Uncovering the hidden within shipping containers: Molecular biosurveillance confirms a pathway for introducing multiple regulated and invasive species.

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Yoamel Milián-García, Cassandre Pyne, Ashley Chen, Kate Lindsay, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4618423/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Feb, 2025 Read the published version in Biological Invasions → Version 1 posted 5 You are reading this latest preprint version Abstract The negative ramifications of invasive alien species (IAS) are considered the second-most cause of biodiversity extinction and endangerment after habitat modification. IAS movements are mainly anthropogenically driven (e.g., transport of shipping containers) and require fast detection to minimize damage and cost. The present study is the first to use molecular biosurveillance of international shipping containers to detect IAS and regulated species identification in Canada. Thirty-eight samples were collected from debris (soil, stems, seeds, individual specimens) found in containers arriving in Canada. A multi-marker approach using COI, ITS, ITS2, and 16S was used to identify four main taxonomic groups: arthropods, fungi, plants, and bacteria, respectively. Eleven IAS species were identified via metabarcoding based on environmental DNA samples, including two arthropods, six fungi, two plants, and one bacteria. The origin of the eDNA detected from each species was linked to their native distribution and country of origin, except for Lymantria dispar . Four physical specimens were also collected from shipping container debris and DNA barcoded, identifying three non-regulated species (two arthropods and one fungus). Altogether, these results demonstrate the importance of integrating molecular identification into current toolkits for the biosurveillance of invasive alien species and provide a set of validated protocols ready to be used in this context. Additionally, it reaffirms international shipping containers as a pathway for multiple invasive aliens and regulated species introduction in Canada. It also highlights the need to establish regular and effective molecular biosurveillance at the Canadian border to avoid new or recurrent invasions. Biosurveillance Invasive alien species shipping containers DNA barcoding eDNA metabarcoding arthropod fungi bacteria Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction The adverse effects of invasive alien species (IAS) are recognized as a leading cause of large-scale biodiversity and economic losses (Clavero and García-Berthou 2005 ; Reid et al. 2021 ). The International Union for the Conservation of Nature (IUCN) associated the harmful effects of IAS with around 54% (91 out of 170) of documented animal species extinctions (Clavero and García-Berthou 2005 ). Consequently, IAS are a problem of global importance (Westfall et al. 2020 ), and concerns about their adverse effects are exacerbated as we face a biodiversity crisis and economic instability. The financial burden associated with managing and mitigating IAS totals CAD 187 million annually in Canada alone, with projections estimating an increase of up to CAD 34.5 billion yearly (Colautti et al. 2006 ). In Canada, the Canadian Food Inspection Agency (CFIA) primarily handles terrestrial IAS biosecurity and management (Reid et al. 2021 ). The CFIA Plant Health business line conducts regular biosurveillance for early detection of IAS, including fungi, bacteria, plants, arthropods, or animals, which may impact native ecosystems or the agricultural livestock sector (Milián-García et al. 2020 ; Milián-García et al. 2023 ). Currently, there are 272 federally regulated terrestrial species in Canada, excluding aquatic invasive species (Government of Canada 2023), including both invasive and regulated species. The latter includes species with a recognized potential to become invasive. For simplicity, we here refer to both CFIA-regulated and invasive species as “IAS.” Early detection and management of IAS are essential to minimize associated costs and damage; this can only be done effectively by having precise knowledge of the pathways by which an IAS can be introduced (Saul et al. 2017 ; Reid et al. 2021 ). Pathways refer to routes by which species move from one locale to another, either within a country or between countries (McNeely et al. 2001 ). In contrast, vector refers to the physical means or agent (i.e. aeroplane, ship, etc.) in or on which a species moves outside its native range (past or present) (Canada 2015a ). The first stage of species invasion consists mainly of human-mediated species movement from one geographical location to another (Blackburn et al. 2011 ). The international transport of shipping containers is a recognized pathway for IAS introduction, as IAS can access containers and remain hidden for extended periods (Paini and Yemshanov 2012 ). In an era of globalization, biosurveillance of IAS should be fast enough to cope with the speed of international trade (Hulme 2009 ). The delayed identification of an IAS before or during its establishment leads to more detrimental impacts on native biodiversity, ecosystem services, and the economy. Traditional detection of IAS (e.g., morphological identifications and direct field observations) is time-consuming and requires taxonomic expertise, which is difficult to unify for multiple taxonomic groups. These traditional methods are considered labour-intensive, are limited in the early stages of invasions, require morphological integrity or preservation of key traits, and are usually only feasible at particular life stages of a given IAS (e.g., adults). Primary limitations of morphological-based methods can also be influenced by the patchy distribution of IAS (Westfall et al. 2020 ), their presence in small numbers, and the lack of taxonomic keys at life stages other than adulthood. In addition, border control can only examine a small subset of containers; for example, as of 2005, it was estimated that only 2% of shipping containers were inspected at the United States border (Work et al. 2005 ). DNA-based identification strategies, including DNA barcoding and metabarcoding, can help to overcome the limitations mentioned above by using standardized DNA fragments for species identification through comparison to reference databases (Hebert et al. 2003 ). Environmental DNA (eDNA) metabarcoding is a DNA barcoding-based molecular technique for multi-species identification. This approach supports the analysis of complex samples in a high-throughput manner for species identification from mixed DNA released by the species into their environment. These methods allow for detecting an IAS regardless of life stage and morphological integrity and do not require taxonomic expertise when traditional taxonomy information has already been linked to molecular data in reference repositories. Consequently, DNA reference databases (e.g., The Barcode of Life Data System [BOLD]) are considered permanent repositories of molecular and traditional taxonomic data that allow the identification of unknown sequences to known reference data. Previous studies have used eDNA to detect aquatic IAS from ballast water in shipping vessels or water or sediment from shipping ports (Egan et al. 2015 ; Brown et al. 2016 ; Borrell et al. 2017 ; Grey et al. 2018 ; van den Heuvel-Greve et al. 2021 ; Gargan et al. 2022 ). However, fewer studies are specifically designed to detect terrestrial IAS. In this study, we aim to assess the capacity and effectiveness of eDNA metabarcoding to detect terrestrial IAS eDNA using shipping containers as a vector. This is the first study in Canada to assess eDNA as a tool for early screening of terrestrial IAS in shipping containers. Here, a combination of DNA barcoding and eDNA metabarcoding was employed for molecular biosurveillance of international shipping containers to address the following research questions: i- Can molecular biosurveillance methods be effective for the identification of invasive alien or Canadian-regulated species in a regulatory/early screening of international shipping containers?; if so, ii- What is the diversity of invasive alien or Canadian-regulated species using shipping containers transportation pathways? Materials and Methods Sampling Thirty-eight samples were collected from shipping containers arriving in Canada from six countries between 2020 (N = 28) and 2021 (N = 10). Sample size per country of origin varied as follows: Germany (N = 21), China (N = 10), Taiwan (N = 2), Ghana (N = 1), Iran (N = 1), and one undisclosed country of origin (N = 3). Thirty-one of the 38 samples were soil debris (hereafter soil samples) collected from the containers at the Canadian border. In addition, two bags of seeds, one bag of stems, one insect larva, one snail, and one tissue fragment were all collected from containers shipped from Germany. The snail and insect larva samples were collected from the same shipping container. The last non-soil sample, consisting primarily of bark, was obtained from a container that originated in China. All samples were deposited in Whirl Pak or Ziplock bags and sent to the Hanner Laboratory at the University of Guelph. Once received, samples were stored at -80°C until laboratory processing. eDNA extraction DNA was extracted from tissue samples obtained from the insect larva and snail using the DNEasy Blood and Tissue kit (Qiagen), following the manufacturer’s instructions. All soil samples were extracted using the DNeasy PowerSoil Pro kit as follows. Every soil sample was subsampled thrice into approximately 250 mg samples. They were placed into individual PowerBead Pro tubes, and 800 µL of Solution CD1 was added to each tube and vortexed thoroughly for 10 seconds. Samples were made homogenous using the TissueLyser II at 25 Hz for 5 minutes. The adapter was reoriented, and the process was repeated at 25 Hz for another 5 minutes. The tubes were centrifuged at 15,000 g for 1 minute, then transferred the supernatant, with a maximum volume of 600 µL, to a clean 2 mL microcentrifuge tube. After this, 200 µL of solution CD2 (stored at 4°C) was added, and tubes were vortexed for 5 seconds. Then, tubes were centrifuged at 15,000 g for 1 minute, and the supernatant was transferred into a clean 2 mL microcentrifuge tube while avoiding the pellets. 600 µL of solution CD3 was added, and the tubes were vortexed briefly. 650 µL of the lysate was loaded onto an MB Spin Column and centrifuged at 15,000 g for 1 minute, and the flow-through was discarded. This step was repeated to ensure all the lysates had passed through the column. The spin columns were then carefully placed into clean 2 mL collection tubes to avoid splashing and contamination. 500 µL of solution EA was added to the spin column and centrifuged at 15,000 g for 1 minute. The collection tube and flow-through were discarded, and the MB spin columns were placed back into the same 2 mL collection tube. 500 µL of solution C5 was added to the MB spin column and centrifuged at 15,000 g for 1 minute, and the collection tube and flow-through were discarded. The MB spin column was then placed into a new 2 mL collection tube and centrifuged at 16,000 g for 2 minutes, then placed into a new 1.5 mL DNA LoBind tube (Eppendorf) rather than a 1.5 mL elution tube to prevent the binding of DNA to the wall of the tube. We then added 100 µL of solution C6 in the center of the white membrane to ensure complete elution of DNA from the MB Spin Column filter membrane. This process was concluded by centrifuging at 15,000 g for 1 minute and discarding the spin column. DNA extracts were quantified (ng/ul) by fluorometry using a Qubit dsDNA High-Sensitivity Assay kit in a Qubit 4 fluorometer. DNA barcoding DNA extracted from individual specimens or specimen fragments was used for molecular identification using versatile COI primers and PCR cycling conditions previously described (Folmer et al. 1994 ), with slight modifications as follows: each PCR reaction contained 5 uL of each primer (LCO1490 and HCO2498 at 1 uM), 12.5 uL of 2x High-Fidelity Kapa Master Mix, and 2.5 uL of DNA template. PCR products were cleaned up using magnetic beads (Machery-Nagel) at a 1x ratio following the manufacturer's instructions. The purified PCR products were then Sanger sequenced in both directions at the Advanced Analysis Center at the University of Guelph. eDNA metabarcoding DNA libraries were prepared for metabarcoding analysis using four molecular markers: 16S (for bacterial identification), ITS (for fungi identification), ITS2 (for plant identification) and COI (for arthropod identification), and following protocols previously established in the Hanner laboratory (Milián-García et al. 2020 ), with only a few modifications as indicated below. Cycling conditions for the first PCR of metabarcoding library preparation for 16S, ITS, and COI were indicated in Milián‐García et al. 2020, while conditions for ITS2 can be found in Chen et al. 2010 . PCR products were checked on 2% agarose eGels after every PCR and after every clean-up, using 5 uL of the product in each case. After the first and second PCR, clean-ups were conducted with a 1x ratio of magnetic beads (Machery-Nagel) following the manufacturer’s protocol. Each index PCR reaction contained 5 uL of a pre-prepared mix of index primers (10 uM), 25 uL of 2x High-Fidelity Kapa Master Mix, 15 uL of water, and 5 uL of cleaned-up DNA/amplicon template. Cycling conditions for all index reactions were as follows: 95°C for 180s, followed by eight cycles at 95°C for 30s, 55°C for 30s and 72°C for 30s, and a final extension at 72°C for 300s. An Illumina MiSeq System with a MiSeq reagent kit v3 (600 cycles) was employed for sequencing the samples. To maximize efficiency and cost-effectiveness, each sample was allocated a maximum of 1% of the total sequencing capacity per run, enabling the simultaneous sequencing of up to 100 samples in a single MiSeq run. After the sequencing process, the MiSeq Reporter software was utilized for demultiplexing, which involved separating the sequencing data based on unique sample identifiers, ensuring that the reads from each sample were correctly assigned and segregated. Additionally, the software performed adapter trimming, removing the artificial sequences added during library preparation from the raw sequencing data. The output of this process was a set of two paired-end raw FASTQ files for each sample, containing the sequencing reads ready for further analysis and processing. Data analysis QIIME2 v2023.7 was used to determine if any IAS were present in the shipping container samples, based on ITS and 16S (Bolyen et al. 2019 ). QIIME2 is a bioinformatics platform that uses paired-end sequences to retrieve taxonomic assignments while also storing data provenance information. Input is taken as paired-end sequences that are primer and quality trimmed and filtered, paired, dereplicated and clustered using Vsearch. Primer trimming was achieved using pattern-match trimming with CUTADAPT. The parameters used in QIIME2 are as follows: (1) trimming (error rate: 0.1, overlap: 3), (2) pairing (quality: 20, max number of Ns: 3, min length: 200bp, min overlap: 25), (3) filtering (min quality: 20). To retrieve taxonomic identifications of sequences, a ribosomal database (RDP) classifier was used with QIIME2’s feature-classifier plugin. For 16S, a pre-trained RDP classifier using sequences from Greengenes2 v2022.10 was used. For ITS, a pre-trained RDP classifier using sequences from UNITE v8.3 was used (Nilsson et al. 2019 ). To complement the analysis in QIIME2 for 16S and ITS, MetaWorks v1.12.0 was also used to analyze the COI samples (Porter and Hajibabaei 2022 ). MetaWorks can be used for 16S, ITS, and COI since it can use different RDP classifiers for taxonomic assignment (Wang et al. 2007 ). Raw paired-end reads are trimmed using CUTADAPT, then de-replicated and denoised using VSEARCH. For COI, a pre-trained RDP classifier was used (v5.1.0) ( https://github.com/terrimporter/CO1Classifier ) for taxonomic assignment, accessed August 1, 2023. For 16S, a pre-trained RDP classifier using sequences from NCBI was used ( https://github.com/terrimporter/16SvertebrateClassifier ) , accessed August 1, 2023. Lastly, the ITS pre-trained RDP classifier was trained using UNITE sequences (v2) ( https://github.com/terrimporter/UNITE_ITSClassifier ) , accessed August 1, 2023. We also used the PLANiTS ITS pre-trained classifier (v1.1.1) ( https://github.com/terrimporter/PLANiTS_ITSClassifier ) , accessed August 1, 2023. The parameters for each marker in MetaWorks used the same reference parametrization as in previous studies (Milián-García et al. 2023 ): (1) pairing (min quality: 20; min overlap; 25, the max fraction of mismatches: 0.02; min fraction of overlap: 0.90); (2) trimming and filtering (min length: 200bp; error rate: 0.1; end quality score: 20,20; min adapter overlap: 3; max number of Ns). DNA barcoding Bidirectional sequences generated with Sanger sequencing were individually analyzed and 5´and 3´manually trimmed based on quality using Geneious Prime 2023.2.1 ( https://www.geneious.com ). Forward and reverse sequences were aligned using MAFFT v7.490 and keeping parameters by default as implemented in Geneious Prime 2023.2.1 ( https://www.geneious.com ). Consensus sequences were manually inspected for ambiguities, and in instances of poor alignments, only the strand with the higher quality was used as a reference for posterior molecular identifications. Consensus sequences obtained from the alignments and without ambiguities were used for molecular identification through the BOLD System ( http://www.boldsystems.org/index.php ) and BLASTn against NCBI’s nucleotide database as implemented in Geneious Prime 2022.2.2 ( https://www.geneious.com ). Results Molecular species identification Successful DNA extractions were completed from all the samples analyzed despite suboptimal conservation before sampling, as samples from shipping containers experience varying temperatures and remain in the containers for long periods, enhancing DNA degradation. Average DNA concentrations per sample processed ranged from 0.05 to 38.10 ng/ul. A total of 37,147,820 COI reads, 64,411,024 ITS reads, 38,525,960 ITS2 reads, and 33,275,010 16S reads were generated from the 32 soil samples for the metabarcoding analysis, plus any sequences observed in the controls. The distribution of reads per sample, molecular marker, and technical replicate are shown in the Supplementary Information (Online Resource 1). Rarefaction curves generated for all the samples and per molecular marker reached a plateau, suggesting that sequencing depth was enough to maximize the recovery of the exact sequence variants diversity given the primers chosen (Fig. 1 ). No sequence reads were observed in the extraction negative controls when processing the samples with all the markers but ITS. In contrast, a considerable number of reads were obtained from the COI and ITS2 PCR negative and sequencing controls, respectively. However, none of the reads in these negative controls were assigned to a molecular operational taxonomic unit (MOTU), indicating only spurious amplification, chimeras, and low-quality reads that did not pass any of the quality controls rather than cross-contaminations (Fig. 2 ). Single-species (DNA barcoding) and multispecies (eDNA metabarcoding) identifications Three taxa were identified by DNA barcoding the specimens or parts of specimens found in the shipping containers as follows: Tipula sp., Cepaea nemoralis , and Cercospora sojina (Table 1 and Fig. 3 ). Table 1 Summary of sample ID, country of container origin, length of the DNA barcode region generated, GenBank accession number for the deposited sequence, BOLD and GenBank molecular-based identifications, including percentage of mean similarity [MS(%)] and percentage of identity [PI(%)], query cover, and GenBank accession number of the top BLAST hit. Sample ID Country Seq Length GenBank Accession # BOLD ID MS (%) GenBank ID PI (%) Query cover Top hit accession # 1-L Germany 629 bp PP330842 Tipula irrorate 100 Tipula confusa 100 100% OY744480.1 1-S Germany 631bp PP330843 Cepaea nemoralis 100 Cepaea nemoralis 99.67 100% KC954854.1 1-F Germany 496 bp PP330844 Cepaea nemoralis 98.89 Cepaea nemoralis 94.35 100% MH980029.1 0002-C China 661 bp XXXX N/A N/A Cercospora sp. 83.80 98% OK075294.1 Multispecies identification based on COI marker detected eDNA from two arthropods ( Lymantria dispar and Ips typographus ) and one fungus ( Fusarium oxysporum ) using two bioinformatics pipelines for metabarcoding data analysis (Table 2 and Fig. 4 ). eDNA from five additional fungi ( Puccinia coronata , Puccinia graminis , Gremmeniella abietina , Urocystis agropyri , and Venturia nashicola ) was identified using the ITS molecular marker plus one plant ( Dioscorea polystachya ) [Table 2 and Fig. 5 ]. Besides, eDNA from one additional plant invasive species ( Senecio inaequidens ) and one bacteria ( Clavibacter michiganensis ) was identified based on ITS2 (Table 2 and Fig. 6 ) and 16S (Table 2 and Fig. 7 ), respectively. ITS2 also confirmed Fusarium oxysporum detection based on eDNA present in the container samples. Table 2 Summary of the number of samples, exact sequence variant (ESV) count, and bootstrap support associated with the molecular identification of every invasive alien species. COI, MetaWorks ESV Number of Samples ESV count Sequence Species Bootstrap Zotu4858 1 5 Online Resource 2 Lymantria dispar 1 Zotu7701 1 3 Online Resource 2 Fusarium oxysporum 0.99 ITS, Unite MetaWorks ESV Number of Samples ESV count Sequence Species Bootstrap Zotu1380 17 40 Online Resource 2 Puccinia coronata 0.97 Zotu1483 5 99 Online Resource 2 Puccinia coronata 1 Zotu15192 1 5 Online Resource 2 Puccinia coronata 1 Zotu1114 10 100 Online Resource 2 Puccinia coronata 1 Zotu4004 4 20 Online Resource 2 Puccinia coronata 0.97 Zotu3821 1 109 Online Resource 2 Gremmeniella abietina 1 Zotu4489 1 81 Online Resource 2 Gremmeniella abietina 1 Zotu1362 8 92 Online Resource 2 Puccinia graminis 1 ITS2 Unite, MetaWorks ESV Number of Samples ESV count Sequence Species Bootstrap Zotu35 9 1,392 Online Resource 2 Senecio naequidens 0.98 16S, QIIME2 Feature ID Number of samples Sequence count Sequence Species Bootstrap KF663871 2 1 Online Resource 2 Clavibacter michiganensis 1 Discussion The present results revealed eDNA molecular identification from eleven IAS spanning four main groups (arthropods, fungi, plants, and bacteria) using molecular data from samples collected in international shipping containers arriving at Canadian ports. This confirms container transportation as a potential pathway for introducing IAS in Canada regardless of taxonomic group. More importantly, we are proposing a fast, scalable, and accurate molecular biosurveillance method that allows IAS eDNA detection that, if added to the current biosurveillance protocols, would allow more containers to be explored and signalled for deeper biosurveillance. Currently, only a small percentage of imported containers are inspected, as traditional biosurveillance methods are not scalable. Noticeably, finding the IAS eDNA does not directly translate into finding a viable IAS; however, this might not be the case for the microorganisms detected here. Regardless of the potential differences between microorganisms and microorganisms’ viability, IAS DNA detections in the containers might signal their propagule presence and the need for more comprehensive biosurveillance in those cases where detection occurred before triggering further measures. It is already well established that species become aliens and invaders only after spreading out of their native range, typically through primarily human-mediated processes. Invasive alien species (IAS) are any harmful non-native species (insects, fungi, plants, bacteria, viruses, etc.) whose introduction or spread threatens the environment, the economy, and/or society, including human health (Canada 2015b ). They can originate from any non-native geographic range, including continents, neighbouring countries, or other ecosystems within the same country (Canada 2015b ). Also, IAS can extend their geographical range beyond their natural dispersal through global trade, international shipments, and transportation (Paini and Yemshanov 2012 ). In that regard, risks for IAS new introductions or recurrence are simply higher without sufficiently sensitive biosurveillance protocols in place at ports of entry. Barcoded specimens Both a shell and tissue fragment of Cepaea nemoralis were collected from shipping container debris from a container originating in Germany. Cepaea nemoralis is commonly known as the wood snail or banded grove snail, among others, and has been widely introduced nearly worldwide, intentionally and unintentionally (Dees 1970 ; Mead 1971 ; Abbott 1989 ). Cepaea nemoralis feeds primarily on plant detritus and, therefore, seldom acts as an agricultural pest but can damage crops in high numbers and is still considered a potential pest species by the United States Department of Agriculture (USDA) (Turton 1857 ; Dees 1970 ; Thompson 1996 ). There is also a concern about the potential negative impacts of non-native snails, such as C. nemoralis , on native snail populations (Mead 1971 ; Cowie and Robinson 2003 ; Whitson 2005 ). The successful molecular identification of a morphologically unidentifiable tissue fragment present in a shipping container highlights the advantages of the DNA-based biosurveillance approaches over traditional methods. In the latter case, the morphological integrity of key morphological characters remains necessary for successful identifications. However, as reaffirmed here, effective molecular detections can be reached regardless of specimen morphological integrity and life cycle stage. Ascomycota DNA-based evidence was detected from a shipping container originating from China, potentially belonging to Cercospora sojina , a fungal plant pathogen with 14 races recorded in the country of container origin (Ma and Li 1997 ). Unfortunately, there is low resolution for the COI fragment to unambiguously resolve at the fungi species level. Cercospora sojina causes frogeye leaf spots in most soybean-growing countries (Athow and Probst 1952 ; Bernaux 1979 ; Akem et al. 1992 ; Ma 1994 ). It was first reported in Japan in 1915 (Melchers 1925 ), then in the United States in 1924 and is now present in 26 additional countries globally (Lehman 1928 ; Lin and Kelly 2018 ). Reported losses of frogeye leaf spot range from 10–60%, making it an economically significant species (Bernaux 1979 ; Dashiell and Akem 1991 ; Akem et al. 1992 ; Ma 1994 ; Mian et al. 1998 ). Lastly, a larval specimen belonging to the genus Tipula (Tipulidae) was detected from a shipping container originating in Germany. Tipula is the largest genus of the family, with over 2,400 species (Oosterbroek 2022 ). Larvae of Tipula sp. are indistinguishable morphologically at the genus level due to a significant variation in larval character states (Gelhaus 1986 ), which makes DNA identification of larval specimens especially important. Although most species of Tipula are not invasive and generally not considered pests, there are at least two examples, such as Tipula paludosa and Tipula oleracea , considered invasive turfgrass pests in North America (Wilkinson and MacCarthy 1967 ; Gelhaus 2005 ). Current results ratify the capacity for successful molecular identifications at larval stages and tool utility in a regulatory context. Again, this constitutes an advantage over morphology-based identifications, where key traits are often linked to the adulthood life stage, or in some cases, there is simply a lack of taxonomic keys at the early stages of species development. Metabarcoding detections Bark beetles (Subfamily Scolytinae ) are among the most destructive forest pests globally (Grégoire et al. 2015 ; Raffa et al. 2015 ). However, they also play an essential role in forest ecosystems as they typically live in dead or decaying plants and thus are critical early decomposers (Raffa et al. 2015 ). Nevertheless, when droughts or extreme environmental events occur, bark beetles shift to occupying live trees, causing outbreaks and severe damage to forests (Wermelinger 2004 ). eDNA from the spruce bark beetle ( Ips typographus ) was detected here; which is an endemic species to Eurasia (Wermelinger 2004 ) but is now widespread from Europe, across Asia to Japan (EFSA Panel on Plant Health (PLH) et al. 2017a ) (Global Biodiversity Information Facility [GBIF]) and ranks among the most destructive of the bark beetles (Grégoire et al. 2015 ). It is also one of the most common bark beetles to be intercepted at U.S. ports of entry (Haack 2001 ), and it is predicted it could colonize select North American tree species if given a chance (Flø et al. 2018 ). The potential presence of this species was detected in samples taken from a shipping container originating in China, demonstrating the effectiveness of molecular biosurveillance tools in early detection and signalling the need for a broader inspection of the flagged container. Our study also detected Lymantria dispar eDNA in debris from a shipping container from Ghana, a country outside the recognized species' geographic distribution. Although containers can get "contaminated" elsewhere with a given IAS, border control in Canada will be needed first to detect them and then avoid their establishment and spread, irrespective of their origin. Lymantria dispar is typically treated as three subspecies, L.d. dispar , L.d. asiatica and L.d japonica , with the subspecies L. d. dispar endemic to Europe, Asia and North Africa between latitudes of 30°N and 60°N (Zahiri et al. 2019 ). Studies examining the possible future spread based on climatic and shipping port variables, among other variables, indicate a low likelihood of the species occurring in Ghana (Yanjun et al. 2021 ; Song et al. 2022 ). Despite the low likelihood of spreading to Ghana, other factors that could explain the presence of L. dispar eDNA in the shipping container: stops at different ports with established L. dispar populations during its journey or having previously visited a country where contact with L. dispar is likely, are possible explanations. Current information recorded by the CFIA on the specific shipping container (where Lymantria dispar eDNA was found) includes only the most immediate port of export. This implies that the IAS may have infiltrated the shipping container through previous origins or departures and remained undetected (Paini and Yemshanov 2012 ). The latter highlights the need to obtain the exact locations of all ports visited during each shipping expedition, as this information is necessary for concluding the possible distribution of L. dispar . Fusarium oxysporum fungus eDNA was detected in shipping containers from Taiwan, China, Ghana, and Germany, although not linked to any specific formae speciales . Fusarium oxysporum has many different host-specific strains, many of which are global in their distribution (Gordon 2017 ). Some strains of F. oxysporum act as pathogens to various plant species; those that are wilt-causing are responsible for damaging many economically relevant plant species (Olivain and Alabouvette 1997 ). Fusarium oxysporum is mainly managed through soil fumigation, which is environmentally damaging, or through breeding resistant cultivars, which is difficult when dominant genes are unknown and when new strains overcome host resistance (Fravel et al. 2003 ). In Canada, Fusarium oxysporum f. sp. cannabis is considered a regulated pest, and its biosurveillance is essential to prevent any potential unfavourable impact in the hemp-related industry. Several strains of F. oxysporum affecting cannabis were detected in British Columbia in 2013–2014 and reported in 2018 from Ontario and British Columbia. However, they have not been linked to f. sp. cannabis . Thus, these strains are likely generalized crown and root rot forms of the pathogen Fusarium oxysporum and more research is needed to determine this pathogen's host range and distribution (Punja and Rodriguez 2018 ). Fusarium oxysporum f. sp. cannabis causes crown infection and root browning, ultimately leading to stunted growth, yellowing leaves and/or plant death (Punja 2021 ). Consequently, early detection along other potential routes of introduction is crucial to prevent future spread. Puccinia coronata eDNA was also detected in containers from Taiwan, China, Germany, and Iran. It is a fungus causing crown rust disease in oats (Nazareno et al. 2018 ), barley and wheat (Jin et al. 1992 ; Niu et al. 2014 ), and some grasses (Jin and Steffenson 1999 ). Puccinia coronata is divided into multiple physiological variants ( formae speciales ), which do not necessarily reflect genetic differences but are used to differentiate host preference (Nazareno et al. 2018 ). The pathogen causing crown rust of oats is typically referred to as Puccinia coronata f. sp. avenae (Nazareno et al. 2018 ), which causes pustules to form on the leaves, leading to significant yield losses (Berlin et al. 2018 ). Crown rust of oats is globally distributed and continues to cause epidemics with yield losses of up to 40% (Martinelli et al. 1994 ; Nazareno et al. 2018 ). Similarly, Puccinia graminis eDNA was detected in containers from Taiwan, China, and Germany, signalling a plant fungus known as stem rust, mainly affecting wheat and other cereals (Abbasi et al. 2005 ). Many authors speculate that the fungus originated in Asia or North Africa and was spread globally by human activities (Abbasi et al. 2005 ). However, resistant strains of wheat and fungicide have been developed (Singh et al. 2008 ; Bhattacharya 2017 ; Lewis et al. 2018 ), and new variants have caused recent outbreaks and epidemics, leading to significant economic losses (Lewis et al. 2018 ). Outbreaks include those in Germany and Ethiopia in 2013 (Olivera et al. 2015 ; Lewis et al. 2018 ) and Sicily in 2016 (Bhattacharya 2017 ). Urocystis agropyri , or flag smut of wheat, is an economically damaging fungal plant pathogen first reported in Australia in 1868 (McALPiNE 1905 ; Ram and Singh 2004 ). Since then, it has spread globally, mainly via infected seed, to all continents and almost all wheat-growing Countries, including Canada (Pal Singh 2017 ). However, flag smut in Canada only affects grasses and not wheat (Purdy 1965 ). The damaging effects of flag smut can cause losses of up to 100% in wheat crops (Purdy 1965 ; Pal Singh 2017 ). Once introduced, it persists for at least four and up to seven years (Purdy 1965 ; Pal Singh 2017 ). Gremmeniella abietina , found in containers with undisclosed country of origin, a fungus causing shoot blight and stem canker of conifers, has two distinct races in North America, both of which affect pine, spruce, larch and fir species (Government of Canada 2012; Botella and Hantula 2018 ). It was first detected in North America in Michigan in the mid-1900s. The “European race” is the more virulent of the two strains and killed over 90% of pine trees in the Adirondack mountains of New York in 1974 (Government of Canada 2012). Gremmeniella abietina is found in most provinces in Canada, in the northeast U.S., all of Europe, Georgia, and Japan (Botella and Hantula 2018 ). Gremmeniella abietina can survive under a wide range of climatic conditions and can be present in an endophytic (asymptomatic) stage for an undetermined period, giving it the potential to spread to new areas while making its detection at early stages especially difficult from a morphological perspective (EFSA Panel on Plant Health (PLH) et al. 2017b ). Using eDNA detection methods can facilitate early identification of this pest to control its spread. Venturia nashicola , or scab of Asian pear, occurs in China, Japan, South Korea and Taiwan and infects the Asian and Chinese pear ( Pyrus pyrifolia var. culta and P. ussuriensis ) (Chevalier et al. 2004 ; Abe et al. 2008 ; González-Domínguez et al. 2017 ). It was also found in a container with undisclosed country of origin. This fungus is a distinct species and is host-specific to Asian pear varieties, as shown by various studies (Ishii and Yanase 2000 ; Park et al. 2000 ; Abe et al. 2008 ). Venturia species often infect the fruits of a plant, causing considerable economic losses in fruit crops (Sivanesan 1977 ). In Eastern Asia, V. nashicola is one of the most serious pathogens in Pyrus pyrifolia var. culta , P. bretschneideri , and P. ussuriensis . The pathogen causes fruit drop, cracking, and malformation. Current results ratify pathway risk assessment as one of the most critical tasks in preventing this IAS (Hulme 2009 ). Additionally, the current study detected eDNA from Dioscorea polystachya from shipping containers originating in Germany, Taiwan, and China, with no observed evidence of their propagules being present in the samples. Dioscorea polystachya , commonly called the Chinese Yam, is a regulated pest in Canada (Government of Canada 2016). It is a climbing vine species and has the potential to quickly spread to natural habitats, which can reduce biodiversity and damage other plant species (Government of Canada 2016). Dioscorea polsctachya is native to China but is now grown throughout East Asia in areas including Japan, Korea, the Kuril Islands, and Vietnam (Xu and Chang 2017 ). Dioscorea polystachya was likely introduced to Japan and the United States around the 17th and 19th centuries, respectively, and is now considered invasive in those countries (Xu and Chang 2017 ). Dioscorea polystachya is currently not established in Canada (Government of Canada 2016) but is more tolerant to frost than other yams (Xu and Chang 2017 ), enabling it to survive the Canadian climate. Since this species has yet to be introduced to Canada, early detection through shipping container routes can help prevent its potential establishment. On the other hand, Senecio inaequidens , commonly known as South African ragwort, is a flowering species native to South Africa. Its recent spread to Hawaii and Australia has had detrimental effects, including liver damage to livestock and humans ( https://inspection.canada.ca/plant-health/invasive-species/invasive-plants/invasive-plants/south-african-ragwort/eng/1331757285388/1331757407583 ). While not discovered in Canada yet; there is a potential pathway due to high traffic between infected countries in Europe. Its eDNA was identified in containers from Germany, where it is known to be established. Clavibacter michiganensis is a pathogen that causes bacterial canker disease in tomatoes. It is one of the most devastating agricultural diseases and is found in all regions of tomato production. In the present study, its eDNA was found in containers coming from Taiwan and Germany. The bacterium causes canker and wilt symptoms by invasion through open wounds and proliferation in the xylem (Nandi et al. 2018 ). Young and well-fertilized plants in high humidity conditions are prone to infection, resulting in widespread crop loss in developing countries (Abo-Elyousr et al. 2019 ). Importance of molecular biosurveillance in shipping containers Invasive species, especially those that are small or undetectable, can often be missed even during intensive border surveillance of shipping containers, leading to increased spread through human-mediated pathways (Chapple et al. 2013 ). In addition, limited funding and resources for biosecurity can result in a lack of thorough inspection of containers (Lucardi et al. 2020 ). A recent study showed that despite having global regulations in place for the proper treatment of wood packaging material used for global trade (eg., International Standards For Phytosanitary Measures No. 15 [ISPM 15]), pests' movement between borders continues to be detected, likely due to fraud, insufficient treatment and/or non-compliance (Greenwood et al. 2023 ). In these cases, molecular biosurveillance has a significant advantage, as it can detect multiple invasive species cost-efficiently and more effectively than traditional methods (e.g., morphology IDs), regardless of size, morphological integrity, or life stage, while not being labour-intensive at the inspection phase. In order to successfully implement molecular biosurveillance in shipping containers, an expansive knowledge of shipping container history, including previous destinations or ports and their immediate origin, is necessary (Paini and Yemshanov 2012 ). For example, Australian government policies only evaluate the immediate area of departure, allowing species from previous ports to infiltrate and remain hidden in marine shipping containers for extended periods, leading to increased spread and subsequent damage in different countries (Paini and Yemshanov 2012 ). The global shipping container trade transports various goods, ranging from seafood to fresh fruits, which require refrigerated shipping containers to preserve produce longevity (Lucardi et al. 2020 ). Temperature-controlled shipping containers provide an ideal environment for harbouring IAS for several reasons, as they: i) contain air-intake grills which can collect propagules of IAS along their journey (Whitehurst et al. 2020 ) ii) usually contain soil and debris which can behave as a reservoir for harmful bacteria and fungi, and iii) can prevent the degradation of harmful organisms (extending their viability) since they are temperature controlled (Whitehurst et al. 2020 ). Additionally, in creating an ideal environment for invasive organisms, temperature-controlled containers can also increase the preservation of an organism’s DNA, providing an opportunity for eDNA biosurveillance. IAS negatively impact the economy, environment, and/or agriculture. The impacts on the agricultural sector can be expressed in terms of financial costs, with Canada losing 175 million CAD per year in efforts to manage the top ten alien species (Hulme 2014 ). Significant costs include management, monitoring efforts and loss of international trade. Plant pathogens, including bacteria, viruses, and fungi, affect North American crop yield the most, and without management, it would lead to a 51–82% loss of crops (Hulme 2014 ). International and global trade agreements facilitate exchange but also allow new pathways for invasion, with Canada receiving 44% of imports from the USA or Mexico (Hulme 2014 ). Due to these regional agreements, most pests found at the Canadian border originate from the USA (Hulme 2014 ). Through early detection of invasive species by implementing effective eDNA metabarcoding protocols, detrimental effects of IAS can be minimized. By incorporating eDNA-based identification techniques, known IAS or regulated species can be accurately detected when working with large samples consisting of several species and can also be used to confirm prior morphological identification (Darling and Blum 2007 ; Milián-García et al. 2023 ). Therefore, they can be combined with preexisting methods for cost-effective and reliable results, allowing us to trace the origins of a broad range of species. Although IAS eDNA detection does not translate directly into viable species or their propagules' presence in the containers, especially for macroorganisms, it might not be the same for the microorganisms detected. For example, Fusarium oxysporum viability in soil samples can be observed for at least one year (Vakalounakis and Chalkias 2004 ; Paugh and Gordon 2021 ). At the same time, Urocystis agropyri can survive for four years in soil samples and even longer in favourable storage conditions. Similarly, Claribacter michiganensis can remain viable in soil samples (Trevors and Finnen 1990 ), and propagules of Gremmeniella abietina can survive in branches left on the ground after two years (Laflamme and Rioux 2015 ). It suggests that strict molecular biosurveillance approaches combined with microorganism viability tests may be a critical management tool for IAS prevention and mitigation risks. Conclusions and perspectives Molecular identification of invasive alien and Canadian-regulated species from complex samples collected from international shipping containers demonstrates to be an effective and powerful tool for detecting invaders in advance of their introduction, spread and establishment in new environments. Frequent biosurveillance integrating DNA-based techniques into the current CFIA toolkit is strongly suggested. The vast majority of IAS identified based on their eDNA in the present study were microorganisms (7/11), and additional viability tests might be critical for a more comprehensive risk assessment. Extending the battery of molecular markers for broader taxonomic identification (e.g., RBCL for plant identification) is also recommended. It is essential to highlight that IAS’ eDNA detection in shipping containers does not directly translate into viable IAS detection or their propagules. However, it might signal their presence and the need for deeper biosurveillance in cases where detection occurred. Declarations Declaration of competing interest The authors declare that they have no competing interests. Author contributions Conceptualization, YMG and RHH; Data curation, YMG and CP; Formal analysis, YMG and CP; Funding acquisition, RHH; Investigation, YMG, CP, AC, KL; Methodology, YMG; Project administration, RHH and YMG; Resources, RHH; Validation, YMG, CP, AC, KL; Visualization, YMG and CP; Roles/Writing - original draft, YMG, CP, AC, KL; Writing - review & Editing, YMG, CP, AC, KL, RHH. Acknowledgment UoG-BIO acknowledges the financial support of the Canadian Food Inspection Agency (CFIA) [FAP#2122-002]. We sincerely thank all surveyors for contributing to the sample collection. We are deeply thankful to Ian Thompson for the support provided in imaging individual specimens. Yoamel Milián-García was supported by Mitacs through the Mitacs Elevate Program (IT34941). Availability of data and materials The study complies with local and national regulations and guidelines. 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Methods in Ecology and Evolution n/a: https://doi.org/10.1111/2041-210X.13552 Effect of Bacterial Pustule and Frogeye Leafspot on Yield of Clark Soybean1 - Laviolette - 1970 - Crop Science - Wiley Online Library. https://acsess.onlinelibrary.wiley.com/doi/abs/10.2135/cropsci1970.0011183X001000040031x?casa_token=QV0L6WVFdFgAAAAA:9_qDYpHqKHNOPo82xXXEN_9lLtX2vjDxnq2ggh40p3x74O44OduHHTb2UErmG3ySTMotLEpdcrfhS93s. Accessed 29 Nov 2022a Ips typographus (eight-toothed bark beetle) | CABI Compendium. https://www.cabidigitallibrary.org/doi/10.1079/cabicompendium.28843. Accessed 19 Jan 2023b Damage and Control of Bawbilt Organisms an Overview | SpringerLink. https://link.springer.com/chapter/10.1007/978-1-4020-2241-8_4. Accessed 19 Jan 2023c Fusarium oxysporum and its biocontrol - Fravel - 2003 - New Phytologist - Wiley Online Library. https://nph.onlinelibrary.wiley.com/doi/full/10.1046/j.1469-8137.2003.00700.x. Accessed 19 Jan 2023d 2015 Meeting | Fungal diseases of Cannabis sativa in British Columbia, Canada. https://www.apsnet.org/meetings/Documents/2015_meeting_abstracts/aps2015abP319.htm. Accessed 19 Jan 2023e Urocystis agropyri (flag smut of wheat) | CABI Compendium. https://www.cabidigitallibrary.org/doi/10.1079/cabicompendium.55784. Accessed 19 Jan 2023f EPPO Global Database. https://gd.eppo.int/. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4618423","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":321814699,"identity":"e6bd9fcc-70e1-438e-b830-00e31065632d","order_by":0,"name":"Yoamel Milián-García","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYNCCAgYGfhCdUEC0FgMGBskGkBYDUrQYHIAyCCs+3vx0wweDbXabz69O/PDAgEGeX+wAAS1njpndnGFwO3nbjbebJYAOM5w5O4GAlhsJZrd5gFrMbpzdANKSYHCboJb0b7f/ALUYzzi7+QeRWnLMbjMY3LYz4O/dRpwtkmfOlN3sASqTuMG7zSLBQIKwX/iOt2+78aPitj1//9nNN39U2MjzSxPQonAAQic2SIBVSuBXDgLyDRDanoH/AGHVo2AUjIJRMDIBAGo7TSmx5KU5AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-6596-5063","institution":"University of Guelph","correspondingAuthor":true,"prefix":"","firstName":"Yoamel","middleName":"","lastName":"Milián-García","suffix":""},{"id":321814700,"identity":"cb6dfd6b-2270-4342-a772-1c8502caeb7b","order_by":1,"name":"Cassandre Pyne","email":"","orcid":"","institution":"University of Toronto","correspondingAuthor":false,"prefix":"","firstName":"Cassandre","middleName":"","lastName":"Pyne","suffix":""},{"id":321814701,"identity":"b807c232-b7fd-4aae-9e76-a12a674fc12a","order_by":2,"name":"Ashley Chen","email":"","orcid":"","institution":"University of Guelph","correspondingAuthor":false,"prefix":"","firstName":"Ashley","middleName":"","lastName":"Chen","suffix":""},{"id":321814702,"identity":"b6ef736f-f169-4bff-83a7-bbe2b42f787a","order_by":3,"name":"Kate Lindsay","email":"","orcid":"","institution":"University of Guelph","correspondingAuthor":false,"prefix":"","firstName":"Kate","middleName":"","lastName":"Lindsay","suffix":""},{"id":321814703,"identity":"ffc3f725-499a-4806-8664-741ffffd4016","order_by":4,"name":"Robert H. Hanner","email":"","orcid":"","institution":"University of Guelph","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"H.","lastName":"Hanner","suffix":""}],"badges":[],"createdAt":"2024-06-21 16:52:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4618423/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4618423/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10530-025-03549-w","type":"published","date":"2025-02-24T15:57:59+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":61178872,"identity":"0dc6bc5a-8a07-40a8-adc3-1915c50ea226","added_by":"auto","created_at":"2024-07-26 16:02:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":351407,"visible":true,"origin":"","legend":"\u003cp\u003eRarefaction curves per every sample analyzed for COI, ITS, ITS2, and 16S in the present study. D0, D1, and D2 correspond to the diversity indexes: species richness, the Shannon index, and the Simpson index, respectively. Coverage represents the Good’s coverage index (Zinger et al. 2021).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4618423/v1/b4c0e04ed190846ac3014256.png"},{"id":61177548,"identity":"c4d1264e-239b-4746-8431-f676b0804b99","added_by":"auto","created_at":"2024-07-26 15:54:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":157155,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentation of the total number of reads retained after bioinformatic analyses across all the samples and negative controls analyzed for COI, ITS, ITS2, and 16S, including the resulting proportion of molecular operational taxonomic units (MOTUs).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4618423/v1/bd51b2c6cc3a905c6e2e9748.png"},{"id":61177551,"identity":"0281a768-7182-4231-a73b-b2b08002d307","added_by":"auto","created_at":"2024-07-26 15:54:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1207434,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular identification of individual samples collected from the shipping containers, based on DNA barcoding technique.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-4618423/v1/b800b73ca678b2e9c4253071.png"},{"id":61177550,"identity":"0f94b6fb-5a03-42e5-a522-97e39826a944","added_by":"auto","created_at":"2024-07-26 15:54:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":55904,"visible":true,"origin":"","legend":"\u003cp\u003eBarplots illustrating the proportion of invasive alien species detected based on the eDNA shed in shipping containers using COI molecular marker and MetaWorks (\u003cstrong\u003eA\u003c/strong\u003e) and mBRAVE (\u003cstrong\u003eB\u003c/strong\u003e) bioinformatic pipelines [eDNA metabarcoding].\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-4618423/v1/c58b64047f15d0870ded4558.png"},{"id":61177546,"identity":"2fab7b3c-dc21-4dce-8b72-41203cbf26f5","added_by":"auto","created_at":"2024-07-26 15:54:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":144546,"visible":true,"origin":"","legend":"\u003cp\u003eBarplot representing the proportion of fungi invasive alien species and plant IAS detection in shipping container samples for ITS using MetaWorks (\u003cstrong\u003eA\u003c/strong\u003e) and QIIME2 (\u003cstrong\u003eB\u003c/strong\u003e) [eDNA metabarcoding].\u003c/p\u003e","description":"","filename":"floatimage11.png","url":"https://assets-eu.researchsquare.com/files/rs-4618423/v1/13e3c188d1324720428b28a3.png"},{"id":61179279,"identity":"b264822e-611d-48eb-8a5e-876e8b519b09","added_by":"auto","created_at":"2024-07-26 16:10:44","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":51823,"visible":true,"origin":"","legend":"\u003cp\u003ePlant invasive alien species detected in shipping containers using ITS2 molecular marker and MetaWorks (\u003cstrong\u003eA\u003c/strong\u003e) and QIIME2 (\u003cstrong\u003eB\u003c/strong\u003e) [eDNA metabarcoding].\u003c/p\u003e","description":"","filename":"floatimage12.png","url":"https://assets-eu.researchsquare.com/files/rs-4618423/v1/73dc2b9c217cde5a6123bd71.png"},{"id":61178874,"identity":"e5fa51b0-db43-42e6-9f47-4910c4f24677","added_by":"auto","created_at":"2024-07-26 16:02:44","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":40524,"visible":true,"origin":"","legend":"\u003cp\u003eBacterial invasive alien species detection in shipping container samples for 16S using QIIME2 (eDNA metabarcoding).\u003c/p\u003e","description":"","filename":"floatimage13.png","url":"https://assets-eu.researchsquare.com/files/rs-4618423/v1/25a39386758a4a9ce163127e.png"},{"id":77622512,"identity":"f732f897-3510-4b9a-ac0e-31eead6e8a7d","added_by":"auto","created_at":"2025-03-03 16:07:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3182281,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4618423/v1/30c88c6e-48e0-4766-81a1-72677bae6a0f.pdf"},{"id":61179278,"identity":"7c6c8dca-d09c-4db9-800e-ff9612080cb9","added_by":"auto","created_at":"2024-07-26 16:10:44","extension":"csv","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":55369,"visible":true,"origin":"","legend":"","description":"","filename":"ONLINERESOURCE1.csv","url":"https://assets-eu.researchsquare.com/files/rs-4618423/v1/cd2412559e311ad4949b6c00.csv"},{"id":61178875,"identity":"bb0f2f0e-18db-46b0-8262-fcd1c4e5e0e6","added_by":"auto","created_at":"2024-07-26 16:02:44","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":14696,"visible":true,"origin":"","legend":"","description":"","filename":"ONLINERESOURCE2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4618423/v1/a1996382577716bbbaf71ec1.xlsx"}],"financialInterests":"","formattedTitle":"Uncovering the hidden within shipping containers: Molecular biosurveillance confirms a pathway for introducing multiple regulated and invasive species.","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe adverse effects of invasive alien species (IAS) are recognized as a leading cause of large-scale biodiversity and economic losses (Clavero and Garc\u0026iacute;a-Berthou \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Reid et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The International Union for the Conservation of Nature (IUCN) associated the harmful effects of IAS with around 54% (91 out of 170) of documented animal species extinctions (Clavero and Garc\u0026iacute;a-Berthou \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Consequently, IAS are a problem of global importance (Westfall et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and concerns about their adverse effects are exacerbated as we face a biodiversity crisis and economic instability.\u003c/p\u003e \u003cp\u003eThe financial burden associated with managing and mitigating IAS totals CAD 187\u0026nbsp;million annually in Canada alone, with projections estimating an increase of up to CAD 34.5\u0026nbsp;billion yearly (Colautti et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). In Canada, the Canadian Food Inspection Agency (CFIA) primarily handles terrestrial IAS biosecurity and management (Reid et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The CFIA Plant Health business line conducts regular biosurveillance for early detection of IAS, including fungi, bacteria, plants, arthropods, or animals, which may impact native ecosystems or the agricultural livestock sector (Mili\u0026aacute;n-Garc\u0026iacute;a et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mili\u0026aacute;n-Garc\u0026iacute;a et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCurrently, there are 272 federally regulated terrestrial species in Canada, excluding aquatic invasive species (Government of Canada 2023), including both invasive and regulated species. The latter includes species with a recognized potential to become invasive. For simplicity, we here refer to both CFIA-regulated and invasive species as \u0026ldquo;IAS.\u0026rdquo; Early detection and management of IAS are essential to minimize associated costs and damage; this can only be done effectively by having precise knowledge of the pathways by which an IAS can be introduced (Saul et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Reid et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Pathways refer to routes by which species move from one locale to another, either within a country or between countries (McNeely et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). In contrast, vector refers to the physical means or agent (i.e. aeroplane, ship, etc.) in or on which a species moves outside its native range (past or present) (Canada \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2015a\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe first stage of species invasion consists mainly of human-mediated species movement from one geographical location to another (Blackburn et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The international transport of shipping containers is a recognized pathway for IAS introduction, as IAS can access containers and remain hidden for extended periods (Paini and Yemshanov \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In an era of globalization, biosurveillance of IAS should be fast enough to cope with the speed of international trade (Hulme \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The delayed identification of an IAS before or during its establishment leads to more detrimental impacts on native biodiversity, ecosystem services, and the economy. Traditional detection of IAS (e.g., morphological identifications and direct field observations) is time-consuming and requires taxonomic expertise, which is difficult to unify for multiple taxonomic groups. These traditional methods are considered labour-intensive, are limited in the early stages of invasions, require morphological integrity or preservation of key traits, and are usually only feasible at particular life stages of a given IAS (e.g., adults). Primary limitations of morphological-based methods can also be influenced by the patchy distribution of IAS (Westfall et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), their presence in small numbers, and the lack of taxonomic keys at life stages other than adulthood. In addition, border control can only examine a small subset of containers; for example, as of 2005, it was estimated that only 2% of shipping containers were inspected at the United States border (Work et al. \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). DNA-based identification strategies, including DNA barcoding and metabarcoding, can help to overcome the limitations mentioned above by using standardized DNA fragments for species identification through comparison to reference databases (Hebert et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Environmental DNA (eDNA) metabarcoding is a DNA barcoding-based molecular technique for multi-species identification. This approach supports the analysis of complex samples in a high-throughput manner for species identification from mixed DNA released by the species into their environment. These methods allow for detecting an IAS regardless of life stage and morphological integrity and do not require taxonomic expertise when traditional taxonomy information has already been linked to molecular data in reference repositories.\u003c/p\u003e \u003cp\u003eConsequently, DNA reference databases (e.g., The Barcode of Life Data System [BOLD]) are considered permanent repositories of molecular and traditional taxonomic data that allow the identification of unknown sequences to known reference data. Previous studies have used eDNA to detect aquatic IAS from ballast water in shipping vessels or water or sediment from shipping ports (Egan et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Brown et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Borrell et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Grey et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; van den Heuvel-Greve et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Gargan et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, fewer studies are specifically designed to detect terrestrial IAS. In this study, we aim to assess the capacity and effectiveness of eDNA metabarcoding to detect terrestrial IAS eDNA using shipping containers as a vector. This is the first study in Canada to assess eDNA as a tool for early screening of terrestrial IAS in shipping containers. Here, a combination of DNA barcoding and eDNA metabarcoding was employed for molecular biosurveillance of international shipping containers to address the following research questions: i- Can molecular biosurveillance methods be effective for the identification of invasive alien or Canadian-regulated species in a regulatory/early screening of international shipping containers?; if so, ii- What is the diversity of invasive alien or Canadian-regulated species using shipping containers transportation pathways?\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSampling\u003c/h2\u003e \u003cp\u003eThirty-eight samples were collected from shipping containers arriving in Canada from six countries between 2020 (N\u0026thinsp;=\u0026thinsp;28) and 2021 (N\u0026thinsp;=\u0026thinsp;10). Sample size per country of origin varied as follows: Germany (N\u0026thinsp;=\u0026thinsp;21), China (N\u0026thinsp;=\u0026thinsp;10), Taiwan (N\u0026thinsp;=\u0026thinsp;2), Ghana (N\u0026thinsp;=\u0026thinsp;1), Iran (N\u0026thinsp;=\u0026thinsp;1), and one undisclosed country of origin (N\u0026thinsp;=\u0026thinsp;3). Thirty-one of the 38 samples were soil debris (hereafter soil samples) collected from the containers at the Canadian border. In addition, two bags of seeds, one bag of stems, one insect larva, one snail, and one tissue fragment were all collected from containers shipped from Germany. The snail and insect larva samples were collected from the same shipping container. The last non-soil sample, consisting primarily of bark, was obtained from a container that originated in China. All samples were deposited in Whirl Pak or Ziplock bags and sent to the Hanner Laboratory at the University of Guelph. Once received, samples were stored at -80\u0026deg;C until laboratory processing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eeDNA extraction\u003c/h2\u003e \u003cp\u003eDNA was extracted from tissue samples obtained from the insect larva and snail using the DNEasy Blood and Tissue kit (Qiagen), following the manufacturer\u0026rsquo;s instructions. All soil samples were extracted using the DNeasy PowerSoil Pro kit as follows. Every soil sample was subsampled thrice into approximately 250 mg samples. They were placed into individual PowerBead Pro tubes, and 800 \u0026micro;L of Solution CD1 was added to each tube and vortexed thoroughly for 10 seconds. Samples were made homogenous using the TissueLyser II at 25 Hz for 5 minutes. The adapter was reoriented, and the process was repeated at 25 Hz for another 5 minutes.\u003c/p\u003e \u003cp\u003eThe tubes were centrifuged at 15,000 g for 1 minute, then transferred the supernatant, with a maximum volume of 600 \u0026micro;L, to a clean 2 mL microcentrifuge tube. After this, 200 \u0026micro;L of solution CD2 (stored at 4\u0026deg;C) was added, and tubes were vortexed for 5 seconds. Then, tubes were centrifuged at 15,000 g for 1 minute, and the supernatant was transferred into a clean 2 mL microcentrifuge tube while avoiding the pellets. 600 \u0026micro;L of solution CD3 was added, and the tubes were vortexed briefly. 650 \u0026micro;L of the lysate was loaded onto an MB Spin Column and centrifuged at 15,000 g for 1 minute, and the flow-through was discarded. This step was repeated to ensure all the lysates had passed through the column. The spin columns were then carefully placed into clean 2 mL collection tubes to avoid splashing and contamination. 500 \u0026micro;L of solution EA was added to the spin column and centrifuged at 15,000 g for 1 minute. The collection tube and flow-through were discarded, and the MB spin columns were placed back into the same 2 mL collection tube. 500 \u0026micro;L of solution C5 was added to the MB spin column and centrifuged at 15,000 g for 1 minute, and the collection tube and flow-through were discarded. The MB spin column was then placed into a new 2 mL collection tube and centrifuged at 16,000 g for 2 minutes, then placed into a new 1.5 mL DNA LoBind tube (Eppendorf) rather than a 1.5 mL elution tube to prevent the binding of DNA to the wall of the tube. We then added 100 \u0026micro;L of solution C6 in the center of the white membrane to ensure complete elution of DNA from the MB Spin Column filter membrane. This process was concluded by centrifuging at 15,000 g for 1 minute and discarding the spin column. DNA extracts were quantified (ng/ul) by fluorometry using a Qubit dsDNA High-Sensitivity Assay kit in a Qubit 4 fluorometer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDNA barcoding\u003c/h2\u003e \u003cp\u003eDNA extracted from individual specimens or specimen fragments was used for molecular identification using versatile COI primers and PCR cycling conditions previously described (Folmer et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1994\u003c/span\u003e), with slight modifications as follows: each PCR reaction contained 5 uL of each primer (LCO1490 and HCO2498 at 1 uM), 12.5 uL of 2x High-Fidelity Kapa Master Mix, and 2.5 uL of DNA template. PCR products were cleaned up using magnetic beads (Machery-Nagel) at a 1x ratio following the manufacturer's instructions. The purified PCR products were then Sanger sequenced in both directions at the Advanced Analysis Center at the University of Guelph.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eeDNA metabarcoding\u003c/h2\u003e \u003cp\u003eDNA libraries were prepared for metabarcoding analysis using four molecular markers: 16S (for bacterial identification), ITS (for fungi identification), ITS2 (for plant identification) and COI (for arthropod identification), and following protocols previously established in the Hanner laboratory (Mili\u0026aacute;n-Garc\u0026iacute;a et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), with only a few modifications as indicated below. Cycling conditions for the first PCR of metabarcoding library preparation for 16S, ITS, and COI were indicated in Mili\u0026aacute;n‐Garc\u0026iacute;a et al. 2020, while conditions for ITS2 can be found in Chen et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2010\u003c/span\u003e. PCR products were checked on 2% agarose eGels after every PCR and after every clean-up, using 5 uL of the product in each case. After the first and second PCR, clean-ups were conducted with a 1x ratio of magnetic beads (Machery-Nagel) following the manufacturer\u0026rsquo;s protocol. Each index PCR reaction contained 5 uL of a pre-prepared mix of index primers (10 uM), 25 uL of 2x High-Fidelity Kapa Master Mix, 15 uL of water, and 5 uL of cleaned-up DNA/amplicon template. Cycling conditions for all index reactions were as follows: 95\u0026deg;C for 180s, followed by eight cycles at 95\u0026deg;C for 30s, 55\u0026deg;C for 30s and 72\u0026deg;C for 30s, and a final extension at 72\u0026deg;C for 300s. An Illumina MiSeq System with a MiSeq reagent kit v3 (600 cycles) was employed for sequencing the samples. To maximize efficiency and cost-effectiveness, each sample was allocated a maximum of 1% of the total sequencing capacity per run, enabling the simultaneous sequencing of up to 100 samples in a single MiSeq run. After the sequencing process, the MiSeq Reporter software was utilized for demultiplexing, which involved separating the sequencing data based on unique sample identifiers, ensuring that the reads from each sample were correctly assigned and segregated. Additionally, the software performed adapter trimming, removing the artificial sequences added during library preparation from the raw sequencing data. The output of this process was a set of two paired-end raw FASTQ files for each sample, containing the sequencing reads ready for further analysis and processing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eQIIME2 v2023.7 was used to determine if any IAS were present in the shipping container samples, based on ITS and 16S (Bolyen et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). QIIME2 is a bioinformatics platform that uses paired-end sequences to retrieve taxonomic assignments while also storing data provenance information. Input is taken as paired-end sequences that are primer and quality trimmed and filtered, paired, dereplicated and clustered using Vsearch. Primer trimming was achieved using pattern-match trimming with CUTADAPT. The parameters used in QIIME2 are as follows: (1) trimming (error rate: 0.1, overlap: 3), (2) pairing (quality: 20, max number of Ns: 3, min length: 200bp, min overlap: 25), (3) filtering (min quality: 20). To retrieve taxonomic identifications of sequences, a ribosomal database (RDP) classifier was used with QIIME2\u0026rsquo;s feature-classifier plugin. For 16S, a pre-trained RDP classifier using sequences from Greengenes2 v2022.10 was used. For ITS, a pre-trained RDP classifier using sequences from UNITE v8.3 was used (Nilsson et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo complement the analysis in QIIME2 for 16S and ITS, MetaWorks v1.12.0 was also used to analyze the COI samples (Porter and Hajibabaei \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). MetaWorks can be used for 16S, ITS, and COI since it can use different RDP classifiers for taxonomic assignment (Wang et al. \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Raw paired-end reads are trimmed using CUTADAPT, then de-replicated and denoised using VSEARCH. For COI, a pre-trained RDP classifier was used (v5.1.0) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/terrimporter/CO1Classifier\u003c/span\u003e\u003cspan address=\"https://github.com/terrimporter/CO1Classifier\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e for taxonomic assignment, accessed August 1, 2023. For 16S, a pre-trained RDP classifier using sequences from NCBI was used (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/terrimporter/16SvertebrateClassifier\u003c/span\u003e\u003cspan address=\"https://github.com/terrimporter/16SvertebrateClassifier\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e, accessed August 1, 2023. Lastly, the ITS pre-trained RDP classifier was trained using UNITE sequences (v2) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/terrimporter/UNITE_ITSClassifier\u003c/span\u003e\u003cspan address=\"https://github.com/terrimporter/UNITE_ITSClassifier\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e, accessed August 1, 2023. We also used the PLANiTS ITS pre-trained classifier (v1.1.1) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/terrimporter/PLANiTS_ITSClassifier\u003c/span\u003e\u003cspan address=\"https://github.com/terrimporter/PLANiTS_ITSClassifier\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e, accessed August 1, 2023. The parameters for each marker in MetaWorks used the same reference parametrization as in previous studies (Mili\u0026aacute;n-Garc\u0026iacute;a et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e): (1) pairing (min quality: 20; min overlap; 25, the max fraction of mismatches: 0.02; min fraction of overlap: 0.90); (2) trimming and filtering (min length: 200bp; error rate: 0.1; end quality score: 20,20; min adapter overlap: 3; max number of Ns).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDNA barcoding\u003c/h2\u003e \u003cp\u003eBidirectional sequences generated with Sanger sequencing were individually analyzed and 5\u0026acute;and 3\u0026acute;manually trimmed based on quality using Geneious Prime 2023.2.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.geneious.com\u003c/span\u003e\u003cspan address=\"https://www.geneious.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e Forward and reverse sequences were aligned using MAFFT v7.490 and keeping parameters by default as implemented in Geneious Prime 2023.2.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.geneious.com\u003c/span\u003e\u003cspan address=\"https://www.geneious.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e Consensus sequences were manually inspected for ambiguities, and in instances of poor alignments, only the strand with the higher quality was used as a reference for posterior molecular identifications. Consensus sequences obtained from the alignments and without ambiguities were used for molecular identification through the BOLD System (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.boldsystems.org/index.php\u003c/span\u003e\u003cspan address=\"http://www.boldsystems.org/index.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e and BLASTn against NCBI\u0026rsquo;s nucleotide database as implemented in Geneious Prime 2022.2.2 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.geneious.com\u003c/span\u003e\u003cspan address=\"https://www.geneious.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eMolecular species identification\u003c/h2\u003e \u003cp\u003eSuccessful DNA extractions were completed from all the samples analyzed despite suboptimal conservation before sampling, as samples from shipping containers experience varying temperatures and remain in the containers for long periods, enhancing DNA degradation. Average DNA concentrations per sample processed ranged from 0.05 to 38.10 ng/ul. A total of 37,147,820 COI reads, 64,411,024 ITS reads, 38,525,960 ITS2 reads, and 33,275,010 16S reads were generated from the 32 soil samples for the metabarcoding analysis, plus any sequences observed in the controls. The distribution of reads per sample, molecular marker, and technical replicate are shown in the Supplementary Information (Online Resource 1).\u003c/p\u003e \u003cp\u003eRarefaction curves generated for all the samples and per molecular marker reached a plateau, suggesting that sequencing depth was enough to maximize the recovery of the exact sequence variants diversity given the primers chosen (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). No sequence reads were observed in the extraction negative controls when processing the samples with all the markers but ITS. In contrast, a considerable number of reads were obtained from the COI and ITS2 PCR negative and sequencing controls, respectively. However, none of the reads in these negative controls were assigned to a molecular operational taxonomic unit (MOTU), indicating only spurious amplification, chimeras, and low-quality reads that did not pass any of the quality controls rather than cross-contaminations (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSingle-species (DNA barcoding) and multispecies (eDNA metabarcoding) identifications\u003c/h2\u003e \u003cp\u003eThree taxa were identified by DNA barcoding the specimens or parts of specimens found in the shipping containers as follows: \u003cem\u003eTipula\u003c/em\u003e sp., \u003cem\u003eCepaea nemoralis\u003c/em\u003e, and \u003cem\u003eCercospora sojina\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of sample ID, country of container origin, length of the DNA barcode region generated, GenBank accession number for the deposited sequence, BOLD and GenBank molecular-based identifications, including percentage of mean similarity [MS(%)] and percentage of identity [PI(%)], query cover, and GenBank accession number of the top BLAST hit.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSeq Length\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGenBank Accession #\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBOLD ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMS (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGenBank ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePI (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eQuery cover\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTop hit accession #\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1-L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e629 bp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePP330842\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eTipula irrorate\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eTipula confusa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eOY744480.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1-S\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e631bp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePP330843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eCepaea nemoralis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eCepaea nemoralis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e99.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eKC954854.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1-F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e496 bp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePP330844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eCepaea nemoralis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e98.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eCepaea nemoralis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e94.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eMH980029.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0002-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e661 bp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eXXXX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eCercospora\u003c/em\u003e sp.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e83.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e98%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eOK075294.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMultispecies identification based on COI marker detected eDNA from two arthropods (\u003cem\u003eLymantria dispar\u003c/em\u003e and \u003cem\u003eIps typographus\u003c/em\u003e) and one fungus (\u003cem\u003eFusarium oxysporum\u003c/em\u003e) using two bioinformatics pipelines for metabarcoding data analysis (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eeDNA from five additional fungi (\u003cem\u003ePuccinia coronata\u003c/em\u003e, \u003cem\u003ePuccinia graminis\u003c/em\u003e, \u003cem\u003eGremmeniella abietina\u003c/em\u003e, \u003cem\u003eUrocystis agropyri\u003c/em\u003e, and \u003cem\u003eVenturia nashicola\u003c/em\u003e) was identified using the ITS molecular marker plus one plant (\u003cem\u003eDioscorea polystachya\u003c/em\u003e) [Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e]. Besides, eDNA from one additional plant invasive species (\u003cem\u003eSenecio inaequidens\u003c/em\u003e) and one bacteria (\u003cem\u003eClavibacter michiganensis\u003c/em\u003e) was identified based on ITS2 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) and 16S (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e), respectively. ITS2 also confirmed \u003cem\u003eFusarium oxysporum\u003c/em\u003e detection based on eDNA present in the container samples.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of the number of samples, exact sequence variant (ESV) count, and bootstrap support associated with the molecular identification of every invasive alien species.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eCOI, MetaWorks\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of Samples\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eESV count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSequence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBootstrap\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZotu4858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnline Resource 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eLymantria dispar\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZotu7701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnline Resource 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eFusarium oxysporum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eITS, Unite MetaWorks\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of Samples\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eESV count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSequence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBootstrap\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZotu1380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnline Resource 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ePuccinia coronata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZotu1483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnline Resource 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ePuccinia coronata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZotu15192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnline Resource 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ePuccinia coronata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZotu1114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnline Resource 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ePuccinia coronata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZotu4004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnline Resource 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ePuccinia coronata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZotu3821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnline Resource 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eGremmeniella abietina\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZotu4489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnline Resource 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eGremmeniella abietina\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZotu1362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnline Resource 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ePuccinia graminis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eITS2 Unite, MetaWorks\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of Samples\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eESV count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSequence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBootstrap\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZotu35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnline Resource 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eSenecio naequidens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e16S, QIIME2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeature ID\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of samples\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSequence count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSequence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBootstrap\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKF663871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnline Resource 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eClavibacter michiganensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present results revealed eDNA molecular identification from eleven IAS spanning four main groups (arthropods, fungi, plants, and bacteria) using molecular data from samples collected in international shipping containers arriving at Canadian ports. This confirms container transportation as a potential pathway for introducing IAS in Canada regardless of taxonomic group. More importantly, we are proposing a fast, scalable, and accurate molecular biosurveillance method that allows IAS eDNA detection that, if added to the current biosurveillance protocols, would allow more containers to be explored and signalled for deeper biosurveillance. Currently, only a small percentage of imported containers are inspected, as traditional biosurveillance methods are not scalable. Noticeably, finding the IAS eDNA does not directly translate into finding a viable IAS; however, this might not be the case for the microorganisms detected here. Regardless of the potential differences between microorganisms and microorganisms’ viability, IAS DNA detections in the containers might signal their propagule presence and the need for more comprehensive biosurveillance in those cases where detection occurred before triggering further measures. It is already well established that species become aliens and invaders only after spreading out of their native range, typically through primarily human-mediated processes. Invasive alien species (IAS) are any harmful non-native species (insects, fungi, plants, bacteria, viruses, etc.) whose introduction or spread threatens the environment, the economy, and/or society, including human health (Canada \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2015b\u003c/span\u003e). They can originate from any non-native geographic range, including continents, neighbouring countries, or other ecosystems within the same country (Canada \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2015b\u003c/span\u003e). Also, IAS can extend their geographical range beyond their natural dispersal through global trade, international shipments, and transportation (Paini and Yemshanov \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In that regard, risks for IAS new introductions or recurrence are simply higher without sufficiently sensitive biosurveillance protocols in place at ports of entry.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eBarcoded specimens\u003c/h2\u003e \u003cp\u003eBoth a shell and tissue fragment of \u003cem\u003eCepaea nemoralis\u003c/em\u003e were collected from shipping container debris from a container originating in Germany. \u003cem\u003eCepaea nemoralis\u003c/em\u003e is commonly known as the wood snail or banded grove snail, among others, and has been widely introduced nearly worldwide, intentionally and unintentionally (Dees \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1970\u003c/span\u003e; Mead \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e1971\u003c/span\u003e; Abbott \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1989\u003c/span\u003e). \u003cem\u003eCepaea nemoralis\u003c/em\u003e feeds primarily on plant detritus and, therefore, seldom acts as an agricultural pest but can damage crops in high numbers and is still considered a potential pest species by the United States Department of Agriculture (USDA) (Turton \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e1857\u003c/span\u003e; Dees \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1970\u003c/span\u003e; Thompson \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). There is also a concern about the potential negative impacts of non-native snails, such as \u003cem\u003eC. nemoralis\u003c/em\u003e, on native snail populations (Mead \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e1971\u003c/span\u003e; Cowie and Robinson \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Whitson \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The successful molecular identification of a morphologically unidentifiable tissue fragment present in a shipping container highlights the advantages of the DNA-based biosurveillance approaches over traditional methods. In the latter case, the morphological integrity of key morphological characters remains necessary for successful identifications. However, as reaffirmed here, effective molecular detections can be reached regardless of specimen morphological integrity and life cycle stage.\u003c/p\u003e \u003cp\u003eAscomycota DNA-based evidence was detected from a shipping container originating from China, potentially belonging to \u003cem\u003eCercospora sojina\u003c/em\u003e, a fungal plant pathogen with 14 races recorded in the country of container origin (Ma and Li \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). Unfortunately, there is low resolution for the COI fragment to unambiguously resolve at the fungi species level. \u003cem\u003eCercospora sojina\u003c/em\u003e causes frogeye leaf spots in most soybean-growing countries (Athow and Probst \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1952\u003c/span\u003e; Bernaux \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1979\u003c/span\u003e; Akem et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Ma \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). It was first reported in Japan in 1915 (Melchers \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1925\u003c/span\u003e), then in the United States in 1924 and is now present in 26 additional countries globally (Lehman \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1928\u003c/span\u003e; Lin and Kelly \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Reported losses of frogeye leaf spot range from 10–60%, making it an economically significant species (Bernaux \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1979\u003c/span\u003e; Dashiell and Akem \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Akem et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Ma \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Mian et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Lastly, a larval specimen belonging to the genus \u003cem\u003eTipula\u003c/em\u003e (Tipulidae) was detected from a shipping container originating in Germany. \u003cem\u003eTipula\u003c/em\u003e is the largest genus of the family, with over 2,400 species (Oosterbroek \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Larvae of \u003cem\u003eTipula\u003c/em\u003e sp. are indistinguishable morphologically at the genus level due to a significant variation in larval character states (Gelhaus \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1986\u003c/span\u003e), which makes DNA identification of larval specimens especially important. Although most species of \u003cem\u003eTipula\u003c/em\u003e are not invasive and generally not considered pests, there are at least two examples, such as \u003cem\u003eTipula paludosa\u003c/em\u003e and \u003cem\u003eTipula oleracea\u003c/em\u003e, considered invasive turfgrass pests in North America (Wilkinson and MacCarthy \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e1967\u003c/span\u003e; Gelhaus \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Current results ratify the capacity for successful molecular identifications at larval stages and tool utility in a regulatory context. Again, this constitutes an advantage over morphology-based identifications, where key traits are often linked to the adulthood life stage, or in some cases, there is simply a lack of taxonomic keys at the early stages of species development.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eMetabarcoding detections\u003c/h2\u003e \u003cp\u003eBark beetles (Subfamily \u003cem\u003eScolytinae\u003c/em\u003e) are among the most destructive forest pests globally (Grégoire et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Raffa et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). However, they also play an essential role in forest ecosystems as they typically live in dead or decaying plants and thus are critical early decomposers (Raffa et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Nevertheless, when droughts or extreme environmental events occur, bark beetles shift to occupying live trees, causing outbreaks and severe damage to forests (Wermelinger \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). eDNA from the spruce bark beetle (\u003cem\u003eIps typographus\u003c/em\u003e) was detected here; which is an endemic species to Eurasia (Wermelinger \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) but is now widespread from Europe, across Asia to Japan (EFSA Panel on Plant Health (PLH) et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2017a\u003c/span\u003e) (Global Biodiversity Information Facility [GBIF]) and ranks among the most destructive of the bark beetles (Grégoire et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). It is also one of the most common bark beetles to be intercepted at U.S. ports of entry (Haack \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), and it is predicted it could colonize select North American tree species if given a chance (Flø et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The potential presence of this species was detected in samples taken from a shipping container originating in China, demonstrating the effectiveness of molecular biosurveillance tools in early detection and signalling the need for a broader inspection of the flagged container.\u003c/p\u003e \u003cp\u003eOur study also detected \u003cem\u003eLymantria dispar\u003c/em\u003e eDNA in debris from a shipping container from Ghana, a country outside the recognized species' geographic distribution. Although containers can get \"contaminated\" elsewhere with a given IAS, border control in Canada will be needed first to detect them and then avoid their establishment and spread, irrespective of their origin. \u003cem\u003eLymantria dispar\u003c/em\u003e is typically treated as three subspecies, \u003cem\u003eL.d. dispar\u003c/em\u003e, \u003cem\u003eL.d. asiatica\u003c/em\u003e and \u003cem\u003eL.d japonica\u003c/em\u003e, with the subspecies \u003cem\u003eL. d. dispar\u003c/em\u003e endemic to Europe, Asia and North Africa between latitudes of 30°N and 60°N (Zahiri et al. \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Studies examining the possible future spread based on climatic and shipping port variables, among other variables, indicate a low likelihood of the species occurring in Ghana (Yanjun et al. \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Song et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Despite the low likelihood of spreading to Ghana, other factors that could explain the presence of \u003cem\u003eL. dispar\u003c/em\u003e eDNA in the shipping container: stops at different ports with established \u003cem\u003eL. dispar\u003c/em\u003e populations during its journey or having previously visited a country where contact with \u003cem\u003eL. dispar\u003c/em\u003e is likely, are possible explanations. Current information recorded by the CFIA on the specific shipping container (where \u003cem\u003eLymantria dispar\u003c/em\u003e eDNA was found) includes only the most immediate port of export. This implies that the IAS may have infiltrated the shipping container through previous origins or departures and remained undetected (Paini and Yemshanov \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The latter highlights the need to obtain the exact locations of all ports visited during each shipping expedition, as this information is necessary for concluding the possible distribution of \u003cem\u003eL. dispar\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cem\u003eFusarium oxysporum\u003c/em\u003e fungus eDNA was detected in shipping containers from Taiwan, China, Ghana, and Germany, although not linked to any specific \u003cem\u003eformae speciales\u003c/em\u003e. \u003cem\u003eFusarium oxysporum\u003c/em\u003e has many different host-specific strains, many of which are global in their distribution (Gordon \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Some strains of \u003cem\u003eF. oxysporum\u003c/em\u003e act as pathogens to various plant species; those that are wilt-causing are responsible for damaging many economically relevant plant species (Olivain and Alabouvette \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). \u003cem\u003eFusarium oxysporum\u003c/em\u003e is mainly managed through soil fumigation, which is environmentally damaging, or through breeding resistant cultivars, which is difficult when dominant genes are unknown and when new strains overcome host resistance (Fravel et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). In Canada, \u003cem\u003eFusarium oxysporum\u003c/em\u003e f. sp. \u003cem\u003ecannabis\u003c/em\u003e is considered a regulated pest, and its biosurveillance is essential to prevent any potential unfavourable impact in the hemp-related industry. Several strains of \u003cem\u003eF. oxysporum\u003c/em\u003e affecting cannabis were detected in British Columbia in 2013–2014 and reported in 2018 from Ontario and British Columbia. However, they have not been linked to f. sp. \u003cem\u003ecannabis\u003c/em\u003e. Thus, these strains are likely generalized crown and root rot forms of the pathogen \u003cem\u003eFusarium oxysporum\u003c/em\u003e and more research is needed to determine this pathogen's host range and distribution (Punja and Rodriguez \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). \u003cem\u003eFusarium oxysporum\u003c/em\u003e f. sp. \u003cem\u003ecannabis\u003c/em\u003e causes crown infection and root browning, ultimately leading to stunted growth, yellowing leaves and/or plant death (Punja \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Consequently, early detection along other potential routes of introduction is crucial to prevent future spread.\u003c/p\u003e \u003cp\u003e \u003cem\u003ePuccinia coronata\u003c/em\u003e eDNA was also detected in containers from Taiwan, China, Germany, and Iran. It is a fungus causing crown rust disease in oats (Nazareno et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), barley and wheat (Jin et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Niu et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), and some grasses (Jin and Steffenson \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). \u003cem\u003ePuccinia coronata\u003c/em\u003e is divided into multiple physiological variants (\u003cem\u003eformae speciales\u003c/em\u003e), which do not necessarily reflect genetic differences but are used to differentiate host preference (Nazareno et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The pathogen causing crown rust of oats is typically referred to as \u003cem\u003ePuccinia coronata\u003c/em\u003e f. sp. \u003cem\u003eavenae\u003c/em\u003e (Nazareno et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), which causes pustules to form on the leaves, leading to significant yield losses (Berlin et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Crown rust of oats is globally distributed and continues to cause epidemics with yield losses of up to 40% (Martinelli et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Nazareno et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSimilarly, \u003cem\u003ePuccinia graminis\u003c/em\u003e eDNA was detected in containers from Taiwan, China, and Germany, signalling a plant fungus known as stem rust, mainly affecting wheat and other cereals (Abbasi et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Many authors speculate that the fungus originated in Asia or North Africa and was spread globally by human activities (Abbasi et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). However, resistant strains of wheat and fungicide have been developed (Singh et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Bhattacharya \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Lewis et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and new variants have caused recent outbreaks and epidemics, leading to significant economic losses (Lewis et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Outbreaks include those in Germany and Ethiopia in 2013 (Olivera et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Lewis et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Sicily in 2016 (Bhattacharya \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eUrocystis agropyri\u003c/em\u003e, or flag smut of wheat, is an economically damaging fungal plant pathogen first reported in Australia in 1868 (McALPiNE \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1905\u003c/span\u003e; Ram and Singh \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Since then, it has spread globally, mainly via infected seed, to all continents and almost all wheat-growing Countries, including Canada (Pal Singh \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, flag smut in Canada only affects grasses and not wheat (Purdy \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e1965\u003c/span\u003e). The damaging effects of flag smut can cause losses of up to 100% in wheat crops (Purdy \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e1965\u003c/span\u003e; Pal Singh \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Once introduced, it persists for at least four and up to seven years (Purdy \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e1965\u003c/span\u003e; Pal Singh \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eGremmeniella abietina\u003c/em\u003e, found in containers with undisclosed country of origin, a fungus causing shoot blight and stem canker of conifers, has two distinct races in North America, both of which affect pine, spruce, larch and fir species (Government of Canada 2012; Botella and Hantula \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). It was first detected in North America in Michigan in the mid-1900s. The “European race” is the more virulent of the two strains and killed over 90% of pine trees in the Adirondack mountains of New York in 1974 (Government of Canada 2012). \u003cem\u003eGremmeniella abietina\u003c/em\u003e is found in most provinces in Canada, in the northeast U.S., all of Europe, Georgia, and Japan (Botella and Hantula \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). \u003cem\u003eGremmeniella abietina\u003c/em\u003e can survive under a wide range of climatic conditions and can be present in an endophytic (asymptomatic) stage for an undetermined period, giving it the potential to spread to new areas while making its detection at early stages especially difficult from a morphological perspective (EFSA Panel on Plant Health (PLH) et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017b\u003c/span\u003e). Using eDNA detection methods can facilitate early identification of this pest to control its spread.\u003c/p\u003e \u003cp\u003e \u003cem\u003eVenturia nashicola\u003c/em\u003e, or scab of Asian pear, occurs in China, Japan, South Korea and Taiwan and infects the Asian and Chinese pear (\u003cem\u003ePyrus pyrifolia\u003c/em\u003e var. \u003cem\u003eculta\u003c/em\u003e and \u003cem\u003eP. ussuriensis\u003c/em\u003e) (Chevalier et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Abe et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; González-Domínguez et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). It was also found in a container with undisclosed country of origin. This fungus is a distinct species and is host-specific to Asian pear varieties, as shown by various studies (Ishii and Yanase \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Park et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Abe et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). \u003cem\u003eVenturia\u003c/em\u003e species often infect the fruits of a plant, causing considerable economic losses in fruit crops (Sivanesan \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e1977\u003c/span\u003e). In Eastern Asia, \u003cem\u003eV. nashicola\u003c/em\u003e is one of the most serious pathogens in \u003cem\u003ePyrus pyrifolia\u003c/em\u003e var. \u003cem\u003eculta\u003c/em\u003e, \u003cem\u003eP. bretschneideri\u003c/em\u003e, and \u003cem\u003eP. ussuriensis\u003c/em\u003e. The pathogen causes fruit drop, cracking, and malformation. Current results ratify pathway risk assessment as one of the most critical tasks in preventing this IAS (Hulme \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdditionally, the current study detected eDNA from \u003cem\u003eDioscorea polystachya\u003c/em\u003e from shipping containers originating in Germany, Taiwan, and China, with no observed evidence of their propagules being present in the samples. \u003cem\u003eDioscorea polystachya\u003c/em\u003e, commonly called the Chinese Yam, is a regulated pest in Canada (Government of Canada 2016). It is a climbing vine species and has the potential to quickly spread to natural habitats, which can reduce biodiversity and damage other plant species (Government of Canada 2016). \u003cem\u003eDioscorea polsctachya\u003c/em\u003e is native to China but is now grown throughout East Asia in areas including Japan, Korea, the Kuril Islands, and Vietnam (Xu and Chang \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). \u003cem\u003eDioscorea polystachya\u003c/em\u003e was likely introduced to Japan and the United States around the 17th and 19th centuries, respectively, and is now considered invasive in those countries (Xu and Chang \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). \u003cem\u003eDioscorea polystachya\u003c/em\u003e is currently not established in Canada (Government of Canada 2016) but is more tolerant to frost than other yams (Xu and Chang \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), enabling it to survive the Canadian climate. Since this species has yet to be introduced to Canada, early detection through shipping container routes can help prevent its potential establishment.\u003c/p\u003e \u003cp\u003eOn the other hand, \u003cem\u003eSenecio inaequidens\u003c/em\u003e, commonly known as South African ragwort, is a flowering species native to South Africa. Its recent spread to Hawaii and Australia has had detrimental effects, including liver damage to livestock and humans (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://inspection.canada.ca/plant-health/invasive-species/invasive-plants/invasive-plants/south-african-ragwort/eng/1331757285388/1331757407583\u003c/span\u003e\u003cspan address=\"https://inspection.canada.ca/plant-health/invasive-species/invasive-plants/invasive-plants/south-african-ragwort/eng/1331757285388/1331757407583\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e While not discovered in Canada yet; there is a potential pathway due to high traffic between infected countries in Europe. Its eDNA was identified in containers from Germany, where it is known to be established.\u003c/p\u003e \u003cp\u003e \u003cem\u003eClavibacter michiganensis\u003c/em\u003e is a pathogen that causes bacterial canker disease in tomatoes. It is one of the most devastating agricultural diseases and is found in all regions of tomato production. In the present study, its eDNA was found in containers coming from Taiwan and Germany. The bacterium causes canker and wilt symptoms by invasion through open wounds and proliferation in the xylem (Nandi et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Young and well-fertilized plants in high humidity conditions are prone to infection, resulting in widespread crop loss in developing countries (Abo-Elyousr et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eImportance of molecular biosurveillance in shipping containers\u003c/h2\u003e \u003cp\u003eInvasive species, especially those that are small or undetectable, can often be missed even during intensive border surveillance of shipping containers, leading to increased spread through human-mediated pathways (Chapple et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In addition, limited funding and resources for biosecurity can result in a lack of thorough inspection of containers (Lucardi et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). A recent study showed that despite having global regulations in place for the proper treatment of wood packaging material used for global trade (eg., International Standards For Phytosanitary Measures No. 15 [ISPM 15]), pests' movement between borders continues to be detected, likely due to fraud, insufficient treatment and/or non-compliance (Greenwood et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In these cases, molecular biosurveillance has a significant advantage, as it can detect multiple invasive species cost-efficiently and more effectively than traditional methods (e.g., morphology IDs), regardless of size, morphological integrity, or life stage, while not being labour-intensive at the inspection phase. In order to successfully implement molecular biosurveillance in shipping containers, an expansive knowledge of shipping container history, including previous destinations or ports and their immediate origin, is necessary (Paini and Yemshanov \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). For example, Australian government policies only evaluate the immediate area of departure, allowing species from previous ports to infiltrate and remain hidden in marine shipping containers for extended periods, leading to increased spread and subsequent damage in different countries (Paini and Yemshanov \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe global shipping container trade transports various goods, ranging from seafood to fresh fruits, which require refrigerated shipping containers to preserve produce longevity (Lucardi et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Temperature-controlled shipping containers provide an ideal environment for harbouring IAS for several reasons, as they: i) contain air-intake grills which can collect propagules of IAS along their journey (Whitehurst et al. \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) ii) usually contain soil and debris which can behave as a reservoir for harmful bacteria and fungi, and iii) can prevent the degradation of harmful organisms (extending their viability) since they are temperature controlled (Whitehurst et al. \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Additionally, in creating an ideal environment for invasive organisms, temperature-controlled containers can also increase the preservation of an organism’s DNA, providing an opportunity for eDNA biosurveillance.\u003c/p\u003e \u003cp\u003eIAS negatively impact the economy, environment, and/or agriculture. The impacts on the agricultural sector can be expressed in terms of financial costs, with Canada losing 175\u0026nbsp;million CAD per year in efforts to manage the top ten alien species (Hulme \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Significant costs include management, monitoring efforts and loss of international trade. Plant pathogens, including bacteria, viruses, and fungi, affect North American crop yield the most, and without management, it would lead to a 51–82% loss of crops (Hulme \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). International and global trade agreements facilitate exchange but also allow new pathways for invasion, with Canada receiving 44% of imports from the USA or Mexico (Hulme \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Due to these regional agreements, most pests found at the Canadian border originate from the USA (Hulme \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Through early detection of invasive species by implementing effective eDNA metabarcoding protocols, detrimental effects of IAS can be minimized. By incorporating eDNA-based identification techniques, known IAS or regulated species can be accurately detected when working with large samples consisting of several species and can also be used to confirm prior morphological identification (Darling and Blum \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Milián-García et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, they can be combined with preexisting methods for cost-effective and reliable results, allowing us to trace the origins of a broad range of species.\u003c/p\u003e \u003cp\u003eAlthough IAS eDNA detection does not translate directly into viable species or their propagules' presence in the containers, especially for macroorganisms, it might not be the same for the microorganisms detected. For example, \u003cem\u003eFusarium oxysporum\u003c/em\u003e viability in soil samples can be observed for at least one year (Vakalounakis and Chalkias \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Paugh and Gordon \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). At the same time, \u003cem\u003eUrocystis agropyri\u003c/em\u003e can survive for four years in soil samples and even longer in favourable storage conditions. Similarly, \u003cem\u003eClaribacter michiganensis\u003c/em\u003e can remain viable in soil samples (Trevors and Finnen \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e1990\u003c/span\u003e), and propagules of \u003cem\u003eGremmeniella abietina\u003c/em\u003e can survive in branches left on the ground after two years (Laflamme and Rioux \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). It suggests that strict molecular biosurveillance approaches combined with microorganism viability tests may be a critical management tool for IAS prevention and mitigation risks.\u003c/p\u003e \u003c/div\u003e "},{"header":"Conclusions and perspectives","content":"\u003cp\u003eMolecular identification of invasive alien and Canadian-regulated species from complex samples collected from international shipping containers demonstrates to be an effective and powerful tool for detecting invaders in advance of their introduction, spread and establishment in new environments. Frequent biosurveillance integrating DNA-based techniques into the current CFIA toolkit is strongly suggested. The vast majority of IAS identified based on their eDNA in the present study were microorganisms (7/11), and additional viability tests might be critical for a more comprehensive risk assessment. Extending the battery of molecular markers for broader taxonomic identification (e.g., RBCL for plant identification) is also recommended. It is essential to highlight that IAS’ eDNA detection in shipping containers does not directly translate into viable IAS detection or their propagules. However, it might signal their presence and the need for deeper biosurveillance in cases where detection occurred.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eDeclaration of competing interest\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor contributions\u003c/h2\u003e \u003cp\u003eConceptualization, YMG and RHH; Data curation, YMG and CP; Formal analysis, YMG and CP; Funding acquisition, RHH; Investigation, YMG, CP, AC, KL; Methodology, YMG; Project administration, RHH and YMG; Resources, RHH; Validation, YMG, CP, AC, KL; Visualization, YMG and CP; Roles/Writing - original draft, YMG, CP, AC, KL; Writing - review \u0026amp; Editing, YMG, CP, AC, KL, RHH.\u003c/p\u003e\u003ch2\u003eAcknowledgment\u003c/h2\u003e \u003cp\u003eUoG-BIO acknowledges the financial support of the Canadian Food Inspection Agency (CFIA) [FAP#2122-002]. We sincerely thank all surveyors for contributing to the sample collection. We are deeply thankful to Ian Thompson for the support provided in imaging individual specimens. Yoamel Mili\u0026aacute;n-Garc\u0026iacute;a was supported by Mitacs through the Mitacs Elevate Program (IT34941).\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e \u003cp\u003eThe study complies with local and national regulations and guidelines. The datasets generated (Raw data [FASTQ files]) and/or analyzed during the current study are available in the NCBI Sequence Read Archive (SRA), accession PRJNA1073689, and the Borealis Research Data Repository (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5683/SP3/NVJO3S\u003c/span\u003e\u003cspan address=\"10.5683/SP3/NVJO3S\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbbasi M, Goodwin SB, Scholler M (2005) Taxonomy, phylogeny, and distribution of Puccinia graminis, the black stem rust: new insights based on rDNA sequence data. Mycoscience 46:241\u0026ndash;247. https://doi.org/10.1007/S10267-005-0244-X\u003c/li\u003e\n \u003cli\u003eAbbott RT (1989) Compendium of landshells. 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Accessed 29 Nov 2022g\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"biological-invasions","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"binv","sideBox":"Learn more about [Biological Invasions](https://www.springer.com/journal/10530)","snPcode":"10530","submissionUrl":"https://submission.nature.com/new-submission/10530/3","title":"Biological Invasions","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Biosurveillance, Invasive alien species, shipping containers, DNA barcoding, eDNA metabarcoding, arthropod, fungi, bacteria","lastPublishedDoi":"10.21203/rs.3.rs-4618423/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4618423/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe negative ramifications of invasive alien species (IAS) are considered the second-most cause of biodiversity extinction and endangerment after habitat modification. IAS movements are mainly anthropogenically driven (e.g., transport of shipping containers) and require fast detection to minimize damage and cost. The present study is the first to use molecular biosurveillance of international shipping containers to detect IAS and regulated species identification in Canada. Thirty-eight samples were collected from debris (soil, stems, seeds, individual specimens) found in containers arriving in Canada. A multi-marker approach using COI, ITS, ITS2, and 16S was used to identify four main taxonomic groups: arthropods, fungi, plants, and bacteria, respectively. Eleven IAS species were identified via metabarcoding based on environmental DNA samples, including two arthropods, six fungi, two plants, and one bacteria. The origin of the eDNA detected from each species was linked to their native distribution and country of origin, except for \u003cem\u003eLymantria dispar\u003c/em\u003e. Four physical specimens were also collected from shipping container debris and DNA barcoded, identifying three non-regulated species (two arthropods and one fungus). Altogether, these results demonstrate the importance of integrating molecular identification into current toolkits for the biosurveillance of invasive alien species and provide a set of validated protocols ready to be used in this context. Additionally, it reaffirms international shipping containers as a pathway for multiple invasive aliens and regulated species introduction in Canada. It also highlights the need to establish regular and effective molecular biosurveillance at the Canadian border to avoid new or recurrent invasions.\u003c/p\u003e","manuscriptTitle":"Uncovering the hidden within shipping containers: Molecular biosurveillance confirms a pathway for introducing multiple regulated and invasive species.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-26 15:54:39","doi":"10.21203/rs.3.rs-4618423/v1","editorialEvents":[{"type":"communityComments","content":2},{"type":"reviewerAgreed","content":"","date":"2024-07-03T14:31:29+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-02T15:35:15+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Biological Invasions","date":"2024-06-24T23:31:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-22T11:44:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Biological Invasions","date":"2024-06-21T12:12:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"biological-invasions","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"binv","sideBox":"Learn more about [Biological Invasions](https://www.springer.com/journal/10530)","snPcode":"10530","submissionUrl":"https://submission.nature.com/new-submission/10530/3","title":"Biological Invasions","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"373b3e05-5446-4f06-ba61-dae679522d30","owner":[],"postedDate":"July 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-03T16:02:30+00:00","versionOfRecord":{"articleIdentity":"rs-4618423","link":"https://doi.org/10.1007/s10530-025-03549-w","journal":{"identity":"biological-invasions","isVorOnly":false,"title":"Biological Invasions"},"publishedOn":"2025-02-24 15:57:59","publishedOnDateReadable":"February 24th, 2025"},"versionCreatedAt":"2024-07-26 15:54:39","video":"","vorDoi":"10.1007/s10530-025-03549-w","vorDoiUrl":"https://doi.org/10.1007/s10530-025-03549-w","workflowStages":[]},"version":"v1","identity":"rs-4618423","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4618423","identity":"rs-4618423","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}