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<p>Topography is a dominant driver of microclimate, soil conditions and disturbance regimes in mountain environments on various scales, and thus a key component of the specific landscape experienced by alpine plants. Over the last two decades, very high‑resolution digital elevation models (VHR DEMs; resolution ≤ 1&#xa0;m) have transformed our capacity to quantify topography and its synthetic derivatives across nested spatial scales. These data have progressively reshaped how we conceptualize and measure environmental heterogeneity in evolutionary ecology. Multiscale analyses based on VHR DEMs and their derived proxies of ecological relevance can disentangle complex selective pressures exerted by alpine landscapes. DEM‑derived variables have been used in species distribution models and in landscape genomics of alpine plants, emphasizing the transition from single‑scale to explicitly multiscale frameworks. Here, we review practical issues associated with the acquisition of such data as well as computational and statistical challenges related to the modelling phase. Showing how environmental variables associated with genomic data at multiple scales have already advanced our understanding of local adaptation, we discuss how the integration of multiscale proxies may further help to reconcile correlative and mechanistic approaches (e.g., process-based or eco-physiological models), and guide conservation decisions in rapidly warming alpine ecosystems.</p>

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Scaling the mountains: multiscale proxies derived from very high-resolution digital elevation models to characterize heterogeneous alpine landscapes and their local effects on plant adaptation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月27日

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  • Stéphane Joost,
  • Christian Parisod,
  • Felix Gugerli

摘要

Topography is a dominant driver of microclimate, soil conditions and disturbance regimes in mountain environments on various scales, and thus a key component of the specific landscape experienced by alpine plants. Over the last two decades, very high‑resolution digital elevation models (VHR DEMs; resolution ≤ 1 m) have transformed our capacity to quantify topography and its synthetic derivatives across nested spatial scales. These data have progressively reshaped how we conceptualize and measure environmental heterogeneity in evolutionary ecology. Multiscale analyses based on VHR DEMs and their derived proxies of ecological relevance can disentangle complex selective pressures exerted by alpine landscapes. DEM‑derived variables have been used in species distribution models and in landscape genomics of alpine plants, emphasizing the transition from single‑scale to explicitly multiscale frameworks. Here, we review practical issues associated with the acquisition of such data as well as computational and statistical challenges related to the modelling phase. Showing how environmental variables associated with genomic data at multiple scales have already advanced our understanding of local adaptation, we discuss how the integration of multiscale proxies may further help to reconcile correlative and mechanistic approaches (e.g., process-based or eco-physiological models), and guide conservation decisions in rapidly warming alpine ecosystems.