Evidence map›Paper›PMID 37583877›Full record

ArticlePlant-environment interactions (Hoboken, N.J.)2023

Using long-term data from a whole ecosystem warming experiment to identify best spring and autumn phenology models.

Christina Schädel, Bijan Seyednasrollah, Paul J Hanson, Koen Hufkens, Kyle J Pearson, Jeffrey M Warren, Andrew D Richardson

Abstract read
In one paragraph

Article in Plant-environment interactions (Hoboken, N.J.), 2023. 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. Review
  2. Article
  3. Article
  4. 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

7 authors.

Christina SchädelCenter for Ecosystem Science and Society Northern Arizona University Flagstaff Arizona USA.ORCID https://orcid.org/0000-0003-2145-6210
Bijan SeyednasrollahSchool of Informatics, Computing and Cyber Systems Northern Arizona University Flagstaff Arizona USA.ORCID https://orcid.org/0000-0002-5195-2074
Paul J HansonEnvironmental Sciences Division and Climate Change Science Institute Oak Ridge National Laboratory Oak Ridge Tennessee USA.ORCID https://orcid.org/0000-0001-7293-3561
Koen HufkensBlueGreen Labs 9120 Melsele Belgium.ORCID https://orcid.org/0000-0002-5070-8109
Kyle J PearsonEnvironmental Sciences Division and Climate Change Science Institute Oak Ridge National Laboratory Oak Ridge Tennessee USA.ORCID https://orcid.org/0000-0002-5981-6835
Jeffrey M WarrenEnvironmental Sciences Division and Climate Change Science Institute Oak Ridge National Laboratory Oak Ridge Tennessee USA.ORCID https://orcid.org/0000-0002-0680-4697
Andrew D RichardsonCenter for Ecosystem Science and Society Northern Arizona University Flagstaff Arizona USA.ORCID https://orcid.org/0000-0002-0148-6714

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Predicting vegetation phenology in response to changing environmental factors is key in understanding feedbacks between the biosphere and the climate system. Experimental approaches extending the temperature range beyond historic climate variability provide a unique opportunity to identify model structures that are best suited to predicting phenological changes under future climate scenarios. Here, we model spring and autumn phenological transition dates obtained from digital repeat photography in a boreal

Indexed as

Akaike Information Criterionclimate changeCO2Larix laricinapeatlandPicea marianatransition dates

Identifiers

PMID37583877
PMCPMC10423976

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.