WSP00036

• File Number: 8200.750
• Description: San Juan River General
• State: CO
• Basin: San Juan/Dolores
• Water Division: 7
• Date: 3/1/1975
• Author: BOR
• Title: San Juan Ecology Project - Interim Progress Report - March 1975
• Water Supply Pro - Doc Type: Report/Study

4.3.1 Introduction

4.3 PHYTOSOCIOLOGY (Dr. R.L. Dix and J.D. Richards)

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Vegetation continuously responds to the physical
environment and therefore any significant change in
that environment through time can be expected to
cause a corresponding change in vegetation. There-
fore, possible increases in snowpack and snow dura-
tion, which may be brought abput by the weather
modification program in the San Juan Mountains, can
be expected to result in adjustments in its vegetation
structure and dynamics. Since the dominant plant
species of this vegetation are long lived perennials,
this adjustment is expected to be slow, it will
probably occur over a period of many decades. The
establishment of the weather modification program
before adequate research had begun on the vegetation
of the San Juan Mountains necessarily precludes the
establishment of appropriate experiments. We are,
therefore, limited to studies which show the principal
environmental gradients along which vegetation
responds and to determining the nature and magnitude
of these responses. This knowledge will enable us to
predict what changes may be expected as the physical
environment of the San Juan Mountains is artificially
modified. Limited time and funds also necessitated
th~t our study be limited to the subalpine forest of
these mountains.

4.3.2 Ob1ectives

The overall objectives of this project are twofold:
(1) to provide a quantitative description of the
subalpine forest of the San Juan Mountains within
which the results of other investigations may be
expressed (Table 1); and (2), to predict the effects
that weather modification may have on the composition
and dynamics of this vegetation. Since the establish-
ment of experiments was not possible, a major objec-
tive is to establish the principal environmental
gradients along which the subalpine forest responds so
that this information can be used to predict possible
changes whicb may be brought about by the weather
modification program. In addition, our description of
the subalpine forest provides a data base (too large
to be presented here), established during 1971-1973,
for the detection of possible changes in vegetation
associated with weather modification programs through
subsequent years.

4.3.3 Methods

Data were collected from 61 sites selected over a wide
range of environmental conditions. These included 20
aspen, 37 Englemann spruce-subalpine fir, 3 white fir,
and 1 douglas fir dominated stands. The majority of
these stands are located on Missionary Ridge, although
a few were selected from the Rico and Wolf Creek Pass
study areas.

Standard phytosociological techniques were used to
measure tree species for density, dominance (basal
area), height, vitality and age structure. These tree
species were measured in 3 size classes: (1) trees
(diameter at breast height (dbh) greater than or equal
to 8.16 cm.), (2) saplings (dbh greater than 2.54 cm.
but less than 8.16 cm.), and (3) seedlings (dbh equal
to or less than 2.54 em.). Cover and frequency were
recorded for shrubs. Frequency values, in 50 x 50 em.
quadrants, were obtained for all understory species.
Selected environmental parameters were recorded from
each site. Snow duration data were determined for 23
sites from sequential aerial photographs from flights
flown in 1971. Partial snow duration data are

available for 4 additional stands. More frequent and
more extensive photo coverage was expected from 1973
aerial surveys, but did not materialize.

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Principal components analysis (PCA), a form of
indirect gradient analysis, was used to define the
major structural gradients within the vegetation, and
to correlate measured environmental parameters to
those gradients. The gradients defined by the prin-
cipal components analysis are vegetational gradients
which are determined statistically to account for as
much of the variation in the vegetational data as
possible. The analysis allows correlations of the
measured environmental parameters with the derived
vegetational gradients. Understory species data were
used in the analysis since the large number of
species involved provides for precise definitions of
the vegetational gradients. The methodology of PCA
has been used and discussed by Seal (1964), Orloci
(1966), Gittens (1969), and Walker and Wehrhahn
(1971) .

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4.3.4 Results

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Our first objective of providing a quantitative
description of the subalpine vegetation of the San
Juan Mountains is given below in the presentation of
the indirect gradient analysis. This particular
method of display will probably be most useful to
other workers on the project because it provides the
phytosocio10gical display on the gradients of
greatest interest; namely to snow duration and
related gradients. Our second objective of providing
an analysis of the effects of weather modification on
vegetational composition is treated below by tech-
niques of direct gradient analyses.

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- Indirect gradient analysis

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Major gradients in the vegetation were derived from a
principal components analysis (PCA) of the understqry
species frequency data. So that snow duration dll:ta
could be included in the analysis, and an interpreta-
tion of snow duration effects could be made, only
those stands with aerial photo coverage were used in
the analysis presented here. Another peA using 57
subalpine stands (the 23 snow duration stands plus 34
stands not within the aerial survey) was done with
virtually identical results; therefore, the gradients
described by the analysis of only the stands with
photo coverage are presented.

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Table 1 shows the first three gradients or components
described by the PCA. The first component is a
gradient which accounts for the maximum possible
variance in the data, and each successive component
accounts for as much of the remaining variance as
possible. Each species has a loading on each
component which is, in fact, the correlation coeffi-
cient between that species and that component (or
gradient). The square of this loading is the propor-
tion of variance of the species' data accounted for
by that component. The column IIh21l is the sum
squares of the first three components and is the
amount of variance in the data of that species which
is accounted for by the first three components. A
total of 94 understory species, 5 tree species, and
10 environmental parameters was included in the PCA.
For brevity the table includes only those species for
which: (1) over 65% of the variance was accounted for
by the first three components, or the loading on the
first component was greater than 0.6, and the species
was present in more than one stand on Missionary

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