3.8 Article

Multivariate trait analysis reveals diatom plasticity constrained to a reduced set of biological axes

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ISME COMMUNICATIONS
卷 1, 期 1, 页码 -

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SPRINGERNATURE
DOI: 10.1038/s43705-021-00062-8

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  1. Gordon and Betty Moore Foundation Marine Microbes Initiative [MMI 7397]

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Trait-based approaches have become popular in phytoplankton ecology, with this study demonstrating that phenotypic diversity within the marine diatom genus Thalassiosira cannot be predicted from genotypic diversity. Plasticity can lead to highly divergent phenotypes, represented by multivariate phenotypes in a reduced dimensional space termed as a 'trait-scape'. Understanding trait-scapes can reveal common constraints on multi-trait plasticity in phytoplankton and will be critical in predicting microbial responses to environmental change.
Trait-based approaches to phytoplankton ecology have gained traction in recent decades as phenotypic traits are incorporated into ecological and biogeochemical models. Here, we use high-throughput phenotyping to explore both intra- and interspecific constraints on trait combinations that are expressed in the cosmopolitan marine diatom genus Thalassiosira. We demonstrate that within Thalassiosira, phenotypic diversity cannot be predicted from genotypic diversity, and moreover, plasticity can create highly divergent phenotypes that are incongruent with taxonomic grouping. Significantly, multivariate phenotypes can be represented in reduced dimensional space using principal component analysis with 77.7% of the variance captured by two orthogonal axes, here termed a 'trait-scape'. Furthermore, this trait-scape can be recovered with a reduced set of traits. Plastic responses to the new environments expanded phenotypic trait values and the trait-scape, however, the overall pattern of response to the new environments was similar between strains and many trait correlations remained constant. These findings demonstrate that trait-scapes can be used to reveal common constraints on multi-trait plasticity in phytoplankton with divergent underlying phenotypes. Understanding how to integrate trait correlational constraints and trade-offs into theoretical frameworks like biogeochemical models will be critical to predict how microbial responses to environmental change will impact elemental cycling now and into the future.

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