23 January 2024 | Ali Ismaeel, Amos P. K. Tai, Erone Chizoni Santos, Heveakore Marai, Iris Aalto, Jan Altman, Jiří Doležal, Jonas J. Lembrechts, José Luis Camargo, Juha Aalto, Kateřina Sam, Lair Cristina Avelino do Nascimento, Martin Kopecký, Martin Svátek, Matheus Henrique Nunes, Radim Matula, Roman Plichta, Temesgen Abera, Eduardo Eiji Maeda
This study presents a high-resolution, pantropical estimate of near-ground (15 cm above the surface) temperatures inside tropical forests, quantifying diurnal and seasonal variability to reveal spatial and temporal microclimate patterns. The average understory temperature is 1.6 °C cooler than open-air temperatures, with a diurnal temperature range 1.7 °C lower. The study highlights substantial spatial variability in microclimate characteristics, influenced by large-scale climate conditions, vegetation structure, and topography. These findings contribute to understanding the thermal ranges experienced by organisms in tropical forests and provide insights into how these limits may be affected by climate change and ecosystem disturbances. The results also demonstrate the importance of incorporating microclimate data in ecological and biophysical models to improve predictions of species distribution and responses to climate change.This study presents a high-resolution, pantropical estimate of near-ground (15 cm above the surface) temperatures inside tropical forests, quantifying diurnal and seasonal variability to reveal spatial and temporal microclimate patterns. The average understory temperature is 1.6 °C cooler than open-air temperatures, with a diurnal temperature range 1.7 °C lower. The study highlights substantial spatial variability in microclimate characteristics, influenced by large-scale climate conditions, vegetation structure, and topography. These findings contribute to understanding the thermal ranges experienced by organisms in tropical forests and provide insights into how these limits may be affected by climate change and ecosystem disturbances. The results also demonstrate the importance of incorporating microclimate data in ecological and biophysical models to improve predictions of species distribution and responses to climate change.