Rosen et al. (2026) Modelling forest dynamics using integral projection models and repeat lidar

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Remote Sensing in Ecology and Conservation
• Year: 2026
• Date: 2026-04-11
• Authors: Alice Rosen, Robin Battison, Christina M. Hernández, Oliver G. Spacey, Jessica McLean, Suzanne M. Prober, Samuel J. L. Gascoigne, Sean M. McMahon, Tommaso Jucker, Roberto Salguero‐Gómez
• DOI: 10.1002/rse2.70050

Research Groups

[Information not available in the abstract.]

Short Summary

This study integrates repeat airborne lidar data with an integral projection model (IPM) to analyze forest-wide demography in response to environmental drivers. It successfully modeled the survival, growth, and life expectancy of approximately 40,000 eucalypt trees over a decade, revealing distinct responses of small and large trees to competition and soil moisture, with drier conditions reducing life expectancy, especially for larger trees.

Objective

• To demonstrate an approach that integrates repeat airborne lidar data with a structured demographic model (integral projection model, IPM) to examine forest-wide demography in response to environmental drivers.

Study Configuration

• Spatial Scale: Regional (Australia's Great Western Woodlands), focusing on individual trees (approximately 40,000 eucalypts).
• Temporal Scale: 10 years.

Methodology and Data

• Models used: Integral projection model (IPM), a stage-structured demographic model.
• Data sources: Repeat airborne lidar data.

Main Results

• Successfully modeled the survival, growth, and life expectancy of approximately 40,000 eucalypt trees over a decade.
• Vital rates were modeled using tree height for small trees and crown area for large trees, reflecting a size-dependent shift in growth strategy.
• Demonstrated distinct responses of small and large trees to proxies for competition (local canopy density) and soil moisture (topographic wetness index).
• A reduction in topographic wetness index, indicating drier conditions, led to lower life expectancy, particularly for larger trees, suggesting increased vulnerability to drought for larger individuals.
• The developed framework enables scalable demographic analysis using widely available lidar data.

Contributions

• Provides a novel, scalable approach for forest-wide demographic analysis by integrating repeat airborne lidar data with an integral projection model, overcoming limitations of traditional field-data intensive methods.
• Offers a valuable tool for forest monitoring, modeling, and management by linking individual tree trajectories to whole-forest outcomes using remote sensing data.
• Identifies key priorities for broader application, including analysis of mixed species stands and multilayered canopies, full life cycle modeling (reproduction and early life stages), and long-term or comparative studies using high-quality repeat lidar.

Funding

[Information not available in the abstract.]

Citation

@article{Rosen2026Modelling,
  author = {Rosen, Alice and Battison, Robin and Hernández, Christina M. and Spacey, Oliver G. and McLean, Jessica and Prober, Suzanne M. and Gascoigne, Samuel J. L. and McMahon, Sean M. and Jucker, Tommaso and Salguero‐Gómez, Roberto},
  title = {Modelling forest dynamics using integral projection models and repeat lidar},
  journal = {Remote Sensing in Ecology and Conservation},
  year = {2026},
  doi = {10.1002/rse2.70050},
  url = {https://doi.org/10.1002/rse2.70050}
}