Application of eDNA metabarcoding for high-resolution reconstruction of the trophic web of an Arctic fjord

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eDNA metabarcoding of Arctic fjord samples revealed distinct coastal and offshore trophic webs, differing in species richness, links, connectance, and generality, offering a sensitive method for ecosystem monitoring.

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The study applied eDNA metabarcoding in Kongsfjorden (an Arctic fjord) to reconstruct trophic webs by sampling environmental DNA with metaprobe passive samplers under two configurations: alongside set fish traps in the coastal area and via a towed transect in the offshore domain. The researchers amplified mitochondrial COI (for metazoans) and ribosomal 18S (for protists), then used metabarcoding output taxa as nodes and inferred prey–predator and producer–consumer links through literature review, summarizing food-web structure with indicators including species richness, number of links, direct connectance, and generality. They found distinct web structures, especially at the apical part of the networks, with a clear separation between coastal and offshore domains, and reported that eDNA was sensitive to these differences. The paper does not provide explicit limitations in the abstract beyond framing the approach as cost-effective and rapid compared with traditional sampling. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

ABSTRACT In the face of a rapidly changing Arctic, the ecosystem of Kongsfjorden was put under the spotlight to explore its community composition and structural dynamics. An eDNA metabarcoding approach was implemented to carry out a Food Web Analysis. eDNA samples were collected using metaprobes, innovative passive samplers, deployed under two different sampling configurations: in association with set fish traps in the coastal area and a towed sampling along a central transect, an offshore domain of the fjord. Amplification of the mithocondrial COI and ribosomal 18S genes was conducted in order to obtain a comprehensive view of metazoans and protists communities, respectively. The output taxa from the metabarcoding process constituted trophic webs’ nodes while producers-consumers and prey-predator’s relationships were identified through a literature review. Qualitative food networks were successfully obtained for each sampled site and for the two domains identified in the ecosystem, the coastal and offshore areas. Moreover, these networks were characterized by using four food web indicators: Species Richness (N), Number of links (L), Direct Connectance (C) and Generality (G). Differences in the apical part of the webs instantly emerged, as well as a clear separation between the coastal and offshore domain. Analyzing the values of the trophic indicators allowed for a deeper consideration regarding the nets’ structure and relative stability. Overall, eDNA proved sensitive and precise in capturing differences between the two domains and in providing insights into ecosystem structure. Moreover, eDNA-based Food Web Analysis could set the basis for long term monitoring studies in the same area, being cost-effective, rapid and easy to implement when compared to traditional methods.
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ABSTRACT In the face of a rapidly changing Arctic, the ecosystem of Kongsfjorden was put under the spotlight to explore its community composition and structural dynamics. An eDNA metabarcoding approach was implemented to carry out a Food Web Analysis. eDNA samples were collected using metaprobes, innovative passive samplers, deployed under two different sampling configurations: in association with set fish traps in the coastal area and a towed sampling along a central transect, an offshore domain of the fjord. Amplification of the mithocondrial COI and ribosomal 18S genes was conducted in order to obtain a comprehensive view of metazoans and protists communities, respectively. The output taxa from the metabarcoding process constituted trophic webs’ nodes while producers-consumers and prey-predator’s relationships were identified through a literature review. Qualitative food networks were successfully obtained for each sampled site and for the two domains identified in the ecosystem, the coastal and offshore areas. Moreover, these networks were characterized by using four food web indicators: Species Richness (N), Number of links (L), Direct Connectance (C) and Generality (G). Differences in the apical part of the webs instantly emerged, as well as a clear separation between the coastal and offshore domain. Analyzing the values of the trophic indicators allowed for a deeper consideration regarding the nets’ structure and relative stability. Overall, eDNA proved sensitive and precise in capturing differences between the two domains and in providing insights into ecosystem structure. Moreover, eDNA-based Food Web Analysis could set the basis for long term monitoring studies in the same area, being cost-effective, rapid and easy to implement when compared to traditional methods. Competing Interest Statement The authors have declared no competing interest.

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