Unravelling Antarctic Coastal Waters: Exploring Marine Biodiversity and Detecting Potential Invasive Species via eDNA Metabarcoding in South Bay, Doumer Island

doi:10.21203/rs.3.rs-4614931/v1

Download PDF

Research Article

Unravelling Antarctic Coastal Waters: Exploring Marine Biodiversity and Detecting Potential Invasive Species via eDNA Metabarcoding in South Bay, Doumer Island

https://doi.org/10.21203/rs.3.rs-4614931/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

The average global temperature has increased significantly in recent decades, with no exception for the polar regions, including the Arctic and Antarctica. In Antarctica, this climate change directly affects the Antarctic Peninsula, which experienced significant temperature increases between 1979 and 2019. Doumer Island, located in the Palmer Archipelago of the Western Antarctic Peninsula, has become an important location both as an Antarctic Specially Protected Area 146 and as a witness to the future changing ecosystem, since South Bay of Doumer Island is recognized as one of the global warming hotspots.

The use of eDNA metabarcoding has been shown to be a successful approach in accurately capturing the diversity of marine ecosystems. In this study, eDNA analysis was utilized to monitor biodiversity and detect non-native species in South Bay, Doumer Island. Seawater samples were collected from four sampling stations near the Chilean Antarctic scientific base Yelcho (64.9° S, 63.6° W) aboard a boat. We present additional data on the coastal pelagic community for the first time, expanding the biodiversity records of western coastal Antarctica. This includes newly discovered species as well as potential non-native species in South Bay near the Yelcho base.

Our results indicate that eDNA analysis is an effective method for assessing marine biodiversity and detecting invasive species. However, the technique has some limitations that need to be addressed. The reference DNA databases for Antarctic species are incomplete, which impedes accurate species identification from eDNA samples. Consequently, further research is necessary to enhance these databases and improve taxonomic descriptions.

Antarctica

Biological invasion

eDNA

Doumer Island

Yelcho Base

ASPA 146

The average global temperature has increased significantly since the beginning of the 20th century (Pörtner et al, 2022). These climate changes directly affect Antarctica, especially the Antarctic Peninsula, with particularly high temperature increases during 1979–2019 (Turner et al, 2021). Doumer Island is an island in the Palmer Archipelago of Western Antarctic peninsula (WAP). This place is also considered important for scientific study due to the one of the global warming hot spot in Antarctica. In particular, the South Bay (64.9° S; 63.6° W) of Doumer Island is an area appointed as the Antarctic Specially Protected Area (ASPA) 146 to minimize human intervention and preserve conditions for future research. Different benthic microhabitats have been observed in this area, such as rocky areas with algal growth up to 30 meters deep, predominantly rocky areas covered with algae, sediments, and sponges up to 110 meters deep, mixed bottoms with mud deposits and some rock outcrops with sponges up to 150 meters, and soft sediment and mud bottoms up to 200 meters (Rovelli et al, 2019; Morales et al, 2024). Notably, this area is characterized by a rich benthic fauna, especially in the coastal zone up to 45 meters deep, and possess significant biodiversity attributes. In addition, as much as this regional importance, several invertebrates, such as gastropods, Cnidarians (Anthozoa), amphipods, and euphausiids, are widely distributed as endemic species in South Bay of Doumer Island, including various macroalgae; at least 6 groups of 112 species have been reported (Morales et al, 2024). However, recent, this area has already recorded significant increase in seawater temperature (Cárdenas et al, 2018; Villegas et al, 2018). This warming is not only a threat to marine ecosystem, but it can also contribute to the invasion of alien species, directly and indirectly (Sahade et al, 2017; Cárdenas et al, 2020). In Antarctica, various invasive species have been reported due to the effects of climate change;it is known that approximately 13% of the Antarctic species are considered locally invasive (Leihy et al., 2023). A variety of invasive species have been observed in Antarctica as non-native marine animal species, including chordatiere, cnidarians, bryozoans, brachyurans, and anomurans (McCarthy et al, 2018). Particularly, Granaster nutrix, which has not been registered in South Bay to date, has also been reported as a new species (Morales et al., 2024). However, only few studies have been reported based on SCUVA diving and image analysis from photoquardrats of marine benthic fauna, and the data about coastal pelagic community are insufficient. The impact of climate changes can result in many biological responses, such as changes in the distribution of species in Antarctic marine species, changes in the biological niche, and potential settlement and spread of invasive species. Therefore, study on the presence of non-native species in coastal pelagic zone is needed in western Antarctic waters along with native marine species.

Environmental DNA (eDNA) metabarcoding methodologies, has emerged in recent years as a promising tool for generating biotic surveys of marine ecosystems (Koziol et al. 2018, Sahu et al. 2023). These methods entail extracting and analyzing genetic material from environmental samples like seawater, biofilm, and sediment to detect and identify various aquatic organisms (Valentini et al., 2016; Stat et al., 2017; Monuki et al., 2021; Feng et al., 2022; West et al., 2020; Fujii et al., 2019; Bylemans et al., 2019; Suter et al., 2020; Havermans et al., 2022).The application of eDNA metabarcoding has proven to be a successful method for accurately capturing the diversity of marine fish assemblages (Thomsen et al., 2012), mesozooplankton (Feng et al., 2022), coral reef communities (West et al., 2020), and freshwater fishes (Bylemans et al., 2019). It has also been utilized to detect deep-sea fishes (McClenaghan et al., 2020), depth partitioning in kelp forest ecosystems (Monuki et al., 2021), and tropical shark diversity (Bakker et al., 2017). Furthermore, eDNA metabarcoding has been applied to monitor aquatic biodiversity in various marine habitats, such as nearshore rocky reef environments (Ely et al., 2021), and the open ocean (Suter et al., 2020). The application of eDNA metabarcoding in marine environments has several advantages, such as the capacity to minimize the required sampling effort and taxonomic expertise required for biodiversity surveys (McClenaghan et al., 2020). It also provides a non-invasive and less labor-intensive method for biological surveys (Wei et al., 2019). Additionally, eDNA metabarcoding has been shown to be effective in capturing fine-scale community variation across remote tropical island ecosystems (West et al., 2020). However, it is important to note that the effectiveness of eDNA metabarcoding can be influenced by factors such as substrate selection (Koziol et al., 2018), sampling methods, and temporal dynamics of eDNA (Ely et al., 2021). In the Antarctic marine environment, eDNA metabarcoding has been used to document benthic diversity and detect species such as king crabs, which are known to expand their ranges poleward and colonize the Antarctic shelf (Havermans et al., 2022). This demonstrates the potential of eDNA metabarcoding in monitoring and understanding the biodiversity of Antarctic marine ecosystems.

Here, we performed the metabarcoding to address the biodiversity of marine organisms in South Bay, Doumer Island, near the Chilean Antarctic scientific base Yelcho, using eDNA techniques, and suggested the possible non-native species in order to monitor the impact of global warming.

II.1 Area of study and sample collection

The seawater samples were collected at 50cm under the sea surface, from four sampling sites in South Bay, Doumer Island, near the Chilean Antarctic scientific Yelcho station (Fig. 1). Sampling points P2 and P3 are located within the Antarctic Specially Protected Area number 146 (ASPA 146), while sampling points P1 and P4 are located outside (Fig. 1). The depth of the sea at point P1 is approximately 25 meters. The sea depth at points P2 and P3 ranges from approximately 8 to 12 meters, whereas the depth at point P4 exceeds 70 meters (Zamorano, 1983). The ASPA 146 consists of a small area of coastal and subtidal ecosystem down to a 45 m depth. This area is part of a long-term study on marine ecology, focusing on the interactions between marine organisms in the region and is of significant interest for ongoing or planned scientific research (https://www.ats.aq/devph/en/apa-database/50).

The surface seawater samples were collected aboard a boat using a sterile bucket at each sampling point between February 20 and March 10, 2023. Ten liters of water were collected at each sampling point and stored in plastic containers. Subsequently, the samples underwent filtration utilizing a Filter System equipped with a 75 µm Filter (Filters S-Pak, pore 0,45 µm, diameter 47 mm, white color, squared surface). Prior to commencing filtration, both the filtration apparatus and the workspace were subjected to decontamination using 70% ethanol to mitigate the risk of contamination. Seawater samples were meticulously poured into the filtration unit, ensuring minimal exposure to air and preventing splashes. Following activation of the vacuum pump, the seawater underwent gentle filtration through the sterile filter membrane. Continuous monitoring of the filtration process was maintained to avert clogging; in instances of filter obstruction, a fresh filter membrane was employed to process the remaining sample volume.

Each filter membrane was retrieved from the filtration unit using sterile forceps. Subsequently, the membranes were folded inward, encapsulating the captured material, and deposited into individual sterile tubes housed within a freezer maintained at -80°C. The samples were subsequently transported to Punta Arenas, Chile, stored in liquid nitrogen containers at -70ºC. Upon arrival at the laboratories of the Instituto Antártico Chileno (INACH) in Punta Arenas, the samples were treated with proteinase-K and subsequently conveyed to the laboratories of the Korea Polar Research Institute (KOPRI) for eDNA extraction and analysis.

II.2 DNA extraction and eDNA sequencing

Each eDNA was extracted from a total of four filter samples using a Quick-DNA Microprep plus kit (Zymo Research, CA, USA) following the manufacture's protocol. Polymerase chain reaction (PCR) was performed using the primers mlCOIintF (5′-GGWACWGGWTGAACWGTWTAYCCYCC- 3′) (Leray et al., 2013) and HCO2198 (5′-TAAACTTCAGGGTGACCAAAAAATCA- 3′) (Folmer et al. 1994) to amplify the mitochondrial cytochrome c oxidase subunit I (COI) gene, which is widely used in Metazoan DNA barcoding. The PCR products were purified and used for the 2nd PCR templates to add Illumina adapters and index sequences to both ends. The quality and quantity of the libraries were checked with 4200 TapeStation system (Agilent Technologies, Santa Clara, CA, USA). All libraries were pooled in equal amounts based on their concentration. The amplicon sequencing was carrie422d out using the Illumina HiSeq platform (Illumina, San Diego, CA, USA), according to the manufacturer's instruction.

II.3 Bioinformatic analysis

The raw sequence reads were pre-processed using Trimmomatic version 0.39 (Bolger et al., 2014) with the options of LEADING:3, TRAILING:3, SLIDINGWINDOW:4:20, MINLEN:50. We used Qiime2 platform (Hall & Beiko, 2018) for the clustering analysis. DADA2 (Callahan et al., 2016) denoised the forward (--p-trunc-len-f 270) and reverse (--p-trunc-len-r 210) reads to generate amplicon sequencing variants (ASVs) less than 250 bp in length, followed by Uchime (Edgar et al., 2011) for removing chimera sequences. After ASVs generation, taxonomy assignments were conducted using BLAST+ (Altschul et al., 1990; Altschul 1997; Camacho et al., 2009) applying the following parameters: identity 80 and 97%, e-value 0.001, query coverage 80%, maxaccepts hits 1. We used the databases downloaded from National Center for Biotechnology Information (NCBI) nucleotide (released on Mar 04, 2023) (Sayers et al., 2022) and Barcode of Life Data System (BOLD) (released on Sep 15, 2023) (Ratnasingham & Hebert, 2007). The bioinformatic analysis process is presented in Fig. 2.

III.1 Summary statistics

Illumina Hiseq sequencing results in a total of 4,174,694 reads for samples and a read count of at least 146,398 to a maximum of 244,704 per library. The filtering of sequences with ambiguous bases, barcode errors, or mismatches has resulted in the removal of 21.2% of reads. The remaining sequences were used for ASV construction, a total of 10,456 ASVs were created, with a minimum length of 271 bp, a maximum length of 466 bp, and an average length of 386 bp.

III.2 Metabarcoding analysis of surface seawater samples

Taxonomic assignment analysis with BLAST identity 97% identified a total of 24 eukaryote species across the four sampling sites (Fig. 3 and Table 1). Among a total of 10,456 ASVs, only 4.5% ASVs were successfully assigned. These species represented thirteen phyla: Annelida, Arthropoda, Rhodophyta, Bacillariophyta, Chlorophyta, Mollusca, Phaeophyceae, Ascomycota, Cnidaria, Dinophyceae, Filasterea, Haptophyta and Rotifera. Rhodophyta had the highest number of species observed (6 species), followed by Bacillariophyta (3 species), Arthropoda (2 species), Chlorophyta (2 species), Mollusca (2 species), and Phaeophyceae (2 species). Due to the limited number of species assignments of 97% identity, we conducted additional taxonomy assignments with a lower BLAST identity threshold of 80% to assess the overall taxonomic composition of the samples (Supplementary Figs. 1 and 2). At these criteria, the phyla with the highest number of families observed were Arthropoda (46 Families), followed by Cnidaria (17 Families), Bacillariophyta (10 Families), Porifera (10 Families), Pseudomonadota (10 Families), Rhodophyta (10 Families), and Mollusca (10 Families).

Table 1

Taxonomically assigned 24 eukaryotic species in in South Bay, Doumer Island in Antarctica
		Point 1	Point 2	Point 3	Point 4
Phylum	Species Name	Outside ASPA 146	Inside ASPA / ASPA 146	Inside ASPA / ASPA 146	Isolate in South Bay
Annelida	Barrukia cristata	-	-	-	+
Arthropoda	Cryptopygus antarcticus	-	-	-	+
Arthropoda	Oithonidae unknown	-	-	-	-
Ascomycota	Penicillium rubens	+	+	-	+
Bacillariophyta	Navicula glaciei	-	-	-	+
Bacillariophyta	Grammonema striatula	-	-	-	+
Bacillariophyta	Fragilariopsis cylindrus	-	+	-	-
Chlorophyta	Bathycoccus prasinos	+	+	+	-
Chlorophyta	Micromonas pusilla	+	+	+	-
Cnidaria	Obelia dichotoma	-	-	-	+
Haptophyta	Phaeocystis antarctica	+	-	-	-
Mollusca	Mysella subquadrata	-	-	-	+
Mollusca	Aequiyoldia eightsii	-	-	-	+
Rhodophyta	Palmaria decipiens	+	-	+	+
Rhodophyta	Bangia fuscopurpurea	-	-	-	+
Rhodophyta	Iridaea cordata	+	-	-	+
Rhodophyta	Curdiea racovitzae	+	-	-	+
Rhodophyta	Gymnogongrus turquetii	-	-	-	+
Rhodophyta	Sarcopeltis antarctica	+	-	-	+
Rotifera	Macrotrachela jankoi	-	-	-	+
Gyrista	Desmarestia menziesii	+	-	+	+
Choanozoa	Ministeria vibrans	-	-	-	+
Myzozoa	Thoracosphaera heimii	-	-	-	+
Gyrista	Desmarestia antarctica	+	-	-	-
Total number of taxa		10	4	4	18

The Rhodophyta, including red algae, accounted for 25% of this metabarcoding analysis, highlighting their significant presence in the Antarctic coastal region and dominance among macroalgae in benthic communities in South Bay, Doumer Island (Fig. 3). During the austral summer from November to February, these algae experience optimal growth and reproduction conditions, including gamete release and spore production, due to increased light availability and slightly higher temperatures. We assume that their free-living spores and gametes can disperse and exist independently in the water column, thereby enhancing their detection in metabarcoding analysis.

In total, 14 previously undocumented Antarctic species in South Bay, Doumer Island were newly identified (Table 2). The phyla with highest number of species were Rhodophyta (4 species), followed by Bacillariophyta (3 species). A relatively large number of species were found at sampling station P4. Regarding the findings of taxonomically assigned eukaryotic species in South Bay (Table 1), it is noteworthy that sampling station P4, characterized by the greatest sea depth, exhibited the highest number of recorded species. In contrast, stations P2 and P3, associated with shallower depths, contained the fewest species. Station P1, with an intermediate sea depth of approximately 25m, displayed a moderate number of species, consistent with its intermediate depth profile.

Table 2

Newly reported Antarctic species in South Bay, Doumer Island in Antarctica
			Point 1	Point 2	Point 3	Point 4
Phylum	Species Name	Previously known Distribution	Outside ASPA 146	Inside ASPA / ASPA 146	Inside ASPA / ASPA 146	Isolate in South Bay
Bacillariophyta	Fragilariopsis cylindrus	Antarctic	-	+	-	-
Bacillariophyta	Pseudo-nitzschia subcurvata	Southern Ocean	+	-	-	-
Bacillariophyta	Navicula glaciei	Antarctic	-	-	-	+
Gyrista	Desmarestia antarctica	Antarctic	+	-	-	-
Gyrista	Desmarestia menziesii	Antarctic	+	-	+	+
Haptophyta	Phaeocystis antarctica	Antarctic	+	-	-	-
Rhodophyta	Bangia fuscopurpurea	Antarctic, Cosmopolitan	-	-	-	+
Rhodophyta	Sarcopeltis antarctica	Antarctic	+	+	-	+
Rhodophyta	Gymnogongrus turquetii	Antarctic, Sub-Antarctic, S. America	-	-	-	+
Rhodophyta	Curdiea racovitzae	Antarctic, Sub-Antarctic, S. America	+	+	-	+
Annelida	Barrukia cristata	Antarctic	-	-	-	+
Arthropoda	Cryptopygus antarcticus	Antarctic	-	-	-	+
Mollusca	Mysella subquadrata	Antarctic	-	-	-	+
Mollusca	Aequiyoldia eightsii	Antarctic	-	-	-	+
Rotifera	Macrotrachela jankoi	Antarctic	-	-	-	+
Total number of taxa			6	3	1	11

III.3 Identification of unrecorded species and possible non-native species

Doumer Island, designated as an Antarctic Specially Protected Area (ASPA), experiences relatively limited human activity due to ongoing environmental conservation efforts. This region is characterized by rich benthic fauna, especially in the coastal zone up to 45 meters deep, and possesses significant biodiversity. Monitoring the biodiversity and presence of non-native species in this area is crucial.

Based on the available but limited database around this area, we identified a total of five species that have not been previously reported in Antarctica (Table 3). These include two species of Chlorophyta (Bathycoccus prasinos and Micromonas pusilla), one Choanozoa (Ministeria vibrans), one Moizoa (Thoracosphaera heimii), and one Cnidaria (Obelia dichotoma).

Table 3

Newly reported potential non-native species in South Bay, Doumer Island in Antarctica
			Point 1	Point 2	Point 3	Point 4
Phylum	Species Name	Previously known Distribution	Outside ASPA 146	Inside ASPA / ASPA 146	Inside ASPA / ASPA 146	Islate in South Bay
Bacillariophyta	Grammonema striatula	Europe	-	-	-	+
Chlorophyta	Bathycoccus prasinos	Europe, N. America, Asia	+	+	+	-
Chlorophyta	Micromonas pusilla	Europe, N. America, S. America, Australia and NZ	+	+	+	-
Choanozoa	Ministeria vibrans	North Atlantic	-	-	-	+
Cnidaria	Obelia dichotoma	Europe, N. America, S. America, S. Africa, Australia and NZ	-	-	-	+
Myzozoa	Thoracosphaera heimii	Europe, N. America, S. America, S. Africa, Australia and NZ	-	-	-	+
Total number of taxa			2	2	2	4

Within Chlorophyta, both species belong to the order Mamiellales. Micromonas pusilla has been found in significantly lower temperatures, such as the Arctic, whereas Bathycoccus prasinos is prevalent in most oceans. Previous metagenomic analyses have detected only Micromonas in Antarctic waters, suggesting connectivity between polar populations through deep-sea currents. Bathycoccus prasinos has not been reported in Antarctic waters (Simmons et al., 2015).

The heterotrophic flagellate Ministeria vibrans is broadly found in marine environments, but specific findings in the southern hemisphere, including Antarctica, have not been reported.

The dinoflagellate Thoracosphaera heimii is primarily found in the upper waters of the equatorial and tropical Atlantic Ocean. Its calcareous cysts are important for paleoenvironmental studies as they are deposited in sediment records. This species has also not been documented in Antarctic waters.

The most intriguing finding is the detection of Obelia dichotoma. Typically inhabiting shallow coastal waters, attachingd to substrates such as rocks, shells, and algae, this hydrozoan species is known to be absent from Arctic and Antarctic waters. Given its tendency to form extensive colonies on submerged surfaces, we hypothesize that the detection of O. dichotoma may result from biofouling on the ship as it traveled in and out of the sea (Coutts & Taylor, 2005, Ferreira et al., 2006, Lee & Chown 2009). Nevertheless, we cannot entirely discount the possibility of this species naturally occurring in the area due to the significant numbers of reads observed.

The structure of benthic communities in Antarctic waters is significantly impacted by the presence of ice. Studies have shown that factors such as sea ice, ocean circulation, and advected primary production from coastal polynyas play a crucial role in shaping the composition and productivity of benthic communities in Antarctic waters (Norkko et al., 2007). Ice-related disturbances, like anchor ice and ice scouring events, contribute to the zonation and variability observed in shallow-water benthic communities (Denny et al., 2011; Pasotti et al., 2014). Additionally, the dependence of seafloor communities on lateral advection of food particles highlights the influence of ice on nourishing benthic organisms in Antarctic regions (Thatje et al., 2008).

The interplay between sea ice dynamics and the food web structure of Antarctic benthic communities in medium-deep waters highlights the importance of understanding how ice influences basal resource inputs and community dynamics (Rossi et al., 2019). Ice scour has been identified as a key regulator of seaweed vertical zonation and abundance in Antarctic shallow waters (Deregibus et al., 2017). Additionally, Ice scour is a significant determinant of the structure of benthic megafauna communities in Antarctica, leading to increased mortality and reduced biomass (Khim, 2024).

In this context, the reason the higher biodiversity observed at sampling point P4 might be related to the deeper depth of the seabed in this area, potentially fostering more diverse benthic communities at the mouth of South Bay. On the other hand, points P1, P2, and P3 being shallower, are likely more susceptible to disturbances caused by ice, such as the anchor effect of icebergs on the seabed. The abrasive effect produced by the annual ice formation and drifting ice is responsible for the scarcity of macrobenthic organisms in the intertidal and upper sublittoral zones, restricting their existence to protected habitats such as crevices and fissures (Zamorano 1983).

Research using metabarcoding techniques to assess biodiversity in the Antarctic Ocean has been growing in recent years. Numerous studies have applied DNA metabarcoding to analyze various aspects of Antarctic marine ecosystems. For example, studies have examined benthic communities, meiofauna, and plankton biodiversity in different regions of the Southern Ocean eDNA surveys, in conjunction with existing monitoring methods, have the potential to establish or enhance the assessment of biodiversity in the ASPA.

However, it is important to consider potential limitations and challenges associated with eDNA analysis in marine water. For instance, there have been cases where non-resident freshwater species have been detected in marine eDNA studies, highlighting the need to account for potential sources of error and systematic bias (Collins et al., 2018). Moreover, the persistence of marine organism eDNA and the influence of sunlight have been studied using mesocosm experiments, emphasizing the importance of understanding the factors that may affect eDNA persistence in marine waters (Andruszkiewicz et al., 2017).

In this pilot study, seawater samples were collected from South Bay, Doumer Island in Antarctica to evaluate the potential efficiency of eDNA surveys in assessing biodiversity and detecting the presence of non-native species. Taxonomic assignment analysis identified only 23 eukaryote species. The reason for the small number of identified species is generally due to the lack or absence of reference sequences in library and/or the insufficient polymorphisms in the marker regions that that not distinguish between species in the genus. In this study, we found that only 59 COI sequences were NCBI and BOLD database registered out of the South Bay, Doumer Island 117 endemic species list. This highlights the importance of generating and curating new reference barcode sequences to enable more comprehensive identification of biodiversity assessment and non-native species detection in Antarctica.

The study area, ASPA 146 and Point 4, presents a prevalence of macroalgae, including the newly reported five additional macroalgae species. Previous studies (Rovelli et al, 2019, Morales et al, 2024) focused only on benthic assemblages, while this study, conducted at a relatively shallow depth of 45 meters, is the first to observe the pelagic community. Consequently, it appears that the newly observed macroalgae species were not reported in earlier studies. Rhodophyta, the most prevalence macroalgae, are a notable component of the Antarctic shallow water ecosystems. They are particularly abundant in the benthic communities of the Antarctic Peninsula and play a crucial role in the overall ecological dynamics of the shallow waters, with various species adapting to the unique environmental conditions of the Antarctic coastal zones.

The detection of marine species in Antarctic bioinvasion using environmental DNA (eDNA) presents both challenges and opportunities. Here, we report five non-Antarctic species. Among them, Hydra Obelia dichotoma, a cosmopolite marine adhesive specie, is a cause for concern in Antarctica due to its potential to disrupt the local ecosystem through competition with native species. These results highlight the need to obtain results from continuous eDNA monitoring, for the detection of invasive species and the creation of early warning about invasive species.

The application of eDNA approaches to marine systems has emerged as a promising tool for both single species detection and biodiversity monitoring (Suárez-Bregua et al., 2022). The fate and transport of eDNA in Antarctic benthic environments pose unique challenges, and the detection of eDNA in marine environments may not always align with the presence of the target species (Clarke et al., 2021; Takahashi et al., 2020). Nevertheless, eDNA can distinguish fish assemblages inside and outside marine protected areas and detect other vertebrates, such as marine mammals and birds, of special conservation concern (Gold et al., 2020). The use of eDNA for alien ant monitoring has also shown effectiveness in detecting invasive ant species, suggesting its potential for improving the ability to detect invasive species (Yasashimoto et al., 2021).

The limitations of eDNA detection, including incomplete detection and the complexities of abiotic and biotic factors influencing eDNA detection, raise questions regarding appropriate eDNA sampling strategies for monitoring programs focused on rare species and understanding the spatial distribution of eDNA (Moyer et al., 2014; Harper et al., 2018). Furthermore, the use of different molecular methods, such as end-point PCR, qPCR/ddPCR, viability PCR, metabarcoding, and shotgun sequencing, can provide biodiversity information that can be used for various marine environmental research purposes, including biosecurity applications and general biodiversity assessment (Zaiko et al., 2018).

Additionally, the spatial and temporal distribution of eDNA in Antarctic ecosystems, as well as the influence of abiotic and biotic factors on eDNA detection such as substrate characteristics, environmental parameters, organismal behavior, should be carefully considered to ensure the effectiveness of eDNA surveillance for detecting bioinvasions in the Antarctic (Clarke et al., 2021; Smart et al., 2015; Harper et al., 2018). The incorporation of these considerations into eDNA surveillance and monitoring initiatives has the potential to augment the identification of invasive species and thereby contribute significantly to the conservation of Antarctic biodiversity.

The presence of ice significantly shapes the structure, composition, and productivity of benthic communities in Antarctic shallow waters. Ice-related disturbances, ice scouring events, and the dependence of seafloor communities on ice-influenced factors contribute to the intricate relationship between ice and Antarctic benthic ecosystems. This fact might also be reflected in the species abundance detected by the eDNA metabarcoding monitoring method used in this study. However, further studies of this type are needed to test this hypothesis.

Marine heatwaves are increasingly significant due to global warming, leading to longer and more frequent occurrences of these extreme climatic events (Oliver et al., 2018). The West Antarctic Peninsula (WAP), known for its high productivity, has been experiencing notable changes such as glacier retreat, reduction of sea-ice cover, and shifts in marine populations, which can be exacerbated by marine heatwaves (Moffat & Meredith, 2018).

The interaction between marine heat waves and invasive species can have profound effects on marine communities. As marine heat waves alter the abundance and structure of microbial populations associated with marine organisms like oysters, mass mortality events can occur, impacting the overall ecosystem health (Green et al., 2018). Furthermore, the ability of invasive species to outperform native species in heat wave scenarios has been demonstrated in laboratory studies, highlighting the potential for invasive species to thrive under changing environmental conditions (Crespo et al., 2021).

Funding declaration

This work was supported by Agencia Nacional de Investigación y Desarrollo (Grant/Award Number: FOVI220036) and the Korea Polar Research Institute (Grant Number: PE23140).

Competing Interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Authors’ contribution

CXS conceptualized and designed the study, collected the study samples, interpreted the data and wrote the manuscript; SK designed the study, analyzed and interpreted the data and wrote the manuscript, SL conceptualized the research and reviewed the manuscript, YWK reviewed the manuscript, EJ analyzed the data, SK conceptualized the research, designed the study and wrote and reviewed the manuscript.

Altschul, S.F., et al., Basic local alignment search tool. Journal of molecular biology, 1990. 215(3): p. 403-410.
Altschul, S.F., et al., Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic acids research, 1997. 25(17): p. 3389-3402.
Andruszkiewicz, E., Sassoubre, L., & Boehm, A. (2017). Persistence of marine fish environmental DNA and the influence of sunlight. Plos One, 12(9), e0185043. https://doi.org/10.1371/journal.pone.0185043
Bakker, J., Wangensteen, O., Chapman, D., Boussarie, G., Buddo, D., Guttridge, T., … & Mariani, S. (2017). Environmental DNA reveals tropical shark diversity in contrasting levels of anthropogenic impact. Scientific Reports, 7(1). https://doi.org/10.1038/s41598-017-17150-2
Bolger, A.M., M. Lohse, and B. Usadel, Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics, 2014: p. btu170.
Bolyen, E., et al., Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature biotechnology, 2019. 37(8): p. 852-857.
Bylemans, J., Gleeson, D., Duncan, R., Hardy, C., & Furlan, E. (2019). A performance evaluation of targeted eDNA and eDNA metabarcoding analyses for freshwater fishes. Environmental Dna, 1(4), 402-414. https://doi.org/10.1002/edn3.41
Callahan, B.J., et al., DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods, 2016. 13(7): p. 581-583.
Camacho, C., et al., BLAST+: architecture and applications. BMC bioinformatics, 2009. 10(1): p. 1-9.
Clarke, L., Suter, L., Deagle, B., Polanowski, A., Terauds, A., Johnstone, G., … & Stark, J. (2021). Environmental DNA metabarcoding for monitoring metazoan biodiversity in antarctic nearshore ecosystems. Peerj, 9, e12458. https://doi.org/10.7717/peerj.12458
Cárdenas, C., González-Aravena, M., & Santibañez, P. (2018). The importance of local settings: within-year variability in seawater temperature at South Bay, Western Antarctic Peninsula. PeerJ. 6, e4289.
Cárdenas, L., Leclerc, J., Bruning, P., Garrido, I., Détrée, C., Figueroa, A., & Pardo, L. (2020). First mussel settlement observed in Antarctica reveals the potential for future invasions. Sci Rep. 10(1), 5552.
Collins, R., Wangensteen, O., O’Gorman, E., Mariani, S., Sims, D., & Genner, M. (2018). Persistence of environmental DNA in marine systems. Communications Biology, 1(1). https://doi.org/10.1038/s42003-018-0192-6
Coutts, A. D., & Taylor, M. D. (2005). Biofouling on merchant vessels in New Zealand. Hull fouling as a mechanism for marine invasive species introductions. Bishop Mus. Tech. Rep, 28, 14-21.
Crespo, D., Leston, S., Rato, L. D., Martinho, F., Novais, S. C., Pardal, M. Â., … & Lemos, M. F. (2021). Does an invasive bivalve outperform its native congener in a heat wave scenario? a laboratory study case with ruditapes decussatus and r. philippinarum. Biology, 10(12), 1284. https://doi.org/10.3390/biology10121284
Denny, M., Dorgan, K., Evangelista, D., Hettinger, A., Leichter, J., Ruder, W., … & Tuval, I. (2011). Anchor ice and benthic disturbance in shallow antarctic waters: interspecific variation in initiation and propagation of ice crystals. Biological Bulletin, 221(2), 155-163. https://doi.org/10.1086/bblv221n2p155
Deregibus, D., Quartino, M., Zacher, K., Campana, G., & Barnes, D. (2017). Understanding the link between sea ice, ice scour and antarctic benthic biodiversity–the need for cross-station and international collaboration. Polar Record, 53(2), 143-152. https://doi.org/10.1017/s0032247416000875
Edgar, R.C., et al., UCHIME improves sensitivity and speed of chimera detection. Bioinformatics, 2011. 27(16): p. 2194-2200.
Ely, T., Barber, P., Man, L., & Gold, Z. (2021). Short-lived detection of an introduced vertebrate eDNA signal in a nearshore rocky reef environment. Plos One, 16(6), e0245314. https://doi.org/10.1371/journal.pone.0245314
Feng, Y., Sun, D., Shao, Q., Chen, F., & Wang, C. (2022). Mesozooplankton biodiversity, vertical assemblages, and diel migration in the western tropical pacific ocean revealed by eDNA metabarcoding and morphological methods. Frontiers in Marine Science, 9. https://doi.org/10.3389/fmars.2022.1004410
Ferreira, C. E. L., Gonçalves, J. E. A., & Coutinho, R. (2006). Ship hulls and oil platforms as potential vectors to marine species introduction. Journal of Coastal Research, SI39, 1340-1345.
Fujii, K., Doi, H., Matsuoka, S., Nagano, M., Sato, H., & Yamanaka, H. (2019). Environmental DNA metabarcoding for fish community analysis in backwater lakes: a comparison of capture methods. Plos One, 14(1), e0210357. https://doi.org/10.1371/journal.pone.0210357
Gold, Z., Sprague, J., Kushner, D., Zerecero, E., & Barber, P. (2020). eDNA metabarcoding as a biomonitoring tool for marine protected areas.. https://doi.org/10.1101/2020.08.20.258889
Green, T. J., Siboni, N., King, W. L., Labbate, M., Seymour, J. R., & Raftos, D. A. (2018). Simulated marine heat wave alters abundance and structure of vibrio populations associated with the pacific oyster resulting in a mass mortality event. Microbial Ecology, 77(3), 736-747. https://doi.org/10.1007/s00248-018-1242-9
Harper, L., Griffiths, N., Handley, L., Sayer, C., Read, D., Harper, K., … & Hänfling, B. (2018). Development and application of environmental DNA surveillance for the threatened crucian carp (Carassius carassius). Freshwater Biology, 64(1), 93-107. https://doi.org/10.1111/fwb.13197
Havermans, C., Dischereit, A., Pantiukhin, D., Friedrich, M., & Murray, A. (2022). Environmental DNA in an ocean of change: status, challenges and prospects. Arquivos De Ciências Do Mar, 55(Especial), 298-337. https://doi.org/10.32360/acmar.v55iespecial.78188
Khim, J. (2024). Shifts in benthic megafauna communities after glacial retreat in an antarctic fjord.. https://doi.org/10.21203/rs.3.rs-4317484/v1
Koziol, A, M., Stat, M., Simpson, T., Jarman, S., DiBattista, J., Harvey, E., … & McDonald, J. (2018). Environmental DNA metabarcoding studies are critically affected by substrate selection. Molecular Ecology Resources, 19(2), 366-376. https://doi.org/10.1111/1755-0998.12971
Lee, J. E., & Chown, S. L. (2009). Temporal development of hull-fouling assemblages associated with an Antarctic supply vessel. Marine Ecology Progress Series, 386, 97-105.
Leconte, J., Timsit, Y., Delmont, T. O., Lescot, M., Piganeau, G., Wincker, P., & Jaillon, O. (2021). Equatorial to Polar genomic variability of the microalgae Bathycoccus prasinos. bioRxiv, 2021-07.
Leray, M., et al., A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: application for characterizing coral reef fish gut contents. Frontiers in Zoology, 2013. 10(1): p. 34.
Leihy, R.., Peake, L., Clarke, D., Chown, S., & McGeoch, M. (2023). Introduced and invasive alien species of Antarctica and the Southern Ocean Island. Scientific Data,
McCarthy, A. H., Peck, L. S., Hughes, K. A., & Aldridge, D. C. (2018). Antarctica: The final frontier for marine biological invasions. Glob Chang Biol. 25(7), 2221-2241.
McClenaghan, B., Côté, D., Chawarski, J., McCarthy, A., Rajabi, H., Singer, G., … & Hajibabaei, M. (2020). Harnessing the power of eDNA metabarcoding for the detection of deep-sea fishes. Plos One, 15(11), e0236540. https://doi.org/10.1371/journal.pone.0236540
Moffat, C. and Meredith, M. P. (2018). Shelf–ocean exchange and hydrography west of the antarctic peninsula: a review. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 376(2122), 20170164. https://doi.org/10.1098/rsta.2017.0164
Monuki, K., Barber, P., & Gold, Z. (2021). eDNA captures depth partitioning in a kelp forest ecosystem. Plos One, 16(11), e0253104. https://doi.org/10.1371/journal.pone.0253104
Moyer, G., Díaz-Ferguson, E., Hill, J., & Shea, C. (2014). Assessing environmental DNA detection in controlled lentic systems. Plos One, 9(7), e103767. https://doi.org/10.1371/journal.pone.0103767
Morales, S., Cárdenas, C. A., Bravo-Gómez, D., Lagger, C. (2024). Shallow hard-bottom benthic assemblages of Soth Bay (Antarctic Peninsula): An update 40 years later. Diversity, 16, 162.
Norkko, A., Thrush, S., Cummings, V., Gibbs, M., Andrew, N., Norkko, J., … & Schwarz, A. (2007). Trophic structure of coastal antarctic food webs associated with changes in sea ice and food supply. Ecology, 88(11), 2810-2820. https://doi.org/10.1890/06-1396.1
Oliver, E. C. J., Donat, M. G., Burrows, M. T., Moore, P. J., Smale, D. A., Alexander, L. V., … & Wernberg, T. (2018). Longer and more frequent marine heatwaves over the past century. Nature Communications, 9(1). https://doi.org/10.1038/s41467-018-03732-9
Pasotti, F., Manini, E., Giovannelli, D., Wölfl, A., Monien, D., Verleyen, E., … & Vanreusel, A. (2014). Antarctic shallow water benthos in an area of recent rapid glacier retreat. Marine Ecology, 36(3), 716-733. https://doi.org/10.1111/maec.12179
Pörtner, H.O., Roberts, D.C., Adams, H., Adler, C., Aldunce, P., Ali, E., … & Biesbroek, R. (2022). Climate Change 2022: Impacts, Adaptation and Vulnerability. IPCC:Geneva, Switzerland.
Ratnasingham, S. and P.D. Hebert, BOLD: The Barcode of Life Data System (http://www. barcodinglife. org). Molecular ecology notes, 2007. 7(3): p. 355-364.
Rossi, L., Caputi, S., Calizza, E., Careddu, G., Oliverio, M., Schiaparelli, S., … & Costantini, M. (2019). Antarctic food web architecture under varying dynamics of sea ice cover. Scientific Reports, 9(1). https://doi.org/10.1038/s41598-019-48245-7
Rovelli, L., Attard, K. M., Cárdenas, C. A., & Glud, R. N. (2019). Benthic primary production and respiration of shallow rocky habitats: a case study from South Bay (Doumer Island, Western Antarctic Peninsula). Polar Biol. 42(8), 1459-1474.
Sahade, R., Lagger, C., Torre, L., Momo, F., Monien, P., & Abele, D. (2015). Climate change and glacier retreat drive shifts in an Antarctic benthic ecosystem. Sci Adv. 1(10), e1500050.
Sahu, A., Kumar, N., Singh, C. P., & Singh, M. (2023). Environmental DNA (eDNA): Powerful technique for biodiversity conservation. Journal for Nature Conservation, 71, 126325. https://doi.org/10.1016/j.jnc.2022.126325
Sayers, E.W., et al., Database resources of the national center for biotechnology information. Nucleic Acids Res, 2022. 50(D1): p. D20-d26.
Simmons, M. P., Bachy, C., Sudek, S., Van Baren, M. J., Sudek, L., Ares Jr, M., & Worden, A. Z. (2015). Intron invasions trace algal speciation and reveal nearly identical Arctic and Antarctic Micromonas populations. Molecular biology and evolution, 32(9), 2219-2235.
Smart, A., Tingley, R., Weeks, A., Rooyen, A., & McCarthy, M. (2015). Environmental DNA sampling is more sensitive than a traditional survey technique for detecting an aquatic invader. Ecological Applications, 25(7), 1944-1952. https://doi.org/10.1890/14-1751.1
Stat, M., Huggett, M., Bernasconi, R., DiBattista, J., Berry, T., Newman, S., … & Bunce, M. (2017). Ecosystem biomonitoring with eDNA: metabarcoding across the tree of life in a tropical marine environment. Scientific Reports, 7(1). https://doi.org/10.1038/s41598-017-12501-5
Steig, E. J., Schneider, D. P., Rutherford, S. D., Mann, M. E., Comiso, J. C., & Shindell, D. T. (2009). Warming of the Antarctic ice-sheet surface since the 1957 international geophysical year. Nature. 157(7228), 459-462.
Suárez-Bregua, P., Álvarez-González, M., Parsons, K., Rotllant, J., Pierce, G., & Saavedra, C. (2022). Environmental DNA (eDNA) for monitoring marine mammals: challenges and opportunities. Frontiers in Marine Science, 9. https://doi.org/10.3389/fmars.2022.987774
Suter, L., Polanowski, A., Clarke, L., Kitchener, J., & Deagle, B. (2020). Capturing open ocean biodiversity: comparing environmental DNA metabarcoding to the continuous plankton recorder. Molecular Ecology, 30(13), 3140-3157. https://doi.org/10.1111/mec.15587
Takahashi, S., Takada, S., Yamanaka, H., Masuda, R., & Kasai, A. (2021). Intraspecific genetic variability and diurnal activity affect environmental DNA detection in japanese eel. Plos One, 16(9), e0255576. https://doi.org/10.1371/journal.pone.0255576
Thatje, S., Hillenbrand, C., Mackensen, A., & Larter, R. (2008). Life hung by a thread: endurance of antarctic fauna in glacial periods. Ecology, 89(3), 682-692. https://doi.org/10.1890/07-0498.1
Thomsen, P., Kielgast, J., Iversen, L., Møller, P., Rasmussen, M., & Willerslev, E. (2012). Detection of a diverse marine fish fauna using environmental DNA from seawater samples. Plos One, 7(8), e41732. https://doi.org/10.1371/journal.pone.0041732
Turner, J., Lu, H., King J., Marshall, G., Phillips, T., … & Colwell, S. (2021). Extreme temperatures in the Antarctic. J Clim, 36, 2653-2668.
Valentini, A., Taberlet, P., Miaud, C., Civade, R., Herder, J., Thomsen, P., … & Déjean, T. (2015). Next‐generation monitoring of aquatic biodiversity using environmental DNA metabarcoding. Molecular Ecology, 25(4), 929-942. https://doi.org/10.1111/mec.13428
Villegas, N., Málikov, I., & Cárdenas, C. (2018). An initial aproximation to the meteo-marine conditions of South Bay (Doumer island) and comparison of the meteorological behavior between Doumer and Anvers island, Antarctica (austral summer 2016-2017). Anales Institituto Patagonia. 46(1), 23-32.
Wei, N., Nakajima, F., & Tobino, T. (2019). Variation of environmental DNA in sediment at different temporal scales in nearshore area of Tokyo bay. Journal of Water and Environment Technology, 17(3), 153-162. https://doi.org/10.2965/jwet.18-047
West, K., Stat, M., Harvey, E., Skepper, C., DiBattista, J., Richards, Z., … & Bunce, M. (2020). eDNA metabarcoding survey reveals fine‐scale coral reef community variation across a remote, tropical island ecosystem. Molecular Ecology, 29(6), 1069-1086. https://doi.org/10.1111/mec.15382
Yasashimoto, T., Sakata, M., Sakita, T., Nakajima, S., Ozaki, M., & Minamoto, T. (2021). Environmental DNA detection of an invasive ant species (Linepithema humile) from soil samples. Scientific Reports, 11(1). https://doi.org/10.1038/s41598-021-89993-9
Zamorano, J. H. (1983). Zonación y biomasa de la macrofauna bentónica en Bahía South, Archipiélago de Palmer, Antártica. INACH Serie Científica, 30, 27-38.

SupplementaryMaterial.docx

Download PDF

Version 1

posted

You are reading this latest preprint version

Unravelling Antarctic Coastal Waters: Exploring Marine Biodiversity and Detecting Potential Invasive Species via eDNA Metabarcoding in South Bay, Doumer Island

Status:

Version 1

Abstract

Figures

I. Introduction

II. Materials and Method

II.1 Area of study and sample collection

II.2 DNA extraction and eDNA sequencing

II.3 Bioinformatic analysis

III. Results

III.1 Summary statistics

III.2 Metabarcoding analysis of surface seawater samples

III.3 Identification of unrecorded species and possible non-native species

IV. Discussion and conclusions

Declarations

References

Supplementary Files

Status:

Version 1