Evidence map›Paper›PMID 34188866›Full record

ArticleEcology and evolution2021

Challenges and opportunities for comparative studies of survival rates: An example with male pinnipeds.

Jamie L Brusa, Jay J Rotella, Katharine M Banner, Patrick R Hutchins

Abstract read
In one paragraph

Article in Ecology and evolution, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jamie L BrusaDepartment of Ecology Montana State University Bozeman MT USA.ORCID https://orcid.org/0000-0003-4787-0460
Jay J RotellaDepartment of Ecology Montana State University Bozeman MT USA.
Katharine M BannerDepartment of Mathematical Sciences Montana State University Bozeman MT USA.ORCID https://orcid.org/0000-0002-7103-0042
Patrick R HutchinsDepartment of Ecology Montana State University Bozeman MT USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Survival rates are a central component of life-history strategies of large vertebrate species. However, comparative studies seldom investigate interspecific variation in survival rates with respect to other life-history traits, especially for males. The lack of such studies could be due to the challenges associated with obtaining reliable datasets, incorporating information on the 0-1 probability scale, or dealing with several types of measurement error in life-history traits, which can be a computationally intensive process that is often absent in comparative studies. We present a quantitative approach using a Bayesian phylogenetically controlled regression with the flexibility to incorporate uncertainty in estimated survival rates and quantitative life-history traits while considering genetic similarity among species and uncertainty in relatedness. As with any comparative analysis, our approach makes several assumptions regarding the generalizability and comparability of empirical data from separate studies. Our model is versatile in that it can be applied to any species group of interest and include any life-history traits as covariates. We used an unbiased simulation framework to provide "proof of concept" for our model and applied a slightly richer model to a real data example for pinnipeds. Pinnipeds are an excellent taxonomic group for comparative analysis, but survival rate data are scarce. Our work elucidates the challenges associated with addressing important questions related to broader ecological life-history patterns and how survival-reproduction trade-offs might shape evolutionary histories of extant taxa. Specifically, we underscore the importance of having high-quality estimates of age-specific survival rates and information on other life-history traits that reasonably characterize a species for accurately comparing across species.

Indexed as

comparative analysislife‐history evolutionphylogenetic uncertaintypinnipedssurvival rates

Identifiers

PMID34188866
PMCPMC8216918

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.