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      Principles of seed banks and the emergence of complexity from dormancy

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          Abstract

          Across the tree of life, populations have evolved the capacity to contend with suboptimal conditions by engaging in dormancy, whereby individuals enter a reversible state of reduced metabolic activity. The resulting seed banks are complex, storing information and imparting memory that gives rise to multi-scale structures and networks spanning collections of cells to entire ecosystems. We outline the fundamental attributes and emergent phenomena associated with dormancy and seed banks, with the vision for a unifying and mathematically based framework that can address problems in the life sciences, ranging from global change to cancer biology.

          Abstract

          Seed banks are generated when individuals enter a dormant state, a phenomenon that has evolved among diverse taxa, but that is also found in stem cells, brains, and tumors. Here, Lennon et al. synthesize the fundamentals of seed-bank theory and the emergence of complex patterns and dynamics in mathematics and the life sciences.

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          Most cited references148

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          A network theory of mental disorders.

          In recent years, the network approach to psychopathology has been advanced as an alternative way of conceptualizing mental disorders. In this approach, mental disorders arise from direct interactions between symptoms. Although the network approach has led to many novel methodologies and substantive applications, it has not yet been fully articulated as a scientific theory of mental disorders. The present paper aims to develop such a theory, by postulating a limited set of theoretical principles regarding the structure and dynamics of symptom networks. At the heart of the theory lies the notion that symptoms of psychopathology are causally connected through myriads of biological, psychological and societal mechanisms. If these causal relations are sufficiently strong, symptoms can generate a level of feedback that renders them self-sustaining. In this case, the network can get stuck in a disorder state. The network theory holds that this is a general feature of mental disorders, which can therefore be understood as alternative stable states of strongly connected symptom networks. This idea naturally leads to a comprehensive model of psychopathology, encompassing a common explanatory model for mental disorders, as well as novel definitions of associated concepts such as mental health, resilience, vulnerability and liability. In addition, the network theory has direct implications for how to understand diagnosis and treatment, and suggests a clear agenda for future research in psychiatry and associated disciplines.
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            Phenotypic diversity, population growth, and information in fluctuating environments.

            Organisms in fluctuating environments must constantly adapt their behavior to survive. In clonal populations, this may be achieved through sensing followed by response or through the generation of diversity by stochastic phenotype switching. Here we show that stochastic switching can be favored over sensing when the environment changes infrequently. The optimal switching rates then mimic the statistics of environmental changes. We derive a relation between the long-term growth rate of the organism and the information available about its fluctuating environment.
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              The sampling theory of selectively neutral alleles.

              W.J. Ewens (1972)
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                Author and article information

                Contributors
                lennonj@indiana.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                10 August 2021
                10 August 2021
                2021
                : 12
                : 4807
                Affiliations
                [1 ]GRID grid.411377.7, ISNI 0000 0001 0790 959X, Indiana University, Department of Biology, ; Bloomington, USA
                [2 ]GRID grid.5132.5, ISNI 0000 0001 2312 1970, Universiteit Leiden, Mathematical Institute, ; Leiden, Netherlands
                [3 ]GRID grid.7468.d, ISNI 0000 0001 2248 7639, Humboldt-Universität zu Berlin, Institute of Mathematics, ; Berlin, Germany
                [4 ]GRID grid.6734.6, ISNI 0000 0001 2292 8254, Technische Universität Berlin, Institute of Mathematics, ; Berlin, Germany
                Author information
                http://orcid.org/0000-0003-3126-6111
                http://orcid.org/0000-0003-2866-9470
                Article
                24733
                10.1038/s41467-021-24733-1
                8355185
                34376641
                a57b11ff-9011-4c00-afa6-43d44f9ad4bb
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 July 2020
                : 2 July 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000104, National Aeronautics and Space Administration (NASA);
                Award ID: 80NSSC20K0618
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft (German Research Foundation);
                Award ID: DFG SPP 1590
                Award Recipient :
                Categories
                Review Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                biodiversity,theoretical ecology,evolutionary theory,applied mathematics
                Uncategorized
                biodiversity, theoretical ecology, evolutionary theory, applied mathematics

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