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Browsing Biology by Subject "boosted regression tree (BRT) analysis"
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Item Species traits predict the aryl hydrocarbon receptor 1 (AHR1) subtypes responsible for dioxin sensitivity in birds(Nature Portfolio, 2020) Bianchini, Kristin; Morrissey, ChristyDifferences in avian sensitivity to dioxin-like compounds (DLCs) are directly attributable to the identities of amino acids at two sites within the ligand binding domain (LBD) of the aryl hydrocarbon receptor 1 (AHR1). Recent work suggests that by influencing avian exposure to naturally occurring dioxins, differences in diet, habitat, and migration may have influenced the evolution of three AHR1 LBD genotypes in birds: type 1 (high sensitivity), type 2 (moderate sensitivity), and type 3 (low sensitivity). Using a boosted regression tree (BRT) analysis, we built on previous work by examining the relationship between a comprehensive set of 17 species traits, phylogeny, and the AHR1 LBD across 89 avian species. The 17 traits explained a combined 74% of the model deviance, while phylogenetic relatedness explained only 26%. The strongest predictors of AHR1 LBD were incubation period and habitat type. We found that type 3 birds tended to occupy aquatic habitats, and, uniquely, we also found that type 3 birds tended to have slower developmental rates. We speculate that this reflects higher evolutionary exposure to naturally occurring dioxins in waterbirds and species with K-selected life histories. This study highlights the value of trait-based approaches in helping to understand differing avian species sensitivities to environmental contaminants.