An Arctic-Breeding Bird Survey on the Northwestern Ungava Peninsula, Quebec, Canada

ARCTIC ◽  
2009 ◽  
Vol 59 (3) ◽  
Author(s):  
Brad A. Andres
Keyword(s):  
Breeding Bird Survey ◽  
Breeding Bird ◽  
Bird Survey

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 A Breeding Bird Survey on Uncultivated Grassland at Regina

Blue Jay ◽  
1966 ◽  
Vol 24 (3) ◽  
Author(s):  
Hugh Smith ◽  
Joyce Smith
Keyword(s):  
Breeding Bird Survey ◽  
Breeding Bird ◽  
Bird Survey

scholarly journals North American Breeding Bird Survey status and trend estimates to inform a wide-range of conservation needs, using a flexible Bayesian hierarchical generalized additive model

2020 ◽  
Author(s):  
Adam C. Smith ◽  
Brandon P.M. Edwards
Keyword(s):  
Statistical Model ◽  
North American ◽  
Breeding Bird Survey ◽  
Breeding Bird ◽  
Bayesian Hierarchical ◽  
The North ◽  
Smooth Component ◽  
Bird Survey ◽  
Wide Range ◽  
Predictive Fit

ABSTRACTThe status and trend estimates derived from the North American Breeding Bird Survey (BBS), are critical sources of information for bird conservation. However, the estimates are partly dependent on the statistical model used. Therefore, multiple models are useful because not all of the varied uses of these estimates (e.g. inferences about long-term change, annual fluctuations, population cycles, recovery of once declining populations) are supported equally well by a single statistical model. Here we describe Bayesian hierarchical generalized additive models (GAM) for the BBS, which share information on the pattern of population change across a species’ range. We demonstrate the models and their benefits using data a selection of species; and we run a full cross-validation of the GAMs against two other models to compare predictive fit. The GAMs have better predictive fit than the standard model for all species studied here, and comparable predictive fit to an alternative first difference model. In addition, one version of the GAM described here (GAMYE) estimates a population trajectory that can be decomposed into a smooth component and the annual fluctuations around that smooth. This decomposition allows trend estimates based only on the smooth component, which are more stable between years and are therefore particularly useful for trend-based status assessments, such as those by the IUCN. It also allows for the easy customization of the model to incorporate covariates that influence the smooth component separately from those that influence annual fluctuations (e.g., climate cycles vs annual precipitation). For these reasons and more, this GAMYE model is a particularly useful model for the BBS-based status and trend estimates.LAY SUMMARYThe status and trend estimates derived from the North American Breeding Bird Survey are critical sources of information for bird conservation, but they are partly dependent on the statistical model used.We describe a model to estimate population status and trends from the North American Breeding Bird Survey data, using a Bayesian hierarchical generalized additive mixed-model that allows for flexible population trajectories and shares information on population change across a species’ range.The model generates estimates that are broadly useful for a wide range of common conservation applications, such as IUCN status assessments based on trends or changes in the rates of decline for species of concern; and the estimates have better or similar predictive accuracy to other models., and

scholarly journals Use of North American Breeding Bird Survey data in avian conservation assessments

The Condor ◽  
2017 ◽  
Vol 119 (3) ◽  
pp. 594-606 ◽  
Author(s):  
Kenneth V. Rosenberg ◽  
Peter J. Blancher ◽  
Jessica C. Stanton ◽  
Arvind O. Panjabi
Keyword(s):  
Survey Data ◽  
North American ◽  
Breeding Bird Survey ◽  
Avian Conservation ◽  
Breeding Bird ◽  
Bird Survey ◽  
Conservation Assessments
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