Biodiversity & Species Data
A map of occurrence records is a map of where people looked.
Species occurrence records are the largest open spatial dataset about life on earth and the most misread. Every record is a presence — there are no absences — the coordinates carry a radius that is usually ignored, and the density of records tracks roads and weekends more closely than it tracks the species. These guides start with what a Darwin Core record contains and how badly it is biased; then download and clean GBIF records, build richness grids and correct them for effort, thin records for modelling, fit and honestly evaluate a distribution model, draw ranges, and join species to protected areas — with the fixes for truncated downloads, records in the ocean, richness maps that are effort maps, models that score well and predict badly, and ranges that cover a quarter of the planet.
Step two is the one that changes how the rest reads: once the bias is measured rather than assumed — an elevenfold over-representation within ten kilometres of a town — every later step is about what the records can and cannot support.
Start here
The cornerstone guide — the whole workflow end to end. Everything after it goes deeper into one part of it.
Step 1 Species Occurrence Data Explained species occurrence data explained Begin the path →The full path, in order
The concepts underneath the work, then each task, then the errors that task produces. Work down, or jump to the step you need.
- Sampling Bias in Occurrence Data Explained sampling bias occurrence data 🧭 Concept
- Coordinate Uncertainty Explained coordinate uncertainty in meters 🧭 Concept
- Species Distribution Models Explained species distribution model explained 🧭 Concept
- Biodiversity Metrics Explained biodiversity metrics richness diversity 🧭 Concept
- Protected Area Data Explained protected area data wdpa 🧭 Concept
- How to download GBIF occurrences in Python download gbif occurrences python ⚙️ How-To
- How to clean species occurrence records clean species occurrence records ⚙️ How-To
- How to build a species richness grid species richness grid python ⚙️ How-To
- How to correct richness for sampling effort rarefaction sampling effort richness ⚙️ How-To
- How to thin occurrence records spatially spatial thinning occurrence records ⚙️ How-To
- How to fit a species distribution model in Python species distribution model python ⚙️ How-To
- How to draw a species range from occurrence points species range map alpha hull ⚙️ How-To
- How to find which species occur in protected areas species in protected areas python ⚙️ How-To
- How to extract climate covariates at occurrence points worldclim covariates at points python ⚙️ How-To
- A GBIF download is missing records gbif download missing records 🔧 Fix
- Occurrence records fall in the ocean occurrence records in the ocean 🔧 Fix
- A richness map is a map of sampling effort richness map sampling effort 🔧 Fix
- A species distribution model scores well and predicts badly sdm auc spatial cross validation 🔧 Fix
- A range polygon has the wrong shape range polygon wrong shape 🔧 Fix
Topics this path covers
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