Matrix population models are frequently built and used by ecologists to analyse demography and elucidate the processes driving population growth or decline. Life Table Response Experiments (LTREs) are comparative analyses that decompose the realized difference or variance in population growth rate () into contributions from the differences or variances in the vital rates (i.e. the matrix elements). Since their introduction, LTREs have been based on approximations and have not included biologically relevant interaction terms. We used the functional analysis of variance framework to derive an exact LTRE method, which calculates the exact response of to the difference or variance in a given vital rate, for all interactions among vital rates—including higher‐order interactions neglected by the classical methods. We used the publicly available COMADRE and COMPADRE databases to perform a meta‐analysis comparing the results of exact and classical LTRE methods. We analysed 186 and 1487 LTREs for animal and plant matrix population models, respectively. We found that the classical methods often had small errors, but that very high errors were possible. Overall error was related to the difference or variance in the matrices being analysed, consistent with the Taylor series basis of the classical method. Neglected interaction terms accounted for most of the errors in fixed design LTRE, highlighting the importance of two‐way interaction terms. For random design LTRE, errors in the contribution terms present in both classical and exact methods were comparable to errors due to neglected interaction terms. In most examples we analysed, evaluating exact contributions up to three‐way interaction terms was sufficient for interpreting 90% or more of the difference or variance in . Relative error, previously used to evaluate the accuracy of classical LTREs, is not a reliable metric of how closely the classical and exact methods agree. Error compensation between estimated contribution terms and neglected contribution terms can lead to low relative error despite faulty biological interpretation. Trade‐offs or negative covariances among matrix elements can lead to high relative error despite accurate biological interpretation. Exact LTRE provides reliable and accurate biological interpretation, and the R package
Longevity plays a key role in the fitness of organisms, so understanding the processes that underlie variance in senescence has long been a focus of ecologists and evolutionary biologists. For decades, the performance and ultimate decline of mitochondria have been implicated in the demise of somatic tissue, but exactly why mitochondrial function declines as individual’s age has remained elusive. A possible source of decline that has been of intense debate is mutations to the mitochondrial DNA. There are two primary sources of such mutations: oxidative damage, which is widely discussed by ecologists interested in aging, and mitochondrial replication error, which is less familiar to most ecologists. The goal of this review is to introduce ecologists and evolutionary biologists to the concept of mitochondrial replication error and to review the current status of research on the relative importance of replication error in senescence. We conclude by detailing some of the gaps in our knowledge that currently make it difficult to deduce the relative importance of replication error in wild populations and encourage organismal biologists to consider this variable both when interpreting their results and as viable measure to include in their studies.
more » « less- NSF-PAR ID:
- 10116831
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Integrative and Comparative Biology
- Volume:
- 59
- Issue:
- 4
- ISSN:
- 1540-7063
- Page Range / eLocation ID:
- p. 970-982
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract exactLTRE makes the exact method accessible to ecologists. -
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