Spot-fire distance increases disproportionately for wildfires compared to prescribed fires as grasslands transition to Juniperus woodlands

Victoria M Donovan; Dillon T Fogarty; Dirac Twidwell

doi:10.1371/journal.pone.0283816

. 2023 Apr 11;18(4):e0283816. doi: 10.1371/journal.pone.0283816

Spot-fire distance increases disproportionately for wildfires compared to prescribed fires as grasslands transition to Juniperus woodlands

Victoria M Donovan ^1,^2,^*, Dillon T Fogarty ¹, Dirac Twidwell ¹

Editor: Walter Finsinger³

PMCID: PMC10089345 PMID: 37040377

Abstract

Woody encroachment is one of the greatest threats to grasslands globally, depleting a suite of ecosystem services, including forage production and grassland biodiversity. Recent evidence also suggests that woody encroachment increases wildfire danger, particularly in the Great Plains of North America, where highly volatile Juniperus spp. convert grasslands to an alternative woodland state. Spot-fire distances are a critical component of wildfire danger, describing the distance over which embers from one fire can cause a new fire ignition, potentially far away from fire suppression personnel. We assess changes in spot-fire distances as grasslands experience Juniperus encroachment to an alternative woodland state and how spot-fire distances differ under typical prescribed fire conditions compared to conditions observed during wildfire. We use BehavePlus to calculate spot-fire distances for these scenarios within the Loess Canyons Experimental Landscape, Nebraska, U.S.A., a 73,000-ha ecoregion where private-lands fire management is used to reduce woody encroachment and prevent further expansion of Juniperus fuels. We found prescribed fire used to control woody encroachment had lower maximum spot-fire distances compared to wildfires and, correspondingly, a lower amount of land area at risk to spot-fire occurrence. Under more extreme wildfire scenarios, spot-fire distances were 2 times higher in grasslands, and over 3 times higher in encroached grasslands and Juniperus woodlands compared to fires burned under prescribed fire conditions. Maximum spot-fire distance was 450% greater in Juniperus woodlands compared to grasslands and exposed an additional 14,000 ha of receptive fuels, on average, to spot-fire occurrence within the Loess Canyons Experimental Landscape. This study demonstrates that woody encroachment drastically increases risks associated with wildfire, and that spot fire distances associated with woody encroachment are much lower in prescribed fires used to control woody encroachment compared to wildfires.

Introduction

Woody encroachment is one of the greatest threats to grasslands globally [1–6], increasing the level of degradation to one of the world’s most at-risk ecosystems [7,8]. As a system transitions from a grassland state to a woody state, rapid and persistent changes in system processes and structure occur [9–11]. For instance, woody encroachment can alter grassland properties by shifting a system from below to above ground biomass storage [12], decreasing grassland species richness and diversity [3,13], altering soil carbon and nitrogen [14], decreasing herbaceous biomass production [15,16], and increasing demands on the water table [17]. Changes in fuel structure during the transition from a grassland to woodland state also shift fire regime characteristics from frequent, low flame length surface fires in grasslands to infrequent, high flame length crown fires in woodlands [11,18], with recent evidence suggesting that this transition can increase large wildfire risk [19].

Given recent trends of increasing wildfire activity and woody encroachment in North America [4,20,21], there is a need to quantify relationships between fire risk and woody encroachment so land managers can make informed decisions tied to fire management and planning. In regions like the North American Great Plains, woody encroachment can largely be tied to the loss of frequent fire in grassland systems due to fire suppression and the loss of human fire stewardship practices [1,22]. The application of prescribed fire in grassland and woodland states can prevent and reverse woody encroachment [23–25]. For instance, using high intensity fire to burn juniper woodlands has been shown to overcome hysteretic thresholds and return a system to grassland dominance [23]. However, prescribed fire has not been widely implemented across North America [26,27]. Fire is often viewed as unnatural and risky outside of the scientific community [28–30]. Perceived risks associated with prescribed fires often outweigh that of woody encroachment, meaning that many land managers are more likely to allow woody encroachment than apply prescribed fire [27,31]. However, the increase in woody vegetation in the Great Plains has been associated with recent surging wildfire activity, with risk of large wildfire increasing once woody cover exceeds 20% of the landscape [19,21]. Since it is clear that fire cannot be removed from flammable landscapes [32,33], there is a need to quantify the relative risk of wildfire versus the risk of prescribed fire to control woody encroachment.

One of the greatest concerns associated with managing fire on a landscape is spot fire [34–36]. Spot fires are fires that start outside of the original fire perimeter from lofted sparks or firebrands and can act as a significant mechanism of fire spread [35]. Fire brands can overcome typical methodologies of fire risk reduction like fuel breaks and remain a primary reason why many private and public land managers are hesitant to conduct prescribed burns [30,34]. Escaped fires can be disastrous, resulting in the destruction of property and loss of life [37,38]. Long range spotting that carries embers far outside of the immediate fire area can be more difficult to monitor, control, and suppress. Spotting has played a major role in destructive wildfires [36]. Greater maximum potential spotting distance can increase fire spread rate and fire escape, enhancing the probability for property damage and loss of life.

In this study, we use spot fire distance to examine the relative risk of using prescribed fire to control woody plants at various stages of the encroachment process versus waiting for wildfire to occur. Spot fires are dependent on sequential mechanisms of generation, transport, and ignition in receptive fuels (i.e. fuels that can ignite from a firebrand and support the spread of wildland fire) [35]. During the process of woody encroachment, we predict that the shift towards a woodland will increase the risk of spot fire by enhancing the probability of fire brand generation and lofting. Because of the restricted wind speeds under which prescribed fires occur, we predict that prescribed fires will have lower maximum spot fire distances, regardless of encroachment stage, and thus, have lower risk potential compared to wildfire.

We use the Loess Canyons Experimental Landscape in Nebraska as a model landscape for our assessment. This region has experienced substantial encroachment from eastern redcedar (Juniperus virginiana), a prevalent native invader in the Great Plains that overruns grasslands in the absence of controlling processes like fire [11,22,39]. Prescribed fires are being used to prevent woody encroachment in remaining grasslands in the Loess Canyons, but because of the extent of encroachment already prevalent on the landscape, landowners are also using prescribed fire to remove established juniper trees in invaded areas to revert them back to grasslands [23,40]. Quantifying the relative risks of employing prescribed fire as a controlling process for woody encroachment versus waiting for wildfire to occur will help land mangers make informed decisions regarding the application of prescribed fire to manage woody encroachment.

Materials and methods

Study area

The Loess Canyons Experimental Landscape is a 73,000-ha area of mixed grass prairie located in south-central Nebraska (Fig 1). The landscape represents a private-lands approach to science co-production [41] where partnerships among landowners, natural resource agencies, and scientists support landowner-led efforts to confront a regional trend of woody encroachment [40]. Vegetation communities can be described based on a gradient of woody encroachment from un-encroached mixed grass prairie to a juniper woodland state that has resulted from unchecked woody encroachment into grassland areas. Prior to European settlement, the region experienced frequent fire (6–10 year fire return interval) [42] and was maintained as a prairie region with minimal tree cover. However, fire exclusion has resulted in woody encroachment and the widespread establishment of juniper woodlands. Canyons are the primary landform, with elevation ranging from 781–989 m above sea level. Mean annual precipitation is 550 mm, with the majority of rainfall occurring in the growing season. Mean annual temperature is 9.8°C (climate data is from [43]).

Between 2002 and 2019, over 90 prescribed burns have been conducted in the Loess Canyons Experimental Landscape to assist in regional-scale grassland restoration [23]. Prescribed burns were conducted by local prescribed burn associations and ranged in size from 9–1,041 ha. Burns are typically conducted between early February and late April and target fire intensities that exceed juniper mortality thresholds [46]. Fuel manipulation is used to increase prescribed fire intensity. Prescribed burns in the Loess Canyons Experimental Landscape therefore result in high rates of woodland collapse and stimulate herbaceous plant recovery [23]. The Loess Canyons is currently in the reclamation phase of restoration, and thus, a prescribed fire return interval has yet to be established in this region.

Maximum spot fire distance models

To predict spot fire behaviour, we calculated maximum spot fire distance using BehavePlus software v. 5.0.5. BehavePlus is a mathematical fire simulation program that predicts fire behaviour relative to environmental and fuel-based characteristics using a point system, where conditions are assumed uniform. It is widely used by fire managers in the U.S. to predict fire behaviour and assess wildland fuel hazards [47]. The SPOT module in BehavePlus calculates maximum spot fire distance based on models developed by Albini [48–50] for both surface fire and torching trees [51].

We used BehavePlus to compare the relative spot fire distance that could occur as a result of fire burning under three different levels of juniper encroachment: grassland, juniper encroached grassland, and juniper woodland. To identify the appropriate fuel model input for BehavePlus spot fire calculations, we mapped the distribution of receptive fuel beds in and around the Loess Canyons using maps of Anderson Fire Behaviour Fuel Models [52]. This data contains 13 standard fire behaviour models that represent standard surface fuel arrangements [53] that can serve as input for fire behaviour and fire spread models in BehavePlus (Table 1; S1 Fig). Non-receptive fuels in this land cover classification included agriculture, water, snow/ice, urban areas, and barren areas.

Table 1. Summary of fuel models and their percent cover within the Loess Canyons.

Fuel models and descriptions are from Anderson, [53]. The percent cover of each fuel model type within the Loess Canyons and a surrounding 5 mile buffer were calculated using data from LANDFIRE [52].

Fuel Model	Typical Fuel Complex ^a	Description ^b	% Cover within the Loess Canyons ^c
FBFM1	Grass and grass-dominated: Short grass (1 foot)	Fire spread is rapid and determined by fine continuous herbaceous fuels that are cured and curing, very little shrub or timber present, primarily grasslands and savanna	15%
FBFM2	Grass and grass-dominated: Timber (grass understory)	Fire spread is through fine, herbaceous fuels though litter and dead down stem wood may contribute to spread, open shrub or timber over story cover 1/3 to 2/3 of area	54%
FBFM3	Grass and grass-dominated: Tall grass (2.5 feet)	Most intense fire of grass group, high rates of spread, stands average 3 ft tall, 1/3 or more of stand is dead or cured	6%
FBFM5	Chaparral and shrub fields: Brush (2 ft)	Low intensity fires carried by litter, young shrubs that almost totally cover an area with little dead material	7%
FBFM6	Chaparral and shrub fields: Dormant brush, hardwood slash	Fire spread through shrub layer and requires moderate winds to maintain flame at shrub height	<0.1%
FBFM8	Timber Litter: Closed timber litter	Slow fire spread through ground fuels with low flame lengths, closed canopy stands with short needle conifers or hardwoods, only under severe weather conditions to fuels pose a fire hazard	7%
FBFM9	Timber Litter: Hardwood litter	Longer flames and quicker surface fires than FBFM8, leaves in the fall can cause spot fire, dead-down woody material can lead to possible torching, spotting and crowing	<0.1%
Non-Burnable		Urban, agriculture, water, barren	11%

Open in a new tab

^a Typical fuel complex reported in Anderson, [53].

^b Description summarised from Anderson, [53].

^c Percentages calculated from LANDFIRE [52].

We represented grasslands with the fuel model FBFM1 (Tables 2 and 3), which represents fuel characteristics for short grass, the most common fuel type in the Loess Canyons based on classification by LANDFIRE’s Anderson Fire Behaviour Fuel Models landcover maps (Table 1). Because both surface and canopy fuels can contribute to potential spot fires in encroached grasslands, we modelled maximum spotting distance in juniper encroached grasslands in two ways. First, we modelled surface fire in juniper encroached grasslands using fuel model FBFM2 (Tables 2 and 3), which represents grassy timber understory (Table 1). Second, we modelled a single torching tree (Table 3). Tree species was set as Grand fir since juniper species models were not available at the time this study was conducted. In a study conducted by Blunck et al. [54], grand fir and western juniper species were shown to have similar ember flux (number of embers deposited in a region) relative to Doug-fir and Ponderosa pine. We compared spot fire distances modelled using the surface fire model and torching tree model for encroached grasslands. Because outputs were similar, we used surface fire outputs to represent spot fire distances in encroached grasslands because they were slightly higher at higher wind speeds. We modelled a juniper woodland as 30 torching trees (Table 3), the maximum number of torching trees that could be modelled in the BehavePlus in order to represent a dense juniper woodland state.

Table 2. Model parameters for calculating flame length values to be input into surface fire spotting distance models.

Model parameter	Value	Justification
Grassland State
Fuel Model	1	Most common grassland fuel model
1-h Fuel Moisture	7%	Minimum recommend fuel moisture to burn under during a prescribed burn [34]
Midflame Wind Speed	0–52 km/h	Calculated by multiplying 6 m wind speed with a correction factor of 0.4 [55]
Slope Steepness	0%	Tests indicated there was little influence of slopes measured in the Loess Canyons on flame length except under low wind speeds, which resulted in minimal changes to spot fire distance.
Encroached Grassland
Fuel Model	2	Represents juniper invaded grassland
1-h Moisture	7%	Minimum recommend fuel moisture to burn under during a prescribed burn [34]
10-h Moisture	8%	Weir [34] suggests a range of 6–15% fuel moisture for 10-h fuels during prescribed fires. National Wildfire Coordinating Group recommends adding 1–2% fuel moisture content to 1-h fuels to calculate 10-h fuel moisture values [55]. We added 1%.
100-h Moisture	9%	NRCS [56] suggests a range of 7–20% fuel moisture for 100-h fuels during prescribed fires. National Wildfire Coordinating Group recommends adding 2–4% fuel moisture content to 1-h fuels to calculate 100-h fuel moisture values [55]. We added 2%.
Live Herbaceous Moisture	30%	Minimum possible in BehavePlus
Mid-flame Wind Speed	0–52 km/h	Calculated by multiplying 6 m wind speed with a correction factor of 0.4 [55]
Slope Steepness	0%	Tests indicated there was little influence of slopes measured in the Loess Canyons on flame length except under low wind speeds, which resulted in minimal changes to spot fire distance.

Open in a new tab

Table 3. Fuel model parameters and justification for spot fire distance models.

Model parameter	Value	Justification
Grassland State
Downwind Canopy Height	0 m	Minimum possible in BehavePlus
20-ft Wind Speed	0–129 km/h	NOAA wind speed records from North Platte Regional Airport Weather Station indicated wind gusts could reach up to 137 km/h in the Loess Canyons region. 129 km/h was the maximum wind speed that could be modelled by BehavePlus.
Ridge-to-Valley Elevation Difference	0 m	There was no influence of elevation on spot fire distance.
Flame Length	0–2.1 m	Recorded flame length varied slightly relative to wind speed.
Encroached Grassland
Downwind Canopy Height	0 m	Minimum possible in BehavePlus
20-ft Wind Speed	0–129 km/h	NOAA wind speed records from North Platte Regional Airport Weather Station indicated wind gusts could reach up to 137 km/h in the Loess Canyons region. 129 km/h was the maximum wind speed that could be modelled by BehavePlus.
Ridge-to-Valley Elevation Difference	0 m	There was no influence of elevation on spot distance.
Flame Length	0–9.9 m	Flame length varied based on wind speed.
Woodland State
Downwind Canopy Height	0 m	Minimum possible in BehavePlus
Torching Tree Height	12 m	Maximum tree height recorded during field sampling in the Loess Canyons [40].
Spot Tree Species	Grand Fir	There are no juniper species models in BehavePlus. In a study conducted by [54], grand fir and western juniper species were shown to have similar ember flux (number of embers deposited in a region), relative to Doug-fir and Ponderosa pine.
DBH	45.7 cm	The mid-point in the range of juniper DBH [57].
20-ft wind speed	0–129 km/h	NOAA wind speed records from North Platte Regional Airport Weather Station indicated wind gusts could reach up to 137 km/h in the Loess Canyons region. 129 km/h was the maximum wind speed that could be modelled by BehavePlus.
Ridge-to-Valley Elevation Difference	0	Elevations changes observed in the Loess Canyons had no influence on spot fire distance.
Number of Torching Trees	30	Maximum number of torching trees allowed in BehavePlus

Open in a new tab

Surface spot fire models require a flame length and slope parameter. Flame length was calculated in BehavePlus (Table 2). We set fuel moisture at 7–9% to match the minimum recommend fuel moisture to burn under during a prescribed burn [34] (Table 2). Slope was sampled across the Loess Canyons using 120 random sampling points. We assessed the influence of slope on flame length in BehavePlus, setting the maximum slope value assessed to match the maximum percent slope value recorded in the Loess Canyons (45%). While slope influenced flame length, it had little to no influence on spot fire distance. Thus, we held slope constant at zero in our simulations (Tables 2 and 3).

Both tree height and tree diameter influence spot fire distance. For both of our torching tree scenarios, diameter at breast height was set to the mid-point in the range of DBH reported by Lawson [57] for mature juniper trees (Table 3). Tree height was set at maximum juniper height recorded during sampling in the Loess Canyons [40] (Table 3).

To determine maximum wind speed for our assessment, we used NOAA (www.climate.gov) wind speed records from North Platte Regional Airport Weather Station (Latitude = 41.1213, Longitude = -100.669) between 2010 and 2020, which indicated that wind gusts could reach up to 137 km/h in the Loess Canyons region. However, 129 km/h was the maximum wind speed that could be modelled by BehavePlus. Thus, we set the maximum wind speed at 129 km/h.

We ran models for maximum spot fire distance with wind speeds ranging from 0–129 km/h over a 1.6 km/h (1 mph) interval. In Nebraska, burn plans need to be approved by local fire chiefs, and thus wind speed limits on prescribed burns vary by plan and fire chief [58]. Best management practice guidelines set maximum wind speeds between 24 and 40 km/h [34,58,59]. We represented prescribed fire conditions as the center point of this range (32 km/h) and below. All wind speeds were considered potential wildfire conditions. Changes in maximum spot fire distance relative to juniper encroachment scenario and wind speed were plotted with R statistical software [60,61].

In addition, receptive fuels were mapped using the LANDFIRE 2014 data set. Non-receptive fuels in the Loess Canyons included water, barren lands, agriculture, and urban areas (Table 1). Receptive fuel included short and tall grass, timber with grassy understory, brush, and hardwood and closed timber litter (Table 1). We used buffers representing maximum spot fire distance under different encroachment and wind speed scenarios around prescribed fire burn units in the Loess Canyons to assess how receptive fuel exposure changed with woody encroachment level and wind speed in the Loess Canyons.

Results

Woody encroachment substantially increased maximum potential spot fire distance in grasslands in the Loess Canyons (Fig 2). Maximum spot fire distance did not exceed 1.4 km even under the most extreme wind conditions in grasslands (129 km/h wind speeds; Figs 2 and 3), exposing an average of 1,559 ha ± 471 SD of receptive fuels to spot fire (Figs 3 and 4). In encroached grasslands, this distance was more than doubled (4.3 km; Fig 2), exposing an average 7,912 ha ± 1,654 SD of receptive fuels to potential spot fire (Figs 3 and 4). Following a transition to a woodland state, the maximum spotting distance more than quadrupled, reaching nearly 7 km (Fig 2), and exposing an average of 15,825 ha ± 2681 SD of receptive fuels to spot fire (Figs 3 and 4).

Fig 3 — Column 1 shows a landscape representation of changes in the potential exposure of receptive fuels relative to maximum spot fire distance from burn units in the Loess Canyons if they were all grassland (yellow), all juniper encroached grassland (orange), and all woodland (red). Column 2 focuses on changes in maximum spot fire distance relative to a single burn unit, where black lines represent the circumference of potential spot fire exposure and coloured lines represent the maximum spot fire distance if the burn unit was all grassland (yellow), woody encroached grassland (orange), or woodland (red). Column 3 lists maximum spot fire distances for each encroachment scenario. Green areas in maps represent receptive fuels and grey areas represent non-receptive fuels (urban areas, agriculture, water, barren areas) [52]. Maps were generated using ArcGIS [45].

Fires that burned under prescribed fire wind conditions had lower spot fire risk at each stage of woody encroachment compared to those that burned under the full range of wind conditions. Maximum potential spot fire distances decreased by a factor of ~2 in grasslands under typical prescribed fire conditions (32 km/h wind speeds) compared to high wind speeds that only occur during wildfires (129 km/h; 0.8 km versus 1.4 km; Fig 2). Fires that burn under typical prescribed fire wind speeds also had much lower receptive fuel exposure than fires that burn under wind speeds only seen during wildfire. Receptive fuel exposure was 1,559 ha ± 471 SD under high wind speed conditions (129 km/h) compared to 690 ha ± 388 SD under typical prescribed fire wind conditions in grasslands (Figs 3 and 4). Differences between typical prescribed fire spotting risk versus wildfire spotting risk were further distinguished as woody encroachment progressed. Maximum potential spot fire distance decreased by a factor of ~3 under prescribed fire conditions compared to the high wind speeds only observed during wildfire in encroached grasslands (1.3 km versus 4.3) and Juniperus woodlands (6.6 km versus 2.6 km; Fig 2). Moreover, fires that burned under a typical prescribed fire wind speed decreased average receptive fuel exposure by a factor of over 7 compared to fires that burned under wildfire conditions in encroached grasslands (from 7,912 ha ± 1,654 SD to 1,025 ha ± 489 SD; Figs 3 and 4) and in juniper woodlands (from 2,102 ha ± 749 SD to 15,825 ha ± 2,681 SD).

Discussion

Prescribed fires have less spot fire risk than wildfires, regardless of the stage of woody encroachment. Spot fire distances under typical prescribed fire conditions were 2- to 3-fold less than those associated with high wind speeds that only occur during wildfires in the same stage of woody encroachment. A key implication from our results is that using prescribed fire as a controlling process for woody encroachment, either by sustaining existing grasslands or restoring grasslands that have been encroached, has a high potential to reduce fire risk compared to waiting for wildfire to occur. Fire was a critical feedback in grasslands that has not been replaced at large scales and this is compromising our ability to prevent long-term trends of increasing wildfire risk [62,63]. Repeated prescribed fires in grasslands are a well-known and effective method for preventing woody encroachment [4,64,65], while using high intensity prescribed fire in juniper woodlands can reverse woody encroachment [23,46]. For instance, Bielski et al. [23] demonstrate the ability of high intensity fire generated by fuel additions to restore herbaceous biomass following a state-transition to a juniper woodland. However, re-encroachment following high intensity burns in juniper woodlands can begin 1–2 years post-fire and proceeds along a rapid, nonlinear trajectory [15,40]. Thus, frequent low intensity prescribed fires are needed in either maintained or restored grasslands to prevent woody encroachment.

Woody encroachment increases spot fire risk. Maximum spot fire distance greatly increased as sites shifted from a grassland to a woodland state in the Loess Canyons. Woody vegetation is associated with more extreme fire behavior including long flame lengths that can exceed 14 m, making fires that ignite the crown in woody fuels more difficult to control and suppress [11]. It has been speculated that the high propensity for wildfire in woody vegetation in the Great Plains is associated with lower probabilities of fire suppression [19]. Efforts to reduce future wildfire risk should focus on maintaining grassland sites using prescribed fire, which we show have the lowest spot fire risk. Prescribed fires applied after woody encroachment has begun will require higher fire intensities to drive mortality of mature juniper [25,46], while lower intensity fires can be used to control juvenile woody plants. Management can often underinvest at the early stages of encroachment and overinvest in the later stages where control is less likely, more costly, and as we demonstrate, hosts greater risk [39,66,67]. Our results further emphasize that early application of prescribed fires is the best strategy for reducing fire risk in flammable ecosystems like the Great Plains.

Prescribed fires will help reduce the costs of fire management and suppression. Identifying and suppressing spot fire requires sufficient allocation of ground crews, air tankers, Unmanned Ariel Devices (UAVs), or other resources across the potential spot fire range to conduct fire suppression tasks and asset protection [68–70]. We found that woody encroachment substantially increased potential spot fire distance and subsequently the amount of area that needed to be monitored during the application of prescribed fire, indicating there is higher risk associated with applying prescribed burns after encroachment has already begun. However, fire management costs will be further exacerbated by waiting for wildfires to occur, which increased the area of potential spot fire occurrence in our assessment. Because it is clear that fire cannot be removed from flammable landscapes [32,33], applying prescribed fires, regardless of encroachment phase, will decrease demands on suppression personnel and equipment and risks to human life and property. Land managers tend to be more likely to allow woody encroachment than apply prescribed fire [27,31]. However, with both wildfires and woody encroachment increasing across much of North America [20,21,71], continuing to avoid prescribed fire application will strain already limited fire management resources that struggle to keep up with increasing large wildfire occurrence [21,33].

Changing social perspectives and double-think management policies tied to woody vegetation and fire will be imperative to promoting pro-active grassland management [39]. Fire and afforestation policies based on the assumption that fire can be eliminated from landscapes need to be re-evaluated [21,32,33]. Often management policies and social perspectives oppose well established ecological knowledge tied to woody encroachment and fire [26,39]. It is clear that fire is an inevitable terrestrial ecosystem process that maintains and benefits grassland systems [22,72–75]. Co-existence with fire was achieved through fire stewardship by the Indigenous peoples of North America for thousands of years before Euro-American colonisation [22,75,76]. Elimination of human stewarded fire increases fuel accumulation and woody vegetation, promoting large wildfires outside of human control that can lead to losses of human life and property [19,21]. As we demonstrate, there is higher risk associated with wildfires that burn in woody encroached grasslands. Yet afforestation of grasslands is still largely promoted and subsidised [77–79]. Moreover, prescribed fire application is highly regulated, where fire ban policies, strict liability laws, and lack of private citizen knowledge of prescribed fire limits its use across grasslands [11,31,78,80]. Continued outreach and education regarding the benefits of prescribed fire for reducing wildfire risk associated with woody encroachment is needed.

There are clear social-ecological benefits to applying wide-spread prescribed fire in grassy ecosystems [11,63,81]. Typical brush control methods are associated with significant economic investments that function at too small of a scale to combat the wide-spread woody encroachment occurring in the Great Plains [78]. Intensive control methods for juniper, like herbicides, can cost over $90 per hectare to apply compared to prescribed fire treatments which cost less than $5 per hectare [82]. Prescribed fires can prevent and reverse woody encroachment to mitigate wildfire risk [11,23,46]. In addition, prescribed fires can boost forage production [83], enhance grassland biodiversity and wildlife habitat [84–86], and control invasive species [87,88]. Our results provide an additional level of scientific support for the application of prescribed fire in grassland systems that can be used to support policy and management that promote pro-active prescribed fire application.

Supporting information

S1 Fig. The distribution of Anderson [53] fuel models in the Loess Canyons (dark grey outline) from LANDFIRE [52].

(TIF)

Click here for additional data file.^{(3.8MB, tif)}

Acknowledgments

We thank landowners in the Loess Canyons who provided their prescribed burn information.

Data Availability

Data is available on Dryad via https://doi.org/10.5061/dryad.vmcvdncxs.

Funding Statement

DT received funding Nebraska Game & Parks Commission (W-125-R-1) http://outdoornebraska.gov/ Nebraska Environmental Trust (20-139-2) https://environmentaltrust.nebraska.gov/ University of Nebraska’s Institute of Agriculture and Natural Resources https://ianr.unl.edu/ The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1.Briggs JM, Knapp AK, Blair JM, Heisler JL, Hoch GA, Lett MS, et al. An Ecosystem in Transition: Causes and Consequences of the Conversion of Mesic Grassland to Shrubland. BioScience. 2005;55: 243–254. doi: 10.1641/0006-3568(2005)055[0243:AEITCA]2.0.CO;2 [DOI] [Google Scholar]
2.Fensham RJ, Fairfax RJ, Archer SR. Rainfall, land use and woody vegetation cover change in semi-arid Australian savanna. Journal of Ecology. 2005;93: 596–606. doi: 10.1111/j.1365-2745.2005.00998.x [DOI] [Google Scholar]
3.Ratajczak Z, Nippert JB, Collins SL. Woody encroachment decreases diversity across North American grasslands and savannas. Ecology. 2012;93: 697–703. doi: 10.1890/11-1199.1 [DOI] [PubMed] [Google Scholar]
4.Archer SR, Andersen EM, Predick KI, Schwinning S, Steidl RJ, Woods SR. Woody Plant Encroachment: Causes and Consequences. Rangeland Systems. Springer, Cham; 2017. pp. 25–84. doi: 10.1007/978-3-319-46709-2_2 [DOI] [Google Scholar]
5.Mistry J, Schmidt IB, Eloy L, Bilbao B. New perspectives in fire management in South American savannas: The importance of intercultural governance. Ambio. 2019;48: 172–179. doi: 10.1007/s13280-018-1054-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Sühs RB, Giehl ELH, Peroni N. Preventing traditional management can cause grassland loss within 30 years in southern Brazil. Scientific Reports. 2020;10: 783. doi: 10.1038/s41598-020-57564-z [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Hoekstra JM, Boucher TM, Ricketts TH, Roberts C. Confronting a biome crisis: global disparities of habitat loss and protection. Ecology Letters. 2005;8: 23–29. doi: 10.1111/j.1461-0248.2004.00686.x [DOI] [Google Scholar]
8.Newbold T, Hudson LN, Arnell AP, Contu S, Palma AD, Ferrier S, et al. Has land use pushed terrestrial biodiversity beyond the planetary boundary? A global assessment. Science. 2016;353: 288–291. doi: 10.1126/science.aaf2201 [DOI] [PubMed] [Google Scholar]
9.Holling CS. Resilience and Stability of Ecological Systems. Annual Review of Ecology and Systematics. 1973;4: 1–23. doi: 10.1146/annurev.es.04.110173.000245 [DOI] [Google Scholar]
10.Scheffer M, Carpenter S, Foley JA, Folke C, Walker B. Catastrophic shifts in ecosystems. Nature. 2001;413: 591–596. doi: 10.1038/35098000 [DOI] [PubMed] [Google Scholar]
11.Twidwell D, Rogers WE, Fuhlendorf SD, Wonkka CL, Engle DM, Weir JR, et al. The rising Great Plains fire campaign: citizens’ response to woody plant encroachment. Frontiers in Ecology and the Environment. 2013;11: e64–e71. doi: 10.1890/130015 [DOI] [Google Scholar]
12.McKinley DC, Norris MD, Blair JM, Johnson LC. Altered Ecosystem Processes as a Consequence of Juniperus virginiana L. Encroachment into North American Tallgrass Prairie. In: Auken OWV, editor. Western North American Juniperus Communities. Springer New York; 2008. pp. 170–187. doi: 10.1007/978-0-387-34003-6_9 [DOI] [Google Scholar]
13.Price JN, Morgan JW. Woody plant encroachment reduces species richness of herb-rich woodlands in southern Australia. Austral Ecology. 2008;33: 278–289. doi: 10.1111/j.1442-9993.2007.01815.x [DOI] [Google Scholar]
14.McKinley DC, Blair JM. Woody Plant Encroachment by Juniperus virginiana in a Mesic Native Grassland Promotes Rapid Carbon and Nitrogen Accrual. Ecosystems. 2008;11: 454–468. doi: 10.1007/s10021-008-9133-4 [DOI] [Google Scholar]
15.Briggs JM, Hoch GA, Johnson LC. Assessing the Rate, Mechanisms, and Consequences of the Conversion of Tallgrass Prairie to Juniperus virginiana Forest. Ecosystems. 2002;5: 578–586. doi: 10.1007/s10021-002-0187-4 [DOI] [Google Scholar]
16.Fuhlendorf SD, Archer SA, Smeins F, Engle DM, Taylor CA. The Combined Influence of Grazing, Fire, and Herbaceous Productivity on Tree–Grass Interactions. In: Van Auken OW, editor. Western North American Juniperus Communities: A Dynamic Vegetation Type. New York, NY: Springer; 2008. pp. 219–238. doi: 10.1007/978-0-387-34003-6_12 [DOI] [Google Scholar]
17.Scott RL, Huxman TE, Williams DG, Goodrich DC. Ecohydrological impacts of woody-plant encroachment: seasonal patterns of water and carbon dioxide exchange within a semiarid riparian environment. Global Change Biology. 2006;12: 311–324. doi: 10.1111/j.1365-2486.2005.01093.x [DOI] [Google Scholar]
18.Finney MA, McHugh CW, Grenfell IC, Riley KL, Short KC. A simulation of probabilistic wildfire risk components for the continental United States. Stoch Environ Res Risk Assess. 2011;25: 973–1000. doi: 10.1007/s00477-011-0462-z [DOI] [Google Scholar]
19.Donovan VM, Wonkka CL, Wedin DA, Twidwell D. Land-use type as a driver of large wildfire occurrence in the U.S. Great Plains. Remote Sensing. 2020;12: 1869. doi: 10.3390/rs12111869 [DOI] [Google Scholar]
20.Dennison PE, Brewer SC, Arnold JD, Moritz MA. Large wildfire trends in the western United States, 1984–2011. Geophys Res Lett. 2014;41: 2014GL059576. doi: 10.1002/2014GL059576 [DOI] [Google Scholar]
21.Donovan VM, Wonkka CL, Twidwell D. Surging wildfire activity in a grassland biome. Geophys Res Lett. 2017;44: 2017GL072901. doi: 10.1002/2017GL072901 [DOI] [Google Scholar]
22.Engle DM, Coppedge BR, Fuhlendorf SD. From the Dust Bowl to the Green Glacier: Human Activity and Environmental Change in Great Plains Grasslands. In: Auken OWV, editor. Western North American Juniperus Communities. Springer New York; 2008. pp. 253–271. doi: 10.1007/978-0-387-34003-6_14 [DOI] [Google Scholar]
23.Bielski CH, Scholtz R, Donovan VM, Allen CR, Twidwell D. Overcoming an “irreversible” threshold: A 15-year fire experiment. Journal of Environmental Management. 2021;291: 112550. doi: 10.1016/j.jenvman.2021.112550 [DOI] [PubMed] [Google Scholar]
24.O’Connor RC, Taylor JH, Nippert JB. Browsing and fire decreases dominance of a resprouting shrub in woody encroached grassland. Ecology. 2020;101: e02935. doi: 10.1002/ecy.2935 [DOI] [PubMed] [Google Scholar]
25.Twidwell D, Rogers WE, Wonkka CL, Taylor CA, Kreuter UP. Extreme prescribed fire during drought reduces survival and density of woody resprouters. Journal of Applied Ecology. 2016;53: 1585–1596. doi: 10.1111/1365-2664.12674 [DOI] [Google Scholar]
26.Bernardo D, Engle D. The effect of manager risk attitudes on range improvement decisions. Journal of Range Management. 1990;43: 242–249. [Google Scholar]
27.Harr RN, Morton LW, Rusk SR, Engle DM, Miller JR, Debinski D. Landowners’ perceptions of risk in grassland management: woody plant encroachment and prescribed fire. Ecology and Society. 2014;19. [Google Scholar]
28.Bowman DMJS, Balch J, Artaxo P, Bond WJ, Cochrane MA, D’Antonio CM, et al. The human dimension of fire regimes on Earth. Journal of Biogeography. 2011;38: 2223–2236. doi: 10.1111/j.1365-2699.2011.02595.x [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Morton LW, Regen E, Engle DM, Miller JR, Harr RN. Perceptions of Landowners Concerning Conservation, Grazing, Fire, and Eastern Redcedar Management in Tallgrass Prairie. Rangeland Ecology & Management. 2010;63: 645–654. doi: 10.2111/REM-D-09-00041.1 [DOI] [Google Scholar]
30.Weir JR, Kreuter UP, Wonkka CL, Twidwell D, Stroman DA, Russell M, et al. Liability and Prescribed Fire: Perception and Reality. rama. 2019;72: 533–538. doi: 10.1016/j.rama.2018.11.010 [DOI] [Google Scholar]
31.Stroman DA, Kreuter UP, Wonkka CL. Landowner perceptions of woody plants and prescribed fire in the Southern Plains, USA. PLOS ONE. 2020;15: e0238688. doi: 10.1371/journal.pone.0238688 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Moritz MA, Batllori E, Bradstock RA, Gill AM, Handmer J, Hessburg PF, et al. Learning to coexist with wildfire. Nature. 2014;515: 58–66. doi: 10.1038/nature13946 [DOI] [PubMed] [Google Scholar]
33.Schoennagel T, Balch JK, Brenkert-Smith H, Dennison PE, Harvey BJ, Krawchuk MA, et al. Adapt to more wildfire in western North American forests as climate changes. PNAS. 2017;114: 4582–4590. doi: 10.1073/pnas.1617464114 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Weir JR. Conducting prescribed fires: A comprehensive manual. College Station, Texas, USA: Texas A&M University Press; 2009. [Google Scholar]
35.Koo E, Pagni PJ, Weise DR, Woycheese JP, Koo E, Pagni PJ, et al. Firebrands and spotting ignition in large-scale fires. Int J Wildland Fire. 2010;19: 818–843. doi: 10.1071/WF07119 [DOI] [Google Scholar]
36.Cruz MG, Sullivan AL, Gould JS, Sims NC, Bannister AJ, Hollis JJ, et al. Anatomy of a catastrophic wildfire: The Black Saturday Kilmore East fire in Victoria, Australia. Forest Ecology and Management. 2012;284: 269–285. doi: 10.1016/j.foreco.2012.02.035 [DOI] [Google Scholar]
37.Ryan KC, Knapp EE, Varner JM. Prescribed fire in North American forests and woodlands: history, current practice, and challenges. Frontiers in Ecology and the Environment. 2013;11: e15–e24. doi: 10.1890/120329 [DOI] [Google Scholar]
38.Wonkka CL, Rogers WE, Kreuter UP. Legal barriers to effective ecosystem management: exploring linkages between liability, regulations, and prescribed fire. Ecological Applications. 2015;25: 2382–2393. doi: 10.1890/14-1791.1 [DOI] [PubMed] [Google Scholar]
39.Roberts CP, Uden DR, Allen CR, Twidwell D. Doublethink and scale mismatch polarize policies for an invasive tree. PLOS ONE. 2018;13: e0189733. doi: 10.1371/journal.pone.0189733 [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Fogarty DT, de Vries C, Bielski C, Twidwell D. Rapid Re-encroachment by Juniperus virginiana After a Single Restoration Treatment. Rangeland Ecology & Management. 2021;78: 112–116. doi: 10.1016/j.rama.2021.06.002 [DOI] [Google Scholar]
41.Naugle DE, Allred BW, Jones MO, Twidwell D, Maestas JD. Coproducing Science to Inform Working Lands: The Next Frontier in Nature Conservation. BioScience. 2020;70: 90–96. doi: 10.1093/biosci/biz144 [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Guyette RP, Stambaugh MC, Dey DC, Muzika R-M. Predicting fire frequency with chemistry and climate. Ecosystems. 2012;15: 322–335. [Google Scholar]
43.Arguez A, Durre I, Applequist S, Vose RS, Squires MF, Yin X, et al. NOAA’s 1981–2010 U.S. Climate Normals: An Overview. Bulletin of the American Meteorological Society. 2012;93: 1687–1697. doi: 10.1175/BAMS-D-11-00197.1 [DOI] [Google Scholar]
44.U.S. Department of Commerce. State boundaries (generalized for mapping)—ScienceBase-Catalog. 2012. [cited 21 Feb 2023]. Available: https://www.sciencebase.gov/catalog/item/52c78623e4b060b9ebca5be5. [Google Scholar]
45.ESRI. ArcGIS Desktop. Redlands, California, USA: Environmental Systems Research Institute; 2023. [Google Scholar]
46.Twidwell D, Fuhlendorf SD, Taylor CA, Rogers WE. Refining thresholds in coupled fire–vegetation models to improve management of encroaching woody plants in grasslands. J Appl Ecol. 2013;50: 603–613. doi: 10.1111/1365-2664.12063 [DOI] [Google Scholar]
47.Andrews PL. BehavePlus fire modeling system: Past, present, and future. In: Proceedings of 7th Symposium on Fire and Forest Meteorology; 23–25 October 2007, Bar Harbor, Maine Boston, MA: American Meteorological Society 13 p. 2007 [cited 14 Aug 2020]. Available: https://www.fs.usda.gov/treesearch/pubs/31549.
48.Albini FA. Potential spotting distance from wind-driven surface fires. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station; 1983. p. 27 p. Report No.: Research Paper INT-309. [Google Scholar]
49.Albini FA. Spot fire distance from isolated sources-extensions of a predictive model. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station; 1981. p. 9 p. Report No.: Research Note INT-309. [Google Scholar]
50.Albini FA. Spot fire distance from burning trees-a predictive model. Ogden, UT: USDA Forest Service, Intermountain Forest and Range Experiment Station; 1979. p. 73 p. Report No.: General Technical Report INT-GTR-56. [Google Scholar]
51.Morris G. A simple method for computing spotting distances from wind-driven surface fires, Research Note INT-374. Ogden, UT: US Department of Agriculture, Forest Service, Intermountain Research Station; 1987. p. 6 p. Report No.: Research Note INT-374. [Google Scholar]
52.LANDFIRE. 13 Anderson Fire Behavior Fuel Models. U.S. Department of the Interior, Geological Survey, and U.S. Department of Agriculture; 2014. Available: Accessed 4/30/2020 from https://landfire.gov/index.php. [Google Scholar]
53.Anderson HE. Aids to determining fuel models for estimating fire behavior. Ogden, UT: US Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station; 1982. Report No.: Gen. Tech. Rep. INT-122. [Google Scholar]
54.Blunck DL, Butler BW, Bailey JD, Wagenbrenner NS. Multi-scale study of ember production and transport under multiple environmental and fuel conditions—Final Report to the Joint Fire Science Program. Joint Fire Science Program; 2019. [Google Scholar]
55.National Wildfire Coordinating Group. Fire Behaviour Field Reference Guide. National Wildfire Coordinating Group; 2019. Report No.: PMS 437. Available: https://www.nwcg.gov/publications/pms437. [Google Scholar]
56.NRCS. Natural Resources Conservation Service Conservation Practice Standard: Prescribed burning (Ac.) code 338 . USDA Natural Resources Conservation Service- North Mexico; 2011. pp. 1–9. [Google Scholar]
57.Lawson ER. Eastern redcedar (Juniperus virginiana L.). Fayetteville, AR: United States Department of Agriculture, Forest Service; 1986. Report No.: FS-260. [Google Scholar]
58.Volesky JD, Stubbendieck JL, Mitchell RB. Conducting a prescribed burn and prescribed burning checklist. Lincoln, Nebraska, USA: University of Nebraska-Lincoln Extension; 2007. Report No.: EC121. [Google Scholar]
59.NRCS. Prescribed burning fact sheet. USDA Natural Resources Conservation Service- North Dakota; 2012. Report No.: 338. [Google Scholar]
60.R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2018. Available: https://www.R-project.org/. [Google Scholar]
61.Wickham H. ggplot2: Elegant Graphics for Data Analysis. New York, NY: Springer-Verlag; 2016. Available: http://ggplot2.org. [Google Scholar]
62.Bond WJ, Keeley JE. Fire as a global ‘herbivore’: the ecology and evolution of flammable ecosystems. Trends in Ecology & Evolution. 2005;20: 387–394. doi: 10.1016/j.tree.2005.04.025 [DOI] [PubMed] [Google Scholar]
63.Fuhlendorf SD, Engle DM, Elmore RD, Limb RF, Bidwell TG. Conservation of Pattern and Process: Developing an Alternative Paradigm of Rangeland Management. Rangeland Ecology & Management. 2012;65: 579–589. doi: 10.2111/REM-D-11-00109.1 [DOI] [Google Scholar]
64.Miller JED, Damschen EI, Ratajczak Z, Özdoğan M. Holding the line: three decades of prescribed fires halt but do not reverse woody encroachment in grasslands. Landscape Ecol. 2017;32: 2297–2310. doi: 10.1007/s10980-017-0569-9 [DOI] [Google Scholar]
65.Capozzelli JF, Miller JR, Debinski DM, Schacht WH. Restoring the fire–grazing interaction promotes tree–grass coexistence by controlling woody encroachment. Ecosphere. 2020;11: e02993. doi: 10.1002/ecs2.2993 [DOI] [Google Scholar]
66.Epanchin-Niell RS, Liebhold AM. Benefits of invasion prevention: effect of time lags, spread rates, and damage persistence. Ecological Economics. 2015;116: 146–153. [Google Scholar]
67.Yokomizo H, Possingham HP, Thomas MB, Buckley YM. Managing the impact of invasive species: the value of knowing the density–impact curve. Ecological Applications. 2009;19: 376–386. doi: 10.1890/08-0442.1 [DOI] [PubMed] [Google Scholar]
68.Simpson H, Bradstock R, Price O. A Temporal Framework of Large Wildfire Suppression in Practice, a Qualitative Descriptive Study. Forests. 2019;10: 884. doi: 10.3390/f10100884 [DOI] [Google Scholar]
69.Twidwell D, Allen CR, Detweiler C, Higgins J, Laney C, Elbaum S. Smokey comes of age: unmanned aerial systems for fire management. Frontiers in Ecology and the Environment. 2016;14: 333–339. doi: 10.1002/fee.1299 [DOI] [Google Scholar]
70.Weir JR, Twidwell D, Wonkka CL. Prescribed burn association activity, needs, and safety record: a survey of the Great Plains. Great Plains Fire Science Exchange GPE Publication. 2015;6: 19. [Google Scholar]
71.Fogarty DT, Roberts CP, Uden DR, Donovan VM, Allen CR, Naugle DE, et al. Woody plant encroachment and the sustainability of priority conservation areas. Sustainability. 2020;12: 8321. doi: 10.3390/su12208321 [DOI] [Google Scholar]
72.Anderson RC. Evolution and origin of the Central Grassland of North America: climate, fire, and mammalian grazers1. tbot. 2006;133: 626–647. doi: 10.3159/1095-5674(2006)133[626:EAOOTC]2.0.CO;2 [DOI] [Google Scholar]
73.Anderson RC. The historic role of fire in the North American grassland. In: Collins SL, Wallace LL, editors. Fire in North American tallgrass prairies. Norman, OK: University of Oklahoma Press; 1990. pp. 8–18. [Google Scholar]
74.Bowman DMJS Balch JK, Artaxo P Bond WJ, Carlson JM Cochrane MA, et al. Fire in the Earth System. Science. 2009;324: 481–484. doi: 10.1126/science.1163886 [DOI] [PubMed] [Google Scholar]
75.Pyne SJ. Fire: a brief history. Seattle, WA, USA: University of Washington Press; 2001. [Google Scholar]
76.Twidwell D, Bielski CH, Scholtz R, Fuhlendorf SD. Advancing Fire Ecology in 21st Century Rangelands. Rangeland Ecology & Management. 2020. [cited 30 Apr 2021]. doi: 10.1016/j.rama.2020.01.008 [DOI] [Google Scholar]
77.Donovan VM, Burnett JL, Bielski CH, Birgé HE, Bevans R, Twidwell D, et al. Social–ecological landscape patterns predict woody encroachment from native tree plantings in a temperate grassland. Ecology and Evolution. 2018;8: 9624–9632. doi: 10.1002/ece3.4340 [DOI] [PMC free article] [PubMed] [Google Scholar]
78.Garmestani A, Twidwell D, Angeler DG, Sundstrom S, Barichievy C, Chaffin BC, et al. Panarchy: opportunities and challenges for ecosystem management. Frontiers in Ecology and the Environment. 2020;18: 576–583. doi: 10.1002/fee.2264 [DOI] [PMC free article] [PubMed] [Google Scholar]
79.Veldman JW, Overbeck GE, Negreiros D, Mahy G, Stradic SL, Fernandes GW, et al. Tyranny of trees in grassy biomes. Science. 2015;347: 484–485. doi: 10.1126/science.347.6221.484-c [DOI] [PubMed] [Google Scholar]
80.Twidwell D, West AS, Hiatt WB, Ramirez AL, Taylor Winter J, Engle DM, et al. Plant Invasions or Fire Policy: Which Has Altered Fire Behavior More in Tallgrass Prairie? Ecosystems. 2016;19: 356–368. doi: 10.1007/s10021-015-9937-y [DOI] [Google Scholar]
81.Sangha KK, Evans J, Edwards A, Russell-Smith J, Fisher R, Yates C, et al. Assessing the value of ecosystem services delivered by prescribed fire management in Australian tropical savannas. Ecosystem Services. 2021;51: 101343. doi: 10.1016/j.ecoser.2021.101343 [DOI] [Google Scholar]
82.Ortmann J, Stubbendieck J, Masters RA, Pfeiffer G, Bragg T. Efficacy and costs of controlling eastern redcedar. Journal of Range Management. 2012;51: 158–163. [Google Scholar]
83.Augustine DJ, Derner JD, Milchunas DG. Prescribed Fire, Grazing, and Herbaceous Plant Production in Shortgrass Steppe. Rangeland Ecology & Management. 2010;63: 317–323. doi: 10.2111/REM-D-09-00044.1 [DOI] [Google Scholar]
84.Fuhlendorf SD, Harrell WC, Engle DM, Hamilton RG, Davis CA, Leslie DM Jr. Should Heterogeneity Be the Basis for Conservation? Grassland Bird Response to Fire and Grazing. Ecological Applications. 2006;16: 1706–1716. doi: 10.1890/1051-0761(2006)016[1706:shbtbf]2.0.co;2 [DOI] [PubMed] [Google Scholar]
85.Hovick TJ, Allred BW, Elmore RD, Fuhlendorf SD, Hamilton RG, Breland A. Dynamic Disturbance Processes Create Dynamic Lek Site Selection in a Prairie Grouse. PLoS One. 2015;10: e0137882. doi: 10.1371/journal.pone.0137882 [DOI] [PMC free article] [PubMed] [Google Scholar]
86.Starns HD, Fuhlendorf SD, Elmore RD, Twidwell D, Thacker ET, Hovick TJ, et al. Effects of pyric herbivory on prairie-chicken (Tympanuchus spp) habitat. PLOS ONE. 2020;15: e0234983. doi: 10.1371/journal.pone.0234983 [DOI] [PMC free article] [PubMed] [Google Scholar]
87.DiTomaso JM, Brooks ML, Allen EB, Minnich R, Rice PM, Kyser GB. Control of invasive weeds with prescribed burning. Weed Technology. 2006;20: 535–548. [Google Scholar]
88.Kral K, Limb R, Ganguli A, Hovick T, Sedivec K. Seasonal prescribed fire variation decreases inhibitory ability of Poa pratensis L. and promotes native plant diversity. J Environ Manage. 2018;223: 908–916. doi: 10.1016/j.jenvman.2018.06.096 [DOI] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0283816.r001

Decision Letter 0

Walter Finsinger

23 Nov 2022

PONE-D-22-20383

Prescribed fire reduces wildfire risk from woody encroachment in grasslands

PLOS ONE

Dear Dr. Donovan,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

I'm awfully sorry to get back to you after such a long time. Meanwhile, I received comments from one reviewer and additionally assessed the manuscript myself. The reviewer noted that the manuscript should be improved as it lacked clarity in some parts of the text and Figures could be reduced and improved.

Please also find my additional thoughts:

L55: am not sure as to whether the term "extreme fire" is sufficiently clear in this context. Does "extreme" refer to the fire severity?

L103-104: here you mention that vegetation communities are dominated by two "alternative states: mixed grass prairie communities and monoculture woodlands consisting of mature juniper trees".

However, as of L131-132 it seems that there are at least three different levels of juniper encroachment, including vegetation types ranging from grasslands, to juniper encroached grasslands, to juniper woodland.

Moreover, I wonder whether the term "monoculture woodlands" may cause confusion, as it may be associated with plantation forestry.

L189-192: it is not entirely clear why the Wildfire category does not include fires occurring at low wind speeds. I can see the arguments for limiting the occurrence of "Prescribed Fires" to a certain range of wind speeds, but wonder on which basis the occurrence of wildfires at low wind speeds is excluded. In other words: why not include fires occurring at low wind speeds in the wildfire category and modify the text and Figures 2-4.

L192: could you clarify which smoothing function you used and show in Figure 2 the actual non smoothed values (for instance as empty circles) ?

L235-255: (Following my suggestion to L189-192) To my humble understanding, you are assuming that wildfires never occur at low wind speeds, which explains the categorisation into "prescribed fires" and "wildfires". By contrast, you could take another, eventually more balanced viewpoint to argue that fires occurring at low wind speeds (such as prescribed fires) have lower spot fire distances. Further, I might be wrong, but think that lower spot-fire distances in less-encroached landscapes may reduce the risk of fire spread, but I wonder if they would reduce the risk of fire occurrence.

Caption to Figure 1: could you clarify what land-cover types are included in the "non-receptive fuels" category?

Figure 1: an inset showing the location of Nebraska in N-America may be useful.

Figure 2: the yellow and orange lines seem to intercept the y-axis at slightly negative values, thus at negative maximum spotting distance.

Figure 4: could you highlight in Figure 1 (or in Figure 4 Column 1) the single burn unit that is shown in Column 2 ?

Please submit your revised manuscript by Jan 07 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Walter Finsinger, PhD

Academic Editor

PLOS ONE

Journal requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/fileid=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf.

2. Thank you for stating the following in the Acknowledgments Section of your manuscript:

“Funding for this research was provided by Nebraska Game & Parks Commission (W-125-R-1), Nebraska Environmental Trust (20-139-2), and the University of Nebraska’s Institute of Agriculture and Natural Resources. We thank landowners in the Loess Canyons who provided their prescribed burn information.”

We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form.

Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows:

“DT received funding

Nebraska Game & Parks Commission (W-125-R-1) http://outdoornebraska.gov/

Nebraska Environmental Trust (20-139-2) https://environmentaltrust.nebraska.gov/

University of Nebraska’s Institute of Agriculture and Natural Resources https://ianr.unl.edu/

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.”

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

3. We note that [Figures 1 and 4] in your submission contain [map/satellite] images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth). For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright.

We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission:

a. You may seek permission from the original copyright holder of Figures 1 and 4 to publish the content specifically under the CC BY 4.0 license.

We recommend that you contact the original copyright holder with the Content Permission Form (http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:

“I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. Please reply and provide explicit written permission to publish XXX under a CC BY license and complete the attached form.”

Please upload the completed Content Permission Form or other proof of granted permissions as an ""Other"" file with your submission.

In the figure caption of the copyrighted figure, please include the following text: “Reprinted from [ref] under a CC BY license, with permission from [name of publisher], original copyright [original copyright year].”

b. If you are unable to obtain permission from the original copyright holder to publish these figures under the CC BY 4.0 license or if the copyright holder’s requirements are incompatible with the CC BY 4.0 license, please either i) remove the figure or ii) supply a replacement figure that complies with the CC BY 4.0 license. Please check copyright information on all replacement figures and update the figure caption with source information. If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only.

The following resources for replacing copyrighted map figures may be helpful:

USGS National Map Viewer (public domain): http://viewer.nationalmap.gov/viewer/

The Gateway to Astronaut Photography of Earth (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/

Maps at the CIA (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.html

NASA Earth Observatory (public domain): http://earthobservatory.nasa.gov/

Landsat: http://landsat.visibleearth.nasa.gov/

USGS EROS (Earth Resources Observatory and Science (EROS) Center) (public domain): http://eros.usgs.gov/#

Natural Earth (public domain): http://www.naturalearthdata.com/.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This study is aiming at guiding the stakeholders to choose the prescribed burn solution instead of waiting for wildfires to occur. The study site is in a mixed vegetation covers, offering three major landscape fuels: herb dominated, mixed herb and trees, and woodland.

I noticed three majors lacks of clear and complete details in the manuscript about the vegetation, about the landscape and about the modelling choices, that I would strongly suggest to address.

The first one is about the juniper species tested here, and not available in BehavePlus model. Even if there are similar ember flux between juniper tree and the fir considered, they don’t have the same vegetative height, moisture behavior, and flammable behavior.

As you considered partly juniper parameters directly, why not implemented directly the species into the model?

Furthermore, as it is an encroachment, the juniper trees are not mature, and should probably not attain the max height. I would suggest to use the median values instead.

We miss here important details on the fire regime (frequency, fire return intervals in the three different landscapes in wildfire conditions, is the prescribed burn annual?). We also miss information on how the fire ignition is modelled (fig. 4 landscape and single). why the ignition on the single fire panels is always at the same place? Where are the fire ignitions in landscape panels?

And most of all, in the encroachment landscape, the proportion of trees in the landscape is not detailed, as well as the torching trees portion in the trees and in the landscape.

In the discussion section, the authors stated that the prescribed fires mitigate the spot fire risk associated with wildfires, but they did not test this hypothesis. Indeed, they looked at the spot fires in these two different conditions, but did not run a wildfire after a prescribed burn in the same area. The fire risk is not reduced, but the area burned and the spot distance can be if a wildfire occurs after a prescribed burn.

In general, the differences, as stated in the results and discussion section are not tested.

Here are minor comments:

L 118-120 Seasonality and frequency of prescribed fires are lacking

L 132 what proportion of the landscape represents junipers in the encroachment landscape?

A figure of Loess Canyons Fuel complex will help to understand the fuel load and possible spread.

Fig 1: Rather than a small insert of Nebraska alone, readers can gain in having the juniper tree distribution map in the continental US

Table 3. what percentage that represents in the landscape 30 torching trees?

L 176 diameter

Fig 2 this maximum spot fire distance depends on the number of juniper trees in the landscape. Please add this information somewhere

Fig 2 and 3 are repetitive. I’ll go for fig 3 only, and change the caption (the difference is not tested here, but the range of values with the median highlighted in boxplots)

L 263 how a low intensity fire can burn a juniper tree while an intense fire is required to suppress them each 1-2 years? Is frequent here use to determine more than 1 burn a year?

L276 so this is a reverse version of what you just said.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2023 Apr 11;18(4):e0283816. doi: 10.1371/journal.pone.0283816.r002

Author response to Decision Letter 0

2 Mar 2023

Response to Review: Manuscript PONE-D-22-20383

Response to Editor

E1.1: L55: am not sure as to whether the term "extreme fire" is sufficiently clear in this context. Does "extreme" refer to the fire severity?

Response: We have changed the term to high intensity fire.

E1.2: L103-104: here you mention that vegetation communities are dominated by two "alternative states: mixed grass prairie communities and monoculture woodlands consisting of mature juniper trees". However, as of L131-132 it seems that there are at least three different levels of juniper encroachment, including vegetation types ranging from grasslands, to juniper encroached grasslands, to juniper woodland. Moreover, I wonder whether the term "monoculture woodlands" may cause confusion, as it may be associated with plantation forestry.

Response: Thank you for noting this. We have edited the text to read: “Vegetation communities can be described based on a gradient of woody encroachment from un-encroached mixed grass prairie to juniper woodlands that have resulted from unchecked woody encroachment into grassland areas.” We have removed the term “monoculture woodland” to avoid confusion.

E1.3: L189-192: it is not entirely clear why the Wildfire category does not include fires occurring at low wind speeds. I can see the arguments for limiting the occurrence of "Prescribed Fires" to a certain range of wind speeds, but wonder on which basis the occurrence of wildfires at low wind speeds is excluded. In other words: why not include fires occurring at low wind speeds in the wildfire category and modify the text and Figures 2-4.

Response: We have updated the manuscript to include all windspeeds in the wildfire category. The text has been correspondingly updated throughout, and we have edited Figures 3-4 to represent this change as recommended. Based on comment R1.10 from Reviewer 1, we have removed Figure 2 from the manuscript.

E1.4: L192: could you clarify which smoothing function you used and show in Figure 2 the actual non smoothed values (for instance as empty circles)?

Response: Based on comment R1.10 from Reviewer 1, we have removed Figure 2 from the manuscript.

E1.5: L235-255: (Following my suggestion to L189-192) To my humble understanding, you are assuming that wildfires never occur at low wind speeds, which explains the categorization into "prescribed fires" and "wildfires". By contrast, you could take another, eventually more balanced viewpoint to argue that fires occurring at low wind speeds (such as prescribed fires) have lower spot fire distances. Further, I might be wrong, but think that lower spot-fire distances in less-encroached landscapes may reduce the risk of fire spread, but I wonder if they would reduce the risk of fire occurrence.

Response: As suggested in E1.3, we have updated the manuscript to discuss wildfires as referring to the full range of wind speeds. We have updated the phrasing of this paragraph to reflect this change as suggested.

E1.6: Caption to Figure 1: could you clarify what land-cover types are included in the "non-receptive fuels" category?

Response: We removed the receptive and non-receptive fuels map from Fig 1 while revising to accommodate E1.7 and R1.6.

E1.7: Figure 1: an inset showing the location of Nebraska in N-America may be useful.

Response: Completed.

E1.8: Figure 2: the yellow and orange lines seem to intercept the y-axis at slightly negative values, thus at negative maximum spotting distance.

Response: Based on comment R1.10 from Reviewer 1, we have removed Figure 2 from the manuscript.

E1.9: Figure 4: could you highlight in Figure 1 (or in Figure 4 Column 1) the single burn unit that is shown in Column 2?

Response: We have highlighted the burn unit in Figure 4.

Response to Reviewer 1

R1.1: This study is aiming at guiding the stakeholders to choose the prescribed burn solution instead of waiting for wildfires to occur. The study site is in a mixed vegetation covers, offering three major landscape fuels: herb dominated, mixed herb and trees, and woodland.

I noticed three majors lacks of clear and complete details in the manuscript about the vegetation, about the landscape and about the modelling choices, that I would strongly suggest to address.

Furthermore, as it is an encroachment, the juniper trees are not mature, and should probably not attain the max height. I would suggest to use the median values instead.

Response: There is no juniper model available to use to model spot fire distance and to our knowledge, the data needed to develop our own model is not available. Thus, we chose the best option available to be input into Albini’s spot fire models.

We have clarified in the text that we selected surface fire models in an encroached grassland over the torching tree scenario to represent spot fire distances in encroached grasslands because, while similar, this model had slightly higher spot fire distances at high wind speeds and we were interested in maximum potential spot fire distances. Decreasing the tree height as suggested only decreases the spot fire distance from the torching tree, and thus, further supports our use of the surface fuel model to determine the maximum spot fire distance possible under this scenario.

R1.2: We miss here important details on the fire regime (frequency, fire return intervals in the three different landscapes in wildfire conditions, is the prescribed burn annual?). We also miss information on how the fire ignition is modelled (fig. 4 landscape and single). why the ignition on the single fire panels is always at the same place? Where are the fire ignitions in landscape panels? And most of all, in the encroachment landscape, the proportion of trees in the landscape is not detailed, as well as the torching trees portion in the trees and in the landscape.

Response: We have clarified in the text that we do not assess fire regime, only fire behavior predicted under each listed scenario. Behave Plus is based on a point system where conditions are assumed uniform. Thus, there is no spatial configuration associated with ignition. We have added this to the text. Figure 4 (now Figure 3- see our response to R1.10) simply visualizes the different maximum spot fire distances possible based on the fuel model outputs from different wind speeds and encroachment scenarios relative to burn unit perimeters used in the Loess Canyons. We have updated the language in the Figure caption to clarify this point.

R1.3: In the discussion section, the authors stated that the prescribed fires mitigate the spot fire risk associated with wildfires, but they did not test this hypothesis. Indeed, they looked at the spot fires in these two different conditions, but did not run a wildfire after a prescribed burn in the same area. The fire risk is not reduced, but the area burned and the spot distance can be if a wildfire occurs after a prescribed burn. In general, the differences, as stated in the results and discussion section are not tested.

Response: Thank you for this comment. We agree. We re-phrased sections of the abstract, results, and discussion to reflect our findings more clearly. We have also adjusted the title of our manuscript for further clarity. We think this will also bring more clarity to the questions raised by the reviewer in R1.2.

R1.4: L 118-120 Seasonality and frequency of prescribed fires are lacking

Response: As noted in the text, burns occur between early February and late April. The landscape is currently under reclamation; thus, burns are not currently being repeated. We have added this to the text. Also, please see our response to R1.2.

R1.5: L 132 what proportion of the landscape represents junipers in the encroachment landscape? A figure of Loess Canyons Fuel complex will help to understand the fuel load and possible spread.

Response: Fuel complex percentages in the Loess Canyons are summarized in Table 1. We have added a fuel complex map for the Loess Canyons to the supporting information (S1 Fig). Changes in tree cover in the Loess Canyons can be seen on the Rangeland Analysis Platform (https://rangelands.app/). Due to copyright limitations associated with PLOS’s open access policy, we cannot provide maps from the Rangeland Analysis Platform in our manuscript. However, the reviewer can view the Loess Canyons region by going to the coordinates (40.8611304, -100.2479634).

R1.6: Fig 1: Rather than a small insert of Nebraska alone, readers can gain in having the juniper tree distribution map in the continental US

Response: We have added a map inset of the United States to show where the Loess Canyons landscape falls and have color coded states based on the current distribution of Juniperus virginiana.

R1.7: Table 3. what percentage that represents in the landscape 30 torching trees?

Response: We selected 30 torching trees because it was the highest number of trees we could select in Behave Plus and thus would represent the densest woodland on the landscape. Data isn’t available to calculate the number of trees per unit area in the Loess Canyons. That said, using the Rangeland Analysis Platform, we have calculated that ~9% of the Loess Canyons has greater than 50% tree cover in 2020. Tree cover in the Loess Canyons can be seen on the Rangeland Analysis Platform (https://rangelands.app/). Due to copyright limitations associated with PLOS’s open access policy, we cannot provide a map. However, the reviewer can view the Loess Canyons region by going to the co-ordinates (40.8611304, -100.2479634).

R1.8: L 176 diameter

Response: Thank you for catching this. Fixed.

R1.9: Fig 2 this maximum spot fire distance depends on the number of juniper trees in the landscape. Please add this information somewhere

Response: Based on the reviewer’s comment in R1.10, we have removed Figure 2 from the manuscript.

R1.10: Fig 2 and 3 are repetitive. I’ll go for fig 3 only, and change the caption (the difference is not tested here, but the range of values with the median highlighted in boxplots)

Response: We have removed Fig 2 from the manuscript as recommended.

R1.11: L 263 how a low intensity fire can burn a juniper tree while an intense fire is required to suppress them each 1-2 years? Is frequent here use to determine more than 1 burn a year?

L276 so this is a reverse version of what you just said.

Response: Seedlings can be killed with low intensity fire but adult trees cannot. High intensity fire is needed to overcome adult juniper mortality thresholds. In the Loess Canyons, this is achieved through fuel manipulation. Following high intensity fire, juniper encroachment can rapidly begin again. Thus, frequent low intensity prescribed fires are needed to maintain grasslands following restoration with high intensity fire. We clarify this in the Discussion and note that fuel manipulation is used to achieve high intensity fire under prescribed fire conditions in the Loess Canyons in the Methods.

Attachment

Submitted filename: Response to Review3.docx

Click here for additional data file.^{(24.8KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0283816.r003

Decision Letter 1

Walter Finsinger

20 Mar 2023

Spot-fire distance increases disproportionately for wildfires compared to prescribed fires as grasslands transition to Juniperus woodlands

PONE-D-22-20383R1

Dear Dr. Donovan,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Walter Finsinger, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Please make sure all data underlying the findings in their manuscript fully available (see https://journals.plos.org/plosone/s/data-availability) and that there's a link from your paper to the repository holding the data.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

**********

6. Review Comments to the Author

Reviewer #1: (No Response)

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Berangere Leys

**********

PLoS One. doi: 10.1371/journal.pone.0283816.r004

Acceptance letter

Walter Finsinger

3 Apr 2023

PONE-D-22-20383R1

Spot-fire distance increases disproportionately for wildfires compared to prescribed fires as grasslands transition to Juniperus woodlands

Dear Dr. Donovan:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Walter Finsinger

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig. The distribution of Anderson [53] fuel models in the Loess Canyons (dark grey outline) from LANDFIRE [52].

(TIF)

Click here for additional data file.^{(3.8MB, tif)}

Attachment

Submitted filename: Response to Review3.docx

Click here for additional data file.^{(24.8KB, docx)}

Data Availability Statement

Data is available on Dryad via https://doi.org/10.5061/dryad.vmcvdncxs.

[pone.0283816.ref001] 1.Briggs JM, Knapp AK, Blair JM, Heisler JL, Hoch GA, Lett MS, et al. An Ecosystem in Transition: Causes and Consequences of the Conversion of Mesic Grassland to Shrubland. BioScience. 2005;55: 243–254. doi: 10.1641/0006-3568(2005)055[0243:AEITCA]2.0.CO;2 [DOI] [Google Scholar]

[pone.0283816.ref002] 2.Fensham RJ, Fairfax RJ, Archer SR. Rainfall, land use and woody vegetation cover change in semi-arid Australian savanna. Journal of Ecology. 2005;93: 596–606. doi: 10.1111/j.1365-2745.2005.00998.x [DOI] [Google Scholar]

[pone.0283816.ref003] 3.Ratajczak Z, Nippert JB, Collins SL. Woody encroachment decreases diversity across North American grasslands and savannas. Ecology. 2012;93: 697–703. doi: 10.1890/11-1199.1 [DOI] [PubMed] [Google Scholar]

[pone.0283816.ref004] 4.Archer SR, Andersen EM, Predick KI, Schwinning S, Steidl RJ, Woods SR. Woody Plant Encroachment: Causes and Consequences. Rangeland Systems. Springer, Cham; 2017. pp. 25–84. doi: 10.1007/978-3-319-46709-2_2 [DOI] [Google Scholar]

[pone.0283816.ref005] 5.Mistry J, Schmidt IB, Eloy L, Bilbao B. New perspectives in fire management in South American savannas: The importance of intercultural governance. Ambio. 2019;48: 172–179. doi: 10.1007/s13280-018-1054-7 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0283816.ref006] 6.Sühs RB, Giehl ELH, Peroni N. Preventing traditional management can cause grassland loss within 30 years in southern Brazil. Scientific Reports. 2020;10: 783. doi: 10.1038/s41598-020-57564-z [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0283816.ref007] 7.Hoekstra JM, Boucher TM, Ricketts TH, Roberts C. Confronting a biome crisis: global disparities of habitat loss and protection. Ecology Letters. 2005;8: 23–29. doi: 10.1111/j.1461-0248.2004.00686.x [DOI] [Google Scholar]

[pone.0283816.ref008] 8.Newbold T, Hudson LN, Arnell AP, Contu S, Palma AD, Ferrier S, et al. Has land use pushed terrestrial biodiversity beyond the planetary boundary? A global assessment. Science. 2016;353: 288–291. doi: 10.1126/science.aaf2201 [DOI] [PubMed] [Google Scholar]

[pone.0283816.ref009] 9.Holling CS. Resilience and Stability of Ecological Systems. Annual Review of Ecology and Systematics. 1973;4: 1–23. doi: 10.1146/annurev.es.04.110173.000245 [DOI] [Google Scholar]

[pone.0283816.ref010] 10.Scheffer M, Carpenter S, Foley JA, Folke C, Walker B. Catastrophic shifts in ecosystems. Nature. 2001;413: 591–596. doi: 10.1038/35098000 [DOI] [PubMed] [Google Scholar]

[pone.0283816.ref011] 11.Twidwell D, Rogers WE, Fuhlendorf SD, Wonkka CL, Engle DM, Weir JR, et al. The rising Great Plains fire campaign: citizens’ response to woody plant encroachment. Frontiers in Ecology and the Environment. 2013;11: e64–e71. doi: 10.1890/130015 [DOI] [Google Scholar]

[pone.0283816.ref012] 12.McKinley DC, Norris MD, Blair JM, Johnson LC. Altered Ecosystem Processes as a Consequence of Juniperus virginiana L. Encroachment into North American Tallgrass Prairie. In: Auken OWV, editor. Western North American Juniperus Communities. Springer New York; 2008. pp. 170–187. doi: 10.1007/978-0-387-34003-6_9 [DOI] [Google Scholar]

[pone.0283816.ref013] 13.Price JN, Morgan JW. Woody plant encroachment reduces species richness of herb-rich woodlands in southern Australia. Austral Ecology. 2008;33: 278–289. doi: 10.1111/j.1442-9993.2007.01815.x [DOI] [Google Scholar]

[pone.0283816.ref014] 14.McKinley DC, Blair JM. Woody Plant Encroachment by Juniperus virginiana in a Mesic Native Grassland Promotes Rapid Carbon and Nitrogen Accrual. Ecosystems. 2008;11: 454–468. doi: 10.1007/s10021-008-9133-4 [DOI] [Google Scholar]

[pone.0283816.ref015] 15.Briggs JM, Hoch GA, Johnson LC. Assessing the Rate, Mechanisms, and Consequences of the Conversion of Tallgrass Prairie to Juniperus virginiana Forest. Ecosystems. 2002;5: 578–586. doi: 10.1007/s10021-002-0187-4 [DOI] [Google Scholar]

[pone.0283816.ref016] 16.Fuhlendorf SD, Archer SA, Smeins F, Engle DM, Taylor CA. The Combined Influence of Grazing, Fire, and Herbaceous Productivity on Tree–Grass Interactions. In: Van Auken OW, editor. Western North American Juniperus Communities: A Dynamic Vegetation Type. New York, NY: Springer; 2008. pp. 219–238. doi: 10.1007/978-0-387-34003-6_12 [DOI] [Google Scholar]

[pone.0283816.ref017] 17.Scott RL, Huxman TE, Williams DG, Goodrich DC. Ecohydrological impacts of woody-plant encroachment: seasonal patterns of water and carbon dioxide exchange within a semiarid riparian environment. Global Change Biology. 2006;12: 311–324. doi: 10.1111/j.1365-2486.2005.01093.x [DOI] [Google Scholar]

[pone.0283816.ref018] 18.Finney MA, McHugh CW, Grenfell IC, Riley KL, Short KC. A simulation of probabilistic wildfire risk components for the continental United States. Stoch Environ Res Risk Assess. 2011;25: 973–1000. doi: 10.1007/s00477-011-0462-z [DOI] [Google Scholar]

[pone.0283816.ref019] 19.Donovan VM, Wonkka CL, Wedin DA, Twidwell D. Land-use type as a driver of large wildfire occurrence in the U.S. Great Plains. Remote Sensing. 2020;12: 1869. doi: 10.3390/rs12111869 [DOI] [Google Scholar]

[pone.0283816.ref020] 20.Dennison PE, Brewer SC, Arnold JD, Moritz MA. Large wildfire trends in the western United States, 1984–2011. Geophys Res Lett. 2014;41: 2014GL059576. doi: 10.1002/2014GL059576 [DOI] [Google Scholar]

[pone.0283816.ref021] 21.Donovan VM, Wonkka CL, Twidwell D. Surging wildfire activity in a grassland biome. Geophys Res Lett. 2017;44: 2017GL072901. doi: 10.1002/2017GL072901 [DOI] [Google Scholar]

[pone.0283816.ref022] 22.Engle DM, Coppedge BR, Fuhlendorf SD. From the Dust Bowl to the Green Glacier: Human Activity and Environmental Change in Great Plains Grasslands. In: Auken OWV, editor. Western North American Juniperus Communities. Springer New York; 2008. pp. 253–271. doi: 10.1007/978-0-387-34003-6_14 [DOI] [Google Scholar]

[pone.0283816.ref023] 23.Bielski CH, Scholtz R, Donovan VM, Allen CR, Twidwell D. Overcoming an “irreversible” threshold: A 15-year fire experiment. Journal of Environmental Management. 2021;291: 112550. doi: 10.1016/j.jenvman.2021.112550 [DOI] [PubMed] [Google Scholar]

[pone.0283816.ref024] 24.O’Connor RC, Taylor JH, Nippert JB. Browsing and fire decreases dominance of a resprouting shrub in woody encroached grassland. Ecology. 2020;101: e02935. doi: 10.1002/ecy.2935 [DOI] [PubMed] [Google Scholar]

[pone.0283816.ref025] 25.Twidwell D, Rogers WE, Wonkka CL, Taylor CA, Kreuter UP. Extreme prescribed fire during drought reduces survival and density of woody resprouters. Journal of Applied Ecology. 2016;53: 1585–1596. doi: 10.1111/1365-2664.12674 [DOI] [Google Scholar]

[pone.0283816.ref026] 26.Bernardo D, Engle D. The effect of manager risk attitudes on range improvement decisions. Journal of Range Management. 1990;43: 242–249. [Google Scholar]

[pone.0283816.ref027] 27.Harr RN, Morton LW, Rusk SR, Engle DM, Miller JR, Debinski D. Landowners’ perceptions of risk in grassland management: woody plant encroachment and prescribed fire. Ecology and Society. 2014;19. [Google Scholar]

[pone.0283816.ref028] 28.Bowman DMJS, Balch J, Artaxo P, Bond WJ, Cochrane MA, D’Antonio CM, et al. The human dimension of fire regimes on Earth. Journal of Biogeography. 2011;38: 2223–2236. doi: 10.1111/j.1365-2699.2011.02595.x [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0283816.ref029] 29.Morton LW, Regen E, Engle DM, Miller JR, Harr RN. Perceptions of Landowners Concerning Conservation, Grazing, Fire, and Eastern Redcedar Management in Tallgrass Prairie. Rangeland Ecology & Management. 2010;63: 645–654. doi: 10.2111/REM-D-09-00041.1 [DOI] [Google Scholar]

[pone.0283816.ref030] 30.Weir JR, Kreuter UP, Wonkka CL, Twidwell D, Stroman DA, Russell M, et al. Liability and Prescribed Fire: Perception and Reality. rama. 2019;72: 533–538. doi: 10.1016/j.rama.2018.11.010 [DOI] [Google Scholar]

[pone.0283816.ref031] 31.Stroman DA, Kreuter UP, Wonkka CL. Landowner perceptions of woody plants and prescribed fire in the Southern Plains, USA. PLOS ONE. 2020;15: e0238688. doi: 10.1371/journal.pone.0238688 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0283816.ref032] 32.Moritz MA, Batllori E, Bradstock RA, Gill AM, Handmer J, Hessburg PF, et al. Learning to coexist with wildfire. Nature. 2014;515: 58–66. doi: 10.1038/nature13946 [DOI] [PubMed] [Google Scholar]

[pone.0283816.ref033] 33.Schoennagel T, Balch JK, Brenkert-Smith H, Dennison PE, Harvey BJ, Krawchuk MA, et al. Adapt to more wildfire in western North American forests as climate changes. PNAS. 2017;114: 4582–4590. doi: 10.1073/pnas.1617464114 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0283816.ref034] 34.Weir JR. Conducting prescribed fires: A comprehensive manual. College Station, Texas, USA: Texas A&M University Press; 2009. [Google Scholar]

[pone.0283816.ref035] 35.Koo E, Pagni PJ, Weise DR, Woycheese JP, Koo E, Pagni PJ, et al. Firebrands and spotting ignition in large-scale fires. Int J Wildland Fire. 2010;19: 818–843. doi: 10.1071/WF07119 [DOI] [Google Scholar]

[pone.0283816.ref036] 36.Cruz MG, Sullivan AL, Gould JS, Sims NC, Bannister AJ, Hollis JJ, et al. Anatomy of a catastrophic wildfire: The Black Saturday Kilmore East fire in Victoria, Australia. Forest Ecology and Management. 2012;284: 269–285. doi: 10.1016/j.foreco.2012.02.035 [DOI] [Google Scholar]

[pone.0283816.ref037] 37.Ryan KC, Knapp EE, Varner JM. Prescribed fire in North American forests and woodlands: history, current practice, and challenges. Frontiers in Ecology and the Environment. 2013;11: e15–e24. doi: 10.1890/120329 [DOI] [Google Scholar]

[pone.0283816.ref038] 38.Wonkka CL, Rogers WE, Kreuter UP. Legal barriers to effective ecosystem management: exploring linkages between liability, regulations, and prescribed fire. Ecological Applications. 2015;25: 2382–2393. doi: 10.1890/14-1791.1 [DOI] [PubMed] [Google Scholar]

[pone.0283816.ref039] 39.Roberts CP, Uden DR, Allen CR, Twidwell D. Doublethink and scale mismatch polarize policies for an invasive tree. PLOS ONE. 2018;13: e0189733. doi: 10.1371/journal.pone.0189733 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0283816.ref040] 40.Fogarty DT, de Vries C, Bielski C, Twidwell D. Rapid Re-encroachment by Juniperus virginiana After a Single Restoration Treatment. Rangeland Ecology & Management. 2021;78: 112–116. doi: 10.1016/j.rama.2021.06.002 [DOI] [Google Scholar]

[pone.0283816.ref041] 41.Naugle DE, Allred BW, Jones MO, Twidwell D, Maestas JD. Coproducing Science to Inform Working Lands: The Next Frontier in Nature Conservation. BioScience. 2020;70: 90–96. doi: 10.1093/biosci/biz144 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0283816.ref042] 42.Guyette RP, Stambaugh MC, Dey DC, Muzika R-M. Predicting fire frequency with chemistry and climate. Ecosystems. 2012;15: 322–335. [Google Scholar]

[pone.0283816.ref043] 43.Arguez A, Durre I, Applequist S, Vose RS, Squires MF, Yin X, et al. NOAA’s 1981–2010 U.S. Climate Normals: An Overview. Bulletin of the American Meteorological Society. 2012;93: 1687–1697. doi: 10.1175/BAMS-D-11-00197.1 [DOI] [Google Scholar]

[pone.0283816.ref044] 44.U.S. Department of Commerce. State boundaries (generalized for mapping)—ScienceBase-Catalog. 2012. [cited 21 Feb 2023]. Available: https://www.sciencebase.gov/catalog/item/52c78623e4b060b9ebca5be5. [Google Scholar]

[pone.0283816.ref045] 45.ESRI. ArcGIS Desktop. Redlands, California, USA: Environmental Systems Research Institute; 2023. [Google Scholar]

[pone.0283816.ref046] 46.Twidwell D, Fuhlendorf SD, Taylor CA, Rogers WE. Refining thresholds in coupled fire–vegetation models to improve management of encroaching woody plants in grasslands. J Appl Ecol. 2013;50: 603–613. doi: 10.1111/1365-2664.12063 [DOI] [Google Scholar]

[pone.0283816.ref047] 47.Andrews PL. BehavePlus fire modeling system: Past, present, and future. In: Proceedings of 7th Symposium on Fire and Forest Meteorology; 23–25 October 2007, Bar Harbor, Maine Boston, MA: American Meteorological Society 13 p. 2007 [cited 14 Aug 2020]. Available: https://www.fs.usda.gov/treesearch/pubs/31549.

[pone.0283816.ref048] 48.Albini FA. Potential spotting distance from wind-driven surface fires. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station; 1983. p. 27 p. Report No.: Research Paper INT-309. [Google Scholar]

[pone.0283816.ref049] 49.Albini FA. Spot fire distance from isolated sources-extensions of a predictive model. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station; 1981. p. 9 p. Report No.: Research Note INT-309. [Google Scholar]

[pone.0283816.ref050] 50.Albini FA. Spot fire distance from burning trees-a predictive model. Ogden, UT: USDA Forest Service, Intermountain Forest and Range Experiment Station; 1979. p. 73 p. Report No.: General Technical Report INT-GTR-56. [Google Scholar]

[pone.0283816.ref051] 51.Morris G. A simple method for computing spotting distances from wind-driven surface fires, Research Note INT-374. Ogden, UT: US Department of Agriculture, Forest Service, Intermountain Research Station; 1987. p. 6 p. Report No.: Research Note INT-374. [Google Scholar]

[pone.0283816.ref052] 52.LANDFIRE. 13 Anderson Fire Behavior Fuel Models. U.S. Department of the Interior, Geological Survey, and U.S. Department of Agriculture; 2014. Available: Accessed 4/30/2020 from https://landfire.gov/index.php. [Google Scholar]

[pone.0283816.ref053] 53.Anderson HE. Aids to determining fuel models for estimating fire behavior. Ogden, UT: US Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station; 1982. Report No.: Gen. Tech. Rep. INT-122. [Google Scholar]

[pone.0283816.ref054] 54.Blunck DL, Butler BW, Bailey JD, Wagenbrenner NS. Multi-scale study of ember production and transport under multiple environmental and fuel conditions—Final Report to the Joint Fire Science Program. Joint Fire Science Program; 2019. [Google Scholar]

[pone.0283816.ref055] 55.National Wildfire Coordinating Group. Fire Behaviour Field Reference Guide. National Wildfire Coordinating Group; 2019. Report No.: PMS 437. Available: https://www.nwcg.gov/publications/pms437. [Google Scholar]

[pone.0283816.ref056] 56.NRCS. Natural Resources Conservation Service Conservation Practice Standard: Prescribed burning (Ac.) code 338 . USDA Natural Resources Conservation Service- North Mexico; 2011. pp. 1–9. [Google Scholar]

[pone.0283816.ref057] 57.Lawson ER. Eastern redcedar (Juniperus virginiana L.). Fayetteville, AR: United States Department of Agriculture, Forest Service; 1986. Report No.: FS-260. [Google Scholar]

[pone.0283816.ref058] 58.Volesky JD, Stubbendieck JL, Mitchell RB. Conducting a prescribed burn and prescribed burning checklist. Lincoln, Nebraska, USA: University of Nebraska-Lincoln Extension; 2007. Report No.: EC121. [Google Scholar]

[pone.0283816.ref059] 59.NRCS. Prescribed burning fact sheet. USDA Natural Resources Conservation Service- North Dakota; 2012. Report No.: 338. [Google Scholar]

[pone.0283816.ref060] 60.R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2018. Available: https://www.R-project.org/. [Google Scholar]

[pone.0283816.ref061] 61.Wickham H. ggplot2: Elegant Graphics for Data Analysis. New York, NY: Springer-Verlag; 2016. Available: http://ggplot2.org. [Google Scholar]

[pone.0283816.ref062] 62.Bond WJ, Keeley JE. Fire as a global ‘herbivore’: the ecology and evolution of flammable ecosystems. Trends in Ecology & Evolution. 2005;20: 387–394. doi: 10.1016/j.tree.2005.04.025 [DOI] [PubMed] [Google Scholar]

[pone.0283816.ref063] 63.Fuhlendorf SD, Engle DM, Elmore RD, Limb RF, Bidwell TG. Conservation of Pattern and Process: Developing an Alternative Paradigm of Rangeland Management. Rangeland Ecology & Management. 2012;65: 579–589. doi: 10.2111/REM-D-11-00109.1 [DOI] [Google Scholar]

[pone.0283816.ref064] 64.Miller JED, Damschen EI, Ratajczak Z, Özdoğan M. Holding the line: three decades of prescribed fires halt but do not reverse woody encroachment in grasslands. Landscape Ecol. 2017;32: 2297–2310. doi: 10.1007/s10980-017-0569-9 [DOI] [Google Scholar]

[pone.0283816.ref065] 65.Capozzelli JF, Miller JR, Debinski DM, Schacht WH. Restoring the fire–grazing interaction promotes tree–grass coexistence by controlling woody encroachment. Ecosphere. 2020;11: e02993. doi: 10.1002/ecs2.2993 [DOI] [Google Scholar]

[pone.0283816.ref066] 66.Epanchin-Niell RS, Liebhold AM. Benefits of invasion prevention: effect of time lags, spread rates, and damage persistence. Ecological Economics. 2015;116: 146–153. [Google Scholar]

[pone.0283816.ref067] 67.Yokomizo H, Possingham HP, Thomas MB, Buckley YM. Managing the impact of invasive species: the value of knowing the density–impact curve. Ecological Applications. 2009;19: 376–386. doi: 10.1890/08-0442.1 [DOI] [PubMed] [Google Scholar]

[pone.0283816.ref068] 68.Simpson H, Bradstock R, Price O. A Temporal Framework of Large Wildfire Suppression in Practice, a Qualitative Descriptive Study. Forests. 2019;10: 884. doi: 10.3390/f10100884 [DOI] [Google Scholar]

[pone.0283816.ref069] 69.Twidwell D, Allen CR, Detweiler C, Higgins J, Laney C, Elbaum S. Smokey comes of age: unmanned aerial systems for fire management. Frontiers in Ecology and the Environment. 2016;14: 333–339. doi: 10.1002/fee.1299 [DOI] [Google Scholar]

[pone.0283816.ref070] 70.Weir JR, Twidwell D, Wonkka CL. Prescribed burn association activity, needs, and safety record: a survey of the Great Plains. Great Plains Fire Science Exchange GPE Publication. 2015;6: 19. [Google Scholar]

[pone.0283816.ref071] 71.Fogarty DT, Roberts CP, Uden DR, Donovan VM, Allen CR, Naugle DE, et al. Woody plant encroachment and the sustainability of priority conservation areas. Sustainability. 2020;12: 8321. doi: 10.3390/su12208321 [DOI] [Google Scholar]

[pone.0283816.ref072] 72.Anderson RC. Evolution and origin of the Central Grassland of North America: climate, fire, and mammalian grazers1. tbot. 2006;133: 626–647. doi: 10.3159/1095-5674(2006)133[626:EAOOTC]2.0.CO;2 [DOI] [Google Scholar]

[pone.0283816.ref073] 73.Anderson RC. The historic role of fire in the North American grassland. In: Collins SL, Wallace LL, editors. Fire in North American tallgrass prairies. Norman, OK: University of Oklahoma Press; 1990. pp. 8–18. [Google Scholar]

[pone.0283816.ref074] 74.Bowman DMJS Balch JK, Artaxo P Bond WJ, Carlson JM Cochrane MA, et al. Fire in the Earth System. Science. 2009;324: 481–484. doi: 10.1126/science.1163886 [DOI] [PubMed] [Google Scholar]

[pone.0283816.ref075] 75.Pyne SJ. Fire: a brief history. Seattle, WA, USA: University of Washington Press; 2001. [Google Scholar]

[pone.0283816.ref076] 76.Twidwell D, Bielski CH, Scholtz R, Fuhlendorf SD. Advancing Fire Ecology in 21st Century Rangelands. Rangeland Ecology & Management. 2020. [cited 30 Apr 2021]. doi: 10.1016/j.rama.2020.01.008 [DOI] [Google Scholar]

[pone.0283816.ref077] 77.Donovan VM, Burnett JL, Bielski CH, Birgé HE, Bevans R, Twidwell D, et al. Social–ecological landscape patterns predict woody encroachment from native tree plantings in a temperate grassland. Ecology and Evolution. 2018;8: 9624–9632. doi: 10.1002/ece3.4340 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0283816.ref078] 78.Garmestani A, Twidwell D, Angeler DG, Sundstrom S, Barichievy C, Chaffin BC, et al. Panarchy: opportunities and challenges for ecosystem management. Frontiers in Ecology and the Environment. 2020;18: 576–583. doi: 10.1002/fee.2264 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0283816.ref079] 79.Veldman JW, Overbeck GE, Negreiros D, Mahy G, Stradic SL, Fernandes GW, et al. Tyranny of trees in grassy biomes. Science. 2015;347: 484–485. doi: 10.1126/science.347.6221.484-c [DOI] [PubMed] [Google Scholar]

[pone.0283816.ref080] 80.Twidwell D, West AS, Hiatt WB, Ramirez AL, Taylor Winter J, Engle DM, et al. Plant Invasions or Fire Policy: Which Has Altered Fire Behavior More in Tallgrass Prairie? Ecosystems. 2016;19: 356–368. doi: 10.1007/s10021-015-9937-y [DOI] [Google Scholar]

[pone.0283816.ref081] 81.Sangha KK, Evans J, Edwards A, Russell-Smith J, Fisher R, Yates C, et al. Assessing the value of ecosystem services delivered by prescribed fire management in Australian tropical savannas. Ecosystem Services. 2021;51: 101343. doi: 10.1016/j.ecoser.2021.101343 [DOI] [Google Scholar]

[pone.0283816.ref082] 82.Ortmann J, Stubbendieck J, Masters RA, Pfeiffer G, Bragg T. Efficacy and costs of controlling eastern redcedar. Journal of Range Management. 2012;51: 158–163. [Google Scholar]

[pone.0283816.ref083] 83.Augustine DJ, Derner JD, Milchunas DG. Prescribed Fire, Grazing, and Herbaceous Plant Production in Shortgrass Steppe. Rangeland Ecology & Management. 2010;63: 317–323. doi: 10.2111/REM-D-09-00044.1 [DOI] [Google Scholar]

[pone.0283816.ref084] 84.Fuhlendorf SD, Harrell WC, Engle DM, Hamilton RG, Davis CA, Leslie DM Jr. Should Heterogeneity Be the Basis for Conservation? Grassland Bird Response to Fire and Grazing. Ecological Applications. 2006;16: 1706–1716. doi: 10.1890/1051-0761(2006)016[1706:shbtbf]2.0.co;2 [DOI] [PubMed] [Google Scholar]

[pone.0283816.ref085] 85.Hovick TJ, Allred BW, Elmore RD, Fuhlendorf SD, Hamilton RG, Breland A. Dynamic Disturbance Processes Create Dynamic Lek Site Selection in a Prairie Grouse. PLoS One. 2015;10: e0137882. doi: 10.1371/journal.pone.0137882 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0283816.ref086] 86.Starns HD, Fuhlendorf SD, Elmore RD, Twidwell D, Thacker ET, Hovick TJ, et al. Effects of pyric herbivory on prairie-chicken (Tympanuchus spp) habitat. PLOS ONE. 2020;15: e0234983. doi: 10.1371/journal.pone.0234983 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0283816.ref087] 87.DiTomaso JM, Brooks ML, Allen EB, Minnich R, Rice PM, Kyser GB. Control of invasive weeds with prescribed burning. Weed Technology. 2006;20: 535–548. [Google Scholar]

[pone.0283816.ref088] 88.Kral K, Limb R, Ganguli A, Hovick T, Sedivec K. Seasonal prescribed fire variation decreases inhibitory ability of Poa pratensis L. and promotes native plant diversity. J Environ Manage. 2018;223: 908–916. doi: 10.1016/j.jenvman.2018.06.096 [DOI] [PubMed] [Google Scholar]

PERMALINK

Spot-fire distance increases disproportionately for wildfires compared to prescribed fires as grasslands transition to Juniperus woodlands

Victoria M Donovan

Dillon T Fogarty

Dirac Twidwell

Roles

Abstract

Introduction

Materials and methods

Study area

Fig 1. The distribution of prescribed fires (yellow) from 2000–2019 in the Loess Canyons Biologically Unique Landscape in Nebraska.

Maximum spot fire distance models

Table 1. Summary of fuel models and their percent cover within the Loess Canyons.

Table 2. Model parameters for calculating flame length values to be input into surface fire spotting distance models.

Table 3. Fuel model parameters and justification for spot fire distance models.

Results

Fig 2. The difference in maximum spot fire distance under prescribed fire (0–32 km/h) versus wildfire (0–129 km/h) conditions relative to 3 different levels of juniper encroachment: The grassland state, a woody encroached grassland, and the woodland state.

Fig 4. The change in receptive fuel area exposed to potential spot fire surrounding individual burn units in the Loess Canyons Experimental Landscape as juniper encroachment level and wind speed increase.

Discussion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Walter Finsinger

Roles

Author response to Decision Letter 0

Decision Letter 1

Walter Finsinger

Roles

Acceptance letter

Walter Finsinger

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases