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April 27, 2026Scientific Data0 citationsOpen Access

A Global Dataset of Alpine Treeline Elevational Transects

CWChenyang WeiAWAdam M. Wilson

Key Points

  • To develop a comprehensive dataset that characterizes the elevational gradients of Alpine Treeline Ecotone (ATE) worldwide.
  • Created a geospatial dataset of 2.3 million elevational transects within global ATEs
  • Integrated climatology with environmental attributes like elevation, landforms, hydrology, and land cover
  • Facilitated standardized analysis by mapping ecological transitions from montane forests to alpine zones.
  • Mapped diverse ecological transitions effectively across global ATEs
  • Provided a robust tool for modeling ecosystem properties and tracking environmental changes
  • Enabled forecasts of climate change effects on mountain ecosystems.

Abstract

The Alpine Treeline Ecotone (ATE) is an important ecological transition zone at the juncture of montane forests and alpine vegetation. It serves as a crucial habitat for diverse species and a sensitive indicator of climate change. Consistent characterization of the elevational gradients of ATE is challenging due to complex topography and data limitations. This study introduces a comprehensive geospatial dataset delineating 2.3 million elevational transects within global ATEs. The dataset integrates global climatology with key environmental attributes, such as elevation, landforms, hydrology, and land cover. These transects effectively map the ecological transition from dense montane forests to barren, higher-altitude ridges. Their spatial flexibility facilitates standardized comparative analysis of ATEs, effectively bridging the gap between local field studies and global assessments in alpine research. The dataset can be employed to model the elevational distribution of ecosystem properties within ATEs, track the temporal changes of environmental factors along the ATE’s elevational gradients, and forecast the specific, enduring effects of climate change on mountain ecosystems worldwide.

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Cite This Study

Wei et al. (2026) studied this question.

synapsesocial.com/papers/69eefd64fede9185760d406ahttps://doi.org/10.1038/s41597-026-07293-1
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