We report on efforts to integrate curricular activities with research on diversity and forest above-ground net primary productivity (ANPP), carbon (C) stocks, net soil CO2 efflux rate (NCER), and fine root production (FRP) in a temperate rainforest permanent plot network near the Puget Sound, Washington, USA. Measurements were conducted with four 16-credit courses, involving more than 200 students, at the Evergreen State College. We used several models to examine efficacy of integrating ecosystem measurements with high numbers of students. Models we used included using student measurements as analytical replicates, detailed one-on-one instruction with a small number of students, having student groups error check and re-collect data, peer review of student work, and community-based ownership of data and research outcomes.
Results/Conclusions
Using student work on a 30-year-old permanent plot network, and another 3-year-old 44-plot permanent plot network (http://academic.evergreen.edu/projects/EEON/), we estimate changes in C stocks to be approximately 3.0 tons C ha-1 y-1. Carbon flux and pool estimates agree with estimates derived from forest modeling software (FVS), and data from nearby experimental forests. We find interesting positive relationships between forest tree diversity and ANPP and NCER that are complimentary to studies on diversity and ecosystem function. While some measures like ANPP and carbon stocks were easily integrated with high numbers of students, measures involving complex technology such as minirhizotron cameras (FRP) and infra-red gas analyzers (NCER) were more suited to one-on-one instruction. However, analysis of minirhizotron images was surprisingly effective when integrated with class instruction on GIS tools. We suggest that this work indicates that robust and nuanced estimates of C-flux can be produced from even large student groups. Far from being inconvenienced by integrating ecosystem-level research with curriculum, ecosystem scientists can use these experiences to simultaneously teach about the realities of conducting field science, and collect important data reliant on multiple manual measurements. Related studies suggest that fine root distribution is lower under large woody debris, leaf decomposition occurs faster on large woody debris than on the forest floor, and a key fungal endophyte decelerates leaf decomposition of big-leaf maple (Acer macrophyllum) in streams. These additional studies emphasize how involvement of a diverse number of participants increases the chance of discovering nuanced patterns in data, and increases efficacy of rapid generation of large datasets.
