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Ballast water exchange and invasion risk posed by intra-coastal vessel traffic: An evaluation using high throughput sequencing John Darling, John Martinson, Yunguo Gong, Sara Okum, Erik Pilgrim, katrina Lohan, Katharine J. Carney, and Gregory Ruiz Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b02108 • Publication Date (Web): 30 Jul 2018 Downloaded from http://pubs.acs.org on July 31, 2018

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TITLE: Ballast water exchange and invasion risk posed by intra-coastal vessel traffic: An evaluation using high throughput sequencing SHORT TITLE: Metabarcoding analysis of ballast water exchange

AUTHORS: John A. Darling1*, John Martinson1, Yunguo Gong2, Sara Okum2, Erik Pilgrim1, Katrina M. Pagenkopp Lohan3, Katharine J. Carney3, and Gregory M. Ruiz3

AUTHOR AFFILIATIONS: 1

United States Environmental Protection Agency, National Exposure Research Laboratory

2

contractor to United States Environmental Protection Agency

3

Smithsonian Environmental Research Center, Edgewater, MD 21037 USA

*CORRESPONDING AUTHOR: US Environmental Protection Agency National Exposure Research Laboratory 109 T.W. Alexander Drive Research Triangle Park, NC 27711 Phone: 1-919-541-1912 Email: [email protected]

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ABSTRACT:

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Ballast water remains a potent vector of non-native aquatic species introductions, despite increased

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global efforts to reduce risk of ballast water mediated invasions. This is particularly true of intra-coastal

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vessel traffic, whose characteristics may limit the feasibility and efficacy of management through ballast

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water exchange (BWE). Here we utilize High Throughput Sequencing (HTS) to assess biological

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communities associated with ballast water being delivered to Valdez, Alaska from multiple source ports

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along the Pacific Coast of the United States. Our analyses indicate that BWE has a significant but modest

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effect on ballast water assemblages. Although overall richness was not reduced with exchange, we

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detected losses of some common benthic coastal taxa (e.g. decapods, mollusks, bryozoans, cnidaria) and

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gains of open ocean taxa (e.g., certain copepods, diatoms, and dinoflagellates), including some

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potentially toxic species. HTS-based metabarcoding identified significantly differentiated biodiversity

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signatures from individual source ports; this signal persisted, though weakened, in vessels undergoing

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BWE, indicating incomplete faunal turnover associated with management. Our analysis also enabled

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identification of taxa that may be of particular concern if established in Alaskan waters. While these

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results reveal a clear effect of BWE on diversity in intra-coastal transit, they also indicate continued

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introduction risk of non-native and harmful taxa.

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KEYWORDS:

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Ballast water, ballast water exchange, high throughput sequencing, metabarcoding, invasive species,

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surveillance

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INTRODUCTION

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For over three decades the transport of ballast water (BW) has been acknowledged as an important

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vector of species introductions to coastal ecosystems and has been implicated in establishment of

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invasive species with significant ecological and socio-economic impacts1-3. This recognition has driven

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the creation of various legal instruments for mitigating invasion risks posed by global vessel traffic. The

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most widely relevant such instrument, the International Maritime Organization’s (IMO) 2004

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International Convention for the Control and Management of Ship’s Ballast Water and Sediments,

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entered into force in September 2017 and mandates attainment of numerical organism discharge

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standards achievable through BW treatment4. In the United States, similar numerical standards have

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been adopted in the 2012 final BW rule of the US Coast Guard (USCG) and in the US Environmental

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Protection Agency’s (USEPA) 2013 Vessel General Permit5, 6.

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These numerical standards herald a significant step in the evolution of increasingly rigorous

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management practices aimed at reducing invasion risk associated with BW. Prior to the adoption of

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discharge standards, management practices have focused primarily on open ocean BW exchange (BWE),

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adopted as a means to reduce both the abundance of coastal organisms in ballast tanks (through

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replacement with open ocean water and associated taxa) and their viability (through salinity shock)7.

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Although numerical standards are meant to supersede BWE, schedules for implementation of approved

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treatment systems will preclude full compliance with the international standard until 20248, and

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extensions of installation deadlines in the US will likely continue until 20219. In the interim, BWE remains

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an important and widely used management tool, and understanding its effectiveness is an important

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aim of BW research. While in many cases BWE has been shown to result in dramatic declines in

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propagule pressure to recipient ports10, 11, multiple studies have suggested that efficacy may vary

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broadly depending on vessel route, voyage duration, biotic composition, and environmental

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conditions12-14. Limitations to the efficacy of BWE may be exacerbated in the case of intra-coastal vessel

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traffic, where exemptions frequently enable transfer of unexchanged ballast, greatly elevating risks of

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invasion posed by such voyages15-17.

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Here we explore biodiversity of BW being transported to Valdez, Alaska (AK) from multiple ports on the

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Pacific coast of the US. Given the prevalence of known invasive coastal species in west coast donor

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(source) ports, voyages from the mainland US to AK potentially present substantial invasion risk18, 19.

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That risk may be heightened in the future by increasing vessel traffic and warming trends at higher

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latitudes20, 21, particularly for dispersal-limited species whose intracoastal spread is mediated primarily

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by human vectors. We explore the role of BWE in moderating this risk by comparing diversity present on

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ships conducting BWE with that present in unmanaged ballast. To obtain a broad survey of metazoan

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diversity in ballast tanks, we employ High Throughput Sequencing (HTS) based on a nuclear 18S

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ribosomal DNA locus, which allows assessment of both metazoan and protist communities. HTS-based

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approaches have become widely adopted in various marine monitoring contexts22-25, and a growing

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number of studies are beginning to apply these tools to BW surveillance26, 27. The primary objective of

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the current study was to explore the power of HTS data to ascertain biodiversity signatures associated

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both with geography (location of ballast uptake) and with biotic turnover driven by BWE. In addition, we

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attempt to identify specific taxa that are either indicative of BWE or potentially represent risk of

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invasion to AK coastal waters. Our results contribute to a growing literature establishing the value of

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HTS as a tool for understanding biological invasions, and add to our knowledge of the risks posed by

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intra-coastal vessel traffic and the challenges associated with managing those risks.

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MATERIALS and METHODS

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Sampling. All vessels sampled were crude oil tankers arriving at the Valdez Marine Terminal, AK (Figure

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1). On each vessel researchers collected the following information: BW source location, date of uptake,

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management (yes or no), type of management, date of management, and last port of call. Ballast tanks

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were accessed via a manhole on deck. A plankton net with 35 µm mesh (50 µm in diagonal dimension,

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consistent with selection for the >50 µm zooplankton size class defined in IMO, USCG, and USEPA

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regulations) was lowered into the tank until the cod end reached the bottom of the accessible tow

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depth. The net was towed vertically through the water column at a consistent speed to the surface of

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the tank. A manual spray washer was used to rinse the net and cod end with filtered tank water, and the

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sample was collected in a 125 mL Nalgene sample bottle. In the laboratory, the sample was filtered

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using a 35 µm mesh to remove the BW and preserved in 95% ethanol. Prior to processing, the sample

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was filtered again using a 20 µm mesh and rinsed with 95% ethanol into a 50 mL Falcon tube. Vessels

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that listed mixed ballast sources or undertook management practices other than exchange were

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excluded from the analysis. In total 39 ships were sampled, 18 of which had undergone BWE during the

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voyage and 21 of which discharged unmanaged ballast. Ships originated from 5 different source regions

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along the Pacific US coast: Alaska (4 vessels, none undergoing BWE), Puget Sound (19 vessels, 11

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undergoing BWE), Offshore Oregon (2 vessels not undergoing BWE), San Francisco Bay (8 vessels, 2

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undergoing BWE), and Los Angeles/Long Beach (6 vessels, 4 undergoing BWE). The overall sample size

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represents approximately 5% of the total vessel arrivals to Valdez during the sampling period.

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DNA extraction, PCR amplification, and Sequencing. Detailed methods on sample DNA extraction and

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preparation for amplification and sequencing are provided in Supporting Information. Samples were

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vacuum-filtered, and the entire filter phenol-chloroform extracted to ensure complete recovery of

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sample DNA. Each set of extractions was accompanied by a sterile water extraction blank, and each day

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a separate filter blank was also run; these blanks were carried through the amplification and sequencing

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process as negative controls along with negative PCR reaction controls run alongside each set of DNA

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templates. A fragment of the small subunit (SSU or 18S) ribosomal RNA was amplified using primers

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SSU_F04 (GCTTGTAAAGATTAAGCC ) and SSU_R22 (GCCTGCTGCCTTCCTTGGA) as described by Blaxter et

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al., 199828. Subsequent cleaning and preparation of amplicons for dual-indexing PCR and MiSeq

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sequencing was conducted according to standard protocols (see Supporting Information).

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Bioinformatic analyses. The AK samples analyzed in this work were part of a broader sampling effort

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including other recipient ports, and all samples were processed through a common bioinformatic

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pipeline; numbers reported here refer only to AK samples. Additional details on sequence processing are

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provided in Supporting Information. Briefly, ~3M pairs of raw Illumina sequences from three sequencing

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runs were demultiplexed by sample and combined in a single working directory. After trimming of

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primers, merging, and removal of phiX contamination, 2.5M reads remained. We selected 350 bps as a

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standard length after evaluation of length vs. expected error rates; 1.5M sequences remained after

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trimming and selection of full length sequences with 10x that of the maximum observed across controls;

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this latter approach was adopted to retain OTUs whose presence at high frequency in samples suggests

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that they are ecologically relevant, despite low level contamination of controls. 583 OTUs remained

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after these corrections.

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Statistical analyses. OTU accumulation curves were generated by random subsampling without

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replacement over 1,000 permutations, using the specaccum function of the vegan package30, 31 in R v.

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3.3.332. All ordination analyses were also implemented in the vegan package, and were conducted using

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log-transformed count data after rarefaction to the median sample size, as this approach has been

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shown to improve analytical outcomes while minimizing loss of informative data33; alternative

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rarefaction approaches did not alter analytical results (data not shown). Non-Metric Dimensional Scaling

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(NMDS) was conducted in two dimensions on transformed OTU counts using Bray-Curtis distances, and

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redundancy analysis (RDA) was conducted on transformed counts of OTUs observed at the family level

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as ascertained through taxonomic assignment. Data transformed to presence/absence and assessed

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using Jaccard’s distance resulted in similar analytical outcomes (see Supplemental Figure 1). Statistical

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significance of the effect of BWE in ordinations was assessed either by testing partitions of sums of

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squares using dissimilarities with the adonis function34 (for unconstrained NMDS) or by implementing

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ANOVA-like permutations for the effect of constraints in RDA using the anova function35; significance of

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all tests was determined with 1,000 permutations. Variation partitioning in RDA across multiple

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explanatory variables was done using the varpart function in vegan, with significance assessed by

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ANOVA on the partitions35.

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Mantel tests of correlation between geographic distance and Bray-Curtis dissimilarity were

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implemented in the R package ecodist36. Shortest great circle distances between pairs of sites were

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generated based on latitude and longitude measurements using the haversine distance function

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implemented in the R package geosphere37.

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Formal identification of indicator taxa was conducted using the indicspecies package in R, which

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assesses strength of association between species patterns and groups of samples38, 39. We adopted the

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IndVal association index (I), which is based on both the likelihood of a sample belonging to a test group

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assuming the presence of the indicator (specificity or positive predictive power) and the likelihood of the

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indicator being present in a sample belonging to the test group (sensitivity); 1,000 permutations were

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used to assess statistical significance of associations. For some comparisons between managed and

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unmanaged ballast we attempted to minimize the effect of source by restricting analysis to the 19

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samples derived from Puget Sound.

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Identification of coastal taxa potentially posing risk of invasion to AK was done by three methods. First,

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we compared OTUs present in unexchanged ballast from vessels originating outside AK with those from

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vessels originating in Nikiski, AK. OTUs with assignments to the species level that were at least 1,000

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times more common in vessels originating outside AK were identified as taxa of potential interest.

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Second, we cross-referenced OTU tables with lists of known invasive marine species obtained through

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the National Exotic Marine and Estuarine Species Information System (NEMESIS40) and the World

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Register of Introduced Marine Species (WRIMS41). Third, additional taxa of interest were identified

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through manual inspection of OTU tables. For all taxa of interest we downloaded additional sequences

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for comparison from GenBank, including all or a subset of the SSU gene sequences available for that

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genus and at least one outgroup. For each genus, sequences were aligned using the MAFFT plugin with

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default parameters in Geneious v11.0.4 (Biomatters Ltd). The ends of the alignments were trimmed to

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remove terminal gaps. Neighbor-joining trees were then generated in Geneious v11.0.4 using the

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Tamura-Nei genetic distance model and 1,000 bootstrap replicates with random resampling. Confidence

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in final assignments was assessed qualitatively based on RDP confidence scores, availability of reference

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sequences, tree topology, and bootstrap values for tree nodes.

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RESULTS

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Effect of BWE on alpha and beta diversity. BWE did not have significant effect on alpha diversity. OTU

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accumulation rates at the recipient port for vessels undergoing BWE were indistinguishable from rates

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for vessels not managing ballast (Figure 2). We also observed no differences in alpha diversity between

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managed and unmanaged vessels in terms of OTU count (Student’s t test, P = 0.56), number of observed

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families (P = 0.65) or extrapolated OTU richness (Chao’s estimate42, P = 0.30) (see Supplemental Table 1).

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However, BWE had a clear effect on beta diversity. NMDS ordination based on log-transformed OTU

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abundance revealed statistically significant clustering of samples into management groups (Figure 3A;

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adonis R2 = 0.0827, P < 0.001 for difference between group centroids; analysis of dispersion indicated

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homogeneity of variance between groups), and RDA based on log-transformed abundance at the family

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level similarly distinguished managed from unmanaged vessels (Figure 3B; ANOVA F = 3.024, P = 0.002);

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the latter relationship was preserved even when RDA was conditioned on source port (ANOVA F = 2.727,

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P < 0.001, data not shown). These relationships were unchanged when analysis was conducted on binary

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data (Supplemental Figure 1). We observed no significant differences between empty-refill (ER) and

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flow-through (FT) BWE methods, either in terms of alpha diversity (Student’s t test based on Shannon-

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Weaver diversity, P = 0.51) or beta diversity (adonis R2 = 0.0735, P = 0.16). Generally, the effect of BWE

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was significant but relatively weak, with adjusted R2 of only 0.0455 (Table 1). Variation partitioning

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revealed significant correlations between beta diversity and management (BWE vs. no exchange),

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source port, and location of most recent ballasting operations (by latitude), although the effect of

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source port was considerably stronger than that of the other two factors. Effects of both source port

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and BWE remained significant in partial correlations when controlling for other factors (adjusted R2 =

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0.1702 and 0.0299, respectively).

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The effect of location of ballasting operations on diversity was further confirmed by significant Mantel

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correlations between geographic and Bray-Curtis distances (Mantel’s r = 0.3953, P = 0.001; see

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Supplemental Figure 2). Additional support for the effect of source port was obtained through

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ordination analyses conducted independently on managed and unmanaged vessels. Among the latter,

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source port had a very strong and significant effect, with ordination clearly revealing regional clusters

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based on vessel origin (Figure 4A; adonis R2 = 0.7346, P < 0.001). When considering only managed

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vessels, the effect of source port remained significant but was considerably weaker (Figure 4B, adonis R2

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= 0.3703, P = 0.0089), with largely overlapping regional clusters in the ordination.

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Taxa indicative of BWE. Analysis of exchanged and unexchanged ballast originating from a single high-

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salinity source region (Puget Sound) indicates that the major shifts in biodiversity are restricted to

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relatively few phyla (Supplemental Figure 3), including ctenophores (decrease in relative abundance

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associated with exchange from 6.6% to 1.1%), dinoflagellates (increase associated with exchange from

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3.1% to 13.7%), and bacillariophytes (diatoms, increase from 0.4% to 11.5%). Across the entire dataset,

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indicator analysis conducted at the family level (Table 2) identified 31 families out of 234 that were

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significantly associated with either unexchanged (15 families) or exchanged (16 families) ballast.

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Generally, taxa associated with unexchanged ballast derived from groups of benthic coastal organisms,

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including mollusks, cnidarians, bryozoans, and crustaceans; among the latter, multiple families

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comprised species that are typically parasitic on other benthic coastal taxa. In contrast, families

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associated with exchanged ballast were dominated by planktonic dinoflagellates, diatoms, and other

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protists, along with planktonic copepods.

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Potential taxa of interest entering AK. We identified ten taxa that we considered “of concern” given

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their potential risk of establishment in AK and their known history of invasiveness or capacity for

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negative ecological or health impacts (Table 3). Detailed analyses of the OTUs assigned to these taxa

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(see Supplemental Figures 4-12) revealed varying levels of confidence in initial assignments, with only

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half evaluated at “high” confidence (four species level assignments and one genus level). These included

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two species of polychaetes, one bivalve, a genus of shrimp, and a parasitic dinoflagellate. Raw sequence

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counts of these OTUs were not consistently lower in exchanged ballast vs. unexchanged ballast, and

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these differences were not significantly different with the exception of the polychaete genus Capitella

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(Student’s t test P = 0.038).

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DISCUSSION

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Efficacy of ballast water exchange. Comparisons between vessels that exchanged their BW and those

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that did not suggest that BWE has a detectable but modest effect on the diversity of OTUs present in

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ballast tanks. Generally, our results are consistent with expected patterns of biotic turnover resulting

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from exchange; taxa statistically associated with unexchanged ballast tend to be benthic organisms

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typically encountered in shallower coastal environments and ports, whereas those associated with

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exchanged ballast are frequently planktonic open ocean taxa (Table 2). However, while the effect of

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BWE is significant it explains only a small fraction of the observed variation in biodiversity, considerably

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less than is explained by source port (Table 1), and it appears to have no effect on overall OTU richness

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(Figure 2). This latter observation may result in part from compensatory changes in biodiversity

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associated with BWE. Exchange is expected to considerably reduce concentrations of coastal biota,

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resulting in loss of some taxa11, 43; however, richness is likely augmented with open ocean species during

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exchange, resulting in little overall change despite shifts in community composition. Persistence of

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residual water in exchanged tanks—as much as 5% of BW may remain even when BWE complies with

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existing standards—may further limit shifts in biodiversity12.

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These results are in broad agreement with previous studies revealing variable and often limited effects

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of BWE on zooplankton and phytoplankton diversity12. BWE appears to be most reliably effective at

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reducing abundance and species richness being transferred from freshwater and low salinity ports, likely

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due to the large impact of osmotic shock on residual freshwater coastal biota when exposed to high

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salinity open ocean water during and after exchange10, 44, 45. For other types of voyages, the reported

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effects of exchange have been less consistent. Multiple studies have observed a reduction in abundance

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of both phyto- and zooplankton associated with BWE, although with limited change in corresponding

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biodiversity11, 13, 18, 43, 46. In some cases, species richness has even been observed to increase following

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exchange16, 43. Generally, the loss of coastal species appears to be lower than expected given the rate of

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water dilution47, and the effect of BWE on source diversity is often low when controlling for high natural

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mortality that typically occurs in tanks11, 47. Efficacy of BWE has also been observed to vary with the

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method of exchange employed, although results have again been variable; Cordell et al18 reported

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greater efficacy of ER over FT exchange in reducing zooplankton abundance, whereas Simard et al11

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found FT to be more efficient than a partial ER method. In our analysis, although mean alpha diversity

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was lower for vessels conducting FT exchange, this difference was not significant, nor was there any

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significant difference in beta diversity observed based on ordination.

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Certain taxa appear to be particularly difficult to manage by BWE. Multiple studies suggest that BWE is

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inefficient at removing dinoflagellates, and may even increase the abundance and/or diversity of some

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species, including potentially harmful taxa11, 16, 48, 49. The previously observed association of diatoms and

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dinoflagellates with exchanged ballast11 is again consistent with our indicator taxa analyses (Table 2).

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Given observations of dinoflagellate cysts in ballast sediments50, it is also possible that agitation of

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sediments associated with BWE may contribute to increased abundance of dinoflagellates and other

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encysting organisms in ballast water. While those analyses also reveal that certain coastal taxa are

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significantly reduced by BWE, the relatively small overall shifts in biodiversity between managed and

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unmanaged vessels are reflective of incomplete biotic turnover associated with BWE, as is the presence

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of a number of coastal taxa of concern in unexchanged ballast (Table 3).

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Invasion risk to Alaska associated with ballast water. A substantial volume of BW is discharged into

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Alaskan waters, with one study providing a conservative estimate of approximately 60 million metric

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tons discharged between 1999 and 200319. This may pose considerable risk of new species introductions

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to the state, representing a particularly difficult challenge for environmental policy51. Of particular

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concern is intra-coastal domestic traffic from highly invaded estuaries in California, Oregon, and

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Washington states. Voyages among these ports have been shown to pose high risk of secondary spread

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of established coastal invasive species17, and one study of BW entering Puget Sound revealed that

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domestic vessels carried significantly higher densities of high risk taxa than did ships transiting the

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Pacific18. Thus, while much of the BW being discharged into Alaska may derive from foreign arrivals19,

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relatively short voyage lengths and dense assemblages of non-native species associated with Pacific US

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source ports render these routes particularly problematic. This flux of propagules associated with vessel

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traffic is unlikely to diminish in the future without significant changes in current BW management,

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especially given the widely recognized opening of arctic ports, as well as warming trends that may

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extend the range limits of potentially invasive species21.

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Our analysis suggests that BWE is an incompletely protective strategy for managing this risk. As noted

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above this limitation has been previously recognized, and explains in large part the current status of

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BWE as an interim measure pending full implementation of BW treatment systems. Despite the

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anticipated shift to numerical discharge standards, understanding the risks associated with current BW

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management practices may provide valuable information for those tasked with anticipating the

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likelihood of new introductions. This is particularly important given that the current risk profile

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associated with BWE, as depicted here and elsewhere, may remain essentially unchanged for several

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years while vessels move toward compliance with new regulations.

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We clearly demonstrate that BWE has significant effects on phyto- and zooplankton assemblages, and

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has the capacity to reduce some coastal taxa and replace them with open ocean taxa. This result

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suggests that, all else being equal, greater application of best BWE practices (e.g. greater compliance

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with BWE outside of 200 nautical miles, fewer exemptions, etc.) should decrease risk of potentially

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damaging introductions to AK. Nevertheless, this risk cannot be reduced to zero. Overall, BWE appears

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to have modest effects on BW diversity, and is incapable of removing all coastal taxa of potential

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concern from ballast tanks. Of the small number of taxa identified as posing particular risk to AK based

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on their known history as invasive or injurious species, only one polychaete genus exhibited significantly

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lower raw sequence count in exchanged as opposed to unexchanged ballast (Table 3). Our results

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therefore suggest the possibility of ballast-mediated transport of these taxa into Alaskan waters, even

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on vessels that have undergone BWE. However, we recommend caution in interpreting these results

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given the limitations of the HTS method noted below.

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Our detailed analysis of sequence data provides more thorough assessment of confidence in taxonomic

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assignments for potentially troubling OTUs based on available reference sequences. Among those taxa

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of concern designated moderate or high confidence (Table 3), one (Parvilucifera sinerae) is an alveolate

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parasite that infects a wide range of dinoflagellate species, and is thus potentially capable of causing

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significant shifts in food webs, given the importance of its host species to primary productivity in those

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systems52. Notably, this species has been previously described from BW arriving to the Atlantic coast of

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the US29. Four other taxa of concern (Palaemon sp., Membranipora mebranacea, Pseudopolydora

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paucibranchiata, and Ruditapes philippinarum) are recognized introductions to North America, with

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both Palaemon spp. and R. philippinarum exhibiting known invasive characteristics in their non-native

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ranges53-55; none, however, have yet been reported from Alaska. Pseudopolydora paucibranchiata and R.

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philippinarum are already present on the Pacific coast from California through British Columbia40, and at

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least one Palaemon species (P. modestus) is a highly impactful non-native in estuaries from central

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California through Washington state55; propagules of these taxa would therefore be expected to be

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available for ballast-mediated transfer to Alaska. Our results are thus consistent both with previous

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reports of potentially injurious species transported in BW and with known distributions of introduced

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species in the source region. However, our analysis provides only a preliminary and incomplete account

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of the taxa of potential concern present in the ballast tanks of vessels entering Valdez, since (a) we only

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sampled a small subset of arriving vessels in a two-year period, (b) taxonomic assignment was only

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possible for a fraction of detected sequences, and (c) non-native species are continuing to invade source

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ports, especially those in California, which is a global hotspot for invasions17.

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Utility of HTS methods for ballast water monitoring. The application of HTS and the adoption of 18S as

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a target metabarcoding locus has allowed us to investigate broadly the taxonomic composition of BW

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samples, facilitating comparisons that elucidate patterns associated with BW transport and its

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management. In addition to demonstrating the ability of this approach to recognize signatures of biotic

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turnover associated with BWE—signatures that incorporate both zooplankton and phytoplankton taxa—

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we further establish the capacity of HTS to distinguish between BW sources at relatively fine geographic

316

resolution. Ordination analyses reveal clear clustering of samples derived from different regions in

317

Pacific North America, and despite limited sampling suggest the possibility of distinguishing even

318

between different ports within those regions (Figure 4). To our knowledge, this is the first time such

319

resolution in BW source tracking has been clearly demonstrated, either with HTS or any other method

320

(though see below). Interestingly, these signals of source biota are partially obscured by the effects of

321

BWE, again reflecting the impact of management on BW diversity.

322

These advances build on a growing literature illustrating the value of HTS for BW research. For instance,

323

multiple metabarcoding studies of ballast being transported in a single vessel from the North Sea to

324

South Africa56-58 provided evidence of the presence of potentially invasive metazoan taxa, including the

325

European mudsnail Peringia ulvae and the red alga Polysiphonia. Other researchers have utilized HTS to

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investigate changes in ballast water communities during lengthy voyages59. HTS has similarly been

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employed to identify protistan taxa in BW, including a diverse assemblage of parasitic and potentially

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harmful species29. In one particularly comprehensive study, Pagenkopp Lohan et al60 described protistan

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diversity across more than three dozen vessels entering three US ports, revealing surprisingly high

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microbial diversity and considerable variation in community composition associated with different

331

recipient systems.

332

Most HTS analysis of ballast has focused on bacterial diversity, variously revealing relationships between

333

community composition in ballast and coastal source environments61, diversity present in ballast tank

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sediments62, and the efficacy of BW treatment63. Perhaps the most extensive analysis of bacterial

335

communities was recently reported by Lymperopoulou and Dobbs64, who assessed diversity on 17

336

vessels arriving to the US from diverse European and North American sources. Similar to the current

337

study, that work detected some signal of source diversity in ordination and clustering analyses, most

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clearly among North American vessels that had not undergone BWE, suggesting that 1) HTS is capable of

339

distinguishing sources based on bacterial diversity and 2) BWE likely obscures that source signal by

340

altering microbial community composition. Our analysis of a more extensive and yet geographically

341

constrained sample set has allowed us to more clearly demonstrate the power of HTS to identify these

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ballast source signals and the changes associated with management.

343

Results of indicator taxa analysis further suggest the possibility that HTS-based tools may be developed

344

to supplement existing methods for BWE verification. Currently available verification methods adopt

345

chemical tracers that exhibit significant changes between exchanged and unexchanged ballast, allowing

346

discrimination of coastal from oceanic BW in a large majority of cases65, 66. Similar approaches based on

347

shifts in biodiversity have thus far remained largely unexplored, in part due to insufficient breadth and

348

resolution of traditional approaches for biodiversity assessment. As illustrated here, HTS-based

349

approaches may provide the necessary taxonomic detail to identify biotic indicators of effective

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exchange. However, it remains to be seen how generalizable this approach might be across broader

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source biogeography; investigating its utility will necessitate generation of HTS data from a much more

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diverse sample of vessels, to determine if universally applicable predictive models can be developed.

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Despite the increasingly apparent utility of HTS for describing diversity present in BW, several

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methodological limitations persist26, 27, 58. These are perhaps best illustrated by considering the

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identification of taxa of concern entering Alaskan waters. First, with current methods it is impossible to

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distinguish between living or dead organisms being released with ballast into Valdez56. This limitation is

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not unique to HTS analysis; generally, methods capable of assessing viability are restricted to compliance

358

testing contexts, in which case taxonomic identity of living organisms may remain undetermined26.

359

Second, HTS approaches cannot provide confident measures of abundance, either absolute or relative. A

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number of metabarcoding studies have demonstrated that sequence counts can, in some cases,

361

correlate reasonably well with abundance counts based on morphological examination or experimental

362

design67-69. In general, however, the capacity of HTS to provide reliable estimates of abundance across

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taxa and ecosystems remains unclear. Together, these two considerations recommend caution in

364

interpreting the results of our analyses identifying taxa of concern, and suggest that in this context HTS

365

should be adopted primarily as an early indicator of potential risk, to be followed up with additional

366

surveys. Third, our results suggest that bioinformatic assignment of taxonomic names to OTUs should be

367

interrogated rigorously, as limitations of reference databases and classification algorithms may

368

sometimes result in false or misleading classifications. This is particularly important for primer sets such

369

as 18S, which exhibit broad taxonomic coverage but relatively low resolution, and which may be poorly

370

represented in sequence databases for many groups. It is also important to note that our approach of

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clustering sequences into OTUs, while particularly useful for assessing overall richness and comparing

372

patterns in community structure, has been shown to render some species undetectable at very low

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sequence abundances70. This approach is thus likely to bias results toward Type II error (false negatives)

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and potentially missing rare non-native taxa, while limiting the likelihood of Type I error (false positives);

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it should thus be considered a conservative approach to identifying potential taxa of concern. Finally,

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taxonomic biases in DNA amplification associated with even “universal” primer sets guarantee that taxa

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will be over- or under-represented, or even completely missed, resulting in false negative detections of

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potential taxa of concern57, 58. This consideration highlights the potential importance of employing

379

multiple primer sets to obtain more complete estimation of taxonomic composition. The analyses

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presented here, while revealing the value of primer sets that offer broad representation of ballast taxa

381

for pattern detection and hypothesis testing, also underscore the potential limitations of that approach

382

for identifying particular species of concern.

383

SUPPORTING INFORMATION

384



Detailed molecular methods

385



Detailed bioinformatic methods

386



Figure illustrating ordination analyses based on presence/absence data

387



Figure illustrating Mantel tests for correlation between beta diversity and geographic distance

388



Figure comparing phylum-level diversity between unexchanged and exchanged ballast

389



Figures illustrating neighbor joining trees for taxa of concern highlighted in Table 3.

390

ACKNOWLEDGEMENTS

391

Sample collection was funded by an award from the United Station Coast Guard to G. Ruiz. K. Lohan is a

392

Robert and Arlene Kogod Secretarial Scholar. Authors would also like to thank Kim Holzer and Danielle

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Verna for additional sample collection, and R. Martin for advice on statistical analyses. Assistance with

394

vessel access and sample collection was provided by Alyeska Valdez Marine Terminal (Mr. B. Roberts),

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Alaska Tanker Company (Mr. M. Meadors), SeaRiver Maritime (Ms. A. Fruschetto and Mr. J. Pace),

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ConocoPhillips Polar Tankers (Mr. M. Morgan) and Prince William Sound Community College (Dr. J.

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Fronzuto and Mr. S. Shiell). The United States Environmental Protection Agency, through its Office of

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Research and Development, supported the research described here. Though it has been subjected to

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Agency administrative review and approved for publication, its content does not necessarily reflect

400

official Agency policy. This manuscript benefitted from discussions at the meeting of the International

401

Council for the Exploration of the Seas (ICES) Working Group on Ballast and Other Ship Vectors held in

402

Madeira, Portugal in 2018.

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FIGURE and TABLE LEGENDS

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FIGURE 1. Locations of BW uptake. Blue indicates uptake at the voyage source for vessels not

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undergoing BWE; red indicates location of BWE for all other vessels. Symbol shape reflects the source

406

region for each voyage, including those undergoing BWE (AK = Alaska, PS = Puget Sound, OR = Offshore

407

Oregon, SFB = San Francisco Bay, LA = Los Angeles). Destination for all voyages is Valdez, AK, indicated

408

by the star. Coastline and national boundaries map obtained using the worldHires function in the

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mapdata package of R.

410

FIGURE 2. OTU accumulation curves based on vessels entering Valdez. A) Curve for vessels undergoing

411

BWE; B) curve for unmanaged vessels. Shaded area shows 95% confidence interval; confidence interval

412

and box and whisker plots for individual points are based on 1000 permutations of sites added in

413

random order. Overall diversity was not significantly different between managed and unmanaged

414

ballast.

415

FIGURE 3. Ordination analyses. A) Non-metric dimensional scaling (NMDS) plot of all samples based on

416

Bray-Curtis distance determined from log-transformed OTU abundance; blue circles indicate vessels that

417

have not undergone BWE, red circles indicate vessels that have undergone exchange. Ellipses show 95%

418

confidence interval around the centroid for “exchange” and “no exchange” clusters. B) Redundancy

419

analysis (RDA) showing effect of BWE on beta diversity at the family level. Blue and red circles indicate

420

management status as in (A), grey circles represent families; diamonds indicate cluster centroids.

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Sample clusters are delineated by grey polygons, and solid ellipses indicate 95% confidence interval

422

around the centroid.

423

FIGURE 4. NMDS of vessels not undergoing BWE (A) or undergoing BWE (B), based on Bray-Curtis

424

distance generated from log transformed OTU abundance data. Symbol colors indicate source ports as

425

shown in the legend at right. Gray polygons represent source region clusters, with dashed ellipses

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indicating 95% confidence interval around the cluster centroids. Note that ellipses collapse to lines when

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there are fewer than three vessels per cluster. Effect of source port on diversity, A) adonis R2 = 0.7346, P

428

< 0.001; B) adonis R2 = 0.3703, P = 0.0089.

429

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430 431

432 433 434

FIGURE 1.

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435 436 437

FIGURE 2.

438 439

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440 441

FIGURE 3.

442

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443 444 445

446 447

FIGURE 4.

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448

Correlations

Partial correlations

Explanatory variable(s) D.f. BWE 1 source 11 BWloc 1 BWE + source 12 BWE + BWloc 2 source + BWloc 12 BWE + source + BWloc 13 BWE | source + BWloc 1 source | BWE + BWloc 11 BWloc | source + BWE 1

Adjusted R2 0.0455 0.2225 0.0434 0.2567 0.0902 0.2305 0.2604 0.0299 0.1702 0.0037

P 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.004 0.001 0.296

450 452 454

TABLE 1. Results of variation partitioning using redundancy analysis ordination. BWE = ballast water exchange (yes or no), source = source port, BWloc = latitude of ballasting operations (either location of exchange or location of initial uptake in the case of vessels not undergoing exchange), D.f. = degrees of freedom. Residual variation was 74%.

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Families associates with unexchanged ballast Sagittidae Clausidiidae Lichomolgidae Mysidae Xarifiidae Philinidae Ostreidae Pharidae Triticellidae Bougainvilliidae Dendronotidae Diadunenidae Hippolytidae Pseudodiaptomidae Phyllophoridae

A 0.8582 0.9816 0.8677 0.9174 0.9848 1 0.986 1 1 0.9972 0.9723 0.9698 1 1 1

B 0.7619 0.5238 0.5714 0.4762 0.4286 0.381 0.381 0.3333 0.3333 0.3333 0.3333 0.3333 0.2857 0.2857 0.2381

I 0.809 0.717 0.704 0.661 0.65 0.617 0.613 0.577 0.577 0.577 0.569 0.569 0.535 0.535 0.488

P value 0.009 0.013 0.047 0.037 0.016 0.008 0.036 0.009 0.01 0.05 0.039 0.029 0.014 0.022 0.039

RDA1 0.52 0.48 0.27 0.76 0.50 0.37 0.48 0.32 0.19 0.29 0.24 0.24 0.43 0.20 0.13

Common name Arrow worms Copepods (parasitic) Copepods (parasitic) Mysid shrimps Copepods (parasitic) Sea slugs Oysters Clams Bryozoans Hydroids Sea slugs Anemones Shrimps Copepods Sea cucumbers

** * * * * ** * ** ** * * * * * *

P value 0.006 0.008 0.001 0.024 0.001 0.001 0.015 0.001 0.004 0.007 0.004 0.012 0.024 0.03 0.034 0.048

RDA1 -0.90 -0.79 -0.63 -0.72 -0.45 -0.77 -0.58 -0.49 -0.42 -0.28 -0.23 -0.57 -0.24 -0.18 -0.11 -0.09

Common name Copepods Diatoms Dinoflagellates Diatoms Dinoflagellates Dinoflagellates Diatoms Diatoms Diatoms Cryptophytes Dinoflagellates Copepods Fungi Protozoans Dinoflagellates Nematodes

** ** *** * *** *** * *** ** ** ** * * * * *

Families associated with exchanged ballast Ectinosomatidae Chaetocerotaceae Gymnodiniaceae Rhizosoleniaceae Kareniaceae Gonyaulacaceae Skeletonemataceae Corethraceae Asterolampraceae Geminigeraceae Amoebophryaceae Eucalanidae Basidiobolaceae Plasmodiophoridae Peridiniaceae Tripyloididae

A 0.9789 0.9634 0.971 0.9895 0.913 0.7954 0.9772 1 0.9962 0.8413 1 0.9843 0.9957 0.91 0.8537 1

B 0.8889 0.8889 0.8333 0.7222 0.7778 0.8889 0.7222 0.5 0.4444 0.5 0.3889 0.3889 0.3333 0.3333 0.3333 0.2222

I 0.933 0.925 0.9 0.845 0.843 0.841 0.84 0.707 0.665 0.649 0.624 0.619 0.576 0.551 0.533 0.471

456 458 460 462

TABLE 2. Taxa at the family level statistically significantly associated with either unexchanged (top) or exchanged (bottom) ballast water. A, the likelihood of a sample belonging to the test group (exchanged vs. unexchanged) assuming the presence of the family (indicator specificity); B, the likelihood of the family being present in a sample belonging to the test group (indicator sensitivity); I, IndVal association index; RDA1, score along RDA axis (separating clusters with and without BWE, see Figure 3); stars indicate significance level based on P values; *, p < 0.05, **, p < 0.01, *** p < 0.001. Total number of families examined was 234.

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Assignment confidence low

with BWE (overall count/# vessels) 434/10

without BWE (overall count/# vessels) 183/3

OTU# 307

Taxon Alexandrium hiranoi

437

Capitella sp.

low

2/1

203/8

345

Hematodinium sp.

low

124/7

115/5

415

Membranipora membranacea

moderate

43/9

521/8

862

Neomysis integer

low

0/0

125/1

93

Palaemon sp.

high

1450/1

2318/4

209

Parvilucifera sinerae

high

258/9

285

Pseudopolydora paucibranchiata

high

132

Pseudopolydora reticulata Ruditapes philippinarum

223

reasons for concern Members of the genus Alexandrium are known to produce toxins responsible for causing Paralytic Shellfish Poisoning (PSP) in humans that ingest affected shellfish. Other species of this genus are known harmful taxa in AK.

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References 71

Multiple species of the genus are cryptogenic along the Pacific coast of North America. Parasitic dinoflagellates in Syndiniales. Members of the genus infect a wide range of wild and commercially exploited crustaceans. One Hematodinium species is known from AK; however this does not appear to be the same species and is the first record of Hematodinium in ballast water. Encrusting bryozoan known to foul kelp species, reducing growth and damaging fronds; potential to affect natural populations and commercial farms. Known invasive in eastern US. European native not known from North America, but history of introduction in the Mediterranean and northern Europe The genus is a known introduction to the North American west coast. P. modestus has become a dominant species in Sacramento-San Joaquin Delta in CA, outcompeting native species and threatening food webs that may impact Pacific salmon.

40, 72

911/8

Generalist parasite (Alveolata) of dinoflagellates; previously reported from ballast water.

52

245/7

557/9

Known introduction to North America from CA to BC. Unknown impacts, but could displace native species.

40

high

2153/7

529/10

Native to Taiwan, not known from North America.

76

moderate

207/10

1238/14

Known introduction from CA to BC. May outcompete native bivalves and alter food webs.

53, 54

464

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74

75

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468 470 472

TABLE 3. OTUs assignments indicating taxa of concern. Assignment confidence is based on qualitative examination of Neighbor Joining trees generated from 18S sequences of related congeneric taxa pulled from GenBank. Low confidence indicates that tree clustering is inconsistent with initial assignment. Moderate confidence indicates that NJ trees are consistent with initial assignment, but do not provide additional support due to lack of data (low sequence representation in GenBank) or poor resolution of the tree. High confidence indicates that initial assignments are further supported by reasonably resolved trees. Also indicated are the raw sequence counts in both exchanged and unexchanged BW samples, along with the number of vessels in each category.

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474 476 478 480 482 484 486 488 490 492 494 496 498 500 502 504 506 508 510 512 514 516 518

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