15N reflects wetland nitrogen processing on a national scale as predicted by soil chemistry stoichiometry
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Wetlands provide critical ecosystem services by intercepting and retaining excess non-point nitrogen (N) inputs moving through the environment. However, not all wetlands have the same capacity to store and remove N via denitrification, plant uptake, or storage in soil organic matter. The extent of these N transformations depends on factors such as regional differences in climate, N loading to the wetland watershed, and hydrogeomorphic and biogeochemical properties of the wetland itself. This study aims to identify wetland characteristics that target N removal by processing within wetlands as indicated by d15N values within the top 10 cm of wetland soils. In 2016, the US Environmental Protection Agency’s National Wetland Condition Assessment (NWCA) collected soil samples from ~1000 wetlands across the conterminous United States (US) in addition to a range of chemical, physical, and biological variables. Stable N isotope ratios (d15N) were measured on soil cores because we expected them to integrate signals from ecosystem N sources and N transformations over time. Using generalized additive models, we tested the influence of other wetland variables across climate, in situ wetland characteristics, and catchment land use, hydrology and inputs on soil d15N values. The primary driver of the d15N values was in-situ soil chemistry that captures the pH and stoichiometric ratio of C:N associated with denitrification, explaining ~ 50% of the overall variance. Other factors such as N inputs and sources entering the wetland were far less important than the inherent soil chemistry, revealing the surprising result that wetland soils preserve a historic N processing signal largely independent of recent N loading. We developed a predictive model of wetland in-situ N processing that can be used to identify wetlands with strong N processing and removal capacity. Excess N in US waters leads to ecosystem risks such as eutrophication, biodiversity losses, and more. Therefore, identifying wetlands that are efficient at processing non-point N pollution is a critical step to inform nutrient reduction strategies at watershed scales.