Open access

Marine ecozones represent a major gap in Canadian DNA barcoding efforts

Publication: FACETS
18 October 2024

Abstract

Because of Canada’s large size, it is impractical to obtain a comprehensive perspective on biotic change through morphological approaches. DNA metabarcoding offers a potential path, but its application requires access to a well-parameterized DNA barcode reference library. This study presents the current state of DNA barcode coverage for Canadian animals, highlighting progress, identifying gaps, and providing recommendations for future research. Our analysis indicates that many of the known species (100 000 terrestrial and 6000 marine) in the Canadian fauna possess DNA barcode coverage, but there are important gaps geographically and taxonomically. We summarize DNA barcode coverage for the species in freshwater, marine, and terrestrial environments by ecoregion, finding that 95.6% of the 2.3 million Canadian barcode records derive from terrestrial ecosystems. Although the density of barcode records per 100 km² is 13x higher for terrestrial than aquatic environments (22.4 vs. 1.7), coverage for 58% of marine species is available (54% for annelids, 52% for arthropods, 88% for chordates, 39% for echinoderms, and 46% for molluscs). By revealing data-deficient areas and taxonomic groups, this study offers a roadmap for expanding the DNA barcode library for the Canadian fauna as an essential foundation for the scalable biosurveillance initiatives that inform biodiversity conservation efforts.

Graphical Abstract

Introduction

To protect species and the ecosystem services which they provide, comprehensive monitoring is critical to understand the trends, risks, and drivers of biodiversity loss (Pimm et al. 2014; Hochkirch et al. 2021). However, biodiversity monitoring in Canada is challenging because of its status as the world’s second-largest nation and the difficulty in accessing remote areas (Archambault et al. 2010). This is particularly true for marine habitats because sampling requires expensive ship support (Archambault et al. 2010). With the world’s longest coastline bordering three oceans and an estimated 71%–91% of marine taxa undescribed (Costello et al. 2010; Mora et al. 2011; Appeltans et al. 2012; Luypaert et al. 2020; Bouchet et al. 2023; Rogers et al. 2023), there are substantial gaps in knowledge of the Canadian marine fauna.
By differentiating species based on standardized DNA regions (Hebert et al. 2003; Hebert et al. 2003), DNA barcoding makes it possible to map species distributions at scale. It not only enables estimates of species diversity, but also aids the recognition of unknown species and tracking biodiversity changes over time (Deiner et al. 2017). DNA barcoding also makes it possible to monitor diversity in lineages whose taxonomy is weakly developed, providing the spatially explicit and taxonomically comprehensive data needed to evaluate changes in species distributions in response to environmental change (Archambault et al. 2010; Hochkirch et al. 2021; Borgelt et al. 2022). Building on the capabilities provided by the Barcode of Life Data System (BOLD) (Ratnasingham and Hebert 2007, 2013), Canada has been the global leader in this approach, significantly advancing the understanding and conservation of its biodiversity. However, gaps in the sequence database hinder scalable, high-resolution biosurveillance (Leray and Knowlton 2016; Sinniger et al. 2016; Weigand et al. 2019).
DNA barcode records include a voucher specimen, its taxonomic assignment, details on its point and time of collection, and a barcode sequence (Ratnasingham and Hebert 2013). Once a species enters BOLD, members of the same taxon can be rapidly identified from their DNA barcode whether derived from a single specimen, from bulk samples (DNA metabarcoding), or from environmental samples (eDNA) such as water, air, soil, or sediment (Ruppert et al. 2019). However, when analysis of metabarcoding or eDNA samples reveals sequences unrepresented in the reference library, the inferred taxonomic composition is incomplete or inaccurate (Beng and Corlett 2020). While taxonomy-free approaches for assessing biodiversity from molecular analysis escape this problem (Apothéloz-Perret-Gentil et al. 2017; Callahan et al. 2017; Mächler et al. 2021), they fail to connect sequences with the biological attributes of the species that served as their source. As a consequence, species identifications remain essential for understanding ecology, functional roles, population genetics, and tracking invasive or endangered species.
A key step in directing future work in library construction involves summarizing progress in securing DNA barcode coverage from a biogeographic perspective. Ecological land classifications delineate geographic regions (e.g., provinces, ecoregions, and ecozones) based on geological, climatic, and biotic differences (Omernik 1995). As such, these units provide a framework for understanding spatial complexity, conducting biological risk assessments, and directing conservation action (Omernik 1995; Smith et al. 2020; Spalding et al. 2007).
In this study, we evaluate DNA barcode coverage for each of Canada’s 28 ecozones to identify variation in coverage among them and to highlight taxonomic groups lacking data. Summarizing the number of barcode records by ecozone allowed a comparison of terrestrial and aquatic habitats. Additionally, we investigated barcode coverage for Canadian marine invertebrates across taxonomic groups to highlight gaps and aid prioritization of future efforts.

Materials and methods

To assess DNA barcode coverage for the Canadian fauna, we downloaded all public Canadian records from BOLD (Ratnasingham and Hebert 2007, 2013; accessed 6 June 2022). Each record with GPS coordinates was assigned to one of Canada’s 28 ecozones (15 terrestrial, 12 marine, and 1 freshwater) (Fig. 1). Canada’s National Ecological Framework (Ecological Stratification Working Group 1995; Marshall et al. 1996; Hirvonen 2001) was used to define ecozone boundaries (Fig. 1). Shapefiles were downloaded from the National Ecological Framework website (Government of Canada 2017; accessed 8 October 2022) for terrestrial ecozones, and from the Canadian Council on Ecological Areas website (CCEA 2015; accessed 8 October 2022) for aquatic ecozones. Both sets of ecozones have 1 m resolution. We compared the total number of records, records per ecozone, and records per 100 km2 for terrestrial and aquatic ecozones. In addition, we plotted the accumulation of unique BINs and species as a function of the number of barcode records for terrestrial and aquatic organisms. To do this, we randomized the list of records and sampled without replacement, counting the number of unique BINs or species accumulated until the records were exhausted. This process was repeated 100 times, and values at each sample size were averaged to produce a smooth line.
Fig. 1.
Fig. 1. (A) Boundaries of the 15 Canadian terrestrial ecozones and (B) boundaries of the one freshwater and 12 marine and ecozones, as defined by the National Ecological Framework (Ecological Stratification Working Group 1995; Marshall et al. 1996; Hirvonen 2001). Basemap and ecozone boundaries are from the National Ecological Framework website (Government of Canada 2017; accessed 8 October 2022) for terrestrial ecozones, and from the Canadian Council on Ecological Areas website (CCEA 2015; accessed 8 October 2022) for aquatic ecozones. Maps use the geographic coordinate system and the NAD83 (CSRS98) coordinate system.
For marine animals, we also summarized barcode progress by taxonomic group. We downloaded publicly available BOLD records (accessed 20 August 2022) whose identification matched marine species or genera in the Canadian Register of Marine Species (CaRMS) (CaRMS 2022, accessed 8 October 2022). Records using synonymized or otherwise invalid names were relabelled with the accepted name. BOLD assigns a Barcode Index Number (BIN; a species proxy) to each sequence record that meets specified quality requirements (>500 bp in length, <1% ambiguous bases, no frameshifts, contaminants, or chimeras) and possesses complete metadata (sample ID, field or museum voucher ID, phylum, country, and institution storing the specimen) (Ratnasingham and Hebert 2013). For each animal phylum, we summarized the number of accepted Canadian species, the number of accepted species with at least one record on BOLD, the number of accepted species with at least one BIN, the total number of records, and the total number of unique BINs. We calculated coverage as the percentage of described species with at least one BIN. We also summarized coverage and average BINs per species by family (see Supp. Data Table S1).

Results

In total, 2.3 million Canadian animal specimens have been barcoded, providing coverage for 85 706 BINs and 37 327 named species. Most of these records (94.7%) include GPS coordinates for the collection location, enabling their assignment to an ecozone. Of these, 98.5% of records were arthropods. The total area of Canada’s terrestrial ecozones is about 50% greater than its aquatic ecozones, but the difference in barcode records was far greater as 95.6% (2213 305) derived from land, while just 4.4% (100 894 records) were from water (Tables 1 and 2). Coverage among ecozones showed >1000-fold variation (Fig. 2). Terrestrial ecozones showed a 100-fold range from 6023 records (Taiga Shield;Fig. 2A, #15; Table 1) to 667 342 (Mixedwood Plains; Fig. 2A, #7; Table 1). Marine ecozones showed nearly a 1000-fold range from 29 (Arctic Archipelago; Fig. 2B, #22) to 22 062 (Gulf of Saint Lawrence; Fig. 2B, #27). The number of records on an areal basis averaged 22.4 records per 100 km2 for land (Table 1) versus 1.7 records per 100 km2 for water (Table 2), but records were not evenly distributed within ecozones (Fig. 3). Specimens collected within terrestrial ecozones included representatives for 78 139 BINs and 23 775 named species, while the specimens collected within aquatic ecozones included 12 535 BINs and 6 117 species (Fig. 4). The ratio of BINs to species was 3.29 for terrestrial records and 2.04 for aquatic records (Fig. 4).
Fig. 2.
Fig. 2. The number of public Barcode of Life Data System (BOLD) records for (A) terrestrial and (B) marine/freshwater ecozones. The black arrow indicates the single freshwater ecozone (Great Lakes). n = 2314 199 georeferenced records. Basemap and ecozone boundaries are from the National Ecological Framework website (Government of Canada 2017; accessed 8 October 2022) for terrestrial ecozones, and from the Canadian Council on Ecological Areas website (CCEA 2015; accessed 8 October 2022) for aquatic ecozones. Maps use the geographic coordinate system and the NAD83 (CSRS98) coordinate system.
Fig. 3.
Fig. 3. Coordinates of public Barcode of Life Data System records (red dots) within Canada’s three marine regions: (A) Pacific Region, (B) Arctic Region, and (C) Atlantic Region. n = 60 132 georeferenced records. Basemap and ecozone boundaries are from the National Ecological Framework website (Government of Canada 2017; accessed 8 October 2022) for terrestrial ecozones, and from the Canadian Council on Ecological Areas website (CCEA 2015; accessed 8 October 2022) for aquatic ecozones. Maps use the geographic coordinate system and the NAD83 (CSRS98) coordinate system.
Fig. 4.
Fig. 4. Cumulative Barcode Index Numbers (BINs) and species as a function of number of specimens for terrestrial and aquatic DNA barcodes. Note the scales differ between panels.
Table 1.
Table 1. The area, number of georeferenced public Barcode of Life Data System records and records per 100 km2 for each of the 15 Canadian terrestrial ecozones.
EcozoneNameArea (km2)RecordsRecords per 100 km2
1Arctic Cordillera244 56828 15911.5
2Atlantic Maritime201 735237 720117.8
3Boreal Cordillera470 758139 47229.6
4Boreal Plain740 69399 48713.4
5Boreal Shield1886 657228 90912.1
6Hudson Plain375 66587 83123.4
7Mixedwood Plains115 103667 342579.8
8Montane Cordillera489 977363 02774.1
9Northern Arctic1521 95160 3654.0
10Pacific Maritime208 927100 27548.0
11Prairie467 029118 79225.4
12Southern Arctic852 23027 8553.3
13Taiga Cordillera266 97218 9657.1
14Taiga Plain657 77829 0834.4
15Taiga Shield1393 22760230.4
 Total9893 2692213 30522.4
 Mean659 551147 55464
 SD537 785174 673146
Table 2.
Table 2. The number of georeferenced public Barcode of Life Data System records and records per 100 km2 for each of Canada’s 12 aquatic ecozones.
EcozoneNameArea (km2)RecordsRecords per 100 km2
16Strait of Georgia896918 690208.38
17Southern Shelf28 159361112.82
18Offshore Pacific315 7241540.05
19Northern Shelf101 66333893.33
20Arctic Basin751 988740.01
21Western Arctic539 86215190.28
22Arctic Archipelago268 800290.01
23Eastern Arctic782 56612890.16
24Hudson Bay Complex1244 67046190.37
25Newfoundland-Labrador Shelves1054 42214900.14
26Scotian Shelf416 25532060.77
27Gulf of Saint Lawrence246 64822 0628.94
28Great Lakes88 36840 76246.13
 Total5848 094100 8941.73
 Mean449 853776122
 SD400 48212 16958
Despite the low sampling effort geographically, 60.5% of the marine animal species in CaRMS (n = 6373) were represented in BOLD by at least one record (Table 3). Most of these taxa possessed a high-quality sequence as 57.8% of the species on the CaRMS list were represented by at least one BIN (Fig. 5; Table 3) with an average of 39.3 records (±115 SD) per species, but 9.7% had just a single record. On average, 45.5% of known species for the 23 phyla in CaRMS possessed a BIN on BOLD. One phylum (Nematomorpha) lacked coverage, while all four species of Phorinida and 88.1% of the 1834 species of Chordata had coverage (Table 3). Among the 151 601 records for Canadian marine taxa, 74.7% derived from two phyla (Fig. 5; Table 3): Chordata (75 881 records) and Arthropoda (37 304 records). Coverage for the major marine groups was 54.4% for Annelida (55.3% for Polychaeta); 51.7% for Arthropoda (51.1% for Crustacea, 90.9% for Balanomorpha, 81.4% for Decapoda, and 54.3% for Peracarida); 88.1%% for Chordata (94.6% for Tetrapoda, 92.0% for Chondrichthyes, 38.7% for Tunicata, and 89.0% for Actinopterygii); 39.2% for Echinodermata (33.4% for Asteroidea, 100% for Crinoidea, 47.2% for Holothuroidea, and 76.0% for Ophiuroidea); 45.5% for Mollusca (45.9% for Bivalvia, 43.3% for Gastropoda, and 72.7% for Polyplacophora) (Tables 3 and 4). Family-level coverage averaged 56.3% (±42.3%) across phyla, and the highest ratio of BINs to species was 39 for one species in the family Hippothoidae (Bryozoa) (Supp. Data Table S1).
Fig. 5.
Fig. 5. Bar graph showing the number of species in 23 animal phyla with/without DNA barcode coverage for (A) phyla with >50 accepted species and (B) phyla with <50 accepted species. n = 6373 described species the Canadian Register of Marine Species (2022).
Table 3.
Table 3. Progress in assembling DNA barcode coverage for Canadian marine animal species by phylum, including the number of accepted Canadian species according to the Canadian Register of Marine Species (2022), the number of species with at least one record, the number of species with at least one Barcode Index Number (BIN), coverage (% of accepted species with at least one BIN), the total number of records on Barcode of Life Data System (BOLD), and the number of BIN-compliant records on BOLD.
PhylumAccepted speciesSpecies with recordsSpecies with BINsCoverage (%)Total recordsBIN-compliant records
Chordata18341633161588.175 88165 798
Arthropoda158985782151.737 30432 507
Mollusca80238236445.415 58612 660
Annelida57933131554.474716 732
Echinodermata50822219939.260094 563
Cnidaria35922520456.845523 687
Platyhelminthes2161562.8647393
Bryozoa183635127.9766657
Nematoda971799.347886
Porifera62322946.8338285
Nemertea38222257.9730705
Acanthocephala34181441.2560481
Chaetognatha17111058.8929653
Xenacoelomorpha125541.755
Kinorhyncha94444.477
Ctenophora76228.610013
Entoprocta53360.01010
Hemichordata54480.03333
Rotifera51120.022
Brachiopoda41125.02424
Phoronida444100.04241
Priapulida32266.7127126
Nematomorpha1000.000
Total63733858368557.8151 601129 468
Table 4.
Table 4. Progress in assembling DNA barcode coverage for taxonomic groups within the major marine animal phyla: Annelida, Arthropoda, Chordata, Echinodermata, and Mollusca, including the number of accepted Canadian species according to the Canadian Register of Marine Species (2022), the number of species with at least one record, the number of species with at least one Barcode Index Number (BIN), coverage (% of accepted species with at least one BIN), the total number of records on Barcode of Life Data System (BOLD), and the number of BIN-compliant records.
PhylumGroupAccepted speciesSpecies on BOLDSpecies with BIN(s)Coverage (%)Total recordsBIN-compliant records
AnnelidaClass Polychaeta54431730155.369496213
ArthropodaSubphylum Crustacea154682479051.132 48928 004
Order Balanomorpha11111090.923142204
Order Decapoda18815615381.497008285
Superorder Peracarida59734232454.398688646
 Order Amphipoda38123422158.082857174
 Order Isopoda84494756.0573514
ChordataMegaclass Tetrapoda16816015994.651434678
Parvphylum Chondrichthyes11310410492.010 3368704
Subphylum Tunicata62302438.719721401
Gigaclass Actinopterygii14771326131589.058 10350 711
EchinodermataClass Asteroidea37714512633.426172002
Class Crinoidea222100.01611
Class Echinoidea72373447.217381118
Class Holothuroidea32181856.3575562
Class Ophiuroidea25201976.01063870
MolluscaClass Bivalvia24611911345.959914445
Class Gastropoda49022021243.381727010
Class Polyplacophora119872.7197183

Discussion and conclusions

Considerable progress has been made in assembling a DNA barcode reference library for the Canadian fauna, but 95.6% of the 2.4 million records derive from terrestrial settings versus 4.4% for aquatic environments. On an areal basis, the number of records differs 13-fold between these two environments with 22.4/100 km2 versus 1.7/100 km2. Viewed from a taxonomic basis, BOLD has barcodes for 57.8% of described Canadian marine species, but certain phyla were underrepresented or absent. We highlight several important gaps that warrant targeted efforts going forward.
Our geographic analysis revealed major gaps in coverage for marine ecozones and northern regions. Marine records were concentrated along coastlines and inshore areas close to population centers, reflecting the fact that sampling remote marine settings requires substantial resources (Archambault et al. 2010). For this reason, northerly ecozones have received little attention as evidenced by two Arctic marine ecozones (Arctic Basin and Acric Archipelago) with fewer than 100 records (74 and 29, respectively). Significant gaps in barcode coverage were also evident in northern terrestrial ecozones. More than 0.5 million records derive from the Mixedwood Plains, Canada’s most southerly ecozone, while five of six arctic and subarctic ecozones had fewer than 30 000 records each. A direct comparison of sampling effort among biomes and ecozones is difficult because the distribution of organisms is not uniform. Since the number of records from remote regions may be doubly impacted by low biodiversity and by the concentration of sampling in more easily accessible areas, environments such as the open ocean and north should be prioritized for sampling. Addressing gaps in northern areas experiencing rapid warming is crucial for understanding the impacts of climate change (WWF 2022; IPCC 2023).
Sampling continued to capture new BINs as more specimens were analyzed in both terrestrial and aquatic ecozones. Despite the higher number of BINs relative to species, the terrestrial curves were closer to an asymptote than the aquatic curves, reflecting the extensive sampling effort on land. Aquatic records had twice as many BINs as species, a value higher than the 1.5x BINs per species found in a similar analysis in Europe (Leite et al. 2020). This difference may be driven by a few groups with many BINs per species, such as the bryozoan family Hippothoideae. The summary of barcode coverage by family (Supp. Data Table S1) provides a roadmap for prioritizing future efforts where the concentration of genetic diversity is likely the greatest.
Our summary of coverage by ecozone did not recover the same data as our summary by taxonomy. In fact, our geographic summary recovered 6117 aquatic species while our taxonomic summary recovered records for just 3858 species. Given this discordance, our sampling may be even lower for marine ecozones than suggested by our geographic analysis. The additional taxa attributed to aquatic ecozones in the geographic analysis likely included some terrestrial specimens collected along shorelines. As well, our aquatic ecozone analysis included the freshwater Great Lakes ecozone while the taxonomic analysis was restricted to marine taxa. Finally, some species within the taxonomic dataset with ranges extending either southwards or into Alaska may have been collected in the USA. While specimens collected elsewhere remain important as reference sequences, they may differ genetically from their Canadian conspecifics. Future work could assess whether any species have only been collected outside of Canada so sampling efforts can prioritize these groups.
The barcode coverage for described Canadian marine species from our taxonomic analysis is encouraging. Weigand et al. (2019) reported barcodes for just 22% of European marine species, while Leite et al. (2020) found 37% coverage within Atlantic Iberia. Coverage within major marine phyla was also lower in Europe than Canada (Weigand et al. 2019; Leite et al. 2020). However, among phyla with 50 or more described species, Nematoda and Platyhelminthes were severely under-represented in Canada. In addition, the checklist of marine animals for Canada is suspiciously low: it includes just 6373 species compared to Europe’s 16 962 species (Weigand et al. 2019) for a much smaller area. Certainly, taxonomic studies on the European marine fauna have been underway for far longer than similar work in Canada, and the number of taxonomists is much higher (Archambault et al. 2010). Accordingly, the apparently high coverage for the Canadian marine fauna may be an artefact of an incomplete species checklist rather than more comprehensive DNA barcode coverage.
Although more than half of the marine animal species known from Canada are on BOLD, the actual proportion of marine species with DNA barcodes is certainly lower because the CaRMS is incomplete as most marine species are undescribed. While CaRMS lists 7100 species across all kingdoms (CaRMS 2022), Archambault et al. (2010) estimated a final count of 15 988–61 148 marine species. Globally, 71%–91% of marine species are thought to be undescribed (Costello et al. 2010; Mora et al. 2011; Appeltans et al. 2012; Luypaert et al. 2020; Bouchet et al. 2023; Rogers et al. 2023). Despite recent improvements in constructing accessible reference libraries (Bucklin et al. 2021), the taxonomic diversity and deep evolutionary history of marine invertebrate lineages can complicate DNA barcode recovery (Radulovici et al. 2010; Bucklin et al. 2011; Lobo et al. 2013). For marine invertebrates, where specimen identifications can be slow to acquire (Ramirez et al. 2020), there is a need to reinforce collaborations between taxonomists and molecular biologists. Unfortunately, there are too few taxonomists to meet the need (Engel et al. 2021), and little funding for taxonomic research (Rogers et al. 2023). As a result, marine taxonomy is increasingly dependent upon retired experts and amateur scientists (Bouchet et al. 2023).
Additional limitations of current barcode coverage are the small number of public records for many species and discordances in taxonomic assignments. While our analysis did not include private records, coverage would be substantially improved by their inclusion (Weigand et al. 2019). Understanding species distributions, abundances, and trends over time requires multiple records per species (Hochkirch et al. 2021; Cowie et al. 2022), but many species on BOLD are currently represented by a single record (Weigand et al. 2019). For organisms with a broad geographic range, 14–25 records may be needed to evaluate the extent of regional variation (van Proosdij et al. 2016). Acquiring multiple barcodes per species is especially important for groups with high intraspecific variation or multiple BINs per species, where multiple sequences are needed to understand barcode variation (Meyer and Paulay 2005; Leite et al. 2020). A review of major marine invertebrate groups on BOLD found that 24% of species include misidentifications, ambiguities, or discordances, often reflecting taxonomic challenges (Radulovici et al. 2021). Addressing these limitations is crucial to enhance the effectiveness of DNA barcode reference libraries (Weigand et al. 2019; Fontes et al. 2021).
As arthropods are, by far, the most diverse animal phylum (Larsen et al. 2017), most Canadian barcoding efforts have focused on them (Pentinsaari et al. 2020; Young et al. 2021; Lowe et al. 2022). The resulting records address a critical need for biodiversity monitoring and conservation planning for species weakly represented in frameworks such as the IUCN Red List (IUCN 2023) which is focused on mammals and birds (Hochkirch et al. 2021). Geographic coordinates enhance the value of barcode data for tracking species distributions, range size, regional differences, invasive species, and susceptibility to anthropogenic pressures (Pimm et al. 2014; Seebens et al. 2021). Combining large-scale biodiversity databases like BOLD with spatial data on land and sea will provide a powerful tool for advancing progress towards biodiversity protection targets (Pimm et al. 2014).
The intensive studies on terrestrial organisms have reshaped knowledge of biodiversity patterns, including evolutionary insights and ecological patterns (Costa and Carvalho 2010; Joly et al. 2014; Mir et al. 2021). Barcoding has revealed hidden diversity in many insect orders, such as Lepidoptera (Hebert et al. 2004; D'Ercole et al. 2023), Coleoptera (Brunke et al. 2019; Pentinsaari et al. 2019), and Diptera (Bukowski et al. 2022; Chimeno et al. 2022). It has also challenged traditional taxonomic classifications, prompting revisions in species counts and altering our understanding of key biodiversity nodes (Stork 2017). DNA barcoding studies of marine invertebrates have also unveiled cryptic diversity (Carr et al. 2011; Matzen da Silva et al. 2011; Layton et al. 2014; Brasier et al. 2016; Vieira et al. 2022) and the steep slope of our species accumulation curve for marine species indicates that increased sampling in marine environments will reveal many more taxa. These cases of cryptic diversity suggest that further DNA barcoding and metabarcoding will continue to provide important insights into marine biodiversity, mirroring its success in terrestrial ecosystems (Hupało et al. 2019; Vieira et al. 2019, 2022).
In conclusion, this study has documented significant progress in building a DNA barcode reference library for the Canadian fauna, but it has also revealed geographic and taxonomic gaps. Marine environments, particularly northern and open ocean regions, require far more attention. Our results provide a roadmap for DNA barcoding efforts to address data gaps and to improve the quality of reference libraries. Potential paths for expanding taxonomic and regional coverage include dedicated initiatives that prioritize indicator species and target phylogenetic gaps (Weigand et al. 2019) and leveraging regular offshore surveys conducted by federal agencies such as Fisheries and Oceans Canada. This strategic approach will advance the scalability and cost-effectiveness of the molecular biosurveillance programs crucial for global biodiversity assessment and conservation (Compson et al. 2020; Grant et al. 2021; Ray et al. 2021).

Acknowledgements

This project was enabled by an NSERC Discovery grant to PDNH, by an NSERC CGS-D Scholarship to JS, and by an Accelerate Fellowship from MITACS. We thank Chris Ho, Adriana Radulovici, Sujeevan Ratnasingham, and Tyler Elliott for aiding data analysis and for their revisionary suggestions to the manuscript. This work was carried out at the University of Guelph that is situated within the treaty lands and territory of the Mississaugas of the Credit. The Anishinnabe and Hodinöhsö:ni′ peoples also have long-standing and on-going relationships with this land and each other while the Attawandaron people are represented in the archaeological record.

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Supplementary material

Supplementary Material 1 (XLSX / 102 KB).

Information & Authors

Information

Published In

cover image FACETS
FACETS
Volume 9Number 1January 2024
Pages: 1 - 11
Editor: Michael Rennie

History

Received: 22 January 2024
Accepted: 9 July 2024
Version of record online: 18 October 2024

Data Availability Statement

Data used in this study are publicly available on the Barcode of Life Data System (BOLD; https://boldsystems.org/). Supplemental data tables S1 contains family-level DNA barcode coverage information for marine animal phyla.

Key Words

  1. biogeographic regions
  2. biodiversity
  3. conservation
  4. marine invertebrates
  5. DNA barcoding
  6. species distribution

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Plain Language Summary

DNA Barcoding and Biodiversity in Canada: Progress, Gaps, and the Path Forward for Conservation

Authors

Affiliations

Department of Integrative Biology, University of Guelph, Guelph, ON, Canada
Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
Author Contributions: Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, and Writing – review & editing.
Paul D.N. Hebert
Department of Integrative Biology, University of Guelph, Guelph, ON, Canada
Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
Author Contributions: Conceptualization, Data curation, Funding acquisition, Methodology, Project administration, Resources, Supervision, and Writing – review & editing.

Author Contributions

Conceptualization: PDNH
Data curation: JAS, PDNH
Formal analysis: JAS
Funding acquisition: PDNH
Investigation: JAS
Methodology: JAS, PDNH
Project administration: PDNH
Resources: PDNH
Supervision: PDNH
Visualization: JAS
Writing – original draft: JAS
Writing – review & editing: JAS, PDNH

Competing Interests

The authors declare no competing interests.

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