Evidence map›Paper›PMID 36208107›Full record

ArticleEcology2023

Functional traits' annual variation exceeds nitrogen-driven variation in grassland plant species.

George R Wheeler, Chad E Brassil, Johannes M H Knops

Abstract read
In one paragraph

Article in Ecology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

3 authors.

George R WheelerSchool of Biological Sciences, University of Nebraska-Lincoln, Lincoln, Nebraska, USA.ORCID 0000-0003-3975-9826
Chad E BrassilSchool of Biological Sciences, University of Nebraska-Lincoln, Lincoln, Nebraska, USA.ORCID 0000-0002-9611-7283
Johannes M H KnopsSchool of Biological Sciences, University of Nebraska-Lincoln, Lincoln, Nebraska, USA.ORCID 0000-0002-9647-9209

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Effective application of functional trait approaches to ecological questions requires understanding the patterns of trait variation within species as well as between them. However, few studies address the potential for intraspecific variation to occur on a temporal basis and, thus, for trait-based findings to be contingent upon sampling year. To quantify annual variation in the functional traits of grassland plant species, we measured specific leaf area, leaf dry matter content, plant height, and chlorophyll content in 12 shortgrass prairie plant species. We repeated these measurements across 4 years, both in long-term nitrogen addition plots and in corresponding control plots. Three of the four traits showed significant year-to-year variation in a linear mixed model analysis, generally following a pattern of more acquisitive leaf economics spectrum traits in higher rainfall years. Furthermore, two of the measured traits responded interactively to nitrogen addition and sampling year, although only one, leaf dry matter content, showed the expected pattern of stronger nitrogen responses in high rainfall years. For leaf dry matter content and specific leaf area, trait responses to sampling year were larger than responses to the nitrogen addition treatment. These findings illustrate that species' functional traits can respond strongly to environmental changes across years, and thus that trait variation in a species or community is likely to extend beyond the values and patterns observed in any single year.

Indexed as

GrasslandNitrogenPhenotypePlant LeavesPlantsNitrogenannual variationdroughtfunctional traitgrasslandintraspecific trait variationNutNetnutrients

Identifiers

PMID36208107
PMCPMC10078297

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.