A flexible model for thermal performance curves.

Area of Science:

• Ecology
• Evolutionary Biology
• Physiology

Background:

• Biological traits often exhibit thermal performance curves (TPCs) modeled phenomenologically or mechanistically.
• Existing TPC models lack flexibility or biological interpretability.

Purpose of the Study:

• Introduce flexTPC, a novel model for TPCs.
• Parameterize TPCs using biologically meaningful quantities.
• Enable flexible and interpretable modeling of temperature-dependent biological responses.

Main Methods:

• Developed flexTPC, a model using thermal minimum, optimum, maximum, peak value, and breadth.
• Applied flexTPC to microbial and entomological datasets.
• Compared flexTPC performance against the Briere model.

Main Results:

• flexTPC accurately describes TPCs of varying skewness and breadth.
• flexTPC demonstrated superior predictive performance compared to the Briere model in tested datasets.
• The model's parameters are directly interpretable in biological terms.

Conclusions:

• flexTPC offers a flexible, interpretable, and predictive approach to modeling TPCs.
• Ideal for studying how thermal responses change with environmental factors or evolve.
• Facilitates cross-species and cross-trait comparisons of thermal performance.