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Abstract Freshwater wetlands process large amounts of nutrients originating from agricultural fields. Yet, these systems also have the potential to produce substantial amounts of nitrous oxide (N2O) and methane (CH4), both potent greenhouse gasses (GHGs). Agricultural land use alters delivery of nutrients and carbon (C) to downstream wetlands, and changing climate is altering hydroperiods. These drivers modulate wetland microbial processes responsible for GHG production including denitrification and methanogenesis. Studies have correlated GHGs to C quantity and nutrients independently; fewer studies identify how nutrients and C composition interact to modulate GHG concentrations in wetlands. In wetlands located in Indiana, USA, we studied how CH4, N2O, and carbon dioxide (CO2) correlated to C quantity and composition, nutrient concentrations, size, hydrology, and surrounding agricultural land use. CH4production was correlated to dissolved organic carbon (DOC) concentrations and composition using UV‐Vis spectroscopy. CH4concentrations were positively correlated to spectral slope from 275 to 295 nm, an indicator of autochthonous primary production, and negatively correlated to humification index. N2O concentrations positively correlated to total dissolved nitrogen and humification index (HIX). CH4concentrations were highest in the large wetland with negligible canopy cover, dense macrophytes and algae, and high concentrations of autochthonous‐like DOC. Thus, we suspect phototrophic methanogenesis is an important driver of CH4variation across systems. Concentrations of N2O were highest in the agricultural wetland, likely driven by higher NO3−concentrations. Our findings suggest agricultural nutrients strongly shift greenhouse gas production profiles but do not necessarily increase global warming potential of GHGs released by wetlands.
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Contextualizing Wetlands Within a River Network to Assess Nitrate Removal and Inform Watershed Management
Aquatic nitrate removal depends on interactions throughout an interconnected network of lakes, wetlands, and river channels. Herein, we present a network-based model that quantifies nitrate- nitrogen and organic carbon concentrations through a wetland-river network and estimates nitrate export from the watershed. This model dynamically accounts for multiple competing limitations on nitrate removal, explicitly incorporates wetlands in the network, and captures hierarchical network effects and spa- tial interactions. We apply the model to the Le Sueur Basin, a data-rich 2,880 km2 agricultural landscape in southern Minnesota and validate the model using synoptic field measurements during June for years 2013–2015. Using the model, we show that the overall limits to nitrate removal rate via denitrification shift between nitrate concentration, organic carbon availability, and residence time depending on discharge, characteristics of the waterbody, and location in the network. Our model results show that the spatial context of wetland restorations is an important but often overlooked factor because nonlinearities in the system, e.g., deriving from switching of resource limitation on denitrification rate, can lead to unexpected changes in downstream biogeochemistry. Our results demonstrate that reduction of watershed-scale nitrate concentrations and downstream loads in the Le Sueur Basin can be most effectively achieved by increasing water residence time (by slowing the flow) rather than by increasing organic carbon concentrations (which may limit denitrification). This framework can be used toward assessing where and how to restore wetlands for reducing nitrate concentrations and loads from agricultural watersheds.
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- PAR ID:
- 10053918
- Date Published:
- Journal Name:
- Water Resources Research
- ISSN:
- 0043-1397
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1002/2017WR021859
