Differential Carbon and Nitrogen Controls of Denitrification in Riparian Zones and Streams along an Urban to Exurban Gradient

Hydro-bio-geo-socio-chemical interactions and the sustainability of residential landscapes

Residential landscapes are essential to the sustainability of large areas of the United States. However, spatial and temporal variation across multiple domains complicates developing policies to balance these systems' environmental, economic, and equity dimensions. We conducted multidisciplinary studies in the Baltimore, MD, USA, metropolitan area to identify locations (hotspots) or times (hot moments) with a disproportionate influence on nitrogen export, a widespread environmental concern. Results showed high variation in the inherent vulnerability/sensitivity of individual parcels to cause environmental damage and in the knowledge and practices of individual managers. To the extent that hotspots are the result of management choices by homeowners, there are straightforward approaches to improve outcomes, e.g. fertilizer restrictions and incentives to reduce fertilizer use. If, however, hotspots arise from the configuration and inherent characteristics of parcels and neighborhoods, efforts to improve outcomes may involve more intensive and complex interventions, such as conversion to alternative ecosystem types.

Relationships between denitrification rates and functional gene abundance in a wetland: The roles of single- and multiple-species plant communities

Wetland soil denitrification removes excess inorganic nitrogen (N) and prevents eutrophication in aquatic ecosystems. Wetland plants have been considered the key factors determining the capacity of wetland soil denitrification to remove N pollutants in aquatic ecosystems. However, the influences of various plant communities on wetland soil denitrification remain unknown. In the present study, we measured variations in soil denitrification under different herbaceous plant communities including single Phragmites karka (PK), single Paspalum thunbergia (PT), single Zizania latifolia (ZL), a mixture of Paspalum thunbergia plus Phragmites karka (PTPK), a mixture of Paspalum thunbergia plus Zizania latifolia (PTZL), and bare soil (CK) in the Estuary of Nantiaoxi River, the largest tributary of Qingshan Lake in Hangzhou, China. The soil denitrification rate was significantly higher in the surface (0-10 cm) than the subsurface (10-20 cm) layer. Wetland plant growth increased the soil denitrification rate by significantly increasing the soil water content, nitrate concentration, and ln(nirS) + ln(nirK). A structural equation model (SEM) showed that wetland plants indirectly regulated soil denitrification by altering the aboveground and belowground plant biomass, nitrate concentration, abundances of denitrifying functional genes, and denitrification potential. There was no significant difference in soil denitrification rates among PT, PK and ZL. The soil denitrification rate was significantly lower in PTZL than PTPK. Two-plant communities did not necessarily enhance the denitrification rate compared to single planting, the former had a greater competitiveness on N uptake and consequently reduced the amount of nitrate available for denitrification. As PTPK had the highest denitrification rate, co-planting P. thunbergia and P. karka could effectively improve N removal efficiency and help mitigate eutrophication in adjacent aquatic ecosystems. The results of this investigation provide useful information guiding the selection of appropriate wetland herbaceous plant species for wetland construction and the removal of N pollutants in aquatic ecosystems.

Interacting drivers and their tradeoffs for predicting denitrification potential across a strong urban to rural gradient within heterogeneous landscapes

Denitrification is a significant regulator of nitrogen pollution in diverse landscapes but is difficult to quantify. We examined relationships between denitrification potential and soil and landscape properties to develop a model that predicts denitrification potential at a landscape level. Denitrification potential, ancillary soil variables, and physical landscape attributes were measured at study sites within urban, suburban, and forested environments in the Gwynns Falls watershed in Baltimore, Maryland in a series of studies between 1998 and 2014. Data from these studies were used to develop a statistical model for denitrification potential using a subset of the samples (N = 188). The remaining measurements (N = 150) were used to validate the model. Soil moisture, soil respiration, and total soil nitrogen were the best predictors of denitrification potential (R²_adj = 0.35), and the model was validated by regressing observed vs. predicted values. Our results suggest that soil denitrification potential can be modeled successfully using these three parameters, and that this model performs well across a variety of natural and developed land uses. This model provides a framework for predicting nitrogen dynamics in varying land use contexts. We also outline approaches to develop appropriate landscape-scale proxies for the key model inputs, including soil moisture, respiration, and soil nitrogen.