Choosing a Distance Sampling Method to Count Wildlife: An NPS Guide

Dall's sheep in Alaska, one of the species whose surveys illustrate the guide. NPS.

Estimating wildlife populations means correcting for the animals surveyors miss. Several distance sampling methods do that, but choosing among them can be confusing. This review — a comprehensive guide — explains when to use each, their main assumptions, and how to analyze the data.

The methods

Much of the confusion comes from not being clear which part of the detection process each method addresses. The authors frame their review around those components, so practitioners know what part of the population a survey actually measures.

Tools for practitioners

• Alaska examples: surveys of sheep, muskoxen, bears, landbirds and mountain goats illustrate each concept — and together review much of Alaska's wildlife survey work.
• A decision tree shows when a more complex method (MRDS or TEDS) is worth it.
• Total error: more complex methods can remove more bias but may lose precision, so the guide compares methods by total estimator error.
• Advanced options: informed priors, open-population models and integrated models can reduce error further by drawing on existing information.

Sources

Based on "Using Distance Sampling to Estimate Wildlife Populations," National Park Service, summarizing Joshua H. Schmidt, W. L. Thompson, T. L. Wilson and J. H. Reynolds (2022), "Distance sampling surveys: using components of detection and total error to select among approaches," Wildlife Monographs 210; a work of the United States government in the public domain. The journal cover is left out; the Dall's sheep photograph comes from the NPS article on spatial distance sampling.