Table 2.
Overview of research questions, underlying hypotheses, approaches and their challenges, and potential solutions for the research agenda suggested in the paper
| Question | Hypothesis | Approach | Challenges | Solutions |
|---|---|---|---|---|
| How does demographic (actuarial) aging vary across populations within a species? | Is variation of lifespan across populations of a species attributable to differences in (i) background (nonaging) mortality, (ii) steepness of increase in mortality rate with age (aging rate), (iii) onset of age‐related increase in mortality or (iv) their combination? | Collating life‐time survival data on replicated wild populations with a sample size attributable to fitting demographic models (n > 50), ideally with variable (and measurable) levels of extrinsic mortality | Long‐term research program or using short‐lived organisms amendable to individual marking | New advances in bioinformatics now allow for much easier use of mark‐recapture data, providing robust estimates of aging‐related demography (1) |
| How much intraspecific variation in lifespan is attributable to an intrinsic (i.e., nonenvironmental) component? | Is interpopulation variation in lifespan lower in captivity than in the wild? | Comparing survival data from wild populations with wild‐derived (matched genetic background) populations in captivity | Choice of taxon amendable to field‐ and laboratory‐based estimates (small philopatric animals) | (i) New advances in bioinformatics now allow for easier use of mark‐recapture data (1); (ii) some datasets from the wild can be matched with existing data on captive populations, e.g., in zoos (2) |
| Are functional declines in the wild comparable to those observed in captivity? | Individuals in the wild experience faster physiological deterioration due to more challenging conditions (stronger stress) | Estimating identical functional declines in wild and captive (wild‐derived) populations with a matched genetic background | Nondestructive sampling to enable collection of longitudinal (individual‐based) dataset | High performance methods using minute tissue samples from blood, feathers, epidermal or hair samples (hormonal assays, immunosenescence, oxidative stress, telomere attrition) (3–5) |
| How much variation of longevity within a natural population is attributable to gene‐by‐environment interactions? | Environmental context significantly modulates the expression of aging rates | Common garden experiment with split‐clutch (family) design manipulating key stressors. Alternatively, a cross‐fostering experiment in the wild (or semi‐natural setting) across contrasting social or environmental conditions | Long‐term research agenda for most study taxa | Using short‐lived species for common garden experiments (6,7), taxa with low dispersal/high recapture rates (8) or seminatural cross‐fostering experiments ((9) |