Apr 7, 2020

Improved status and trend estimates from the North American Breeding Bird Survey using a Bayesian hierarchical generalized additive model

bioRxiv
Ka Kit LamDavid Tse

Abstract

The status and trend estimates derived from the North American Breeding Bird Survey (BBS), are critical sources of information for bird conservation. However, many of the varied uses of these estimates are poorly supported by the current standard model. For example, inferences about population recovery require models that are more sensitive to non-linear patterns such as population cycles. In addition, regional status assessments would benefit from models that share information across the species' range. Here we describe Bayesian hierarchical generalized additive models (GAM) that fit these criteria, generating status and trend estimates optimized for many common uses related to conservation assessments. We demonstrate the models and their benefits using data for Barn Swallow (Hirundo rustica), Wood Thrush (Hylocichla mustelina), Carolina Wren (Thryothorus ludovicianus), and a selection of other species, and we run a full cross-validation of the GAMs against two other BBS models to compare predictive fit. The GAMs have better predictive fit than the standard model for all species studied here, and better or comparable predictive fit compared to an alternative first difference model. In addition, one version of the GAM described...Continue Reading

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Research Study
Molecular Assembly/Self Assembly

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