Metal Bioaccumulation in Marine Mollusks with Temperature-Dependent Models

Experimental evidence for marine univalve and bivalve mollusks synthesizes temperature-dependent metal bioaccumulation. The dataset, authored by Minh Hieu Pham and last updated in April 2026, couples toxicokinetic modeling with machine learning for predictor screening. The framework was evaluated against an independent dataset, achieving an R² of approximately 0.73.

Use Cases

• Calibrating temperature-aware toxicokinetic models based on the described one-compartment mass-balance framework.
• Predicting metal bioaccumulation under warming scenarios based on thermal performance curves for filtration and growth.
• Screening predictors for metal uptake using machine learning methods mentioned in the description.
• Improving the interpretation of bioaccumulation factors and seasonal biomonitoring data as referenced in the description.

Strengths

• Framework validation shows good agreement with an independent dataset (R² ≈ 0.73).
• Explicitly models temperature-sensitive pathways, enabling scenario testing for heat extremes.
• Integrates multiple methodologies: toxicokinetic modeling, thermal performance curves, and machine learning.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The positive association between temperature and elimination is noted as provisional, pending more data.

Provenance

Source

figshare

Collection Method

Synthesis of experimental evidence and model development.

Time Range

null

Freshness

Last updated 2026-04-22 20:43:41; freshness should be verified.

Geography

Marine environments (specific regions not stated).