PREDICTING NITROGEN REMOVAL IN AGRICULTURAL WETLAND BUFFERS USING TRAITS OF THE PLANT COMMUNITY

Microbial denitrification is a critical ecosystem service in areas that receive high inputs of nitrogen from agricultural activity. Inputs of nitrogen can amplify production of algae in downstream aquatic ecosystems, leading to hypoxia and associated consequences for aquatic wildlife. Wetland ecosystems tend to support high rates of denitrification and provide value to the landscape by removing nitrogen from surface and subsurface agricultural run-off, thereby improving local water quality. However, predicting patterns of denitrification, as well as the value of various wetlands in terms of the amount of nitrogen they can potentially remove, remains a significant problem in the field of ecology. Here we propose a framework wherein we use easily observable/measurable traits of the wetland plant community to predict soil characteristics and rates of microbial denitrification in wetland soils. Such a framework would allow managers to assess the potential for wetland buffers to remove nutrients from agriculture run-off.

We expect that soils with greater organic carbon content, and wetland plant communities with greater aboveground and belowground growth, will support higher rates of denitrification. We have initiated a study in a multispecies emergent wetland plant community located at the William H. Miner Agricultural Institute (Chazy, NY). The wetland is adjacent to a dairy-cow calving field with a likely gradient of dairy-cow effluent downslope into the wetland. We established permanent plots at 5 m intervals on 4 replicate transects along this gradient. At each position on the transects, we identified plants to species and quantified total cover of each species using 0.25 m² quadrats. We extracted two sediment cores. One core was used to measure total belowground biomass of the plant community, and one was used to quantify soil density, moisture, organic content, and extractable nutrient content. We will use these data construct predictive models of nitrogen removal, which we plan to test with field measurements of extractable nutrient content and assays of microbial denitrification activity during the spring and summer.