Evidence map›Paper›PMID 29238864›Full record

ArticleOecologia2018

Species' traits do not converge on optimum values in preferred habitats.

Rachel M Mitchell, Justin P Wright, Greg M Ames

Abstract read
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In one paragraph

Article in Oecologia, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

4 citing papers in PubMed.

  1. Article
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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.

Rachel M MitchellDepartment of Biology, Duke University, Box 90338, Durham, NC, 27708, USA. rachel.mitchell@nau.edu.ORCID 0000-0002-0867-9068
Justin P WrightDepartment of Biology, Duke University, Box 90338, Durham, NC, 27708, USA.
Greg M AmesDepartment of Biology, Duke University, Box 90338, Durham, NC, 27708, USA.

Funding

Directorate for Biological Sciences DBI-1401800
6 · The paper itself

Abstract

Plant trait expression is shaped by filters, which can alter trait means and variances, theoretically driving species toward an "optimum" trait value for a set of environmental conditions. Recent research has highlighted the ubiquity of intraspecific variation in functional traits, which can cause plants to diverge from a hypothesized "optimum". We examined whether species occurring in "core" habitats (where they occur frequently, abundantly, and consistently) express traits that are nearer to "optimum", as captured by the community-weighted mean (CWM). We also asked whether trait variance showed signs of environmental filtering. We used cluster analysis to group plots based on environmental factors along a wet-to-dry ecotone. We used indicator species analysis to identify species with strong associations within each cluster. Trait means and variances were compared, and evidence of variance filtering was tested using a null-model approach. Trait means and trait variances respond to local-scale environmental filtering and species in core habitats were not necessarily nearer to the CWM than in other habitats. Intraspecific trait variability shows a strong signal of filtering, as variability was reduced for nearly all species and all traits compared to estimates of variability generated in the absence of environmental filtering. Our results provide strong evidence that species traits are not necessarily near "optimum" trait values in core habitats, and that trait distributions within species are strongly shaped by the environment. Future analyses should account for this divergence when calculating metrics of functional diversity, and extrapolating to ecosystem function.

Indexed as

EcosystemPlantsPhenotypeFilteringFunctional traitsIntraspecific variationLDMCSLA

Identifiers

What OpenQuestion holds

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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.