Observer error in sampling a rare plant population

Abstract

Background: Estimation of abundance in vegetation sampling involving observers is almost always characterised by observer error, although such error is rarely reported.

Aims: To quantify observer error in population estimation of the rare plant species Physaria filiformis in Missouri, USA.

Methods: The abundance of P. filiformis was estimated within 25-m² plots by six trained observers with varying experience levels over 10 years. Observers assigned plots to six predefined density classes. A total of 477 plots were estimated annually, and actual counts were conducted on ca. 10% of the plots to assess per cent agreement of estimates with counts.

Results: Over a third of the estimates of plant abundance evaluated for accuracy (36.4%) deviated from exhaustive counts. The majority of the misestimates were underestimates by one density class (29.4%). The number and type of misestimates varied systematically with density class.

Conclusions: Observer error could be explained to some degree by variation in population density, but not by experience. It appears that inherent differences exist among observers that cannot be entirely compensated for by experience or training. Observer error in this system represents a systematic bias, and can be compensated for by use of correction factors, which would ideally be both density class-dependent and observer-specific.

Keywords:

• density class
• monitoring
• observer error
• Physaria filiformis
• rare plant sampling

Acknowledgements

Michael DeBacker provided helpful comments on an earlier draft. Laszlo Nagy and an anonymous reviewer contributed many helpful suggestions to the manuscript. Views, statements, findings, conclusions, recommendations and data in this report are those of the author(s) and do not necessarily reflect views and policies of the National Park Service, US Department of the Interior. Mention of trade names or commercial products does not constitute endorsement or recommendation for use by the National Park Service.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Lloyd W. Morrison

Lloyd Morrison is the quantitative ecologist for the Heartland Network of the National Park Service Inventory and Monitoring Program (NPS I&M) and adjunct faculty at Missouri State University. His research interests include biogeography, macroecology and conservation. His publications can be found at http://people.missouristate.edu/LloydMorrison/.

Craig C. Young

Craig Young is an ecologist and exotic plant management team leader with the Heartland Network of the NPS I&M, with an interest in the use of empirical data in land management decisions.