Skip to main content
Dryad

Data from: Shell trace elemental fingerprints of the deep-sea methane seep mussel Gigantidas Childressi vary by depth, site, and growth region

Grace, Ian1

Research facility: University of North Carolina at Chapel Hill
Published Jan 26, 2026 on Dryad. https://doi.org/10.5061/dryad.wh70rxx2q

Data files

Jan 26, 2026 version files 21.64 MB

Click names to download individual files

Abstract

Larval dispersal is a key driver of population persistence and resilience of marine metapopulations and communities. Determining where and how larvae disperse in the deep sea is one of the most vexing challenges in deep-sea ecology. We used laser ablation inductively coupled plasma mass spectrometry to evaluate the potential role of trace elemental fingerprints (TEFs) of the deep-sea methane seep mussel Gigantidas childressi (n = 92 valves) in discriminating among collection depths, geographic regions (Gulf of Mexico and West Atlantic Margin; GOM and WAM), methane seep sites, and shell growth regions. A priori permutational analyses of variance (PERMANOVA) discriminated among mussel valve TEFs across a depth gradient (650 m to 2206 m), among eight methane seep sites, and among shell growth regions. A priori canonical analyses of principal coordinates (CAP) generally matched PERMANOVA results and additionally discriminated TEFs among geographic regions. Results for post-hoc analyses on individual shell growth regions varied by statistical approach (PERMANOVA VS CAP) and by shell growth region (larval prodissoconch I and prodissoconch II VS settler dissoconch shell). Post-hoc PERMANOVA discriminated only among sites, while post-hoc CAP discriminated among all study factors. Discrimination among depths was mainly driven by the elemental ratio Ba:Ca; discrimination among geographic regions was driven mainly by Ba:Ca and Sr:Ca; discrimination among sites and shell growth regions was driven by all three elemental ratios. Overall, shell TEFs show potential to discern spatial distribution of larval population pools.

This dataset contains files and tools (e.g., MATLAB programs) associated with the raw data, data reduction/pre-proccessing, processing itself, and statistical analysis in PRIMER-e v7 software.