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Exposing wind stress as a driver of fine-scale variation in plant communities

Cite this dataset

Momberg, Mia; Hedding, David; Luoto, Miska; le Roux, Peter (2022). Exposing wind stress as a driver of fine-scale variation in plant communities [Dataset]. Dryad.


The effects of temperature and precipitation, and the impacts of changes in these climatic conditions, on plant communities have been investigated extensively. The roles of other climatic factors are, however, comparatively poorly understood, despite potentially also strongly structuring community patterns. Wind, for example, is seldom considered when forecasting species responses to climate change, despite having direct physiological and mechanical impacts on plants. It is, therefore, important to understand the magnitude of potential impacts of changing wind conditions on plant communities, particularly given that wind patterns are shifting globally.

Here, we examine the relationship between wind stress (i.e. a combination of wind exposure and wind speed) and species richness, vegetation cover and community composition using fine-scale, field-collected data from 1440 quadrats in a windy sub-Antarctic environment.

Wind stress was consistently a strong predictor of all three community characteristics, even after accounting for other potentially ecophysiologically important variables, including pH, potential direct incident solar radiation, winter and summer soil temperature, soil moisture, soil depth, and rock cover. Plant species richness peaked at intermediate wind stress, and vegetation cover was highest in plots with the greatest wind stress. Community composition was also related to wind stress, and, after the influence of soil moisture and pH, had a similar strength of effect as winter soil temperature.

Synthesis: Wind conditions are, therefore, clearly related to plant community characteristics in this ecosystem that experiences chronic winds. Based on these findings, wind conditions require greater attention when examining environment-community relationships, and changing wind patterns should be explicitly considered in climate change impact predictions.