# Trivial pursuits

## TL;DR

This paper critiques previous claims about nonlinear averaging predicting organism performance under temperature fluctuations, highlighting experimental and statistical flaws that affect the validity of those conclusions.

## Contribution

It identifies key methodological issues in prior research, emphasizing the importance of proper experimental design and statistical analysis in ecological performance studies.

## Key findings

- Previous conclusions are flawed due to hidden treatment effects.
- Single low-frequency temperature fluctuations can be tracked by organisms, affecting results.
- Using population growth rate as a performance metric can mask variability.

## Abstract

We demonstrate that the conclusions drawn by Bernhard et al. (2018) regarding the ability of nonlinear averaging to accurately predict organismal performance under fluctuating temperatures are flawed because of a series of experimental and statistical issues that include the presence of a hidden treatment effect, the use of a single low frequency temperature fluctuation that could easily be tracked by the fast growing organism, and the decision to quantify performance via population growth rate, a metric that can mask significant variation in population size.