Quantitative assessment of reef foraminifera community from metabarcoding data

Molecular Ecology Resources, vol. 24, pp. e14000

Abstract

Describing living community compositions is essential to monitor ecosystems in a rapidly changing world, but it is challenging to produce fast and accurate depiction of ecosystems due to methodological limitations. Morphological methods provide absolute abundances with limited throughput, whereas metabarcoding provides relative abundances of genes that may not correctly represent living communities from environmental DNA assessed with morphological methods. However, it has the potential to deliver fast descriptions of living communities provided that it is interpreted with validated species-specific calibrations and reference databases. Here, we developed a quantitative approach to retrieve from metabarcoding data the assemblages of living large benthic foraminifera (LBF), photosymbiotic calcifying protists, from Indonesian coral reefs that are under increasing anthropogenic pressure. To depict the diversity, we calculated taxon-specific correction factors to reduce biological biases by comparing surface area, biovolume and calcite volume, and the number of mitochondrial gene copies in seven common LBF species. To validate the approach, we compared calibrated datasets of morphological communities from mock samples with bulk reef sediment; both sample types were metabarcoded. The calibration of the data significantly improved the estimations of genus relative abundance, with a difference of ±5% on average, allowing for comparison of past morphological datasets with future molecular ones. Our results also highlight the application of our quantitative approach to support reef monitoring operations by capturing fine-scale processes, such as seasonal and pollution-driven dynamics, that require high-throughput sampling treatment.

Authors 6

1. Elsa B. Girard corresponding Aachen Naturalis Biodiversity Center Leiden The Netherlands Naturalis Biodiversity Center

   Naturalis Biodiversity Center · University of Amsterdam

   Affiliation as printed

   IBED, University of Amsterdam Amsterdam The Netherlands

   Naturalis Biodiversity Center Leiden The Netherlands

   IBED, University of Amsterdam, Amsterdam, The Netherlands

   Naturalis Biodiversity Center, Leiden, The Netherlands

2. Emilie A. Didaskalou Aachen

   Leiden University

   Affiliation as printed

   CML, University of Leiden Leiden The Netherlands

   CML, University of Leiden, Leiden, The Netherlands

3. Andi M. A. Pratama

   Hasanuddin University

   Affiliation as printed

   Marine Science Department, Faculty of Marine Science and Fisheries Hasanuddin University Makassar Indonesia

   Marine Science Department, Faculty of Marine Science and Fisheries, Hasanuddin University, Makassar, Indonesia

4. Carolina Rattner Aachen Naturalis Biodiversity Center Leiden The Netherlands Naturalis Biodiversity Center

   Naturalis Biodiversity Center

   Affiliation as printed

   Naturalis Biodiversity Center Leiden The Netherlands

   Naturalis Biodiversity Center, Leiden, The Netherlands

5. Raphaël Morard

   University of Bremen

   Affiliation as printed

   MARUM, University of Bremen Bremen Germany

   MARUM, University of Bremen, Bremen, Germany

6. Willem Renema Aachen Naturalis Biodiversity Center Leiden The Netherlands Naturalis Biodiversity Center

   Naturalis Biodiversity Center · University of Amsterdam

   Affiliation as printed

   IBED, University of Amsterdam Amsterdam The Netherlands

   Naturalis Biodiversity Center Leiden The Netherlands

   IBED, University of Amsterdam, Amsterdam, The Netherlands

   Naturalis Biodiversity Center, Leiden, The Netherlands