The evolution of predictive adaptive responses in human life history

Abstract

Many studies in humans have shown that adverse experience in early life is associated with accelerated reproductive timing, and there is comparative evidence for similar effects in other animals. There are two different classes of adaptive explanation for associations between early-life adversity and accelerated reproduction, both based on the idea of predictive adaptive responses (PARs). According to external PAR hypotheses, early-life adversity provides a 'weather forecast' of the environmental conditions into which the individual will mature, and it is adaptive for the individual to develop an appropriate phenotype for this anticipated environment. In internal PAR hypotheses, early-life adversity has a lasting negative impact on the individual's somatic state, such that her health is likely to fail more rapidly as she gets older, and there is an advantage to adjusting her reproductive schedule accordingly. We use a model of fluctuating environments to derive evolveability conditions for acceleration of reproductive timing in response to early-life adversity in a long-lived organism. For acceleration to evolve via the external PAR process, early-life cues must have a high degree of validity and the level of annual autocorrelation in the individual's environment must be almost perfect. For acceleration to evolve via the internal PAR process requires that early-life experience must determine a significant fraction of the variance in survival prospects in adulthood. The two processes are not mutually exclusive, and mechanisms for calibrating reproductive timing on the basis of early experience could evolve through a combination of the predictive value of early-life adversity for the later environment and its negative impact on somatic state.

Keywords: developmental plasticity; early-life stress; humans; life history; predictive adaptive response.

Figure 1.

Illustrative 200-year periods of values of M for different levels of annual autocorrelation, (a) r = 0, (b) r = 0.7 and (c) r = 0.95. In (b) and particularly (c), there emerge runs of good or bad conditions lasting many years.

Figure 2.

Predictive value of early-life experience for adult environment as a function of the annual autocorrelation r of the environment. The three lines show different levels of the cue validity v, v = 1 (solid line), v = 0.8 (dashed line), v = 0.6 (dotted line). (a) Represents 1-year sampling, where cues from the first year of life only are used, and (b) 5-year sampling, where the mean of the first 5 years is used. Data represent 10 000 simulated lifetimes for each 0.01 increment of r and each value of v.

Figure 3.

Regions of parameter space (shaded dark) in which an individual ends up on average better matched to her adult environment by using early-life cues to set adult phenotype, rather than following a genetically fixed strategy where she develops matched to the mean of conditions experienced by the lineage over evolutionary time. Data represent 2000 simulated lifetimes for each parameter combination.

Figure 4.

Predictive power of early-life experience for adult environment outcome as a function of r, the degree of annual autocorrelation, for different values of d, the impact of early-life experience on adult internal state. (a) Represents 1-year sampling and (b) 5-year sampling. Solid lines represent v = 1 and dashed lines v = 0.6. Data represent 10 000 simulated lifetimes for each parameter combination.

Figure 5.

Regions of parameter space (shaded dark) in which an individual ends up on average better matched to her adult environment by using early-life cues to set adult phenotype, rather than following a genetically fixed strategy where she develops matched to the mean of conditions experienced by the lineage over evolutionary time, for five values of d, the effect of early experience on somatic state. Data represent 2000 simulated lifetimes for each parameter combination.