High-Resolution, Long-Term Trends in Relative Abundance from Spatial Modeling of Continent-Wide Bird Counts

Abstract

Continent-wide bird counts by community volunteers provide valuable information about the conservation needs of many bird species. The statistical modeling techniques commonly used to analyze these counts provide robust long-term trend estimates from heterogeneous community science data at regional, national, and continental scales. Here we present a novel modeling framework that increases the spatial resolution of trend estimates, and reduces the computational burden of trend estimation, each by an order of magnitude. We demonstrate the approach with data for the American Robin (Turdus migratorius) from Audubon Christmas Bird Counts conducted between 1966 and 2017, and show that aggregate regional trend estimates from the proposed method align well with those from the current standard method. Thus, it appears that the proposed technique can provide reasonable large-scale trend estimates for users concerned with general patterns, while also providing higher resolution estimates for others examining correlates of abundance trends at finer spatial scales.