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Financial opportunity costs and deaths among close kin are independently associated with reproductive timing in a contemporary high-income society.

ABSTRACT: Evolutionary demography predicts that variation in reproductive timing stems from socio-ecologically contingent trade-offs between current and future reproduction. In contemporary high-income societies, the costs and benefits of current reproduction are likely to vary by socioeconomic status (SES). Two influential hypotheses, focusing on the parenthood 'wage penalty', and responses to local mortality have separately been proposed to influence the timing of parenthood. Economic costs of reproduction (i.e. income loss) are hypothesized to delay fertility, especially among high childhood SES individuals who experience greater opportunities to build capital through advantageous education and career opportunities. On the other hand, relatively low childhood SES individuals experience higher mortality risk, which may favour earlier reproduction. Here, we examine both hypotheses with a representative register-based, multigenerational dataset from contemporary Finland (N = 47 678). Consistent with each hypothesis, the predicted financial cost of early parenthood was smaller, and mortality among close kin was higher for individuals with lower childhood SES. Within the same dataset, lower predicted adulthood income and more kin deaths were also independently associated with earlier parenthood. Our results provide a robust demonstration of how economic costs and mortality relate to reproductive timing. We discuss the implications of our findings for demographic theory and public policy.

SUBMITTER: Berg V

PROVIDER: S-EPMC7015326 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Financial opportunity costs and deaths among close kin are independently associated with reproductive timing in a contemporary high-income society.

Berg V V Lawson D W DW Rotkirch A A

Proceedings. Biological sciences 20200122 1919

Evolutionary demography predicts that variation in reproductive timing stems from socio-ecologically contingent trade-offs between current and future reproduction. In contemporary high-income societies, the costs and benefits of current reproduction are likely to vary by socioeconomic status (SES). Two influential hypotheses, focusing on the parenthood 'wage penalty', and responses to local mortality have separately been proposed to influence the timing of parenthood. Economic costs of reproduct ...[more]

PMID: 31964300

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Project description:Close-kin mark-recapture (CKMR) is a method for estimating abundance and vital rates from kinship relationships observed in genetic samples. CKMR inference only requires animals to be sampled once (e.g., lethally), potentially widening the scope of population-level inference relative to traditional monitoring programs.One assumption of CKMR is that, conditional on individual covariates like age, all animals have an equal probability of being sampled. However, if genetic data are collected opportunistically (e.g., via hunters or fishers), there is potential for spatial variation in sampling probability that can bias CKMR estimators, particularly when genetically related individuals stay in close proximity.We used individual-based simulation to investigate consequences of dispersal limitation and spatially biased sampling on performance of naive (nonspatial) CKMR estimators of abundance, fecundity, and adult survival. Population dynamics approximated that of a long-lived mammal species subject to lethal sampling.Naive CKMR abundance estimators were relatively unbiased when dispersal was unconstrained (i.e., complete mixing) or when sampling was random or subject to moderate levels of spatial variation. When dispersal was limited, extreme variation in spatial sampling probabilities negatively biased abundance estimates. Reproductive schedules and survival were well estimated, except for survival when adults could emigrate out of the sampled area. Incomplete mixing was readily detected using Kolmogorov-Smirnov tests.Although CKMR appears promising for estimating abundance and vital rates with opportunistically collected genetic data, care is needed when dispersal limitation is coupled with spatially biased sampling. Fortunately, incomplete mixing is easily detected with adequate sample sizes. In principle, it is possible to devise and fit spatially explicit CKMR models to avoid bias under dispersal limitation, but development of such models necessitates additional complexity (and possibly additional data). We suggest using simulation studies to examine potential bias and precision of proposed modeling approaches prior to implementing a CKMR program.

Dataset Information

Financial opportunity costs and deaths among close kin are independently associated with reproductive timing in a contemporary high-income society.

Publications

Financial opportunity costs and deaths among close kin are independently associated with reproductive timing in a contemporary high-income society.

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