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Read counts from environmental DNA (eDNA) metabarcoding reflect fish abundance and biomass in drained ponds
Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2020.07.29.226845v1?rss=1
Authors: Di Muri, C., Lawson Handley, L. J., Bean, C. W., Li, J., Peirson, G., Sellers, G. S., Walsh, K., Watson, H. V., Winfield, I. J., Hänfling, B.
Abstract:
The sampling of environmental DNA (eDNA) coupled with cost-efficient and ever-advancing sequencing technology is propelling changes in biodiversity monitoring within aquatic ecosystems. Despite the growth of DNA metabarcoding approaches, the ability to quantify species biomass and abundance in natural systems remains a major challenge. Few studies have examined the association between eDNA metabarcoding data and biomass inferred by whole-organism sampling, mesocosms or mock communities, and the interpretation of sequencing reads as a measure of biomass or number of organisms is largely disputed. Here we tested whether read counts from eDNA metabarcoding provide accurate quantitative estimates of fish abundance in holding ponds with known fish biomass and number of individuals. eDNA samples were collected from two fishery ponds with high fish density and broad species diversity. In one pond, two different DNA capture strategies (on-site filtration with enclosed filters and three different preservation buffers versus lab filtration using open filters) were used to evaluate their performance in relation to fish community composition and biomass/abundance estimates. Fish species read counts were significantly correlated with both biomass and abundance, and this result, together with information on fish diversity, was repeatable when open or enclosed filters with different preservation buffers were used. This research demonstrates that eDNA metabarcoding provides accurate qualitative and quantitative information on fish communities in small ponds, and results are consistent between different methods of DNA capture. This method flexibility will be beneficial for future eDNA-based fish monitoring and their integration into fisheries management.
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Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2020.07.29.226845v1?rss=1
Authors: Di Muri, C., Lawson Handley, L. J., Bean, C. W., Li, J., Peirson, G., Sellers, G. S., Walsh, K., Watson, H. V., Winfield, I. J., Hänfling, B.
Abstract:
The sampling of environmental DNA (eDNA) coupled with cost-efficient and ever-advancing sequencing technology is propelling changes in biodiversity monitoring within aquatic ecosystems. Despite the growth of DNA metabarcoding approaches, the ability to quantify species biomass and abundance in natural systems remains a major challenge. Few studies have examined the association between eDNA metabarcoding data and biomass inferred by whole-organism sampling, mesocosms or mock communities, and the interpretation of sequencing reads as a measure of biomass or number of organisms is largely disputed. Here we tested whether read counts from eDNA metabarcoding provide accurate quantitative estimates of fish abundance in holding ponds with known fish biomass and number of individuals. eDNA samples were collected from two fishery ponds with high fish density and broad species diversity. In one pond, two different DNA capture strategies (on-site filtration with enclosed filters and three different preservation buffers versus lab filtration using open filters) were used to evaluate their performance in relation to fish community composition and biomass/abundance estimates. Fish species read counts were significantly correlated with both biomass and abundance, and this result, together with information on fish diversity, was repeatable when open or enclosed filters with different preservation buffers were used. This research demonstrates that eDNA metabarcoding provides accurate qualitative and quantitative information on fish communities in small ponds, and results are consistent between different methods of DNA capture. This method flexibility will be beneficial for future eDNA-based fish monitoring and their integration into fisheries management.
Copy rights belong to original authors. Visit the link for more info