Erin K. Grey

Rapid Molecular Detection of Invasive Species in Ballast and Harbor Water by Integrating Environmental DNA and Light Transmission Spectroscopy

Invasive species introduced via the ballast water of commercial ships cause enormous environmental and economic damage worldwide. Accurate monitoring for these often microscopic and morphologically indistinguishable species is challenging but critical for mitigating damages. We apply eDNA sampling, which involves the filtering and subsequent DNA extraction of microscopic bits of tissue suspended in water, to ballast and harbor water sampled during a commercial ships 1400 km voyage through the North American Great Lakes. Using a lab-based gel electrophoresis assay and a rapid, field-ready light transmission spectroscopy (LTS) assay, we test for the presence of two invasive species: quagga (Dreissena bugensis) and zebra (D. polymorpha) mussels. Furthermore, we spiked a set of uninfested ballast and harbor samples with zebra mussel tissue to further test each assays detection capabilities. In unmanipulated samples, zebra mussel was not detected, while quagga mussel was detected in all samples at a rate of 85% for the gel assay and 100% for the LTS assay. In the spiked experimental samples, both assays detected zebra mussel in 94% of spiked samples and 0% of negative controls. Overall, these results demonstrate that eDNA sampling is effective for monitoring ballast-mediated invasions and that LTS has the potential for rapid, field-based detection.

Improving management of aquatic invasions by integrating shipping network, ecological, and environmental data: data mining for social good

The unintentional transport of invasive species (i.e., non-native and harmful species that adversely affect habitats and native species) through the Global Shipping Network (GSN) causes substantial losses to social and economic welfare (e.g., annual losses due to ship-borne invasions in the Laurentian Great Lakes is estimated to be as high as USD 800 million). Despite the huge negative impacts, management of such invasions remains challenging because of the complex processes that lead to species transport and establishment. Numerous difficulties associated with quantitative risk assessments (e.g., inadequate characterizations of invasion processes, lack of crucial data, large uncertainties associated with available data, etc.) have hampered the usefulness of such estimates in the task of supporting the authorities who are battling to manage invasions with limited resources. We present here an approach for addressing the problem at hand via creative use of computational techniques and multiple data sources, thus illustrating how data mining can be used for solving crucial, yet very complex problems towards social good. By modeling implicit species exchanges as a network that we refer to as the Species Flow Network (SFN), large-scale species flow dynamics are studied via a graph clustering approach that decomposes the SFN into clusters of ports and inter-cluster connections. We then exploit this decomposition to discover crucial knowledge on how patterns in GSN affect aquatic invasions, and then illustrate how such knowledge can be used to devise effective and economical invasive species management strategies. By experimenting on actual GSN traffic data for years 1997-2006, we have discovered crucial knowledge that can significantly aid the management authorities.

Disregarding human pre-introduction selection can confound invasive crayfish risk assessments.

Trait-based risk assessments of invasive species focus on identifying intrinsic biological or ecological traits associated with invasion success, which allows for a new species’ invasion risk to be assessed a priori, thus facilitating cost-effective prevention strategies. However, human preferences for species traits—preferences that might affect which species enter into different pathways of invasion—exist for taxa closely associated with people. Disregarding such preferences can confound correlations between species traits and invasion success. Here we develop a risk assessment for crayfish, a group of culturally and ecologically important decapod crustaceans with numerous harmful invasive species, that explicitly accounts for species traits as well as human preferences as they are expressed in different pathways (e.g., aquaculture, live angling bait for fishing, harvesting). Our results indicate that species traits and human preferences are confounded for introduction and establishment risk models, but subsequent spread risk is not associated with human preferences and can be predicted by clutch size. Although not commonly addressed, this study demonstrates that accounting for human preferences in trait-based risk assessments is important for taxa closely associated with people, as pre-introduction human selection of traits may bias such analyses.

Evaluation of Blue Crab, Callinectes sapidus, Megalopal Settlement and Condition during the Deepwater Horizon Oil Spill.

The Blue Crab, Callinectes sapidus, is a commercially, culturally, and ecologically significant species in the Gulf of Mexico (GOM), whose offshore stages were likely impacted by the Deepwater Horizon oil spill (DWH). To test for DWH effects and to better understand the planktonic ecology of this species, we monitored Callinectes spp. megalopal settlement and condition at sites within and outside of the spill extent during and one year after the DWH. We tested for DWH effects by comparing 2010 settlement against baseline data available for two sites, and by testing for differences in settlement and condition inside and outside of the spill extent. We also developed time series models to better understand natural drivers of daily settlement variation (seasonal and lunar trends, hydrodynamics, wind) during 2010 and 2011. Overall, we found that neither megalopal settlement nor body weight were significantly reduced at oiled sites, but that high unexplained variation and low statistical power made detection of even large effects unlikely. Time series models revealed remarkably consistent and relatively strong seasonal and lunar trends within sites (explaining on average 28% and 9% of variation, respectively), while wind and hydrodynamic effects were weak (1–5% variation explained) and variable among sites. This study provides insights into DWH impacts as well as the natural drivers of Callinectes spp. megalopal settlement across the northern GOM.

Early detection monitoring for aquatic non-indigenous species: Optimizing surveillance, incorporating advanced technologies, and identifying research needs

Following decades of ecologic and economic impacts from a growing list of nonindigenous and invasive species, government and management entities are committing to systematic early- detection monitoring (EDM). This has reinvigorated investment in the science underpinning such monitoring, as well as the need to convey that science in practical terms to those tasked with EDM implementation. Using the context of nonindigenous species in the North American Great Lakes, this article summarizes the current scientific tools and knowledge - including limitations, research needs, and likely future developments - relevant to various aspects of planning and conducting comprehensive EDM. We begin with the scope of the effort, contrasting target-species with broad-spectrum monitoring, reviewing information to support prioritization based on species and locations, and exploring the challenge of moving beyond individual surveys towards a coordinated monitoring network. Next, we discuss survey design, including effort to expend and its allocation over space and time. A section on sample collection and analysis overviews the merits of collecting actual organisms versus shed DNA, reviews the capabilities and limitations of identification by morphology, DNA target markers, or DNA barcoding, and examines best practices for sample handling and data verification. We end with a section addressing the analysis of monitoring data, including methods to evaluate survey performance and characterize and communicate uncertainty. Although the body of science supporting EDM implementation is already substantial, research and information needs (many already actively being addressed) include: better data to support risk assessments that guide choice of taxa and locations to monitor; improved understanding of spatiotemporal scales for sample collection; further development of DNA target markers, reference barcodes, genomic workflows, and synergies between DNA-based and morphology-based taxonomy; and tools and information management systems for better evaluating and communicating survey outcomes and uncertainty.

eDNA metabarcoding as a new surveillance approach for coastal Arctic biodiversity

Abstract Because significant global changes are currently underway in the Arctic, creating a large‐scale standardized database for Arctic marine biodiversity is particularly pressing. This study evaluates the potential of aquatic environmental DNA (eDNA) metabarcoding to detect Arctic coastal biodiversity changes and characterizes the local spatio‐temporal distribution of eDNA in two locations. We extracted and amplified eDNA using two COI primer pairs from ~80 water samples that were collected across two Canadian Arctic ports, Churchill and Iqaluit, based on optimized sampling and preservation methods for remote regions surveys. Results demonstrate that aquatic eDNA surveys have the potential to document large‐scale Arctic biodiversity change by providing a rapid overview of coastal metazoan biodiversity, detecting nonindigenous species, and allowing sampling in both open water and under the ice cover by local northern‐based communities. We show that DNA sequences of ~50% of known Canadian Arctic species and potential invaders are currently present in public databases. A similar proportion of operational taxonomic units was identified at the species level with eDNA metabarcoding, for a total of 181 species identified at both sites. Despite the cold and well‐mixed coastal environment, species composition was vertically heterogeneous, in part due to river inflow in the estuarine ecosystem, and differed between the water column and tide pools. Thus, COI‐based eDNA metabarcoding may quickly improve large‐scale Arctic biomonitoring using eDNA, but we caution that aquatic eDNA sampling needs to be standardized over space and time to accurately evaluate community structure changes.

Implications for U.S. Trade and Nonindigenous Species Risk Resulting from Increased Economic Integration of the Asia-Pacific Region

ABSTRACT This work investigates how potential changes in trade patterns resulting from increased economic integration in the Asia-Pacific region may affect the risk for nonindigenous species spread to the United States. We construct an invasion risk index utilizing the results from a global economic modeling framework in tandem with data for climate similarities between trade partners. The index is based on risk of introduction, determined by changes in trade, and risk of establishment, given by terrestrial and marine climate similarities between countries. The results indicate that Japan may be the riskiest trade partner for the United States in the Asia-Pacific region from a nonindigenous species perspective. This is driven by large expected changes in trade and high environmental similarity between the two countries. This research provides the basis of a risk assessment prediction system to examine the effects of changes in trade on nonindigenous species risk, an important, novel contribution to the trade policy literature.

Effects of sampling effort on biodiversity patterns estimated from environmental DNA metabarcoding surveys

Environmental DNA (eDNA) metabarcoding can greatly enhance our understanding of global biodiversity and our ability to detect rare or cryptic species. However, sampling effort must be considered when interpreting results from these surveys. We explored how sampling effort influenced biodiversity patterns and nonindigenous species (NIS) detection in an eDNA metabarcoding survey of four commercial ports. Overall, we captured sequences from 18 metazoan phyla with minimal differences in taxonomic coverage between 18 S and COI primer sets. While community dissimilarity patterns were consistent across primers and sampling effort, richness patterns were not, suggesting that richness estimates are extremely sensitive to primer choice and sampling effort. The survey detected 64 potential NIS, with COI identifying more known NIS from port checklists but 18 S identifying more operational taxonomic units shared between three or more ports that represent un-recorded potential NIS. Overall, we conclude that eDNA metabarcoding surveys can reveal global similarity patterns among ports across a broad array of taxa and can also detect potential NIS in these key habitats. However, richness estimates and species assignments require caution. Based on results of this study, we make several recommendations for port eDNA sampling design and suggest several areas for future research.

Current and Projected Distribution of the Red-Eared Slider Turtle, Trachemys scripta elegans, in the Great Lakes Basin

Abstract Exotic species introduced through the pet trade pose an ecological and economic threat to the Great Lakes region. Trachemys scripta elegans, the red-eared slider turtle, is a globally invasive species already present in the Great Lakes basin whose distribution and potential for spread is poorly known. We assembled a detailed dataset on T. s. elegans occurrence and establishment in the region and created a niche model to assess the potential for the spread of this species under current climate conditions and future scenarios. We found T. s. elegans occurs throughout the Great Lakes basin and suitable area will likely increase from 26% to 39–50% of the entire basin by 2050, with Lake Erie at greatest risk with ∼95% of its total area suitable for T. s. elegans by 2050. These findings highlight the need for further research to assess impacts of T. s. elegans on native species and proactive efforts to prevent its further spread.