Continuous quantification of forest microclimate temperatures in space and time using fibre‐optic technology

Abstract Most species experience microclimate temperatures, that is, variable and fine‐grained thermal conditions determined by atmospheric conditions interacting with biotic and abiotic components of the earth's surface. Unfortunately, measuring microclimates at biologically meaningful grain sizes is challenging. We showcase the potential of fibre‐optic distributed temperature sensing (DTS) to quantify diurnal variation in microclimatic air temperatures during the growing season along a 135‐m forest edge‐to‐interior transect at 25‐cm horizontal resolution. We benchmark DTS measurements against the microclimate quantified with ultrafine wire thermocouples and more conventional sensors at 15‐m intervals along the transect. Diurnal measurements from DTS indicate maximal cooling of forest floor temperatures (up to −6°C) in the morning (around 8:00 AM) and well away from the forest edge. Negative offset values gradually increased during the day reaching zero (0°C) in the evening (around 21:00 PM). Synthesis . While both DTS and discrete point sampling with microclimate loggers allow to quantify diurnal cycles of microclimate gradients with unified spatial and temporal patterns, DTS provides accurate temperature measurements at a spatial detail nearly impossible to achieve with discrete point sampling. When applied over transects of several hundreds of meters—up to kilometres—fibre‐optic DTS is a cost‐efficient alternative offering substantial potential to advancing microclimate research.

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Publication Details

Journal
Methods in Ecology and Evolution
Published
2025-09-18
DOI
https://doi.org/10.1111/2041-210x.70151
Citations
1
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
1.72

Funders

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article

Continuous quantification of forest microclimate temperatures in space and time using fibre‐optic technology

Pieter De Frenne, Louise Terryn, Kim Calders, Tom Verhelst et al.
1 citations
Methods in Ecology and Evolution
Remote Sensing in Agriculture
1.72
article

Continuous quantification of forest microclimate temperatures in space and time using fibre‐optic technology

Pieter De Frenne, Louise Terryn, Kim Calders, Tom Verhelst, Pieter Sanczuk, Yanlu Li, Ilya M. D. Maclean, Emma Van de Walle, Bart Kuyken, Michiel Stock, Ruth Warfield, Félicien Meunier, Hans Verbeeck, Zhizhi Yang
article en
1 citations

Abstract

Abstract Most species experience microclimate temperatures, that is, variable and fine‐grained thermal conditions determined by atmospheric conditions interacting with biotic and abiotic components of the earth's surface. Unfortunately, measuring microclimates at biologically meaningful grain sizes is challenging. We showcase the potential of fibre‐optic distributed temperature sensing (DTS) to quantify diurnal variation in microclimatic air temperatures during the growing season along a 135‐m forest edge‐to‐interior transect at 25‐cm horizontal resolution. We benchmark DTS measurements against the microclimate quantified with ultrafine wire thermocouples and more conventional sensors at 15‐m intervals along the transect. Diurnal measurements from DTS indicate maximal cooling of forest floor temperatures (up to −6°C) in the morning (around 8:00 AM) and well away from the forest edge. Negative offset values gradually increased during the day reaching zero (0°C) in the evening (around 21:00 PM). Synthesis . While both DTS and discrete point sampling with microclimate loggers allow to quantify diurnal cycles of microclimate gradients with unified spatial and temporal patterns, DTS provides accurate temperature measurements at a spatial detail nearly impossible to achieve with discrete point sampling. When applied over transects of several hundreds of meters—up to kilometres—fibre‐optic DTS is a cost‐efficient alternative offering substantial potential to advancing microclimate research.

Methods in Ecology and EvolutionVol. 16(12)
Research Institute for Nature and Forest (BE), University of Exeter (GB), Ghent University (BE)
Met Office, Fonds Wetenschappelijk Onderzoek, Universiteit Gent, Bijzonder Onderzoeksfonds UGent
Openalex Percentile: Top 14%
Remote Sensing in Agriculture
1.72
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