The Monitoring Avian Productivity and Survivorship (MAPS) program has been tracking continental trends in bird populations since 1989.  Run by the Institute for Bird Populations, MAPS consists of a network of banding stations throughout the U.S. and Canada.  Data collected from MAPS stations are crucial for understanding how habitat loss, climate change, and other large-scale factors affect the abundance and distribution of birds, and are used to inform policy and conservation actions. Onondaga Audubon Society (OAS) and SUNY-ESF's Department of Environmental and Forest Biology (EFB) have jointly re-established a MAPS station at Baltimore Woods Nature Center in Marcellus, NY that has been inactive since the early 1990's.

​The effort has been led by OAS President Alison Kocek and OAS Board Member Michelle Stantial, both of whom are Ph.D. candidates in the Cohen lab.   On weekends throughout the summer, Alison and Michelle, with a team of volunteers that includes Dr. Cohen, work from sunrise to noon banding and taking measurements on birds at the Nature Center.   They will report their data to MAPS, where it will be incorporated into statistical models of survival and reproductive success.   In this way, we hope to understand how bird populations at Baltimore woods will change over time, and to contribute to scientists' understanding of how we might reverse declines that are currently observed for many of our avian species across North America.

Breeding bird atlases are unique datasets that rely on volunteers to collect information about where birds are found across entire states at a very fine scale. New York, for example, contains over 5,000 individual atlas blocks with a record of every species that was observed there in the early 1980s and again in the early 2000s. As a result, Atlas data can offer powerful insights into the factors that shape species distributions over time. One problem with Atlas data, however, is that they haven’t been collected in a way that makes it easy to account for imperfect detection. When a volunteer is out in the field looking for birds, inevitably a few species will be missed due to secretive behavior, misidentification, or even poor weather conditions. Failure to account for imperfect detection of birds that are actually present means we will underestimate how widespread those species are and potentially draw inaccurate conclusions about the factors that influence their distributions. Typically, researchers estimate detection probability by visiting the same site multiple times and recording how often each species is observed. Atlas data does not include information about how often a species was detected in each block. It does, however, include an estimate of effort, or the amount of time spent surveying. Ph.D. student Michelle Peach and coauthors have published a method in Journal of Applied Ecology to account for imperfect detection with Atlas data using effort as a surrogate for repeated surveys and covariates, such as habitat availability, to estimate whether a block was truly occupied or not. The approach was applied to model Canada warbler distributions in New York over a 20 year period and demonstrated a potential decline that wasn’t seen using other methods. It was also found that declines were particularly high in areas where Canada warblers were initially more likely to be found. This approach thus makes it possible to both identify declining species and more effectively target conservation efforts.