Gradients of local species richness may be a function of local habitat cover; regional patterns of land use, land cover and geography; or continental-scale gradients associated with climate.  Breeding birds provide a biodiversity indicator that has been surveyed in a consistent way throughout continental North America and Puerto Rico. Undergraduates find it challenging to evaluate and integrate hypotheses about community patterns at multiple spatial scales. Traditional ecology ‘labs’ focus on hypotheses about local patterns of diversity, tested using locally collected data. In this poster, I report on a problem-based learning module for teaching undergraduate community ecology that evaluates patterns of bird species richness, using archived georeferenced  standardized survey data in the USGS Patuxent Wildlife Research Center Bird Point Count Database, with latitude and patterns of local and regional land-cover and land-use, using the National Land Cover Data and GoogleEarth.  Students are tasked to test hypotheses about local, regional and continental scale patterns of breeding bird species richness using these web-accessible, publicly-available data.

Results/Conclusions

Based on preliminary assessment data of a first test class-cohort, I will report on how completion of the activity affects students’ understandings about the ecological importance of spatial scale, land use and land cover, latitudinal gradients, and species richness patterns. I will report on measures of their engagement and satisfaction with the learning activity, as compared to traditional ecology lab exercises. I will also review conceptual and practical challenges to successfully using this exercise in the undergraduate classroom, and the general challenges to designing successful learning activities that use continental-scale publicly-available data. Finally, I will provide a template and some practical pointers on how to develop learning activities that teach ecological concepts by using multiple sources of web-based data.  This project is a component of an ongoing collaboration between the Ecological Society of America (ESA), the National Ecological Observatory Network (NEON), and the National Center for Ecological Analysis and Synthesis (NCEAS) to improve undergraduate ecology education using large, continental-scale data sets.