The Contributions of Maternal Age Heterogeneity to Variance in Lifetime Reproductive Output

Abstract

Variance among individuals in fitness components reflects both genuine heterogeneity between individuals and stochasticity in events experienced along the life cycle. Maternal age represents a form of heterogeneity that affects both the mean and variance of lifetime reproductive output (LRO). Here we quantify the relative contribution of maternal age heterogeneity to the variance in LRO, using individual-level laboratory data on the rotifer Brachionus manjavacas to parameterize a multistate age×maternal-age matrix model. In B. manjavacas, advanced maternal age has large negative effects on offspring survival and fertility. We used multistate Markov chains with rewards to quantify the contributions to variance in LRO of heterogeneity and of the stochasticity inherent in the outcomes of probabilistic transitions and reproductive events. Under laboratory conditions, maternal age heterogeneity contributes 26% of the variance in LRO. The contribution changes when mortality and fertility are reduced to mimic more ecologically relevant environments. Over the parameter space where populations are near stationarity, maternal age heterogeneity contributes an average of 3% of the variance. Thus, the contributions of maternal age heterogeneity and individual stochasticity can be expected to depend strongly on environmental conditions; over most of the parameter space, the variance in LRO is dominated by stochasticity.

A standard protocol to report discrete stage-structured demographic information

“…In studies of "luck," variance among individuals for a life history outcome is partitioned into contributions from between-group and within-group variation (e.g., van Daalen & Caswell, 2017;Snyder & Ellner, 2018). Examples of sources of individual heterogeneity include maternal age (van Daalen, Hernández, Caswell, Neubert, & Gribble, 2022), birth-year environment (Snyder & Ellner, 2022), and genetic variation (Steiner, Tuljapurkar, & Roach, 2021). The within-group variation is called individual stochasticity or "luck" and arises from the fact that vital rates are probabilistic processes.…”

“…It is composed of a set of matrices giving transitions among stages for each age class, a set of matrices 𝑫 giving age transitions for each -34 -stagethemselves, as well as the matrix construction procedure (for example, Hernández et al (2020) uses a stage-within-age construction). For MPMs that incorporate a Markov chain with rewards, the definitions of absorbing states and rewards must be clearly presented; reproducibility also requires knowing the mixing distribution that was used for variance analysis (seevan Daalen et al, 2022). The development of MPMs to accommodate these richer realities requires a more detailed report of their data and metadata.…”

A standard protocol to report discrete stage‐structured demographic information

“…Snyder & Ellner, 2018; van Daalen & Caswell, 2017). Examples of sources of individual heterogeneity include maternal age (van Daalen et al, 2022), birth‐year environment (Snyder & Ellner, 2022), and genetic variation (Steiner et al, 2021). The within‐group variation is called individual stochasticity or ‘luck’ and arises from the fact that vital rates are probabilistic processes.…”

“…In studies of 'luck', variance among individuals for a life history outcome is partitioned into contributions from between-group and within-group variation (e.g. Snyder & Ellner, 2018;van Daalen & Caswell, 2017). Examples of sources of individual heterogeneity include maternal age (van Daalen et al, 2022), birth-year environment (Snyder & Ellner, 2022), and genetic variation (Steiner et al, 2021).…”

Stochasticity explains non-genetic inheritance of lifespan and apparent trade-offs between reproduction and ageing

“…How reproduction changes with age, often termed reproductive senescence, has also been shown to vary amongst individuals in human and other animal populations 15,16 . In addition to this there are mechanistically unexplained effects of parental age on offspring lifespan and reproduction 17,18 . Non-genetic inheritance of how organisms age is thus documented but not understood.…”