Model selection for the North American Breeding Bird Survey.
Bayesian analysis
North American Breeding Bird Survey
Watanabe/Akaike information criterion
bayesian predictive information criterion
hierarchical models
leave-one-out cross-validation
model selection
Journal
Ecological applications : a publication of the Ecological Society of America
ISSN: 1051-0761
Titre abrégé: Ecol Appl
Pays: United States
ID NLM: 9889808
Informations de publication
Date de publication:
09 2020
09 2020
Historique:
received:
24
01
2020
accepted:
24
02
2020
pubmed:
24
4
2020
medline:
7
1
2021
entrez:
24
4
2020
Statut:
ppublish
Résumé
The North American Breeding Bird Survey (BBS) provides data that can be used in complex, multiscale analyses of population change, while controlling for scale-specific nuisance factors. Many alternative models can be fit to the data, but most model selection procedures are not appropriate for hierarchical models. Leave-one-out cross-validation (LOOCV), in which relative model fit is assessed by omitting an observation and assessing the prediction of a model fit using the remainder of the data, provides a reasonable approach for assessing models, but is time consuming and not feasible to apply for all observations in large data sets. We report the first large-scale formal model selection for BBS data, applying LOOCV to stratified random samples of observations from BBS data. Our results are for 548 species of North American birds, comparing the fit of four alternative models that differ in year effect structures and in descriptions of extra-Poisson overdispersion. We use a hierarchical model among species to evaluate posterior probabilities that models are best for individual species. Models in which differences in year effects are conditionally independent (D models) were generally favored over models in which year effects are modeled by a slope parameter and a random year effect (S models), and models in which extra-Poisson overdispersion effects are independent and t-distributed (H models) tended to be favored over models where overdispersion was independent and normally distributed. Our conclusions lead us to recommend a change from the conventional S model to D and H models for the vast majority of species (544/548). Comparison of estimated population trends based on the favored model relative to the S model currently used for BBS summaries indicates no consistent differences in estimated trends. Of the 18 species that showed large differences in estimated trends between models, estimated trends from the default S model were more extreme, reflecting the influence of the slope parameter in that model for species that are undergoing large population changes. WAIC, a computationally simpler alternative to LOOCV, does not appear to be a reliable alternative to LOOCV.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e02137Informations de copyright
© 2020 by the Ecological Society of America.
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