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Media type:
E-Article
Title:
Refining the Use of Point Counts for Winter Studies of Individual Species
Contributor:
Gutzwiller, Kevin J.
imprint:
Wilson Ornithological Society, 1993
Published in:The Wilson Bulletin
Language:
English
ISSN:
0043-5643
Origination:
Footnote:
Description:
<p>I conducted 167 unlimited-distance point counts in central Texas in February 1987 and January and February 1988 to determine how count duration, time of day, site type (woodland perimeter, woodland interior), winter date (before or after 14 February), and year were related to the winter detection probabilities of 13 species. Within a species, differences in detection probability among the levels of a factor helped identify the environmental (e.g., site type) or methodological (e.g., count duration) conditions under which one could maximize both detectability and point-count sample size. Among the levels of time of day, the detectabilities of each of several species were comparable. Thus, instead of restricting censuses to the morning hours as is common in breeding-season studies, researchers could sample and obtain comparable rates of detection for one of these species throughout the day. An important benefit would be larger point-count sample sizes, which would generally improve the statistical power of subsequent analyses. Similarly, detection probabilities did not differ among 5-, 10-, and 15-min counts for several species; one could capitalize on this similarity by using 5-min counts to maximize the number of counts during a fixed time interval. Comparisons of detection probabilities among the levels of significant interaction effects demonstrated that a variety of levels, involving combinations of main-effect levels, yielded like detection probabilities. Such combinations could be scheduled to maximize simultaneously both point-count sample size and detection probabilities. Because additional point counts and improved detectability would tend to yield data that are more accurate, these strategies are likely to increase the accuracy of ecological inferences based on winter point-count data.</p>