Benthic foraminiferal assemblage data across methane seepage intensity levels at the Haima cold seep, South China Sea
Description
This dataset supports a study of benthic foraminiferal assemblage variation across relative methane seepage intensity levels at the Haima cold seep, South China Sea. The study tested whether assemblage composition, abundance, diversity, and functional traits differ among a non-seep reference station and stations representing low, moderate, and high seepage intensity. Surface sediment samples were collected from four stations at approximately 1425 m water depth. Relative seepage intensity was classified from ROV observations of mussels, sediment characteristics, and authigenic carbonates. One 30 cm³ wet-sediment sample integrating the 0 to 10 cm interval was analyzed at each station. Unstained benthic foraminiferal specimens larger than 150 μm were counted and identified to the lowest practicable taxonomic level. Taxa were also classified by test composition, microhabitat preference, and oxygen tolerance. The dataset contains benthic foraminiferal specimen counts, taxon-level functional-trait classifications, and selected station observations used to assign relative seepage categories. These data can be used to calculate assemblage metrics and evaluate benthic foraminiferal responses to methane seepage. Agglutinated taxa were less abundant at seep-affected stations, total abundance was highest at the moderate-intensity station, and taxon richness and diversity were highest at the high-intensity station. These data can be used to reproduce the reported assemblage comparisons and evaluate benthic foraminiferal responses to methane seepage. Because each seepage category is represented by one station and one sample, the observed differences should be interpreted as site-specific patterns.
Files
Steps to reproduce
Assemblage metrics can be calculated from the specimen counts provided in Foraminiferal_counts.xlsx. Taxon-level functional traits are provided in Trait_classification.xlsx. Station_metadata.xlsx contains selected station observations and the assigned relative seepage categories. Match records among files using taxon names and station codes.
Institutions
- Peking UniversityBeijing, Beijing