First you get the money, then you get the power: Comparing the cost and power of monitoring programs to detect changes in occupancy of a threatened marsupial predator

Abstract Ecological monitoring is crucial for tracking changes in the status of species over time. However, ensuring that monitoring programs possess adequate statistical power—capacity to detect changes in populations with a high level of confidence—remains a challenge for many wildlife managers gl...

Full description

Bibliographic Details
Main Authors: Harry A. Moore, Judy A. Dunlop, Hayley M. Geyle, Leanne Greenwood, Dale G. Nimmo
Format: Article
Language:English
Published: Wiley 2023-02-01
Series:Conservation Science and Practice
Subjects:
Online Access:https://doi.org/10.1111/csp2.12881
Description
Summary:Abstract Ecological monitoring is crucial for tracking changes in the status of species over time. However, ensuring that monitoring programs possess adequate statistical power—capacity to detect changes in populations with a high level of confidence—remains a challenge for many wildlife managers globally. While new monitoring technologies potentially offer cost effective solutions to this problem, transitioning to these methods requires careful calibration with existing techniques, such that differences in power and cost can be measured and assessed accurately. Here, we compare new (camera traps) and conventional (live trapping) survey methods in terms of cost and statistical power in tracking occupancy declines in an endangered marsupial predator, the northern quoll (Dasyurus hallucatus). We show that camera trap monitoring designs can detect northern quoll occupancy declines of 30%, 50%, and 80% at reduced cost when compared to live trap designs, without compromising statistical power. Overall, we find support for the cost‐effectiveness of camera traps for species monitoring and its potential to replace existing live trap sampling of species when measuring changes in occupancy. Additionally, we offer a robust framework to compare new monitoring techniques against pre‐existing methods on the basis of statistical power.
ISSN:2578-4854