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Week 1: Spatial Thinking in Biodiversity Science

Introductory Business

  • Review syllabus
  • Let's generate an acceptable use of AI policy for ourselves.

Core Questions

  • Why does geography matter in ecology and evolution?
  • How do spatial scale, extent, and grain shape biodiversity inference?
  • What is the difference between spatial and non-spatial data?
  • What does a reproducible spatial biodiversity workflow require?

Concepts

  • Spatial scales and extent.
  • Spatial grain versus extent.
  • Point, polygon, and raster representations.
  • Geographic coordinates.
  • Spatial versus non-spatial data.
  • Reproducible computational workflows.

Python Tools

  • Jupyter.
  • NumPy.
  • pandas.
  • GeoPandas.
  • matplotlib.

Applied Lab

Start with a simple dataset containing species, latitude, longitude, elevation, and site. Students create a basic map, species-specific maps, sampling-density maps, histograms of latitude and elevation, and a species-by-site matrix.

Deliverable

Submit a reproducible notebook with the first biodiversity maps and a short project idea memo identifying a candidate study system, spatial question, response data, and possible environmental predictors.