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ORIGINAL RESEARCH article

Front. Ecol. Evol.

Sec. Biogeography and Macroecology

Volume 13 - 2025 | doi: 10.3389/fevo.2025.1474446

This article is part of the Research TopicBiodiversity of Antarctic and Subantarctic EcosystemsView all 12 articles

Modelling Snow Algal Habitat Suitability and Ecology Under Extreme Weather Events on the Antarctic Peninsula

Provisionally accepted
  • 1Norwegian Institute for Nature Research (NINA), Trondheim, Norway
  • 2College of Science and Engineering, University of Edinburgh, Edinburgh, Scotland, United Kingdom
  • 3Scottish Association For Marine Science, Oban, United Kingdom
  • 4British Antarctic Survey (BAS), Cambridge, United Kingdom
  • 5Department of Plant Sciences, Faculty of Biology, School of Biological Sciences, University of Cambridge, Cambridge, England, United Kingdom

The final, formatted version of the article will be published soon.

Snow algae form extensive blooms within Antarctica's coastal snowpacks and are a crucial contributor to its scarce terrestrial ecosystems. There is limited knowledge about the factors that contribute to snow algal bloom occurrence, distribution, ecological niche thresholds, or the prevalence of suitable conditions for bloom formation. To address these knowledge gaps and gain a clearer understanding of the current and potential future distribution of blooms, a habitat suitability model, using a Bayesian additive regression tree approach, was established. The model incorporated remotely sensed observations of blooms, physical environmental predictor variables, and snow melt modelling based on different climate scenarios. This was used to describe the ecological niche of snow algae and predict its occurrence at a landscape scale across the Antarctic Peninsula. The findings revealed that most habitable snow was predicted north of latitude 66° S, with patch density, area, and habitable elevation decreasing poleward. Factors that strongly influenced bloom presence were days of snow melt and aspect, with blooms of red-coloured algae being associated with longer seasons and north-facing slopes. The model outputs also suggested heterogeneous preferences for environmental conditions amongst red and green snow algae blooms, suggesting a diversity of ecological niches for bloom-forming algae. Long-term climate-change impacts were difficult to discern as extreme summer temperatures and melt during the timeframe of this study in 2021 exceeded the projected 2100 temperatures for parts of the Antarctic Peninsula. However, warmer conditions produced a greater area of potentially habitable snow at higher elevation and latitude. Conversely, small and low-lying islands were predicted to lose habitable snow under a warming scenario. Model and training imagery both indicated that algal blooms are forming on snow-covered icecaps in the South Shetland Islands, suggesting greater potential for glacier-based algal blooms in the future, should recent trends for extreme summer temperatures persist.

Keywords: Snow algae, remote sensing, Species distribution model, extreme weather events, Antarctica, Climate Change

Received: 01 Aug 2024; Accepted: 03 Sep 2025.

Copyright: © 2025 Gray, Thomson, Colesie, Convey, Fretwell, Smith, Peck and Davey. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Andrew Gray, Norwegian Institute for Nature Research (NINA), Trondheim, Norway

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