Evidence map›Paper›PMID 26830847›Full record

ArticleScientific reports2016

Altered rainfall patterns increase forb abundance and richness in native tallgrass prairie.

Sydney K Jones, Scott L Collins, John M Blair, Melinda D Smith, Alan K Knapp

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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  10. Climate and plant community diversity in space and time.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Review
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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

5 authors.

Sydney K JonesDepartment of Biology, MSC03-2020, University of New Mexico, Albuquerque, NM, 87131, United States.
Scott L CollinsDepartment of Biology, MSC03-2020, University of New Mexico, Albuquerque, NM, 87131, United States.
John M BlairDivision of Biology, Kansas State University, Manhattan, KS, 66506, United States.
Melinda D SmithGraduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, 80523, United States.
Alan K KnappGraduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, 80523, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Models predict that precipitation variability will increase with climate change. We used a 15-year precipitation manipulation experiment to determine if altering the timing and amount of growing season rainfall will impact plant community structure in annually burned, native tallgrass prairie. The altered precipitation treatment maintained the same total growing season precipitation as the ambient precipitation treatment, but received a rainfall regime of fewer, larger rain events, and longer intervals between events each growing season. Although this change in precipitation regime significantly lowered mean soil water content, overall this plant community was remarkably resistant to altered precipitation with species composition relatively stable over time. However, we found significantly higher forb cover and richness and slightly lower grass cover on average with altered precipitation, but the forb responses were manifest only after a ten-year lag period. Thus, although community structure in this grassland is relatively resistant to this type of altered precipitation regime, forb abundance in native tallgrass prairie may increase in a future characterized by increased growing season precipitation variability.

Indexed as

GrasslandModels, BiologicalRainSeasons

Identifiers

PMID26830847
PMCPMC4735582

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.