Access, visualization and statistical tools for the analysis of North American butterfly monitoring data

Background/Question/Methods

Citizen-scientists throughout North America perform thousands of surveys each year as part of a continent-wide network of butterfly monitoring programs.  Unlike their European counterparts, these monitoring programs are little known and the growing data resources are rarely used.  This is due to a lack of 1) published papers using these data, 2) tools to search, access, and visualize these critical data sets, and 3) appropriate models for analysis. Through a new NSF-funded project, several new tools will be developed and launched, including a web interface and visualization tool for the only continental-scale butterfly monitoring program in existence, the North American Butterfly Association’s Count Program.  Further research will focus on: a framework for the distribution and visualization for data emerging from regional butterfly monitoring programs; a publically-accessible database of species' traits; and a suite of statistical models to analyze data resulting from the most common types of butterfly monitoring protocols  The three factors that we will focus on for analysis are developing models to account for 1) non-random placement of survey sites, 2) variable detectability based on weather, and 3) the asynchronous emergence schedule of most insects, including butterflies.  Finally, we will work to make these models transferrable between different programs.

Results/Conclusions

A workshop with participants from all major North American butterfly monitoring programs will be held in May 2012 with the goal to establish a framework for the development and deployment of resources for all monitoring programs, which we will describe.   To demonstrate the value of the information in these data, we will present analyses that have shown that species community metrics are similar between the continental and region-based programs, with correlation coefficients for relative abundances of the fifty most common butterfly species in Ohio and Illinois (the two largest and longest-running regional programs) at 0.97 and 0.77 respectively.   Finally, we will use the monarch, one of the most common and well-known butterfly species, as an example to show that year-to-year patterns for single species also shows consistency between programs, and that these data can be used to track large-scale impacts, such as climate, throughout their range.