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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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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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4
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Deng J, Taylor W, Levin SA, Saavedra S. On the limits to invasion prediction using coexistence outcomes. J Theor Biol 2024; 577:111674. [PMID: 38008157 DOI: 10.1016/j.jtbi.2023.111674] [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: 04/20/2023] [Revised: 11/01/2023] [Accepted: 11/14/2023] [Indexed: 11/28/2023]
Abstract
The dynamics of ecological communities in nature are typically characterized by probabilistic processes involving invasion dynamics. Because of technical challenges, however, the majority of theoretical and experimental studies have focused on coexistence dynamics. Therefore, it has become central to understand the extent to which coexistence outcomes can be used to predict analogous invasion outcomes relevant to systems in nature. Here, we study the limits to this predictability under a geometric and probabilistic Lotka-Volterra framework. We show that while individual survival probability in coexistence dynamics can be fairly closely translated into invader colonization probability in invasion dynamics, the translation is less precise between community persistence and community augmentation, and worse between exclusion probability and replacement probability. These results provide a guiding and testable theoretical framework regarding the translatability of outcomes between coexistence and invasion outcomes when communities are represented by Lotka-Volterra dynamics under environmental uncertainty.
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Affiliation(s)
- Jie Deng
- Department of Civil and Environmental Engineering, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
| | - Washington Taylor
- Center for Theoretical Physics, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Simon A Levin
- Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA; High Meadows Environmental Institute, Princeton University, Princeton, NJ 08544, USA
| | - Serguei Saavedra
- Department of Civil and Environmental Engineering, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139, USA; Santa Fe Institute, 1399 Hyde Park Rd, Santa Fe, NM 87501, USA
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5
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Flores-Arguedas H, Antolin-Camarena O, Saavedra S, Angulo MT. Assembly archetypes in ecological communities. J R Soc Interface 2023; 20:20230349. [PMID: 38016640 PMCID: PMC10684342 DOI: 10.1098/rsif.2023.0349] [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: 06/20/2023] [Accepted: 11/03/2023] [Indexed: 11/30/2023] Open
Abstract
An instrumental discovery in comparative and developmental biology is the existence of assembly archetypes that synthesize the vast diversity of organisms' body plans-from legs and wings to human arms-into simple, interpretable and general design principles. Here, we combine a novel mathematical formalism based on category theory with experimental data to show that similar 'assembly archetypes' exist at the larger organization scale of ecological communities when assembling a species pool across diverse environmental contexts, particularly when species interactions are highly structured. We applied our formalism to clinical data discovering two assembly archetypes that differentiate between healthy and unhealthy human gut microbiota. The concept of assembly archetypes and the methods to synthesize them can pave the way to discovering the general assembly principles of the ecological communities we observe in nature.
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Affiliation(s)
- Hugo Flores-Arguedas
- Institute of Mathematics, Universidad Nacional Autónoma de México, Juriquilla, Queretaro, Mexico
| | - Omar Antolin-Camarena
- Institute of Mathematics, Universidad Nacional Autónoma de México, Ciudad Universitaria, Mexico City, Mexico
| | - 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
| | - Marco Tulio Angulo
- Institute of Mathematics, Universidad Nacional Autónoma de México, Juriquilla, Queretaro, Mexico
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6
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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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7
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Deng J, Taylor W, Saavedra S. Understanding the impact of third-party species on pairwise coexistence. PLoS Comput Biol 2022; 18:e1010630. [PMID: 36279302 PMCID: PMC9632822 DOI: 10.1371/journal.pcbi.1010630] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 11/03/2022] [Accepted: 10/03/2022] [Indexed: 11/06/2022] Open
Abstract
The persistence of virtually every single species depends on both the presence of other species and the specific environmental conditions in a given location. Because in natural settings many of these conditions are unknown, research has been centered on finding the fraction of possible conditions (probability) leading to species coexistence. The focus has been on the persistence probability of an entire multispecies community (formed of either two or more species). However, the methodological and philosophical question has always been whether we can observe the entire community and, if not, what the conditions are under which an observed subset of the community can persist as part of a larger multispecies system. Here, we derive long-term (using analytical calculations) and short-term (using simulations and experimental data) system-level indicators of the effect of third-party species on the coexistence probability of a pair (or subset) of species under unknown environmental conditions. We demonstrate that the fraction of conditions incompatible with the possible coexistence of a pair of species tends to become vanishingly small within systems of increasing numbers of species. Yet, the probability of pairwise coexistence in isolation remains approximately the expected probability of pairwise coexistence in more diverse assemblages. In addition, we found that when third-party species tend to reduce (resp. increase) the coexistence probability of a pair, they tend to exhibit slower (resp. faster) rates of competitive exclusion. Long-term and short-term effects of the remaining third-party species on all possible specific pairs in a system are not equally distributed, but these differences can be mapped and anticipated under environmental uncertainty.
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Affiliation(s)
- Jie Deng
- Department of Civil and Environmental Engineering, MIT, Cambridge, Massachusetts, United States of America
| | - Washington Taylor
- Center for Theoretical Physics, MIT, Cambridge, Cambridge, Massachusetts, United States of America
| | - Serguei Saavedra
- Department of Civil and Environmental Engineering, MIT, Cambridge, Massachusetts, United States of America
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8
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Pereira AJ, Masciocchi M, Corley JC. Long-term coexistence of two invasive vespid wasps in NW Patagonia (Argentina). Oecologia 2022; 199:661-669. [PMID: 35781744 DOI: 10.1007/s00442-022-05210-y] [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: 10/26/2021] [Accepted: 06/14/2022] [Indexed: 10/17/2022]
Abstract
In Patagonia (Argentina) two non-native vespid wasps became established in the last decades. Vespula germanica was first detected in 1980, while V. vulgaris arrived some 30 years later. Both species can have a strong negative impact on agro-industrial economic activities, the natural environment, and outdoor human activities. Biological invasions may be influenced negatively by the degree of interaction with the resident native community and alien species already present. The sequential arrival and coexistence of Vespula wasps in Argentina for several years allows us to understand key questions of invasion ecology. Additionally, recognizing the outcome of the invasion by vespids in Patagonia, a region lacking native social wasps, may help plan species-focused mitigation and control strategies. We explored the role of competition in terms of invasion success, and the strategies that promote coexistence. Two possible scenarios, using niche overlap indices and isocline equations, were proposed to determine competition coefficients. Using a simple mathematical modeling framework, based on field collected data, we show that food resources do not play a central role in competitive interaction. The competition coefficients obtained from the equations were different from those inferred from the overlap indices (0.53 and 0.54-0.076 and 0.197, respectively). Together, these findings suggest that no matter the arrival order, V. vulgaris, always reaches higher densities than V. germanica when both species invade new regions. Our work contributes to further our understanding on the worldwide invasion processes deployed by these two eusocial insects.
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Affiliation(s)
- Ana Julia Pereira
- Centro de Investigaciones en Toxicología Ambiental y Agrobiotecnología del Comahue, CITAAC (CONICET, UNCo), Neuquén, Argentina.
| | - Maité Masciocchi
- Grupo de Ecología de Poblaciones de Insectos, IFAB (CONICET, INTA EEA Bariloche), Bariloche, Argentina
| | - Juan C Corley
- Grupo de Ecología de Poblaciones de Insectos, IFAB (CONICET, INTA EEA Bariloche), Bariloche, Argentina.,Departamento de Ecología, Centro Regional Universitario Bariloche, Universidad Nacional del Comahue, Bariloche, Argentina
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9
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Saavedra S, Bartomeus I, Godoy O, Rohr RP, Zu P. Towards a system-level causative knowledge of pollinator communities. Philos Trans R Soc Lond B Biol Sci 2022; 377:20210159. [PMID: 35491588 PMCID: PMC9058529 DOI: 10.1098/rstb.2021.0159] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 02/14/2022] [Indexed: 12/27/2022] Open
Abstract
Pollination plays a central role in both crop production and maintaining biodiversity. However, habitat loss, pesticides, invasive species and larger environmental fluctuations are contributing to a dramatic decline of pollinators worldwide. Different management solutions require knowledge of how ecological communities will respond following interventions. Yet, anticipating the response of these systems to interventions remains extremely challenging due to the unpredictable nature of ecological communities, whose nonlinear behaviour depends on the specific details of species interactions and the various unknown or unmeasured confounding factors. Here, we propose that this knowledge can be derived by following a probabilistic systems analysis rooted on non-parametric causal inference. The main outcome of this analysis is to estimate the extent to which a hypothesized cause can increase or decrease the probability that a given effect happens without making assumptions about the form of the cause-effect relationship. We discuss a road map for how this analysis can be accomplished with the aim of increasing our system-level causative knowledge of natural communities. This article is part of the theme issue 'Natural processes influencing pollinator health: from chemistry to landscapes'.
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Affiliation(s)
- Serguei Saavedra
- Department of Civil and Environmental Engineering, MIT, 77 Massachusetts Av., Cambridge, MA 02139, USA
| | - Ignasi Bartomeus
- Estación Biológica de Doñana (EBD-CSIC), 41092, Isla de la Cartuja, Seville, Spain
| | - Oscar Godoy
- Departamento de Biología, Instituto Universitario de Ciencias del Mar (INMAR), Universidad de Cádiz, Royal Port E-11510, Spain
| | - Rudolf P. Rohr
- Department of Biology - Ecology and Evolution, University of Fribourg, Chemin du Musée 10, Fribourg CH-1700, Switzerland
| | - Penguan Zu
- Department of Environmental Systems Science, ETH Zurich, Schmelzbergstrasse 9, Zurich CH-8092, Switzerland
- Department Fish Ecology and Evolution, Swiss Federal Institute of Aquatic Science and Technology (Eawag), Seestrasse 79, Kastanienbaum CH-6047, Switzerland
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10
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AlAdwani M, Saavedra S. Feasibility conditions of ecological models: Unfolding links between model parameters. Ecol Modell 2022. [DOI: 10.1016/j.ecolmodel.2022.109900] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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11
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Song C, Fukami T, Saavedra S. Untangling the complexity of priority effects in multispecies communities. Ecol Lett 2021; 24:2301-2313. [PMID: 34472694 DOI: 10.1111/ele.13870] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 05/23/2021] [Accepted: 08/09/2021] [Indexed: 11/28/2022]
Abstract
The history of species immigration can dictate how species interact in local communities, thereby causing historical contingency in community assembly. Since immigration history is rarely known, these historical influences, or priority effects, pose a major challenge in predicting community assembly. Here, we provide a graph-based, non-parametric, theoretical framework for understanding the predictability of community assembly as affected by priority effects. To develop this framework, we first show that the diversity of possible priority effects increases super-exponentially with the number of species. We then point out that, despite this diversity, the consequences of priority effects for multispecies communities can be classified into four basic types, each of which reduces community predictability: alternative stable states, alternative transient paths, compositional cycles and the lack of escapes from compositional cycles to stable states. Using a neural network, we show that this classification of priority effects enables accurate explanation of community predictability, particularly when each species immigrates repeatedly. We also demonstrate the empirical utility of our theoretical framework by applying it to two experimentally derived assembly graphs of algal and ciliate communities. Based on these analyses, we discuss how the framework proposed here can help guide experimental investigation of the predictability of history-dependent community assembly.
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Affiliation(s)
- Chuliang Song
- Department of Civil and Environmental Engineering, MIT, Cambridge, MA, USA.,Department of Biology, McGill University, Montreal, Canada.,Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada
| | - Tadashi Fukami
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Serguei Saavedra
- Department of Civil and Environmental Engineering, MIT, Cambridge, MA, USA
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