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We turn now to look in more detail at the patterns of birth and death in a variety of life cycles, and at how these patterns are quantified. Often, in order to monitor and examine changing patterns of mortality with age or stage, a life table may be drawn up. This allows a survivorship curve to be constructed, which traces the decline in numbers, over time, of a group of newly born or newly emerged individuals or modules. It can also be thought of as a plot of the probability, for a representative newly born individual, of surviving to various ages. Patterns of birth amongst individuals of different ages are often monitored at the same time as life tables are constructed. These patterns are displayed in age‐specific fecundity schedules.

The underlying principles are explained in Figure 4.9. There, a population is portrayed as a series of diagonal lines, each line representing the life ‘track’ of an individual. As time passes, each individual ages (moves from bottom‐left to top‐right along its track) and eventually dies (the dot at the end of the track). Here, individuals are classified by their age. In other cases it may be more appropriate to split the life of each individual into different developmental stages.

Figure 4.9 Derivation of cohort and static life tables. See text for details.

Time is divided into successive periods: t₀, t₁, etc. In the present case, three individuals were born (started their life track) prior to the time period t₀, four during t₀, and three during t₁. To construct a cohort life table, we direct our attention to a particular cohort and monitor what happens to them subsequently. Here we focus on those born during t₀. The life table is constructed by noting the number surviving to the start of each time period. So, four were there at the beginning of t₁, two of the four survived to the beginning of t₂; only one of these was alive at the beginning of t₃; and none survived to the start of t₄. The first data column of a cohort life table for these individuals would thus comprise the series of declining numbers in the cohort: 4, 2, 1, 0.

A different approach is necessary when we cannot follow cohorts but we know the ages of all the individuals in a population (perhaps from some clue such as the condition of the teeth in a species of deer). We can then, as the figure shows, direct our attention to the whole population during a single period (in this case, t₁) and note the numbers of survivors of different ages in the population. These may be thought of as entries in a life table if we assume that rates of birth and death are, and have previously been, constant – a very big assumption. What results is called a static life table. Here, of the 11 individuals alive during t₁, five were actually born during t₁ and are hence in the youngest age group, four were born in the previous time interval, two in the interval before that, and none in the interval before that. The first data column of the static life table thus comprises the series 5, 4, 2, 0. This amounts to saying that over these time intervals, a typical cohort will have started with five and declined over successive time intervals to four, then two, then zero.