Illinois Butterfly Monitoring Network

The Illinois Butterfly Monitoring Network engages citizen scientists in the process of collecting quantitative data on butterfly populations. Their goal is to provide data collected with a standardized protocol that allows land managers to evaluate long-term trends in a changing landscape. The Network also offers opportunities for fellowship, mentorship, and continuing education between citizen scientists and professional biologists.

Monitoring Activity Tracker


Coordinator: Taron, Doug
Program Started: 1987
Institutional Affiliation: Peggy Notebaert Nature Museum
Institution Type: Museum
Species Focus: All butterfly species


Protocol Type: Restricted search, Pollard
Data Type(s): Abundance
Survey Focus: Adults
Incidental Data Collected: Weather, Habitat notes
Effort Tracking: Time spent monitoring each route is recorded.
Protocol Notes: A typical pollard protocol but with detections allowed up to 20 ft (~9m) on either side and in front of observer. Route length varies and contains multiple sections divided by habitat. Volunteers must complete at least 6 visits between Jun1 and Aug 7, but higher frequencies and visits outside these dates are encouraged. All butterflies observed during each survey are recorded.

Program Results

Research Spotlight:

Illinois Butterfly Monitoring Network Research Spotlight graphMatteson, K.C., D.J. Taron, E.S. Minor. 2012. Assessing citizen contributions to butterfly monitoring in two large cities. Cons. Biol. 26:557-564. This comparison between species composition trends between Chicago (a transect-based monitoring system) and New York (NABA’s Sightings program, an opportunistic system) showed that using two different approaches to collecting citizen-science data, similar patterns were recovered in two major urban environments. The figure to left shows similar patterns of commonness and rarity in both locations (although Chicago showed more common species overall). Importantly, when controlling for effort, programs recovered similar representation from the local species pool, suggesting that different monitoring methods are able to recover community composition patterns.