Getting more by asking for less: Linking species interactions to species co-distributions in metacommunities

Peer Community Journal, Journal Year: 2025, Volume and Issue: 5

Published: Jan. 2, 2025

One of the more difficult challenges in community ecology is inferring species interactions on basis patterns spatial distribution organisms. At its core, problem that distributional reflect 'realized niche', net result a complex interplay processes involving dispersal, environmental, and interaction effects. Disentangling these effects can be at least two distinct levels. From statistical point view, splitting population's variation into contributions from partners, abiotic environment proximity requires 'natural experiments' where all three factors somehow vary independently each other. On conceptual level, it not even clear how to meaningfully separate processes: for instance, could depend state biotic environment, may combine highly non-additive ways. Here we show latter issue arises almost inescapably, simple theoretical setting designed minimize it. Using model competitive metacommunity dynamics direct are assumed context-independent, accurately cross-species correlations major challenge under but most restrictive assumptions. However, also find possible estimate moments (mean value variance) much robustly, if precise values cannot inferred. Consequently, argue study multi-species still informative approaches build distributions parameters predict macroscopic outcomes assembly.

Language: Английский

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Connecting microbial community assembly and function

Current Opinion in Microbiology, Journal Year: 2024, Volume and Issue: 80, P. 102512 - 102512

Published: July 16, 2024

Language: Английский

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Exact solution of dynamical mean-field theory for a linear system with annealed disorder

Journal of Statistical Mechanics Theory and Experiment, Journal Year: 2025, Volume and Issue: 2025(2), P. 023301 - 023301

Published: Feb. 3, 2025

Abstract We investigate a disordered multi-dimensional linear system in which the interaction parameters are colored noises, varying stochastically time with defined temporal correlations. refer to this type of disorder as ‘annealed’, contrast quenched couplings fixed over time. Using generating functional methods, we extend dynamical mean-field theory accommodate annealed and employ it find exact solution model limit large number degrees freedom. Our analysis yields analytical results for non-stationary autocorrelation, stationary variance, power spectral density, phase diagram model. Some unexpected features emerge upon changing correlation interactions. The variance critical generally found be non-monotonic functions also that re-entrant transition can take place when is varied.

Language: Английский

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Microbial populations hardly ever grow logistically and never sublinearly

Physical review. E, Journal Year: 2025, Volume and Issue: 111(4)

Published: April 4, 2025

Language: Английский

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Microbiomes Through the Looking Glass

Published: April 11, 2025

Bacterial communities are pivotal to maintaining ecological function and preserving the rich tapestry of biological diversity. The rapid development environmental sequencing technologies, such as metagenomics, has revolutionized our capacity probe However, despite these advances, a theoretical understanding connecting empirical data with ecosystem modelling, in particular framework disordered systems akin spin glasses, is still its infancy. Here, we present comprehensive using theories decode microbiome data, which offers insight into forces that shape macroecological states. By employing quenched generalized Lotka-Volterra model, analyze species abundance healthy diseased human gut microbiomes. Results reveal emergence two distinct patterns species-interaction networks, elucidating pathways through dysbiosis may drive instability. Interaction thus provide window systemic shifts accompanying transition from health disease, offering new perspective on dynamics microbial community. Our findings suggest potential theory characterize microbiomes by capturing essence interactions their consequences stability functioning, leveraging linkages dynamics.

Language: Английский

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Microbiomes Through the Looking Glass

Published: April 11, 2025

Bacterial communities are pivotal to maintaining ecological function and preserving the rich tapestry of biological diversity. The rapid development environmental sequencing technologies, such as metagenomics, has revolutionized our capacity probe However, despite these advances, a theoretical understanding connecting empirical data with ecosystem modelling, in particular framework disordered systems akin spin glasses, is still its infancy. Here, we present comprehensive using theories decode microbiome data, which offers insight into forces that shape macroecological states. By employing quenched generalized Lotka-Volterra model, analyze species abundance healthy diseased human gut microbiomes. Results reveal emergence two distinct patterns species-interaction networks, elucidating pathways through dysbiosis may drive instability. Interaction thus provide window systemic shifts accompanying transition from health disease, offering new perspective on dynamics microbial community. Our findings suggest potential theory characterize microbiomes by capturing essence interactions their consequences stability functioning, leveraging linkages dynamics.

Language: Английский

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Macroecological patterns in experimental microbial communities

PLoS Computational Biology, Journal Year: 2025, Volume and Issue: 21(5), P. e1013044 - e1013044

Published: May 8, 2025

Ecology has historically benefited from the characterization of statistical patterns biodiversity within and across communities, an approach known as macroecology. Within microbial ecology, macroecological approaches have identified universal diversity abundance that can be captured by effective models. Experimentation simultaneously played a crucial role, advent high-replication community time-series allowed researchers to investigate underlying ecological forces. However, there remains gap between experiments performed in laboratory documented natural systems, we do not know whether these recapitulated lab experimental manipulations produce effects. This work aims at bridging ecology Using time-series, demonstrate observed nature exist setting, despite controlled conditions, unified under Stochastic Logistic Model growth (SLM). We found demographic (e.g., migration) impact patterns. By modifying SLM incorporate said alongside details sampling), obtain predictions are consistent with outcomes. combining models, macroecology viewed predictive discipline.

Language: Английский

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A macroecological perspective on genetic diversity in the human gut microbiome

PLoS ONE, Journal Year: 2023, Volume and Issue: 18(7), P. e0288926 - e0288926

Published: July 21, 2023

While the human gut microbiome has been intensely studied, we have yet to obtain a sufficient understanding of genetic diversity that it harbors. Research efforts demonstrated considerable fraction within-host variation in is driven by ecological dynamics co-occurring strains belonging same species, suggesting an lens may provide insight into empirical patterns diversity. Indeed, model self-limiting growth and environmental noise known as Stochastic Logistic Model (SLM) was recently shown successfully predict temporal within single host. However, its ability across hosts be tested. In this manuscript I determine whether predictions SLM explain unrelated for 22 common microbial species. Specifically, stationary distribution explains allele frequencies predicts harboring given (i.e., prevalence) sites. The accuracy correlated with independent estimates strain structure, follow statistically similar forms due existence strain-level ecology.

Language: Английский

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Statistical mechanics of phenotypic eco-evolution: From adaptive dynamics to complex diversification

Physical Review Research, Journal Year: 2024, Volume and Issue: 6(2)

Published: April 19, 2024

The ecological and evolutionary dynamics of large populations can be addressed theoretically using concepts methodologies from statistical mechanics. This approach has been extensively discussed in the literature, both within realm population genetics, which focuses on genes or “genotypes,” adaptive dynamics, emphasizes traits “phenotypes.” Following this tradition, here we construct a theoretical framework allowing us to derive “macroscopic” equations general “microscopic” stochastic representing fundamental processes reproduction, mutation, selection community individuals, each one characterized by its phenotypic features. Importantly, our setup, timescales are intertwined, makes it particularly suitable describe microbial communities, timely topic utmost relevance. leads probabilistic description—even case arbitrarily populations—of distribution individuals space as encoded what call “generalized Crow-Kimura equation” replicator-mutator equation.” We discuss limits such an equation reduces (deterministic) theory “adaptive dynamics,” i.e., standard space. Moreover, emphasize aspects that beyond reach dynamics. In particular, developing simple model growing competing illustrative example, demonstrate resulting probability undergo “dynamical phase transitions.” These transitions may involve shifts unimodal bimodal distribution, generated branching event, multimodal through cascade events. Furthermore, formalism allows rationalize these cascades parsimonious Landau's transitions. Finally, extend account for finite illustrate possible consequences “demographic” effects. Altogether, present extends and/or complements existing approaches paves way more systematic studies communities well future developments including analyses process perspective nonequilibrium Published American Physical Society 2024

Language: Английский

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Exploring spatial segregation induced by competition avoidance as driving mechanism for emergent coexistence in microbial communities

Physical review. E, Journal Year: 2024, Volume and Issue: 110(1)

Published: July 8, 2024

This study investigates the role of spatial segregation, prompted by competition avoidance, as a key mechanism for emergent coexistence within microbial communities. Recognizing these communities complex adaptive systems, we challenge sufficiency mean-field pairwise interaction models, and consider impact dynamics. We developed an individual-based simulation depicting bacterial movement through pattern random walks influenced leading to formation spatially segregated clusters. model was integrated with Lotka-Volterra metapopulation framework focused on competitive interactions. Our findings reveal that segregation combined low diffusion rates high compositional heterogeneity among patches can lead in reveals novel underpinning stable, coexisting microbe clusters, which is nonetheless incapable promoting case isolated pairs species. underscores importance considering factors understanding dynamics ecosystems.

Language: Английский

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