SCIENCE®!!!! discovers what my dad (a civil engineer) taught me more than 50 years ago.
New paper published in Nature Communications.
Here is the abstract and introduction to this open access paper, which of course has the obligatory nod to “climate change” no matter how insignificant to the result.
Abstract
Fire suppression is the primary management response to wildfires in many areas globally. By removing less-extreme wildfires, this approach ensures that remaining wildfires burn under more extreme conditions. Here, we term this the “suppression bias” and use a simulation model to highlight how this bias fundamentally impacts wildfire activity, independent of fuel accumulation and climate change. We illustrate how attempting to suppress all wildfires necessarily means that fires will burn with more severe and less diverse ecological impacts, with burned area increasing at faster rates than expected from fuel accumulation or climate change. Over a human lifespan, the modeled impacts of the suppression bias exceed those from fuel accumulation or climate change alone, suggesting that suppression may exert a significant and underappreciated influence on patterns of fire globally. Managing wildfires to safely burn under low and moderate conditions is thus a critical tool to address the growing wildfire crisis.
Introduction
Wildfires are becoming more destructive and deadly around the world1,2,3,4. The societal and ecological impacts of fires5,6 are in our collective consciousness—from Australia’s 2019–2020 megafires7, to destructive wildfires in the Mediterranean8, to beloved giant sequoias killed by fire in California9—prompting widespread calls to address the wildfire crisis8,10,11,12,13,14. We understand the broad drivers of increasing fire activity: changes in climate1,15,16, vegetation and fuel accumulation8,17,18, and ignition patterns19. However, humans also play a direct role in modifying fire activity across much of the globe by engaging with fires minutes to hours after ignition (i.e., initial attack20,21), and subsequent suppression of escaped fires22,23,24. While weather, fuels, topography, and ignitions determine how fires might burn, humans strongly shape this into when, where, and how fires do burn (Fig. 1).
a Potential fire behavior depends on the fire triangle (topography, weather, fuel) and ignitions. Intentional ignitions (i.e., prescribed fires and cultural burning) do not pass through the suppression filter, as they are allowed to burn unimpeded if within prescription. Unplanned human ignitions and lightning ignitions only burn if they successfully pass through the “suppression filter.” Fire “removed” by the suppression filter leads to fuel accumulation, influencing fires from all ignition types (suppression paradox, brown color). Wildfires that do burn are biased toward the fire that was not removed (suppression bias, red). These wildfires, together with intentional fires, form the realized fire regime with the suppression paradox and suppression bias inherently incorporated. b The suppression filter. 1) Initial attack success probability as a function of fireline intensity and fire size at initial attack (from Hirsch et al.69); 2) Proportion of escaped fire suppressed as a function of fire intensity. Suppression becomes increasingly impossible at high fire intensities. Colors depict the suppression scenarios used in the simulation. c Fire perimeters (viewed from overhead) after the first day of burning for an example ignition. Colors correspond to suppression scenarios shown in panel b. Fire intensity of the burned area is displayed with a color ramp.
a Potential fire behavior depends on the fire triangle (topography, weather, fuel) and ignitions. Intentional ignitions (i.e., prescribed fires and cultural burning) do not pass through the suppression filter, as they are allowed to burn unimpeded if within prescription. Unplanned human ignitions and lightning ignitions only burn if they successfully pass through the “suppression filter.” Fire “removed” by the suppression filter leads to fuel accumulation, influencing fires from all ignition types (suppression paradox, brown color). Wildfires that do burn are biased toward the fire that was not removed (suppression bias, red). These wildfires, together with intentional fires, form the realized fire regime with the suppression paradox and suppression bias inherently incorporated. b The suppression filter. 1) Initial attack success probability as a function of fireline intensity and fire size at initial attack (from Hirsch et al.69); 2) Proportion of escaped fire suppressed as a function of fire intensity. Suppression becomes increasingly impossible at high fire intensities. Colors depict the suppression scenarios used in the simulation. c Fire perimeters (viewed from overhead) after the first day of burning for an example ignition. Colors correspond to suppression scenarios shown in panel b. Fire intensity of the burned area is displayed with a color ramp.
a Potential fire behavior depends on the fire triangle (topography, weather, fuel) and ignitions. Intentional ignitions (i.e., prescribed fires and cultural burning) do not pass through the suppression filter, as they are allowed to burn unimpeded if within prescription. Unplanned human ignitions and lightning ignitions only burn if they successfully pass through the “suppression filter.” Fire “removed” by the suppression filter leads to fuel accumulation, influencing fires from all ignition types (suppression paradox, brown color). Wildfires that do burn are biased toward the fire that was not removed (suppression bias, red). These wildfires, together with intentional fires, form the realized fire regime with the suppression paradox and suppression bias inherently incorporated. b The suppression filter. 1) Initial attack success probability as a function of fireline intensity and fire size at initial attack (from Hirsch et al.69); 2) Proportion of escaped fire suppressed as a function of fire intensity. Suppression becomes increasingly impossible at high fire intensities. Colors depict the suppression scenarios used in the simulation. c Fire perimeters (viewed from overhead) after the first day of burning for an example ignition. Colors correspond to suppression scenarios shown in panel b. Fire intensity of the burned area is displayed with a color ramp.
Wildfires only burn if they are not extinguished through suppression. Thus, suppression is a “filter” that allows certain types of fire to pass through while removing other types of fire (Fig. 1b). In some locations (e.g., a remote wilderness area) this filter may be relatively porous, and many fires may burn with only minimal suppression25. In most landscapes, however, aggressive suppression of fire is a cultural expectation, and the suppression filter is much less permeable, with only the most extreme fires escaping (e.g., Maximum suppression in Fig. 1)20,21. Intentional fires (i.e., prescribed fires and cultural burning) are the only types of fires that do not pass through the suppression filter, as they are allowed to burn unimpeded if they are within prescription (Fig. 1a). Area that does not burn because it was “removed” through suppression, results in fuel accumulation and ultimately increases the likelihood and intensity of future fires26,27 (Fig. 1a). This well-known consequence has been termed the “fire suppression paradox”28,29: by putting out a fire today, we make fires harder to put out in the future26,30,31,32 (Table 1).
Term | Definition | Mechanism | Impact | Time lag |
---|---|---|---|---|
Fire suppression paradox | By suppressing fire today, we increase fuel loads, making fires harder to suppress in the future | Fuel accumulation | Indirect | Future |
Fire suppression bias | By suppressing some fire types more than others, the remainder reflects a biased representation of fire types | Differential suppression filter | Direct | Immediate |
Suppressing wildfires also has an additional and poorly quantified consequence that we define as the “suppression bias”: fire suppression extinguishes some types of fire (e.g., surface fire) more than others (e.g., crown fire), and thus skews the resulting fire activity toward those types less likely to be removed (Table 1). In contemporary fire management, which easily suppresses and removes low-intensity fire, this bias is inevitably toward higher-intensity burning occurring under extreme weather20,21,33,34,35. Thus, the fires which ecosystems, species, and people experience are skewed towards the most severe and destructive.
We define management approaches that suppress lower-intensity fire more heavily than higher-intensity fire as “regressive suppression,” borrowing language from economics (e.g., a regressive tax rate decreases as taxable income increases) (Table 2). In some instances, however, management could contain and suppress relatively higher-intensity fire more heavily than lower-intensity fire, an approach we term “progressive suppression” (e.g., a progressive tax rate increases as taxable income increases) (Table 2). Both regressive and progressive suppression are subject to the same upper limit, above which fires are simply too intense to suppress (Fig. 1b)36; however, within the domain where suppression is possible, regressive and progressive approaches can have profoundly different impacts (i.e., biases) on the way fires burn.
Type of suppression | Definition | Direction of suppression bias |
---|---|---|
Regressive suppression | Suppresses lower-intensity fire more heavily than higher-intensity fire | Toward higher-intensity fires, more extreme fires |
Progressive suppression | Suppresses higher-intensity fire more heavily than lower-intensity fire | Toward lower-intensity fires, more moderate fires |
Although the fire suppression bias has been referenced tangentially in the literature8,28,33,37,38,39, the emergent impacts of the suppression bias have not been assessed. This is largely due to the difficulty of isolating the impact of suppression with empirical data. Suppression is so ubiquitous that we have virtually no control landscapes where fire is completely unsuppressed; even in remote wilderness areas, some fires are still suppressed40. Furthermore, it is difficult to measure the magnitude of suppression efforts because even relatively direct proxies such as suppression cost are confounded by other factors, including terrain accessibility, human infrastructure at risk, and availability of suppression resources41. Finally, data on suppression efforts are generally only available for larger fires42, obscuring the many ignitions that are quickly and easily suppressed during initial attack20,21. To overcome these constraints, we used a simulation approach to assess and quantify the magnitude of the fire suppression bias on fire behavior and ecological impacts, relative to the influence of climate change and fuel accumulation.
Our modeling framework simulates fundamental components of fires: weather and fuel moisture; ignitions; fire growth; fire suppression (through initial attack and containment of escaped fires); and ecological effects. To isolate the effect of fire suppression, we simulated thousands of fires with identical biophysical conditions, but which differed only in their suppression scenario, including three “regressive suppression” scenarios (Moderate, High, and Maximum; Fig. 1b), one “progressive suppression” scenario (Progressive; Fig. 1b), and a control scenario with no suppression. For each fire, we calculated the proportion burned at high severity, average fire severity, daily and total fire size, and the diversity of fire severity43. To compare the influence of suppression to that of climate change and fuel accumulation, we simulated fires across a range of plausible current and future fuel aridity (vapor pressure deficit; VPD) and fuel loading conditions in forest ecosystems in North America. These ranges represent a 240-year time period of modeled increases (e.g., increased VPD based on RCP 8.5 climate scenario44; fuel loading rates based on historical fuel modeling45).
Using this modeling framework, we show how the suppression bias directly influences fire activity and subsequent fire effects. Specifically, we asked: 1) How does fire suppression influence patterns of area burned, ecological impacts (i.e., fire severity), and the diversity of both factors over space and time? 2) How does the magnitude of this influence compare to that from climate change and fuel accumulation?
The title of the first paragraph of the result section is pretty straightforward
Results
Regressive fire suppression makes fires more severe
You can read the full, obvious, known forever, realizations about forest and land management article here.
https://www.nature.com/articles/s41467-024-46702-0
H/T Duane
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