Bird populations have been declining for decades, with three billion birds lost over the last 50 years. Understanding the drivers of these loses is a monumental task because most bird species have ranges that span large expanses across a mosaic of land uses. This task is further complicated by migratory species which spend the annual cycle moving across even larger areas and borders with different conservation values and practices in place. Finally, longitudinal data allowing scientists to monitor long-term trends require great effort and costs that can be limiting.
Community science data collection is being used more and more to overcome these limitations. These data are unique in that people from across a species range and annual cycle, and over many years, are able to submit observations then used by scientists to study bird populations. However, community science data are often biased and have little-to-no sampling design that can lead to all sorts of data quality issues. Bird Conservancy of the Rockies’ Integrated Monitoring in Bird Conservation Regions (IMBCR) program provides high-quality count data from rigorous sampling designs. However, these data are typically only available for a portion of a species’ range and across shorter periods of time. Combining the strengths of both of these data sets could overcome their individual shortcomings.
An IMBCR Field Technician gathering data.
Bird Conservancy staff led by Qing Zhao recently published their work which brought this idea to life. They devised a new statistical method that combines high-quality IMBCR data with expansive community science data to create a win-win for bird population monitoring. Using computer simulations, they demonstrated this method is capable of overcoming the limitations of community science data by building on the strengths of IMBCR data to produce high-quality analyses of bird populations and their needs over time.
Baird’s Sparrow. Photo by Rick Bohn.
To test this new method, the research team examined populations of Baird’s Sparrows to better understand their habitat requirements across their full range. Current IMBCR data on Baird’s Sparrows is limited to parts of the U.S. However, the team combined IMBCR data with North American Breeding Bird Survey (BBS) and eBird data collected by community scientists to track their populations over time and provide a more comprehensive understanding of biotic and abiotic requirements across their entire range. Model results reveal that Baird’s Sparrow population growth is influenced by mean maximum monthly summer ambient temperatures. This relationship was much less clear when using IMBCR data alone. Model results also demonstrated their strong reliance on the presence of large, intact grassland, supporting the need for grassland conservation for this species.
The strength of this new method is in the rigor of IMBCR data and the expansiveness of community science data. Combined, these data sets help us understand populations of bird species across their full range and over large expanses of time. This ability will help to identify important areas for conservation using conservation strategies that endure across time and space, ensuring we are working effectively to restore populations of birds across the continent.
So the next time you submit an ebird checklist during your bird outing remember that you are contributing to the recovery of birds and the science community at large. You can read the whole scientific paper here.
Qing Zhao is a Research Scientist with Bird Conservancy of the Rockies.
