PS 54-147 - Using δ15N of Chironomidae to help assess lake condition and possible stressors in EPA’s National Lakes Assessment

Wednesday, August 8, 2012
Exhibit Hall, Oregon Convention Center
J. Renée Brooks1, Jana E. Compton2, Alan T. Herlihy3, Daniel J. Sobota4, John L. Stoddard1 and Marc Weber1, (1)Western Ecology Division, NHEERL, US EPA, Corvallis, OR, (2)US EPA, NHEERL, Western Ecology Division, Corvallis, OR, (3)Fisheries and Wildlife, Oregon State University, Corvallis, OR, (4)In residence at the Western Ecology Division, US EPA, National Research Council Postdoctoral Fellow, Corvallis, OR
Background/Question/Methods

As interest in continental-scale ecology increases to address large-scale ecological problems, ecologists need indicators of complex processes that can be collected quickly at many sites across large areas. We are exploring the utility of stable isotopes from basal food chain organisms in providing information about nitrogen sources and processing at large scales within EPA’s water quality monitoring program.  EPA has implemented the National Aquatic Resource Surveys, which use a probabilistic survey design to monitor 1000-2000 sites across the nation per water body type (Lake, River/Stream, Estuary, Wetland).  While EPA measures many parameters during the one-day site visits, data on complex processes such as denitrification cannot be measured with such limited visit times.  We are exploring the potential for δ15N measured in a family of insects, Chironomidae, which occupies several functional feeding groups in aquatic ecosystems to help classify lakes based on likely sources of or processes that affect nitrogen (N).  In 2007, EPA conducted the National Lakes Assessment (NLA) on 1000 lakes, collecting composite benthic invertebrate samples from the littoral zone at 10 locations around each lake shoreline.  After samples were counted and identified for biodiversity assessments, chironomids were separated, and then analyzed for δ15N.

Results/Conclusions

Chironomid δ15N values varied from -2 to 20 ‰ with a mean of 5.7 ‰ and were significantly higher in lakes with high nutrient concentrations.  Since δ15N values can vary from both changes in N source (e.g. fertilizer vs. manure) and from N processing such as denitrification, we cannot determine a unique cause of δ15N enrichment.  Instead, we used a decision tree approach to categorize lakes for likely N sources and whether denitrification is an important process in watershed N dynamics.  Lakes with relatively high fertilizer loading (>10 kg/ha/yr) in the watershed generally had higher chironomid δ15N values suggesting higher nitrogen processing.  We found that lakes with atmospheric nitrogen as their dominant loading source had low chironomid δ15N values resembling the low δ15N value of atmospheric deposition.  For lakes with sewage or manure as the dominant N source in the watershed, chironomid δ15N values did not vary with watershed loading levels, and with a mean of 5.7 ‰, they did not reflect these relatively enriched δ15N sources.  This decision tree approach in conjunction with other NLA data, chironomid δ15N values are promising to be highly useful indicators of denitrification and attributing N sources in national water quality monitoring efforts.