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Large, high‐intensity fire events in southern California shrublands: debunking the fine‐grain age patch model

Overview of attention for article published in Ecological Applications, January 2009
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
4 news outlets
blogs
5 blogs
policy
1 policy source
twitter
12 X users
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
111 Dimensions

Readers on

mendeley
181 Mendeley
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Title
Large, high‐intensity fire events in southern California shrublands: debunking the fine‐grain age patch model
Published in
Ecological Applications, January 2009
DOI 10.1890/08-0281.1
Pubmed ID
Authors

Jon E. Keeley, Paul H. Zedler

Abstract

We evaluate the fine-grain age patch model of fire regimes in southern California shrublands. Proponents contend that the historical condition was characterized by frequent small to moderate size, slow-moving smoldering fires, and that this regime has been disrupted by fire suppression activities that have caused unnatural fuel accumulation and anomalously large and catastrophic wildfires. A review of more than 100 19th-century newspaper reports reveals that large, high-intensity wildfires predate modern fire suppression policy, and extensive newspaper coverage plus first-hand accounts support the conclusion that the 1889 Santiago Canyon Fire was the largest fire in California history. Proponents of the fine-grain age patch model contend that even the very earliest 20th-century fires were the result of fire suppression disrupting natural fuel structure. We tested that hypothesis and found that, within the fire perimeters of two of the largest early fire events in 1919 and 1932, prior fire suppression activities were insufficient to have altered the natural fuel structure. Over the last 130 years there has been no significant change in the incidence of large fires greater than 10,000 ha, consistent with the conclusion that fire suppression activities are not the cause of these fire events. Eight megafires (> or = 50,000 ha) are recorded for the region, and half have occurred in the last five years. These burned through a mosaic of age classes, which raises doubts that accumulation of old age classes explains these events. Extreme drought is a plausible explanation for this recent rash of such events, and it is hypothesized that these are due to droughts that led to increased dead fine fuels that promoted the incidence of firebrands and spot fires. A major shortcoming of the fine-grain age patch model is that it requires age-dependent flammability of shrubland fuels, but seral stage chaparral is dominated by short-lived species that create a dense surface layer of fine fuels. Results from the Behave Plus fire model with a custom fuel module for young chaparral shows that there is sufficient dead fuel to spread fire even under relatively little winds. Empirical studies of fuel ages burned in recent fires illustrate that young fuels often comprise a major portion of burned vegetation, and there is no difference between evergreen chaparral and semi-deciduous sage scrub. It has also been argued that the present-day fire size distribution in northern Baja California is a model of the historical patterns that were present on southern California landscapes. Applying this model with historical fire frequencies shows that the Baja model is inadequate to maintain these fire-prone ecosystems and further demonstrates that fire managers in southern California are not likely to learn much from studying modern Baja California fire regimes. Further supporting this conclusion are theoretical cellular automata models of fire spread, which show that, even in systems with age dependent flammability, landscapes evolve toward a complex age mosaic with a plausible age structure only when there is a severe stopping rule that constrains fire size, and only if ignitions are saturating.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 181 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 4%
Australia 3 2%
Brazil 2 1%
Turkey 1 <1%
Germany 1 <1%
Canada 1 <1%
Portugal 1 <1%
Spain 1 <1%
Argentina 1 <1%
Other 0 0%
Unknown 162 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 47 26%
Student > Master 29 16%
Student > Ph. D. Student 19 10%
Other 15 8%
Student > Bachelor 11 6%
Other 38 21%
Unknown 22 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 54 30%
Environmental Science 53 29%
Earth and Planetary Sciences 15 8%
Engineering 6 3%
Social Sciences 6 3%
Other 8 4%
Unknown 39 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 82. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 September 2020.
All research outputs
#517,425
of 25,371,288 outputs
Outputs from Ecological Applications
#113
of 3,326 outputs
Outputs of similar age
#1,530
of 183,274 outputs
Outputs of similar age from Ecological Applications
#1
of 25 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,326 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.5. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 183,274 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.