Work

Integrating multiple data sources with species distribution models to estimate the distribution and abundance of northern bobwhite (Colinus virginianus) in the United States

Year: 2025

Type: article

Abstract: Species distribution models (SDMs) are a widely used tool for informing wildlife management and conservation. Integrating multiple broad-scale datasets on species occurrence and abundance in an SDM framework can retain the strengths of each data type and, at least partially, offset their weaknesses. We developed abundance-based, spatially-varying SDMs to predict the distribution of northern bobwhite (Colinus virginianus) across the eastern United States and to assess the environmental drivers of the bobwhite distribution. SDMs were built within a hierarchical Bayesian framework by integrating structured North American Breeding Bird Survey and semi-structured eBird count data. We then used circuit theory to estimate bobwhite connectivity across the range. We found that bobwhite abundance was concentrated in three main regions: southern Texas, the Great/Midwestern Plains, and the southeastern coastal plain. Total abundance across the range was estimated at 5,576,395 (5,237,626 - 5,936,891). Models integrating both datasets performed better than models developed with each dataset individually. Covariate effects on abundance varied by region, though abundance across the range was quadratically related to shrub cover and negatively associated with the number of days of snow cover, intensity of urbanization, and cover of grassland, water, and bare ground. Our study provides an important example of how datasets collected at different spatial scales under different observation protocols can be integrated in an SDM framework to improve predictive accuracy. Our modeling framework provides region-specific estimates of the drivers of bobwhite abundance and range-wide estimates of abundance and movement potential for guiding both local and range-wide bobwhite management.

Source: Ecological Modelling

DOI: 10.1016/j.ecolmodel.2025.111265