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Steven W. Kembel

Researcher at Université du Québec à Montréal

Publications -  103
Citations -  15892

Steven W. Kembel is an academic researcher from Université du Québec à Montréal. The author has contributed to research in topics: Phyllosphere & Phylogenetic tree. The author has an hindex of 40, co-authored 88 publications receiving 13094 citations. Previous affiliations of Steven W. Kembel include University of Oregon & University of Alberta.

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Drivers of phyllosphere microbial functional diversity in a neotropical forest

TL;DR: Functional profiling based on metagenomic shotgun sequencing offers evidence for the presence of a core functional microbiome across phyllosphere communities of neotropical trees and suggests that there is adaptive matching between phyllospheric microbes and their plant hosts.
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The Gut Microbiome of the Eastern Spruce Budworm Does Not Influence Larval Growth or Survival

TL;DR: In this paper, the authors studied the effects of the gut microbial community on the growth and survival of the eastern spruce budworm Choristoneura fumiferana, an economically important lepidopteran forest pest in eastern Canada and the northeastern United States.
Posted ContentDOI

Links between mouse and vole social networks and their gut microbiomes support predictions from metacommunity theory

TL;DR: GM composition associated with interspecific social proximity, and mouse GM diversity correlated with number of vole neighbours, and contributions of host-host bacterial transmission to the GM partly follow metacommunity theory but depend on host species.
Posted ContentDOI

Fine-scale adaptations to environmental variation and growth strategies drive phyllosphere methylobacterium diversity.

TL;DR: In this article, the authors investigated how phylogenetic diversity within the genus Methylobacterium is structured by biogeography, seasonality, and growth strategies using deep, culture-independent barcoded marker gene sequencing coupled with culture-based approaches.
Journal ArticleDOI

Transfer index, NetUniFrac and some useful shortest path-based distances for community analysis in sequence similarity networks.

TL;DR: The shortest path concept can be extended to sequence similarity networks by defining five new distances, NetUniFrac, Spp, Spep, Spelp and Spinp, and the Transfer index, between species communities present in the network, and it is shown how these new measures can be used to analyze microbiota and antibiotic resistance gene similarity networks.