Evidence map›Paper›PMID 34731170›Full record

ArticlePloS one2021

Relationships of climate, human activity, and fire history to spatiotemporal variation in annual fire probability across California.

Isaac W Park, Michael L Mann, Lorraine E Flint, Alan L Flint, Max Moritz

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.5field-weighted citation impact, top 19% of its field
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

3 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. The importance of geography in forecasting future fire patterns under climate change.Proceedings of the National Academy of Sciences of the United States of America · 2024
    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 at 3 institutions in 1 country.

Isaac W ParkDepartment of Ecology, Evolution, and Marine Biology, University of California-Santa Barbara, Santa Barbara, California, United States of America.ORCID 0000-0001-5539-1641
Michael L MannDepartment of Geography, George Washington University, Washington, D.C., United States of America.
Lorraine E FlintU.S. Geological Survey, Sacramento, CA, United States of America.
Alan L FlintU.S. Geological Survey, Sacramento, CA, United States of America.
Max MoritzUniversity of California Cooperative Extension, Santa Barbara, CA, United States of America.
United States Geological Survey · USUniversity of California, Santa Barbara · USGeorge Washington University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the face of recent wildfires across the Western United States, it is essential that we understand both the dynamics that drive the spatial distribution of wildfire, and the major obstacles to modeling the probability of wildfire over space and time. However, it is well documented that the precise relationships of local vegetation, climate, and ignitions, and how they influence fire dynamics, may vary over space and among local climate, vegetation, and land use regimes. This raises questions not only as to the nature of the potentially nonlinear relationships between local conditions and the fire, but also the possibility that the scale at which such models are developed may be critical to their predictive power and to the apparent relationship of local conditions to wildfire. In this study we demonstrate that both local climate-through limitations posed by fuel dryness (CWD) and availability (AET)-and human activity-through housing density, roads, electrical infrastructure, and agriculture, play important roles in determining the annual probabilities of fire throughout California. We also document the importance of previous burn events as potential barriers to fire in some environments, until enough time has passed for vegetation to regenerate sufficiently to sustain subsequent wildfires. We also demonstrate that long-term and short-term climate variations exhibit different effects on annual fire probability, with short-term climate variations primarily impacting fire probability during periods of extreme climate anomaly. Further, we show that, when using nonlinear modeling techniques, broad-scale fire probability models can outperform localized models at predicting annual fire probability. Finally, this study represents a powerful tool for mapping local fire probability across the state of California under a variety of historical climate regimes, which is essential to avoided emissions modeling, carbon accounting, and hazard severity mapping for the application of fire-resistant building codes across the state of California.

Indexed as

ClimateHuman ActivitiesWildfiresAgricultureCaliforniaClimate ChangeEcosystemHousingHumans

Identifiers

PMID34731170
PMCPMC8565767
OpenAlexW3208211169

What OpenQuestion holds

Textmetadata
LicenceCC0
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.