Cited by 245Fire effects on ecosystemsRangeland and Wildlife ManagementFire dynamics and safety research

The DOI matches its Crossref record; 94 of the 99 references it cites were found in a registry or an index.

Wildland fire as a self‐regulating mechanism: the role of previous burns and weather in limiting fire progression

Abstract

Theory suggests that natural fire regimes can result in landscapes that are both self‐regulating and resilient to fire. For example, because fires consume fuel, they may create barriers to the spread of future fires, thereby regulating fire size. Top‐down controls such as weather, however, can weaken this effect. While empirical examples demonstrating this pattern–process feedback between vegetation and fire exist, they have been geographically limited or did not consider the influence of time between fires and weather. The availability of remotely sensed data identifying fire activity over the last four decades provides an opportunity to explicitly quantify the ability of wildland fire to limit the progression of subsequent fire. Furthermore, advances in fire progression mapping now allow an evaluation of how daily weather as a top‐down control modifies this effect. In this study, we evaluated the ability of wildland fire to create barriers that limit the spread of subsequent fire along a gradient representing time between fires in four large study areas in the western United States. Using fire progression maps in conjunction with weather station data, we also evaluated the influence of daily weather. Results indicate that wildland fire does limit subsequent fire spread in all four study areas, but this effect decays over time; wildland fire no longer limits subsequent fire spread 6–18 years after fire, depending on the study area. We also found that the ability of fire to regulate subsequent fire progression was substantially reduced under extreme conditions compared to moderate weather conditions in all four study areas. This study increases understanding of the spatial feedbacks that can lead to self‐regulating landscapes as well as the effects of top‐down controls, such as weather, on these feedbacks. Our results will be useful to managers who seek to restore natural fire regimes or to exploit recent burns when managing fire.

Overview

Integrity signals

Registry

Crossref · 10.1890/14-1430.1

Cites

94 of 94 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Flagged first, then by citations

Show all 99 references

5 of the 99 references couldn’t be matched to a known paper.

Research works printed but not linked: 13

  1. Agee J. K, 1999, Fire effects on landscape fragmentation in interior West forests, Forest fragmentation: wildlife and management implications, 323
  2. Beckman S, 2008, An assessment of wildland fire use in areas of the Selway-Bitterroot and Frank Church-River of No Return Wilderness
  3. ESRI, 2012, ArcMap version 10.1
  4. Gibson C. E, 2005, Fire history polygons for Northern Rockies, 1889–2003
  5. Hijmans R. J, 2011, Geographic analysis and modeling with raster data
  6. Keane R. E, 1994, Landscape assessment of the decline of whitebark-pine (Pinus albicaulis) in the Bob Marshall Wilderness Complex, Montana, USA, Northwest Science, 68, 213
  7. Keane R. E, 2002, The cascading effects of fire exclusion in Rocky Mountain ecosystems, Rocky Mountain futures: an ecological perspective, 133
  8. NCAR, 2013, Verification: Weather Forecast Verification Utilities. R package version 1.36
  9. 10.1023/A:1021584519109 · DOI
  10. Swetnam T. W, 1985, Fire history of ponderosa pine forests in the Gila Wilderness, New Mexico, Proceedings–symposium and workshop on wilderness fire, 390
  11. USDA Forest Service, 1924, Annual grazing report
  12. USDA Forest Service, 2003, The Frank Church-River of No Return wilderness management plan
  13. U.S. Environmental Protection Agency, 2014, Climate change indicators in the United States, 2014

Cited by

Sorted by citations

Items 201–245 of 245

Metadata

Authors
Parks, S. A., Holsinger, L. M., Miller, C., & Nelson, C. R.
Affiliations
  • US Forest Service (US)
  • University of Montana (US)
Corresponding author
Parks, Sean A.
Venue
Ecological Applications
Publisher
Wiley
Published
2015-09
Volume
25
Issue
6
Pages
1478-1492
ISSN
  • 1051-0761 (ISSN-L)
  • 1939-5582
OpenAlex
W2160689515
Cited by
239
References
99
Citations by year
2026: 18 · 2025: 19 · 2024: 21 · 2023: 23 · 2022: 19 · 2021: 26 · 2020: 20 · 2019: 22 · 2018: 19 · 2017: 20 · 2016: 24 · 2015: 8
FWCI
21.03
Type
journal article
Language
en
Open access
closed
Locations
  • Ecological Applications (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Fire effects on ecosystems
  • Physical Sciences › Environmental Science › Ecology › Rangeland and Wildlife Management
  • Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Fire dynamics and safety research
Keywords
forest fires, fire regimes, fire barriers, time since fire, fire management, natural fire regimes
MeSH terms
Conservation of Natural Resources, Environmental Monitoring, Fires, United States, Weather

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review