Navigating uncertainty in environmental DNA detection of a nuisance marine macroalga

Early detection of nuisance species is crucial for the conservation and management of threatened ecosystems, reducing the risk of widespread establishment. Environmental DNA (eDNA) data can increase the sensitivity of biomonitoring programs, oftentimes with minimal cost and effort. However, eDNA analyses have inherent errors that can complicate the integration of molecular survey methods into existing management frameworks. Therefore, it is crucial for eDNA studies to consider imperfect detections and estimate error rates accordingly. Detecting nuisance species in low abundance with minimal uncertainty is vital to increase the chance of containment and eradication. We developed a novel eDNA assay to detect a nuisance marine macroalga across its colonization front using surface seawater samples from Papahānaumokuākea Marine National Monument (PMNM), one of the world’s largest marine reserves. Chondria tumulosa, a cryptogenic red alga with invasive characteristics, has been documented for..., , , # Navigating uncertainty in environmental DNA detection of a nuisance marine macroalga

[https://doi.org/10.5061/dryad.kkwh70s8q](https://doi.org/10.5061/dryad.kkwh70s8q)

Quantitative PCR (qPCR) data were exported as CSV files directly from the CFX Manager software (Bio-Rad) and includes:

* **quantification amplification results** (Quantification_Amplification_Results_SYBR.csv) - raw qPCR data used to visualize amplification curves (cycle number, relative fluorescence units \"value\", detection threshold as calculated by the CFX96 and efficiency \"E\", as calculated using the CFX Manager software)
* **melt curve derivative results** (Melt_Curve_Derivative_Results_SYBR.csv) - raw qPCR data used in the melt curve analysis (cycle temperature C, negative first derivative of the melting-curve, -dF/dT \"value\", detection threshold as calculated by the CFX96 and efficiency \"E\", as calculated using the CFX Manager software)
* **quantification Cq results** (Quantification_Cq_Results_SYBR.csv)...