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      Microbial symbionts and ecological divergence of Caribbean sponges: A new perspective on an ancient association

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          Abstract

          Marine sponges host diverse communities of microbial symbionts that expand the metabolic capabilities of their host, but the abundance and structure of these communities is highly variable across sponge species. Specificity in these interactions may fuel host niche partitioning on crowded coral reefs by allowing individual sponge species to exploit unique sources of carbon and nitrogen, but this hypothesis is yet to be tested. Given the presence of high sponge biomass and the coexistence of diverse sponge species, the Caribbean Sea provides a unique system in which to investigate this hypothesis. To test for ecological divergence among sympatric Caribbean sponges and investigate whether these trends are mediated by microbial symbionts, we measured stable isotope ( δ 13C and δ 15N) ratios and characterized the microbial community structure of sponge species at sites within four regions spanning a 1700 km latitudinal gradient. There was a low (median of 8.2 %) overlap in the isotopic niches of sympatric species; in addition, host identity accounted for over 75% of the dissimilarity in both δ 13C and δ 15N values and microbiome community structure among individual samples within a site. There was also a strong phylogenetic signal in both δ 15N values and microbial community diversity across host phylogeny, as well as a correlation between microbial community structure and variation in δ 13C and δ 15N values across samples. Together, this evidence supports a hypothesis of strong evolutionary selection for ecological divergence across sponge lineages and suggests that this divergence is at least partially mediated by associations with microbial symbionts.

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          Diversity in tropical rain forests and coral reefs.

          The commonly observed high diversity of trees in tropical rain forests and corals on tropical reefs is a nonequilibrium state which, if not disturbed further, will progress toward a low-diversity equilibrium community. This may not happen if gradual changes in climate favor different species. If equilibrium is reached, a lesser degree of diversity may be sustained by niche diversification or by a compensatory mortality that favors inferior competitors. However, tropical forests and reefs are subject to severe disturbances often enough that equilibrium may never be attained.
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            Testing for phylogenetic signal in comparative data: behavioral traits are more labile.

            The primary rationale for the use of phylogenetically based statistical methods is that phylogenetic signal, the tendency for related species to resemble each other, is ubiquitous. Whether this assertion is true for a given trait in a given lineage is an empirical question, but general tools for detecting and quantifying phylogenetic signal are inadequately developed. We present new methods for continuous-valued characters that can be implemented with either phylogenetically independent contrasts or generalized least-squares models. First, a simple randomization procedure allows one to test the null hypothesis of no pattern of similarity among relatives. The test demonstrates correct Type I error rate at a nominal alpha = 0.05 and good power (0.8) for simulated datasets with 20 or more species. Second, we derive a descriptive statistic, K, which allows valid comparisons of the amount of phylogenetic signal across traits and trees. Third, we provide two biologically motivated branch-length transformations, one based on the Ornstein-Uhlenbeck (OU) model of stabilizing selection, the other based on a new model in which character evolution can accelerate or decelerate (ACDC) in rate (e.g., as may occur during or after an adaptive radiation). Maximum likelihood estimation of the OU (d) and ACDC (g) parameters can serve as tests for phylogenetic signal because an estimate of d or g near zero implies that a phylogeny with little hierarchical structure (a star) offers a good fit to the data. Transformations that improve the fit of a tree to comparative data will increase power to detect phylogenetic signal and may also be preferable for further comparative analyses, such as of correlated character evolution. Application of the methods to data from the literature revealed that, for trees with 20 or more species, 92% of traits exhibited significant phylogenetic signal (randomization test), including behavioral and ecological ones that are thought to be relatively evolutionarily malleable (e.g., highly adaptive) and/or subject to relatively strong environmental (nongenetic) effects or high levels of measurement error. Irrespective of sample size, most traits (but not body size, on average) showed less signal than expected given the topology, branch lengths, and a Brownian motion model of evolution (i.e., K was less than one), which may be attributed to adaptation and/or measurement error in the broad sense (including errors in estimates of phenotypes, branch lengths, and topology). Analysis of variance of log K for all 121 traits (from 35 trees) indicated that behavioral traits exhibit lower signal than body size, morphological, life-history, or physiological traits. In addition, physiological traits (corrected for body size) showed less signal than did body size itself. For trees with 20 or more species, the estimated OU (25% of traits) and/or ACDC (40%) transformation parameter differed significantly from both zero and unity, indicating that a hierarchical tree with less (or occasionally more) structure than the original better fit the data and so could be preferred for comparative analyses.
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              Diversity, structure and convergent evolution of the global sponge microbiome

              Sponges (phylum Porifera) are early-diverging metazoa renowned for establishing complex microbial symbioses. Here we present a global Porifera microbiome survey, set out to establish the ecological and evolutionary drivers of these host–microbe interactions. We show that sponges are a reservoir of exceptional microbial diversity and major contributors to the total microbial diversity of the world's oceans. Little commonality in species composition or structure is evident across the phylum, although symbiont communities are characterized by specialists and generalists rather than opportunists. Core sponge microbiomes are stable and characterized by generalist symbionts exhibiting amensal and/or commensal interactions. Symbionts that are phylogenetically unique to sponges do not disproportionally contribute to the core microbiome, and host phylogeny impacts complexity rather than composition of the symbiont community. Our findings support a model of independent assembly and evolution in symbiont communities across the entire host phylum, with convergent forces resulting in analogous community organization and interactions.
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                Author and article information

                Contributors
                freemancj@cofc.edu
                Journal
                ISME J
                ISME J
                The ISME Journal
                Nature Publishing Group UK (London )
                1751-7362
                1751-7370
                20 March 2020
                20 March 2020
                June 2020
                : 14
                : 6
                : 1571-1583
                Affiliations
                [1 ]ISNI 0000 0001 0479 0204, GRID grid.452909.3, Smithsonian Marine Station, ; Fort Pierce, FL USA
                [2 ]ISNI 0000 0004 1936 7769, GRID grid.254424.1, Department of Biology, , College of Charleston, ; Charleston, SC USA
                [3 ]ISNI 0000 0001 2168 8324, GRID grid.261241.2, Halmos College of Natural Sciences and Oceanography, , Nova Southeastern University, ; Dania Beach, FL USA
                [4 ]ISNI 0000 0001 2111 6385, GRID grid.260001.5, Biology Department, , Middle Tennessee State University, ; Murfreesboro, TN USA
                [5 ]ISNI 0000000106344187, GRID grid.265892.2, Department of Biology, , University of Alabama at Birmingham, ; Birmingham, AL USA
                [6 ]ISNI 0000 0001 2192 7591, GRID grid.453560.1, Smithsonian Institution, National Museum of Natural History, ; Washington, DC USA
                [7 ]ISNI 0000 0001 2216 9681, GRID grid.36425.36, Department of Ecology and Evolution, , Stony Brook University, ; Stony Brook, NY USA
                [8 ]ISNI 0000 0001 2296 9689, GRID grid.438006.9, Smithsonian Tropical Research Institute, ; Box 0843-03092, Balboa, Republic of Panama
                [9 ]ISNI 0000000121742757, GRID grid.194645.b, The Swire Institute of Marine Science, School of Biological Sciences, , University of Hong Kong, ; Hong Kong, PR China
                Author information
                http://orcid.org/0000-0002-9654-0073
                http://orcid.org/0000-0002-0308-4954
                Article
                625
                10.1038/s41396-020-0625-3
                7242429
                32203120
                776bba2a-35af-4708-afff-6c9184e84f1f
                © The Author(s) 2020

                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
                : 25 June 2019
                : 17 February 2020
                : 25 February 2020
                Categories
                Article
                Custom metadata
                © International Society for Microbial Ecology 2020

                Microbiology & Virology
                microbial ecology,stable isotope analysis
                Microbiology & Virology
                microbial ecology, stable isotope analysis

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