Assessing the cost-efficiency of environmental DNA sampling

Environmental DNA (eDNA) sampling can be a highly sensitive method for detecting aquatic taxa; however, the cost-efficiency of this technique relative to traditional methods has not been rigorously assessed. We show how methods that account for imperfect and stochastic detection can be used to (i) determine the optimal allocation of survey effort with eDNA sampling for a fixed budget (i.e. identify the optimal combination of water samples vs. site visits), and (ii) assess the cost-efficiency of eDNA sampling relative to traditional survey techniques. We illustrate this approach by comparing eDNA sampling and bottle-trapping for an exotic newt species (Lissotriton v. vulgaris) recently detected in Melbourne, Australia. Bottle traps produced much lower detection rates than eDNA sampling, but the cost-efficiency of the two methods can be similar because bottle-trapping is cheaper per sample. The relative cost-efficiency of the two sampling methods was sensitive to the available survey budget, the costs of eDNA primer/probe development and sample processing and the number of positive quantitative PCR assays (qPCRs) used to designate a water sample as positive for newt DNA. Environmental DNA sampling was more cost-efficient than bottle-trapping for small to intermediate budgets when primer/probe development and sample processing costs were low, and 1/4 or 2/4 positive qPCRs were used to label a water sample as positive for newt eDNA. However, bottle traps were generally more cost-efficient than eDNA sampling when primer/probe development and sample processing costs were high, regardless of qPCR threshold or survey budget. Traditional sampling methods may achieve lower detection probabilities compared to eDNA sampling, but the totality of costs can make eDNA sampling less efficient than traditional techniques in some circumstances. Our approach provides a quantitative framework for determining how many water samples and site visits are required to maximize detection probabilities with eDNA sampling, and can calculate the cost-efficiency of any sampling method.