The following is the established format for referencing this article:Maxwell, C., R. M. Scheller, J. W. Long and P. Manley. 2022. Frequency of disturbance mitigates high-severity fire in the Lake Tahoe Basin, California and Nevada. Ecology and Society 27(1):21.
ABSTRACTBecause of past land use changes and changing climate, forests are moving outside of their historical range of variation. As fires become more severe, forest managers are searching for strategies that can restore forest health and reduce fire risk. However, management activities are only one part of a suite of disturbance vectors that shape forest conditions. To account for the range of disturbance intensities and disturbance types (wildfire, bark beetles, and management), we developed a disturbance return interval (DRI) that represents the average return period for any disturbance, human or natural. We applied the DRI to examine forest change in the Lake Tahoe Basin of California and Nevada. We specifically investigated the consequences of DRI on the proportion of high-severity fire and the net sequestration of carbon. In order to test the management component of the DRI, we developed management scenarios with forest managers and stakeholders in the region; these scenarios were integrated into a mechanistic forest landscape model that also accounted for climate change, as well as natural disturbances of wildfire and insect outbreaks. Our results suggest increasing the frequency of disturbances (a lower DRI) would reduce the percentage of high-severity fire on landscape but not the total amount of wildfire in general. However, a higher DRI reduced carbon storage and sequestration, particularly in management strategies that emphasized prescribed fire over hand or mechanical fuel treatments.
Land managers recognize the limitations of current forest and fire policy in maintaining forests under climate change; because of past land use patterns, forests in the western United States are becoming denser and experiencing larger disturbances (Hessburg and Agee 2003, Beaty and Taylor 2007). In addition, climate change is creating larger, more severe fires (Westerling and Bryant 2008). Looking forward, forest restoration should accommodate the changing disturbance regime rather than remain fixed on historical regimes. One challenge is that current vegetation reflects the historical land use and disturbance regime. In the Lake Tahoe Basin (LTB) of California and Nevada, for example, wildfires were substantially more frequent before Euro-American colonization, with some watersheds burned annually until widespread fire exclusion (Taylor and Beaty 2005). The swing toward fire suppression resulted in shade-tolerant white fir (Abies concolor) encroachment into fire-tolerant and fire-maintained pine dominated stands. Although there is interest in increasing the amount of fire on the landscape, fire management in the Basin is constrained by residential development on account of the risk to structures and the importance of recreation to the local economy. The Angora fire, in 2007, was one of America’s most expensive fires up to that time because of the number of structures lost in the fire (Safford et al. 2009). Contemporary forest management activities focus on fuel reduction: reducing the probability of fire spread and high fire intensity, while also suppressing active fires (Safford et al. 2009, Safford et al. 2012). However, the long-term effectiveness of such a strategy may be limited; fires are expected to increase in size under climate change (Westerling and Bryant 2008) and the backlog of areas needing treatment further threatens forest resilience.
Fire is only one part of a larger suite of disturbances affecting forested landscapes. Insects cause significant forest mortality worldwide and are often triggered by the same climatic conditions that magnify fire effects (Kurz et al. 2008, Hicke et al. 2016, Kolb et al. 2016). Moreover, insect outbreaks can cause mortality over large areas and on par with wildfire (Hicke et al. 2016), and for this landscape, bark beetles have caused significant mortality across large portions of the Sierra Nevada (Scheller et al. 2018). Often as important as natural disturbances, management activities—timber harvesting, fuel reduction treatments, prescribed fires—also shape the composition and density of forests through selective mortality through targeting specific combinations of species and ages. The forest’s demography and composition was radically changed with the institution of fire suppression resulting from Euro-American colonization and the harvesting of old-growth wood during the Comstock era (Barbour et al. 2002).
The challenge for management is understanding how to restore historical disturbance processes under a non-stationary climate, given that higher temperatures and increasing aridity can increase the frequency of widespread mortality events (Goulden and Bales 2019). On the other hand, because multiple, interacting disturbances can have a negative feedback on future disturbances (Lucash et al. 2018), we hypothesize that decreasing the disturbance return interval (DRI—the frequency at which an area is impacted by a disturbance), which would lead to more disturbance, would reduce the severity of future disturbances in the long term, which would in turn move the landscape back toward a lower severity fire regime. A potential liability of a high-frequency disturbance regime, however, is that it may reduce carbon sequestration potential, possibly resulting in the forest becoming a carbon source. Our goals were to understand the following: (1) Will shortening the disturbance return interval (DRI) restore a lower severity fire regime to the landscape? (2) Will shortening the DRI reduce landscape-scale carbon sequestration? We used a simulation modeling framework to forecast future forest conditions under natural disturbances and a range of plausible management forcings to address these two questions.
The Lake Tahoe basin is a mostly forested montane landscape approximately 70,000 ha in size, primarily (~70%) under the management of the USDA Forest Service, in the middle of the Sierra Nevada Mountain range straddling the border of California and Nevada, USA. The climate is seasonally dry—most precipitation falls as snow in the winter—with cold winters and warm to hot summers. Forests are mostly mixed conifer, a mix of white fir (Abies concolor) and Jeffrey pine (Pinus jeffreyi) among others at lower elevations, trending to red fir (Abies magnifica) and western white pine (Pinus monticola) at higher elevations. Disturbance return intervals range from infrequent in the subalpine areas to frequent for aspen (Populus tremuloides) components. Prior to colonization, wildfires were frequent in pine-dominated areas, with return intervals ranging from two to 20 years (Taylor and Beatty 2005). Fire suppression has resulted in an increase of shade tolerant white fir at the expense of Jeffrey pine, as well as a widespread decline of aspen, which is dependent on disturbance. Insect outbreaks, and subsequent forest mortality, are natural occurrences in the pine forests of the Sierras; however, their frequency and severity have increased compared to historic conditions (Raffa et al. 2008).
Forest and disturbance modeling
We simulated forest change using the LANDIS-II framework because it represents forest succession, integrates climate change, and captures a wide variety of disturbances across wide spatial extents (Scheller et al. 2007). Trees and shrubs are modeled as species-age cohorts, with each species having its own life history attributes (e.g., shade tolerance, dispersal ability, fire tolerance, susceptibility to beetles). Multiple cohorts can occupy the same space and compete intra- and inter-specifically, which allows emergent behavior in response to external drivers (Scheller et al. 2007). There were ten tree species and four shrub groups modeled and their respective parameters are located in Appendix 1 (Table A1.2). The succession extension (NECN v. 6.1) handles growth and non-disturbance mortality, and tracks carbon across these cohorts and aboveground and belowground pools. Additionally, within the framework, the net losses of carbon from the disturbance extensions (below) are tracked, allowing for the calculation of the forest’s net ecosystem exchange (NEEC), which is whether the system as a whole is absorbing or releasing carbon.
Wild and prescribed fires were modeled using the Social-Climate Related Pyrogenic Processes (SCRPPLE v. 2.1) extension (Scheller et al. 2019). This extension models the spread and intensity of those kinds of fire, while being sensitive to climate conditions and fuel loads. Fire intensity for a given cell is based on conditions within the cell and in neighboring cells, where high intensity fire is possible when two of the following three conditions are met: (1) crossing the fuel loading threshold for fine fuels within the cell, (2) crossing a fuel loading threshold for ladder fuels within the cell, or (3) presence of high intensity fire in a neighboring cell. Five fire experts working the LTB provided a translation from intensity to severity by providing a breakdown of intensity versus mortality for all the modeled species and age classes. Prescribed fire severity was constrained to low severity: the model selected the burn days based on weather constraints to minimize severity (Appendix 1: Table A1.2) because it was assumed that fire managers would limit fire effects anyway.
Three beetle species (Jeffrey pine beetle [Dendroctonus jeffreyi Hopkins], mountain pine beetle [Dendroctonus ponderosae], and fir engraver beetle [Scolytus ventralis]) were modeled using a modified version of the Biological Disturbance Agent (BDA v.2.0.1) extension (Sturtevant et al. 2004), where an outbreak is triggered by the exceedance of climatic water deficit and minimum winter temperature thresholds. The parameters for insect spread and mortality follow Kretchun et al. (2016) and are based on field studies and expert opinion (Egan et al. 2010, 2016).
Initial aboveground biomass estimates were derived from Forest Inventory and Analysis data and validated against Wilson et al. (2013). Recent wildfires (2000–2016) from California FRAP were used to parameterize fire spread and size. Mean annual fire area for observed data was 117 ha/yr (sd = 309), and for modeled data the mean value was 182 ha/yr (sd = 210). Insect and Disease Detection Surveys (1993–2017) were used to validate insect outbreaks under historical climate conditions. Observed mean area impacted annually by fir engraver beetles was ~1120 ha, Jeffrey pine beetle ~295 ha, and mountain pine beetle ~147 ha. Modeled impacts were ~857 ha, ~711 ha, and ~82 ha respectively.
We used management scenarios to capture a range of plausible management activities, each representing a combination of activities, locations, and area treated per year. Five management scenarios were co-developed with managers representing multiple agencies within LTB along with input from stakeholder groups operating in the region (see Table 1). Scenario 1 represented a minimalist scenario that features no fuels management but high-effort fire suppression. Scenario 2 focused on fuel treatments within the wildland–urban interface (WUI) area with treatment type (hand versus mechanical) dependent on accessibility. Like Scenario 1, there was high-effort fire suppression and no prescribed burning. Scenario 3 built off of Scenario 2, increasing both the intensity and extent of fuel treatments, while expanding treatments into the general forest and wilderness areas. Scenario 4 combined the hand and mechanical thinning from Scenario 2 with prescribed fires and managed natural ignitions. Scenario 5 was similar to Scenario 4, but with even higher levels of prescribed burning. Stand re-treatment frequency was set at 20 years for Scenario 2. The re-treatment frequency for Scenarios 3, 4, and 5 was 11 years. Fire suppression effort levels were explicitly set, and for Scenarios 1–3, suppression was at maximum effort. For Scenarios 4 and 5, suppression was at maximum effort for accidental ignitions in all areas and lightning ignitions in the WUI, but minimum effort for lightning ignitions in wildernesses and general forest.
Following the precedence set by the 4th California Climate Assessment, four global change models (GCM; CanESM2, CNRM5, HADGEM2, and MIROC5) under two different relative concentration pathways (RCP) were chosen because they represented a range of possible future conditions (e.g., warmer and wetter, hotter and drier). The RCPs chosen (4.5 and 8.5) represent an optimistic scenario where future emissions are controlled and an uncontrolled emissions scenario, respectively. Climate downscaling used the localized constructed analogs method developed by Pierce et al. (2014), as available on the USGS GeoData Portal (https://cida.usgs.gov/gdp/). We averaged the climate projections across EPA level II climate regions for integration within the model. The climate futures for this region ranged substantially, and although temperatures increased under all projections, precipitation increased, decreased, or changed seasonality.
We calculated DRI by management area, a zone identified to receive a similar suite of treatments, for each year. This calculation was done by dividing the total management area by the sum of the area affected by management activities, insects, and low and moderate severity fire for one year. The DRI is the amount of time it takes a disturbance to affect an area an equivalent size to the relevant management area for that particular annual timestep averaged across multiple replicates. This was done in order to track changes in DRI through time in order to separate the climate signal and track the cumulative effect of disturbance on the landscape. Multiple regression was used to evaluate the relationships that DRI had with fire severity and net ecosystem exchange. All analyses were performed with R (v 3.5.3).
Disturbance return interval
When considering the suite of all forest disturbances, these management strategies have vastly different footprints on the ground. Management actions were the main driver of DRI on the landscape, which is reflected by the large differences in DRI between Scenario 1 (the no action scenario) and the other scenarios that utilized management activity, as well as the DRI in wilderness areas outside of Scenario 3 (Fig. 1). The actions that each scenario implemented had different results on the ground: the scenario that utilized the most prescribed fire (Scenario 5) resulted in the highest amount of low severity fire (Fig. 2). The scenario that had the most fuel treatments (Scenario 3) had the most moderate severity fire of the scenarios. The no-management scenario resulted in the highest percent of high-severity fire (Fig. 2). Increasing the DRI did not result in a reduction in the amount of total area burned but it did reduce the proportion of the landscape that burned at high severity (Fig. 2B; Table 2).
Management and carbon sequestration
Climate change is moving the landscape toward becoming a carbon source (Fig. 3, left). This can be moderated or accelerated by the type of management actions taken on the landscape, which is reflected in the different management areas present (see Table 3). Higher removals of biomass (whether from combustion of litter/downed woody material or from higher mortality than other forms of treatment) by prescribed fires in Scenarios 4 and 5 on the landscape affected the carbon balance (Fig. 3, right), where both live and dead C pools decreased through time. A more direct comparison of Scenario 2 and 4, in spite of similar areas treated, indicated higher mortality from prescribed fires resulting in lower levels of live C but a higher ratio of low severity fire. Scenario 3, the intensive harvest scenario, maintained the highest levels of sequestration despite the highest levels of removals.
Our analysis suggests that, with the management approaches tested, there was a trade-off between C storage and fire severity. Although a lower DRI reduced high-severity fire, the net effect was reduced C storage. Managers must therefore decide whether reduced fire risk (and subsequent avoidance of attendant human health risks, from emissions, and hydrologic risks, from erosion, represented as reduced high-severity fire) justify the costs (both C storage and the additional resources expended to implement these strategies), which are issues addressed in other articles in this special issue. Prescribed fire can have longer lasting reductions in future fire severity over thinning actions because of the greater reduction of plant material and down dead materials, though duration can be limited on highly productive sites (Casals et al. 2016). Nevertheless, prescribed fire can have additional widespread restorative outcomes for wildlife and fire-dependent plant species (Alcasena et al. 2018) that are not in the realm of this study.
An alternative approach to landscape C management could be through the promotion or protection of C hotspots. In our simulations, C dense hotspots on the landscape persisted through time regardless of management scenario but increasing the DRI reduced C heterogeneity across the landscape—reducing the hotspots while increasing the mean elsewhere through the release of the remaining trees (Fig. 4). Large trees store and sequester higher levels of C than smaller trees, and reducing the risk of high-severity fire in the C-dense stands could maintain landscape C in the medium (< 30 years) term (Harris et al. 2019).
To the degree that managers can control DRI, a DRI that is too high may result in the decline of the resilience of landscape C sequestration. Because of climate change, doing nothing also incurs a cost, and so management decisions need to consider the whole suite of inputs and potential outcomes of implementing any given strategy, the goal of this special issue and the implementation of the Environmental Management Decision Support (EMDS) tool (Reynolds et al. 2014). Within the LTB, recent management is largely focused on the WUI (Loudermilk et al. 2014) and has the potential to increase C sequestration over many decades (Loudermilk et al. 2017). These studies assumed, however, that management would be restricted to the WUI. Our scenarios were designed to elucidate trade-offs for management actions occurring across the entire landscape. Scenario 1, the no-management scenario, had the highest levels of live carbon but also the highest rate of high-severity fire. Although Scenario 3 had the lowest DRI, enforcing a lower DRI (high disturbance rate) in the high-elevation forests and wilderness areas—areas that experience limited disturbance otherwise—did not confer any substantial C benefits and would presumably also have the highest cost. Harvesting can enhance growth in remaining trees while also reducing unpredictable high-severity fire. Thus, Scenario 3 might have additional C benefits based on how the harvested forest products are used.
Estimating the DRI provided necessary information for estimating the carbon carrying capacity (Liang et al. 2017) for the Lake Tahoe basin. We found that for a given DRI there was an upper limit for landscape carbon storage. Liang et al. (2017) found that forests in the Sierra Nevada could take hundreds of years to equilibrate to a new carbon carrying capacity under climate change and that climate mediated wildfire. Similarly, our results suggest that by the end of this century, this landscape will likely be above its carry capacity for C given the downward trend in live C and decreasing net ecosystem exchange and will not be approaching any sort of equilibrium within this time frame. This latter point is exemplified by the upturn in simulated high-severity fire occurring in the latter half of the century (Fig. 2).
Although maintaining a forest in its “safe operating space,” where the underlying disturbance regime aligns with the biological traits of the forest species, promotes ecological resilience (Johnstone et al. 2016), the complicating factor is climate change. While the long-term stability of the forests prior to Euro-American colonization and climate change is viewed as that safe-operating space, climate change alters disturbance regimes and forest conditions directly (Johnstone et al. 2016), and such climate mediated disturbances such as fire and insects will substantially limit growth in landscape C and alter patterns of species dominance as we observed in the LTB (Scheller et al. 2018).
There are uncertainties with any modeling study, particularly when trying to account for novel climatic conditions. Although temperatures are unequivocally projected to increase, there is substantial variation in expected precipitation and extreme events that may not be captured by these GCMs. The drought conditions in California in 2021 are part of a larger megadrought made worse by climate change (Williams et al. 2020) that are unprecedented in modern history. Although mechanistic models like LANDIS are generally more robust to novel conditions, they can be limited by an incomplete understanding of mechanism in question (e.g., direct drought mortality) or a resultant new process not previously documented (mass fire due to unprecedented fuel build-up from insect and drought mortality).
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Funders included the following: National Forest Foundation, California Tahoe Conservancy, USDA Lake Tahoe Basin Management Unit, Southern Nevada Public Lands Management Act Public Law 105-263, California Climate Investments, USDA Pacific Southwest Research Station
The model parameters and code used in this analysis that support the findings of this study are openly available in: https://github.com/LANDIS-II-Foundation/Project-Lake-Tahoe-2017/ This code has been archived on zenodo.org at: https://doi.org/10.5281/zenodo.4644579
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Table 1. Management scenario broken down by intent and treatment type, by hectares, annually (approximate, rounded)
|Mechanical||Hand||Prescribed fire||Total||Percent of landscape treated annually||Stand minimum re-treatment time||Natural ignitions as managed fires|
|1||The only management activity was to suppress fires.||0||0||0||0||0%||0||No|
|2||Management activities were focused on forest thinning in the wildland–urban interface (WUI). This management strategy was designed to provide a buffer of defensible space around human-built structures and property. It treated ~2% of the vegetated area each year, all in the WUI. This scenario most closely resembled current management activities in the Lake Tahoe basin. Fire suppression efforts remain the same as Scenario 1.||350||950||0||1300||2%||20||No|
|3||This scenario builds upon Scenario 2 by expanding management activities into the remaining forested landscape beyond the WUI and used predominantly mechanical and some manual methods to thin the forest and reduce biomass. It treats approximately 6.7% of the vegetated area each year. Fire suppression efforts remain the same as Scenario 1.||1200||3800||0||5000||7%||11||No|
|4||This scenario builds upon Scenario 2 by expanding management activities into the remaining forested landscape. Scenario 4 uses primarily prescribed fire and managed wildfire. This scenario treats approximately 4% of the vegetated area each year. Fire suppression efforts were the same as Scenario 1 in WUI areas but natural ignitions were allowed to burn for resource objectives in the wilderness areas.||250||1000||1800||3050||4%||20||Yes, in wilderness|
|5||This scenario builds upon Scenario 4 by greatly expanding the use of prescribed fire. This scenario treats approximately 7.2% of the vegetated area each year, slightly more than Scenario 3, but with the majority of treatments (75%) being prescribed fire. Fire suppression efforts were the same as Scenario 1 in WUI areas but natural ignitions were allowed to burn for resource objectives in the wilderness areas.||250||1000||6600||7850||11%||20||Yes, in wilderness|
Table 2. Results of generalized linear model of percentage of low and moderate severity fire burned each year.
|Percentage of Low and Moderate Severity Fire per Year|
|Akaike Inf. Crit.||-1,106.536|
|* = p < 0.1, ** = p < 0.05, *** = p < 0.01|
Table 3. Results of generalized linear model of net ecosystem exchange and disturbance return interval (DRI) by year and management zone. NEEC, net ecosystem exchange; WUI, wildland–urban interface.
|Mt. Rose Wilderness||5.868***|
|Akaike Inf. Crit.||498,287.100|
|* = p < 0.1, ** = p < 0.05, *** = p < 0.01|