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Measuring senescence in wild animal populations: towards a longitudinal approach

期刊

FUNCTIONAL ECOLOGY
卷 22, 期 3, 页码 393-406

出版社

WILEY
DOI: 10.1111/j.1365-2435.2008.01408.x

关键词

ageing; Capture-Mark-Recapture; heterogeneity; life-history trade-offs; longitudinal data; mixed-effects models; senescence; ungulates; wild populations

类别

资金

  1. NERC [NE/E01237X/1] Funding Source: UKRI
  2. Natural Environment Research Council [NE/B504314/1, NE/E01237X/1] Funding Source: researchfish

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1. A major current challenge in ageing research is to understand why senescence rates vary between individuals, populations and species in wild populations. 2. Recent studies clearly illustrate that senescent declines in key demographic and life-history traits can be observed in many wild animal systems. 3. Here, we summarize the key challenges facing researchers working to understand senescence in the wild. We concentrate on: (i) limited data availability, (ii) the substantial individual heterogeneity typical of wild populations, (iii) incomplete capture histories, and (iv) trade-offs across the life span. 4. We discuss analytical methods to overcome these challenges. We advocate the use of Capture-Mark-Recapture models to remove likely bias associated with re-sampling rates of less than one. We also illustrate that ageing trajectories may vary between different traits in wild populations. Wherever possible, researchers should examine ageing patterns in multiple traits. 5. Numerous models are available to describe the rate and shape of senescence in free-living populations, but there is currently little consensus regarding which is most appropriate in analyses of wild organisms. 6. We argue that only longitudinal studies of marked or recognizable individuals provide reliable sources of information in the study of senescence. Senescence is a within-individual process and only longitudinal studies allow researchers to separate within-individual ageing patterns from between-individual heterogeneity. 7. We examine two analytical approaches to measure ageing using longitudinal data from wild populations: a jack-knifing approach, well-suited to modelling survival probability, and a mixed-effects model approach. Both methods control for sources of between-individual heterogeneity to allow more accurate measurement of within-individual ageing patterns.

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