Use of Algal Assays in Studying Eutrophication Problems
211
from 35 of their routine sampling sites on the Columbia and Snake River systems. Algal
assays, using Selenastrum capricomutum as the test species, were conducted on these
water samples. Although personnel sampling the river systems were familiar with
biological, chemical and physical conditions at the sampling sites, the laboratory
personnel conducting the assays were not. The samples were identified by number only so
that the assay results and their interpretation would not be unintentionally prejudiced.
After the assay results were submitted, the regional personnel provided us a Stream
Classification Code, based on the stream conditions at time of sampling, and special
notations concerning physical conditions at some of the sites at the time of sampling and
known discharges they were receiving. The amount of algal growth obtained in 21-day
assays of the waters collected at the various sampling sites is shown in Table 5. The table
also contains the classification of each sampling site at the time of sampling, and the
chemical analysis for ortho and total dissolved phosphorus and nitrate-nitrogen. Table 6
contains the special notations made by regional personnel relating to certain sampling
sites listed in Table 5.
It is interesting to note that the highest algal growth yields were obtained in those
samples containing relatively high nitrogen and phosphorus concentrations; namely in
waters collected at stations 153016, 153004, 153038, 543014, 153014, 543005 and
543105. Moreover, several of the sampling stations (153016, 543014, 543005 and
543105) were noted as receiving municipal effluent containing sodium tripolyphosphate
(STP), agricultural runoff, irrigation return flows, or industrial wastes. Also, the waters
collected at station 15038 supported good algal growth in the laboratory while only slight
growth was observed in the river at the time of sampling. However, it was noted that
there was excessive turbidity at the time of sampling which prevented algal growth in the
river. Thus the algal assay was capable of predicting the potential for algal growth at the
sampling site even though physical conditions at the time were such that algal growth was
prevented.
A multiple regression analysis, using the various chemical parameters as the
independent variables and the maximum algal yield in mg dry wt/1 as the dependent
variable was run to determine the nutrient having the most influence on algal growth. The
independent variables were as follows: X! = ortho phosphorus, x 2 = inorganic nitrogen,
x 3 = organic nitrogen, x 4 = soluble inorganic nitrogen, x 5 = total soluble carbon, x 6 =
dissolved iron, and x 7 = dissolved phosphorus.
In order to rank these nutrients in order of importance, a stepwise regression, both
backward and forward, was run. The order of additions was as follows: (1) dissolved
phosphorus (R
2 = 0.7984), (2) ortho phosphorus, (R
2 = 0.8155), (3) organic nitrogen
(R
2 = 0.8349), (4) soluble inorganic carbon (R
2 = 0.8472), (5) total soluble carbon (R
2 =
0.8609), (6) inorganic nitrogen (R
2 = 0.8612), and (7) iron (R
2 = 0.8613). The regression
coefficient, R
2 , indicates how much of the variability is explained at that time. That is,
with only one independent variable, dissolved phosphorus, 79.84 percent of the
variability in algal growth in the samples was explained. When ortho phosphorus was
added, the amount of variability increased to 81.56 percent. For all independent variables
together, R
2 = 0.8613, and indicates that other unknown variables have an influence of
13.87 percent on the variability. Dissolved phosphorus alone, therefore, explained 79.84
percent of the variability and the other six nutrients only increased this by 6.29 percent.
Thus dissolved phosphorus was by far the most important nutrient in determining the
maximum algal yield.
211
from 35 of their routine sampling sites on the Columbia and Snake River systems. Algal
assays, using Selenastrum capricomutum as the test species, were conducted on these
water samples. Although personnel sampling the river systems were familiar with
biological, chemical and physical conditions at the sampling sites, the laboratory
personnel conducting the assays were not. The samples were identified by number only so
that the assay results and their interpretation would not be unintentionally prejudiced.
After the assay results were submitted, the regional personnel provided us a Stream
Classification Code, based on the stream conditions at time of sampling, and special
notations concerning physical conditions at some of the sites at the time of sampling and
known discharges they were receiving. The amount of algal growth obtained in 21-day
assays of the waters collected at the various sampling sites is shown in Table 5. The table
also contains the classification of each sampling site at the time of sampling, and the
chemical analysis for ortho and total dissolved phosphorus and nitrate-nitrogen. Table 6
contains the special notations made by regional personnel relating to certain sampling
sites listed in Table 5.
It is interesting to note that the highest algal growth yields were obtained in those
samples containing relatively high nitrogen and phosphorus concentrations; namely in
waters collected at stations 153016, 153004, 153038, 543014, 153014, 543005 and
543105. Moreover, several of the sampling stations (153016, 543014, 543005 and
543105) were noted as receiving municipal effluent containing sodium tripolyphosphate
(STP), agricultural runoff, irrigation return flows, or industrial wastes. Also, the waters
collected at station 15038 supported good algal growth in the laboratory while only slight
growth was observed in the river at the time of sampling. However, it was noted that
there was excessive turbidity at the time of sampling which prevented algal growth in the
river. Thus the algal assay was capable of predicting the potential for algal growth at the
sampling site even though physical conditions at the time were such that algal growth was
prevented.
A multiple regression analysis, using the various chemical parameters as the
independent variables and the maximum algal yield in mg dry wt/1 as the dependent
variable was run to determine the nutrient having the most influence on algal growth. The
independent variables were as follows: X! = ortho phosphorus, x 2 = inorganic nitrogen,
x 3 = organic nitrogen, x 4 = soluble inorganic nitrogen, x 5 = total soluble carbon, x 6 =
dissolved iron, and x 7 = dissolved phosphorus.
In order to rank these nutrients in order of importance, a stepwise regression, both
backward and forward, was run. The order of additions was as follows: (1) dissolved
phosphorus (R
2 = 0.7984), (2) ortho phosphorus, (R
2 = 0.8155), (3) organic nitrogen
(R
2 = 0.8349), (4) soluble inorganic carbon (R
2 = 0.8472), (5) total soluble carbon (R
2 =
0.8609), (6) inorganic nitrogen (R
2 = 0.8612), and (7) iron (R
2 = 0.8613). The regression
coefficient, R
2 , indicates how much of the variability is explained at that time. That is,
with only one independent variable, dissolved phosphorus, 79.84 percent of the
variability in algal growth in the samples was explained. When ortho phosphorus was
added, the amount of variability increased to 81.56 percent. For all independent variables
together, R
2 = 0.8613, and indicates that other unknown variables have an influence of
13.87 percent on the variability. Dissolved phosphorus alone, therefore, explained 79.84
percent of the variability and the other six nutrients only increased this by 6.29 percent.
Thus dissolved phosphorus was by far the most important nutrient in determining the
maximum algal yield.