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Updated: May 20, 2025
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Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
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Modelling microclimatic variability in Andean forests of northern Patagonia
Jonas Fierke1, Birgitta Putzenlechner2, Alois Simon3
1Institute of Geography, University of Goettingen, Goldschmidtstraße 3, 37077, Goettingen, Germany. jonas.fierke@uni-goettingen.de.
International Journal of Biometeorology
|March 25, 2025
Summary
This study models microclimatic conditions in Patagonia, revealing key factors influencing biodiversity response to climate change. The findings provide crucial spatiotemporal data for ecological research in data-scarce regions.
Area of Science:
- Ecology
- Environmental Science
- Climatology
Background:
- Understanding microclimates is vital for ecological processes and biodiversity's response to climate change.
- Data on climate-driven species distribution are scarce in north-western Patagonia.
- Accurate microclimatic data are essential for conservation efforts.
Purpose of the Study:
- To develop high-resolution (30x30m) spatiotemporal microclimatic models for north-western Patagonia.
- To assess the influence of biophysical variables on microclimate dynamics.
- To provide a benchmark for future ecological and climate change impact studies in the region.
Main Methods:
- Utilized in-situ data from 2022-2024.
- Employed random forest-based regression with terrain and vegetation predictors.
- Applied statistical downscaling of ERA5 data for spatiotemporal interpolation.
Main Results:
- Predictor variable influence varied significantly by month and microclimatic variable.
- Models demonstrated strong explanatory power (e.g., R² of 0.88 for max. air temp. at 2m).
- Identified key drivers of microclimatic variability at different vertical forest levels.
Conclusions:
- The developed models offer a valuable tool for understanding species distribution in response to climate change in Patagonia.
- The approach serves as a benchmark for spatiotemporal projections in data-limited areas.
- Future research should incorporate snow cover, land use, soil, and vegetation structure for enhanced dynamical modeling.
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