18 research outputs found
Examples showing the density and configuration of the streams mapped in this study (blue; MaxEnt streams, smoothed and connected as in Figure 3B) compared with the NHD streams (black) for (A) an urban area and (B) a rural area.
<p>The background image shows the 2006 NLCD land cover using the standard color scheme: urban (shades of red), forest (green), agriculture (yellow), and water (blue).</p
Modeled vs. NHD stream density metrics for each HUC12 watershed in the study area.
<p>In (A) modeled stream density is compared to NHD stream density, and in (B) modeled channel head density is compared to NHD channel head density. Although there is a strong correlation, modeled streams exhibit many more small streams per unit area, each with its own channel head.</p
Local slope vs. Log<sub>10</sub>(catchment area) for bins of increasing catchment area (black dots) across the entire survey region and for the locations of channel heads (colored dots).
<p>Characteristics of this plot have been discussed previously in the literature [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074819#B21" target="_blank">21</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074819#B53" target="_blank">53</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074819#B64" target="_blank">64</a>], and are covered briefly in the text.</p
Stream length as a function of the log catchment area for each physiographic province (CP = Coastal plain; PD = Piedmont; BR = Blue ridge; RV = Ridge and valley; and AP = Appalachian plateau).
<p>Stream length as a function of the log catchment area for each physiographic province (CP = Coastal plain; PD = Piedmont; BR = Blue ridge; RV = Ridge and valley; and AP = Appalachian plateau).</p
The mean and variance of stream density for HUC12 watersheds by physiographic province (CP = Coastal plain; PD = Piedmont; BR = Blue ridge; RV = Ridge and valley; and AP = Appalachian plateau).
<p>The mean and variance of stream density for HUC12 watersheds by physiographic province (CP = Coastal plain; PD = Piedmont; BR = Blue ridge; RV = Ridge and valley; and AP = Appalachian plateau).</p
Stream density maps for HUC12 watersheds in the study region.
<p>(A) NHD stream density was more uniform and lower than (B) the stream density calculated from MaxEnt after smoothing, connecting discontinuous segments, and merging with NHD. (C) The percent change in stream density highlights the effects of urban areas and other areas with poor quality NHD stream maps. (D) Spatial variation in stream density can be explained in part by differences in geology between physiographic provinces.</p
False positive and false negative predictions, expressed as a percentage of stream observations in the field survey (10,565), for four stream maps: (A) raw MaxEnt results with the province-specific thresholds applied; (B) MaxEnt results after smoothing and connecting discontinuous stream segments; (C) the results in (B) after merging with NHD maps of streams, and (D) the Tuned Ac stream map, which uses a province-specific critical catchment area to define streams.
<p>Methods for each map are described in detail in the text.</p
Modeled Tradeoffs between Developed Land Protection and Tidal Habitat Maintenance during Rising Sea Levels
<div><p>Tidal habitats host a diversity of species and provide hydrological services such as shoreline protection and nutrient attenuation. Accretion of sediment and biomass enables tidal marshes and swamps to grow vertically, providing a degree of resilience to rising sea levels. Even if accelerating sea level rise overcomes this vertical resilience, tidal habitats have the potential to migrate inland as they continue to occupy land that falls within the new tide range elevations. The existence of developed land inland of tidal habitats, however, may prevent this migration as efforts are often made to dyke and protect developments. To test the importance of inland migration to maintaining tidal habitat abundance under a range of potential rates of sea level rise, we developed a spatially explicit elevation tracking and habitat switching model, dubbed the Marsh Accretion and Inundation Model (MAIM), which incorporates elevation-dependent net land surface elevation gain functions. We applied the model to the metropolitan Washington, DC region, finding that the abundance of small National Park Service units and other public open space along the tidal Potomac River system provides a refuge to which tidal habitats may retreat to maintain total habitat area even under moderate sea level rise scenarios (0.7 m and 1.1 m rise by 2100). Under a severe sea level rise scenario associated with ice sheet collapse (1.7 m by 2100) habitat area is maintained only if no development is protected from rising water. If all existing development is protected, then 5%, 10%, and 40% of the total tidal habitat area is lost by 2100 for the three sea level rise scenarios tested.</p></div
Elevation change function (Eq 1) parameter values used.
<p>Elevation change function (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0164875#pone.0164875.e001" target="_blank">Eq 1</a>) parameter values used.</p
Elevation gain vs. elevation functions.
<p>The empirical function utilized for marsh habitat elevation gain in the simulations is shown in black (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0164875#pone.0164875.e001" target="_blank">Eq 1</a>), and two alternative elevation-gain functions that were used to test model sensitivity to uncertainty in elevation gain rates are shown in gray. Vertical lines show habitat zonation, with dashed lines indicating one standard deviation of the Gaussian distribution from which habitat transition elevations were selected.</p