We are very pleased to announce that the paper introducing bayesTPC has appeared in Methods in Ecology and Evolution. The bayesTPC R package is for Bayesian fitting of Thermal Performance Curves (TPCs) to trait responses. The package is built using the nimble language and machinery as the underlying engine for Markov Chain Monte Carlo (MCMC). The paper, led by former QED undergraduate researcher Sean Sorek. Our main aims in releasing bayesTPC were to support the adoption of Bayesian approaches in thermal physiology, and to promote TPC fitting that adequately quantifies uncertainty. For a bit more information, take a look at the blog post about the paper over at the VectorByte Initiative.
Sorek, S., Smith, J. W. Jr., Huxley, P. J., & Johnson, L. R. (2025). bayesTPC: Bayesian inference for thermal performance curves in R. Methods in Ecology and Evolution, 16, 687–697. https://doi.org/10.1111/2041-210X.70004