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Data from: A high-throughput method to quantify feeding rates in aquatic organisms: A case study with Daphnia

Cite this dataset

Hite, Jessica; Pfenning-Butterworth, Alaina; Vetter, Rachel; Cressler, Clayton (2021). Data from: A high-throughput method to quantify feeding rates in aquatic organisms: A case study with Daphnia [Dataset]. Dryad.


Food ingestion is one of the most basic features of all organisms. However, obtaining precise — and high-throughput — estimates of feeding rates remains challenging, particularly for small, aquatic herbivores such as zooplankton, snails, and tadpoles. These animals typically consume low volumes of food that are time consuming to accurately measure.

We extend a standard high-throughput fluorometry technique, which uses a microplate reader and 96-well plates, as a practical tool for studies in ecology, evolution, and disease biology. We outline technical and methodological details to optimize quantification of individual feeding rates, improve accuracy, and minimize sampling error.

This high-throughput assay offers several advantages over previous methods, including: i) substantially reduced time allotments per sample to facilitate larger, more efficient experiments; ii) technical replicates; and iii) conversion of in vivo measurements to units of carbon (mg dw L-1), which enables broad-scale comparisons across an array of taxa and studies.

To evaluate the accuracy and feasibility of our approach, we use the zooplankton, Daphnia dentifera as a case study. Our results indicate that this procedure accurately quantifies feeding rates and highlights differences among seven genotypes.

The method detailed here has broad applicability to a diverse array of aquatic taxa, their food, environmental contaminants (e.g., plastics), and infectious agents. We discuss simple extensions to quantify epidemiologically relevant traits, such as pathogen exposure and transmission rates, for infectious agents with oral or trophic transmission.


This method uses a microplate reader (TecanÓ, Maennedorf, Switzlerand) to quantify feeding rates using in vivo narrow-band fluorometry, a standard and widely-used method for accurately measuring chlorophyll-a  (Lorenzen, 1966; Kalaji et al., 2014). In brief, the goal is to compare the fluorescence of algae in tubes with animals (consumers) vs. the fluorescence of algae in the animal-free (consumer-free) controls, following Sarnelle and Wilson (2008). We provide a detailed protocol aimed at improving repeatability and analytical accuracy, while minimizing variation among samples. The most important, but easily overlooked, details include: (i) preparing all media in batch cultures and mixing it continuously prior to and throughout distribution to each biological replicate; (ii) conducting the assay under minimal light conditions to prevent spurious spikes in fluorescence; (iii) ensuring that the ratio of chlorophyll to carbon remains constant across assays; and (iv) pair-matching plate-specific controls with their respective treatment samples to reduce among-plate variation.

Usage notes

To minimize noise introduced by among-read variation (Petersen & Nguyen, 2005; Resch-Genger et al., 2005), it is crucial that each plate is treated as a block and contains control samples (i.e., algae from no-animals/consumers replicates) and that the average of these plate-specific controls are used to calculate feeding rates. That is, in the equations below, the control values come from each plate and are not averaged across all controls. This design reflects a matched-pairs layout and uses replication within blocks to help tease apart main effects, block effects, and their interaction (Gotelli & Ellison, 2004). This added step is an obvious limitation of this method. However, this is currently the best solution for maximizing the signal-to-noise ratio given the extreme sensitivity of modern fluorometers. In the online supplementary material that accompanies this manuscript, we include R code to facilitate these additional quality-control steps.


National Institute of General Medical Sciences, Award: F32GM128246