Vol. 24, No. 2 
Page 4 
Table 1. The effect of different levels of public visitation and disturbance 
of prairie chickens on booming grounds (leks) on the subsequent nesting effort 
at Bogota. 
Year 
Blind Mornings 
Known Instances 
Blrds per Blind 
Harriers & Others 
of Flushed 
Morn i ng^- 
Human 
Number of Nests 
Found per Hen 
Observed on Leks 
1976 
46 
0.3 
1.2 
0.9 
1977 
66 
1.9 
1.2 
0.5 
1978 
26 
0.6 
1.2 
1. 1 
1979 
43 
1.2 
1.2 
0.6 
1980 
54 
1.4 
1.3 
0.4 
3 
— A blind morning represents 1 booming ground under observation from 1 or 
more blinds for 1 morning. 
Ecology and Management of White-tailed D eer - V/-37-R C. M. Nixon, 
L. P. Hansen, 
J. E. Chelsvig 
Numerous methods of analyzing hunter kill records have been proposed; many 
involve some form of life-table analysis. Modifications of 2 basic types of 
life-table analysis are being evaluated for use on the Illinois deer kill: 
cohort-specific and time-specific types. The cohort-specific life table uses 
kill records to follow the fate from birth to death of a group all born at the 
same time. The time-specific life table uses the age structure and sex ratio of 
the deer herd at a specific point in time. Unfortunately, these methods include 
assumptions seldom met by the deer-kill information available. The greatest 
deviation from the assumptions is our lack of an unbiased sample of the deer 
herd. Because of hunter selectivity, vulnerability differences among sex and 
age classes, failure of hunters to report the kill of certain sex and age 
classes, and aging errors at check s‘ations, deer-kill information does not 
truely represent herd characteristics; male deer appear to be over-represented 
and fawns are under-represented in the recorded deer harvest. Another assumption, 
especially important in predicting herd dynamics, is that reproduction and 
survival are constant. Deer-kill information probably deviates less from this 
assumption in Illinois than in some northern states because Illinois winters 
are generally not severe and food is abundant. 
The biases noted above can cause serious problems, especially in estimating 
herd size. However, if consistent in the same direction, the biases can be 
delineated by simulation techniques and reduced by mathematical methods. 
Our concern with the deer harvest analysis is not so much the determination 
of deer numbers but the prediction of trends in the deer population so that 
harvest can be adjusted accordingly. In a future newsletter we will compare the 
ability of several techniques to detect trends. 
