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Related Experiment Video

Updated: May 9, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)
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How can model comparison help improving species distribution models?

Emmanuel Stephan Gritti1, Cédric Gaucherel, Maria-Veronica Crespo-Perez

  • 1CEFE, UMR 5175 CNRS/Université Montpellier II, 1919, Route de Mende, 34293, Montpellier, France. emmanuel.gritti@supagro.inra.fr

Plos One
|July 23, 2013
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Summary

Comparing species distribution models (SDMs) for European trees reveals that phenology and abiotic stress resistance, not growth efficiency, primarily determine range limits. Process-based models show promise for accurate climate change impact projections.

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Area of Science:

  • Ecology
  • Climate Change Biology
  • Computational Biology

Background:

  • Correlative species distribution models (SDMs) are widely used for climate change impact projections, but their reliability is increasingly questioned.
  • There is a growing need for process-based SDMs that explicitly model species' physiological responses to environmental conditions.
  • Understanding species' range shifts is crucial for biodiversity conservation and ecosystem service management under climate change.

Purpose of the Study:

  • To compare the performance of three different SDMs (STASH, LPJ, PHENOFIT) along the correlative-to-process-based continuum.
  • To evaluate the accuracy of these models in simulating the current distribution of three major European tree species (Fagus sylvatica, Quercus robur, Pinus sylvestris).
  • To identify the key ecological processes driving species range limits in response to climate change.

Main Methods:

  • Utilized three distinct SDMs: STASH (correlative), LPJ (hybrid), and PHENOFIT (process-based).
  • Employed an innovative comparison map profile method for local and multi-scale consistency analysis of model simulations.
  • Focused on the current distribution of Fagus sylvatica, Quercus robur, and Pinus sylvestris across Europe.

Main Results:

  • All three models accurately simulated the current distribution of the studied European tree species.
  • The process-based model (PHENOFIT) performed comparably to the correlative model (STASH), despite not being fitted to observed distributions.
  • Species range limits at the European scale appear to be primarily determined by establishment and survival influenced by phenology and abiotic stress resistance, rather than growth efficiency.

Conclusions:

  • Process-based and hybrid SDMs offer reliable alternatives to correlative models for projecting species distributions under climate change.
  • Phenology and resistance to abiotic stress are critical factors controlling European tree species' range limits.
  • Future improvements in process-based models should incorporate more realistic representations of species' resistance to environmental stressors, particularly water stress.