Plant competition studies designed to quantify interference between species provide valuable information on competitive interactions and on the effects of agronomic practices on those interactions. The effect of each species' density on the growth of itself and on the growth of the other species is quantified in a series of regression models. Traditionally, the models' regression coefficients have been combined in a series of ratios to quantify relative competitive ability and niche differentiation. Coefficients that are negative (positive interference—facilitation, mutualism) or zero (neutral interference or nonsignificant coefficient) do not lend themselves well to ratio-based methodology because of sign cancellation or undefined values, respectively. As a result, ratio-based methodology is limited to using only positive coefficients (negative interference—amensalism, competition). Rather than using ratios, the absolute-log method uses addition and subtraction of coefficients converted to a pseudologarithmic scale, thus allowing for use of coefficients with values that are negative or zero. As a result, the absolute-log method can be used to quantify relative competitive ability and niche differentiation involving all types of interference—negative, positive, and neutral. The absolute-log method includes an optional statistical procedure constructing confidence intervals for the estimates of relative competitive ability and niche differentiation.

Additional index words: Interference, competition, amensalism, facilitation, mutualism, Spitters, reciprocal yield law.

Abbreviations: A-A, absolute-antilog; AND, absolute-antilog function corollary to ND; ARC, absolute-antilog function corollary to RC; CI, confidence interval; LND, absolute-log method corollary to ND; LRC, absolute-log method corollary to RC; ND, niche differentiation value; RC, relative competitive ability value; SE, standard error.