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. 2023 Apr 28;9(17):eadg1096.
doi: 10.1126/sciadv.adg1096. Epub 2023 Apr 26.

DNA metabarcoding highlights cyanobacteria as the main source of primary production in a pelagic food web model

Andreas Novotny  1 , Baptiste Serandour  1 , Susanne Kortsch  2   3 , Benoit Gauzens  4   5 , Kinlan M G Jan  1 , Monika Winder  1
Affiliations

DNA metabarcoding highlights cyanobacteria as the main source of primary production in a pelagic food web model

Andreas Novotny et al. Sci Adv. .

Abstract

Models that estimate rates of energy flow in complex food webs often fail to account for species-specific prey selectivity of diverse consumer guilds. While DNA metabarcoding is increasingly used for dietary studies, methodological biases have limited its application for food web modeling. Here, we used data from dietary metabarcoding studies of zooplankton to calculate prey selectivity indices and assess energy fluxes in a pelagic resource-consumer network. We show that food web dynamics are influenced by prey selectivity and temporal match-mismatch in growth cycles and that cyanobacteria are the main source of primary production in the investigated coastal pelagic food web. The latter challenges the common assumption that cyanobacteria are not supporting food web productivity, a result that is increasingly relevant as global warming promotes cyanobacteria dominance. While this study provides a method for how DNA metabarcoding can be used to quantify energy fluxes in a marine food web, the approach presented here can easily be extended to other ecosystems.

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Figures

Fig. 1.
Fig. 1.. Combining DNA metabarcoding, species population biomasses, and metabolic allometry to estimate energy fluxes in a bioenergetic model.
We used a bioenergetic model to calculate energy fluxes between zooplankton (consumers) and phytoplankton (resources) in a pelagic food web of the Baltic Sea. The model builds on a steady-state assumption, where total energy gains for each consumer equals their energetic losses. Energy is claimed from resources depending on their availability (e.g., biomasses), assimilation efficiencies, and consumer preferences or selectivity for each resource. Population biomasses and body mass information of the consumers were retrieved from the Swedish national pelagic monitoring database. Resource selectivity indices for each consumer were calculated using DNA metabarcoding of zooplankton gut content and water samples. This information was used to weigh the energy fluxes in the food web model. For a more detailed description, see Materials and Methods.
Fig. 2.
Fig. 2.. Consumer-resource network of the pelagic Baltic Sea.
Link width is proportional to fluxes of energy (kJ/m2) between resources (phytoplankton, bottom) and consumers (zooplankton, top). The width of the nodes (taxa) corresponds to each population’s contribution to annual secondary production. The diameter of each plot is proportional to the square root of the total production.
Fig. 3.
Fig. 3.. Predator-prey selectivity index for the consumers (zooplankton) in the food web calculated from 16S rRNA gene read abundance.
Fig. 4.
Fig. 4.. Seasonal dynamics in the Baltic Sea pelagic food web.
Daily population biomasses (g/m2) of (A) resources (phytoplankton) and (B) consumers (zooplankton). (C) Contribution of each resource to daily food web secondary production (kJ/m2). (D) Daily predation pressure for each resource population (kJ/g).
See this image and copyright information in PMC

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