In this section
@article{Kontopoulos:2024,
author = {Kontopoulos, D-G and Sentis, A and Daufresne, M and Pawar, S},
journal = {Nature Communications},
title = {No universal mathematical model for thermal performance curves across traits and taxonomic groups},
url = {http://hdl.handle.net/10044/1/115067},
year = {2024}
}
TY - JOUR
AB - In ectotherms, the performance of physiological, ecological and life-historytraits universally increases with temperature to a maximum before decreasingagain. Identifying the most appropriate thermal performance model for aspecific trait type has broad applications, from metabolic modelling at thecellular level to forecasting the effects of climate change on population, ecosystem and disease transmission dynamics. To date, numerous mathematicalmodels have been designed, but a thorough comparison among them islacking. In particular, we do not know if certain models consistently outperform others and how factors such as sampling resolution and trait or organismal identity influence model performance. To fill this knowledge gap, wecompile 2,739 thermal performance datasets from diverse traits and taxa, towhich we fit a comprehensive set of 83 existing mathematical models. Wedetect remarkable variation in model performance that is not primarily drivenby sampling resolution, trait type, or taxonomic information. Our resultsreveal a surprising lack of well-defined scenarios in which certain models aremore appropriate than others. To aid researchers in selecting the appropriateset of models for any given dataset or research objective, we derive a classification of the 83 models based on the average similarity of their fits
AU - Kontopoulos,D-G
AU - Sentis,A
AU - Daufresne,M
AU - Pawar,S
PY - 2024///
SN - 2041-1723
TI - No universal mathematical model for thermal performance curves across traits and taxonomic groups
T2 - Nature Communications
UR - http://hdl.handle.net/10044/1/115067
ER -