Evidence for quantity–quality trade-offs, sex-specific parental investment, and variance compensation in colonized Agta foragers undergoing demographic transition
Published Web Locationhttps://doi.org/10.1016/j.evolhumbehav.2016.02.005
Evolutionary ecological models of human fertility predict that: (1) parents will bias investment toward the sex with the highest fitness prospects in a particular socio-ecological context; (2) fertility is subject to quantity–quality trade-offs; and (3) fertility decisions will be sensitive to both predictable and stochastic mortality risk and the relative fitness value of differently sized sib-sets (the variance compensation hypothesis). We test these predictions using demographic records from the Agta, an indigenous population from the Philippines, who, as a result of disruption by loggers, miners, and settlers, are undergoing a demographic and social/ecological transition from foragers to peasant laborers. Leveraging the spatial and temporal variation in the Agta Demographic Database, we conduct an analysis of Agta life-history traits across this transition. Specifically, we compare the Casiguran Agta (CA) with the more isolated peninsular San Ildefonso Agta (SIA) sub-population from before (phase 1) and after (phase 2) encroachment. We find: (1) evidence of a decline in overall survival from phase 1 to phase 2, coupled with increased parental investment in first-born daughters compared to first-born sons in the CA population, and increased parental investment in sons versus daughters in the SIA population; (2) evidence of a moderate quantity–quality trade-off in CA and SIA fertility in phase 1; and (3) support for predictions of the variance compensation hypothesis as a driver of the lowered relative fertility in the CA. Our customized methods, comparative framework, and simultaneous focus on fertility and mortality allow us to show how heterogeneity in mortality and fertility are linked to life history trade-offs and environmental context in a manner consistent with the predictions of evolutionary ecological models.