Quantify geographic sampling bias with {sampbias}

Eukaryota Animalia Chordata Summaries

Human biases play a large role in the data we collect about species. Here we show a simple method to quantify the bias of roads, cities, rivers and airports on species observations of legless lizards in the Northern Territory

Dax Kellie


Dax Kellie


8 August, 2022

Being human plays a big role in the species we observe, when we observe them and where we observe them. In particular, we tend to collect more data in areas that are closer to places we live (or have access to) because there are more opportunities to see species in areas we spend more time in than areas that are far away or inaccessible.

Large, public datasets like the Atlas of Living Australia are especially prone to this sampling bias because they largely reflect opportunistic observations rather than systematic monitoring programs. However, not all species observations are affected equally by these biases, and it’s useful to quantify how biased data are before interpreting them.

Thanks to the sampbias package, we can easily quantify and compare the effects of these biases on our data, specifically whether data are influenced by cities, roads, airports and rivers.

This post expands on a Twitter thread by Dr Ian Brennan to show how sampling bias affects museum records of reptiles. Dr Brennan is currently a Post Doctoral researcher at the Australian National University (ANU). Check out his website to learn more about him and his cool research.

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To begin, we will look at some of Dr Brennan’s favourite reptiles: legless lizards from the genus Delma.