ForestTemp – Sub-canopy microclimate temperatures of European forests

Stef Haesen*, Jonas J. Lembrechts, Pieter De Frenne, Jonathan Lenoir, Juha Aalto, Michael B. Ashcroft, Martin Kopecký, Miska Luoto, Ilya Maclean, Ivan Nijs, Pekka Niittynen, Johan van den Hoogen, Nicola Arriga, Josef Brůna, Nina Buchmann, Marek Čiliak, Alessio Collalti, Emiel De Lombaerde, Patrice Descombes, Mana GharunIgnacio Goded, Sanne Govaert, Caroline Greiser, Achim Grelle, Carsten Gruening, Lucia Hederová, Kristoffer Hylander, Jürgen Kreyling, Bart Kruijt, Martin Macek, František Máliš, Matěj Man, Giovanni Manca, Radim Matula, Camille Meeussen, Sonia Merinero, Stefano Minerbi, Leonardo Montagnani, Lena Muffler, Romà Ogaya, Josep Penuelas, Roman Plichta, Miguel Portillo-Estrada, Jonas Schmeddes, Ankit Shekhar, Fabien Spicher, Mariana Ujházyová, Pieter Vangansbeke, Robert Weigel, Jan Wild, Florian Zellweger, Koenraad Van Meerbeek

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)

Abstract

Ecological research heavily relies on coarse-gridded climate data based on standardized temperature measurements recorded at 2 m height in open landscapes. However, many organisms experience environmental conditions that differ substantially from those captured by these macroclimatic (i.e. free air) temperature grids. In forests, the tree canopy functions as a thermal insulator and buffers sub-canopy microclimatic conditions, thereby affecting biological and ecological processes. To improve the assessment of climatic conditions and climate-change-related impacts on forest-floor biodiversity and functioning, high-resolution temperature grids reflecting forest microclimates are thus urgently needed. Combining more than 1200 time series of in situ near-surface forest temperature with topographical, biological and macroclimatic variables in a machine learning model, we predicted the mean monthly offset between sub-canopy temperature at 15 cm above the surface and free-air temperature over the period 2000–2020 at a spatial resolution of 25 m across Europe. This offset was used to evaluate the difference between microclimate and macroclimate across space and seasons and finally enabled us to calculate mean annual and monthly temperatures for European forest understories. We found that sub-canopy air temperatures differ substantially from free-air temperatures, being on average 2.1°C (standard deviation ± 1.6°C) lower in summer and 2.0°C higher (±0.7°C) in winter across Europe. Additionally, our high-resolution maps expose considerable microclimatic variation within landscapes, not captured by the gridded macroclimatic products. The provided forest sub-canopy temperature maps will enable future research to model below-canopy biological processes and patterns, as well as species distributions more accurately.

Original languageEnglish
Pages (from-to)6307-6319
JournalGlobal Change Biology
Volume27
Issue number23
Early online date3 Oct 2021
DOIs
Publication statusPublished - 2021

Keywords

  • biodiversity
  • boosted regression trees
  • climate change
  • ecosystem processes
  • forest microclimate
  • SoilTemp
  • species distributions
  • thermal buffering

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