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On Modeling Density‐Independent Population Change
Author(s) -
Brockelman Warren Y.,
Fagen Robert M.
Publication year - 1972
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.2307/1934313
Subject(s) - density dependence , randomness , statistics , mathematics , independence (probability theory) , statistic , principal component analysis , population , population density , regression , econometrics , statistical physics , physics , demography , sociology
Several recent papers have shown that when statistical and graphical tests for regulation are applied to artificially generated "density—independent" populations containing random variables, enigmatic evidence for regulation (density dependence) is obtained. In one instance, density independence is confused with randomness of population size. In the other instances, Morris's method of regressing log N t + 1 on log N t yields evidence of regulation in density—independent populations. It is shown here that regression analysis is inappropriate in Morris's test, and that the principal error axis rather than the regression line yields the slope tending toward unity in the absence of regulation. However, the sensitivity of the slope of the principal axis to density dependence depends on the amount of initial displacement from equilibrium and on the number of serial samples. Hence, this statistic is of little usefulness. The effect of serial correlation on tests for the presence of density dependence is discussed briefly.