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ESTIMATING POPULATION CHANGE FROM COUNT DATA: APPLICATION TO THE NORTH AMERICAN BREEDING BIRD SURVEY

ESTIMATING POPULATION CHANGE FROM COUNT DATA: APPLICATION TO THE NORTH AMERICAN BREEDING BIRD SURVEY For birds and many other animal taxa, surveys that collect count data form a primary source of information on population change. Because counts are only indices to population size, care must be taken in using them in analyses of population change. Temporal or geographic differences in the proportion of animals counted can be misinterpreted as differences in population size. Therefore, temporally or geographically varying factors that influence the proportion of animals counted must be incorporated as covariables in the analysis of population parameters from count data. We describe the North American Breeding Bird Survey (BBS) for illustration. The BBS is a major, landscape-level survey of birds in North America; it is typical of many count surveys, in that the same sample units (survey routes) are sampled each year, and change is modeled on these routes over time. We identify covariables related to observer ability, the omission of which can bias estimation of population change from BBS data. Controlling for observer effects or other potential sources of confounding requires the specification of models relating counts to population size. We begin with a partial model specification relating expected counts to population sizes; we describe estimators currently in use in relation to this partial specification. Additional assumptions lead to a class of overdispersed multinomial models, for which we describe estimators of population change and procedures for parsimonious model selection. We illustrate the use of overdispersed multinomial models by an application to data for Carolina Wren ( Thryothorus ludovicianus ). http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Ecological Applications Ecological Society of America

ESTIMATING POPULATION CHANGE FROM COUNT DATA: APPLICATION TO THE NORTH AMERICAN BREEDING BIRD SURVEY

Link, William A.; Sauer, John R.
Ecological Applications , Volume 8 (2) – May 1, 1998
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Publisher
Ecological Society of America
Copyright
Copyright © 1998 by the Ecological Society of America
Subject
Articles
ISSN
1051-0761
DOI
10.1890/1051-0761%281998%29008%5B0258:EPCFCD%5D2.0.CO%3B2
Publisher site
See Article on Publisher Site

Abstract

For birds and many other animal taxa, surveys that collect count data form a primary source of information on population change. Because counts are only indices to population size, care must be taken in using them in analyses of population change. Temporal or geographic differences in the proportion of animals counted can be misinterpreted as differences in population size. Therefore, temporally or geographically varying factors that influence the proportion of animals counted must be incorporated as covariables in the analysis of population parameters from count data. We describe the North American Breeding Bird Survey (BBS) for illustration. The BBS is a major, landscape-level survey of birds in North America; it is typical of many count surveys, in that the same sample units (survey routes) are sampled each year, and change is modeled on these routes over time. We identify covariables related to observer ability, the omission of which can bias estimation of population change from BBS data. Controlling for observer effects or other potential sources of confounding requires the specification of models relating counts to population size. We begin with a partial model specification relating expected counts to population sizes; we describe estimators currently in use in relation to this partial specification. Additional assumptions lead to a class of overdispersed multinomial models, for which we describe estimators of population change and procedures for parsimonious model selection. We illustrate the use of overdispersed multinomial models by an application to data for Carolina Wren ( Thryothorus ludovicianus ).

Journal

Ecological Applications – Ecological Society of America

Published: May 1, 1998

Keywords: counts ; generalized linear models ; monitoring ; North American Breeding Bird Survey ; surveys ; trends

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