12 
D. viracochi 
2.0 - 2.01 ee 
20 ——— PREDICTED 2.33.5 
ele ea ee OBSERVED 
1.4 -| 
: 
12 z 
: 
1.0 -| H 
STANDARD SCORES 
wn 
1 
Fig. 10.—Predicted versus observed abundances (standard- 
ized) for Drosophila viracochi from September, 1961 to Decem- 
ber, 1963. 
D. mesophragmatica 
STANDARD SCORES 
no 
i I 
4 
-6 
-8 
1.0 
1.2 
1.4 
1.6 
1.8 
2.0 — 
Fig. 11.—Predicted versus observed abundances (standard- 
ized) for Drosophila mesophragmatica from September, 1961 to 
December, 1963. 
tions of the predicted from the actual values (with the 
predicted values converted to raw scores), as measured 
by a Chi-square goodness-of-fit test for Drosophila pseu- 
doobscura and mesophragmatica, are highly significant; 
the fit is hardly perfect. 
Some general observations are: 
1. Common species are better modeled than rarer 
ones. 
2. Large, long-term changes can usually be pre- 
dicted, but short-term, small fluctuations cannot, 
particularly for the rarer species. 
3. The last 14 months present a better fit than the 
first 14 months. 
In a practical sense the predicted population levels 
from the above analysis are rather trivial because values 
of a set of common factors were calculated from 28 
observations on 10 variables (species) ; using these cal- 
D. brncici 
——— PREDICTED 
omens OBSERVED 
STANDARD SCORES 
Fig. 12.—Predicted versus observed abundances (standar 
ized) for Drosophila brncici from September, 1961 to Dece: 
ber, 1963. 
D. gasici 
—— PREDICTED 
OBSERVED 
STANDARD SCORES 
Fig. 13.—Predicted versus observed abundances (standa 
ized) for Drosophila gasici from September, 1961 to Decemt 
1963. 
culated factor scores, the population levels of the spec 
for each period were recalculated. However, if the fi 
tors influencing the species of a given community he 
been identified by a previous factor analysis and the 
tation properly carried out, it is possible later to mé 
measurements of the factors, standardize them, and tk 
calculate predicted standard scores for all of the spec 
of the community using a set of specification equati 
as above. I have not been able to do so with these d 
from the literature, because the factors have not be 
identified, or if they had been, no measurements 
available for them. Also, there is no way to check 
validity of the results. 
The use of these predictive equations can be illusty 
ed by a possible application. A factor-analysis study 
ried out on the community of fish in a river had det 
mined that water temperature was one of the import 
