Alternative community analyses, based on quantitative and presence/absence
data, are comparable logically if the data type is the only factor responsi
ble for differences among results. For presence/absence indices that consid
er mutual absences, no quantitative alternatives are known. To facilitate s
uch comparisons, a new family of similarity coefficients is proposed for ab
undance data. Formally, this extension is achieved by generalizing the four
cells of the usual 2 x 2 contingency table to the quantitative case. This
implies an expanded meaning of absence: for a given species at a given site
it is understood as the difference between the actual value and the maximu
m detected in the entire study. The correspondence between 10 presence/abse
nce coefficients and their quantitative counter-parts is evaluated by graph
ical comparisons based on artificial data. The behaviour of the new functio
ns is also examined using field data representing post-fire regeneration pr
ocesses in grasslands and a chronosequence pertaining to forest regeneratio
n after clear-cut. The examples suggest that the new coefficients are most
informative for data sets with low beta-diversity and temporal back-ground
changes.