Mapping red algal blooms and their albedo-reducing effect on seasonal snowfields at Hardangervidda, Southern Norway

Lou Anne Chevrollier; Adrien Wehrlé; Joseph M. Cook; Grégoire Guillet; Liane G. Benning; Alexandre M. Anesio; Martyn Tranter

doi:10.3389/feart.2025.1508719

Mapping red algal blooms and their albedo-reducing effect on seasonal snowfields at Hardangervidda, Southern Norway

Lou Anne Chevrollier^*, Adrien Wehrlé, Joseph M. Cook, Grégoire Guillet, Liane G. Benning, Alexandre M. Anesio, Martyn Tranter

^*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

Abstract

Red snow algae bloom at the surface of snowfields worldwide, and their detection is relevant for ecological, biogeochemical and mass balance studies. In this study, we co-located RGB imagery acquired with a light-weight Uncrewed Aerial Vehicle (UAV) to 129 hyperspectral reflectance spectra from which the snow surface properties were retrieved, thereby enabling high-resolution aerial mapping of algal properties. We present maps of red snow algae abundance and albedo reducing effect over (Formula presented.) 9700 (Formula presented.) of seasonal snowfields across Hardangervidda, Southern Norway, in July and August 2023. The average albedo reducing effect of the algae over the entire area was 0.012 (Formula presented.) 0.005, and attained 0.028 (Formula presented.) 0.004 on a snowfield of (Formula presented.) 710 (Formula presented.). Across snow surfaces with visible blooms only, the algal albedo reducing effect was 0.045 (Formula presented.) 0.003, equivalent to an additional (Formula presented.) 3 mm of daily melting under local illumination conditions, and aggregating to 5,500 (Formula presented.) 2,300 kg of daily snowmelt. The intensity and spatial coverage of surface algal blooms were very variable between and within the individual snowfields. Analysis of the UAV imagery suggests that multiple small and distributed samples are at least twice more likely to yield representative estimates of the average snow algal concentration of a snowfield compared to fewer, larger samples. Our study demonstrates the potential of low-cost and easy to deploy UAVs for red snow algal monitoring at the cm to sub-cm scale, which can be used to better understand their spatial ecology and role in albedo reduction.

Original language	English
Article number	1508719
Journal	Frontiers in Earth Science
Volume	13
ISSN	2095-0195
DOIs	https://doi.org/10.3389/feart.2025.1508719 https://doi.org/10.3389/feart.2025.1508719
Publication status	Published - 2025

Keywords

albedo
algae
blooms
snow
uncrewed aerial vehicle

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@article{8eb656b9db074088b990f2ed92c939fc,

title = "Mapping red algal blooms and their albedo-reducing effect on seasonal snowfields at Hardangervidda, Southern Norway",

abstract = "Red snow algae bloom at the surface of snowfields worldwide, and their detection is relevant for ecological, biogeochemical and mass balance studies. In this study, we co-located RGB imagery acquired with a light-weight Uncrewed Aerial Vehicle (UAV) to 129 hyperspectral reflectance spectra from which the snow surface properties were retrieved, thereby enabling high-resolution aerial mapping of algal properties. We present maps of red snow algae abundance and albedo reducing effect over (Formula presented.) 9700 (Formula presented.) of seasonal snowfields across Hardangervidda, Southern Norway, in July and August 2023. The average albedo reducing effect of the algae over the entire area was 0.012 (Formula presented.) 0.005, and attained 0.028 (Formula presented.) 0.004 on a snowfield of (Formula presented.) 710 (Formula presented.). Across snow surfaces with visible blooms only, the algal albedo reducing effect was 0.045 (Formula presented.) 0.003, equivalent to an additional (Formula presented.) 3 mm of daily melting under local illumination conditions, and aggregating to 5,500 (Formula presented.) 2,300 kg of daily snowmelt. The intensity and spatial coverage of surface algal blooms were very variable between and within the individual snowfields. Analysis of the UAV imagery suggests that multiple small and distributed samples are at least twice more likely to yield representative estimates of the average snow algal concentration of a snowfield compared to fewer, larger samples. Our study demonstrates the potential of low-cost and easy to deploy UAVs for red snow algal monitoring at the cm to sub-cm scale, which can be used to better understand their spatial ecology and role in albedo reduction.",

keywords = "albedo, algae, blooms, snow, uncrewed aerial vehicle",

author = "Chevrollier, {Lou Anne} and Adrien Wehrl{\'e} and Cook, {Joseph M.} and Gr{\'e}goire Guillet and Benning, {Liane G.} and Anesio, {Alexandre M.} and Martyn Tranter",

year = "2025",

doi = "10.3389/feart.2025.1508719",

language = "English",

volume = "13",

journal = "Frontiers in Earth Science",

issn = "2095-0195",

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Mapping red algal blooms and their albedo-reducing effect on seasonal snowfields at Hardangervidda, Southern Norway. / Chevrollier, Lou Anne; Wehrlé, Adrien; Cook, Joseph M. et al.
In: Frontiers in Earth Science, Vol. 13, 1508719, 2025.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

TY - JOUR

T1 - Mapping red algal blooms and their albedo-reducing effect on seasonal snowfields at Hardangervidda, Southern Norway

AU - Chevrollier, Lou Anne

AU - Wehrlé, Adrien

AU - Cook, Joseph M.

AU - Guillet, Grégoire

AU - Benning, Liane G.

AU - Anesio, Alexandre M.

AU - Tranter, Martyn

PY - 2025

Y1 - 2025

N2 - Red snow algae bloom at the surface of snowfields worldwide, and their detection is relevant for ecological, biogeochemical and mass balance studies. In this study, we co-located RGB imagery acquired with a light-weight Uncrewed Aerial Vehicle (UAV) to 129 hyperspectral reflectance spectra from which the snow surface properties were retrieved, thereby enabling high-resolution aerial mapping of algal properties. We present maps of red snow algae abundance and albedo reducing effect over (Formula presented.) 9700 (Formula presented.) of seasonal snowfields across Hardangervidda, Southern Norway, in July and August 2023. The average albedo reducing effect of the algae over the entire area was 0.012 (Formula presented.) 0.005, and attained 0.028 (Formula presented.) 0.004 on a snowfield of (Formula presented.) 710 (Formula presented.). Across snow surfaces with visible blooms only, the algal albedo reducing effect was 0.045 (Formula presented.) 0.003, equivalent to an additional (Formula presented.) 3 mm of daily melting under local illumination conditions, and aggregating to 5,500 (Formula presented.) 2,300 kg of daily snowmelt. The intensity and spatial coverage of surface algal blooms were very variable between and within the individual snowfields. Analysis of the UAV imagery suggests that multiple small and distributed samples are at least twice more likely to yield representative estimates of the average snow algal concentration of a snowfield compared to fewer, larger samples. Our study demonstrates the potential of low-cost and easy to deploy UAVs for red snow algal monitoring at the cm to sub-cm scale, which can be used to better understand their spatial ecology and role in albedo reduction.

AB - Red snow algae bloom at the surface of snowfields worldwide, and their detection is relevant for ecological, biogeochemical and mass balance studies. In this study, we co-located RGB imagery acquired with a light-weight Uncrewed Aerial Vehicle (UAV) to 129 hyperspectral reflectance spectra from which the snow surface properties were retrieved, thereby enabling high-resolution aerial mapping of algal properties. We present maps of red snow algae abundance and albedo reducing effect over (Formula presented.) 9700 (Formula presented.) of seasonal snowfields across Hardangervidda, Southern Norway, in July and August 2023. The average albedo reducing effect of the algae over the entire area was 0.012 (Formula presented.) 0.005, and attained 0.028 (Formula presented.) 0.004 on a snowfield of (Formula presented.) 710 (Formula presented.). Across snow surfaces with visible blooms only, the algal albedo reducing effect was 0.045 (Formula presented.) 0.003, equivalent to an additional (Formula presented.) 3 mm of daily melting under local illumination conditions, and aggregating to 5,500 (Formula presented.) 2,300 kg of daily snowmelt. The intensity and spatial coverage of surface algal blooms were very variable between and within the individual snowfields. Analysis of the UAV imagery suggests that multiple small and distributed samples are at least twice more likely to yield representative estimates of the average snow algal concentration of a snowfield compared to fewer, larger samples. Our study demonstrates the potential of low-cost and easy to deploy UAVs for red snow algal monitoring at the cm to sub-cm scale, which can be used to better understand their spatial ecology and role in albedo reduction.

KW - albedo

KW - algae

KW - blooms

KW - snow

KW - uncrewed aerial vehicle

UR - http://www.scopus.com/inward/record.url?scp=86000080904&partnerID=8YFLogxK

U2 - 10.3389/feart.2025.1508719

DO - 10.3389/feart.2025.1508719

M3 - Journal article

SN - 2095-0195

VL - 13

JO - Frontiers in Earth Science

JF - Frontiers in Earth Science

M1 - 1508719

ER -

Mapping red algal blooms and their albedo-reducing effect on seasonal snowfields at Hardangervidda, Southern Norway

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Keywords

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