Alpine greening deciphered by forest stand and structure dynamics in advancing treelines of the southwestern European Alps

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Abstract

Multidecadal time series of satellite observations, such as those from Landsat, offer the possibility to study trends in vegetation greenness at unprecedented spatial and temporal scales. Alpine ecosystems have exhibited large increases in vegetation greenness as seen from space; nevertheless, the ecological processes underlying alpine greening have rarely been investigated. Here, we used a unique dataset of forest stand and structure characteristics derived from manually orthorectified high-resolution diachronic images (1983 and 2018), dendrochronology and LiDAR analysis to decipher the ecological processes underlying alpine greening in the southwestern French Alps, formerly identified as a hotspot of greening at the scale of the European Alps by previous studies. We found that most of the alpine greening in this area can be attributed to forest dynamics, including forest ingrowth and treeline upward shift. Furthermore, we showed that the magnitude of the greening was highest in pixels/areas where trees were first established at the beginning of the Landsat time series in the mid-80s corresponding to a specific forest successional stage. In these pixels, we observe that trees from the first wave of establishment have grown between 1984 and 2023, while over the same period, younger trees established in forest gaps, leading to increases in both vertical and horizontal vegetation cover. This study provides an in-depth description of the causal relationship between forest dynamics and greening, providing a unique example of how ecological processes translate into radiometric signals, while also paving the way for the study of large-scale treeline dynamics using satellite remote sensing.

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APA

Bayle, A., Nicoud, B., Mansons, J., Francon, L., Corona, C., & Choler, P. (2025). Alpine greening deciphered by forest stand and structure dynamics in advancing treelines of the southwestern European Alps. Remote Sensing in Ecology and Conservation, 11(4), 375–393. https://doi.org/10.1002/rse2.430

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