SoilTemp: A global database of near-surface temperature


Jonas J. Lembrechts, Universiteit Antwerpen
Juha Aalto, Finnish Meteorological Institute
Michael B. Ashcroft, University of WollongongFollow
Pieter De Frenne, Universiteit Gent
Martin Kopecký, Academy of Sciences of the Czech Republic
Jonathan Lenoir, Université de Picardie Jules Verne
Miska Luoto, Helsingin Yliopisto
Ilya M.D. Maclean, University of Exeter
Olivier Roupsard, Ecologie fonctionnelle et biogéochimie des sols et agrosystèmes (Eco&Sols)
Eduardo Fuentes-Lillo, Universidad de Concepcion
Rafael A. García, Universidad de Concepcion
Loïc Pellissier, ETH Zürich
Camille Pitteloud, ETH Zürich
Juha M. Alatalo, Qatar University
Stuart W. Smith, Norges teknisk-naturvitenskapelige universitet
Robert G. Björk, Göteborgs Universitet
Lena Muffler, Universität Greifswald
Amanda Ratier Backes, Martin-Universität Halle-Wittenberg
Simone Cesarz, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig
Felix Gottschall, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig
Joseph Okello, Universiteit Gent
Josef Urban, Mendelova univerzita v Brne
Roman Plichta, Mendelova univerzita v Brne
Martin Svátek, Mendelova univerzita v Brne
Shyam S. Phartyal, Nalanda University
Sonja Wipf, WSL - Institut für Schnee- und Lawinenforschung SLF - Davos
Nico Eisenhauer, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig
Mihai Pușcaș, Universitatea Babeș-Bolyai
Pavel D. Turtureanu, Universitatea Babeș-Bolyai
Krystal Randall, University of WollongongFollow

Publication Details

Lembrechts, JJ, Aalto, J, Kopecký, M, Luoto, M, Maclean, IMD, Roupsard, O, et al. 2020, ‘SoilTemp: A global database of near‐surface temperature’, Global change biology, vol. 26, no. 11, pp. 6616–6629.


Current analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long-term average thermal conditions at coarse spatial resolutions only. Hence, many climate-forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold-air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free-air temperatures, microclimatic ground and near-surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near-surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes.

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