About
Tidy Ecology is a collection of R and QGIS workflows for working with biodiversity data, written for the people who actually have to run the analysis.
A lot of ecological work falls into an awkward gap. It’s too specialised for general data-science tutorials, but too code-heavy for most ecology courses. The aim here is to fill that gap with reproducible workflows: getting field and occurrence data in, cleaning it, and taking it through to diversity indices, ordination, and species distribution models. There are spatial recipes in QGIS for rasters and protected-area layers, notes on where biodiversity data actually comes from (GBIF, iNaturalist and the like), and a fair amount of honesty about the parts that tend to break.
It’s aimed at field biologists, ecology students, and conservation practitioners who want to do more of their own analysis without turning into full-time programmers. If you can already run a script but tend to freeze when something throws an error, the tutorials here are for you.
How the tutorials are checked
Every tutorial is a single source file, and the figures and the numbers in the text are produced by code that runs when the site is built, not typed in afterwards. Where a tutorial simulates data, the simulation is seeded, so running it again gives the same numbers. Before a tutorial is published the code is pulled back out of that file and run on its own, and every sentence carrying a number is read against what the code actually printed: a qualifier like “close to” or “most of” has to be true of the value beside it, not of the value the author expected.
References are checked rather than collected. Each DOI is looked up in two independent metadata services, Crossref and OpenAlex, and the record that comes back has to be the work being cited. A plausible DOI that resolves to a different paper is the specific failure this catches, and it has caught some. Links between tutorials are audited against the real list of pages across the whole site, so a mistyped link cannot sit there quietly returning a 404.
None of this makes a tutorial correct. It makes it reproducible, and it means that a number which is wrong is wrong somewhere you can find.
Corrections
If a published tutorial turns out to be wrong in substance, it is corrected in place and the post carries the date of the change with a line saying what changed. Fixing a typo or a broken link is not worth a note; changing a number, a conclusion, or a piece of advice is.
Spotted a mistake, or want a topic covered? The contact page is the place.