Quantification of Small-Scale Spatial Patterns in Alpine-Treeline Ecotones.

Area of Science:

• Ecology
• Geosciences
• Environmental Science

Background:

• Alpine treeline ecotones exhibit spatial variations linked to climate change responses.
• Key pattern dimensions include abruptness (tree height change) and discreteness (canopy cover change).
• Current classification is often intuitive, lacking standardized, quantifiable metrics for site comparison.

Purpose of the Study:

• To develop and propose robust, consistent metrics for quantifying alpine treeline ecotone spatial patterns.
• To enable standardized comparisons of treeline ecotones across different sites and studies.
• To provide tools for better understanding treeline dynamics in response to climate change.

Main Methods:

• Metrics derived from point-pattern data (tree positions, sizes) and high-resolution tree cover data.
• Quantified abruptness using canopy height change in 5-m bands.
• Quantified discreteness using the steepness of a fitted logistic function to tree cover.
• Utilized field data from the Spanish Pyrenees and the Spatial Treeline-Ecotone Model (STEM).

Main Results:

• The developed 'discreteness' metric satisfactorily quantifies this pattern dimension.
• Quantifying the 'abruptness' pattern dimension proved more challenging with the current methods.
• Standardized settings are recommended for metrics to ensure comparability across studies.

Conclusions:

• The proposed metrics offer a standardized tool for field researchers to compare treeline ecotone sites.
• These metrics have the potential to facilitate global synthesis of treeline data and dynamics.
• Improved quantification of treeline patterns can enhance our understanding of climate change impacts on these sensitive ecosystems.