(L). Among those species, the locations of artiodactyls (Source: After Lynch et al. (2010).
Despite wide variations in size, longevity and taxonomic affiliation, most of the curves were, in essence, type 2, with some element of type 1 (senescence) or type 3 (early mortality). The variation that did exist was significantly associated with the species’ taxonomic order: the artiodactyls showed the least evidence of senescence, the carnivores the most, with the primates somewhere in between (Figure 4.12). This taxonomic variation was in turn associated with variations in age to weaning (relative to lifespan) and litter size, suggesting ‘syndromes’ of associated life history traits. We return to the whole topic of the patterns in life histories and their possible causes in the next chapter. For now, though, the results do provide us with grounds for believing that, based on this analysis, even for species where we have little or no prior knowledge, managers in zoos can make educated predictions with some confidence about likely patterns of mortality, and act accordingly.
4.6.3 Static life tables
Many of the species that ecologists study, and for which life tables would therefore be valuable, have repeated breeding seasons like the marmots, or continuous breeding as in the case of humans, but constructing life tables here is complicated, largely because these populations have individuals of many different ages living together. Building a cohort life table is sometimes possible, as we have seen, but this is relatively uncommon. Apart from the mixing of cohorts in the population, it can be difficult simply because of the longevity of many species.
useful – if used with caution
Another approach is to construct a static life table (Figure 4.9). The data look like a cohort life table – a series of different numbers of individuals in different age classes – but these come simply from the age structure of the population captured at one point in time. Hence, great care is required: they can only be treated and interpreted in the same way as a cohort life table if patterns of birth and survival in the population have remained much the same since the birth of the oldest individuals – and this will happen only rarely. Nonetheless, there is often no alternative and useful insights can still be gained. This is illustrated for a population of small dinosaurs, Psittacosaurus lujiatunensis, recovered as fossils from the Lower Cretaceous Yixian Formation in China, where the alternative of following a cohort is obviously not available (Figure 4.13). They appear to have perished simultaneously in a volcanic mudflow, which might therefore have captured a representative snapshot of the population at the time, around 125 million years ago.
Figure 4.13 Static life tables can be informative, especially when alternatives are not available. (a) The age structure (and hence the static life table) of a population of dinosaurs, Psittacosaurus lujiatunensis, recovered as fossils from the Lower Cretaceous Yixian Formation in China. Age was estimated from the length of the femur, which had been shown in a subsample of specimens to correlate very strongly with the number of ‘growth lines’ (one per year) in the bone. (b) A survivorship curve (log(lx) plotted against age) derived from the life table.
Source: After Erickson et al. (2009).
It appears that mortality rates were high amongst the dinosaurs until around the age of three, after which there was another period of around five years during which mortality rates were low even though the animals continued to grow rapidly, which they did until the age of around nine or 10 years (Figure 4.13b). Mortality rates then seem to have increased again, just as the animals were attaining their maximum size, and broadly coinciding with the appearance in the fossils of characteristics associated with sexual maturity (e.g. enlarged, flaring ‘jugal’ horns). As we shall see in the next chapter, many organisms suffer a cost of reproduction in terms of reductions in growth and/or survival.
Notwithstanding this successful use of a static life table, the interpretation of static life tables generally, and the age structures from which they stem, is fraught with difficulty: usually, age structures offer no easy short cuts to understanding the dynamics of populations.
4.6.4 The importance of modularity
Finally here, we turn to the difficulties of constructing any sort of life table for organisms that are not only iteroparous with overlapping generations but are also modular. We can use a study of the sedge, Carex bigelowii, growing in a lichen heath in Norway, to illustrate this (Figure 4.14). C. bigelowii has an extensive underground rhizome system that produces tillers (aerial shoots) at intervals along its length as it grows. It grows by producing a lateral meristem in the axil of a leaf belonging to a ‘parent’ tiller. This lateral is completely dependent on the parent tiller at first, but is potentially capable of developing into a vegetative parent tiller itself, and also of flowering, which it does when it has produced a total of 16 or more leaves. Flowering, however, is always followed by tiller death. In other words, the tillers are semelparous although the genets are iteroparous.
Figure 4.14 Reconstructed static life table for the modules (tillers) of a Carex bigelowii population. The densities per m2 of tillers are shown in rectangular boxes, and those of seeds in diamond‐shaped boxes. Rows represent tiller types, whilst columns depict size classes of tillers. Purple‐walled boxes represent dead tiller (or seed) compartments, and arrows denote pathways between size classes, death or reproduction.
Source: After Callaghan (1976).
Callaghan (1976) took a number of well‐separated young tillers and excavated their rhizome systems through progressively older generations of parent tillers. This was made possible by the persistence of dead tillers. He excavated 23 such systems containing a total of 360 tillers, and was able to construct a type of static life table (and fecundity schedule) based on the growth stages (
