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U.S. GEOLOGICAL SURVEY
Scientific Investigations Report 2007–5117

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Abstract

Growth and decomposition of dense blooms of Aphanizomenon flos-aquae in Upper Klamath Lake frequently cause extreme water-quality conditions that have led to critical fishery concerns for the region, including the listing of two species of endemic suckers as endangered. The Bureau of Reclamation has asked the U.S. Geological Survey (USGS) to examine water-quality data collected by the Klamath Tribes for relations with lake level. This analysis evaluates a 17-year dataset (1990–2006) and updates a previous USGS analysis of a 5-year dataset (1990–94).

Both univariate hypothesis testing and multivariable analyses evaluated using an information-theoretic approach revealed the same results—no one overarching factor emerged from the data. No single factor could be relegated from consideration either. The lack of statistically significant, strong correlations between water-quality conditions, lake level, and climatic factors does not necessarily show that these factors do not influence water-quality conditions; it is more likely that these conditions work in conjunction with each other to affect water quality. A few different conclusions could be drawn from the larger dataset than from the smaller dataset examined in 1996, but for the most part, the outcome was the same. Using an observational dataset that may not capture all variation in water-quality conditions (samples were collected on a two-week interval) and that has a limited range of conditions for evaluation (confined to the operation of lake) may have confounded the exploration of explanatory factors. In the end, all years experienced some variation in poor water-quality conditions, either in timing of occurrence of the poor conditions or in their duration. The dataset of 17 years simply provided 17 different patterns of lake level, cumulative degree-days, timing of the bloom onset, and poor water-quality conditions, with no overriding causal factor emerging from the variations.

Water-quality conditions were evaluated for their potential to be harmful to the endangered sucker species on the basis of high-stress thresholds—water temperature values greater than 28 degrees Celsius, dissolved-oxygen concentrations less than 4 milligrams per liter, and pH values greater than 9.7. Few water temperatures were greater than 28 degrees Celsius, and dissolved-oxygen concentrations less than 4 milligrams per liter generally were recorded in mid to late summer. In contrast, high pH values were more frequent, occurring earlier in the season and parallel with growth in the algal bloom.

The 10 hypotheses relating water-quality variables, lake level, and climatic factors from the earlier USGS study were tested in this analysis for the larger 1990–2006 dataset. These hypotheses proposed relations between lake level and chlorophyll‑a, pH, dissolved oxygen, total phosphorus, and water temperature. As in the previous study, no evidence was found in the larger dataset for any of these relations based on a seasonal (May–October) distribution. When analyzing only the June data, the previous 5-year study did find evidence for three hypotheses relating lake level to the onset of the bloom, chlorophyll‑a concentrations, and the frequency of high pH values in June. These hypotheses were not supported by the 1990–2006 dataset, but the two hypotheses related to cumulative degree-days from the previous study were: chlorophyll‑a concentrations were lower and onset of the algal bloom was delayed when spring air temperatures were cooler. Other relations between water-quality variables and cumulative degree-days were not significant.

In an attempt to identify interrelations among variables not detected by univariate analysis, multiple regressions were performed between lakewide measures of low dissolved-oxygen concentrations or high pH values in July and August and six physical and biological variables (peak chlorophyll‑a concentrations, degree-days, water temperature, median October–May discharge in the Williamson River, median monthly wind speed, and median monthly lake level). Model sets were developed for each combination of these factors and evaluated using an information-theoretic approach. For each water-quality measure tested, the models with the lowest Akaike Information Criterion statistics, and therefore the best fit, were the models that considered each variable individually. The variables with the best fit for dissolved oxygen were water temperature and wind speed, whereas for pH it was water temperature. Akaike weights for the remaining variables were fairly evenly distributed, indicating that there was no clear hierarchy of importance among those variables.

Although water temperature and wind speed appear to be important explanatory variables for the variance observed in different water-quality measures, no overarching variable or combination of variables was revealed. The dynamic nature of these variables and their interactions from year to year, within a season, and between sites around the lake confounds the ability to explain or predict water-quality conditions in Upper Klamath Lake. At present, no single causal factor can be clearly identified.

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