identified the geomorphology (e.g., meander
and Brown (1997). Geomorphic units were
inactive-floodplain cover deposit) and vegetation
assigned to physiographic settings based on their
structures (e.g., broadleaf forest) associated with
erosional or depositional processes (see App. A).
each ecotype based on the relationships devel-
Surface forms were simplified into a reduced set
oped from the analysis of the field data. We then
of slope elements (i.e., crest, upper slope, lower
were able to assign a reduced set of 44 ecotypes
slope, toe, flat). For vegetation, we used the struc-
to 409 integrated terrain units (geomorphology/
tural levels of the Alaska Vegetation Classification
vegetation combinations) generated by the map-
(Viereck et al. 1992) because they are more readily
ping (see App. A). Three of the ecotypes identi-
identifiable on aerial photography than are floris-
fied from the plot data were not mapped because
tic composition.
they occurred in patches that were too small or
Common relationships among ecosystem com-
could not be differentiated on the aerial photo-
ponents were identified by visual examination of
graphs.
graphic profiles and by use of contingency tables.
For classification of ecosystems at smaller spa-
The contingency tables successively sorted plots
tial scales, geomorphic and physiographic criteria
by climate zone, physiography, texture, geomor-
were used for differentiation (Table 2). Ecosections
phic unit, drainage, and vegetation type. From
were differentiated based on geomorphic patterns
these tables, common associations were identified
and processes. Because each ecosection is unique,
and unusual associations either were lumped
we named the areas on the basis of a general physi-
with those with similar characteristics or excluded
ographic descriptor (e.g., lowland or upland) and
as unusual outliers. Our philosophy was that it
a prominent geographic feature (e.g., prominent
was better to identify strong relationships that
creek or mountain). Classification of ecodistricts
could be used for prediction and mapping than
was based on general physiographic characteris-
to make additional rules and classes that only
tics that were related to associations of geomorphic
increase confusion and degrade accuracy.
units. Naming was similar to that used for eco-
Ecotype names were based on the simplified
sections.
ecosystem components. For example, a full name
for an ecotype for an individual plot would be
Mapping
Boreal Upland Rocky Moist Mixed Forest based
The mapping of ecosystems was done at three
on climatic, physiographic, textural, hydrologic
spatial scales: ecotype (1:50,000), ecosection
(moisture), and vegetative components, respec-
(1:100,000), and ecodistrict and ecosubdistrict
tively. Because this generated a large number of
( 1 : 2 5 0 , 0 0 0 ) . The ecotypes and ecodistricts
specific ecotypes (89) from the 240 field plots, we
involved independent delineations, while the
aggregated many similar types into a reduced set
ecosection map was created by aggregating geo-
of ecotypes (47). Sometimes textural classes were
morphic units from the ecotype map.
grouped (e.g., rocky and loamy) because vegeta-
Ecotypes were mapped by two methods. Exist-
tion remained similar, or similar vegetation struc-
ing Soil Conservation Service (SCS) vegetation
tures (e.g., open and closed black spruce) were
maps (on file: Alaska Department of Natural
grouped because species composition was simi-
Resources [ADNR], Division of Support Services)
lar. This grouping was an arbitrary process that
were available for USGS quadrangles Fairbanks
relied on our own perspective of what we consid-
B1, B2 (eastern half only), C1, C2, C3, C4, D1, and
ered to be the most important elements, our at-
D2, and Big Delta B6, C5, C6, D5, and D6 (SCS/
tempt to balance the need to differentiate ecologi-
ADNR 1990). SCS polygons were transferred to
cal characteristics, and our effort to minimize the
acetate and overlain on 1995 1:24,000 true-color
number of classes for management purposes. This
aerial photographs for the Tanana Flats and
grouping can be done in any number of ways and
1:30,000 enlargements of 1979 and 1986 1:63,360
other users may want to group characteristics in
color-infrared photographs for the Yukon Maneu-
different ways for their own individual purposes.
ver Area. Polygons were recoded with an inte-
This change can easily be done by regrouping
grated-terrain-unit system that included both a
characteristics in Appendix A and applying it to
geomorphology and vegetation code, and bound-
the ITU (International Telecommunication Union)
aries redrawn where necessary. Minimum map-
codes in the database.
ping units for polygons were approximately 1.5 ha
An important consideration in ecosystem classi-
for complexes and 0.5 ha for other polygons.
fication is how well classes can be identified on
For areas lacking SCS mapping, and for three
aerial photographs. For mapping purposes, we
areas where we wanted to do more detailed map-
10
Go to contents page
Previous Page
