Age-dependent traits: a new statistical model to separate within- and between-individual effects

Area of Science:

• Evolutionary biology
• Gerontology
• Quantitative genetics

Background:

• Aging research often uses cross-sectional studies, which can conflate individual aging with population changes.
• Accurate assessment of age-related trait changes requires separating within-individual (e.g., senescence) and between-individual (e.g., selective survival) effects.

Purpose of the Study:

• To develop a novel statistical model for disentangling within- and between-individual changes in traits over a lifetime.
• To provide a simpler framework for quantifying the relative contributions of these two types of changes.

Main Methods:

• Introduction of a new statistical model allowing variance and covariance to differ across aggregation levels.
• Application of the model to data from the oystercatcher (Haematopus ostralegus) focusing on reproductive traits.

Main Results:

• The model successfully quantifies the distinct contributions of within- and between-individual changes.
• For oystercatchers, both individual improvement and selective survival can explain positive age-reproduction associations.

Conclusions:

• The developed statistical model offers a more unbiased approach to studying aging and trait evolution.
• This methodology has broad applicability in biology where within- and between-individual dynamics diverge.