Chang et al. (1982) observe a range from 0.00014

for undisturbed forest to 0.10 for cultivated plots as a function of decreased canopy, litter, and residual stand values. Other studies suggest C-factors as high as 0.38 for bare forests in Turkey ( Özhan et al., 2005) and 0.42 for 25% tree cover in Malaysia ( Teh, 2011). There is much uncertainty with applying Everolimus a C-factor for a model that has no sedimentologic calibration. Average annual sheet and rill erosion across the US for forested landcover is estimated at ∼0.91 ton/acre/yr ( Gianessi et al., 1986); this provides a baseline for assessing sediment contributions to Lily Pond from the surrounding forested landscape. Using the minimum and maximum C-values found for forested cover in the literature ( Table 1) model runs suggest sediment output between 0.002 and 0.85 ton/acre/yr ( Table 3); based on this assessment, it appears the estimate using the highest C-value found during a literature search (0.42; Teh, 2011) comes closest to generating an output that resembles a US-wide mean. The erosion predictions, however, fall short of sediment-weight calculations for Lily Pond to varying degrees, click here depending on C-factor used ( Fig. 11). Three contributing factors likely contribute to an underestimation of sediment yield using published C-factors: (1) the volume–weight conversion likely

overestimates sediment weight in the pond rather than underestimates it, (2) the model underestimates total sediment yield as it does not take gullying and other sediment sources into consideration, and (3) urban forests C-X-C chemokine receptor type 7 (CXCR-7) in the region are highly erosive and should be associated by high USLE C-factor values. Certain assumptions are made in generating the sediment volume-to-dry

weight calculations (Fig. 8). Although studied cores do not appear to show much spatial variation in grain-size distribution and organic content (Fig. 6), uncertainties are presented by interpolating information from 8 cores across a surface area of ∼11,530 m2 (Fig. 6). Standard deviations for each of the conversion/correction factors are listed per core in Table 2; combining these metrics provides an idea of the overall error that may be attributed to these sedimentary analyses. While compaction measurements also vary little between core sites and therefore inferably contribute little substantial error to the analysis, a high degree of variance is displayed by the volume–weight conversion factor (Cvw), which increases uncertainty by an order of magnitude ( Table 2). A broad envelope representing the upper and lower bounds produced by this simplistic error-propagation analysis was created using the aforementioned metrics ( Table 2) and applied uniformly across the entire pond area ( Fig. 11).