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1 October 2012 Large-Scale Monitoring of Shorebird Populations using Count Data and N-Mixture Models: Black Oystercatcher (Haematopus bachmani) Surveys by Land and Sea
James E. Lyons, J. Andrew Royle, Susan M. Thomas, Elise Elliott-Smith, Joseph R. Evenson, Elizabeth G. Kelly, Ruth L. Milner, David R. Nysewander, Brad A. Andres
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Abstract

Large-scale monitoring of bird populations is often based on count data collected across spatial scales that may include multiple physiographic regions and habitat types. Monitoring at large spatial scales may require multiple survey platforms (e.g., from boats and land when monitoring coastal species) and multiple survey methods. It becomes especially important to explicitly account for detection probability when analyzing count data that have been collected using multiple survey platforms or methods. We evaluated a new analytical framework, N-mixture models, to estimate actual abundance while accounting for multiple detection biases. During May 2006, we made repeated counts of Black Oystercatchers (Haematopus bachmani) from boats in the Puget Sound area of Washington (n = 55 sites) and from land along the coast of Oregon (n = 56 sites). We used a Bayesian analysis of N-mixture models to (1) assess detection probability as a function of environmental and survey covariates and (2) estimate total Black Oystercatcher abundance during the breeding season in the two regions. Probability of detecting individuals during boat-based surveys was 0.75 (95% credible interval: 0.42–0.91) and was not influenced by tidal stage. Detection probability from surveys conducted on foot was 0.68 (0.39–0.90); the latter was not influenced by fog, wind, or number of observers but was ∼35% lower during rain. The estimated population size was 321 birds (262–511) in Washington and 311 (276–382) in Oregon. N-mixture models provide a flexible framework for modeling count data and covariates in large-scale bird monitoring programs designed to understand population change.

©2012 by The American Ornithologists' Union. All rights reserved. Please direct all requests for permission to photocopy or reproduce article content through the University of California Press's Rights and Permissions website, http://www.ucpressjournals.com/reprintInfo.asp.
James E. Lyons, J. Andrew Royle, Susan M. Thomas, Elise Elliott-Smith, Joseph R. Evenson, Elizabeth G. Kelly, Ruth L. Milner, David R. Nysewander, and Brad A. Andres "Large-Scale Monitoring of Shorebird Populations using Count Data and N-Mixture Models: Black Oystercatcher (Haematopus bachmani) Surveys by Land and Sea," The Auk 129(4), 645-652, (1 October 2012). https://doi.org/10.1525/auk.2012.11253
Received: 9 November 2011; Accepted: 24 May 2012; Published: 1 October 2012
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KEYWORDS
Bayesian analysis
Black Oystercatcher
detection probability
Haematopus bachmani
Hierarchical model
monitoring
sampling frame
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