Difference between revisions of "NISER 081107 ID Data"

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==Data Overview==
 
==Data Overview==
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[[Image:Largemouth_Bass.jpg|150px|thumbnail|right| [http://en.wikipedia.org/wiki/Largemouth_Bass Largemouth Bass] ]]
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Largemouth bass were studied in 53 different Florida lakes to examine the factors that influence the level of mercury contamination. Water samples were collected from the surface of the middle of each lake in August 1990 and then again in March 1991. The pH level, the amount of chlorophyll, calcium, and alkalinity were measured in each sample. The average of the August and March values were used in the analysis. Next, a sample of fish was taken from each lake with sample sizes ranging from 4 to 44 fish. The age of each fish and mercury concentration in the muscle tissue was measured. (Note: Since fish absorb mercury over time, older fish will tend to have higher concentrations). Thus, to make a fair comparison of the fish in different lakes, the investigators used a regression estimate of the expected mercury concentration in a three year old fish as the standardized value for each lake. Finally, in 10 of the 53 lakes, the age of the individual fish could not be determined and the average mercury concentration ofthe sampled fish was used instead of the standardized value. ([[NISER_081107_ID_Data#References | Reference: Lange, Royals, & Connor. (1993)]])
 
Largemouth bass were studied in 53 different Florida lakes to examine the factors that influence the level of mercury contamination. Water samples were collected from the surface of the middle of each lake in August 1990 and then again in March 1991. The pH level, the amount of chlorophyll, calcium, and alkalinity were measured in each sample. The average of the August and March values were used in the analysis. Next, a sample of fish was taken from each lake with sample sizes ranging from 4 to 44 fish. The age of each fish and mercury concentration in the muscle tissue was measured. (Note: Since fish absorb mercury over time, older fish will tend to have higher concentrations). Thus, to make a fair comparison of the fish in different lakes, the investigators used a regression estimate of the expected mercury concentration in a three year old fish as the standardized value for each lake. Finally, in 10 of the 53 lakes, the age of the individual fish could not be determined and the average mercury concentration ofthe sampled fish was used instead of the standardized value. ([[NISER_081107_ID_Data#References | Reference: Lange, Royals, & Connor. (1993)]])
  

Revision as of 18:21, 24 June 2008

Multi-disciplinary NISER activity - Mercury in Bass - Dataset

Data Overview

Largemouth bass were studied in 53 different Florida lakes to examine the factors that influence the level of mercury contamination. Water samples were collected from the surface of the middle of each lake in August 1990 and then again in March 1991. The pH level, the amount of chlorophyll, calcium, and alkalinity were measured in each sample. The average of the August and March values were used in the analysis. Next, a sample of fish was taken from each lake with sample sizes ranging from 4 to 44 fish. The age of each fish and mercury concentration in the muscle tissue was measured. (Note: Since fish absorb mercury over time, older fish will tend to have higher concentrations). Thus, to make a fair comparison of the fish in different lakes, the investigators used a regression estimate of the expected mercury concentration in a three year old fish as the standardized value for each lake. Finally, in 10 of the 53 lakes, the age of the individual fish could not be determined and the average mercury concentration ofthe sampled fish was used instead of the standardized value. ( Reference: Lange, Royals, & Connor. (1993))

Data Description

  • Number of cases: 53
  • Variable Names:
  1. ID: ID number
  2. Lake: Name of the lake
  3. Alkalinity: Alkalinity (mg/L as Calcium Carbonate)
  4. pH: pH
  5. Calcium: Calcium (mg/l)
  6. Chlorophyll: Chlorophyll (mg/l)
  7. Avg_Mercury: Average mercury concentration (parts per million) in the muscle tissue of the fish sampled from that lake
  8. No.samples: How many fish were sampled from the lake
  9. min: Minimum mercury concentration amongst the sampled fish
  10. max: Maximum mercury concentration amongst the sampled fish
  11. 3_yr_Standard_mercury: Regression estimate of the mercury concentration in a 3 year old fish from the lake (or = Avg Mercury when age data was not available)
  12. age_data: Indicator of the availability of age data on fish sampled

Data Table

ID Lake Alkalinity pH Calcium Chlorophyll Avg_Mercury No.samples min max 3_yr_Standard_Mercury age_data
1 Alligator 5.9 6.1 3 0.7 1.23 5 0.85 1.43 1.53 1
2 Annie 3.5 5.1 1.9 3.2 1.33 7 0.92 1.9 1.33 0
3 Apopka 116 9.1 44.1 128.3 0.04 6 0.04 0.06 0.04 0
4 Blue Cypress 39.4 6.9 16.4 3.5 0.44 12 0.13 0.84 0.44 0
5 Brick 2.5 4.6 2.9 1.8 1.2 12 0.69 1.5 1.33 1
6 Bryant 19.6 7.3 4.5 44.1 0.27 14 0.04 0.48 0.25 1
7 Cherry 5.2 5.4 2.8 3.4 0.48 10 0.3 0.72 0.45 1
8 Crescent 71.4 8.1 55.2 33.7 0.19 12 0.08 0.38 0.16 1
9 Deer Point 26.4 5.8 9.2 1.6 0.83 24 0.26 1.4 0.72 1
10 Dias 4.8 6.4 4.6 22.5 0.81 12 0.41 1.47 0.81 1
11 Dorr 6.6 5.4 2.7 14.9 0.71 12 0.52 0.86 0.71 1
12 Down 16.5 7.2 13.8 4 0.5 12 0.1 0.73 0.51 1
13 Eaton 25.4 7.2 25.2 11.6 0.49 7 0.26 1.01 0.54 1
14 East Tohopekaliga 7.1 5.8 5.2 5.8 1.16 43 0.5 2.03 1 1
15 Farm-13 128 7.6 86.5 71.1 0.05 11 0.04 0.11 0.05 0
16 George 83.7 8.2 66.5 78.6 0.15 10 0.12 0.18 0.15 1
17 Griffin 108.5 8.7 35.6 80.1 0.19 40 0.07 0.43 0.19 1
18 Harney 61.3 7.8 57.4 13.9 0.77 6 0.32 1.5 0.49 1
19 Hart 6.4 5.8 4 4.6 1.08 10 0.64 1.33 1.02 1
20 Hatchineha 31 6.7 15 17 0.98 6 0.67 1.44 0.7 1
21 Iamonia 7.5 4.4 2 9.6 0.63 12 0.33 0.93 0.45 1
22 Istokpoga 17.3 6.7 10.7 9.5 0.56 12 0.37 0.94 0.59 1
23 Jackson 12.6 6.1 3.7 21 0.41 12 0.25 0.61 0.41 0
24 Josephine 7 6.9 6.3 32.1 0.73 12 0.33 2.04 0.81 1
25 Kingsley 10.5 5.5 6.3 1.6 0.34 10 0.25 0.62 0.42 1
26 Kissimmee 30 6.9 13.9 21.5 0.59 36 0.23 1.12 0.53 1
27 Lochloosa 55.4 7.3 15.9 24.7 0.34 10 0.17 0.52 0.31 1
28 Louisa 3.9 4.5 3.3 7 0.84 8 0.59 1.38 0.87 1
29 Miccasukee 5.5 4.8 1.7 14.8 0.5 11 0.31 0.84 0.5 0
30 Minneola 6.3 5.8 3.3 0.7 0.34 10 0.19 0.69 0.47 1
31 Monroe 67 7.8 58.6 43.8 0.28 10 0.16 0.59 0.25 1
32 Newmans 28.8 7.4 10.2 32.7 0.34 10 0.16 0.65 0.41 1
33 Ocean Pond 5.8 3.6 1.6 3.2 0.87 12 0.31 1.9 0.87 0
34 Ocheese Pond 4.5 4.4 1.1 3.2 0.56 13 0.25 1.02 0.56 0
35 Okeechobee 119.1 7.9 38.4 16.1 0.17 12 0.07 0.3 0.16 1
36 Orange 25.4 7.1 8.8 45.2 0.18 13 0.09 0.29 0.16 1
37 Panasoffkee 106.5 6.8 90.7 16.5 0.19 13 0.05 0.37 0.23 1
38 Parker 53 8.4 45.6 152.4 0.04 4 0.04 0.06 0.04 0
39 Placid 8.5 7 2.5 12.8 0.49 12 0.31 0.63 0.56 1
40 Puzzle 87.6 7.5 85.5 20.1 1.1 10 0.79 1.41 0.89 1
41 Rodman 114 7 72.6 6.4 0.16 14 0.04 0.26 0.18 1
42 Rousseau 97.5 6.8 45.5 6.2 0.1 12 0.05 0.26 0.19 1
43 Sampson 11.8 5.9 24.2 1.6 0.48 10 0.27 1.05 0.44 1
44 Shipp 66.5 8.3 26 68.2 0.21 12 0.05 0.48 0.16 1
45 Talquin 16 6.7 41.2 24.1 0.86 12 0.36 1.4 0.67 1
46 Tarpon 5 6.2 23.6 9.6 0.52 12 0.31 0.95 0.55 1
51 Tohopekaliga 25.6 6.2 12.6 27.7 0.65 44 0.3 1.1 0.58 1
47 Trafford 81.5 8.9 20.5 9.6 0.27 6 0.04 0.4 0.27 0
48 Trout 1.2 4.3 2.1 6.4 0.94 10 0.59 1.24 0.98 1
49 Tsala Apopka 34 7 13.1 4.6 0.4 12 0.08 0.9 0.31 1
50 Weir 15.5 6.9 5.2 16.5 0.43 11 0.23 0.69 0.43 1
52 Wildcat 17.3 5.2 3 2.6 0.25 12 0.15 0.4 0.28 1
53 Yale 71.8 7.9 20.5 8.8 0.27 12 0.15 0.51 0.25 1

References




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