1
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Deng J, Cordero OX, Fukami T, Levin SA, Pringle RM, Solé R, Saavedra S. The development of ecological systems along paths of least resistance. Curr Biol 2024:S0960-9822(24)01165-5. [PMID: 39332401 DOI: 10.1016/j.cub.2024.08.050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 07/25/2024] [Accepted: 08/28/2024] [Indexed: 09/29/2024]
Abstract
A long-standing question in biology is whether there are common principles that characterize the development of ecological systems (the appearance of a group of taxa), regardless of organismal diversity and environmental context.1,2,3,4,5,6,7,8,9,10,11 Classic ecological theory holds that these systems develop following a sequenced, orderly process that generally proceeds from fast-growing to slow-growing taxa and depends on life-history trade-offs.2,12,13 However, it is also possible that this developmental order is simply the path with the least environmental resistance for survival of the component species and hence favored by probability alone. Here, we use theory and data to show that the order from fast- to slow-growing taxa is the most likely developmental path for diverse systems when local taxon interactions self-organize in light of environmental resistance. First, we demonstrate theoretically that a sequenced development is more likely than a simultaneous one, at least until the number of iterations becomes so large as to be ecologically implausible. We then show that greater diversity of taxa and life histories improves the likelihood of a sequenced order from fast- to slow-growing taxa. Using data from bacterial and metazoan systems,14,15,16,17,18,19 we present empirical evidence that the developmental order of ecological systems moves along the paths of least environmental resistance. The capacity of simple principles to explain the trend in the developmental order of diverse ecological systems paves the way to an enhanced understanding of collective features of life.
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Affiliation(s)
- Jie Deng
- Department of Civil and Environmental Engineering, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
| | - Otto X Cordero
- Department of Civil and Environmental Engineering, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Tadashi Fukami
- Departments of Biology and Earth System Science, Stanford University, 371 Jane Stanford Way, Stanford, CA 94305, USA
| | - Simon A Levin
- Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Robert M Pringle
- Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA.
| | - Ricard Solé
- Complex Systems Laboratory, Universitat Pompeu Fabra, Dr. Aiguader 88, 08003 Barcelona, Spain; Institució Catalana de Recerca i Estudis Avançats, Lluís Companys 23, 08010 Barcelona, Spain; Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA
| | - Serguei Saavedra
- Department of Civil and Environmental Engineering, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139, USA; Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA.
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2
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Aguadé-Gorgorió G, Anderson ARA, Solé R. Modeling tumors as complex ecosystems. iScience 2024; 27:110699. [PMID: 39280631 PMCID: PMC11402243 DOI: 10.1016/j.isci.2024.110699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/18/2024] Open
Abstract
Many cancers resist therapeutic intervention. This is fundamentally related to intratumor heterogeneity: multiple cell populations, each with different phenotypic signatures, coexist within a tumor and its metastases. Like species in an ecosystem, cancer populations are intertwined in a complex network of ecological interactions. Most mathematical models of tumor ecology, however, cannot account for such phenotypic diversity or predict its consequences. Here, we propose that the generalized Lotka-Volterra model (GLV), a standard tool to describe species-rich ecological communities, provides a suitable framework to model the ecology of heterogeneous tumors. We develop a GLV model of tumor growth and discuss how its emerging properties provide a new understanding of the disease. We discuss potential extensions of the model and their application to phenotypic plasticity, cancer-immune interactions, and metastatic growth. Our work outlines a set of questions and a road map for further research in cancer ecology.
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Affiliation(s)
| | - Alexander R A Anderson
- Integrated Mathematical Oncology Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA
| | - Ricard Solé
- ICREA-Complex Systems Lab, UPF-PRBB, Dr. Aiguader 80, 08003 Barcelona, Spain
- Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA
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3
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Dopson M, Emary C. The persistence of bipartite ecological communities with Lotka-Volterra dynamics. J Math Biol 2024; 89:24. [PMID: 38955850 PMCID: PMC11219392 DOI: 10.1007/s00285-024-02120-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 06/05/2024] [Accepted: 06/13/2024] [Indexed: 07/04/2024]
Abstract
The assembly and persistence of ecological communities can be understood as the result of the interaction and migration of species. Here we study a single community subject to migration from a species pool in which inter-specific interactions are organised according to a bipartite network. Considering the dynamics of species abundances to be governed by generalised Lotka-Volterra equations, we extend work on unipartite networks to we derive exact results for the phase diagram of this model. Focusing on antagonistic interactions, we describe factors that influence the persistence of the two guilds, locate transitions to multiple-attractor and unbounded phases, as well as identifying a region of parameter space in which consumers are essentially absent in the local community.
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Affiliation(s)
- Matt Dopson
- School of Mathematics, Statistics and Physics, Newcastle University, Newcastle-upon-Tyne, NE1 7RU, UK.
| | - Clive Emary
- School of Mathematics, Statistics and Physics, Newcastle University, Newcastle-upon-Tyne, NE1 7RU, UK
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4
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Lampo A, Palazzi MJ, Borge-Holthoefer J, Solé-Ribalta A. Structural dynamics of plant-pollinator mutualistic networks. PNAS NEXUS 2024; 3:pgae209. [PMID: 38881844 PMCID: PMC11177885 DOI: 10.1093/pnasnexus/pgae209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 05/21/2024] [Indexed: 06/18/2024]
Abstract
The discourse surrounding the structural organization of mutualistic interactions mostly revolves around modularity and nestedness. The former is known to enhance the stability of communities, while the latter is related to their feasibility, albeit compromising the stability. However, it has recently been shown that the joint emergence of these structures poses challenges that can eventually lead to limitations in the dynamic properties of mutualistic communities. We hypothesize that considering compound arrangements-modules with internal nested organization-can offer valuable insights in this debate. We analyze the temporal structural dynamics of 20 plant-pollinator interaction networks and observe large structural variability throughout the year. Compound structures are particularly prevalent during the peak of the pollination season, often coexisting with nested and modular arrangements in varying degrees. Motivated by these empirical findings, we synthetically investigate the dynamics of the structural patterns across two control parameters-community size and connectance levels-mimicking the progression of the pollination season. Our analysis reveals contrasting impacts on the stability and feasibility of these mutualistic communities. We characterize the consistent relationship between network structure and stability, which follows a monotonic pattern. But, in terms of feasibility, we observe nonlinear relationships. Compound structures exhibit a favorable balance between stability and feasibility, particularly in mid-sized ecological communities, suggesting they may effectively navigate the simultaneous requirements of stability and feasibility. These findings may indicate that the assembly process of mutualistic communities is driven by a delicate balance among multiple properties, rather than the dominance of a single one.
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Affiliation(s)
- Aniello Lampo
- Grupo Interdisciplinar de Sistemas Complejos (GISC), Departamento de Matemáticas, Universidad Carlos III de Madrid, Av. Universidad, 30 (edificio Sabatini), 28911 Leganés (Madrid), Spain
| | - María J Palazzi
- Internet Interdisciplinary Institute (IN3), Universitat Oberta de Catalunya, Rambla del Poblenou, 154 08018, Barcelona, Catalonia, Spain
| | - Javier Borge-Holthoefer
- Internet Interdisciplinary Institute (IN3), Universitat Oberta de Catalunya, Rambla del Poblenou, 154 08018, Barcelona, Catalonia, Spain
| | - Albert Solé-Ribalta
- Internet Interdisciplinary Institute (IN3), Universitat Oberta de Catalunya, Rambla del Poblenou, 154 08018, Barcelona, Catalonia, Spain
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5
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Samadder A, Chattopadhyay A, Sau A, Bhattacharya S. Interconnection between density-regulation and stability in competitive ecological network. Theor Popul Biol 2024; 157:33-46. [PMID: 38521098 DOI: 10.1016/j.tpb.2024.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 02/25/2024] [Accepted: 03/19/2024] [Indexed: 03/25/2024]
Abstract
In natural ecosystems, species can be characterized by the nonlinear density-dependent self-regulation of their growth profile. Species of many taxa show a substantial density-dependent reduction for low population size. Nevertheless, many show the opposite trend; density regulation is minimal for small populations and increases significantly when the population size is near the carrying capacity. The theta-logistic growth equation can portray the intraspecific density regulation in the growth profile, theta being the density regulation parameter. In this study, we examine the role of these different growth profiles on the stability of a competitive ecological community with the help of a mathematical model of competitive species interactions. This manuscript deals with the random matrix theory to understand the stability of the classical theta-logistic models of competitive interactions. Our results suggest that having more species with strong density dependence, which self-regulate at low densities, leads to more stable communities. With this, stability also depends on the complexity of the ecological network. Species network connectance (link density) shows a consistent trend of increasing stability, whereas community size (species richness) shows a context-dependent effect. We also interpret our results from the aspect of two different life history strategies: r and K-selection. Our results show that the stability of a competitive network increases with the fraction of r-selected species in the community. Our result is robust, irrespective of different network architectures.
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Affiliation(s)
- Amit Samadder
- Agricultural and Ecological Research Unit, Indian Statistical Institute, 203, B.T Road, Kolkata 700108, India.
| | - Arnab Chattopadhyay
- Agricultural and Ecological Research Unit, Indian Statistical Institute, 203, B.T Road, Kolkata 700108, India.
| | - Anurag Sau
- Agricultural and Ecological Research Unit, Indian Statistical Institute, 203, B.T Road, Kolkata 700108, India; Odum School of Ecology, Center for the Ecology of Infectious Diseases, University of Georgia, Athens, Georgia USA.
| | - Sabyasachi Bhattacharya
- Agricultural and Ecological Research Unit, Indian Statistical Institute, 203, B.T Road, Kolkata 700108, India.
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6
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Bloxham B, Lee H, Gore J. Biodiversity is enhanced by sequential resource utilization and environmental fluctuations via emergent temporal niches. PLoS Comput Biol 2024; 20:e1012049. [PMID: 38739654 PMCID: PMC11135710 DOI: 10.1371/journal.pcbi.1012049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 05/29/2024] [Accepted: 04/02/2024] [Indexed: 05/16/2024] Open
Abstract
How natural communities maintain their remarkable biodiversity and which species survive in complex communities are central questions in ecology. Resource competition models successfully explain many phenomena but typically predict only as many species as resources can coexist. Here, we demonstrate that sequential resource utilization, or diauxie, with periodic growth cycles can support many more species than resources. We explore how communities modify their own environments by sequentially depleting resources to form sequences of temporal niches, or intermediately depleted environments. Biodiversity is enhanced when community-driven or environmental fluctuations modulate the resource depletion order and produce different temporal niches on each growth cycle. Community-driven fluctuations under constant environmental conditions are rare, but exploring them illuminates the temporal niche structure that emerges from sequential resource utilization. With environmental fluctuations, we find most communities have more stably coexisting species than resources with survivors accurately predicted by the same temporal niche structure and each following a distinct optimal strategy. Our results thus present a new niche-based approach to understanding highly diverse fluctuating communities.
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Affiliation(s)
- Blox Bloxham
- Physics of Living Systems, Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Hyunseok Lee
- Physics of Living Systems, Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Jeff Gore
- Physics of Living Systems, Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
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7
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Aguadé-Gorgorió G, Anderson AR, Solé R. Modeling tumors as species-rich ecological communities. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.22.590504. [PMID: 38712062 PMCID: PMC11071393 DOI: 10.1101/2024.04.22.590504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Many advanced cancers resist therapeutic intervention. This process is fundamentally related to intra-tumor heterogeneity: multiple cell populations, each with different mutational and phenotypic signatures, coexist within a tumor and its metastatic nodes. Like species in an ecosystem, many cancer cell populations are intertwined in a complex network of ecological interactions. Most mathematical models of tumor ecology, however, cannot account for such phenotypic diversity nor are able to predict its consequences. Here we propose that the Generalized Lotka-Volterra model (GLV), a standard tool to describe complex, species-rich ecological communities, provides a suitable framework to describe the ecology of heterogeneous tumors. We develop a GLV model of tumor growth and discuss how its emerging properties, such as outgrowth and multistability, provide a new understanding of the disease. Additionally, we discuss potential extensions of the model and their application to three active areas of cancer research, namely phenotypic plasticity, the cancer-immune interplay and the resistance of metastatic tumors to treatment. Our work outlines a set of questions and a tentative road map for further research in cancer ecology.
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Affiliation(s)
| | - Alexander R.A. Anderson
- Integrated Mathematical Oncology Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, USA
| | - Ricard Solé
- ICREA-Complex Systems Lab, UPF-PRBB, Dr. Aiguader 80, 08003 Barcelona, Spain
- Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA
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8
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Song C, Spaak JW. Trophic tug-of-war: Coexistence mechanisms within and across trophic levels. Ecol Lett 2024; 27:e14409. [PMID: 38590122 DOI: 10.1111/ele.14409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 02/26/2024] [Accepted: 03/06/2024] [Indexed: 04/10/2024]
Abstract
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.
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Affiliation(s)
- Chuliang Song
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, USA
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, USA
| | - Jurg W Spaak
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, New York, USA
- Institute for Environmental Sciences, RPTU Kaiserslautern-Landau, Landau, Germany
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9
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Hatton IA, Mazzarisi O, Altieri A, Smerlak M. Diversity begets stability: Sublinear growth and competitive coexistence across ecosystems. Science 2024; 383:eadg8488. [PMID: 38484074 DOI: 10.1126/science.adg8488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 02/07/2024] [Indexed: 03/19/2024]
Abstract
The worldwide loss of species diversity brings urgency to understanding how diverse ecosystems maintain stability. Whereas early ecological ideas and classic observations suggested that stability increases with diversity, ecological theory makes the opposite prediction, leading to the long-standing "diversity-stability debate." Here, we show that this puzzle can be resolved if growth scales as a sublinear power law with biomass (exponent <1), exhibiting a form of population self-regulation analogous to models of individual ontogeny. We show that competitive interactions among populations with sublinear growth do not lead to exclusion, as occurs with logistic growth, but instead promote stability at higher diversity. Our model realigns theory with classic observations and predicts large-scale macroecological patterns. However, it makes an unsettling prediction: Biodiversity loss may accelerate the destabilization of ecosystems.
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Affiliation(s)
- Ian A Hatton
- Max Planck Institute for Mathematics in the Sciences, 04103 Leipzig, Germany
- Department of Earth and Planetary Sciences, McGill University, Montreal, QC H3A 0E8, Canada
| | - Onofrio Mazzarisi
- Max Planck Institute for Mathematics in the Sciences, 04103 Leipzig, Germany
- Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS 66045, USA
- The Abdus Salam International Centre for Theoretical Physics (ICTP), 34014 Trieste, Italy
- National Institute of Oceanography and Applied Geophysics (OGS), 34014 Trieste, Italy
| | - Ada Altieri
- Laboratoire Matière et Systèmes Complexes (MSC), Université Paris Cité CNRS, 75013 Paris, France
| | - Matteo Smerlak
- Max Planck Institute for Mathematics in the Sciences, 04103 Leipzig, Germany
- Laboratoire de Biophysique et Evolution, UMR 8231 CBI, ESPCI Paris, PSL Research University, 75005 Paris, France
- Capital Fund Management, 75007 Paris, France
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10
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Vollert SA, Drovandi C, Adams MP. Unlocking ensemble ecosystem modelling for large and complex networks. PLoS Comput Biol 2024; 20:e1011976. [PMID: 38483981 DOI: 10.1371/journal.pcbi.1011976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 03/26/2024] [Accepted: 03/07/2024] [Indexed: 03/27/2024] Open
Abstract
The potential effects of conservation actions on threatened species can be predicted using ensemble ecosystem models by forecasting populations with and without intervention. These model ensembles commonly assume stable coexistence of species in the absence of available data. However, existing ensemble-generation methods become computationally inefficient as the size of the ecosystem network increases, preventing larger networks from being studied. We present a novel sequential Monte Carlo sampling approach for ensemble generation that is orders of magnitude faster than existing approaches. We demonstrate that the methods produce equivalent parameter inferences, model predictions, and tightly constrained parameter combinations using a novel sensitivity analysis method. For one case study, we demonstrate a speed-up from 108 days to 6 hours, while maintaining equivalent ensembles. Additionally, we demonstrate how to identify the parameter combinations that strongly drive feasibility and stability, drawing ecological insight from the ensembles. Now, for the first time, larger and more realistic networks can be practically simulated and analysed.
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Affiliation(s)
- Sarah A Vollert
- Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Christopher Drovandi
- Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Matthew P Adams
- Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Chemical Engineering, The University of Queensland, St Lucia, Australia
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11
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Miller ZR, Clenet M, Della Libera K, Massol F, Allesina S. Coexistence of many species under a random competition-colonization trade-off. Proc Natl Acad Sci U S A 2024; 121:e2314215121. [PMID: 38261621 PMCID: PMC10835059 DOI: 10.1073/pnas.2314215121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 12/14/2023] [Indexed: 01/25/2024] Open
Abstract
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.
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Affiliation(s)
- Zachary R. Miller
- Department of Ecology & Evolution, University of Chicago, Chicago, IL60637
- Department of Plant Biology, University of Illinois, Urbana, IL, 61801
| | - Maxime Clenet
- Laboratoire d’Informatique Gaspard-Monge, UMR 8049, CNRS, Université Gustave Eiffel, Marne-la-Vallée77454, France
| | - Katja Della Libera
- Department of Ecology & Evolution, University of Chicago, Chicago, IL60637
| | - François Massol
- Université Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019–UMR 9017–Center for Infection and Immunity of Lille, LilleF-59000, France
| | - Stefano Allesina
- Department of Ecology & Evolution, University of Chicago, Chicago, IL60637
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12
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Zhu S, Hong J, Wang T. Horizontal gene transfer is predicted to overcome the diversity limit of competing microbial species. Nat Commun 2024; 15:800. [PMID: 38280843 PMCID: PMC10821886 DOI: 10.1038/s41467-024-45154-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Accepted: 01/17/2024] [Indexed: 01/29/2024] Open
Abstract
Natural microbial ecosystems harbor substantial diversity of competing species. Explaining such diversity is challenging, because in classic theories it is extremely infeasible for a large community of competing species to stably coexist in homogeneous environments. One important aspect mostly overlooked in these theories, however, is that microbes commonly share genetic materials with their neighbors through horizontal gene transfer (HGT), which enables the dynamic change of species growth rates due to the fitness effects of the mobile genetic elements (MGEs). Here, we establish a framework of species competition by accounting for the dynamic gene flow among competing microbes. Combining theoretical derivation and numerical simulations, we show that in many conditions HGT can surprisingly overcome the biodiversity limit predicted by the classic model and allow the coexistence of many competitors, by enabling dynamic neutrality of competing species. In contrast with the static neutrality proposed by previous theories, the diversity maintained by HGT is highly stable against random perturbations of microbial fitness. Our work highlights the importance of considering gene flow when addressing fundamental ecological questions in the world of microbes and has broad implications for the design and engineering of complex microbial consortia.
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Affiliation(s)
- Shiben Zhu
- Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Juken Hong
- Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Teng Wang
- Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
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13
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Gralka M. Searching for Principles of Microbial Ecology Across Levels of Biological Organization. Integr Comp Biol 2023; 63:1520-1531. [PMID: 37280177 PMCID: PMC10755194 DOI: 10.1093/icb/icad060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 05/21/2023] [Accepted: 06/01/2023] [Indexed: 06/08/2023] Open
Abstract
Microbial communities play pivotal roles in ecosystems across different scales, from global elemental cycles to household food fermentations. These complex assemblies comprise hundreds or thousands of microbial species whose abundances vary over time and space. Unraveling the principles that guide their dynamics at different levels of biological organization, from individual species, their interactions, to complex microbial communities, is a major challenge. To what extent are these different levels of organization governed by separate principles, and how can we connect these levels to develop predictive models for the dynamics and function of microbial communities? Here, we will discuss recent advances that point towards principles of microbial communities, rooted in various disciplines from physics, biochemistry, and dynamical systems. By considering the marine carbon cycle as a concrete example, we demonstrate how the integration of levels of biological organization can offer deeper insights into the impact of increasing temperatures, such as those associated with climate change, on ecosystem-scale processes. We argue that by focusing on principles that transcend specific microbiomes, we can pave the way for a comprehensive understanding of microbial community dynamics and the development of predictive models for diverse ecosystems.
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Affiliation(s)
- Matti Gralka
- Systems Biology lab, Amsterdam Institute for Life and Environment (A-LIFE), Amsterdam Institute of Molecular and Life Sciences (AIMMS), Vrije Universiteit Amsterdam, 1081 HV, The Netherlands
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14
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Arya S, George AB, O’Dwyer JP. Sparsity of higher-order landscape interactions enables learning and prediction for microbiomes. Proc Natl Acad Sci U S A 2023; 120:e2307313120. [PMID: 37991947 PMCID: PMC10691334 DOI: 10.1073/pnas.2307313120] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 10/16/2023] [Indexed: 11/24/2023] Open
Abstract
Microbiome engineering offers the potential to leverage 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 cataloging 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 mechanisms are included and which are omitted. Here, we resolve both issues by introducing a mechanism-agnostic approach to predicting microbial community compositions and functions using limited data. The critical step is the identification 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 [Formula: see text]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.
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Affiliation(s)
- Shreya Arya
- Department of Physics, University of Illinois, Urbana-Champaign, Urbana, IL61801
| | - Ashish B. George
- Center for Artificial Intelligence and Modeling, Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL61801
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA0214
- Department of Plant Biology, University of Illinois, Urbana-Champaign, Urbana, IL61801
| | - James P. O’Dwyer
- Center for Artificial Intelligence and Modeling, Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL61801
- Department of Plant Biology, University of Illinois, Urbana-Champaign, Urbana, IL61801
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15
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Miller ZR, Allesina S. Habitat Heterogeneity, Environmental Feedbacks, and Species Coexistence across Timescales. Am Nat 2023; 202:E53-E64. [PMID: 37531282 DOI: 10.1086/724821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/04/2023]
Abstract
AbstractClassic ecological theory explains species coexistence in variable environments. While spatial variation is often treated as an intrinsic feature of a landscape, it may be shaped and even generated by the resident community. All species modify their local environment to some extent, driving changes that can feed back to affect the composition and coexistence of the community, potentially over timescales very different from population dynamics. We introduce a simple nested modeling framework for community dynamics in heterogeneous environments, including the possible evolution of heterogeneity over time due to community-environment feedbacks. We use this model to derive analytical conditions for species coexistence in environments where heterogeneity is either fixed or shaped by feedbacks. Among other results, our approach reveals how dispersal and environmental specialization interact to shape realized patterns of habitat association and demonstrates that environmental feedbacks can tune landscape conditions to allow the stable coexistence of any number of species. Our flexible modeling framework helps explain feedback dynamics that arise in a wide range of ecosystems and offers a generic platform for exploring the interplay between species and landscape diversity.
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16
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Chang CY, Bajić D, Vila JCC, Estrela S, Sanchez A. Emergent coexistence in multispecies microbial communities. Science 2023; 381:343-348. [PMID: 37471535 DOI: 10.1126/science.adg0727] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 06/15/2023] [Indexed: 07/22/2023]
Abstract
Understanding the mechanisms that maintain microbial biodiversity is a critical aspiration in ecology. Past work on microbial coexistence has largely focused on species pairs, but it is unclear whether pairwise coexistence in isolation is required for coexistence in a multispecies community. To address this question, we conducted hundreds of pairwise competition experiments among the stably coexisting members of 12 different enrichment communities in vitro. To determine the outcomes of these experiments, we developed an automated image analysis pipeline to quantify species abundances. We found that competitive exclusion was the most common outcome, and it was strongly hierarchical and transitive. Because many species that coexist within a stable multispecies community fail to coexist in pairwise co-culture under identical conditions, we concluded that multispecies coexistence is an emergent phenomenon. This work highlights the importance of community context for understanding the origins of coexistence in complex ecosystems.
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Affiliation(s)
- Chang-Yu Chang
- Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT, USA
- Microbial Sciences Institute, Yale University, New Haven, CT, USA
- Department of Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - Djordje Bajić
- Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT, USA
- Microbial Sciences Institute, Yale University, New Haven, CT, USA
- Department of Biotechnology, Delft University of Technology, Delft, Netherlands
| | - Jean C C Vila
- Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT, USA
- Microbial Sciences Institute, Yale University, New Haven, CT, USA
| | - Sylvie Estrela
- Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT, USA
- Microbial Sciences Institute, Yale University, New Haven, CT, USA
| | - Alvaro Sanchez
- Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT, USA
- Microbial Sciences Institute, Yale University, New Haven, CT, USA
- Department of Microbial Biotechnology. Centro Nacional de Biotecnología - CSIC, Campus de Cantoblanco, Madrid, Spain
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17
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Clenet M, Massol F, Najim J. Equilibrium and surviving species in a large Lotka-Volterra system of differential equations. J Math Biol 2023; 87:13. [PMID: 37335417 DOI: 10.1007/s00285-023-01939-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 04/25/2023] [Accepted: 05/19/2023] [Indexed: 06/21/2023]
Abstract
Lotka-Volterra (LV) equations play a key role in the mathematical modeling of various ecological, biological and chemical systems. When the number of species (or, depending on the viewpoint, chemical components) becomes large, basic but fundamental questions such as computing the number of surviving species still lack theoretical answers. In this paper, we consider a large system of LV equations where the interactions between the various species are a realization of a random matrix. We provide conditions to have a unique equilibrium and present a heuristics to compute the number of surviving species. This heuristics combines arguments from Random Matrix Theory, mathematical optimization (LCP), and standard extreme value theory. Numerical simulations, together with an empirical study where the strength of interactions evolves with time, illustrate the accuracy and scope of the results.
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Affiliation(s)
- Maxime Clenet
- CNRS, Université Gustave Eiffel, Champs-sur-Marne, France.
| | - François Massol
- Univ. Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019 - UMR 9017 - CIIL - Center for Infection and Immunity of Lille, 59000, Lille, France
| | - Jamal Najim
- CNRS, Université Gustave Eiffel, Champs-sur-Marne, France
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18
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Henry LP, Bergelson J. Evolutionary implications of host genetic control for engineering beneficial microbiomes. CURRENT OPINION IN SYSTEMS BIOLOGY 2023; 34:None. [PMID: 37287906 PMCID: PMC10242548 DOI: 10.1016/j.coisb.2023.100455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Engineering new functions in the microbiome requires understanding how host genetic control and microbe-microbe interactions shape the microbiome. One key genetic mechanism underlying host control is the immune system. The immune system can promote stability in the composition of the microbiome by reshaping the ecological dynamics of its members, but the degree of stability will depend on the interplay between ecological context, immune system development, and higher-order microbe-microbe interactions. The eco-evolutionary interplay affecting composition and stability should inform the strategies used to engineer new functions in the microbiome. We conclude with recent methodological developments that provide an important path forward for both engineering new functionality in the microbiome and broadly understanding how ecological interactions shape evolutionary processes in complex biological systems.
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19
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Blonder BW, Lim MH, Sunberg Z, Tomlin C. Navigation between initial and desired community states using shortcuts. Ecol Lett 2023; 26:516-528. [PMID: 36756862 DOI: 10.1111/ele.14171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 01/10/2023] [Indexed: 02/10/2023]
Abstract
Ecological management problems often involve navigating from an initial to a desired community state. We ask whether navigation without brute-force additions and deletions of species is possible via: adding/deleting a small number of individuals of a species, changing the environment, and waiting. Navigation can yield direct paths (single sequence of actions) or shortcut paths (multiple sequences of actions with lower cost than a direct path). We ask (1) when is non-brute-force navigation possible?; (2) do shortcuts exist and what are their properties?; and (3) what heuristics predict shortcut existence? Using a state diagram framework applied to several empirical datasets, we show that (1) non-brute-force navigation is only possible between some state pairs, (2) shortcuts exist between many state pairs; and (3) changes in abundance and richness are the strongest predictors of shortcut existence, independent of dataset and algorithm choices. State diagrams thus unveil hidden strategies for manipulating species coexistence and efficiently navigating between states.
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Affiliation(s)
- Benjamin W Blonder
- Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, California, USA
| | - Michael H Lim
- Department of Electrical Engineering and Computer Science, University of California Berkeley, Berkeley, California, USA
| | - Zachary Sunberg
- Aerospace Engineering Sciences Department, University of Colorado Boulder, Boulder, Colorado, USA
| | - Claire Tomlin
- Department of Electrical Engineering and Computer Science, University of California Berkeley, Berkeley, California, USA
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20
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Baron JW, Jewell TJ, Ryder C, Galla T. Breakdown of Random-Matrix Universality in Persistent Lotka-Volterra Communities. PHYSICAL REVIEW LETTERS 2023; 130:137401. [PMID: 37067312 DOI: 10.1103/physrevlett.130.137401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 06/17/2022] [Accepted: 03/06/2023] [Indexed: 06/19/2023]
Abstract
The eigenvalue spectrum of a random matrix often only depends on the first and second moments of its elements, but not on the specific distribution from which they are drawn. The validity of this universality principle is often assumed without proof in applications. In this Letter, we offer a pertinent counterexample in the context of the generalized Lotka-Volterra equations. Using dynamic mean-field theory, we derive the statistics of the interactions between species in an evolved ecological community. We then show that the full statistics of these interactions, beyond those of a Gaussian ensemble, are required to correctly predict the eigenvalue spectrum and therefore stability. Consequently, the universality principle fails in this system. We thus show that the eigenvalue spectra of random matrices can be used to deduce the stability of "feasible" ecological communities, but only if the emergent non-Gaussian statistics of the interactions between species are taken into account.
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Affiliation(s)
- Joseph W Baron
- Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB), 07122 Palma de Mallorca, Spain
| | - Thomas Jun Jewell
- Department of Physics and Astronomy, School of Natural Sciences, The University of Manchester, Manchester M13 9PL, United Kingdom
| | - Christopher Ryder
- Department of Physics and Astronomy, School of Natural Sciences, The University of Manchester, Manchester M13 9PL, United Kingdom
| | - Tobias Galla
- Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB), 07122 Palma de Mallorca, Spain
- Department of Physics and Astronomy, School of Natural Sciences, The University of Manchester, Manchester M13 9PL, United Kingdom
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21
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García-Callejas D, Godoy O, Buche L, Hurtado M, Lanuza JB, Allen-Perkins A, Bartomeus I. Non-random interactions within and across guilds shape the potential to coexist in multi-trophic ecological communities. Ecol Lett 2023; 26:831-842. [PMID: 36972904 DOI: 10.1111/ele.14206] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 01/12/2023] [Accepted: 02/05/2023] [Indexed: 03/29/2023]
Abstract
Theory posits that the persistence of species in ecological communities is shaped by their interactions within and across trophic guilds. However, we lack empirical evaluations of how the structure, strength and sign of biotic interactions drive the potential to coexist in diverse multi-trophic communities. Here, we model community feasibility domains, a theoretically informed measure of multi-species coexistence probability, from grassland communities comprising more than 45 species on average from three trophic guilds (plants, pollinators and herbivores). Contrary to our hypothesis, increasing community complexity, measured either as the number of guilds or community richness, did not decrease community feasibility. Rather, we observed that high degrees of species self-regulation and niche partitioning allow for maintaining larger levels of community feasibility and higher species persistence in more diverse communities. Our results show that biotic interactions within and across guilds are not random in nature and both structures significantly contribute to maintaining multi-trophic diversity.
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Affiliation(s)
- David García-Callejas
- Estación Biológica de Doñana (EBD-CSIC), Seville, Spain
- Instituto Universitario de Ciencias del Mar (INMAR), Departamento de Biología, Universidad de Cádiz, E-11510, Puerto Real, Spain
- School of Biological Sciences, University of Canterbury, 8140, Christchurch, Private Bag 4800, New Zealand
| | - Oscar Godoy
- Instituto Universitario de Ciencias del Mar (INMAR), Departamento de Biología, Universidad de Cádiz, E-11510, Puerto Real, Spain
| | - Lisa Buche
- Instituto Universitario de Ciencias del Mar (INMAR), Departamento de Biología, Universidad de Cádiz, E-11510, Puerto Real, Spain
| | - María Hurtado
- Estación Biológica de Doñana (EBD-CSIC), Seville, Spain
- Instituto Universitario de Ciencias del Mar (INMAR), Departamento de Biología, Universidad de Cádiz, E-11510, Puerto Real, Spain
| | - Jose B Lanuza
- Estación Biológica de Doñana (EBD-CSIC), Seville, Spain
| | - Alfonso Allen-Perkins
- Estación Biológica de Doñana (EBD-CSIC), Seville, Spain
- Departamento de Ingeniería Eléctrica, Electrónica, Automática y Física Aplicada, ETSIDI, Technical University of Madrid, 28040, Madrid, Spain
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22
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Blonder BW, Gaüzère P, Iversen LL, Ke P, Petry WK, Ray CA, Salguero‐Gómez R, Sharpless W, Violle C. Predicting and controlling ecological communities via trait and environment mediated parameterizations of dynamical models. OIKOS 2023. [DOI: 10.1111/oik.09415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2023]
Affiliation(s)
- Benjamin Wong Blonder
- Dept of Environmental Science, Policy, and Management, Univ. of California Berkeley CA USA
- School of Life Sciences, Arizona State Univ. Tempe AZ USA
| | - Pierre Gaüzère
- School of Life Sciences, Arizona State Univ. Tempe AZ USA
| | | | - Po‐Ju Ke
- Dept of Ecology & Evolutionary Biology, Princeton Univ. Princeton NJ USA
- Institute of Ecology and Evolutionary Biology, National Taiwan Univ. Taipei Taiwan
| | - William K. Petry
- Dept of Ecology & Evolutionary Biology, Princeton Univ. Princeton NJ USA
- Dept of Plant & Microbial Biology, North Carolina State Univ. Raleigh NC USA
| | - Courtenay A. Ray
- Dept of Environmental Science, Policy, and Management, Univ. of California Berkeley CA USA
- School of Life Sciences, Arizona State Univ. Tempe AZ USA
| | - Roberto Salguero‐Gómez
- Dept of Zoology, Univ. of Oxford Oxford UK
- Max Planck Institute for Demographic Research Rostock Germany
- Center of Excellence in Environmental Decisions, Univ. of Queensland Brisbane Australia
| | - William Sharpless
- Dept of Bioengineering, Univ. of California Berkeley Berkeley CA USA
| | - Cyrille Violle
- CEFE ‐ Univ Montpellier ‐ CNRS – EPHE – IRD Montpellier France
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23
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Rubin IN, Ispolatov Y, Doebeli M. Maximal ecological diversity exceeds evolutionary diversity in model ecosystems. Ecol Lett 2023; 26:384-397. [PMID: 36737422 DOI: 10.1111/ele.14156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 10/10/2022] [Accepted: 10/12/2022] [Indexed: 02/05/2023]
Abstract
Understanding community saturation is fundamental to ecological theory. While investigations of the diversity of evolutionary stable states (ESSs) are widespread, the diversity of communities that have yet to reach an evolutionary endpoint is poorly understood. We use Lotka-Volterra dynamics and trait-based competition to compare the diversity of randomly assembled communities to the diversity of the ESS. We show that, with a large enough founding diversity (whether assembled at once or through sequential invasions), the number of long-time surviving species exceeds that of the ESS. However, the excessive founding diversity required to assemble a saturated community increases rapidly with the dimension of phenotype space. Additionally, traits present in communities resulting from random assembly are more clustered in phenotype space compared to random, although still markedly less ordered than the ESS. By combining theories of random assembly and ESSs we bring a new viewpoint to both the saturation and random assembly literature.
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Affiliation(s)
- Ilan N Rubin
- Department of Zoology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Yaroslav Ispolatov
- University of Santiago of Chile (USACH), Physics Department, Santiago, Chile
| | - Michael Doebeli
- Department of Zoology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada
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24
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Complex ecological communities and the emergence of island species-area relationships. THEOR ECOL-NETH 2022. [DOI: 10.1007/s12080-022-00545-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Abstract
AbstractIt has been a century since the species-area relationship (SAR) was first proposed as a power law to explain how species richness scales with area. There have been many attempts to explain the origin of this predominant form. Apart from the power law, numerous empirical studies also report a semi-log form of the SAR, but very few have addressed its incidence. In this work, we test whether these relationships could emerge from the assembly of large random communities on island-like systems. The clustering of same-species individuals is central to our results, which we incorporate by modifying the self-interaction term in the generalized Lotka-Volterra equations. Our analysis demonstrates that the two most widely reported relationship forms can emerge due to differences in immigration rates and skewness towards weak interactions. We particularly highlight the incidence of the semi-log SAR for low immigration rates from a source pool, which is consistent with several previous empirical studies. The two SAR forms might show good fits to data over a large span of areas but a power-law overestimates species richness on smaller islands in remote archipelagoes.
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25
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The geometry of evolved community matrix spectra. Sci Rep 2022; 12:14668. [PMID: 36038623 PMCID: PMC9530164 DOI: 10.1038/s41598-022-17379-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 07/25/2022] [Indexed: 11/18/2022] Open
Abstract
Random matrix theory has been applied to food web stability for decades, implying elliptical eigenvalue spectra and that large food webs should be unstable. Here we allow feasible food webs to self-assemble within an evolutionary process, using simple Lotka–Volterra equations and several elementary interaction types. We show that, as complex food webs evolve under \documentclass[12pt]{minimal}
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\begin{document}$${10^5}$$\end{document}105 invasion attempts, the community matrix spectra become bi-modal, rather than falling onto elliptical geometries. Our results raise questions as to the applicability of random matrix theory to the analysis of food web steady states.
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26
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Saeedian M, Pigani E, Maritan A, Suweis S, Azaele S. Effect of delay on the emergent stability patterns in generalized Lotka-Volterra ecological dynamics. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2022; 380:20210245. [PMID: 35599557 DOI: 10.1098/rsta.2021.0245] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
Understanding the conditions of feasibility and stability in ecological systems is a major challenge in theoretical ecology. The seminal work of May in 1972 and recent developments based on the theory of random matrices have shown the existence of emergent universal patterns of both stability and feasibility in ecological dynamics. However, only a few studies have investigated the role of delay coupled with population dynamics in the emergence of feasible and stable states. In this work, we study the effects of delay on generalized Loka-Volterra population dynamics of several interacting species in closed ecological environments. First, we investigate the relation between feasibility and stability of the modelled ecological community in the absence of delay and find a simple analytical relation when intra-species interactions are dominant. We then show how, by increasing the time delay, there is a transition in the stability phases of the population dynamics: from an equilibrium state to a stable non-point attractor phase. We calculate analytically the critical delay of that transition and show that it is in excellent agreement with numerical simulations. Finally, following a similar approach to characterizing stability in empirical studies, we investigate the coefficient of variation, which quantifies the magnitude of population fluctuations. We show that in the oscillatory regime induced by the delay, the variability at community level decreases for increasing diversity. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.
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Affiliation(s)
- Meghdad Saeedian
- Dipartimento di Fisica 'G. Galilei', Università di Padova, Via Marzolo 8, 35131 Padova, Italy
- School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Emanuele Pigani
- Dipartimento di Fisica 'G. Galilei', Università di Padova, Via Marzolo 8, 35131 Padova, Italy
- Stazione Zoologica Anton Dohrn, Villa Comunale, 80121 Naples, Italy
| | - Amos Maritan
- Dipartimento di Fisica 'G. Galilei', Università di Padova, Via Marzolo 8, 35131 Padova, Italy
| | - Samir Suweis
- Dipartimento di Fisica 'G. Galilei', Università di Padova, Via Marzolo 8, 35131 Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Sandro Azaele
- Dipartimento di Fisica 'G. Galilei', Università di Padova, Via Marzolo 8, 35131 Padova, Italy
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27
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Taguas I, Capitán JA, Nuño JC. Dropping mortality by increasing connectivity in plant epidemics. Phys Rev E 2022; 105:064301. [PMID: 35854574 DOI: 10.1103/physreve.105.064301] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 04/24/2022] [Indexed: 06/15/2023]
Abstract
Pathogen introduction in plant communities can cause serious impacts and biodiversity losses that may take a long time to manage and restore. Effective control of epidemic spreading in the wild is a problem of paramount importance because of its implications in conservation and potential economic losses. Understanding the mechanisms that hinder pathogen propagation is, therefore, crucial. Usual modelization approaches in epidemic spreading are based in compartmentalized models, without keeping track of pathogen concentrations during spreading. In this contribution we present and fully analyze a dynamical model for plant epidemic spreading based on pathogen abundances. The model, which is defined on top of network substrates, is amenable to a deep mathematical analysis in the absence of a limit in the amount of pathogen a plant can tolerate before dying. In the presence of such death threshold, we observe that the fraction of dead plants peaks at intermediate values of network connectivity, and mortality decreases for large average degrees. We discuss the implications of our results as mechanisms to halt infection propagation.
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Affiliation(s)
- Ignacio Taguas
- Department of Applied Mathematics, Universidad Politécnica de Madrid, Avenida Juan de Herrera 6, E-28040 Madrid, Spain
| | - José A Capitán
- Department of Applied Mathematics, Universidad Politécnica de Madrid, Avenida Juan de Herrera 6, E-28040 Madrid, Spain
| | - Juan C Nuño
- Department of Applied Mathematics, Universidad Politécnica de Madrid, Avenida Juan de Herrera 6, E-28040 Madrid, Spain
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28
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Takashina N. Linking multi-level population dynamics: state, role, and population. PeerJ 2022; 10:e13315. [PMID: 35582614 PMCID: PMC9107789 DOI: 10.7717/peerj.13315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 03/31/2022] [Indexed: 01/13/2023] Open
Abstract
The dynamics of an ecological community can be described at different focal scales of the species, such as individual states or the population level. More detailed descriptions of ecological dynamics offer more information, but produce more complex models that are difficult to analyze. Adequately controlling the model complexity and the availability of multiple descriptions of the concerned dynamics maximizes our understanding of ecological dynamics. One of the central goals of ecological studies is to develop links between multiple descriptions of an ecological community. In this article, starting from a nonlinear state-level description of an ecological community (generalized McKendrick-von Foerster model), role-level and population-level descriptions (Lotka-Volterra model) are derived in a consistent manner. The role-level description covers a wider range of situations than the population-level description. However, using the established connections, it is demonstrated that the population-level description can be used to predict the equilibrium status of the role-level description. This approach connects state-, role-, and population-level dynamics consistently, and offers a justification for the multiple choices of model description.
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29
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Miller ZR, Allesina S. Metapopulations with habitat modification. Proc Natl Acad Sci U S A 2021; 118:e2109896118. [PMID: 34857638 PMCID: PMC8670473 DOI: 10.1073/pnas.2109896118] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/26/2021] [Indexed: 11/18/2022] Open
Abstract
Across the tree of life, organisms modify their local environment, rendering it more or less hospitable for other species. Despite the ubiquity of these processes, simple models that can be used to develop intuitions about the consequences of widespread habitat modification are lacking. Here, we extend the classic Levins metapopulation model to a setting where each of n species can colonize patches connected by dispersal, and when patches are vacated via local extinction, they retain a "memory" of the previous occupant-modeling habitat modification. While this model can exhibit a wide range of dynamics, we draw several overarching conclusions about the effects of modification and memory. In particular, we find that any number of species may potentially coexist, provided that each is at a disadvantage when colonizing patches vacated by a conspecific. This notion is made precise through a quantitative stability condition, which provides a way to unify and formalize existing conceptual models. We also show that when patch memory facilitates coexistence, it generically induces a positive relationship between diversity and robustness (tolerance of disturbance). Our simple model provides a portable, tractable framework for studying systems where species modify and react to a shared landscape.
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Affiliation(s)
- Zachary R Miller
- Department of Ecology and Evolution, The University of Chicago, Chicago, IL 60637;
| | - Stefano Allesina
- Department of Ecology and Evolution, The University of Chicago, Chicago, IL 60637
- Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL 60208
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30
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Cui W, Marsland R, Mehta P. Diverse communities behave like typical random ecosystems. Phys Rev E 2021; 104:034416. [PMID: 34654170 DOI: 10.1103/physreve.104.034416] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 09/08/2021] [Indexed: 01/05/2023]
Abstract
In 1972, Robert May triggered a worldwide research program studying ecological communities using random matrix theory. Yet, it remains unclear if and when we can treat real communities as random ecosystems. Here, we draw on recent progress in random matrix theory and statistical physics to extend May's approach to generalized consumer-resource models. We show that in diverse ecosystems adding even modest amounts of noise to consumer preferences results in a transition to "typicality," where macroscopic ecological properties of communities are indistinguishable from those of random ecosystems, even when resource preferences have prominent designed structures. We test these ideas using numerical simulations on a wide variety of ecological models. Our work offers an explanation for the success of random consumer resource models in reproducing experimentally observed ecological patterns in microbial communities and highlights the difficulty of scaling up bottom-up approaches in synthetic ecology to diverse communities.
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Affiliation(s)
- Wenping Cui
- Department of Physics, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02139, USA and Department of Physics, Boston College, 140 Commonwealth Avenue, Chestnut Hill, Massachusetts 02467, USA
| | - Robert Marsland
- Department of Physics, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02139, USA
| | - Pankaj Mehta
- Department of Physics, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02139, USA
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31
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Teodosio-Faustino IA, Chávez-González E, Ruelas Inzunza E. In a Neotropical Periurban Park, Fruit Consumption by Birds Seems to Be a Random Process. Front Ecol Evol 2021. [DOI: 10.3389/fevo.2021.630150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Frugivory interactions between birds and fruit-bearing plants are shaped by the abundance of its interacting species, their temporal overlap, the matching of their morphologies, as well as fruit and seed characteristics. Our study evaluates the role of seven factors of fruits and plants in determining the frequency of whole-fruit consumption by birds. We studied the frugivory network of a Neotropical periurban park in Xalapa, Veracruz, Mexico, and quantified relative abundance and phenology of birds and fruit, as well as fruit morphology, chromatic and achromatic contrast, and nutritional content. Using a maximum likelihood approach, we compared the observed interaction network with 62 single- and multiple-variable probabilistic models. Our network is composed of 11 plants and 17 birds involved in 81 frugivory interactions. This network is nested, modular, and relatively specialized. However, the frequency of pairwise interactions is not explained by the variables examined in our probabilistic models and found the null model has the best performance. This indicates that no single predictor or combination of them is better at explaining the observed frequency of pairwise interactions than the null model. The subsequent four top-ranking models, with ΔAIC values < 100, are single-variable ones: carbohydrate content, lipid content, chromatic contrast, and morphology. Two- and three-variable models show the poorest fit to observed data. The lack of a deterministic pattern does not support any of our predictions nor neutral- or niche-based processes shaping the observed pattern of fruit consumption in our interaction network. It may also mean that fruit consumption by birds in this periurban park is a random process. Although our study failed to find a pattern, our work exemplifies how investigations done in urban settings, poor in species and interactions, can help us understand the role of disturbance in the organization of frugivory networks and the processes governing their structure.
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Spaak JW, Carpentier C, De Laender F. Species richness increases fitness differences, but does not affect niche differences. Ecol Lett 2021; 24:2611-2623. [PMID: 34532957 DOI: 10.1111/ele.13877] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 06/21/2021] [Accepted: 08/20/2021] [Indexed: 11/30/2022]
Abstract
A key question in ecology is what limits species richness. Modern coexistence theory presents the persistence of species as a balance between niche differences and fitness differences that favour and hamper coexistence, respectively. With most applications focusing on species pairs, however, we know little about if and how this balance changes with species richness. Here, we apply recently developed definitions of niche and fitness differences, based on invasion analysis, to multispecies communities. We present the first mathematical proof that, for invariant average interaction strengths, the average fitness difference among species increases with richness, while the average niche difference stays constant. Extensive simulations with more complex models and analyses of empirical data confirmed these mathematical results. Combined, our work suggests that, as species accumulate in ecosystems, ever-increasing fitness differences will at some point exceed constant niche differences, limiting species richness. Our results contribute to a better understanding of coexistence multispecies communities.
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Affiliation(s)
- Jurg W Spaak
- University of Namur, Institute of Life-Earth-Environment, Namur Center for Complex Systems, Namur, Belgium.,Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, New York, USA
| | - Camille Carpentier
- University of Namur, Institute of Life-Earth-Environment, Namur Center for Complex Systems, Namur, Belgium
| | - Frederik De Laender
- University of Namur, Institute of Life-Earth-Environment, Namur Center for Complex Systems, Namur, Belgium
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33
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Capitán JA, Cuenda S, Ordóñez A, Alonso D. A signal of competitive dominance in mid-latitude herbaceous plant communities. ROYAL SOCIETY OPEN SCIENCE 2021; 8:201361. [PMID: 34567583 PMCID: PMC8456147 DOI: 10.1098/rsos.201361] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 08/18/2021] [Indexed: 06/13/2023]
Abstract
Understanding the main determinants of species coexistence across space and time is a central question in ecology. However, ecologists still know little about the scales and conditions at which biotic interactions matter and how these interact with the environment to structure species assemblages. Here we use recent theoretical developments to analyse plant distribution and trait data across Europe and find that plant height clustering is related to both evapotranspiration (ET) and gross primary productivity. This clustering is a signal of interspecies competition between plants, which is most evident in mid-latitude ecoregions, where conditions for growth (reflected in actual ET rates and gross primary productivities) are optimal. Away from this optimum, climate severity probably overrides the effect of competition, or other interactions become increasingly important. Our approach bridges the gap between species-rich competition theories and large-scale species distribution data analysis.
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Affiliation(s)
- José A. Capitán
- Complex Systems Group, Department of Applied Mathematics, Universidad Politécnica de Madrid, Av. Juan de Herrera, 6, 28040 Madrid, Spain
- Theoretical and Computational Ecology, Center for Advanced Studies (CEAB-CSIC), C. Accés Cala St. Francesc 14, 17300 Blanes, Catalonia, Spain
| | - Sara Cuenda
- Facultad de Ciencias Económicas y Empresariales, Depto. Análisis Económico: Economía Cuantitativa, C. Francisco Tomás y Valiente 5, Universidad Autónoma de Madrid, 28049 Madrid, Spain
| | - Alejandro Ordóñez
- Department of Bioscience, Aarhus University, Aarhus, Ny Munkegade 114, 8000 Aarhus C, Denmark
| | - David Alonso
- Theoretical and Computational Ecology, Center for Advanced Studies (CEAB-CSIC), C. Accés Cala St. Francesc 14, 17300 Blanes, Catalonia, Spain
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34
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Emary C, Evans D. Can a complex ecosystem survive the loss of a large fraction of its species? A random matrix theory of secondary extinction. OIKOS 2021. [DOI: 10.1111/oik.08286] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Affiliation(s)
- Clive Emary
- School of Mathematics, Statistics and Physics, Newcastle Univ. Newcastle‐upon‐Tyne UK
| | - Darren Evans
- School of Natural and Environmental Sciences, Newcastle Univ. Newcastle‐upon‐Tyne UK
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35
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Gjini E, Madec S. The ratio of single to co-colonization is key to complexity in interacting systems with multiple strains. Ecol Evol 2021; 11:8456-8474. [PMID: 34257910 PMCID: PMC8258234 DOI: 10.1002/ece3.7259] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 12/16/2020] [Accepted: 01/12/2021] [Indexed: 11/06/2022] Open
Abstract
The high number and diversity of microbial strains circulating in host populations have motivated extensive research on the mechanisms that maintain biodiversity. However, much of this work focuses on strain-specific and cross-immunity interactions. Another less explored mode of pairwise interaction is via altered susceptibilities to co-colonization in hosts already colonized by one strain. Diversity in such interaction coefficients enables strains to create dynamically their niches for growth and persistence, and "engineer" their common environment. How such a network of interactions with others mediates collective coexistence remains puzzling analytically and computationally difficult to simulate. Furthermore, the gradients modulating stability-complexity regimes in such multi-player endemic systems remain poorly understood. In a recent study (Madec & Gjini, Bulletin of Mathematical Biology, 82), we obtained an analytic representation for N-type coexistence in an SIS epidemiological model with co-colonization. We mapped multi-strain dynamics to a replicator equation using timescale separation. Here, we examine what drives coexistence regimes in such co-colonization system. We find the ratio of single to co-colonization, µ, critically determines the type of equilibrium and number of coexisting strains, and encodes a trade-off between overall transmission intensity R 0 and mean interaction coefficient in strain space, k. Preserving a given coexistence regime, under fixed trait variation, requires balancing between higher mean competition in favorable environments, and higher cooperation in harsher environments, and is consistent with the stress gradient hypothesis. Multi-strain coexistence tends to steady-state attractors for small µ, whereas as µ increases, dynamics tend to more complex attractors. Following strain frequencies, evolutionary dynamics in the system also display contrasting patterns with µ, interpolating between multi-stable and fluctuating selection for cooperation and mean invasion fitness, in the two extremes. This co-colonization framework could be applied more generally, to study invariant principles in collective coexistence, and to quantify how critical shifts in community dynamics get potentiated by mean-field and environmental gradients.
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Affiliation(s)
- Erida Gjini
- Instituto Gulbenkian de CiênciaOeirasPortugal
- Center for Computational and Stochastic MathematicsInstituto Superior TécnicoUniversity of LisbonLisbonPortugal
| | - Sten Madec
- Institut Denis PoissonUniversity of ToursToursFrance
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36
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Wiegand T, Wang X, Anderson-Teixeira KJ, Bourg NA, Cao M, Ci X, Davies SJ, Hao Z, Howe RW, Kress WJ, Lian J, Li J, Lin L, Lin Y, Ma K, McShea W, Mi X, Su SH, Sun IF, Wolf A, Ye W, Huth A. Consequences of spatial patterns for coexistence in species-rich plant communities. Nat Ecol Evol 2021; 5:965-973. [PMID: 33941904 PMCID: PMC8257505 DOI: 10.1038/s41559-021-01440-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Accepted: 03/01/2021] [Indexed: 02/02/2023]
Abstract
Ecology cannot yet fully explain why so many tree species coexist in natural communities such as tropical forests. A major difficulty is linking individual-level processes to community dynamics. We propose a combination of tree spatial data, spatial statistics and dynamical theory to reveal the relationship between spatial patterns and population-level interaction coefficients and their consequences for multispecies dynamics and coexistence. Here we show that the emerging population-level interaction coefficients have, for a broad range of circumstances, a simpler structure than their individual-level counterparts, which allows for an analytical treatment of equilibrium and stability conditions. Mechanisms such as animal seed dispersal, which result in clustering of recruits that is decoupled from parent locations, lead to a rare-species advantage and coexistence of otherwise neutral competitors. Linking spatial statistics with theories of community dynamics offers new avenues for explaining species coexistence and calls for rethinking community ecology through a spatial lens.
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Affiliation(s)
- Thorsten Wiegand
- Department of Ecological Modelling, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany.
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
| | - Xugao Wang
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, .
| | - Kristina J Anderson-Teixeira
- Conservation Ecology Center, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
- Forest Global Earth Observatory (ForestGEO), Smithsonian Tropical Research Institute, Washington, DC, USA
| | - Norman A Bourg
- Conservation Ecology Center, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
| | - Min Cao
- CAS Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences
| | - Xiuqin Ci
- Center of Conservation Biology, Core Botanical Gardens, Chinese Academy of Sciences
- Centre for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences
| | - Stuart J Davies
- Forest Global Earth Observatory (ForestGEO), Smithsonian Tropical Research Institute, Washington, DC, USA
| | - Zhanqing Hao
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences
- School of Ecology and Environment, Northwestern Polytechnical University
| | - Robert W Howe
- Department of Natural and Applied Sciences, University of Wisconsin-Green Bay, Green Bay, WI, USA
| | - W John Kress
- Department of Botany, National Museum of Natural History, Smithsonian Institution, Washington, DC, USA
| | - Juyu Lian
- Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences
| | - Jie Li
- Center of Conservation Biology, Core Botanical Gardens, Chinese Academy of Sciences
- Centre for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences
| | - Luxiang Lin
- CAS Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences
| | - Yiching Lin
- Department of Life Science, Tunghai University
| | - Keping Ma
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences
| | - William McShea
- Conservation Ecology Center, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
| | - Xiangcheng Mi
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences
| | | | - I-Fang Sun
- Center for Interdisciplinary Research on Ecology and Sustainability, National Dong Hwa University
| | - Amy Wolf
- Department of Natural and Applied Sciences, University of Wisconsin-Green Bay, Green Bay, WI, USA
| | - Wanhui Ye
- Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences
| | - Andreas Huth
- Department of Ecological Modelling, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Institute of Environmental Systems Research, University of Osnabrück, Osnabrück, Germany
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37
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Altieri A, Roy F, Cammarota C, Biroli G. Properties of Equilibria and Glassy Phases of the Random Lotka-Volterra Model with Demographic Noise. PHYSICAL REVIEW LETTERS 2021; 126:258301. [PMID: 34241496 DOI: 10.1103/physrevlett.126.258301] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 02/06/2021] [Accepted: 05/17/2021] [Indexed: 06/13/2023]
Abstract
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.
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Affiliation(s)
- Ada Altieri
- Laboratoire de Physique de l'École normale supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université de Paris F-75005 Paris, France
- Laboratoire Matière et Systèmes Complexes (MSC), Université de Paris & CNRS, 75013 Paris, France
| | - Felix Roy
- Laboratoire de Physique de l'École normale supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université de Paris F-75005 Paris, France
- Institut de physique théorique, Université Paris Saclay, CEA, CNRS, F-91191 Gif-sur-Yvette, France
| | - Chiara Cammarota
- Dipartimento di Fisica, Universitá "Sapienza," Piazzale A. Moro 2, I-00185 Rome, Italy
- Department of Mathematics, King's College London, Strand London WC2R 2LS, United Kingdom
| | - Giulio Biroli
- Laboratoire de Physique de l'École normale supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université de Paris F-75005 Paris, France
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38
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Haas PA, Goldstein RE. Turing's Diffusive Threshold in Random Reaction-Diffusion Systems. PHYSICAL REVIEW LETTERS 2021; 126:238101. [PMID: 34170176 DOI: 10.1103/physrevlett.126.238101] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 04/29/2021] [Indexed: 05/03/2023]
Abstract
Turing instabilities of reaction-diffusion systems can only arise if the diffusivities of the chemical species are sufficiently different. This threshold is unphysical in most systems with N=2 diffusing species, forcing experimental realizations of the instability to rely on fluctuations or additional nondiffusing species. Here, we ask whether this diffusive threshold lowers for N>2 to allow "true" Turing instabilities. Inspired by May's analysis of the stability of random ecological communities, we analyze the probability distribution of the diffusive threshold in reaction-diffusion systems defined by random matrices describing linearized dynamics near a homogeneous fixed point. In the numerically tractable cases N⩽6, we find that the diffusive threshold becomes more likely to be smaller and physical as N increases, and that most of these many-species instabilities cannot be described by reduced models with fewer diffusing species.
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Affiliation(s)
- Pierre A Haas
- Mathematical Institute, University of Oxford, Woodstock Road, Oxford OX2 6GG, United Kingdom
| | - Raymond E Goldstein
- Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Sciences, University of Cambridge, Wilberforce Road, Cambridge CB3 0WA, United Kingdom
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39
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Coexistence holes characterize the assembly and disassembly of multispecies systems. Nat Ecol Evol 2021; 5:1091-1101. [PMID: 34045718 DOI: 10.1038/s41559-021-01462-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 04/07/2021] [Indexed: 11/08/2022]
Abstract
A central goal of ecological research has been to understand the limits on the maximum number of species that can coexist under given constraints. However, we know little about the assembly and disassembly processes under which a community can reach such a maximum number, or whether this number is in fact attainable in practice. This limitation is partly due to the challenge of performing experimental work and partly due to the lack of a formalism under which one can systematically study such processes. Here, we introduce a formalism based on algebraic topology and homology theory to study the space of species coexistence formed by a given pool of species. We show that this space is characterized by ubiquitous discontinuities that we call coexistence holes (that is, empty spaces surrounded by filled space). Using theoretical and experimental systems, we provide direct evidence showing that these coexistence holes do not occur arbitrarily-their diversity is constrained by the internal structure of species interactions and their frequency can be explained by the external factors acting on these systems. Our work suggests that the assembly and disassembly of ecological systems is a discontinuous process that tends to obey regularities.
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40
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Zhao N, Saavedra S, Liu YY. Impact of colonization history on the composition of ecological systems. Phys Rev E 2021; 103:052403. [PMID: 34134331 PMCID: PMC8217719 DOI: 10.1103/physreve.103.052403] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 04/21/2021] [Indexed: 11/07/2022]
Abstract
Observational studies of ecological systems have shown that different species compositions can arise from distinct species arrival orders during community assembly-also known as colonization history. The presence of multiple interior equilibria in the positive orthant of the state space of the population dynamics will naturally lead to history dependency of the final state. However, it is still unclear whether and under which conditions colonization history will dominate community composition in the absence of multiple interior equilibria. Here, by considering that only one species can invade at a time and there are no recurrent invasions, we show clear evidence that the colonization history can have a big impact on the composition of ecological systems even in the absence of multiple interior equilibria. In particular, we first derive two simple rules to determine whether the composition of a community will depend on its colonization history in the absence of multiple interior equilibria and recurrent invasions. Then we apply them to communities governed by generalized Lotka-Volterra (gLV) dynamics and propose a numerical scheme to measure the probability of colonization history dependence. Finally, we show, via numerical simulations, that for gLV dynamics with a single interior equilibrium, the probability that community composition is dominated by colonization history increases monotonically with community size, network connectivity, and the variation of intrinsic growth rates across species. These results reveal that in the absence of multiple interior equilibria and recurrent invasions, community composition is a probabilistic process mediated by ecological dynamics via the interspecific variation and the size of regional pools.
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Affiliation(s)
- Nannan Zhao
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, 02115, USA
- Department of Applied Mathematics, Northwestern Polytechnical University, Xi’an, 710129, China
| | - Serguei Saavedra
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA
| | - Yang-Yu Liu
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, 02115, USA
- Center for Cancer Systems Biology, Dana Farber Cancer Institute, Boston, MA, 02115, USA
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41
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Liu F, Giometto A, Wu M. Microfluidic and mathematical modeling of aquatic microbial communities. Anal Bioanal Chem 2021; 413:2331-2344. [PMID: 33244684 PMCID: PMC7990691 DOI: 10.1007/s00216-020-03085-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 11/05/2020] [Accepted: 11/19/2020] [Indexed: 01/27/2023]
Abstract
Aquatic microbial communities contribute fundamentally to biogeochemical transformations in natural ecosystems, and disruption of these communities can lead to ecological disasters such as harmful algal blooms. Microbial communities are highly dynamic, and their composition and function are tightly controlled by the biophysical (e.g., light, fluid flow, and temperature) and biochemical (e.g., chemical gradients and cell concentration) parameters of the surrounding environment. Due to the large number of environmental factors involved, a systematic understanding of the microbial community-environment interactions is lacking. In this article, we show that microfluidic platforms present a unique opportunity to recreate well-defined environmental factors in a laboratory setting in a high throughput way, enabling quantitative studies of microbial communities that are amenable to theoretical modeling. The focus of this article is on aquatic microbial communities, but the microfluidic and mathematical models discussed here can be readily applied to investigate other microbiomes.
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Affiliation(s)
- Fangchen Liu
- Department of Biological and Environmental Engineering, Cornell University, Ithaca, NY, 14853, USA
| | - Andrea Giometto
- School of Civil and Environmental Engineering, Cornell University, Ithaca, NY, 14853, USA
| | - Mingming Wu
- Department of Biological and Environmental Engineering, Cornell University, Ithaca, NY, 14853, USA.
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42
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Serván CA, Allesina S. Tractable models of ecological assembly. Ecol Lett 2021; 24:1029-1037. [PMID: 33773006 DOI: 10.1111/ele.13702] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 10/27/2020] [Accepted: 01/12/2021] [Indexed: 12/20/2022]
Abstract
Ecological assembly is a fundamental and yet poorly understood process. Three main obstacles hinder the development of a theory of assembly, and when these issues are sidestepped by making strong assumptions, one can build an assembly graph in which nodes are ecological communities and edges are invasions shifting their composition. The graph can then be analysed directly, without the need to consider dynamics. To showcase this framework, we build and analyse assembly graphs for the competitive Lotka-Volterra model, showing that in these cases sequential assembly (in which species invade a community one at a time) can reach the same configurations found when starting the system with all species present at different initial conditions. We discuss how our results can advance our understanding of assembly both from an empirical and a theoretical point of view, informing the study of ecological restoration and the design of ecological communities.
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Affiliation(s)
- Carlos A Serván
- Department of Ecology & Evolution, University of Chicago, 1101 E 57th St, Chicago, United States, 60637-1503, USA
| | - Stefano Allesina
- Department of Ecology & Evolution, University of Chicago, 1101 E 57th St, Chicago, United States, 60637-1503, USA.,Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL, USA
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43
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Tu C, D'Odorico P, Suweis S. Dimensionality reduction of complex dynamical systems. iScience 2021; 24:101912. [PMID: 33364591 PMCID: PMC7753969 DOI: 10.1016/j.isci.2020.101912] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 11/06/2020] [Accepted: 12/03/2020] [Indexed: 11/23/2022] Open
Abstract
One of the outstanding problems in complexity science and engineering is the study of high-dimensional networked systems and of their susceptibility to transitions to undesired states as a result of changes in external drivers or in the structural properties. Because of the incredibly large number of parameters controlling the state of such complex systems and the heterogeneity of its components, the study of their dynamics is extremely difficult. Here we propose an analytical framework for collapsing complex N-dimensional networked systems into an S+1-dimensional manifold as a function of S effective control parameters with S << N. We test our approach on a variety of real-world complex problems showing how this new framework can approximate the system's response to changes and correctly identify the regions in the parameter space corresponding to the system's transitions. Our work offers an analytical method to evaluate optimal strategies in the design or management of networked systems. We analytically collapse N-dimensional networked dynamics in low-dimensional manifolds We test this approach on a variety of real-world complex problems We accurately predict the system's response to changes in parameter values We identify regions in parameter space corresponding to system's critical transitions
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Affiliation(s)
- Chengyi Tu
- School of Ecology and Environmental Science, Yunnan University, 650091, Kunming, China.,Yunnan Key Laboratory of Plant Reproductive Adaptation and Evolutionary Ecology, 650091, Kunming, China.,Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA 94720-3114, USA
| | - Paolo D'Odorico
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA 94720-3114, USA
| | - Samir Suweis
- Department of Physics and Astronomy "G. Galilei", University of Padova, 35131 Padova, Italy
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44
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Medeiros LP, Boege K, Del-Val E, Zaldívar-Riverón A, Saavedra S. Observed Ecological Communities Are Formed by Species Combinations That Are among the Most Likely to Persist under Changing Environments. Am Nat 2021; 197:E17-E29. [PMID: 33417517 DOI: 10.1086/711663] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
AbstractDespite the rich biodiversity found in nature, it is unclear to what extent some combinations of interacting species, while conceivable in a given place and time, may never be realized. Yet solving this problem is important for understanding the role of randomness and predictability in the assembly of ecological communities. Here we show that the specific combinations of interacting species that emerge from the ecological dynamics within regional species pools are not all equally likely to be seen; rather, they are among the most likely to persist under changing environments. First, we use niche-based competition matrices and Lotka-Volterra models to demonstrate that realized combinations of interacting species are more likely to persist under random parameter perturbations than the majority of potential combinations with the same number of species that could have been formed from the regional pool. We then corroborate our theoretical results using a 10-year observational study, recording 88 plant-herbivore communities across three different forest successional stages. By inferring and validating plant-mediated communities of competing herbivore species, we find that observed combinations of herbivores have an expected probability of species persistence higher than half of all potential combinations. Our findings open up the opportunity to establish a formal probabilistic and predictive understanding of the composition of ecological communities.
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45
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Ho HC, Tylianakis JM, Pawar S. Behaviour moderates the impacts of food-web structure on species coexistence. Ecol Lett 2020; 24:298-309. [PMID: 33205909 DOI: 10.1111/ele.13643] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 10/06/2020] [Accepted: 10/07/2020] [Indexed: 11/29/2022]
Abstract
How species coexistence (mathematical 'feasibility') in food webs emerges from species' trophic interactions remains a long-standing open question. Here we investigate how structure (network topology and body-size structure) and behaviour (foraging strategy and spatial dimensionality of interactions) interactively affect feasibility in food webs. Metabolically-constrained modelling of food-web dynamics based on whole-organism consumption revealed that feasibility is promoted in systems dominated by large-eat-small foraging (consumers eating smaller resources) whenever (1) many top consumers are present, (2) grazing or sit-and-wait foraging strategies are common, and (3) species engage in two-dimensional interactions. Congruently, the first two conditions were associated with dominance of large-eat-small foraging in 74 well-resolved (primarily aquatic) real-world food webs. Our findings provide a new, mechanistic understanding of how behavioural properties can modulate the effects of structural properties on species coexistence in food webs, and suggest that 'being feasible' constrains the spectra of behavioural and structural properties seen in natural food webs.
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Affiliation(s)
- Hsi-Cheng Ho
- Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, SL5 7PY, UK
| | - Jason M Tylianakis
- School of Biological Sciences, University of Canterbury, Private Bag 4800, Christchurch, New Zealand
| | - Samraat Pawar
- Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, SL5 7PY, UK
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46
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AlAdwani M, Saavedra S. Ecological models: higher complexity in, higher feasibility out. J R Soc Interface 2020; 17:20200607. [PMID: 33202176 PMCID: PMC7729046 DOI: 10.1098/rsif.2020.0607] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 10/28/2020] [Indexed: 11/12/2022] Open
Abstract
Finding a compromise between tractability and realism has always been at the core of ecological modelling. The introduction of nonlinear functional responses in two-species models has reconciled part of this compromise. However, it remains unclear whether this compromise can be extended to multispecies models. Yet, answering this question is necessary in order to differentiate whether the explanatory power of a model comes from the general form of its polynomial or from a more realistic description of multispecies systems. Here, we study the probability of feasibility (the existence of at least one positive real equilibrium) in complex models by adding higher-order interactions and nonlinear functional responses to the linear Lotka-Volterra model. We characterize complexity by the number of free-equilibrium points generated by a model, which is a function of the polynomial degree and system's dimension. We show that the probability of generating a feasible system in a model is an increasing function of its complexity, regardless of the specific mechanism invoked. Furthermore, we find that the probability of feasibility in a model will exceed that of the linear Lotka-Volterra model when a minimum level of complexity is reached. Importantly, this minimum level is modulated by parameter restrictions, but can always be exceeded via increasing the polynomial degree or system's dimension. Our results reveal that conclusions regarding the relevance of mechanisms embedded in complex models must be evaluated in relation to the expected explanatory power of their polynomial forms.
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Affiliation(s)
| | - Serguei Saavedra
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
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47
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Capitán JA, Cuenda S, Alonso D. Competitive dominance in plant communities: Modeling approaches and theoretical predictions. J Theor Biol 2020; 502:110349. [PMID: 32511978 DOI: 10.1016/j.jtbi.2020.110349] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 05/21/2020] [Accepted: 05/26/2020] [Indexed: 11/27/2022]
Abstract
Quantitative predictions about the processes that promote species coexistence are a subject of active research in ecology. In particular, competitive interactions are known to shape and maintain ecological communities, and situations where some species out-compete or dominate over some others are key to describe natural ecosystems. Here we develop ecological theory using a stochastic, synthetic framework for plant community assembly that leads to predictions amenable to empirical testing. We propose two stochastic, continuous-time Markov models that incorporate competitive dominance through a hierarchy of species heights. The first model, which is spatially implicit, predicts both the expected number of species that survive and the conditions under which heights are clustered in realized model communities. The second one allows spatially-explicit interactions of individuals and alternative mechanisms that can help shorter plants overcome height-driven competition, and it demonstrates that clustering patterns remain, not only locally but also across increasing spatial scales. Moreover, although plants are actually height-clustered in the spatially-explicit model, plant species abundances are not necessarily skewed to taller plants.
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Affiliation(s)
- José A Capitán
- Complex Systems Group. Department of Applied Mathematics, Universidad Politécnica de Madrid, Av. Juan de Herrera, 6, 28040 Madrid, Spain; Theoretical and Computational Ecology Lab, Center for Advanced Studies, Blanes (CEAB-CSIC), C. Accés Cala St. Francesc 14, 17300 Blanes, Spain.
| | - Sara Cuenda
- Universidad Autónoma de Madrid, Facultad de Ciencias Económicas y Empresariales, Depto. Análisis Económico: Economía Cuantitativa, C. Francisco Tomás y Valiente 5, 28049 Madrid, Spain.
| | - David Alonso
- Theoretical and Computational Ecology Lab, Center for Advanced Studies, Blanes (CEAB-CSIC), C. Accés Cala St. Francesc 14, 17300 Blanes, Spain.
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48
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Wilke T, Hauffe T, Jovanovska E, Cvetkoska A, Donders T, Ekschmitt K, Francke A, Lacey JH, Levkov Z, Marshall CR, Neubauer TA, Silvestro D, Stelbrink B, Vogel H, Albrecht C, Holtvoeth J, Krastel S, Leicher N, Leng MJ, Lindhorst K, Masi A, Ognjanova-Rumenova N, Panagiotopoulos K, Reed JM, Sadori L, Tofilovska S, Van Bocxlaer B, Wagner-Cremer F, Wesselingh FP, Wolters V, Zanchetta G, Zhang X, Wagner B. Deep drilling reveals massive shifts in evolutionary dynamics after formation of ancient ecosystem. SCIENCE ADVANCES 2020; 6:eabb2943. [PMID: 32998898 PMCID: PMC7527215 DOI: 10.1126/sciadv.abb2943] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Accepted: 08/17/2020] [Indexed: 05/27/2023]
Abstract
The scarcity of high-resolution empirical data directly tracking diversity over time limits our understanding of speciation and extinction dynamics and the drivers of rate changes. Here, we analyze a continuous species-level fossil record of endemic diatoms from ancient Lake Ohrid, along with environmental and climate indicator time series since lake formation 1.36 million years (Ma) ago. We show that speciation and extinction rates nearly simultaneously decreased in the environmentally dynamic phase after ecosystem formation and stabilized after deep-water conditions established in Lake Ohrid. As the lake deepens, we also see a switch in the macroevolutionary trade-off, resulting in a transition from a volatile assemblage of short-lived endemic species to a stable community of long-lived species. Our results emphasize the importance of the interplay between environmental/climate change, ecosystem stability, and environmental limits to diversity for diversification processes. The study also provides a new understanding of evolutionary dynamics in long-lived ecosystems.
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Affiliation(s)
- Thomas Wilke
- Department of Animal Ecology & Systematics, Justus Liebig University Giessen, Giessen, Germany.
| | - Torsten Hauffe
- Department of Animal Ecology & Systematics, Justus Liebig University Giessen, Giessen, Germany
| | - Elena Jovanovska
- Department of Animal Ecology & Systematics, Justus Liebig University Giessen, Giessen, Germany
- Department of Palaeoanthropology, Senckenberg Research Institute, Frankfurt am Main, Germany
| | - Aleksandra Cvetkoska
- Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, Netherlands
- Palaeoecology, Department of Physical Geography, Utrecht University, Utrecht, Netherlands
| | - Timme Donders
- Palaeoecology, Department of Physical Geography, Utrecht University, Utrecht, Netherlands
| | - Klemens Ekschmitt
- Department of Animal Ecology & Systematics, Justus Liebig University Giessen, Giessen, Germany
| | - Alexander Francke
- School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, NSW, Australia
| | - Jack H Lacey
- National Environmental Isotope Facility, British Geological Survey, Nottingham, UK
| | - Zlatko Levkov
- Institute of Biology, Ss. Cyril and Methodius University, Skopje, North Macedonia
| | - Charles R Marshall
- Department of Integrative Biology and University of California Museum of Paleontology, University of California, Berkeley, Berkeley, CA, USA
| | - Thomas A Neubauer
- Department of Animal Ecology & Systematics, Justus Liebig University Giessen, Giessen, Germany
- Naturalis Biodiversity Center, Darwinweg 2, 2333 CR Leiden, Netherlands
| | - Daniele Silvestro
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- Department of Biology, University of Fribourg (Ch. de Musee 10), 1700 Fribourg, Switzerland
| | - Björn Stelbrink
- Department of Animal Ecology & Systematics, Justus Liebig University Giessen, Giessen, Germany
- Zoological Institute, Department of Environmental Sciences, University of Basel, Basel, Switzerland
| | - Hendrik Vogel
- Institute of Geological Sciences & Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
| | - Christian Albrecht
- Department of Animal Ecology & Systematics, Justus Liebig University Giessen, Giessen, Germany
| | - Jens Holtvoeth
- School of Earth Sciences, University of Bristol, Bristol, UK
- Cambridge University, Conservation Research Institute, 19 Silver Street, Cambridge CB3 9EP, UK
| | - Sebastian Krastel
- Institute of Geosciences, Christian-Albrechts-Universität zu Kiel, Kiel, Germany
| | - Niklas Leicher
- Institute of Geology and Mineralogy, University of Cologne, Cologne, Germany
| | - Melanie J Leng
- National Environmental Isotope Facility, British Geological Survey, Nottingham, UK
- Centre for Environmental Geochemistry, School of Biosciences, University of Nottingham, Nottingham, UK
| | - Katja Lindhorst
- Institute of Geosciences, Christian-Albrechts-Universität zu Kiel, Kiel, Germany
| | - Alessia Masi
- Dipartimento di Biologia Ambientale, Università di Roma "La Sapienza", Rome, Italy
| | | | | | - Jane M Reed
- Department of Geography, Geology and Environment, University of Hull, Hull, UK
| | - Laura Sadori
- Dipartimento di Biologia Ambientale, Università di Roma "La Sapienza", Rome, Italy
| | - Slavica Tofilovska
- Institute of Biology, Ss. Cyril and Methodius University, Skopje, North Macedonia
| | - Bert Van Bocxlaer
- CNRS, Université de Lille, UMR 8198 Evo-Eco-Paleo, Lille, France
- Department of Invertebrate Zoology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20560, USA
| | | | - Frank P Wesselingh
- Naturalis Biodiversity Center, Leiden, Netherlands
- Department of Earth Sciences, Utrecht University, Utrecht, Netherlands
| | - Volkmar Wolters
- Department of Animal Ecology & Systematics, Justus Liebig University Giessen, Giessen, Germany
| | | | - Xiaosen Zhang
- Institute of Loess Plateau, Shanxi University, Taiyuan, China
| | - Bernd Wagner
- Institute of Geology and Mineralogy, University of Cologne, Cologne, Germany
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49
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Saavedra S, Medeiros LP, AlAdwani M. Structural forecasting of species persistence under changing environments. Ecol Lett 2020; 23:1511-1521. [PMID: 32776667 DOI: 10.1111/ele.13582] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 06/07/2020] [Accepted: 07/08/2020] [Indexed: 12/15/2022]
Abstract
The persistence of a species in a given place not only depends on its intrinsic capacity to consume and transform resources into offspring, but also on how changing environmental conditions affect its growth rate. However, the complexity of factors has typically taken us to choose between understanding and predicting the persistence of species. To tackle this limitation, we propose a probabilistic approach rooted on the statistical concepts of ensemble theory applied to statistical mechanics and on the mathematical concepts of structural stability applied to population dynamics models - what we call structural forecasting. We show how this new approach allows us to estimate a probability of persistence for single species in local communities; to understand and interpret this probability conditional on the information we have concerning a system; and to provide out-of-sample predictions of species persistence as good as the best experimental approaches without the need of extensive amounts of data.
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Affiliation(s)
- Serguei Saavedra
- Department of Civil and Environmental Engineering, MIT, 77 Massachusetts Av, 02139, Cambridge, MA, USA
| | - Lucas P Medeiros
- Department of Civil and Environmental Engineering, MIT, 77 Massachusetts Av, 02139, Cambridge, MA, USA
| | - Mohammad AlAdwani
- Department of Civil and Environmental Engineering, MIT, 77 Massachusetts Av, 02139, Cambridge, MA, USA
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50
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Duthie AB. Component response rate variation underlies the stability of highly complex finite systems. Sci Rep 2020; 10:8296. [PMID: 32427891 PMCID: PMC7237446 DOI: 10.1038/s41598-020-64401-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Accepted: 04/15/2020] [Indexed: 11/08/2022] Open
Abstract
The stability of a complex system generally decreases with increasing system size and interconnectivity, a counterintuitive result of widespread importance across the physical, life, and social sciences. Despite recent interest in the relationship between system properties and stability, the effect of variation in response rate across system components remains unconsidered. Here I vary the component response rates (γ) of randomly generated complex systems. I use numerical simulations to show that when component response rates vary, the potential for system stability increases. These results are robust to common network structures, including small-world and scale-free networks, and cascade food webs. Variation in γ is especially important for stability in highly complex systems, in which the probability of stability would otherwise be negligible. At such extremes of simulated system complexity, the largest stable complex systems would be unstable if not for variation in γ. My results therefore reveal a previously unconsidered aspect of system stability that is likely to be pervasive across all realistic complex systems.
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Affiliation(s)
- A Bradley Duthie
- Biological and Environmental Sciences, University of Stirling, Stirling, FK9 4LA, UK.
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