbors the greatest microbiome diversity of our bodies. Segata et al. (2012) found that the microbiome of diverse habitats along the DT may be classified as four categories or niches with different microbial compositions and metabolic potentials. Nonetheless, few studies have offered theoretical interpretations of the observed patterns, not to mention quantitative mechanistic parameters. Such parameters should capture the essence of the fundamental processes that shape the microbiome distribution, beyond simple ecological metrics such as diversity or composition descriptors, which only capture the manifestations of the mechanisms. Here, we aim to get educated guesses for such parameters by adopting an integrated approach with multisite neutral (MSN) and niche-neutral hybrid (NNH) modeling, via reanalyzing Segata’s 16s-rRNA samples covering 10 DT-sites from over 200 healthy individuals. We evaluate the relative importance of the four essential processes (drift, dispersal, speciation, and selection) in shaping the microbiome distribution and dynamics along DT, which are assumed to form a niche-neutral continuum. Furthermore, the continuum seems to be hierarchical: the selection or niche differentiations seem to play a predominant role (> 90% based on NNH) at the global (the DT metacommunity) level, but the neutral drifts seem to be prevalent (> 90% based on MSN/NNH) at the local sites except for the gut site. An additional finding is that the DT appears to have a fifth niche for the DT microbiome, namely, Keratinized gingival (KG), while in Segata’s original study, only four niches were identified. Specifically, in Segata’s study, KG was classified into the same niche type including buccal mucosa (BM), hard palate (HP), and KG. However, it should be emphasized that the proposal of the fifth niche of KG requires additional verification in the future studies.

Local and collective transitions in sparsely-interacting ecological communities

Interactions in natural communities can be highly heterogeneous, with any given species interacting appreciably with only some of the others, a situation commonly represented by sparse interaction networks. We study the consequences of sparse competitive interactions, in a theoretical model of a community assembled from a species pool. We find that communities can be in a number of different regimes, depending on the interaction strength. When interactions are strong, the network of coexisting species breaks up into small subgraphs, while for weaker interactions these graphs are larger and more complex, eventually encompassing all species. This process is driven by the emergence of new allowed subgraphs as interaction strength decreases, leading to sharp changes in diversity and other community properties, and at weaker interactions to two distinct collective transitions: a percolation transition, and a transition between having a unique equilibrium and having multiple alternative equilibria. Understanding community structure is thus made up of two parts: first, finding which subgraphs are allowed at a given interaction strength, and secondly, a discrete problem of matching these structures over the entire community. In a shift from the focus of many previous theories, these different regimes can be traversed by modifying the interaction strength alone, without need for heterogeneity in either interaction strengths or the number of competitors per species.

Evidence for Alternate Stable States in an Ecuadorian Andean Cloud Forest

Tree diversity inventories were undertaken. The goal of this study was to understand changes in tree community dynamics that may result from common anthropogenic disturbances at the Reserva Los Cedros, a tropical montane cloud forest reserve in northern Andean Ecuador. The reserve shows extremely high alpha and beta tree diversity. We found that all primary forest sites, regardless of age of natural gaps, are quite ecologically resilient, appearing to return to a primary-forest-type community of trees following gap formation. In contrast, forests regenerating from anthropogenic disturbance appear to have multiple possible ecological states. Where anthropogenic disturbance was intense, novel tree communities appear to be assembling, with no indication of return to a primary forest state. Even in ancient primary forests, new forest types may be forming, as we found that seedling community composition did not resemble adult tree communities. We also suggest small watersheds as a useful basic spatial unit for understanding biodiversity patterns in the tropical Andes that confound more traditional Euclidean distance as a basic proxy of dissimilarity. Finally, we highlight the conservation value of Reserva Los Cedros, which has managed to reverse deforestation within its boundaries despite a general trend of extensive deforestation in the surrounding region, to protect a large, contiguous area of highly endangered Andean primary cloud forest.

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.

Stochastic neutral drifts seem prevalent in driving human virome assembly: neutral, near-neutral and non-neutral theoretic analyses

It is estimated that human body is inhabited by approximately 380 trillions of viruses, which exist in the form of viral communities and are collectively termed as human virome. How virome is assembled and what kind of forces maintain the composition and diversity of viral communities is still an open question. The question is of obvious importance because of its implications to human health and diseases. Here we address the question by harnessing the power of Hubbell’s unified neutral theory of biodiversity (UNTB) in terms of three neutral models including standard Hubbell’s neutral model (HNM), Sloan’s near-neutral model (SNM) and Harris et al. (2017) multi-site neutral model (MSN), further augmented by Ning et al. (2019) normalized stochasticity ratio (NSR) and Hammal et al. (2015) power analysis for the neutral test (PNT). With the five models applied to 179 virome samples, we aim to obtain robust findings given both Type-I and Type-II errors are addressed and possible alternative, non-neutral processes are detected. It was found that stochastic neutral drifts seem prevalent: approximately 65–92% at metacommunity/landscape scales and 67–80% at virus species scale. The non-neutral selection is approximately 26–28% at community scale and 23% at species scale. The false negative rate is about 2–3%, which suggested rather limited confounding effects of non-neutral process on neutrality tests. We postulate that prevalence of neutrality in human virome is likely due to extremely simple structure of viruses (stands of DNA/RNA) and their inter-species homogeneities, forming the foundation of species equivalence—the hallmark of neutral theory.

The effect of microbial selection on the occurrence-abundance patterns of microbiomes

Theoretical models are useful to investigate the drivers of community dynamics. In the simplest case of neutral models, the events of death, birth and immigration of individuals are assumed to only depend on their abundance-thus, all types share the same parameters. The community level expectations arising from these simple models and their agreement to empirical data have been discussed extensively, often suggesting that in nature, rates might indeed be neutral or their differences might not be important. However, how robust are these model predictions to type-specific rates? Also, what are the consequences at the level of types? Here, we address these questions moving from simple neutral communities to heterogeneous communities. For this, we build a model where types are differently adapted to the environment. We compute the equilibrium distribution of the abundances. Then, we look into the occurrence-abundance pattern often reported in microbial communities. We observe that large immigration and biodiversity-common in microbial systems-lead to such patterns, regardless of whether the rates are neutral or non-neutral. We conclude by discussing the implications to interpret and test empirical data.

Well-mixed Lotka-Volterra model with random strongly competitive interactions

The random Lotka-Volterra model is widely used to describe the dynamical and thermodynamic features of ecological communities. In this work, we consider random symmetric interactions between species and analyze the strongly competitive interaction case. We investigate different scalings for the distribution of the interactions with the number of species and try to bridge the gap with previous works. Our results show two different behaviors for the mean abundance at zero and finite temperature, respectively, with a continuous crossover between the two. We confirm and extend previous results obtained for weak interactions: at zero temperature, even in the strong competitive interaction limit, the system is in a multiple-equilibria phase, whereas at finite temperature only a unique stable equilibrium can exist. Finally, we establish the qualitative phase diagrams and compare the species abundance distributions in the two cases.

Species Abundance Distributions Patterns between Tiankeng Forests and Nearby Non-Tiankeng Forests in Southwest China

Identifying the species abundance distributions (SADs) in Tiankeng forests is crucial for restoring and managing degraded karst ecosystem, whereas previous studies rarely explored the differences and response of vegetation dynamics to environmental variations. The species composition and SADs of the inner and outer fringe areas of Tiankeng forest and nearby non-Tiankeng forest were compared in Southwest China. Six models were adopted to compare SADs of three habitats. Kolmogrov–Smirnov (K–S) test was selected to compare the discrepancy between the simulated and observed SAD patterns. The Akaike Information Criterion (AIC) test was adopted to compare the models, and the best model was indicated by the lowest AIC value. The results showed that (1) the species dispersal from the inside of Tiankeng forests to the nearby non-Tiankeng forests is limited, while species have unlimited dispersal from nearby non-Tiankeng forests to the inside of Tiankeng forests via the fringe of Tiankeng forests. (2) Species abundance, species rarity, richness, and species accumulation rate in the Tiankeng forests were significant in non-Tiankeng forests (p < 0.05), and most species in inner Tiankeng forests originated from nearby non-Tiankeng forests. (3) Based on the criterion of K-S values, all models have passed the K–S test (p > 0.05), which indicated that niche processes and neutral process worked together in the maintenance of community species diversity, the community in study area is a niche-neutral continuum. (4) Considered the lowest AIC value, the neutral (△mean AIC = 1.3) models performed better than the niche (△mean AIC = 22.7) models and statistical (△mean AIC = 2.7) in the Tiankeng forest, while the statistical models performed better than the niche and neutral models in the non-Tiankeng forests. The results suggested that the main driving force of Tiankeng forests is the neutral process. The negative terrain in Tiankeng restricted the species dispersal due to topographic constraints. However, the species dispersal from the nearby non-Tiankeng forests could promote the species succession in the inner Tiankeng. Therefore, we propose that nearby non-Tiankeng forests should be emphasized for protecting the biodiversity of Tiankeng forests.

The chosen few-variations in common and rare soil bacteria across biomes

Soil bacterial communities are dominated by a few abundant species, while their richness is associated with rare species with largely unknown ecological roles and biogeography. Analyses of previously published soil bacterial community data using a novel classification of common and rare bacteria indicate that only 0.4% of bacterial species can be considered common and are prevalent across biomes. The remaining bacterial species designated as rare are endemic with low relative abundances. Observations coupled with mechanistic models highlight the central role of soil wetness in shaping bacterial rarity. An individual-based model reveals systematic shifts in community composition induced by low carbon inputs in drier soils that deprive common species of exhibiting physiological advantages relative to other species. We find that only a "chosen few" common species shape bacterial communities across biomes; however, their contributions are curtailed in resource-limited environments where a larger number of rare species constitutes the soil microbiome.

The Dynamic Hypercube as a Niche Community Model

Different models of community dynamics, such as the MacArthur–Wilson theory of island biogeography and Hubbell’s neutral theory, have given us useful insights into the workings of ecological communities. Here, we develop the niche-hypervolume concept of the community into a powerful model of community dynamics. We describe the community’s size through the volume of the hypercube and the dynamics of the populations in it through the fluctuations of the axes of the niche hypercube on different timescales. While the community’s size remains constant, the relative volumes of the niches within it change continuously, thus allowing the populations of different species to rise and fall in a zero-sum fashion. This dynamic hypercube model reproduces several key patterns in communities: lognormal species abundance distributions, 1/f-noise population abundance, multiscale patterns of extinction debt and logarithmic species-time curves. It also provides a powerful framework to explore significant ideas in ecology, such as the drift of ecological communities into evolutionary time.

Evaluating the Assembly Dynamics in the Human Vaginal Microbiomes With Niche-Neutral Hybrid Modeling

Using 2,733 longitudinal vaginal microbiome samples (representing local microbial communities) from 79 individuals (representing meta-communities) in the states of healthy, BV (bacterial vaginosis) and pregnancy, we assess and interpret the relative importance of stochastic forces (e.g., stochastic drifts in bacteria demography, and stochastic dispersal) vs. deterministic selection (e.g., host genome, and host physiology) in shaping the dynamics of human vaginal microbiome (HVM) diversity by an integrated analysis with multi-site neutral (MSN) and niche-neutral hybrid (NNH) modeling. It was found that, when the traditional “default” P-value = 0.05 was specified, the neutral drifts were predominant (≥50% metacommunities indistinguishable from the MSN prediction), while the niche differentiations were moderate (<20% from the NNH prediction). The study also analyzed two challenging uncertainties in testing the neutral and/or niche-neutral hybrid models, i.e., lack of full model specificity – non-unique fittings of same datasets to multiple models with potentially different mechanistic assumptions – and lack of definite rules for setting the P-value thresholds (also noted as P_t-value when referring to the threshold of P-value in this article) in testing null hypothesis (model). Indeed, the two uncertainties can be interdependent, which further complicates the statistical inferences. To deal with the uncertainties, the MSN/NNH test results under a series of P-values ranged from 0.05 to 0.95 were presented. Furthermore, the influence of P-value threshold-setting on the model specificity, and the effects of woman’s health status on the neutrality level of HVM were examined. It was found that with the increase of P-value threshold from 0.05 to 0.95, the overlap (non-unique) fitting of MSN and NNH decreased from 29.1 to 1.3%, whereas the specificity (uniquely fitted to data) of MSN model was kept between 55.7 and 82.3%. Also with the rising P-value threshold, the difference between healthy and BV groups become significant. These findings suggested that traditional single P-value threshold (such as the de facto standard P-value = 0.05) might be insufficient for testing the neutral and/or niche neutral hybrid models.

Dispersal-based versus niche-based processes as drivers of flea species composition on small mammalian hosts: inferences from species occurrences at large and small scales

Biological communities may be assembled by both niche-based and dispersal-based (= historic) processes with the relative importance of these processes in community assembly being scale- and context-dependent. To infer whether (a) niche-based or dispersal-based processes play the main role in the assembly of flea communities parasitic on small mammals and whether (b) the main processes of flea community assembly are scale-dependent, we applied a novel permutation-based algorithm (PER-SIMPER) and the dispersal-niche continuum index (DNCI), to data on the species incidence of fleas and their hosts at two spatial scales. At the larger (continental) scale, we analysed flea communities in four biogeographic realms across adjacent continental sections. At the smaller (local) scale, we considered flea communities across two main regions (lowlands and mountains) and seven habitat types within Slovakia. Our analyses demonstrated that species composition of fleas and their small mammalian hosts depended predominantly on historical processes (dispersal) at both scale. This was true for the majority of biogeographic realms at continental scale (except the Nearctic) and both regions at local scale. Nevertheless, strong niche-based assembly mechanism was found in the Nearctic assemblages. At local scale, the intensity of dispersal processes was weaker and niche-driven processes were stronger between habitats within a region than between mountain and lowland regions. We provide historical and ecological explanations for these patterns. We conclude that the assembly of compound flea communities is governed, to a great extent, by the dispersal processes acting on their hosts and, to a lesser extent, by the niche-based processes.

Properties of Equilibria and Glassy Phases of the Random Lotka-Volterra Model with Demographic Noise

We study a reference model in theoretical ecology, the disordered Lotka-Volterra model for ecological communities, in the presence of finite demographic noise. Our theoretical analysis, valid for symmetric interactions, shows that for sufficiently heterogeneous interactions and low demographic noise the system displays a multiple equilibria phase, which we fully characterize. In particular, we show that in this phase the number of locally stable equilibria is exponential in the number of species. Upon further decreasing the demographic noise, we unveil the presence of a second transition like the so-called "Gardner" transition to a marginally stable phase similar to that observed in the jamming of amorphous materials. We confirm and complement our analytical results by numerical simulations. Furthermore, we extend their relevance by showing that they hold for other interacting random dynamical systems such as the random replicant model. Finally, we discuss their extension to the case of asymmetric couplings.

Microbial Communities in Full-Scale Wastewater Treatment Systems Exhibit Deterministic Assembly Processes and Functional Dependency over Time

Microbial communities constitute the core component of biological wastewater treatment processes. We conducted a meta-analysis based on the 16S rRNA gene of temporal samples obtained from diverse full-scale activated sludge and anaerobic digestion systems treating municipal and industrial wastewater (collected in this study and published previously) to investigate their community assembly mechanism and functional traits over time, which are not currently well understood. The influent composition was found to be the main driver of the microbial community's composition, and relatively large proportions of specialist (26.1% and 18.6%) and transient taxa (67.2% and 68.1%) were estimated in both systems. Deterministic processes, especially homogeneous selection events (accounting for >53.8% of assembly events), were consistently identified as the dominant microbial community assembly mechanisms in both systems over time. Significant and strong correlations (Pearson's r = 0.51-0.92) were detected between the dynamics of the temporal community and the functional compositions in both systems, which suggests functional dependency. In contrast, the occurrence of sludge bulking and foaming in the activated sludge system led to an increase in stochastic assembly processes (i.e., limited dispersal and undominated events), a shift toward functional redundancy and less community diversity, a decreased community niche breadth index, and a more compact co-association network. This study illustrates that the mechanism of microbial community assembly and functional traits over time can be used to diagnose system performance and provide information on potential system malfunction.

Nonlinearity-generated resilience in large complex systems

We consider a generic nonlinear extension of May's 1972 model by including all higher-order terms in the expansion around the chosen fixed point (placed at the origin) with random Gaussian coefficients. The ensuing analysis reveals that as long as the origin remains stable, it is surrounded by a "resilience gap": there are no other fixed points within a radius r_{*}>0 and the system is therefore expected to be resilient to a typical initial displacement small in comparison to r_{*}. The radius r_{*} is shown to vanish at the same threshold where the origin loses local stability, revealing a mechanism by which systems close to the tipping point become less resilient. We also find that beyond the resilience radius the number of fixed points in a ball surrounding the original point of equilibrium grows exponentially with N, making systems dynamics highly sensitive to far enough displacements from the origin.

Niche-neutral theoretic approach to mechanisms underlying the biodiversity and biogeography of human microbiomes

The human microbiome consists of five major regional biomes distributed in or on our five body sites including skin, oral, lung, gut, and reproductive tract. Its biogeography (the spatial and temporal distribution of its biodiversity) has far-reaching implications to our health and diseases. Nevertheless, we currently have very limited understanding on the mechanisms shaping the biogeography, since it is often rather difficult to determine the relative importance of drift, dispersal, speciation, and selection, the four processes (mechanisms) determining the patterns of microbial biogeography and community dynamics according to a recent synthesis in community ecology and biogeography. To disentangle these mechanisms, I utilize multisite neutral (MSN) model and niche-neutral hybrid (NNH) model to analyze large number of truly multisite microbiome samples covering all five major human microbiome habitats, including 699 metacommunities and 5,420 local communities. Approximately 89% of metacommunities and 92% local communities exhibit patterns indistinguishable from neutral, and 20% indistinguishable from niche-neutral hybrid model, indicating the relative significance of stochastic neutral forces versus deterministic niche selection in shaping the biogeography of human microbiome. These findings cast supporting evidence to van der Gast's revision to classic Bass-Becking doctrine of microbial biogeography: "Some things are everywhere and some things are not. Sometimes the environment selects and sometimes it doesn't," offering the first educated guess for "some" and "sometimes" in the revised doctrine. Furthermore, the logistic/Cox regression models describing the relationships among community neutrality, niche differentiation, and key community/species characteristics (including community diversity, community/species dominance, speciation, and migration rates) were constructed to quantitatively describe the niche-neutral continuum and the influences of community/species properties on the continuum.

Emergent neutrality in consumer-resource dynamics

Neutral theory assumes all species and individuals in a community are ecologically equivalent. This controversial hypothesis has been tested across many taxonomic groups and environmental contexts, and successfully predicts species abundance distributions across multiple high-diversity communities. However, it has been critiqued for its failure to predict a broader range of community properties, particularly regarding community dynamics from generational to geological timescales. Moreover, it is unclear whether neutrality can ever be a true description of a community given the ubiquity of interspecific differences, which presumably lead to ecological inequivalences. Here we derive analytical predictions for when and why non-neutral communities of consumers and resources may present neutral-like outcomes, which we verify using numerical simulations. Our results, which span both static and dynamical community properties, demonstrate the limitations of summarizing distributions to detect non-neutrality, and provide a potential explanation for the successes of neutral theory as a description of macroecological pattern.

The neutral theory of biodiversity assumes that species are ecologically equivalent. Given the natural history observation of ubiquitous phenotypic differences between species, it is surprising that neutral theory has successfully predicted a broad range of biodiversity patterns, and simultaneously unsurprising that these results have not convinced ecologists that the natural world is neutral. However, we have lacked a description of how neutrality can emerge in a natural way from ecological mechanisms and species differences. Our study sheds light on this question, providing a theoretical backdrop for the success of neutral theory as a description of macroecological pattern. We derive a prediction for the degree to which consumers must differ in preferences for different resources before the resulting biodiversity patterns become distinguishable from neutrality. These predictions, which we confirm using simulations, show that neutral-like outcomes are possible even when resource requirements across consumers are very far from neutral. Our results can be tested in experimental microbial communities, where, equipped with an inferred consumption network, our analysis can yield predictions for biodiversity patterns and community turnover at different taxonomic levels.

Effect of Resource Dynamics on Species Packing in Diverse Ecosystems

The competitive exclusion principle asserts that coexisting species must occupy distinct ecological niches (i.e., the number of surviving species cannot exceed the number of resources). An open question is to understand if and how different resource dynamics affect this bound. Here, we analyze a generalized consumer resource model with externally supplied resources and show that-in contrast to self-renewing resources-species can occupy only half of all available environmental niches. This motivates us to construct a new schema for classifying ecosystems based on species packing properties.

Stochastic logistic models reproduce experimental time series of microbial communities

We analyze properties of experimental microbial time series, from plankton and the human microbiome, and investigate whether stochastic generalized Lotka-Volterra models could reproduce those properties. We show that this is the case when the noise term is large and a linear function of the species abundance, while the strength of the self-interactions varies over multiple orders of magnitude. We stress the fact that all the observed stochastic properties can be obtained from a logistic model, that is, without interactions, even the niche character of the experimental time series. Linear noise is associated with growth rate stochasticity, which is related to changes in the environment. This suggests that fluctuations in the sparsely sampled experimental time series may be caused by extrinsic sources.

Reconstructing ecological networks with noisy dynamics

Ecosystems functioning is based on an intricate web of interactions among living entities. Most of these interactions are difficult to observe, especially when the diversity of interacting entities is large and they are of small size and abundance. To sidestep this limitation, it has become common to infer the network structure of ecosystems from time series of species abundance, but it is not clear how well can networks be reconstructed, especially in the presence of stochasticity that propagates through ecological networks. We evaluate the effects of intrinsic noise and network topology on the performance of different methods of inferring network structure from time-series data. Analysis of seven different four-species motifs using a stochastic model demonstrates that star-shaped motifs are differentially detected by these methods while rings are differentially constructed. The ability to reconstruct the network is unaffected by the magnitude of stochasticity in the population dynamics. Instead, interaction between the stochastic and deterministic parts of the system determines the path that the whole system takes to equilibrium and shapes the species covariance. We highlight the effects of long transients on the path to equilibrium and suggest a path forward for developing more ecologically sound statistical techniques.

Disentangling the mechanisms shaping the surface ocean microbiota

BACKGROUND

The ocean microbiota modulates global biogeochemical cycles and changes in its configuration may have large-scale consequences. Yet, the underlying ecological mechanisms structuring it are unclear. Here, we investigate how fundamental ecological mechanisms (selection, dispersal and ecological drift) shape the smallest members of the tropical and subtropical surface-ocean microbiota: prokaryotes and minute eukaryotes (picoeukaryotes). Furthermore, we investigate the agents exerting abiotic selection on this assemblage as well as the spatial patterns emerging from the action of ecological mechanisms. To explore this, we analysed the composition of surface-ocean prokaryotic and picoeukaryotic communities using DNA-sequence data (16S- and 18S-rRNA genes) collected during the circumglobal expeditions Malaspina-2010 and TARA-Oceans.

RESULTS

We found that the two main components of the tropical and subtropical surface-ocean microbiota, prokaryotes and picoeukaryotes, appear to be structured by different ecological mechanisms. Picoeukaryotic communities were predominantly structured by dispersal-limitation, while prokaryotic counterparts appeared to be shaped by the combined action of dispersal-limitation, selection and drift. Temperature-driven selection appeared as a major factor, out of a few selected factors, influencing species co-occurrence networks in prokaryotes but not in picoeukaryotes, indicating that association patterns may contribute to understand ocean microbiota structure and response to selection. Other measured abiotic variables seemed to have limited selective effects on community structure in the tropical and subtropical ocean. Picoeukaryotes displayed a higher spatial differentiation between communities and a higher distance decay when compared to prokaryotes, consistent with a scenario of higher dispersal limitation in the former after considering environmental heterogeneity. Lastly, random dynamics or drift seemed to have a more important role in structuring prokaryotic communities than picoeukaryotic counterparts.

CONCLUSIONS

The differential action of ecological mechanisms seems to cause contrasting biogeography, in the tropical and subtropical ocean, among the smallest surface plankton, prokaryotes and picoeukaryotes. This suggests that the idiosyncrasy of the main constituents of the ocean microbiota should be considered in order to understand its current and future configuration, which is especially relevant in a context of global change, where the reaction of surface ocean plankton to temperature increase is still unclear. Video Abstract.

Statistical mechanics of interacting metabolic networks

We cast the metabolism of interacting cells within a statistical mechanics framework considering both the actual phenotypic capacities of each cell and its interaction with its neighbors. Reaction fluxes will be the components of high-dimensional spin vectors, whose values will be constrained by the stochiometry and the energy requirements of the metabolism. Within this picture, finding the phenotypic states of the population turns out to be equivalent to searching for the equilibrium states of a disordered spin model. We provide a general solution of this problem for arbitrary metabolic networks and interactions. We apply this solution to a simplified model of metabolism and to a complex metabolic network, the central core of Escherichia coli, and demonstrate that the combination of selective pressure and interactions defines a complex phenotypic space. We also present numerical results for cells fixed in a grid. These results reproduce the qualitative picture discussed for the mean-field model. Cells may specialize in producing or consuming metabolites complementing each other, and this is described by an equilibrium phase space with multiple minima, like in a spin-glass model.

The Community Simulator: A Python package for microbial ecology

Natural microbial communities contain hundreds to thousands of interacting species. For this reason, computational simulations are playing an increasingly important role in microbial ecology. In this manuscript, we present a new open-source, freely available Python package called Community Simulator for simulating microbial population dynamics in a reproducible, transparent and scalable way. The Community Simulator includes five major elements: tools for preparing the initial states and environmental conditions for a set of samples, automatic generation of dynamical equations based on a dictionary of modeling assumptions, random parameter sampling with tunable levels of metabolic and taxonomic structure, parallel integration of the dynamical equations, and support for metacommunity dynamics with migration between samples. To significantly speed up simulations using Community Simulator, our Python package implements a new Expectation-Maximization (EM) algorithm for finding equilibrium states of community dynamics that exploits a recently discovered duality between ecological dynamics and convex optimization. We present data showing that this EM algorithm improves performance by between one and two orders compared to direct numerical integration of the corresponding ordinary differential equations. We conclude by listing several recent applications of the Community Simulator to problems in microbial ecology, and discussing possible extensions of the package for directly analyzing microbiome compositional data.

Effects of niche overlap on coexistence, fixation and invasion in a population of two interacting species

Synergistic and antagonistic interactions in multi-species populations-such as resource sharing and competition-result in remarkably diverse behaviours in populations of interacting cells, such as in soil or human microbiomes, or clonal competition in cancer. The degree of inter- and intra-specific interaction can often be quantified through the notion of an ecological 'niche'. Typically, weakly interacting species that occupy largely distinct niches result in stable mixed populations, while strong interactions and competition for the same niche result in rapid extinctions of some species and fixations of others. We investigate the transition of a deterministically stable mixed population to a stochasticity-induced fixation as a function of the niche overlap between the two species. We also investigate the effect of the niche overlap on the population stability with respect to external invasions. Our results have important implications for a number of experimental systems.

Neutral and niche forces as drivers of species selection

The evolutionary and ecological processes behind the origin of species are among the most fundamental problems in biology. In fact, many theoretical hypothesis on different type of speciation have been proposed. In particular, models of sympatric speciation leading to the formation of new species without geographical isolation, are based on the niche hypothesis: the diversification of the population is induced by the competition for a limited set of available resources. Interestingly, neutral models of evolution have shown that stochastic forces are sufficient to generate coexistence of different species. In this work, we put forward this dichotomy within the context of species formation, studying how neutral and niche forces contribute to sympatric speciation in a model ecosystem. In particular, we study the evolution of a population of individuals with asexual reproduction whose inherited characters or phenotypes are specified by both niche-based and neutral traits. We analyze the stationary state of the dynamics, and study the distribution of individuals in the whole phenotypic space. We show, both numerically and analytically, that there is a non-trivial coupling between neutral and niche forces induced by stochastic effects in the evolution of the population allowing the formation of clusters, that is, species in the phenotypic space. Remarkably, our framework can be generalized also to sexual reproduction or other type of population dynamics.

The importance of neutral over niche processes in structuring Ediacaran early animal communities

The relative influence of niche vs. neutral processes in ecosystem dynamics is an on-going debate, but the extent to which they structured the earliest animal communities is unknown. Some of the oldest known metazoan-dominated paleocommunities occur in Ediacaran age (~ 565 million years old) strata in Newfoundland, Canada and Charnwood Forest, UK. These comprise large and diverse populations of sessile organisms that are amenable to spatial point process analyses, enabling inference of the most likely underlying niche or neutral processes governing community structure. We mapped seven Ediacaran paleocommunities using LiDAR, photogrammetry and a laser line probe. We found that neutral processes dominate these paleocommunities, with niche processes exerting limited influence, in contrast with the niche-dominated dynamics of modern marine ecosystems. The dominance of neutral processes suggests that early metazoan diversification may not have been driven by systematic adaptations to the local environment, but instead may have resulted from stochastic demographic differences.

Fecal Microbiotas of Indonesian and New Zealand Children Differ in Complexity and Bifidobacterial Taxa during the First Year of Life

The biological succession that occurs during the first year of life in the gut of infants in Western countries is broadly predictable in terms of the increasing complexity of the composition of microbiotas. Less information is available about microbiotas in Asian countries, where environmental, nutritional, and cultural influences may differentially affect the composition and development of the microbial community. We compared the fecal microbiotas of Indonesian (n = 204) and New Zealand (NZ) (n = 74) infants 6 to 7 months and 12 months of age. Comparisons were made by analysis of 16S rRNA gene sequences and derivation of community diversity metrics, relative abundances of bacterial families, enterotypes, and cooccurrence correlation networks. Abundances of Bifidobacterium longum subsp. infantis and B. longum subsp. longum were determined by quantitative PCR. All observations supported the view that the Indonesian and NZ infant microbiotas developed in complexity over time, but the changes were much greater for NZ infants. B. longum subsp. infantis dominated the microbiotas of Indonesian children, whereas B. longum subsp. longum was dominant in NZ children. Network analysis showed that the niche model (in which trophic adaptation results in preferential colonization) of the assemblage of microbiotas was supported in Indonesian infants, whereas the neutral (stochastic) model was supported by the development of the microbiotas of NZ infants. The results of the study show that the development of the fecal microbiota is not the same for infants in all countries, and they point to the necessity of obtaining a better understanding of the factors that control the colonization of the gut in early life.IMPORTANCE This study addresses the microbiology of a natural ecosystem (the infant bowel) for children in a rural setting in Indonesia and in an urban environment in New Zealand. Analysis of DNA sequences generated from the microbial community (microbiota) in the feces of the infants during the first year of life showed marked differences in the composition and complexity of the bacterial collections. The differences were most likely due to differences in the prevalence and duration of breastfeeding of infants in the two countries. These kinds of studies are essential for developing concepts of microbial ecology related to the influence of nutrition and environment on the development of the gut microbiota and for determining the long-term effects of microbiological events in early life on human health and well-being.