1
The Limnology of Lake Pleasant Arizona and its Effect
on Water Quality in the Central Arizona Project Canal.
David Walker
University of Arizona Environmental Research Laboratory, 2601 E. Airport Drive
Tucson, AZ. 85706-6985.
Kevin Fitzsimmons
University of Arizona Environmental Research Laboratory, 2601 E. Airport Drive
Tucson, AZ. 85706-6985.
2
David Walker, 06/07/99, The Limnology of Lake Pleasant Arizona and it’s Effect
on Water Quality in the Central Arizona Project Canal. Lake and Reserv.
Manage. Vol. 11(0): 00-00
Abstract
Recent changes in the management strategy of water released from Lake
Pleasant into the Central Arizona Project (CAP) canal have substantially reduced
taste and odor complaints among water consumers. Most of the taste and odor
complaints were probably caused by 2-methylisoborneol (MIB) and geosmin
produced by periphytic cyanobacteria growing on canal surfaces. Except during
flood events, Lake Pleasant consists almost exclusively of water brought in via
the CAP canal. The location of the inlet towers and the Old Waddell Dam
influence sedimentation of material brought in via the CAP canal. In-coming
water was found to contain large amounts of periphyton of the type found
growing on the sides of the CAP canal. Laboratory experiments with sediment
from two different regions of the reservoir revealed that the region between the
Old and New Waddell Dams contains sediments that have a higher potential for
phosphorous release during periods of anoxia than those found in other areas.
Withdrawal of hypolimnetic water early in the spring decreased the time that
sediments were exposed to anaerobic conditions. This potentially decreased the
amount of soluble nutrients released into the CAP canal and available for
periphytic cyanobacteria. Utilizing this management regimen since 1997 has
resulted in a substantial reduction (or elimination) of consumer complaints of
earthy/musty tastes and odors.
3
Keywords: 2-methylisoborneol, geosmin, periphyton, sedimentation,
eutrophication, allochthonous, autochthonous, stratification.
In the first few years after Lake Pleasant Arizona was used as a storage
reservoir for CAP water supplied to several municipalities in the Phoenix Valley,
many consumers complained of earthy/musty tastes and odors (T&O’s) in water
delivered by utilities (pers.comm. Tom Curry, Central AZ. Water Conservation
District). Powdered activated carbon (PAC) was used extensively to alleviate the
earthy/musty T&O’s, often at great expense to utilities. Our project was initiated
in an attempt to decrease the amount of T&O’s in water delivered to consumers.
Anecdotal information suggested that T&O complaints decreased
dramatically when the CAP canal contained raw Colorado River water as
opposed to water that had been stored in Lake Pleasant (pers. comm. Matt
Rexing, Mesa CAP Water Treatment Plant). Also, it appeared that T&O
complaints increased among those utilities in the Phoenix Valley that were
farthest from Lake Pleasant (pers. comm. William Vernon, Scottsdale CAP Water
Treatment Plant; pers. comm. Gene Michael, Glendale CAP Water Treatment
Plant). Earthy/musty T&O’s are often associated with certain species of
cyanobacteria that are capable of producing 2-methylisoborneol (MIB) or
geosmin (Izaguirre et al., 1983, Naes et al., 1988, Izaguirre & Taylor 1995).
Previous studies that have dealt with MIB/geosmin production by cyanobacteria
in source waters have tended to examine the role of reservoirs (Izaguirre et al.,
1982; Berglind et al., 1983; McGuire et al., 1983; Slater & Blok 1983; Yagi et al.,
1983; Negoro et al., 1988; Izaguirre 1992), or canals emanating from these
4
reservoirs (Izaguirre & Taylor, 1995) as separate ecosystems. This study was
initiated to determine whether conditions in Lake Pleasant might promote growth
of known MIB/geosmin producing cyanobacteria within the CAP canal upon
release of water from Lake Pleasant. This required understanding how the
limnology of Lake Pleasant affects the water quality and aquatic biota in the CAP
canal.
Materials and Methods
Study Site
Lake Pleasant is located about 48 km northwest of Phoenix, Arizona and
is used as a storage reservoir for water transported from the Colorado River.
Water is pumped into the lake during winter and released during summer when it
is used for irrigation and drinking water. Prior to 19XX, Lake Pleasant was fed
exclusively by the Agua Fria River entering from the north. The construction of
the New Waddell Dam increased the size of Lake Pleasant from 1,497 to 4,168
hectares (AZ. Game and Fish Dept. unpublished report to U.S. Bureau of
Reclamation, 1990). The Old Waddell Dam remains submerged within the
reservoir immediately to the north of the new dam (Fig. 1). The primary water
source for Lake Pleasant is now the CAP canal. At maximum capacity, Lake
Pleasant contains approximately 811,000 acre feet of water (pers. comm. Tom
Curry, Central AZ. Water Conservation District).
Sampling Sites
We established four sampling sites within Lake Pleasant (“A”, “B”, “C”, and
“D”) (Fig 2), chosen according to an idealized model of reservoir zonation as
5
proposed by Kimmel & Groeger(1984). Locations were determined with a Global
Positioning System (GPS) unit (Magellan Model 2000XL). Site A (33o 50’ 57” N
and 112o 16’ 18” W) is the closest to incoming CAP water. Site B (33o 51’ 04 N
and 112o 17” W) lies between the New and Old Waddell Dams. Site C (33 o 51’
26” N and 112o 16’ 21” W) is to the north of the old dam and Site D (33 o 52’ 20” N
and 112o 16’ 11” W) is the farthest north from the CAP inlet. (Fig. 2)
Within the CAP canal, 5 sampling sites were established. The sites
including approximate kilometers from Lake Pleasant were; Waddell Forebay (0
km), 99th Ave (6 km), Scottsdale WTP (45 km), Granite Reef (70 km), and Mesa
WTP (78 km).
Field Data Collection
Lake Pleasant
Samples were collected at each site every 2 weeks when the reservoir
was stratified (May – November) and monthly when it was de-stratified
(December – April) from 05/1996 – 05/1998. A minimum of 3 samples was
collected at varying depths at each site to obtain a profile of the water column.
The number of samples collected at each site was based on the presence or
absence of a thermocline. Large fluctuations in water levels also resulted in
samples being collected at different depths over time. For example, if the depth
of the water at Site C was 60 m in August and the thermocline depth was 10 m
then samples were collected at 60, 10, and 0.5 m. However, if the depth at the
same site in February was 80 m and no thermocline was evident then samples
were collected at 80, 40 and 0.5 m
6
Water samples were collected in a 2.2l Van Dorn-style sample bottle
(Wildlife Supply Company). Water collected was transferred to two 500ml, and
one 100ml plastic bottles (Nalgene Corp). One of the 500ml bottles contained 2
ml’s of sulfuric acid for analyses of ammonia-N, nitrate-N, and total phosphorous.
The other 500ml bottle was used for phytoplankton identification and
enumeration and contained 50ml of formaldehyde. Samples collected for
orthophosphorous were field filtered using a 0.45micron cellulose acetate sterile
syringe filter and a sterile 100ml syringe and stored in a100ml bottle. All were
kept on ice in coolers for transport to the laboratory.
CAP Canal
Samples were collected approximately every 14 days within each CAP
site and were analyzed for MIB/geosmin and periphyton analysis during the
period of time when water was being released from Lake Pleasant. Periphyton
was collected from the sides of the canal at a depth of 0.5 m. The area scraped
was measured and the sample diluted with 250 ml’s of distilled water and 15 ml’s
of formaldehyde.
Geosmin and MIB samples were collected in 1-liter glass amber bottles and kept
on ice for transport back to the University of Arizona.
Laboratory Methods
Water samples were analyzed for ammonia-N (Nesslerization), nitrate-N
(Standard Method 4500-NO3-), orthophosphate (Standard Method 4500-P), total
phosphorous (Standard Method 4500-P.5), ferrous iron (Standard Method 3500-
7
Fe D), and total iron (Standard Method 3030 D followed by 3500-Fe D). Results
were determined colorometrically using a Hach DR/890 colorimeter.
Phytoplankton and periphyton were enumerated using a Sedgwick-Rafter
counting chamber and an ocular micrometer (Standard Method 10200 F) on a
calibrated Olympus BH2 phase contrast light microscope (Olympus Corp.) at a
magnification of 200X. Identification sometimes was made at higher
magnifications (up to 400X), but all enumerations were performed at 200X.
Identifications were made to genus level and all counts were natural unit counts
and recorded as units/ml for phytoplankton and units/cm 2 for periphyton
(Standard Method 10200 F).
Statistical Analysis
Data were analyzed using univariate one-way analysis of variance
(ANOVA) and principal component analysis (PCA) to determine which linear
combination of X and Y variables had the highest correlation. These correlations
were performed on an individual site basis and for the reservoir as a whole to
determine what drives primary production within the reservoir and what
contributes to tastes and odors within the CAP canal.
For Lake Pleasant data, the independent variables were location (sites A,
B, C, and D) and depth. The depths were categorized based upon the presence
or absence of stratification i.e. epilimnion, metalimnion, hypolimnion, or
homogenous. The dependant variables were temperature, pH, specific
conductivity, dissolved oxygen, turbidity, ammonia-N, nitrate-N, orthophosphate,
total phosphorous, ferrous iron, total iron, phytoplankton taxa (Division or
8
Genus), phytoplankton enumeration (units/ml), periphyton taxa (CAP canal only),
and periphyton enumeration (units/cm2).
For the CAP canal sites,
All statistical analyses were performed using JMP version 4.0.3 statistical
software (SAS Institute Inc.).
Results
Lake Pleasant
Physical Data
Temperatures ranged from 11.05o C on 2/13/97 (40m) to 29.76o C on
8/29/96 (surface sample). There was no significant difference among sites for
temperature (F = 0.50, p = 0.68). Thermal stratification was evident at all sites
beginning in late spring and lasting until mid– to late fall. There was a large
difference in temperature among the epi-, hypo-, and metalimnion (Figs. 3&4)
(ANOVA Temp X Layer). Depth of the thermocline increased throughout the
summer at all sites.
Depth and dissolved oxygen levels were correlated among all sites during
the time of peak stratification (Aug-Oct) both years (r = 0.80) (Fig. 5). Dissolved
oxygen levels were not significantly different among sites (F = 0.416, df = 3, p =
0.7416). Dissolved oxygen levels between the epi-, hypo-, and metalimnion
however, showed significant differences (F = 263.13, df. = 2, p = <.0001) (Fig. 6)
with the hypolimnion becoming completely anoxic during late summer and early
fall of 1996 (Fig. 7). Differences also existed between years with 1996 having
much lower levels (x = 5.1) than 1997 (x = 7.73) (F = 266.62, df = 1, p = <.0001)
9
(Fig 8). A comparison of summer hypolimnetic dissolved oxygen levels between
1996 and 1997 (x = 4.74) reveals even larger differences (x = 0.20 and 3.26
respectively) (F = 254.521, df = 1, p = <.0001) (Fig 9).
Significant differences also existed among layers for pH levels when the
reservoir was stratified (F = 938.93, df = 2, p = <.0001). The hypolimnion had the
lowest mean (x = 7.94), which would indicate that reducing conditions might
occur within this layer seasonally. Differences between sites for pH values were
not significant in either the homogenous or stratified condition (F = 0.145, p =
0.9327 and F = 0.268, p = 0.8487 respectively). There were, however, large
differences in hypolimnetic pH values between 1996 and 1997 (F = 257.801, df =
1, p = <.0001) (Fig 10).
Turbidity by layer revealed that levels were significantly higher when the
reservoir was in the homogenous condition than the epi-, meta-, or hypolimnion
when the reservoir was thermally stratified (F = 5.5903, df = 3, p = 0.0008). When
the reservoir was homogenous, turbidity levels increased with depth (F = 56.45,
df = 1, p = <.0001). During the period of homogeneity, turbidity levels also
differed between sites (F = 11.3483, df = 3, p = <.0001). Site B had the highest
levels (x = 10.9 NTU’s) followed by site C (x = 9.12 NTU’s), site A (x = 5.85
NTU’s) and site D (x = 4.17 NTU’s). The time of homogeneity within the reservoir
is also the time of annual re-filling via the CAP canal.
Specific conductance levels differed between sites when the reservoir was
homogenous (F = 3.8053, df = 3, p = 0.0100) but not when the reservoir was
stratified (F = 1.3924, df = 3, p = 0.2437). When the reservoir was homogenous,
10
specific conductance levels increased with increasing distance from the CAP
inlet towers. Since most of the re-filling of Lake Pleasant occurs during the period
of homogeneity, this would suggest that the infusion of “fresher” CAP canal water
plays a more significant role in the differences between sites than does increased
evaporation during the summer. Specific conductance levels increased with
increasing depth during periods of stratification (F = 98.5862, df = 1, p = <.0001)
but exhibited no significant depth-related change during periods of relative
homogeneity (F = 1.6608, df = 1, p = 0.1978).
During 1996, de-stratification occurred in November. In the summer of
1997, water levels were lower than they were during the same period in 1996.
However, dissolved oxygen levels at similar depths still revealed a significant
increase during 1997 compared to 1996. As early as October of 1997, the
reservoir was homogenous in terms of temperature and dissolved oxygen levels
with isolated pockets of anoxia occurring only in areas deeper than 32 m. (Fig.
11). The mean hypolimnetic dissolved oxygen level at site B during 1996 and
1997 were 1.19 and 5.28 mg/l respectively. Also, at site B in 1996 the
hypolimnion was at times completely anoxic from 16.5 meters to the bottom (35
meters). At this site in 1997, the lowest dissolved oxygen level recorded over the
sediment was 2.53 mg/l.
Phytoplankton Data
Overall phytoplankton numbers increased with depth while the reservoir
was being refilled with Colorado River water via the CAP canal (F = 10.2917, df =
1, p = 0.0018). Inversely, overall phytoplankton numbers decreased with depth
11
while water was being withdrawn from the reservoir back into the CAP canal (F =
10.2917, df = 1, p = 0.0061). Also, the occurrence of increased phytoplankton
numbers with depth during the period of refilling was only discernible at sites B
and C (F = 6.9596, df = 1, p = 0.0142 and F = 8.8252, df = 1, p = 0.0065
respectively). During the same period, Site A exhibited no statistical difference in
phytoplankton numbers with depth (F = 0.6959, df = 1, p = 0.4121) and Site D
exhibited a decrease in phytoplankton numbers with depth (F = 17.6047, df = 1, p
= <0.0001).
During the period of withdrawing water from the reservoir, there was no
significant difference among sites in phytoplankton numbers (F = 1.1118, df = 3,
p = 0.3468). During the period of refilling, however, Site B had the highest overall
phytoplankton numbers (in units/ml) (x = 7257) followed by site C (x = 3977.48 ),
site A (x = 1534.30) and site D (x = 320.04) respectively (F = 3.8097, df = 3, p =
0.0125).
The increase in phytoplankton numbers with depth during the period of
refilling, and the differences among sites in phytoplankton numbers and whether
they were higher or lower at depth, was first observed on 12/4/96 (Fig. 12). The
types of algae found on this date at the deepest levels of sites B and C were
those species usually found growing periphytically on the sides of the CAP canal.
The dominant Division of algae found at depth at sites B and C during the period
of annual re-filling were chrysophytes (Fig. 13) and these being almost
exclusively of the Order Pennales. Within the Division Chrysophyta, Cymbella
spp. was the dominant genus (Fig. 14).
12
CAP Canal
Overall periphyton numbers increased with distance from Lake Pleasant
(F = 3.7219, df = 4, p = 0.0053). This trend was evident for both 1996 (F =
3.4685, df = 4, p = 0.0086) and 1997 (F = 5.4108, df = 4, p = 0.0003). A
comparison of the two years reveals that overall periphyton numbers for all sites
was significantly higher in 1996 than 1997 (x = 6718 and 2431 units/cm2
respectively, F=10.4061, df = 546, p = 0.0013).
The periphyton was comprised of four divisions; Chlorophyta,
Chrysophyta, Pyrrophyta, and Cyanobacteria. Overall, cyanobacteria were the
most abundant (x = 10,190 units/cm2) followed by chrysophytes (x = 3193
units/cm2), chlorophytes (x = 2096 units/cm2), and pyrrophytes (x = 1490
units/cm2) (F = 6.9232, df = 3, p = 0.0001) (Fig. 15).
The periphyton along the CAP canal exhibited a large amount of spatial
variation in regards to community composition. Dividing the CAP canal into two
sections (0 – 45 and 70 – 78 km from Lake Pleasant respectively) shows that
cyanobacterial dominance only becomes evident after 70 km. Within the 0 – 45
km group, there was no significant difference among algal divisions (F = 1.2881,
df = 3, p = 0.2785) (Fig. 16) while in the 70 – 78 km group cyanobacterial
abundance was over 3 times greater than the next most abundant Division,
chrysophytes (F = 5.3192, df = 3, p = 0.0015) (Fig. 17). Cyanobacterial
abundance within the 70-78 km group was over 7 times higher than in the 0-45
km group (x = 16,980 and 2356 units/cm2 respectively, F = 5.4428, df = 1, p =
0.0215).
13
The periphytic cyanobacterial community consisted of 5 species all of
which are capable of producing tastes or odors. In order of abundance these
were Lyngbya sp. (x = 17,601 units/cm2), Anabaena sp. (x = 3691 units/cm2),
Oscillatoria sp. (x = 3205 units/cm2), Phormidium sp. (x = 2387 units/cm2), and
Schizothrix.sp.(x = 290 units/cm2). While no significant statistical difference was
observed for species among all sites (F = 1.2758, df = 4, p = 0.2841), it appears
that Lyngbya was the most prevalent species followed by Anabaena, Oscillatoria,
Phormidium, and Schizothrix (Table 1).
Table 1. Contingency Analysis of Genus By Km's From Source
Km's From Source By Genus
Count
Total %
Col %
Row %
00
06
45
70
78
Anabaena
Lyngbya
Oscillatoria
Phormidium
Schizothrix
2
1.79
6.90
13.33
6
5.36
20.69
31.58
5
4.46
17.24
27.78
9
8.04
31.03
32.14
7
6.25
24.14
21.88
29
25.89
10
8.93
18.52
66.67
9
8.04
16.67
47.37
8
7.14
14.81
44.44
14
12.50
25.93
50.00
13
11.61
24.07
40.63
54
48.21
3
2.68
13.04
20.00
4
3.57
17.39
21.05
5
4.46
21.74
27.78
3
2.68
13.04
10.71
8
7.14
34.78
25.00
23
20.54
0
0.00
0.00
0.00
0
0.00
0.00
0.00
0
0.00
0.00
0.00
0
0.00
0.00
0.00
4
3.57
100.00
12.50
4
3.57
0
0.00
0.00
0.00
0
0.00
0.00
0.00
0
0.00
0.00
0.00
2
1.79
100.00
7.14
0
0.00
0.00
0.00
2
1.79
15
13.39
19
16.96
18
16.07
28
25.00
32
28.57
112
Periphytic cyanobacteria were significantly less abundant for all sites in
1997 compared to 1996 (x = 1213 and 19,833 units/cm 2 respectively, F = 9.1416,
df = 1, p = 0.0031). The difference in periphytic cyanobacteria between 1996 and
1997 was most pronounced with distance from Lake Pleasant. Dividing the CAP
14
canal into groupings based upon distance from Lake Pleasant shows the change
was most significant in the 70-78 km compared to the 0-45 km group (F =
5.6637, df = 1, p = 0.0206 and F = 2.9350, df = 1, p = 0.0929 respectively). The
difference in mean number of cyanobacteria for the 0-45 km group between 1996
and 1997 was 4503 and 1120 units/cm2 respectively while for the 70-78 km group
the mean change between 1996 and 1997 was 28,156 and 1335 units/cm 2
respectively.
There was a significant difference among all sites for levels of 2methylisoborneol (MIB) (F = 24.7623, df = 4, p = <0.0001) (Fig. 18). For all sites,
the amount of MIB exhibited a pattern similar to cyanobacterial numbers,
increasing with distance from Lake Pleasant. The highest levels of MIB were
found 78 km away from Lake Pleasant (x = 6.66 ng/L) and the lowest levels were
within the Waddell Dam Forebay (0 km, x = 1.29 ng/L). Geosmin followed a
similar trend as MIB and decreased with distance from Lake Pleasant (F =
22.7698, df = 4, p = <0.0001) (Fig. 19).
Figure 18. Oneway Analysis of Mean MIB (ng/l) By Km's From Lake Pleasant
30
Mean MIB (ng/l)
25
20
15
10
5
0
00
06
45
70
78
Km's From Source
Oneway Anova
Analysis of Variance
Source
DF
Sum of Squares
Mean Square
F Ratio
Prob > F
15
Source
Km's From Source
Error
C. Total
DF
4
583
587
Sum of Squares
2702.776
15908.434
18611.210
Mean Square
675.694
27.287
F Ratio
24.7623
Prob > F
<.0001
Means for Oneway Anova
Level
Number
Mean
Std Error
00
126
1.28810
0.46537
06
119
1.34622
0.47886
45
92
2.90217
0.54461
70
128
4.95648
0.46172
78
123
6.66260
0.47101
Std Error uses a pooled estimate of error variance
Lower 95%
0.3741
0.4057
1.8325
4.0497
5.7375
Upper 95%
2.2021
2.2867
3.9718
5.8633
7.5877
Mean geosmin (ng/l)
Oneway Analysis of Mean geosmin (ng/l) By Km's From Source
10
0
00
06
45
70
78
Km's From Source
Oneway Anova
Analysis of Variance
Source
Km's From Source
Error
C. Total
DF
4
583
587
Sum of Squares
296.9090
1900.5175
2197.4265
Mean Square
74.2273
3.2599
F Ratio
22.7698
Prob > F
<.0001
Means for Oneway Anova
Level
Number
Mean
Std Error
00
126
0.37302
0.16085
06
119
0.45378
0.16551
45
92
1.47174
0.18824
70
128
1.80703
0.15959
78
123
2.05976
0.16280
Std Error uses a pooled estimate of error variance
Lower 95%
0.0571
0.1287
1.1020
1.4936
1.7400
Upper 95%
0.6889
0.7789
1.8414
2.1205
2.3795
Mean levels of both MIB and geosmin were significantly less in 1997 (x =
1.85 ng/L for MIB and x = 0.92 ng/L for geosmin respectively) than 1996 (x =
5.66 ng/L for MIB and 1.64 ng/L for geosmin respectively) (F = 74.2523, df = 1,
p = <0.0001 for MIB and F = 20.9701, df = 1, p = <0.0001 for geosmin) (Figs 20
& 21).
16
Figure 20. Oneway Analysis of Mean MIB (ng/l) By Year
30
Mean MIB (ng/l)
25
20
15
10
5
0
1996
1997
Year
Oneway Anova
Analysis of Variance
Source
Year
Error
C. Total
DF
1
586
587
Sum of Squares
2093.025
16518.184
18611.210
Mean Square
2093.03
28.19
F Ratio
74.2523
Prob > F
<.0001
Means for Oneway Anova
Level
Number
Mean
Std Error
1996
251
5.66135
0.33512
1997
337
1.84697
0.28921
Std Error uses a pooled estimate of error variance
Lower 95%
5.0032
1.2790
Upper 95%
6.3195
2.4150
Power
Alpha
0.0500
Sigma
5.30924
Delta
1.886681
Number
588
Power
1.0000
Mean geosmin (ng/l)
Figure 21. Oneway Analysis of Mean geosmin (ng/l) By Year
10
0
1996
1997
Year
Oneway Anova
Analysis of Variance
Source
Year
Error
C. Total
DF
1
586
587
Sum of Squares
75.9183
2121.5082
2197.4265
Mean Square
75.9183
3.6203
F Ratio
20.9701
Means for Oneway Anova
Level
1996
Number
251
Mean
1.64263
Std Error
0.12010
Lower 95%
1.4068
Upper 95%
1.8785
Prob > F
<.0001
17
Level
Number
Mean
Std Error
1997
337
0.91617
0.10365
Std Error uses a pooled estimate of error variance
Lower 95%
0.7126
Upper 95%
1.1197
Power
Alpha
0.0500
Sigma
1.902714
Delta
0.359323
Number
588
Power
0.9955
There was a significant correlation between the overall numbers of
cyanobacteria and MIB numbers (r = 0.50). This correlation was not as significant
between geosmin and cyanobacterial numbers (r = 0.28). There appeared to be
an inverse correlation between chlorophyte numbers and both MIB (r = -0.17)
and geosmin (r = -0.03) concentration. Principal component analysis on the
section of the canal that had the most severe taste and odor problems (i.e. the
70-78 km group) reveals that species of Lyngbya and Anabaena were most
closely correlated with geosmin concentrations while Oscillatoria sp. was most
closely correlated with concentrations of MIB (Fig. 22).
Figure 22. Principal Components on Correlations Between Cyanobacterial
Species and MIB/geosmin Concentrations from 70 – 78 km's down-canal from
Lake Pleasant.
EigenValue
2.1143
1.1122
1.0732
0.4448
0.2555
Eigenvectors
Oscillatoria
Anabaena
Lyngbya
Mean MIB (ng/l)
Mean geosmin (ng/l)
Percent
42.286
22.244
21.463
8.896
5.110
Cum Percent
42.286
64.530
85.994
94.890
100.000
0.34258
0.30756
0.25107
0.62398
0.57936
-0.14385
-0.53923
0.80889
0.13587
-0.12556
-0.76650
0.58420
0.26257
-0.01458
0.04503
0.38605
0.46257
0.23455
0.15853
-0.74623
0.35410
0.24368
0.39837
-0.75289
0.29950
18
y
Anabaen
Lyngbya
Mean ge
x
Mean MI
z
Oscilla
__
Figure 15
Oneway ANOVA for Chrysophyte Genus by Units/mL for Sites B & C During Annual
Re-Filling by the CAP Canal
14000
12000
10000
Units/mL
8000
6000
4000
2000
0
-2000
Achnanthes
Amphora
Cocconeis
Cymbella
Fragilaria Gomphonema Gyrosigma
Genus
Oneway Anova
Mean of Response
Observations (or Sum Wgts)
3381.119
67
Melosira
Navicula
Pinnularia
Pleurosigma
19
Analysis of Variance
Source
Genus
Error
C. Total
DF
10
56
66
Sum of Squares
226799384
296258173
523057557
Mean Square
22679938
5290324.5
F Ratio
4.2871
Prob > F
0.0002
Means for Oneway Anova
Level
Number
Mean
Achnanthes
3
2994.67
Amphora
4
2327.75
Cocconeis
3
3946.67
Cymbella
13
6938.00
Fragilaria
11
2843.82
Gomphonema
13
2850.08
Gyrosigma
4
2820.50
Melosira
4
1459.75
Navicula
7
1910.43
Pinnularia
3
1266.67
Pleurosigma
2
1789.50
Std Error uses a pooled estimate of error variance
Std Error
1327.9
1150.0
1327.9
637.9
693.5
637.9
1150.0
1150.0
869.3
1327.9
1626.4
Lower 95%
334.5
24.0
1286.5
5660.1
1454.6
1572.2
516.7
-844.0
168.9
-1393.5
-1468.6
Upper 95%
5654.9
4631.5
6606.9
8215.9
4233.1
4128.0
5124.3
3763.5
3651.9
3926.9
5047.6
Power Details
Test
Genus
Power
Alpha
0.0500
Sigma
2300.071
Delta
1839.855
Number
67
Power
0.9960
Principal Component Analysis and Correlations Between Lake Pleasant
Hypolimnetic Variables and MIB/Geosmin Within the Cap Canal
In order to better view the high-dimensional nature of all the variables
simultaneously, and to detect any correlations (or inverse correlations) among
these variables, principal component analysis (PCA) was performed on the data
from Lake Pleasant simultaneously with the data from the CAP canal. Since we
have proven through the previous univariate analyses that within Lake Pleasant,
site D is lower in nutrients (i.e. species of nitrogen and phosphorous) than sites
A, B, or C, site D was excluded from the PCA analyses. Additionally, since we
have also proven that MIB, geosmin, and periphytic cyanobacterial numbers
were much lower closer to Lake Pleasant (0-45 km) than areas farther removed
(70-78 km), the 0-45 km sites were also removed from these analyses. This was
done in order to answer the question "what conditions (if any) within Lake
20
Pleasant may possibly contribute the most to periphytic cyanobacterial growth in
those areas of the CAP canal that suffer from taste and odor problems
presumably due to these periphytic cyanobacteria?"
By using PCA we could begin to distinguish maximum variability in the
data cloud or in other words, what the most important gradients were and where
they were positioned within the data. We performed standardized principal
component analysis in which the mean was subtracted from the data set and
divided by the standard deviation. By doing this the centroid of the data cloud is
set to zero and the standard deviation of all variables is set to 1. This type of
PCA would therefore be considered an eigenanalysis of the correlation matrix
where the covariance of the standardized variables equals the correlation. The
Gabriel (1971) bi-plots associated with the PCA's reveal the correlations among
the chosen variables by exposing the principal component rays. These rays are
orthogonal to one another in the original high dimensional space that defines all
of the variables. However, as this space becomes forced to approximate fewer
dimensions, it becomes evident that not all of the rays are orthogonal. When the
higher dimensions are reduced into a smaller environmental space, the
correlation between all variables, even those originally thought to be orthogonal,
may come closer together with those becoming the closest exhibiting the
greatest amount of correlation.
The variables from the hypolimnion of Lake Pleasant include total
phosphorous (Tot. P), nitrogen (nitrate-N + ammonia-N), and dissolved oxygen
(D.O.) while those from the CAP canal include MIB and geosmin numbers.
21
The bi-plot and PCA performed on all of the above variables for 1996
shows a very significant correlation between MIB, total phosphorous, and
nitrogen with geosmin showing less of a correlation to both nutrients (Fig 23). It
also appears that there was an inverse correlation between dissolved oxygen
and total phosphorous and nitrogen levels within the hypolimnion of Lake
Pleasant. This inverse correlation was noticed between MIB levels within the
canal and dissolved oxygen levels within the hypolimnion of Lake Pleasant.
While geosmin shared some degree of environmental space as the hypolimnetic
nutrients and MIB, the correlation was less prominent.
For the year 1997, the correlation among nutrient levels and MIB and
geosmin production within the lower reaches of the CAP canal are not evident. It
appears that there is still an inverse correlation between MIB, geosmin, and total
phosphorous, this is not true for nitrogen that now shows a positive relationship
with dissolved oxygen and an inverse correlation with total phosphorous and
MIB/geosmin. In other words, it appears that the only clear correlation that exists
for this year is the inverse relationship between dissolved oxygen within the
hypolimnion of Lake Pleasant and both MIB and geosmin within the CAP canal.