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Early detection monitoring for aquatic non-indigenous species: optimizing surveillance, incorporating advanced technologies, and identifying research needs
Citation:
Trebitz, A., J. Hoffman, J. Darling, E. Pilgrim, J. Kelly, E. Brown, W. Chadderton, S. Egan, E. Grey, S. Hashsham, K. Klymus, A. Mahon, J. Ram, M. Schultz, C. Stepien, AND J. Schardt. Early detection monitoring for aquatic non-indigenous species: optimizing surveillance, incorporating advanced technologies, and identifying research needs. JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, 202:299-310, (2017).
Impact/Purpose:
Early-detection monitoring, meaning monitoring capable of finding new species while they are still few in number and limited in distribution, is increasingly of interest as a component of aquatic invasive species (AIS) prevention and management. The purpose of this manuscript is to review existing scientific understanding for the design and implementation of early detection monitoring, and to discuss areas where further science development and testing is needed. The audience for the manuscript is envisioned as people charged with implementing early detection monitoring and the manuscript is structured around questions confronting them -- namely how to decide which taxa and locations should be monitored, how the monitoring program should be designed (e.g., size and allocation of effort), what the organism collection and identification effort will consist of, and how the resulting monitoring data can be evaluated and applied. The manuscript is an outgrowth of a workshop that was held at EPA/ORD’s Mid-Continent Ecology Division in fall of 2014 and includes many of the workshop attendees as co-authors. The context for the manuscript is AIS issues in the Laurentian Great Lakes, but the themes and science that the manuscript covers are broadly applicable to AIS issues elsewhere.
Description:
Following decades of ecologic and economic impacts from a growing list of invasive species, government and management entities are investing in systematic early- detection monitoring (EDM), which has reinvigorated investment in and evaluation of the science underpinning such monitoring. Using the context of invasive species in the Laurentian Great Lakes and building on a collaborative interchange among scientists and agencies charged with EDM, this article presents the current state of scientific knowledge, assesses existing limitations, and describes research that will be required to support comprehensive future EDM efforts. We begin with the scope of the monitoring effort, contrasting target-species monitoring with broad-spectrum monitoring, reviewing information to support prioritization based on species and locations, and exploring the challenge of moving beyond individual efforts into development of a coordinated monitoring network. Next, we discuss survey design, including determination of overall effort to expend and possibilities for allocating that effort over space and among collection techniques. In a section on sample collection and analysis, we discuss the merits of physical organism samples versus environmental DNA (eDNA), review the capabilities and limitations of the relevant identification methods (by morphology, DNA target markers, or DNA barcoding), and examine best practices for sample handling and data verification. We end with a section addressing the analysis of the monitoring data, including methods to summarize and evaluate survey performance, and to characterizing and communicating survey uncertainty. While the body of science supporting procedures for early-detection monitoring is already substantial, research and information needs identified (many of which are actively being addressed) include: better data to support risk assessments that guide choice of taxa and locations to monitor; better understanding of spatiotemporal scales for sample collection for eDNA especially; continued development of DNA target markers, reference barcodes, and genomic workflow procedures; continued interaction and cross-calibration between DNA-based and morphology-based taxonomy; and additional user-friendly tools for evaluating and communicating survey outcomes and uncertainties.
