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Vegetation Classification and Mapping Project Report - USGS

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<strong>USGS</strong>-NPS <strong>Vegetation</strong> <strong>Mapping</strong> Program<br />

Colonial National Historical Park<br />

<strong>Vegetation</strong> <strong>Classification</strong> <strong>and</strong> Characterization<br />

The vegetation classification used to map seven mid-Atlantic NPS units in Virginia was<br />

developed through successive approximations. The initial classification from 2001 (Fleming<br />

2001) was improved upon by two additional analyses, in 2003 <strong>and</strong> in 2006, each progressively<br />

using a larger regional dataset, with the objective of producing a more robust classification.<br />

All plot data collected in mid-Atlantic national parks as of November 2002 were combined into a<br />

regional data set of 1342 plots from throughout the Virginia Piedmont <strong>and</strong> Coastal Plain <strong>and</strong><br />

from selected NPS units in Maryl<strong>and</strong> <strong>and</strong> the District of Columbia. The resulting preliminary<br />

vegetation classification was reviewed by NPS ecologists <strong>and</strong> Natural Heritage Program<br />

ecologists from Virginia, Maryl<strong>and</strong>, <strong>and</strong> West Virginia. In December 2006, with the addition of<br />

plot data collected since 2002 from Virginia, Maryl<strong>and</strong>, <strong>and</strong> West Virginia, a regional dataset of<br />

2,250 plots was used to develop the final vegetation classification for the project.<br />

All data were examined using a combination of cluster analysis, ordination, <strong>and</strong> tabular<br />

(statistical) analysis. In general, the analytical process was designed to progressively fragment<br />

the large datasets into more workable subsets, using cluster analysis to identify groups, statistical<br />

analysis to validate those groups, <strong>and</strong> lastly ordination studies to examine compositional<br />

gradients between groups <strong>and</strong> correlations with important environmental gradients. In practice,<br />

the process was iterative as increasingly finer groups were identified <strong>and</strong> analyzed.<br />

The general steps included 1) data preparation <strong>and</strong> transformation, 2) numerical classification<br />

(cluster analysis), 3) summary statistics, 4) gradient analysis (ordination), <strong>and</strong> 5) assignment of<br />

classification units to the st<strong>and</strong>ard (crosswalking to USNVC). Each of these steps is outlined<br />

below.<br />

Data Preparation <strong>and</strong> Transformation<br />

Plot data collected during field work were combined with existing data from throughout the Mid-<br />

Atlantic Coastal Plain <strong>and</strong> Piedmont using databases created with Microsoft Access 2000. The<br />

final dataset consisted of 2,250 plots (1,452 upl<strong>and</strong> <strong>and</strong> palustrine wetl<strong>and</strong> plots; plus 798 tidal<br />

plots).<br />

Since individual plant taxa are not always identified to the same taxonomic level in plot<br />

sampling, botanical nomenclature for the whole analysis dataset was reviewed <strong>and</strong> st<strong>and</strong>ardized.<br />

As a rule, taxa were treated at the highest level of resolution possible, but treatment at the<br />

subspecific level was not always possible <strong>and</strong> a few groups of species had to be merged into<br />

"pseudospecies." For example, various plots had Polygonatum biflorum, Polygonatum biflorum<br />

var. biflorum, or Polygonatum biflorum var. commutatum; these were merged at the species<br />

level. Species richness was calculated for each plot using all taxa (including unidentified<br />

species) rooted within plot boundaries. However, taxa identified only at generic or higher levels<br />

(e.g., “Carex sp.” or “unidentified woody seedling”) were deleted from the dataset prior to<br />

analysis to eliminate "noise" <strong>and</strong> potentially erroneous correlations between generic entities.<br />

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