# Numerical and functional response of phagotrophic aquatic protists: the ideal experiment—and why we cannot get it

## TL;DR

The paper discusses challenges in conducting standardized experiments on aquatic protists' growth and feeding rates, emphasizing the need for better methods to reduce experimental noise.

## Contribution

The paper highlights the lack of standardization in NR and FR experiments and provides guidelines to improve experimental reproducibility.

## Key findings

- NR and FR experiments with phagotrophic protists are subject to uncontrolled variables that affect results.
- FR experiments are more prone to experimental bias than NR experiments.
- Standardizing all variables in NR and FR experiments is practically impossible.

## Abstract

Protists are paramount for biogeochemical cycling in every aquatic ecosystem due to their vast population sizes and physiological versatility. Numerical response (NR) and functional response (FR) experiments are cornerstones of trait-based functional ecology and are increasingly studied experimentally with phagotrophic aquatic protists. Such experiments provide estimates of protist growth, production and consumption rates in relation to biotic (food supply) and abiotic variables (e.g., temperature, pH, and salinity) that can be used in mathematical models of ecosystem dynamics. Until now, NR and FR experiments lack standardization and are subject to potential pitfalls that received little attention in the literature. It is a common misconception that an experimental investigation of a phagotrophic protist’s growth and ingestion rates represents a single experiment with replication. I demonstrate that a typical NR or FR experiment consists of a series of individual experiments in which not only the experimental target variable (food, i.e., prey abundance or biomass) changes but also other factors (physiological conditions of prey and predator, nutrient levels, unwanted contaminants) vary that may affect the experimental outcome. Standardizing all variables affecting a series of NR and FR experiments is virtually impossible. I further explain why FR experiments are more prone to experimental bias than NR experiments. Since it is principally impossible to perform an “ideal” NR or FR experiment, fulfilling all criteria of experimental standardization, the goal is to reduce the “noise” to obtain statistically significant and reproducible results. To this end, I provide guidelines that may help achieve this goal in future studies.