Evidence map›Paper›PMID 40846718›Full record

ArticleScientific data2025

High-resolution Canada domain disturbance forcings suitable for land surface modeling applications.

Jason Beaver, Salvatore R Curasi, Joe R Melton, Elyn R Humphreys, Txomin Hermosilla, Michael A Wulder

Abstract read
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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

6 authors.

Jason BeaverDepartment of Geography & Environmental Studies, Carleton University, Ottawa, ON, Canada.
Salvatore R CurasiDepartment of Geography & Environmental Studies, Carleton University, Ottawa, ON, Canada. Sal.Curasi@ec.gc.ca.ORCID http://orcid.org/0000-0002-4534-3344
Joe R MeltonClimate Research Division, Environment, and Climate Change Canada, Victoria, BC, Canada.ORCID http://orcid.org/0000-0002-9414-064X
Elyn R HumphreysDepartment of Geography & Environmental Studies, Carleton University, Ottawa, ON, Canada.
Txomin HermosillaCanadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, Victoria, BC, Canada.
Michael A WulderCanadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, Victoria, BC, Canada.ORCID http://orcid.org/0000-0002-6942-1896

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spatially explicit fire and harvest data are useful for driving land surface model (LSM) simulations of the carbon cycle. From 1985-present, numerous Canadian disturbance datasets exist. However, before the launch of Landsat-4 (1984), few are available. We create spatially explicit LSM disturbance drivers for Canada for 1740-2018. We catalog and harmonize spatial and aspatial datasets and develop a novel algorithm that reconstructs disturbance far back in time using stand age. Based on possible historical scenarios, we reconstruct 283-394 Mha of fire and 3.42 Mha of harvest in total Canada-wide from 1740-1918. After 1918, when spatial records are available, we supplement them by reconstructing 25.79-60.30 Mha of fire and 24.75 Mha of harvest. After 1984, we exclusively use spatially explicit records. We verify the algorithm by comparing the inputs and resultant drivers and examine diagnostic metrics to disentangle the contribution of spatial, aspatial, and stand-age data. The resulting drivers primarily capture stand-replacing disturbance on forested land. Our forcings and algorithm will improve the representation of disturbance-mediated impacts on Canada's terrestrial carbon cycle and possibly in other regions.

Identifiers

PMID40846718
PMCPMC12373880

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.