Investigation of the humic hypothesis using high resolution transects in Upper Klamath Lake, Oregon

John Rueter1, Rich Miller1, Kit Rouhe1, Stan Geiger2

1Portland State University, 2Aquatic Scientific Resources

ABSTRACTAlthough there is strong evidence that the general eutrophic status of Upper Klamath Lake is determined by the annual phosphorus loading, the timing and the nature of the algal blooms may be controlled by additional factors. We explored the hypothesis that the dominant blue-green alga in the lake, Aphanizomenon flos-aquae (AFA), is inhibited by marsh derived humic-rich water. We addressed this hypothesis by comparing the photosynthetic properties of AFA with proxies for dissolved humic material along high resolution transects between marsh water and open water. Photosynthetic properties included photosynthetic efficiency (Fv/Fm), photosynthesis vs. light, phycocyanin fluorescence, and chlorophyll a fluorescence. Dissolved organic carbon and dissolved color were used as proxies for humic material. Temperature, pH, conductivity, dissolved oxygen, extracted chlorophyll a, extracted phycocyanin, and AFA cell counts were also measured along the transects. Results indicate there was no gradient in humic material from marsh to open water. However, the high resolution transects were able to detect ecologically significant patterns that would have been missed by other sampling protocols.

INTRODUCTIONDescription of Upper Klamath Lake - According to the "Atlas of Oregon Lakes", Upper Klamath Lake (UKL) is large (250 km2), shallow (average depth is about 4 meters), and hypereutrophic. Although the lake is natural, the outflow and seasonal height is controlled by a dam. UKL sits at 1261 meters above sea level in a very large (9415 km2) and diverse watershed that includes Crater Lake, Klamath Marsh, Sycan Marsh, farming, rangeland and forests. The lake is used for irrigation, power, wildlife and recreation. Wildlife concerns are particularly critical because the Klamath Basin is the highest biodiversity region in Oregon and UKL is the habitat for several protected fish species. The region has been heavily changed over the last hundred years including reclamation of eighty percent of the original marsh area behind dikes for farming. These efforts also changed the shore line and the relationship between the open water and marsh areas of the lake system. Naturally high levels of phosphorus in the watershed have contributed to UKL being hypereutrophic (Johnson et al. 1985). Blooms of Aphanizomenon flos-aquae (AFA) create excessive chlorophyll concentrations and the decay of the bloom can cause anoxia. These conditions are detrimental to protected fish populations in the lake itself and downstream in the Klamath River system. High densities of AFA are not all bad. AFA is harvested by commercial operations and sold as human nutritional supplement.Several restoration alternatives have been considered and attempted in the past including keeping the water level higher during the summer and dredging a channel that could increase flushing rates out of certain areas. The current management plan is a comprehensive attempt to decrease phosphorus loading to the lake (Oregon DEQ). It is acknowledged that this is a long term solution that might take several years to many decades to show any increase in lake water quality.The Humic Hypothesis - One alternative hypothesis for control or shared-control of lake algal densities is that humic-rich water flowing out of marshes may suppress early growth of AFA. Growth simulation models (that include grazing on filaments by Daphnia) demonstrate that even with only a 30% reduction in the growth rate of AFA filaments early in the season, can lead to a 50 % reduction in the eventual bloom size. There are several possible mechanisms for suppression of AFA growth that are being explored in culture and limno-corrals by our group and other investigators. The focus of this study was to attempt to demonstrate that we could detect patterns of AFA distribution and photosynthetic characteristics with respect to water chemistry characteristics that indicate humic concentration and humic reactivity.

METHODSHigh Resolution Transects - We sampled Upper Klamath Lake on four different days and performed seven high resolution transects in Shoalwater Bay. A suite of in-situ measurements were all tied to GPS location through data logging. Eight other analyses were performed on point samples taken at ten locations along the transect. Boat speed was one meter per second along the transects.

The results from this work illustrate the importance of understanding the hydrodynamic mixing and circulation patterns in the lake. They also show that transect data is very important in UKL due to mixing, scale variability and temporal variability. Physical processes tie together the time scales of biological and chemical processes with the time and space scales of monitoring. We are presently collaborating with Tammy Wood, USGS, on this issue.

Implications for lake management - Management of Upper Klamath Lake must address values and scientific information simultaneously. In such cases, science needs to be driven by social needs but the social understanding of the problem itself changes with advances in knowledge. There are no correct answers, but some paths of science and policy may be more productive than others. The main contributions from the scientific community are 1) to generate new alternative potential solutions and 2) to help assess the success and failures of current activities. These two contributions work together, failures often suggest new alternatives. Generation of new alternatives is crucial for environmental problems (O'Brien 2000). Problems that seemed to be just risk assessment or risk management turned out be much more complicated with unintended consequences. For example, one of the unintended consequences that should be guarded against in this lake is the potential that shifting the nutrients or community structure could result in replacement of the current strains of AFA by toxic cyanobacterial strains that could disrupt the entire region. No matter what management framework is adopted, more information will be required.This work has focused on providing practical alternatives to current standard practice. We are well aware of the time and cost limitations imposed on these studies. Using transects in addition to point measurements is more work. Whenever a new method is adopted it can greatly increase the workload; you have to do the standard method plus the new method in order to compare them. However, automated data capture from devices such as the SCUFA and Cyclops directly linked to time and GPS allows us to study the spatial features at the appropriate scale. Additional linking of these transects data to satellite or remote sensing can provide information on larger scales.

REFERENCESanon. Overview of the Upper Klamath Lake and Agency Lake TMDL, Oregon Department of Environmental Quality: 24 pages.

Johnson, D. M., Richard R. Petersen, D.Richard Lycan, James W. Sweet, Mark E. Neuhaus, and Andrew L. Schaedel (1985). Atlas of Oregon Lakes. Corvalliis, Oregon, Oregon State University Press.

O'Brien, M. (2000). Making Better Environmental Decisions: An alternative to risk assessment. Cambridge, MA, MIT Press.

ACKNOWLEDGEMENTSThis work was supported by a grant from the US Fish and Wildlife Service through the Hatfield Restoration Office.

CONTACT INFORMATIONJohn Rueter rueterj@pdx.eduRich Miller richm@pdx.eduKit Rouhe arouhe@pdx.eduStan Geiger s-dgeiger@comcast.net

(a) (b) (c)

Figure 1. (a) Remote sensing image of Upper Klamath Lake taken on June 25, 1995 by the Bureau of reclamation. High chlorophyll concentration is shown in red. The box indicates Shoalwater Bay, the study site for this research. (b) View of Pelican Butte from Upper Klamath Lake. (c) Expanded view of Shoalwater Bay. The transects marked 4 and 7 are the data collection sites for this study. Transect 8/1/06 was taken to catalog the variability of blooms away from a marsh.

Transect 4 Transect 7

Figure 2. (a) Panel of data collected from transect 4 on June 6, 2006. (b) Panel of data collected from transect 7 on June 8, 2006. Both panels show data trends from the marsh (distance zero) to the lake (distance 1000m). Fv/Fm (on the bottom graph of each panel) is the ratio of the difference between a cells maximum and minimum fluorescence over a cells maximum fluorescence. A high value of Fv/Fm for any cell indicates a healthy rate of photosynthesis. The two transects, taken on different days, show a transition point in the center of the transect. With the exception of Fv/Fm from transect 4 and DOC from transect 4 and 7, all of the data reflects the transition. This is believed to be the point of change from marsh water effects to lake water dominance.

Table 1. Data collection methods and time intervals along transects.

Sample Type Parameter Method

Distance (frequency)

In situ Location Differentially corrected GPS 1.4 m (1 sec)Inv vivo chlorophyll a fluorescence Turner Designs SCUFA 1.4 m (1 sec)Turbidity Turner Designs SCUFA 1.4 m (1 sec)Inv vivo phycocyanin fluorescence Turner Designs CYCLOPS 1.4 m (1 sec)Conductivity Hydrolab Sonde 5 8.4 m (6 sec)Luminescent dissolved oxygen Hydrolab Sonde 5 8.4 m (6 sec)pH Hydrolab Sonde 5 8.4 m (6 sec)Temperature Hydrolab Sonde 5 8.4 m (6 sec)

Point AFA colonies Microscope counts 100 mChlorophyll a Acetone extraction 100 mElectron transport vs. light (ETR) Walz PAM fluorometer 100 mPAM F - Fv/Fm Walz PAM fluorometer 100 mDissolved color Spectrophometer scan from 250-500 nm 100 mDissolved organic carbon (TDN) Combustion to CO2 and NDIR detection 100 mTotal dissolved nitrogen (TDN) Combustion to N2 and chemiluminescent detection 100 m

19

20

21

22

Temperature

(C)

5.0

5.1

5.2

5.3

5.4

5.5

5.6

5.7

DOC (mg/l),

Reactivity index

7.8

7.9

8.0

8.1

8.2

8.3

8.4

pH (units)

97

98

99

100

101

102

103

Oxygen saturation (%)

100

110

120

130

140

150

160

170

180

190

200

-100 100 300 500 700 900 1100

Distance along transect (m)

In vivo chlorophyll a fluorescence (mV)

0

0.2

0.4

0.6

0.8

1

1.2

FV:FM

0

50

100

150

200

250

300

350

400

450

500

In vivo phycocyanin fluorescence (mV)

0

2

4

6

8

10

12

14

16

18

Extracted chlorophyll a (ug/l)

18.1

18.2

18.3

18.4

18.5

18.6

18.7

18.8

18.9

19.0

Temperature

(C)

5.00

5.10

5.20

5.30

5.40

5.50

5.60

5.70

5.80

5.90

6.00

DOC (mg/l),

Reactivity index

80

100

120

140

160

180

200

-100 100 300 500 700 900 1100

Distance along transect (m)

in vivo chlorophyll a fluorescence (mV)

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

FV:FM

0

200

400

600

800

1000

1200

in vivo phycocyanin fluorescence (mV)

0

5

10

15

20

25

30

35

40

45

50

Extracted chlorophyll a (ug/l)

7.0

7.1

7.2

7.3

7.4

7.5

7.6

pH (units)

86

88

90

92

94

96

98

100

102

104

Oxygen saturation (%)

y = 0.0967x - 0.0743

R2 = 0.8452

0

5

10

15

20

25

30

35

40

45

0 100 200 300 400

In situ phycocyanin fluorescence (mV)

Chlorophyll a (ug/l)

0

5

10

15

20

25

30

35

40

45

0 100 200 300 400

In situ chlorophyll fluorescence (mV)

Chlorophyll a (ug/l)

4.5

5

5.5

6

6.5

0.07 0.08 0.09 0.1 0.11

Color (absorbance/cm @ 325 nm)

NPOC (mg/l)

RESULTSShoalwater Bay-transect #4 – The four panels show the transect data for eight of the thirteen parameters that were measured. The GPS data was used to determine the distance along the transect. Several observations can be made from these comparisons:

DOC and the humic reactivity index do not clearly trend with distance away from the marsh. Extracted chlorophyll a values are more closely related to in vivo phycocyanin

fluorescence than in vivo chlorophyll fluorescence (Figure 3). In vivo fluorescence measurements vary at a small spatial scale. This may be due to the distribution of AFA colonies in the small volume sampled by the detector in these two devices. Changes in percent oxygen saturation and pH follow each other very closely. Fv/Fm values are fairly stable throughout the transect

Shoalwater Bay – transect#7 - The four panels show the transect data for eight of the thirteen parameters that were measured. The GPS data was used to determine the distance along the transect. Several observations can be made from these comparisons:

DOC and the humic reactivity index are variable throughout the length of the transect. Extracted chlorophyll a values are more closely related to in vivo phycocyanin

fluorescence than in vivo chlorophyll fluorescence. Changes in percent oxygen saturation and pH do not co-vary. Fv/Fm values become extremely variable over the last half of the transect.

DISCUSSIONObservation of ecological significant patterns - Upper Klamath Lake is very complex environment that requires more observations to understand the patterns. We were able to “see” several structures that would have been missed by either long-term stationary sites, remote sensing, or intensive physiological studies at just one point. In transect #4 there is a 0.3 pH unit change in about 100 meters and in transect #7 there is a dip in dissolved oxygen by 4% over 100 meters. Both of these features would have been missed even with our 10 point samples along the transects.

Relative scale of processes and monitoring- Matching the temporal and spatial scale of biological and physical processes with the appropriate scales of monitoring or observation is crucial to effective research. For example, algal photoadaption and photoinhibition occur over minutes to hours while net population growth or crash may take two to ten days (Figure 4a). These processes require different observational approaches. Current USGS water quality monitoring at stations spaced kilometers apart are appropriate for detecting seasonal and large scale trends. Our research addresses processes that occur at smaller spatial scales and shorter time scales. For example, the remote image of chlorophyll distribution shows high variability over 100s of meters to kilometer scale in the lake (Figure 1). Our HRT data from the deep trench, just west of Eagle Point, shows a dramatic variation in phycocyanin fluorescence and dissolved oxygen at a small spatial scale (0.6 mg/l DO change in just 2 meters) that would not be detected with data from USGS monitoring stations (Figure 4b).

Figure 4. (a) Temporal and spatial scales of some physical and biological processes in Upper Klamath Lake. (b) Transect data collected on 8/1/06 at the deep trench near Eagle Point.

Figure 3. Relationships between NPOC and dissolved color (top), in vivo phycocyanin fluorescence and extracted chlorophyll a (middle), and in vivo chlorophyll fluorescence and extracted chlorophyll a (bottom).

0

50

100

150

200

250

0 500 1000 1500 2000 2500

Distance along transect

Phycocyanin fluorescence (mV)

75

100

125

150

175

200

Oxygen saturation (%)

Close – up of AFA and foam on UKL

(a) (b)