Puerto Rico Land-Based Threat to Benthic Habitats

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Converted from FGDC Content Standards for Digital Geospatial Metadata (version FGDC-STD-001-1998) using 'fgdc_to_inport_xml.pl' script. Contact Tyler Christensen (NOS) for details.

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Unknown | Type of Source Media: aerial photography and scanned photos

Ground control points, camera calibration data, and USGS DTM data were used to orthorectify 500 dpi scans of the aerial photos using Socet Set Version 4.2.1. Orthorectified images were then loaded into ArcView 3.2 with the Image Analyst and Habitat Digitizer Extensions activated. This allowed the photointerpreter to interpret features, delineate and attribute benthic habitat directly into a digital reference system. The data were saved as ArcView shapefiles.to estimate the potential threat to each polygon, the following methodology was employed:Step 1) The first step of the analysis involves estimating likely relative erosion rates for each 30 m resolution grid cell using a modified, simplified form of the Revised Universal Soil Loss Equation (RUSLE) (USDA, 1989). Information on slope, land cover type, precipitation, and soil porosity were integrated to develop an indicator of relative erosion potential (REP) for all land areas within Puerto Rico. Inputs: (REP relies upon four input data sets, three of which were described under the analysis of vulnerability to erosion, above.) 4. Slope (percentage) - for each 30m grid cell, derived from the (raw) DEM (without hydrologic correction.)5. Relative erosion rate by land cover type. Relative erosion rates for each land cover type were calculated using a look-up table. Land cover categories from NASA Geocover-LC products covering Puerto Rico (http://www.MDafederal.com/geocover/geocoverlc/) were reclassified to relative erosion rates, ranging from 15 (for forest) to 220 for barren land. (below) These relative erosion rates are based on published work involving conversion factors. 6.Precipitation during the peak rainfall month (in millimeters) - Long-term average monthly precipitation values for the peak rainfall month of the year is an interpolated grid based on data for climate stations from NOAA's National Climate Data Center (NCDC). This variable was chosen because it is more indicative of the rainy season and more extreme events during the year.7.Soil erodibility factor (K-ffactor) - the K-ffactor was obtained from the SSURGO database of the USDA.Land Cover Type, Grid Code, Relative Erosion RateDeciduous Forest, 1, 15Evergreen Forest, 2, 15Shrub/Scrub, 3, 50Grassland, 4, 125Barren, 5, 220Urban, 6, 210Agriculture, 7, 200Permanent Wetland, 9, 80Mangrove, 10, 80Water, 11, 5Cloud/No Data, 13, 0Equation 2:Relative Erosion Potential (REP) = Slope(%) x precip (mm for peak rainfall month) x soil k-ffactor x relative erosion rate for land cover type / 1000The grid is divided by 1000 and converted to integer for a better data range and easier display.The analysis was implemented in ESRI ArcView 3.2 software, using the map calculator function of Spatial Analyst, which is also available in ArcMap. The raster analysis was done at 30 m resolution in UTM projection (Zone 20N, WGS84.) (continued...)

(continued from above) Two indicators indicative of erosion within the watershed were calculated for each basin:mean REP for the basin (an indicator of average erosion rates for the basin) (REP_MEAN), and total relative erosion within the basin (REP_SUM).Step 2) An indicator of relative sediment delivery at the river mouth was estimated by multiplying total relative erosion in the basin (REP_SUM) by the sediment delivery ratio (SDR) for the basin, which is a function of watershed size. SDR reflects the percentage of erosion within the basin (REP_SUM) which reaches the river mouth.Equation 3:Sediment Delivery Ratio (SDR) = 0.41 x basin area (in sq km)*-0.3. This factor comes from published research on watersheds in the Caribbean. Equation 4:Sediment delivery at the river mouth (SED_DELIV) = REP_SUM x SDR8. The point density tool (Spatial Analyst, ArcGIS) was then used to create a threat layer, using the sediment delivery at the outflow point as input, and a kernel radius of 5 km. 9. This threat layer was then averaged for every benthic habitat polygon (NOAA Benthic Habitats of Puerto Rico and the U.S. Virgin Islands, Kendall et al., 2001) using a zonal function to determine the mean threat. Sources used were NOAA Benthic Habitats Data http://ccma.nos.noaa.gov/products/biogeography/benthic/, Geocover LC http://www.MDafederal.com/geocover/geocoverlc/, USGS National Elevation Dataset http://ned.usgs.gov/, NRCS Soils Database http://www.nrcs.usda.gov/wps/portal/nrcs/site/national/home/, NOAA Monthly Surface Data http://www.ncdc.noaa.gov/oa/climate/climatedata.html. (end continuation)