APPCOR12139

• Permit No: C1981025
• IBM Index Class Name: Application Correspondence
• Doc Date: 4/21/1981
• Doc Name: MEMO OSM VEGETATION COMMENTS ON PRELIMINARY ADEQUACY REVIEW OF SNOWMASS COAL CO PERMIT
• From: MLR
• To: BEN YOUNG
• Media Type: D
• Archive: No

S TAT[ or COLORADO au'.Nnun u.~.Gnv c~~~o~
DEPARTMENT OF NATURAL gESOURCES
D. Monte Pascoe, Executive Director
MllVED LAND RF.I~LAMA'CION
423 Centennial Building, 1313 Sherman Street
Denver, Colorado 80203 Tel. [phone]
III IIIIIIIII
999 IIIIIII
r
David C. Shelton
Director
April 21, 1981
T0: $9b-tTdd9"~ den Yo u n c~
FROM: 44ichael S. Savage
SUBJECT: OSM Vegetation Comments on Preliminary Adequacy Review of
Snowmass Coal Company Permit Application
Our File No. C-025-81
I find that I cannot concur with the large majority of OSM's comments relative '
to the P,A,R. I will respond to each comment on a point by point basis.
1. Snowmass has indicated in Table 3.1-1 the acreage of each vegetation type.
'The extent of surface disturbance in each type can be easily determined by
calculus or the use of a planimeter.
2. OSM's concern in this comment is not clear. If they are refering to my
request for sample locations, I wish to determine whether adequate representation
of a sampling unit has taken place based on abiotic factors such as slope,
aspect and soil type.
3. This comment is entirely correct. A typographic omission has been committed.
The formula should read:
S-_-
_ ~- + -P-
xlx2 nl n2
In addition the State requests all applicants to provide a statistical
demonstration of the comparability of reference and premine areas. The
applicant m~~y provide this in any of the standard formats. If not present I
request a t-test. Relative to the rigor of the t-test. I refer OSM to Zar
(1974):
"The two-sample t test assumes, by dint of its underlying theory,
that both samples came at random from normal populations with equal
variances. The biological researcher cannot, however, always be assured
that these assumptions are correct. Fortunately, numerous studies
have shown that the t test is robust enough to stand considerable
departures from its theoretical assumptions. especially if the sample
areaa are a uai ur pearl a ua1, gnu es eciati when ~wu-~aireu n u~ne~i
are_con_sidered e.g., Boneau, 1960; Box, 1953; Cochran, 1947. If the
underlying populations are markedly skewed, then one should be wary of
one-tailed testing, and if there is considerable nonnormality in the
populations, then very small significance levels (say, a < 0.01) should
not be depended upon. Equal variances appear to be generally the more
important of the two assumptions, and thus some authors have recommended