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Week 6: Species Distribution Modeling

Core Questions

  • What does a species distribution model estimate?
  • How do presence/absence, presence/background, and pseudoabsence designs differ?
  • Why might logistic regression and random forests produce different suitability maps?

Concepts

  • Species-environment relationships.
  • Presence/absence, presence/background, and pseudoabsence data.
  • Logistic regression.
  • Random forests.
  • Habitat suitability.
  • Prediction versus inference.
  • Model evaluation and thresholding.

Python Tools

  • scikit-learn.
  • rasterio or rioxarray.
  • pandas.
  • matplotlib.

Applied Lab

Students combine occurrence data, climate, elevation, and land cover covariates to fit logistic regression and random forest models, then compare predicted suitability rasters.

Deliverable

Submit a first species distribution model with methods, evaluation metrics, prediction maps, and a comparison of model behavior.