Dataset
Landscape effects on metal accumulation and toxicological burden in oysters
Mendeley Data, Vol.29 September 2026
Elsevier Inc.
2026
Abstract
This dataset supports the manuscript “Landscape effects on metal accumulation and toxicological burden in oysters” and contains three CSV files:
• 1. Oyster_Round1_Analyte.csv: Individual-level data for 55 oysters from six estuaries in southeast Queensland, Australia, including tissue element concentrations, morphometric and condition measurements, and landscape variables. The manuscript analyses 17 retained elements; the source file also contains elements excluded during quality control.
• Estuary_Level_Data_Authoritative_n55.csv: Estuary-level summaries derived from the 55-oyster dataset, alongside pooled-estuary BLT-Screen toxicity measurements.
• Toxicity_Metal_Correlations_Spearman_n55.csv: Spearman correlations between estuary-level toxicity and mean tissue concentrations of the 17 retained elements.
BLT-Screen toxicity represents one pooled composite per estuary (six observations). Toxicity values repeated across individual-oyster records are not independent measurements. Toxicity–metal correlations are descriptive estuary-level analyses.
Historical estuary labels “BELLS CREEK” and “TIN CAN BAY - TUAN” correspond to North Pumicestone Passage and Great Sandy Strait, respectively. Missing condition measurements reduce the individual-level condition analysis to 53 oysters. Methods, units and analytical exclusions are described in the accompanying manuscript and supplementary material.
Details
- Title
- Landscape effects on metal accumulation and toxicological burden in oysters
- Authors
- Jackson Milburn (Data Collector)Lucy Goodridge Gaines (Data Collector) - University of the Sunshine CoastJason van de Merwe (Data Collector) - Griffith UniversityBen Gilby (Data Collector) - University of the Sunshine Coast
- Publication details
- Mendeley Data, Vol.29 September 2026
- Format
- 3 x CSV files; Total: 37 KB
- Publisher
- Elsevier Inc.
- Date published
- 2026
- DOI
- 10.17632/5439v5v53r.1
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991264992402621
- Output Type
- Dataset
Metrics
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