Lisa Holsinger

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

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

The FireBGCv2 landscape fire and succession model: a research simulation platform for exploring fire and vegetation dynamics

Fire management faces important emergent issues in the coming years such as climate change, fire exclusion impacts, and wildland-urban development, so new, innovative means are needed to address these challenges. Field studies, while preferable and reliable, will be problematic because of the large time and space scales involved. Therefore, landscape simulation modeling will have more of a role in wildland fire management as field studies become untenable. This report details the design and algorithms of a complex, spatially explicit landscape fire and vegetation model called FireBGCv2. FireBGCv2 is a C++ computer program that incorporates several types of stand dynamics models into a landscape simulation platform. FireBGCv2 is intended as a research tool. Descriptions of FireBGCv2 code, sample input files, and sample output are included in this report, but this report is not intended as a users manual because the inherent complexity and wide scope of FireBGCv2 makes it unwieldy and difficult to use without extensive training. The primary purpose of this report is to document FireBGCv2 in adequate detail to interpret simulation results.

Influences of prior wildfires on vegetation response to subsequent fire in a reburned Southwestern landscape

Large and severe wildfires have raised concerns about the future of forested landscapes in the southwestern United States, especially under repeated burning. In 2011, under extreme weather and drought conditions, the Las Conchas fire burned over several previous burns as well as forests not recently exposed to fire. Our purpose was to examine the influences of prior wildfires on plant community composition and structure, subsequent burn severity, and vegetation response. To assess these relationships, we used satellite-derived measures of burn severity and a nonmetric multidimensional scaling of pre- and post- Las Conchas field samples. Earlier burns were associated with shifts from forested sites to open savannas and meadows, oak scrub, and ruderal communities. These non-forested vegetation types exhibited both resistance to subsequent fire, measured by reduced burn severity, and resilience to reburning, measured by vegetation recovery relative to forests not exposed to recent prior fire. Previous shifts toward non-forested states were strongly reinforced by reburning. Ongoing losses of forests and their ecological values confirm the need for restoration interventions. However, given future wildfire and climate projections, there may also be opportunities presented by transformations toward fire-resistant and resilient vegetation types within portions of the landscape.

How will climate change affect wildland fire severity in the western US

Fire regime characteristics in North America are expected to change over the next several decades as a result of anthropogenic climate change. Although some fire regime characteristics (e.g., area burned and fire season length) are relatively well-studied in the context of a changing climate, fire severity has received less attention. In this study, we used observed data from 1984 to 2012 for the western United States (US) to build a statistical model of fire severity as a function of climate. We then applied this model to several (n = 20) climate change projections representing mid-century (2040–2069) conditions under the RCP 8.5 scenario. Model predictions suggest widespread reduction in fire severity for large portions of the western US. However, our model implicitly incorporates climate-induced changes in vegetation type, fuel load, and fire frequency. As such, our predictions are best interpreted as a potential reduction in fire severity, a potential that may not be realized due human-induced disequilibrium between plant communities and climate. Consequently, to realize the reductions in fire severity predicted in this study, land managers in the western US could facilitate the transition of plant communities towards a state of equilibrium with the emerging climate through means such as active restoration treatments (e.g., mechanical thinning and prescribed fire) and passive restoration strategies like managed natural fire (under suitable weather conditions). Resisting changes in vegetation composition and fuel load via activities such as aggressive fire suppression will amplify disequilibrium conditions and will likely result in increased fire severity in future decades because fuel loads will increase as the climate warms and fire danger becomes more extreme. The results of our study provide insights to the pros and cons of resisting or facilitating change in vegetation composition and fuel load in the context of a changing climate.

Wildland fire limits subsequent fire occurrence

Several aspects of wildland fire are moderated by site- and landscape-level vegetation changes caused by previous fire, thereby creating a dynamic where one fire exerts a regulatory control on subsequent fire. For example, wildland fire has been shown to regulate the size and severity of subsequent fire. However, wildland fire has the potential to influence other properties of subsequent fire. One of those properties – the extent to which a previous wildland fire inhibits new fires from igniting and spreading within its perimeter – is the focus of our study. In four large wilderness study areas in the western United States (US), we evaluated whether or not wildland fire regulated the ignition and spread (hereafter occurrence) of subsequent fire. Results clearly indicate that wildland fire indeed regulates subsequent occurrence of fires ≥ 20 ha in all study areas. We also evaluated the longevity of the regulating effect and found that wildland fire limits subsequent fire occurrence for nine years in the warm/dry study area in the south-western US and over 20 years in the cooler/wetter study areas in the northern Rocky Mountains. Our findings expand upon our understanding of the regulating capacity of wildland fire and the importance of wildland fire in creating and maintaining resilience to future fire events.

Wildland fire deficit and surplus in the western United States, 1984–2012

Wildland fire is an important disturbance agent in the western US and globally. However, the natural role of fire has been disrupted in many regions due to the influence of human activities, which have the potential to either exclude or promote fire, resulting in a “fire deficit” or “fire surplus”, respectively. In this study, we developed a model of expected area burned for the western US as a function of climate from 1984 to 2012. We then quantified departures from expected area burned to identify geographic regions with fire deficit or surplus. We developed our model of area burned as a function of several climatic variables from reference areas with low human influence; the relationship between climate and fire is strong in these areas. We then quantified the degree of fire deficit or surplus for all areas of the western US as the difference between expected (as predicted with the model) and observed area burned from 1984 to 2012. Results indicate that many forested areas in the western US experienced a fire deficit from 1984 to 2012, likely due to fire exclusion by human activities. We also found that large expanses of non-forested regions experienced a fire surplus, presumably due to introduced annual grasses and the prevalence of anthropogenic ignitions. The heterogeneity in patterns of fire deficit and surplus among ecoregions emphasizes fundamentally different ecosystem sensitivities to human influences and suggests that large-scale adaptation and mitigation strategies will be necessary in order to restore and maintain resilient, healthy, and naturally functioning ecosystems.

Evaluating indices that measure departure of current landscape composition from historical conditions

A measure of the degree of departure of a landscape from its range of historical conditions can provide a means for prioritizing and planning areas for restoration treatments. There are few statistics or indices that provide a quantitative context for measuring departure across landscapes. This study evaluated a set of five similarity indices commonly used in vegetation community ecology (Sorensons Index, Chord Distance, Morisitas Index, Euclidean Distance, and Similarity Ratio) for application in estimating landscape departure (where departure = 1 - similarity). This involved comparing composition (vegetation type by area) of a set of reference landscapes to the compositions of 1,000 simulated historical landscapes. Stochastic simulation modeling was used to create a diverse set of synthetic reference and historical landscapes for departure index evaluation. Five reference landscapes were created to represent various degrees of expected departure from historical conditions. Both reference and historical landscapes were created to contain four important factors that could potentially influence departure calculation: (1) number of classes defining landscape composition, (2) dominance of the classes, (3) variability of area with the classes, and (4) temporal autocorrelation. We found that most evaluated indices are useful but not optimal for calculating departure. The Sorensons Index appeared to perform the best with consistent and precise behavior across the ranges of the four treatments. The number of classes used to describe vegetation had the strongest influence on index performance; landscape composition defined by few classes had the least accurate, most imprecise, and most highly variable departure estimates. While results from this study show the utility of similarity indices in evaluating departure, it is also evident that a new set of statistics are needed to provide a more comprehensive analysis of departure for future applications.

Analog-based fire regime and vegetation shifts in mountainous regions of the western US

Climate change is expected to result in substantial ecological impacts across the globe. These impacts are uncertain but there is strong consensus that they will almost certainly affect fire regimes and vegetation. In this study, we evaluated how climate change may influence fire frequency, fire severity, and broad classes of vegetation in mountainous ecoregions of the contiguous western US for early, middle, and late 21st century (2025, 2055, and 2085, respectively). To do so, we employed the concept of a climate analog, whereby specific locations with the best climatic match between one time period and a different time period are identified. For each location (i.e. 1-km2 pixel), we evaluated potential changes by comparing the reference period fire regime and vegetation to that of the fire regime and vegetation of the nearest pixels representative of its future climate. For the mountainous regions we investigated, we found no universal increase or decrease in fire frequency or severity. Instead, potential changes depend on the bioclimatic domain. Specifically, wet and cold regions (i.e. mesic and cold forest) generally exhibited increased fire frequency but decreased fire severity, whereas drier, moisture-limited regions (i.e. shrubland/grassland) displayed the opposite trend. Results also indicate the potential for substantial changes in the amount and distribution of some vegetation types, highlighting important interactions and feedbacks among climate, fire, and vegetation. Our findings also shed light on a potential threshold or tipping point at intermediate moisture conditions that suggest shifts in vegetation from forest to shrubland/grassland are possible as the climate becomes warmer and drier. However, our study assumes that fire and vegetation are in a state of equilibrium with climate, and, consequently, natural and human-induced disequilibrium dynamics should be considered when interpreting our findings. This article is protected by copyright. All rights reserved.

Mean Composite Fire Severity Metrics Computed with Google Earth Engine Offer Improved Accuracy and Expanded Mapping Potential

Landsat-based fire severity datasets are an invaluable resource for monitoring and research purposes. These gridded fire severity datasets are generally produced with pre- and post-fire imagery to estimate the degree of fire-induced ecological change. Here, we introduce methods to produce three Landsat-based fire severity metrics using the Google Earth Engine (GEE) platform: The delta normalized burn ratio (dNBR), the relativized delta normalized burn ratio (RdNBR), and the relativized burn ratio (RBR). Our methods do not rely on time-consuming a priori scene selection but instead use a mean compositing approach in which all valid pixels (e.g., cloud-free) over a pre-specified date range (pre- and post-fire) are stacked and the mean value for each pixel over each stack is used to produce the resulting fire severity datasets. This approach demonstrates that fire severity datasets can be produced with relative ease and speed compared to the standard approach in which one pre-fire and one post-fire scene are judiciously identified and used to produce fire severity datasets. We also validate the GEE-derived fire severity metrics using field-based fire severity plots for 18 fires in the western United States. These validations are compared to Landsat-based fire severity datasets produced using only one pre- and post-fire scene, which has been the standard approach in producing such datasets since their inception. Results indicate that the GEE-derived fire severity datasets generally show improved validation statistics compared to parallel versions in which only one pre-fire and one post-fire scene are used, though some of the improvements in some validations are more or less negligible. We provide code and a sample geospatial fire history layer to produce dNBR, RdNBR, and RBR for the 18 fires we evaluated. Although our approach requires that a geospatial fire history layer (i.e., fire perimeters) be produced independently and prior to applying our methods, we suggest that our GEE methodology can reasonably be implemented on hundreds to thousands of fires, thereby increasing opportunities for fire severity monitoring and research across the globe.

Effects of Climate Change on Forest Vegetation in the Northern Rockies

Increasing air temperature, through its influence on soil moisture, is expected to cause gradual changes in the abundance and distribution of tree, shrub, and grass species throughout the Northern Rockies, with drought tolerant species becoming more competitive. The earliest changes will be at ecotones between lifeforms (e.g., upper and lower treelines). Ecological disturbance, including wildfire and insect outbreaks, will be the primary facilitator of vegetation change, and future forest landscapes may be dominated by younger age classes and smaller trees. High-elevation forests will be especially vulnerable if disturbance frequency increases significantly. Increased abundance and distribution of non-native plant species, as well as the legacy of past land uses, create additional stress for regeneration of native forest species.