Maternal Effect Senescence and Fitness: A Demographic Analysis of a Novel Model Organism

Abstract

Maternal effect senescence-a decline in offspring fitness with maternal age-has been demonstrated in a range of taxa, including humans. Despite decades of phenotypic studies, it remains unclear how maternal effect senescence impacts population structure or evolutionary fitness. To understand the impact of maternal effect senescence on population dynamics, fitness, and selection, we used data from individual-based culture experiments on the microscopic aquatic invertebrate, Brachionus manjavacas (Rotifera), to develop a series of matrix population models in which individuals are classified jointly by age and maternal age. By comparing the results derived from models with and without maternal effects, we found that the fitness difference due to maternal effect senescence arises primarily through decreased fertility, particularly at maternal ages corresponding to the peak reproductive output. In all models, selection gradients decrease with increasing age. They also decrease with maternal age for large maternal ages, implying that maternal effect senescence can evolve through the same process as in Hamilton's theory of the evolution of demographic senescence. We find that maternal effect senescence significantly alters population structure and fitness for B. manjavacas, a species with high maternal investment and maximum reproduction in early-to mid-life. The models developed here were built with data from an emerging model organism, and are widely applicable to evaluate the fitness consequences of maternal effect senescence across species with diverse aging and fertility schedule phenotypes.

The formal demography of kinship II: Multistate models, parity, and sibship

“…It also provides an approach to two-sex kinship models, accounting for male and female kin through male and female lines of descent. Characteristics like maternal age could be incorporated using a model like that of Hernández et al (2019). I have not explored them here, but the same kinds of kin properties investigated by Caswell (2019a) can be applied directly to multistate models (e.g., prevalence of diseases, dependency ratios, mean age (and now also mean parity), and experiences of the death of kin).…”

“…In Section 5, the stage variable will be parity. The model is constructed using the vec-permutation matrix approach introduced by Hunter and and described in detail in ; it has been applied, inter alia, to frailty (Caswell 2014;Hartemink, Missov, and Caswell 2017), latent heterogeneity (Hartemink and Caswell 2018;Jenouvrier et al 2018;van Daalen and Caswell 2020), maternal age effects (Hernández et al 2019), socioeconomic inequality (Caswell 2019b), epidemiology (Klepac and Caswell 2011), and genetics (de Vries and Caswell 2019).…”

The formal demography of kinship II: Multistate models, parity, and sibship

“…It also provides an approach to two-sex kinship models, accounting for male and female kin through male and female lines of descent. Characteristics like maternal age can be incorporated using a model like that of Hernández et al (2019). We have not explored them here, but the same kinds of kin properties investigated by Caswell (2019a) can be applied directly to multistate models (e.g., prevalence of diseases, dependency ratios, mean age (and now also mean parity), experiences of the death of kin).…”

“…The multistate model classifies individuals jointly by age and some other characteristic, referred to generically as “stage.” In Section 5, the stage variable will be parity. The model is constructed using the vec-permutation matrix approach introduced by Hunter and Caswell (2005) and described in detail in Caswell et al (2018); it has been applied, inter alia, to frailty (Caswell, 2014; Hartemink, Missov, and Caswell, 2017), latent heterogeneity (Hartemink and Caswell, 2018; Jenouvrier et al, 2018; van Daalen and Caswell, 2020), maternal age effects (Hernández et al, 2019), socioeconomic inequality (Caswell, 2019b), epidemiology (Klepac and Caswell, 2011), and genetics (de Vries and Caswell, 2019).…”