scholarly journals Estimation Of Annual Indexes of Abundance and Trend From The American Woodcock Singing-Ground Survey:  Comparison Of 4 Models

2021 ◽  
Author(s):  
John R Sauer ◽  
William A. Link ◽  
Mark E. Seamans ◽  
Rebecca D. Rau
Keyword(s):  
Population Change ◽  
Breeding Bird Survey ◽  
Breeding Bird ◽  
Alternative Models ◽  
American Woodcock ◽  
Ground Survey ◽  
Bird Survey ◽  
Leave One Out ◽  
S Model ◽  
D Model

Status and trends of American Woodcock Scolopax minor populations in the eastern and central US and Canada are monitored via a Singing-ground Survey , conducted just after sunset along roadsides in spring.  Annual analyses of the survey produce estimates of trend and annual indexes of abundance for 25 states and provinces, eastern and central management regions, and survey-wide.  In recent years, a log-linear hierarchical model that defines year effects as random effects in the context of a slope parameter (the S Model) has been used to model population change. Recently, alternative models have been proposed for analysis of Singing-ground Survey data.  Analysis of a similar roadside survey, the North American Breeding Bird Survey , has indicated that alternative models are preferable for almost all species analyzed in the Breeding Bird Survey.  Here, we use leave-one-out cross validation to compare model fit for the present Singing-ground Survey model to fits of three alternative models, including a model that describes population change as the difference in expected counts between successive years (the D model) and two models that include t -distributed extra-Poisson overdispersion effects (H models) as opposed to normally-distributed extra-Poisson overdispersion.   Leave-one-out cross validation results indicate that the D model was favored by the Bayesian predictive information criterion but a pairwise t -test indicated that model D was not significantly better-fitting to Singing-ground Survey data than the S model.  The H models are not preferable to the alternatives with normally-distributed overdispersion.   All models provided generally similar estimates of trend and annual indexes suggesting that, within this model set, choice of model will not lead to alternative conclusions regarding population change.  However, as in Breeding Bird Survey analyses, we note a tendency for S model results to provide slightly more extreme estimates of trend relative to D models.   We recommend use of the D model for future Singing-ground Survey analyses.

scholarly journals Consistency counts: Modeling the effects of a change in protocol on Breeding Bird Survey counts

The Condor ◽  
2019 ◽  
Vol 121 (2) ◽  
Author(s):  
John R Sauer ◽  
William A Link ◽  
David J Ziolkowski ◽  
Keith L Pardieck ◽  
Daniel J Twedt
Keyword(s):  
Counting Process ◽  
Population Change ◽  
Southeastern United States ◽  
Bird Species ◽  
Breeding Bird Survey ◽  
Breeding Bird ◽  
Bird Survey ◽  
Primary Means ◽  
Time Distance ◽  
Log Linear

Abstract Analysis of North American Breeding Bird Survey (BBS) data requires controls for factors that influence detectability of birds along survey routes. Identifying factors that influence the counting process and incorporating them into analyses is a primary means of limiting bias in estimates of population change. Twedt (2015) implemented an alternative counting protocol on operational and nonrandom BBS survey routes in the southeastern United States. Observers on selected routes employed a time–distance protocol in which they recorded birds in 1-min intervals and in 2 distance categories. We hypothesized that processing and recording observations using this time–distance protocol could cause observers to count fewer birds relative to observers using the standard protocol. We used a hierarchical log-linear model with a categorical covariate associated with protocol (standard vs. time–distance) to assess whether use of the time–distance protocol had a measurable effect on counting birds along BBS routes. We applied this model to BBS data from portions of 8 states in which the time–distance protocol was implemented and estimated a protocol effect for 167 bird species. We documented a significant overall effect of the time–distance protocol on observers’ counts of birds. On average, the effect of the time–distance protocol was a 10% decline in counted birds; 80% of species had lower counts when the time–distance protocol was used on a survey route. However, because the time–distance protocol was only used on a small portion of the operational BBS routes and for a limited time, including the covariate for the time–distance protocol data had insignificant effects on analysis of population change. Although the covariate controlled for the effects of the time–distance protocol in BBS data, the results emphasize the importance of standardization as well as a need to track and, if necessary, control in analyses for changes in counting procedures along BBS routes.

scholarly journals Estimating Population Trends With a Linear Model: Technical Comments

The Condor ◽  
2004 ◽  
Vol 106 (2) ◽  
pp. 435-440 ◽  
Author(s):  
John R. Sauer ◽  
William A. Link ◽  
J. Andrew Royle
Keyword(s):  
North American ◽  
Population Change ◽  
Survey Design ◽  
Population Trends ◽  
Breeding Bird Survey ◽  
Breeding Bird ◽  
The North ◽  
Bird Survey ◽  
Substantial Bias ◽  
Modelo Lineal

Abstract Controversy has sometimes arisen over whether there is a need to accommodate the limitations of survey design in estimating population change from the count data collected in bird surveys. Analyses of surveys such as the North American Breeding Bird Survey (BBS) can be quite complex; it is natural to ask if the complexity is necessary, or whether the statisticians have run amok. Bart et al. (2003) propose a very simple analysis involving nothing more complicated than simple linear regression, and contrast their approach with model-based procedures. We review the assumptions implicit to their proposed method, and document that these assumptions are unlikely to be valid for surveys such as the BBS. One fundamental limitation of a purely design-based approach is the absence of controls for factors that influence detection of birds at survey sites. We show that failure to model observer effects in survey data leads to substantial bias in estimation of population trends from BBS data for the 20 species that Bart et al. (2003) used as the basis of their simulations. Finally, we note that the simulations presented in Bart et al. (2003) do not provide a useful evaluation of their proposed method, nor do they provide a valid comparison to the estimating- equations alternative they consider. Estimando Tendencias Poblacionales con un Modelo Lineal: Comentarios Técnicos Resumen. A veces ha surgido controversia sobre la necesidad de considerar las limitantes del diseño de muestreo al estimar cambios poblacionales a partir de datos de conteos de aves. Los análisis de muestreos como el Muestreo de Aves Reproductivas de América del Norte (North American Breeding Bird Survey [BBS]) pueden ser bastante complejos; es natural preguntarse si esta complejidad es necesaria, o si los aná lisis estadísticos son desmedidos. Bart et al. (2003) proponen un análisis muy simple que sólo involucra regresión lineal simple, y contrastan su enfoque con los procedimientos basados en modelos. Nosotros revisamos los supuestos implícitos en el método que ellos proponen y documentamos que estos supuestos no son probablemente válidos para muestreos tales como el BBS. Una limitante fundamental de un enfoque basado exclusivamente en el diseño es la ausencia de controles para factores que influencian la detección de aves en los sitios de muestreo. Mostramos que el hecho de no modelar los efectos del observador en los datos de muestreo lleva a sesgos substanciales en las estimaciones de las tendencias poblacionales de las 20 especies que Bart et al. (2003) usaron como la base de sus simulaciones a partir de datos del BBS. Finalmente, notamos que las simulaciones presentadas en Bart et al. (2003) no brindan una evaluación útil del método que proponen ni tampoco ofrecen una comparación vá lida para la alternativa de estimación de ecuaciones que ellos consideran.

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