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Savannah-forest dynamics: encroachment speed, model inference and spatial simulations.

Yuval R Zelnik1, Ivric Valaire Yatat-Djeumen2,3, Le Bienfaiteur Sagang4,5,6

  • 1Ecology, Swedish University of Agricultural Sciences , Uppsala, Uppsala County, Sweden.

Journal of the Royal Society, Interface
|June 16, 2026
PubMed
Summary
This summary is machine-generated.

Tropical forest expansion into savannahs is accelerating. This study calibrates a reaction-diffusion model using satellite data, revealing faster forest front speeds and providing key biomass dispersal estimates for better vegetation dynamics modeling.

Keywords:
encroachmentforest–savannahfront speedlandscape transformationmodel calibrationspatially explicit modelling

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Area of Science:

  • Ecology
  • Remote Sensing
  • Mathematical Modeling

Background:

  • Forest encroachment into savannahs is a growing concern in tropical regions, particularly in Africa.
  • Process-based, spatially explicit modeling of this phenomenon lags behind empirical observations.

Purpose of the Study:

  • To calibrate a reaction-diffusion model using remotely sensed data to simulate vegetation dynamics in the savannah biome.
  • To estimate woody biomass dispersal coefficients and provide baseline data for understanding savannah changes.

Main Methods:

  • Utilized diachronic Landsat satellite imagery from Central Cameroon (Mpem and Djim National Park) spanning five decades.
  • Calibrated a simple reaction-diffusion model to simulate interactions between grass and woody biomass.
  • Estimated woody biomass dispersal coefficients through model simulations and used historical data for grass dispersal estimates.

Main Results:

  • Observed dramatic forest extension over savannahs in Central Cameroon over the last five decades.
  • Estimated forest front speeds significantly higher (5-7 m yr-1) than previously reported (0.5-2 m yr-1).
  • Successfully demonstrated the utility of broad-scale remote sensing data for calibrating vegetation dynamics models.

Conclusions:

  • Broad-scale remote sensing data is effective for calibrating reaction-diffusion models of savannah vegetation dynamics.
  • Calibrated models serve as a baseline for predicting changes and understanding spatial environmental factor influences.
  • This approach offers a valuable tool for ecological research and conservation planning in savannah ecosystems.