Biology subjects

O'Dwyer, J. P.

Publications and source records attributed to O'Dwyer, J. P..

11 recordsLinked to original sources

bioRxiv2026

A minimal model of a forest after neutral theory

Community ecology seeks the mechanisms underlying biodiversity, and simplified models can reveal them. Neutral ecology exemplifies this approach, but it doesn't distinguish species, limiting its capability for forecasting and prediction. We address this by developing a predictive, minimal model for forest dynamics. We show in a neotropical forest plot that environmental variation couples to the community as a single common effect on all species' growth rates. Life history acts on that variation, forecasting species' gains and losses a decade ahead. Finally, immigration, coupled to competition and life history, allows us to predict long-run species abundances. Simple rules thus govern the dynamics of this forest: competition, immigration, and the effect of the environment on growth. Beyond that, species are set apart by their life histories alone.

ecology↗

bioRxiv2024

On the structure of multiple stable equilibria in competitive ecological systems

For some ecological systems with a large pool of possible species, there can be multiple stable equilibria with different species composition. Natural or anthropogenic disruption can induce a shift between different such equilibria. While some work has been done on ecological systems with multiple equilibria, there is no general theory governing the distribution of equilibria or characterizing the basins of attraction of different equilibria. This article addresses these questions in a simple class of Lotka-Volterra models. We focus on competitive systems of species on a niche axis with multiple equilibria. We find that basins of attraction are generally larger for equilibria with greater biomass; in many cases, the basin of attraction size scales roughly exponentially with the net biomass of equilibria. This is illustrated in two ecologically relevant limits. In a continuous limit with species spaced arbitrarily closely on the niche axis, equilibria with different numbers of species provide new perspective on the notion of limiting similarity. In another limit, akin to a statistical mechanical model, the niche axis becomes infinite while the range of interactions remains fixed; in this limit we prove the exponential relation between basin size and biomass using the Markov chain central limit theorem.

ecology↗

bioRxiv2023

Metabolic trade-offs can reverse the resource-diversityrelationship

For species that partition resources, the classic expectation is that increasing resource diversity allows for increased species diversity. On the other hand, for neutral species, such as those competing equally for a single resource, diversity reflects a balance between the rate of introduction of novelty (for example by immigration or speciation) and the rate of extinction. Recent models of microbial metabolism have identified scenarios where metabolic trade-offs among species partitioning multiple resources can produce emergent neutral-like dynamics. In this hybrid scenario, one might expect that both resource diversity and immigration will act to boost species diversity. We show, however, that the reverse may be true: when metabolic trade-offs hold and population sizes are sufficiently large, increasing resource diversity can act to reduce species diversity, sometimes drastically. This reversal is explained by a generic transition between neutral- and niche-like dynamics, driven by the diversity of resources. The inverted resource-diversity relationship that results may be a signature of consumer-resource systems with strong metabolic trade-offs.

ecology↗

bioRxiv2023

Sparsity of higher-order interactions enables learning and prediction for microbiomes

Microbiome engineering offers the potential to lever-age microbial communities to improve outcomes in human health, agriculture, and climate. To translate this potential into reality, it is crucial to reliably predict community composition and function. But a brute force approach to cataloguing community function is hindered by the combinatorial explosion in the number of ways we can combine microbial species. An alternative is to parameterize microbial community outcomes using simplified, mechanistic models, and then extrapolate these models beyond where we have sampled. But these approaches remain data-hungry, as well as requiring an a priori specification of what kinds of mechanism are included and which are omitted. Here, we resolve both issues by introducing a new, mechanism-agnostic approach to predicting microbial community compositions and functions using limited data. The critical step is the discovery of a sparse representation of the community landscape. We then leverage this sparsity to predict community compositions and functions, drawing from techniques in compressive sensing. We validate this approach on in silico community data, generated from a theoretical model. By sampling just [~] 1% of all possible communities, we accurately predict community compositions out of sample. We then demonstrate the real-world application of our approach by applying it to four experimental datasets, and showing that we can recover interpretable, accurate predictions on composition and community function from highly limited data.

ecology↗

bioRxiv2022

Universal abundance fluctuations across microbial communities, tropical forests, and urban populations

The growth of complex populations, such as microbial communities, forests, and cities, occurs over vastly different spatial and temporal scales. Although research in different fields has developed detailed, system-specific models to understand each individual system, a unified analysis of different complex populations is lacking; such an analysis could deepen our understanding of each system and facilitate cross-pollination of tools and insights across fields. Here, for the first time we use a shared framework to analyze time-series data of the human gut microbiome, tropical forest, and urban employment. We demonstrate that a single, three-parameter model of stochastic population dynamics can reproduce the empirical distributions of population abundances and fluctuations in all three data sets. The three parameters characterizing a species measure its mean abundance, deterministic stability, and stochasticity. Our analysis reveals that, despite the vast differences in scale, all three systems occupy a similar region of parameter space when time is measured in generations. In other words, although the fluctuations observed in these systems may appear different, this difference is primarily due to the different physical timescales associated with each system. Further, we show that the distribution of temporal abundance fluctuations is described by just two parameters and derive a two-parameter functional form for abundance fluctuations to improve risk estimation and forecasting.

ecology↗

bioRxiv2021

Stability criteria for the consumption and exchange of essential resources

Models of pairwise interactions have informed our understanding of when ecological communities will have stable equilibria. However, these models do not explicitly include the effect of the resource environment, which has the potential to refine or modify our understanding of when a group of interacting species will coexist. Recent consumer-resource models incorporating the exchange of resources alongside competition exemplify this: such models can lead to either stable or unstable equilibria, depending on the resource supply. On the other hand, 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 Liebigs law, where species require and deplete multiple resources, but each consumers growth rate is only limited by a single one of these multiple resources. Consumed resources that do not lead to growth are leaked back into the environment, 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, once 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 we derive analytically apply to a broader class of network structures and resource inflow profiles, including cases in which 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 ecological mechanism is modeled directly. Author summaryOne of the longstanding challenges in community ecology is to understand how diverse ecosystems assemble and stably persist. Microbial communities are a particularly acute example of this open problem, because thousands of different bacterial species can coexist in the same environment. Interactions between bacteria are of central importance across a wide variety of systems, from the dynamics of the human gut microbiome to the functioning of industrial bioreactors. As a result, a predictive understanding of which microbes can coexist together, and how they do it, will have far-reaching applications. In this paper, we incorporate a more realistic understanding of microbial metabolism into classic mathematical models of consumer-resource dynamics. In our model, bacteria deplete multiple abiotic nutrients but only grow on one of these resources. In addition, they recycle some of the nutrients they consume back into the environment as new resources. We analytically derive criteria which, if satisfied, guarantee that any number of microbes will coexist. We find that there are special types of interaction networks which remain stable even when resources are scarce. Our theory can be used in conjunction with experimentally determined interaction networks to predict which species assemblages are likely to stably coexist in a specified resource environment.

ecology↗

bioRxiv2019

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. Author SummaryThe 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.

ecology↗

bioRxiv2019

Species dynamics and interactions via metabolically informed consumer-resource models

Quantifying the strength, sign, and origin of species interactions, along with their dependence on environmental context, is at the heart of prediction and understanding in ecological communities. Pairwise interaction models like Lotka-Volterra provide an important and flexible foundation, but notably absent is an explicit mechanism mediating interactions. Consumer-resource models incorporate mechanism, but describing competitive and mutualistic interactions is more ambiguous. Here, we bridge this gap by modeling a coarse-grained version of a species true, cellular metabolism to describe resource consumption via uptake and conversion into biomass, energy, and byproducts. This approach does not require detailed chemical reaction information, but it provides a more explicit description of underlying mechanisms than pairwise interaction or consumer-resource models. Using a model system, we find that when metabolic reactions require two distinct resources we recover Liebigs Law and multiplicative co-limitation in particular limits of the intracellular reaction rates. In between these limits, we derive a more general phenomenological form for consumer growth rate, and we find corresponding rates of secondary metabolite production, allowing us to model competitive and non-competitive interactions (e.g., facilitation). Using the more general form, we show how secondary metabolite production can support coexistence even when two species compete for a shared resource, and we show how differences in metabolic rates change species abundances in equilibrium. Building on these findings, we make the case for incorporating coarse-grained metabolism to update the phenomenology we use to model species interactions.

ecology↗

bioRxiv2019

Cooperation and Stability for Complex Systems in Resource Limited Environments

Resource-limited complex systems are ubiquitous in the natural world, as is the potential for instability in such systems. Classic models of interacting species have provided a basis for our understanding of stability in these systems, and suggest that stable coexistence requires weak, rare, and asymmetric interactions. But missing from these models is an explicit understanding of how resource exchange and resource limitation can drive or prevent instability. Here we show that systems based on general rules for the consumption and exchange of resources are guaranteed to be stable when exchange of resources is reciprocated by each pair of partners. These cooperative, mutualistic interactions can be arbitrarily strong and yet not disrupt stability. More general modes of exchange will lead to instability when supply rates are low, but when resource supply from outside the system is sufficiently high, arbitrary exchange is consistent with a stable equilibrium.

ecology↗

bioRxiv2017

Ecological Insights from the Evolutionary History of Microbial Innovations

Bacteria and Archaea represent the base of the evolutionary tree of life and contain the vast majority of phylogenetic and functional diversity. Because these organisms and their traits directly impact ecosystems and human health, a focus on functional traits has become increasingly common in microbial ecology. These trait-based approaches have the potential to link microbial communities and their ecological function. But an open question is how, why, and in what order microorganisms acquired the traits we observe in the present day. To address this, we reconstructed the evolutionary history of microbial traits using genomic data to understand the evolution, selective advantage, and similarity of traits in extant organisms and provide insights into the composition of genomes and communities. We used the geological timeline and physiological expectations to provide independent evidence in support of this evolutionary history. Using this reconstructed evolutionary history, we explored hypotheses related to the composition of genomes. We showed that gene transition rates can be used to make predictions about the size and type of genes in a genome: generalist genomes comprise many evolutionarily labile genes while specialist genomes comprise more highly conserved functional genes. These findings suggest that generalist organisms do not build up and hoard an array of functions, but rather tend to experiment with functions related to environmental sensing, transport, and complex resource degradation. Our results provide a framework for understanding the evolutionary history of extant microorganisms, the origin and maintenanceof traits, and linking evolutionary relatedness and ecological function.

microbiology↗

bioRxiv2017

Ecophylogenetics Reveals the Evolutionary Associations between Mammals and their Gut Microbiota

A tantalizing hypothesis posits that mammals coevolved with their gut microbiota. Unfortunately, the limited resolution of microbial taxonomy hinders the exploration of this hypothesis and specifically challenges the discovery of gut microbes that are linked to mammalian evolution. To address this, we developed a novel approach that groups microbes into new, more meaningful taxonomic units based on their common ancestry and ecological redundancy. Treating mammalian lineages as different ecosystems, we quantified the distribution of these microbial taxa across mammals. Our analysis discovered monophyletic clades of gut bacteria that are unexpectedly prevalent, or conserved, across all mammals, as well as conserved clades that are exclusive to particular mammalian lineages. These clades often manifest phylogenetic patterns indicating that they are subject to selection. Lineage - specific changes in clade conservation, including a human-accelerated loss of conserved clades, suggest that mammalian evolution associates with a change in the selective regimes that act on gut microbiota. Collectively, these results point to the existence of microbes that possess traits that facilitate their dispersion or survival in the mammalian gut, possibly because they are subject to host selection. Ultimately, our analysis clarifies the relationship between the diversification of the gut microbiome and mammalian evolutionary history.

microbiology↗