The influence of climate and habitat on stable isotope signatures and the isotopic niche of nestling White-headed Woodpeckers (Dryobates albolarvatus).

The majority of landbird species feed their nestlings arthropods and variation in arthropod populations can impact reproductive outcomes in these species. Arthropod populations in turn are influenced by climate because temperature affects survival and reproduction, and larval development. Thus, climate factors have the potential to influence many bird species during their reproductive phases. In this study, we assessed climate factors that impact the diet of nestling White-headed Woodpecker (Dryobates albolarvatus), an at-risk keystone species in much of its range in western North America. To do this, we measured stable isotope signatures (δ13C and δ15N) in 152 nestlings across six years and linked variation in isotopic values to winter (December-February) and spring (June) precipitation and temperature using mixed effects models. We also explored habitat factors that may impact δ13C and δ15N and the relationship between δ15N and nest productivity. Last, we estimated isotopic niche width for nestlings in different watersheds and years using Bayesian standard ellipses, which allowed us to compare dietary niche width and overlap. We found that colder winter temperatures were associated with an increase in δ15N and δ15N levels had a weak positive relationship with nest productivity. We also found that sites with a more diverse tree community were associated with a broader isotopic niche width in nestlings. Our findings suggest that nestling diet is affected by climate, and under future warming climate scenarios, White-headed Woodpecker nestling diet may shift in favor of lower trophic level prey (prey with lower δ15N levels). The impact of such changes on woodpecker populations merits further study.

Inter-comparison of multiple statistically downscaled climate datasets for the Pacific Northwest, USA.

Statistically downscaled climate data have been widely used to explore possible impacts of climate change in various fields of study. Although many studies have focused on characterizing differences in the downscaling methods, few studies have evaluated actual downscaled datasets being distributed publicly. Spatially focusing on the Pacific Northwest, we compare five statistically downscaled climate datasets distributed publicly in the US: ClimateNA, NASA NEX-DCP30, MACAv2-METDATA, MACAv2-LIVNEH and WorldClim. We compare the downscaled projections of climate change, and the associated observational data used as training data for downscaling. We map and quantify the variability among the datasets and characterize the spatio-temporal patterns of agreement and disagreement among the datasets. Pair-wise comparisons of datasets identify the coast and high-elevation areas as areas of disagreement for temperature. For precipitation, high-elevation areas, rainshadows and the dry, eastern portion of the study area have high dissimilarity among the datasets. By spatially aggregating the variability measures into watersheds, we develop guidance for selecting datasets within the Pacific Northwest climate change impact studies.