Key-Factor/Key-Stage Analysis for Life Table Data

Organisms are subjected to various mortality factors, each of which causes different mortality in each life stage of the organism. The factor that contributes most to the population fluctuation should be called the “key factor.” Similarly, the stage that contributes most to the population fluctuation should be called the “key stage.” The conventional key-factor analyses divide the variation of the total mortality through all stages, K, into the variation of the mortality in the ith stage, ki. These analyses identify the key stage but do not identify the key factor, unless each stage is subjected to only a single mortality factor. Hence, the conventional key-factor analyses should be called key-stage analyses. A “key-factor/key-stage analysis” is proposed by integrating the conventional key-factor analyses and ANOVA, emphasizing the importance of discriminating between the key factor and the key stage. This analysis identifies the key factor, the key stage, and the combination of factor and stage that is most influential in determining the fluctuation of total mortality.