Evidence map›Paper›PMID 28280593›Full record

ArticleRoyal Society open science2017

Morphology captures diet and locomotor types in rodents.

Luis D Verde Arregoitia, Diana O Fisher, Manuel Schweizer

Abstract read
In one paragraph

Article in Royal Society open science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
–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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

3 authors.

Luis D Verde ArregoitiaNaturhistorisches Museum Bern, Bernastrasse 15, Bern 3005 , Switzerland.ORCID 0000-0001-9520-6543
Diana O FisherSchool of Biological Sciences , University of Queensland , St Lucia, Queensland 4072 , Australia.
Manuel SchweizerNaturhistorisches Museum Bern, Bernastrasse 15, Bern 3005 , Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To understand the functional meaning of morphological features, we need to relate what we know about morphology and ecology in a meaningful, quantitative framework. Closely related species usually share more phenotypic features than distant ones, but close relatives do not necessarily have the same ecologies. Rodents are the most diverse group of living mammals, with impressive ecomorphological diversification. We used museum collections and ecological literature to gather data on morphology, diet and locomotion for 208 species of rodents from different bioregions to investigate how morphological similarity and phylogenetic relatedness are associated with ecology. After considering differences in body size and shared evolutionary history, we find that unrelated species with similar ecologies can be characterized by a well-defined suite of morphological features. Our results validate the hypothesized ecological relevance of the chosen traits. These cranial, dental and external (e.g. ears) characters predicted diet and locomotion and showed consistent differences among species with different feeding and substrate use strategies. We conclude that when ecological characters do not show strong phylogenetic patterns, we cannot simply assume that close relatives are ecologically similar. Museum specimens are valuable records of species' phenotypes and with the characters proposed here, morphology can reflect functional similarity, an important component of community ecology and macroevolution.

Indexed as

discriminant analysisecomorphologynon-metric multi-dimensional scalingphylomorphospacesize correction

Identifiers

PMID28280593
PMCPMC5319359

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.