No description available

No description available

Soils constitute the largest sink of terrestrial carbon (C), and urban soils have the potential to provide significant soil C storage. Soils in urbanized landscapes experience a multitude of human alterations, such as compaction and management subsidies, that impact soil C dynamics. While field studies may provide data on urban soil C storage, modeling soil C dynamics under various human impact scenarios will provide a basis for identifying drivers of urban soil C dynamics and for predicting the potential for these highly altered soils to store C over time intervals not typically amenable to empirical validation. The goal of this study was to model soil C dynamics in residential lawns using CENTURY, a dynamic mechanistic model, to determine whether drivers of soil C dynamics in natural systems (e.g., soil texture) were equally useful for estimating soil C content of highly modified soils in urban residential areas. Without incorporating human impacts, we found no relationship between initial CENTURY model simulations and observed soil C (p > 0.05). Factors that best explained soil C accumulation for the observed soil C (bulk density: r2= 0.30; home age: r2= 0.37; p < 0.01) differed from those found important from the CENTURY model simulations (% sand: r2= 0.72, p < 0.001). Therefore, we conducted a modeling exercise to test whether simulating potential construction disturbance and lawn management practices would improve modeled soil and tree C. We found that incorporating these factors did improve CENTURYs ability to model soil and tree C (p < 0.001). The results from this analysis suggest that incorporating various human disturbances and management practices that occur in urban landscapes into CENTURY model runs will improve its ability to predict urban soil C dynamics, at least within a 100-year time frame. Thus, enhancing our ability to provide recommendations for management and development practices that result in increasing urban soil C storage.

No description available

No description available

No description available

Wave parameters were measured in a Ruppia maritima bed off Bishop’s Head Point in Chesapeake Bay, Maryland in June 2000 when plants were flowering, plant density was 1,270 ± 92 shoots m-2, and seagrasses occupied most of the water column (1 m). Leaves were approximately 1.5 mm wide. A wave gauge (MacroWave, Coastal Leasing) deployed at 1 m depth within the vegetation was used to record pressure data hourly (4,096 points) at a 5Hz frequency over 14 days (non-storm conditions). The data was Fast-Fourier transformed using Wizard (Coastal Leasing) to obtain wave parameters. Significant wave height was then plotted as a function of water depth, i.e. tidal height. Note that seagrasses occupied most of the water column at all times. During low tide, plant biomass is compressed into a smaller volume of water leading to lower wave heights. Error bars represent variability found in the 24 burst recorded daily for 14 days.