Genomic structure predicts metabolite dynamics in microbial communities.

The metabolic activities of microbial communities play a defining role in the evolution and persistence of life on Earth, driving redox reactions that give rise to global biogeochemical cycles. Community metabolism emerges from a hierarchy of processes, including gene expression, ecological interactions, and environmental factors. In wild communities, gene content is correlated with environmental context, but predicting metabolite dynamics from genomes remains elusive. Here, we show, for the process of denitrification, that metabolite dynamics of a community are predictable from the genes each member of the community possesses. A simple linear regression reveals a sparse and generalizable mapping from gene content to metabolite dynamics for genomically diverse bacteria. A consumer-resource model correctly predicts community metabolite dynamics from single-strain phenotypes. Our results demonstrate that the conserved impacts of metabolic genes can predict community metabolite dynamics, enabling the prediction of metabolite dynamics from metagenomes, designing denitrifying communities, and discovering how genome evolution impacts metabolism.

Microbiome Assembly in Fermented Foods.

For thousands of years, humans have enjoyed the novel flavors, increased shelf-life, and nutritional benefits that microbes provide in fermented foods and beverages. Recent sequencing surveys of ferments have mapped patterns of microbial diversity across space, time, and production practices. But a mechanistic understanding of how fermented food microbiomes assemble has only recently begun to emerge. Using three foods as case studies (surface-ripened cheese, sourdough starters, and fermented vegetables), we use an ecological and evolutionary framework to identify how microbial communities assemble in ferments. By combining in situ sequencing surveys with in vitro models, we are beginning to understand how dispersal, selection, diversification, and drift generate the diversity of fermented food communities. Most food producers are unaware of the ecological processes occurring in their production environments, but the theory and models of ecology and evolution can provide new approaches for managing fermented food microbiomes, from farm to ferment.

Coexistence of many species under a random competition-colonization trade-off.

The competition-colonization (CC) trade-off is a well-studied coexistence mechanism for metacommunities. In this setting, it is believed that the coexistence of all species requires their traits to satisfy restrictive conditions limiting their similarity. To investigate whether diverse metacommunities can assemble in a CC trade-off model, we study their assembly from a probabilistic perspective. From a pool of species with parameters (corresponding to traits) sampled at random, we compute the probability that any number of species coexist and characterize the set of species that emerges through assembly. Remarkably, almost exactly half of the species in a large pool typically coexist, with no saturation as the size of the pool grows, and with little dependence on the underlying distribution of traits. Through a mix of analytical results and simulations, we show that this unlimited niche packing emerges as assembly actively moves communities toward overdispersed configurations in niche space. Our findings also apply to a realistic assembly scenario where species invade one at a time from a fixed regional pool. When diversity arises de novo in the metacommunity, richness still grows without bound, but more slowly. Together, our results suggest that the CC trade-off can support the robust emergence of diverse communities, even when coexistence of the full species pool is exceedingly unlikely.

Learning beyond-pairwise interactions enables the bottom-up prediction of microbial community structure.

Understanding the assembly of multispecies microbial communities represents a significant challenge in ecology and has wide applications in agriculture, wastewater treatment, and human healthcare domains. Traditionally, studies on the microbial community assembly focused on analyzing pairwise relationships among species; however, neglecting higher-order interactions, i.e., the change of pairwise relationships in the community context, may lead to substantial deviation from reality. Herein, we have proposed a simple framework that incorporates higher-order interactions into a bottom-up prediction of the microbial community assembly and examined its accuracy using a seven-member synthetic bacterial community on a host plant, duckweed. Although the synthetic community exhibited emergent properties that cannot be predicted from pairwise coculturing results, our results demonstrated that incorporating information from three-member combinations allows the acceptable prediction of the community structure and actual interaction forces within it. This reflects that the occurrence of higher-order effects follows consistent patterns, which can be predicted even from trio combinations, the smallest unit of higher-order interactions. These results highlight the possibility of predicting, explaining, and understanding the microbial community structure from the bottom-up by learning interspecies interactions from simple beyond-pairwise combinations.

Interspecies interactions determine growth dynamics of biopolymer-degrading populations in microbial communities.

Microbial communities perform essential ecosystem functions such as the remineralization of organic carbon that exists as biopolymers. The first step in mineralization is performed by biopolymer degraders, which harbor enzymes that can break down polymers into constituent oligo- or monomeric forms. The released nutrients not only allow degraders to grow, but also promote growth of cells that either consume the degradation products, i.e., exploiters, or consume metabolites released by the degraders or exploiters, i.e., scavengers. It is currently not clear how such remineralizing communities assemble at the microscale-how interactions between the different guilds influence their growth and spatial distribution, and hence the development and dynamics of the community. Here, we address this knowledge gap by studying marine microbial communities that grow on the abundant marine biopolymer alginate. We used batch growth assays and microfluidics coupled to time-lapse microscopy to quantitatively investigate growth and spatial distribution of single cells. We found that the presence of exploiters or scavengers alters the spatial distribution of degrader cells. In general, exploiters and scavengers-which we collectively refer to as cross-feeder cells-slowed down the growth of degrader cells. In addition, coexistence with cross-feeders altered the production of the extracellular enzymes that break down polymers by degrader cells. Our findings reveal that ecological interactions by nondegrading community members have a profound impact on the functions of microbial communities that remineralize carbon biopolymers in nature.

Resource competition can explain simplicity in microbial community assembly.

Predicting the composition and diversity of communities is a central goal in ecology. While community assembly is considered hard to predict, laboratory microcosms often follow a simple assembly rule based on the outcome of pairwise competitions. This assembly rule predicts that a species that is excluded by another species in pairwise competition cannot survive in a multispecies community with that species. Despite the empirical success of this bottom-up prediction, its mechanistic origin has remained elusive. In this study, we elucidate how this simple pattern in community assembly can emerge from resource competition. Our geometric analysis of a consumer-resource model shows that trio community assembly is always predictable from pairwise outcomes when one species grows faster than another species on every resource. We also identify all possible trio assembly outcomes under three resources and find that only two outcomes violate the assembly rule. Simulations demonstrate that pairwise competitions accurately predict trio assembly with up to 100 resources and the assembly of larger communities containing up to twelve species. We then further demonstrate accurate quantitative prediction of community composition using the harmonic mean of pairwise fractions. Finally, we show that cross-feeding between species does not decrease assembly rule prediction accuracy. Our findings highlight that simple community assembly can emerge even in ecosystems with complex underlying dynamics.

Stochastic microbiome assembly depends on context.

Observational studies reveal substantial variability in microbiome composition across individuals. Targeted studies in gnotobiotic animals underscore this variability by showing that some bacterial strains colonize deterministically, while others colonize stochastically. While some of this variability can be explained by external factors like environmental, dietary, and genetic differences between individuals, in this paper we show that for the model organism Drosophila melanogaster, interactions between bacteria can affect the microbiome assembly process, contributing to a baseline level of microbiome variability even among isogenic organisms that are identically reared, housed, and fed. In germ-free flies fed known combinations of bacterial species, we find that some species colonize more frequently than others even when fed at the same high concentration. We develop an ecological technique that infers the presence of interactions between bacterial species based on their colonization odds in different contexts, requiring only presence/absence data from two-species experiments. We use a progressive sequence of probabilistic models, in which the colonization of each bacterial species is treated as an independent stochastic process, to reproduce the empirical distributions of colonization outcomes across experiments. We find that incorporating context-dependent interactions substantially improves the performance of the models. Stochastic, context-dependent microbiome assembly underlies clinical therapies like fecal microbiota transplantation and probiotic administration and should inform the design of synthetic fecal transplants and dosing regimes.

Coexistence in diverse communities with higher-order interactions.

A central assumption in most ecological models is that the interactions in a community operate only between pairs of species. However, two species may interactively affect the growth of a focal species. Although interactions among three or more species, called higher-order interactions, have the potential to modify our theoretical understanding of coexistence, ecologists lack clear expectations for how these interactions shape community structure. Here we analytically predict and numerically confirm how the variability and strength of higher-order interactions affect species coexistence. We found that as higher-order interaction strengths became more variable across species, fewer species could coexist, echoing the behavior of pairwise models. If interspecific higher-order interactions became too harmful relative to self-regulation, coexistence in diverse communities was destabilized, but coexistence was also lost when these interactions were too weak and mutualistic higher-order effects became prevalent. This behavior depended on the functional form of the interactions as the destabilizing effects of the mutualistic higher-order interactions were ameliorated when their strength saturated with species' densities. Last, we showed that more species-rich communities structured by higher-order interactions lose species more readily than their species-poor counterparts, generalizing classic results for community stability. Our work provides needed theoretical expectations for how higher-order interactions impact species coexistence in diverse communities.

Historical contingencies and phage induction diversify bacterioplankton communities at the microscale.

In many natural environments, microorganisms decompose microscale resource patches made of complex organic matter. The growth and collapse of populations on these resource patches unfold within spatial ranges of a few hundred micrometers or less, making such microscale ecosystems hotspots of heterotrophic metabolism. Despite the potential importance of patch-level dynamics for the large-scale functioning of heterotrophic microbial communities, we have not yet been able to delineate the ecological processes that control natural populations at the microscale. Here, we address this challenge by characterizing the natural marine communities that assembled on over 1,000 individual microscale particles of chitin, the most abundant marine polysaccharide. Using low-template shotgun metagenomics and imaging, we find significant variation in microscale community composition despite the similarity in initial species pools across replicates. Chitin-degrading taxa that were rare in seawater established large populations on a subset of particles, resulting in a wide range of predicted chitinolytic abilities and biomass at the level of individual particles. We show, through a mathematical model, that this variability can be attributed to stochastic colonization and historical contingencies affecting the tempo of growth on particles. We find evidence that one biological process leading to such noisy growth across particles is differential predation by temperate bacteriophages of chitin-degrading strains, the keystone members of the community. Thus, initial stochasticity in assembly states on individual particles, amplified through ecological interactions, may have significant consequences for the diversity and functionality of systems of microscale patches.

Higher-order effects, continuous species interactions, and trait evolution shape microbial spatial dynamics.

The assembly and maintenance of microbial diversity in natural communities, despite the abundance of toxin-based antagonistic interactions, presents major challenges for biological understanding. A common framework for investigating such antagonistic interactions involves cyclic dominance games with pairwise interactions. The incorporation of higher-order interactions in such models permits increased levels of microbial diversity, especially in communities in which antibiotic-producing, sensitive, and resistant strains coexist. However, most such models involve a small number of discrete species, assume a notion of pure cyclic dominance, and focus on low mutation rate regimes, none of which well represent the highly interlinked, quickly evolving, and continuous nature of microbial phenotypic space. Here, we present an alternative vision of spatial dynamics for microbial communities based on antagonistic interactions-one in which a large number of species interact in continuous phenotypic space, are capable of rapid mutation, and engage in both direct and higher-order interactions mediated by production of and resistance to antibiotics. Focusing on toxin production, vulnerability, and inhibition among species, we observe highly divergent patterns of diversity and spatial community dynamics. We find that species interaction constraints (rather than mobility) best predict spatiotemporal disturbance regimes, whereas community formation time, mobility, and mutation size best explain patterns of diversity. We also report an intriguing relationship among community formation time, spatial disturbance regimes, and diversity dynamics. This relationship, which suggests that both higher-order interactions and rapid evolution are critical for the origin and maintenance of microbial diversity, has broad-ranging links to the maintenance of diversity in other systems.

The generality of cryptic dietary niche differences in diverse large-herbivore assemblages.

Ecological niche differences are necessary for stable species coexistence but are often difficult to discern. Models of dietary niche differentiation in large mammalian herbivores invoke the quality, quantity, and spatiotemporal distribution of plant tissues and growth forms but are agnostic toward food plant species identity. Empirical support for these models is variable, suggesting that additional mechanisms of resource partitioning may be important in sustaining large-herbivore diversity in African savannas. We used DNA metabarcoding to conduct a taxonomically explicit analysis of large-herbivore diets across southeastern Africa, analyzing ∼4,000 fecal samples of 30 species from 10 sites in seven countries over 6 y. We detected 893 food plant taxa from 124 families, but just two families-grasses and legumes-accounted for the majority of herbivore diets. Nonetheless, herbivore species almost invariably partitioned food plant taxa; diet composition differed significantly in 97% of pairwise comparisons between sympatric species, and dissimilarity was pronounced even between the strictest grazers (grass eaters), strictest browsers (nongrass eaters), and closest relatives at each site. Niche differentiation was weakest in an ecosystem recovering from catastrophic defaunation, indicating that food plant partitioning is driven by species interactions, and was stronger at low rainfall, as expected if interspecific competition is a predominant driver. Diets differed more between browsers than grazers, which predictably shaped community organization: Grazer-dominated trophic networks had higher nestedness and lower modularity. That dietary differentiation is structured along taxonomic lines complements prior work on how herbivores partition plant parts and patches and suggests that common mechanisms govern herbivore coexistence and community assembly in savannas.

Decoupled responses of above- and below-ground beta-diversity to nitrogen enrichment in a typical steppe.

Increased atmospheric nitrogen (N) deposition affects biodiversity in terrestrial ecosystems. However, we do not know whether the effects of N on above-ground plant ß-diversity are coupled with changes occurring in the soil seed bank. We conducted a long-term N-addition experiment in a typical steppe and found that above-ground ß-diversity increased and then decreased with increasing N addition, whereas below-ground ß-diversity decreased linearly. This suggests decoupled dynamics of plant communities and their soil seed bank under N enrichment. Species substitution determined above- and below-ground ß-diversity change via an increasing role of deterministic processes with N addition. These effects were mostly driven by differential responses of the above-ground vegetation and the soil seed bank ß-diversities to N-induced changes in environmental heterogeneity, increased soil inorganic N concentrations and soil acidification. Our findings highlight the importance of considering above- and below-ground processes simultaneously for effectively conserving grassland ecosystems under N enrichment.

A phylogenomic perspective on interspecific competition.

Evolutionary processes may have substantial impacts on community assembly, but evidence for phylogenetic relatedness as a determinant of interspecific interaction strength remains mixed. In this perspective, we consider a possible role for discordance between gene trees and species trees in the interpretation of phylogenetic signal in studies of community ecology. Modern genomic data show that the evolutionary histories of many taxa are better described by a patchwork of histories that vary along the genome rather than a single species tree. If a subset of genomic loci harbour trait-related genetic variation, then the phylogeny at these loci may be more informative of interspecific trait differences than the genome background. We develop a simple method to detect loci harbouring phylogenetic signal and demonstrate its application through a proof-of-principle analysis of Penicillium genomes and pairwise interaction strength. Our results show that phylogenetic signal that may be masked genome-wide could be detectable using phylogenomic techniques and may provide a window into the genetic basis for interspecific interactions.

Trophic tug-of-war: Coexistence mechanisms within and across trophic levels.

Ecological communities encompass rich diversity across multiple trophic levels. While modern coexistence theory has been widely applied to understand community assembly, its traditional formalism only allows assembly within a single trophic level. Here, using an expanded definition of niche and fitness differences applicable to multitrophic communities, we study how diversity within and across trophic levels affects species coexistence. If each trophic level is analysed separately, both lower- and higher trophic levels are governed by the same coexistence mechanisms. In contrast, if the multitrophic community is analysed as a whole, different trophic levels are governed by different coexistence mechanisms: coexistence at lower trophic levels is predominantly limited by fitness differences, whereas coexistence at higher trophic levels is predominantly limited by niche differences. This dichotomy in coexistence mechanisms is supported by theoretical derivations, simulations of phenomenological and trait-based models, and a case study of a primeval forest ecosystem. Our work provides a general and testable prediction of coexistence mechanism operating in multitrophic communities.

Time-dependent interaction modification generated from plant-soil feedback.

Pairwise interactions between species can be modified by other community members, leading to emergent dynamics contingent on community composition. Despite the prevalence of such higher-order interactions, little is known about how they are linked to the timing and order of species' arrival. We generate population dynamics from a mechanistic plant-soil feedback model, then apply a general theoretical framework to show that the modification of a pairwise interaction by a third plant depends on its germination phenology. These time-dependent interaction modifications emerge from concurrent changes in plant and microbe populations and are strengthened by higher overlap between plants' associated microbiomes. The interaction between this overlap and the specificity of microbiomes further determines plant coexistence. Our framework is widely applicable to mechanisms in other systems from which similar time-dependent interaction modifications can emerge, highlighting the need to integrate temporal shifts of species interactions to predict the emergent dynamics of natural communities.

Temporal dynamics of Grime's CSR strategies in plant communities during 60 years of succession.

Grime's competitive, stress-tolerant, ruderal (CSR) theory predicts a shift in plant communities from ruderal to stress-tolerant strategies during secondary succession. However, this fundamental tenet lacks empirical validation using long-term continuous successional data. Utilizing a 60-year longitudinal data of old-field succession, we investigated the community-level dynamics of plant strategies over time. Our findings reveal that while plant communities generally transitioned from ruderal to stress-tolerant strategies during succession, initial abandonment conditions crucially shaped early successional strategies, leading to varied strategy trajectories across different fields. Furthermore, we found a notable divergence in the CSR strategies of alien and native species over succession. Initially, alien and native species exhibited similar ruderal strategies, but in later stages, alien species exhibited higher ruderal and lower stress tolerance compared to native species. Overall, our findings underscore the applicability of Grime's predictions regarding temporal shifts in CSR strategies depending on both initial community conditions and species origin.

Reciprocal inhibition and competitive hierarchy cause negative biodiversity-ecosystem function relationships.

The relationship between biodiversity and ecosystem function (BEF) captivates ecologists, but the factors responsible for the direction of this relationship remain unclear. While higher ecosystem functioning at higher biodiversity levels ('positive BEF') is not universal in nature, negative BEF relationships seem puzzlingly rare. Here, we develop a dynamical consumer-resource model inspired by microbial decomposer communities in pitcher plant leaves to investigate BEF. We manipulate microbial diversity via controlled colonization and measure their function as total ammonia production. We test how niche partitioning among bacteria and other ecological processes influence BEF in the leaves. We find that a negative BEF can emerge from reciprocal interspecific inhibition in ammonia production causing a negative complementarity effect, or from competitive hierarchies causing a negative selection effect. Absent these factors, a positive BEF was the typical outcome. Our findings provide a potential explanation for the rarity of negative BEF in empirical data.

Plant canopies promote climatic disequilibrium in Mediterranean recruit communities.

Current rates of climate change are exceeding the capacity of many plant species to track climate, thus leading communities to be in disequilibrium with climatic conditions. Plant canopies can contribute to this disequilibrium by buffering macro-climatic conditions and sheltering poorly adapted species to the oncoming climate, particularly in their recruitment stages. Here we analyse differences in climatic disequilibrium between understorey and open ground woody plant recruits in 28 localities, covering more than 100,000 m2 , across an elevation range embedding temperature and aridity gradients in the southern Iberian Peninsula. This study demonstrates higher climatic disequilibrium under canopies compared with open ground, supporting that plant canopies would affect future community climatic lags by allowing the recruitment of less arid-adapted species in warm and dry conditions, but also it endorse that canopies could favour warm-adapted species in extremely cold environments as mountain tops, thus pre-adapting communities living in these habitats to climate change.

The Geography of Metacommunities: Landscape Characteristics Drive Geographic Variation in the Assembly Process through Selecting Species Pool Attributes.

AbstractThe nonrandom association between landscape characteristics and the dominant life history strategies observed in species pools is a typical pattern in nature. Here, we argue that these associations determine predictable changes in the relative importance of assembly mechanisms along broadscale geographic gradients (i.e., the geographic context of metacommunity dynamics). To demonstrate that, we employed simulation models in which groups of species with the same initial distribution of niche breadths and dispersal abilities interacted across a wide range of landscapes with contrasting characteristics. By assessing the traits of dominant species in the species pool in each landscape type, we determined how different landscape characteristics select for different life history strategies at the metacommunity level. We analyzed the simulated data using the same analytical approaches used in the study of empirical metacommunities to derive predictions about the causal relationships between landscape characteristics and dominant life histories in species pools, as well as their reciprocal influence on empirical inferences regarding the assembly process. We provide empirical support for these predictions by contrasting the assembly of moth metacommunities in a tropical versus a temperate mountainous landscape. Together, our model framework and empirical analyses demonstrate how the geographic context of metacommunities influences our understanding of community assembly across broadscale ecological gradients.

Uncovering Broad Macroecological Patterns by Comparing the Shape of Species' Distributions along Environmental Gradients.

AbstractSpecies' distributions can take many different forms. For example, fat-tailed or skewed distributions are very common in nature, as these can naturally emerge as a result of individual variability and asymmetric environmental tolerances, respectively. Studying the basic shape of distributions can teach us a lot about the ways climatic processes and historical contingencies shape ecological communities. Yet we still lack a general understanding of how their shapes and properties compare to each other along gradients. Here, we use Bayesian nonlinear models to quantify range shape properties in empirical plant distributions. With this approach, we are able to distil the shape of plant distributions and compare them along gradients and across species. Studying the relationship between distribution properties, we revealed the existence of broad macroecological patterns along environmental gradients-such as those expected from Rapoport's rule and the abiotic stress limitation hypothesis. We also find that some aspects of the shape of observed ranges-such as kurtosis and skewness of the distributions-could be intrinsic properties of species or the result of their historical contexts. Overall, our modeling approach and results untangle the general shape of plant distributions and provide a mapping of how this changes along environmental gradients.