Navigating uncertainty in environmental DNA detection of a nuisance marine macroalga
Data files
May 30, 2024 version files 87.05 MB
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Melt_Curve_Derivative_Results_SYBR.csv
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Quantification_Amplification_Results_SYBR.csv
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Quantification_Cq_Results_SYBR.csv
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README.md
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Sequence_Data.zip
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Sequence_metadata.csv
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Standard_Curve_Data.csv
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VSEARCH_output.txt
Abstract
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 forming dense mats that overgrow coral reefs and smother native flora and fauna in PMNM. We verified the eDNA assay using site-occupancy detection modeling from quantification polymerase chain reaction (qPCR) data, calibrated with visual estimates of benthic cover of C. tumulosa that ranged from < 1% to 95%. Results were subsequently validated with high-throughput sequencing of amplified eDNA and negative control samples. Overall, the probability of detecting C. tumulosa at occupied sites was at least 92% when multiple qPCR replicates were positive. Modeled false-positive inferences were 3% or less and false-negative errors were 11% or less. The developed assay is suitable for routine monitoring at shallow sites (less than 10 m), even when C. tumulosa abundance was less than 1%. Successful implementation of eDNA tools in conservation decision-making relies on balancing uncertainties in both visual and molecular detection methods. Our results and modeling demonstrated the assay’s sensitivity to C. tumulosa, and we outline the necessary steps to infer ecological presence-absence from molecular detection data. By providing a reliable, cost-effective tool for detecting low-abundance species, eDNA analyses have the potential to enhance the surveillance of nuisance species and inform timely management interventions.
README: Navigating uncertainty in environmental DNA detection of a nuisance marine macroalga
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) - raw qPCR detection data used for modeling of site occupancy (quantification cycle Cq, detection threshold as calculated by the CFX96, efficiency "E", as calculated using the CFX Manager software, efficiency-corrected eDNA starting quantities "SQ.E")
- standard curve data (Standard_Curve_Data.csv) - raw qPCR data from standards formatted for plotting standard curve for rbcL marker (quantification cycle Cq and expected starting quantities "SQ") using serial dilutions of template DNA extracted from Chondria tumulosa tissue
High-throughput sequence data run on an Illumina MiSeq includes:
- raw sequence data - Raw sequence data (fastq.gz) from environmental DNA of surface seawater samples
- sequence metadata (Sequence_metadata.csv) - sample IDs, plate IDs, forward reads filename, reverse reads filename
- VSEARCH output - (VSEARCH_output.txt) - command line interface codes and outputs from amplicon metabarcoding workflow
Project metadata is provided in each and includes site IDs, date of sample collection, region, island, locales, site depth (meters), Chondria tumulosa percent benthic cover from visual surveys (%), binary visual presence-absence, and GPS coordinates (Lat./Long.) and X-Y position coordinates.
Entries marked "NA" are not-applicable. Entries marked "NULL" are absent.