Vegetation Classification and Mapping Project Report - USGS

Vegetation Classification and Distribution Mapping Report: Petrified Forest National Park
total area and frequency of occurrence of
that type within the project area.
The team had planned to sample at the
centroid of each selected polygon. If
the sample site was determined to not
be representative of a homogeneous
vegetation community, the relevé was
moved to the closest representative
vegetation community within the
biophysical unit. A 500-m 2 relevé was
established (1000-m 2 in sparsely vegetated
communities with less than 10% cover),
and plant species cover/abundance data, as
well as environmental data, were collected
(table 4). The classification team examined
the field data during the collection period
to determine if adequate numbers of
relevés were sampled for each expected
and observed community type. Plant
communities under-represented in the
stratified sampling design were sampled
opportunistically at the end of the 2003
field season.
Table 4. Summary of data collected within 2003 classification relevés at
Petrified Forest National Park.
Type of information
Plot documentation
Environmental description
Surface cover
Vegetation description
Vegetation strata
Plant species
Other vegetation characteristics
Items noted
Plot location and identification, geographic
references, plot size, picture documentation
Elevation, slope, aspect, position, landform,
geology, soil texture
Fine particles, gravel, cobble, stone, boulders,
bedrock; litter, duff, moss, lichen,
biotic crust; animal use; human/natural
disturbance
Leaf phenology, leaf type, physiognomic
class
Height, cover class and dominant species
each stratum
Observed plant species on survey site
Mortality, nurse plant function, etc.
2.1.1.3 Quantitative Data Analysis
Data from the 2003 classification relevés
were entered into a Microsoft® Access
2000 database and quality checked. The
cover values for species that occurred in
multiple strata were combined into a single
cover estimate for classification and for the
plant community descriptions. However,
total cover estimates for tree, shrub,
and herbaceous cover were calculated
based on cover estimates for lifeform
and not strata height. The classification
team imported the data into an Excel
spreadsheet and formatted it for use in
PC-Ord, a multivariate statistical analysis
program (McCune and Mefford 1999).
The classification team first identified
descriptive statistics in the relevé dataset
and examined whether statistical
differences existed when comparing
the compositional heterogeneity of the
physiognomic groups represented in
the relevé data. The team initially used
non-metric multi-dimensional scaling
(NMS) ordination (which provides
a view of community organization in
multi-dimensional space) to analyze the
entire dataset of 149 relevé sites from the
2003 field efforts (fig. 3). The resulting
descriptive statistics showed high betadiversity
(β=7.46), indicating a high degree
of compositional heterogeneity. The
team then attempted to minimize relevé
heterogeneity by dividing the data into
four groupings or classes, based on the
apparent lifeform of the dominant species
in each relevé: shrubland, grassland, steppe
(a shrub-grassland mixture), and sparse.
All analyses were then rerun on each class
(fig. 4). Species occurring only once within
a class were usually removed from the
dataset in order to reduce noise. However,
if a species occurred only once but was
the dominant species in a relevé, it was
retained because of its influence within the
plant community.
The team also conducted an outlier
analysis to identify any relevés that might
skew the analysis. If it was determined that
the outlier relevés were actually unique
plant communities, we retained those
relevés (despite their introducing noise to
the dataset) due to their importance for
the community analysis.
The team then conducted a cluster
analysis—a hierarchical clustering
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