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2009-06-24_PERMIT FILE - C1981019A (3)
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2009-06-24_PERMIT FILE - C1981019A (3)
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Last modified
8/24/2016 3:48:08 PM
Creation date
9/28/2009 10:40:47 AM
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Template:
DRMS Permit Index
Permit No
C1981019A
IBM Index Class Name
Permit File
Doc Date
6/24/2009
Section_Exhibit Name
4.15 Revegetation Requirements
Media Type
D
Archive
Yes
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accordance with the Cochran formula (below) for determining sample adequacy, whereby <br />the population is estimated to within 10% of the true mean (µ) with 90% confidence. For <br />woody plant density, the estimate is to within 15% of the true mean. <br />When the inequality (nmin <_ n) is true, sampling is deemed adequate; and nmin is <br />determined as follows: <br />nmin = (t2 S2) l (d X )2 <br />where: n = the number of actual samples collected (initial size = 15 or 20) <br />t = the value from the one-tailed t distribution for 90% confidence with n-1 <br />degrees of freedom (a value of approximately 1.3); <br />S2 = the variance of the estimate as calculated from the initial samples; <br />d = precision (0.10 for cover and production or 0.15 for woody plant density; <br />X = the mean of the estimate as calculated from the initial samples. <br />If the initial samples do not provide a suitable estimate of the mean (i.e., the inequality is <br />false), additional samples should be collected until the inequality (nmin < n) becomes <br />true. However, where sampling is for managerial (monitoring) information, adequacy is <br />not necessary and is calculated for informational purposes only. <br />If reverse-null testing will be utilized to document success, then in accordance with Rule <br />4.15.11 (2) (c) a minimum of 30 samples must be collected and a demonstration of <br />sample adequacy is not necessary. In this circumstance a two-sample reverse null t-test is <br />mandated along with Satterthwaite approximated degrees of freedom and standard error. <br />However, if an adequate sample can be obtained from the reference area, then a less <br />complex one-sample t-test may be utilized. With the reverse null test, the smaller the <br />variance (given by extra sampling) the better the chances of passing closely matched <br />parameters. <br />For certain statistical demonstrations of woody plant density, documentation of sampling <br />adequacy is often problematic, hence Rule 4.15.11 (3) may be used in lieu of Rule <br />4.15.11 (2). Rule 4.15.11 (3) (a) is a reverse-null approach based on the median and <br />requires a minimum of 30 samples. Rule 4.15.11 (3) (b) allows direct comparison with <br />standards if a statistically adequate sample cannot be demonstrated in accordance with <br />Rule 4.15.11 (2) (a), however, a minimum of 75 samples with a minimum quadrat size of <br />100 m2 is required (equivalent to total enumeration of 1.85 acres). Rule 4.15.11 (3) (c) is <br />a standard-null approach based on determination of a "running mean" and a minimum of <br />40 samples is required. <br />Success Evaluation <br />To summarize, success evaluations involve either a direct or a statistical t-test <br />comparison of appropriate parameters for each variable of interest (cover, production, <br />4.15-33 Revision Date: 3/14/08 <br />Revision No.: TR-72
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