Optimising sampling and analysis protocols in environmental DNA studies.

Area of Science:

• Ecology
• Conservation Biology
• Statistical Modeling

Background:

• Ecological surveys face challenges with false positive and false negative species detections.
• Environmental DNA (eDNA) methods introduce potential errors at sample collection and laboratory analysis stages.
• Accurate species occupancy estimation is vital for effective conservation and ecological management.

Purpose of the Study:

• To evaluate the impact of false positive errors on occupancy models using qPCR-based eDNA data.
• To compare occupancy estimates from models with and without false positive error correction.
• To determine optimal replication strategies for eDNA sampling to improve parameter estimates.

Main Methods:

• Analysis of a large qPCR-based eDNA dataset using two occupancy models: one accounting for false positives (Griffin et al., 2020) and one assuming no false positives (Stratton et al., 2020).
• Application of the Griffin et al. (2020) model to simulated data to assess the effect of replication at different sampling stages.
• Comparison of occupancy and detectability estimates between the two models and with prior species occupancy data.

Main Results:

• The model assuming no false positives (Stratton et al., 2020) consistently overestimated species occupancy compared to the Griffin et al. (2020) model and previous estimates.
• Incorporating replication at both sample collection and laboratory analysis stages significantly reduced bias and narrowed credible intervals for occupancy and detectability.
• Collecting multiple samples from a site offered greater improvement in parameter estimates than relying solely on numerous laboratory replicates.

Conclusions:

• Statistical models accounting for false positive errors are essential for accurate eDNA-based species occupancy estimation.
• Replication strategies in eDNA surveys, particularly at the sample collection stage, are critical for robust ecological inference.
• Optimized replication protocols can enhance the reliability and precision of eDNA survey results for conservation applications.