Trait-based frameworks are increasingly used for predicting how ecological communities respond to ongoing global change. As species range shifts result in novel encounters between predators and prey, identifying prey ‘guilds’, based on a suite of shared traits, can distill complex species interactions, and aid in predicting food web dynamics. To support advances in trait-based research in open-ocean systems, we present the Pelagic Species Trait Database, an extensive resource documenting functional traits of 529 pelagic fish and invertebrate species in a single, open-source repository. We synthesized literature sources and online resources, conducted morphometric analysis of species images, as well as laboratory analyses of trawl-captured specimens to collate traits describing 1) habitat use and behavior, 2) morphology, 3) nutritional quality, and 4) population status information. Species in the dataset primarily inhabit the California Current system and broader NE Pacific Ocean, but also includes pelagic species known to be consumed by top ocean predators from other ocean basins. The aim of this dataset is to enhance the use of trait-based approaches in marine ecosystems and for predator populations worldwide.
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Summary Coral‐associated microorganisms are thought to play a fundamental role in the health and ecology of corals, but understanding of specific coral–microbial interactions are lacking. In order to create a framework to examine coral–microbial specificity, we integrated and phylogenetically compared 21,100 SSU rRNA gene Sanger‐produced sequences from bacteria and archaea associated with corals from previous studies, and accompanying host, location and publication metadata, to produce the Coral Microbiome Database. From this database, we identified 39 described and candidate phyla of Bacteria and two Archaea phyla associated with corals, demonstrating that corals are one of the most phylogenetically diverse animal microbiomes. Secondly, this new phylogenetic resource shows that certain microorganisms are indeed specific to corals, including evolutionary distinct hosts. Specifically, we identified 2–37 putative monophyletic, coral‐specific sequence clusters within bacterial genera associated with the greatest number of coral species (
Vibrio ,Endozoicomonas andRuegeria ) as well as functionally relevant microbial taxa (“Candidatus Amoebophilus”, “Candidatus Nitrosopumilus” and under recognized cyanobacteria). This phylogenetic resource provides a framework for more targeted studies of corals and their specific microbial associates, which is timely given the escalated need to understand the role of the coral microbiome and its adaptability to changing ocean and reef conditions. -
Abstract We introduce the FunAndes database, a compilation of functional trait data for the Andean flora spanning six countries. FunAndes contains data on 24 traits across 2,694 taxa, for a total of 105,466 entries. The database features plant-morphological attributes including growth form, and leaf, stem, and wood traits measured at the species or individual level, together with geographic metadata (i.e., coordinates and elevation). FunAndes follows the field names, trait descriptions and units of measurement of the TRY database. It is currently available in open access in the FIGSHARE data repository, and will be part of TRY’s next release. Open access trait data from Andean plants will contribute to ecological research in the region, the most species rich terrestrial biodiversity hotspot.more » « less
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null (Ed.)Abstract Background Even when microbial communities vary wildly in their taxonomic composition, their functional composition is often surprisingly stable. This suggests that a functional perspective could provide much deeper insight into the principles governing microbiome assembly. Much work to date analyzing the functional composition of microbial communities, however, relies heavily on inference from genomic features. Unfortunately, output from these methods can be hard to interpret and often suffers from relatively high error rates. Results We built and analyzed a domain-specific microbial trait database from known microbe-trait pairs recorded in the literature to better understand the functional composition of the human microbiome. Using a combination of phylogentically conscious machine learning tools and a network science approach, we were able to link particular traits to areas of the human body, discover traits that determine the range of body areas a microbe can inhabit, and uncover drivers of metabolic breadth. Conclusions Domain-specific trait databases are an effective compromise between noisy methods to infer complex traits from genomic data and exhaustive, expensive attempts at database curation from the literature that do not focus on any one subset of taxa. They provide an accurate account of microbial traits and, by limiting the number of taxa considered, are feasible to build within a reasonable time-frame. We present a database specific for the human microbiome, in the hopes that this will prove useful for research into the functional composition of human-associated microbial communities.more » « less
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1038/sdata.2017.174
