Evidence map›Paper›PMID 41173842›Full record

ArticleScientific data2025

Geospatial Estimation of Forest Relative Density for Carbon Stewardship Decision Support across the Continental US.

Emmerson Chivhenge, Aaron R Weiskittel, Christopher W Woodall, Anthony W D'Amato, Adam Daigneault

Abstract read
PubMed Full text at PMC Publisher
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

5 authors.

Emmerson ChivhengeUniversity of Maine, School of Forest Resources, Orono, ME, USA. emmerson.chivhenge@maine.edu.
Aaron R WeiskittelUniversity of Maine, Center for Research on Sustainable Forests, Orono, ME, USA.ORCID http://orcid.org/0000-0003-2534-4478
Christopher W WoodallUSDA Forest Service (Retired), Inventory, Monitoring, and Assessment Research, Research and Development, Washington, DC, USA.ORCID http://orcid.org/0000-0001-8076-6214
Anthony W D'AmatoUniversity of Vermont, Rubenstein School of Environment and Natural Resources, Burlington, VT, USA.ORCID http://orcid.org/0000-0002-2570-4376
Adam DaigneaultUniversity of Maine, Center for Research on Sustainable Forests, Orono, ME, USA.ORCID http://orcid.org/0000-0002-8287-8727

Funding

National Science Foundation (NSF) 1915078National Science Foundation (NSF) 2416915U.S. Department of Agriculture (United States Department of Agriculture) 2023-68012-38992
6 · The paper itself

Abstract

The US Forest Services (USFS) under the Forest Inventory and Analysis (FIA) program estimates resource characteristics and statistics regarding forest attributes and ecosystem processes at various strategic scales with different levels of precision and refinement. A vital forest resource attribute is tree size-density, which informs regional and national policies and project-scale management. To enhance the development and distribution of key forest tree-size density metrics, a 30 × 30 m wall to wall spatial dataset for stand density index (SDI), maximum SDI (SDI

Identifiers

PMID41173842
PMCPMC12578910

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.