Modelling snow algal habitat suitability and ecology under extreme weather events on the Antarctic Peninsula

Gray, Andrew Møller; Thomson, Alex Innes; Colesie, Claudia; Convey, Peter; Fretwell, Peter; Smith, Alison G.; Peck, Lloyd; Davey, Matthew P.

Modelling snow algal habitat suitability and ecology under extreme weather events on the Antarctic Peninsula

Gray, Andrew Møller; Thomson, Alex Innes; Colesie, Claudia; Convey, Peter ORCID: https://orcid.org/0000-0001-8497-9903; Fretwell, Peter ORCID: https://orcid.org/0000-0002-1988-5844; Smith, Alison G.; Peck, Lloyd ORCID: https://orcid.org/0000-0003-3479-6791; Davey, Matthew P.. 2025 Modelling snow algal habitat suitability and ecology under extreme weather events on the Antarctic Peninsula. Frontiers in Ecology and Evolution, 13, 1474446. 10.3389/fevo.2025.1474446

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Abstract/Summary

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-colored 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.

Item Type:

Publication - Article

Digital Object Identifier (DOI):

10.3389/fevo.2025.1474446

ISSN:

2296-701X

Additional Keywords:

snow algae, remote sensing, species distribution model, extreme weather events, Antarctica, climate change

NORA Subject Terms:

Ecology and Environment
Meteorology and Climatology

Date made live:

23 Sep 2025 10:58 +0 (UTC)