Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Data Files
• Related Publications
• Related Datasets
• Parameters
• Deployments
• Project Information
• Funding

These data were included as Supplemental Data Table 2 in the results publication Dykman et al. (2021) Ecology.  Version 1 of the code used for analyses, statistics, and figures for Dykman et al. (2021) Ecology can be found at Zenodo (Dykman, 2021, DOI: 10.5281/zenodo.4625160).

Location: 9° 50’N on the East Pacific Rise, depth 2500m.

Functional traits were gathered for fifty-eight invertebrate species or higher taxa (when species ID was uncertain) collected from settlement surfaces deployed at deep-sea hydrothermal vents (https://doi.org/10.26008/1912/bco-dmo.733173.2). The identifier columns “scientificNameID” and “AphiaID” in this trait dataset are standardized to World Register of Marine Species (WoRMS), and are an exact subset of the of the same columns in the dataset of colonists from experimental settlement surfaces. Species names are in some cases generic and are not standardized to WoRMS.

Eight traits were chosen to test ecological hypotheses relevant to recovery and succession at deep-sea hydrothermal vents. We define “trait” as a feature or behavior of a species that affects or responds to its environment, and “modality” as a scoring level reflecting how the organism expresses a given trait. Four traits were taken from the sFDvent Database: maximum adult body size, habitat complexity, trophic mode (i.e., trophic level), and relative adult mobility. Four additional traits were added due to their ecological relevance and common use in functional analyses for aquatic invertebrates. These are external protection, feeding method (i.e., how a species feeds), reproductive type, and larval development (Bolam et al. 2016, Greenfield et al. 2016, Veríssimo et al. 2017). For each trait, a modality was assigned for every species based on literature or personal observation. For the traits from sFDvent, modalities were assigned from the recommended data set, except in cases where we suggested updates (Dykman et al., 2021). When species identity was uncertain and individuals were identified to a higher taxonomic level (e.g., amphipods), modalities were assigned from a likely species that is found at our site and included in sFDvent. For the four traits not included in sFDvent, we either provided a citation or cited “expert opinion,” meaning the modality choice was based on direct observation by one of the co-authors. Although the majority of specimens in our study were juveniles, most modality assignments were based on the characteristics of adult organisms due to the availability of data. Modality assignments were fixed for a given species rather than specific to life stages or individuals.

For the column “FUNCTIONAL_GUILD,” species were clustered into guilds based on the similarity of their modalities for all eight traits. The pairwise dissimilarity of species was calculated using the function gowdis in the R package FD (Laliberté et al. 2015). We chose Gower dissimilarity because it accepts both numerical and categorical data and handles missing values (Gower 1971). Podani’s extension was implemented to include ordinal variables (Podani 1999). Clusters were computed from the Gower dissimilarity matrix using the hclust function in the R package cluster (Maechler 2018) and plotted as a dendrogram. The cutoff for assigning functional guilds was chosen by optimizing the tradeoff between minimizing within-group distance and maximizing between-group distance. Code for this and all subsequent analyses are available at Zenodo (Dykman, 2021, DOI: 10.5281/zenodo.4625160).

This data set includes traits and modalities that were gathered from literature and existing databases. The column Functional Guild was generated by hierarchical clustering in R using the function gowdis in the package FD as described in Dykman et al. (2021). Scripts to run these analyses are available at Zenodo (Dykman, 2021, DOI: 10.5281/zenodo.4625160).

BCO-DMO data manager processing notes:
* Data submitted to BCO-DMO in file DataS2_BCO-DMO_Dykman.csv which had missing values as "NA" imported into the BCO-DMO data system.  When this data table is served the missing data identifier will vary depending upon the data format. For example, Matlab files will use NaN.  References to NA values in the metadata changed to refer instead to null values (no value).
* Could not find a 2006 Edition of Barnes et al. with the title "The Invertebrates: A new synthesis" which the submitter indicated came from http://www.marinespecies.org/introduced/wiki/Traits:Multivoltine.   This dataset references Barnes et al. (2006) but the reference list associated with this dataset has the information for the edition I was able to find is for "The Invertebrates: A synthesis" in 2007 (ISBN: 9780632047611).  The reference in the reference list does show 2006 though it may in fact be the 2007 edition.

NSF Award Abstract:
Hydrothermal vents support oases of life in the deep sea and are inhabited by unusual organisms that use chemical energy instead of photosynthesis as the basis of their food web. However, because the vents occur in geologically active areas of the seafloor, entire communities can be eradicated by catastrophic natural disturbances such as eruptions. The main objectives of this project are to quantify how quickly these communities recover from catastrophic disturbance and to determine what processes influence their resilience. The project focuses on both the structure (species diversity) and function (trait diversity) of the communities. The investigators will examine vents on an active segment of the East Pacific Rise where eruptive disturbance occurs on decadal time scales. These activities will create an unprecedented long-term (>14-year) quantitative time-series of colonist species composition and function. The application of trait-based analysis to the question of biological succession at vents has the potential to change the way we think about resilience in other patchy, transient and regionally-connected ecosystems. By considering how traits change over time, the researchers can untangle which species-level characteristics most influence abundance and distribution. The project objectives have broad significance with the growing potential for human-caused disturbances at deep-sea vents through deep-sea mining. Additional impacts include strengthening participation of under-represented minorities in marine science and contributing to international database development for functional traits of deep-sea vent species.

The unique, chemosynthesis-fueled fauna inhabiting deep-sea hydrothermal vents are subject to tectonic and eruptive disturbance that can eradicate entire communities. The main objectives of this project are to quantify how quickly these communities recover from catastrophic disturbance and to determine what processes influence their resilience. The focus is on vents on an active segment of the East Pacific Rise where eruptive disturbance occurs on decadal time scales. Field data on colonization and larval supply are used to characterize not only species succession but also the trajectory of functional diversity after a recent (2006) eruption. A new, promising approach to the colonization studies comes from incorporating trait-based analysis of functional diversity. Functional trait analysis is increasingly recognized in terrestrial and freshwater systems as a tool to holistically answer ecological questions, but trait analysis has not been often applied to marine systems. By considering how traits of incoming colonists change over time, the investigators can untangle which species-level factors most influence abundance and distribution. This project will create an unprecedented long-term (>14-year) quantitative time-series of colonist species composition and function. It includes multiple vent sites to encompass the full diversity of habitat conditions, and assesses both local processes and regional connectivity through larval supply. Field observations at individual sites contribute to broader questions when placed in the context of metacommunity theory. In this theoretical framework, field data such as this can be used to answer such questions as how the eradication of the vent community at a particular site affects the persistence of the metacommunity overall, and which vent sites contribute most to regional biodiversity.