Evidence map›Paper›PMID 40691457›Full record

ArticleScientific data2025

PAVC: The foundation for a Pan-Arctic Vegetation Cover database.

Morgan R Steckler, Jitendra Kumar, Amy L Breen, Tianqi Zhang, Forrest M Hoffman, William W Hargrove, Donald A Walker, Aaron F Wells, Amanda Droghini, Timm W Nawrocki and 6 more

Abstract readDataset
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

16 authors.

Morgan R StecklerOak Ridge National Laboratory Computational Science and Engineering Division, Oak Ridge, TN, USA. stecklermr@ornl.gov.ORCID 0000-0002-5620-6716
Jitendra KumarOak Ridge National Laboratory Environmental Sciences Division, Oak Ridge, TN, USA.ORCID 0000-0002-0159-0546
Amy L BreenUniversity of Alaska Fairbanks International Arctic Research Center, Fairbanks, AK, USA.
Tianqi ZhangOak Ridge National Laboratory Environmental Sciences Division, Oak Ridge, TN, USA.
Forrest M HoffmanOak Ridge National Laboratory Computational Science and Engineering Division, Oak Ridge, TN, USA.
William W HargroveUSDA Forest Service Southern Research Station, Asheville, NC, USA.
Donald A WalkerUniversity of Alaska Fairbanks Institute of Arctic Biology, Fairbanks, AK, USA.
Aaron F WellsAECOM Technical Services, Anchorage, AK, USA.ORCID 0000-0002-0485-3567
Amanda DroghiniUniversity of Alaska Anchorage Alaska Center for Conservation Science, Anchorage, AK, USA.
Timm W NawrockiUniversity of Alaska Anchorage Alaska Center for Conservation Science, Anchorage, AK, USA.
Stan D WullschlegerOak Ridge National Laboratory Environmental Sciences Division, Oak Ridge, TN, USA.
Matthew J MacanderAlaska Biological Research, Inc., Fairbanks, AK, USA.ORCID 0000-0003-2808-208X
Gerald V FrostAlaska Biological Research, Inc., Fairbanks, AK, USA.
Verity G SalmonOak Ridge National Laboratory Environmental Sciences Division, Oak Ridge, TN, USA.ORCID 0000-0002-2188-551X
David T BarnettNational Ecological Observatory Network, Battelle, Boulder, CO, USA.
Colleen M IversenOak Ridge National Laboratory Environmental Sciences Division, Oak Ridge, TN, USA.ORCID 0000-0001-8293-3450

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Field-measured Arctic vegetation cover data is essential for creating accurate, high-quality vegetation structure and composition maps. Extrapolating field data into high-resolution cover maps provides detailed, function-specific information for use in Earth System Models, vegetation classifications, and monitoring vegetation change over time and space. However, field campaigns that collect plant cover vary substantially in scope, method, and purpose, which makes them difficult to unify across data stores, and they are often not designed to meet remote sensing needs. In this work, we synthesized and harmonized field-based fractional cover data from various data stores to create a high-quality, consistent repository schema for remote sensing-based vegetation cover mapping applications. We developed a reproducible workflow for synthesizing visual estimate and point-intercept fractional cover data. The resultant Pan-Arctic Vegetation Cover (PAVC) database contains synthesized fractional cover at both the species and plant functional type levels. The latter includes absolute foliar cover for deciduous shrubs and trees, evergreen shrubs and trees, forbs, graminoids, lichen, bryophytes, and "other" vegetation, as well as absolute cover for litter and top cover for water and bare ground.

Indexed as

Databases, FactualPlantsArctic RegionsEcosystemRemote Sensing TechnologyTrees

Identifiers

PMID40691457
PMCPMC12280189

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.