Measurements of Canada Goose Morphology: Sources of Error and Effects on Classification of Subspecies
| Autor: | Lawrence E. Vine, William E. Wheeler, Paul W. Rasmussen, Timothy J. Moser, Donald H. Rusch, Brian D. Sullivan |
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| Rok vydání: | 2001 |
| Předmět: |
Measurement method
education.field_of_study Observational error Ecology biology Population Subspecies biology.organism_classification Anatidae Branta Observer Bias Statistics General Earth and Planetary Sciences Sources of error education Ecology Evolution Behavior and Systematics Nature and Landscape Conservation General Environmental Science Mathematics |
| Zdroj: | The Journal of Wildlife Management. 65:716 |
| ISSN: | 0022-541X |
| DOI: | 10.2307/3803022 |
| Popis: | Subspecific classification of Canada geese (Branta canadensis) based on morphological measurements serves many management and research functions, such as determining harvest pressure on subspecies or estimating the population composition of wintering flocks. Despite this widespread use, the magnitude of error involved in such measurements, the effect of observer experience on measurement error, and the effect of measurement error on classification are not known. To investigate these issues, we carried out a study on Canada geese harvested in Wisconsin involving replicated measurements by observers of different experience levels. Measurement error for experienced observers was half as large as that for inexperienced observers (6-10% vs. 13-21% of all variability for all structures except the tarsus). Experienced observers measured the skull and culmen most precisely, the tarsus least precisely. Consistent differences among observers (observer bias) that could bias classification were smaller for experienced observers. We used reference data and distributional assumptions to estimate that without observer bias or other forms of measurement error, 8-9% of geese measured would be misclassified because of actual size overlap between subspecies. Without observer bias, remaining measurement error among experienced and inexperienced observers increased misclassification by 1% and 2%, respectively. Observer bias can increase misclassification substantially beyond these levels, depending on the magnitude and direction of observer bias and the prevalence of the subspecies. Misclassification of geese resulted in overestimating the prevalence of the less common subspecies in mixed populations, which may be important in developing management strategies. We recommend training observers and standardizing measurement procedures primarily to reduce observer bias that leads to biased classification of geese, and secondarily to reduce other components of measurement error. |
| Databáze: | OpenAIRE |
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