Using Neutral Models to Identify Constraints on Low-severity Fire Regimes

Climate, topography, fuel loadings, and human activities all affect spatial and temporal patterns of fire occurrence. Because fire is modeled as a stochastic process, for which each fire history is only one realization, a simulation approach is necessary to understand baseline variability, thereby identifying constraints, or forcing functions, that affect fire regimes. With a suitable neutral model, characteristics of natural fire regimes estimated from fire history data can be compared to a “null hypothesis”. We generated random landscapes of fire-scarred trees via a point process with sequential spatial inhibition. Random ignition points, fire sizes, and fire years were drawn from uniform and exponential family probability distributions. We compared two characteristics of neutral fire regimes to those from five watersheds in eastern Washington that have experienced low-severity fire. Composite fire intervals (CFIs) at multiple spatial scales displayed similar monotonic decreases with increasing sample area in neutral vs. real landscapes, although patterns of residuals from statistical models differed. In contrast, parameters of the Weibull distribution associated with temporal trends in fire hazard exhibited different forms of scale dependence in real vs. simulated data. Clear patterns in neutral landscapes suggest that deviations from them in empirical data represent real constraints on fire regimes (e.g., topography, fuels). As with any null model, however, neutral fire-regime models need to be carefully tuned to avoid confounding these constraints with artifacts of modeling. Neutral models show promise for investigating low-severity fire regimes to separate intrinsic properties of stochastic processes from the effects of climate, fuel loadings, topography, and management.     

A frame-based spatially explicit model of subarctic vegetation response to climatic change: comparison with a point model

An important challenge in global-change research is to simulate short-term transient changes in climate, disturbance regime, and recruitment that drive long-term vegetation distributions. Spatial features (e.g., topographic barriers) and processes, including disturbance propagation and seed dispersal, largely control these short-term transient changes. Here we present a frame-based spatially explicit model (ALFRESCO) that simulates landscape-level response of vegetation to transient changes in climate and explicitly represents the spatial processes of disturbance propagation and seed dispersal. The spatial model and the point model from which it was developed showed similar results in some cases, but diverged in situations where interactions among neighboring cells (fire spread and seed dispersal) were crucial. Topographic barriers had little influence on fire size in low-flammability vegetation types, but reduced the average fire size and increased the number of fires in highly flammable vegetation (dry grassland). Large fires were more common in landscapes with large contiguous patches of two vegetation types while a more heterogeneous vegetation distribution increased fires in the less flammable vegetation type. When climate was held constant for thousands of years on a hypothetical landscape with the same initial vegetation, the spatial and point models produced identical results for some climates (cold, warm, and hot mesic), but produced markedly different results at current climate and when much drier conditions were imposed under a hot climate. Spruce migration into upland tundra was slowed or prevented by topographic barriers, depending on the size of the corridor. We suggest that frame-based, spatially explicit models of vegetation response to climate change are a useful tool to investigate both short- and long-term transients in vegetation at the regional scale. We also suggest that it is difficult to anticipate when non-spatial models will be reliable and when spatially explicit models are essential. ALFRESCO provides an important link between models of landscape-level vegetation dynamics and larger spatio-temporal models of global climate change.     

The influence of topography and fire in controlling landscape composition and structure in Sierra de Gredos (Central Spain)

Mediterranean landscapes are dynamic systems that undergo temporal changes in composition and structure in response to disturbances, such as fire. Neither landscape patterns nor driving factors that affect them are evenly distributed in space. Accordingly, disturbances and biophysical factors interact in space through time. The aim of this paper is to assess the relative influence of topography and fire on the landscape patterns of a large forested area located in Sierra de Gredos (Central Spain) through time. A series of Landsat MSS images from 1975 to 1990, and a digital elevation model (DEM) were used to map fires, assess topographical complexity and evaluate changes in landscape composition and structure. Functional regions across the entire landscape were identified using different classification criteria (i.e., percentage burned area and topographic properties) to model topographic and fire impacts at regional scales. A canonical variance partition method, with a time series split-plot design, quantified the relative influence and co-variation of topography and fire on land cover patterns through time. Main results indicated that analyzing portions of the landscape under similar environmental conditions and fire histories, the effects of different fire regimes on the spatio-temporal dynamics of main land covers can be highlighted. However, the impact of fire on landscape patterns was high variable among regions due to the different regeneration abilities of main land covers, the topographic constraints and the fire histories of each region. Hence, broad patterns of fire related variance and co-variation with topography emerged across the entire area due to the different conditions of each landscape portion in which this large Mediterranean landscape was divided. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Drivers and trends in landscape patterns of stand-replacing fire in forests of the US Northern Rocky Mountains (1984–2010)

Context

Resilience in fire-prone forests is strongly affected by landscape burn-severity patterns, in part by governing propagule availability around stand-replacing patches in which all or most vegetation is killed. However, little is known about drivers of landscape patterns of stand-replacing fire, or whether such patterns are changing during an era of increased wildfire activity.

Objectives

(a) Identify key direct/indirect drivers of landscape patterns of stand-replacing fire (e.g., size, shape of patches), (b) test for temporal trends in these patterns, and (c) anticipate thresholds beyond which landscape patterns of burn severity may change fundamentally.

Methods

We applied structural equation modeling to satellite burn-severity maps of fires in the US Northern Rocky Mountains (1984–2010) to test for direct and indirect (via influence on fire size and proportion stand-replacing) effects of climate/weather, vegetation, and topography on landscape patterns of stand-replacing fire. We also tested for temporal trends in landscape patterns.

Results

Landscape patterns of stand-replacing fire were strongly controlled by fire size and proportion stand-replacing, which were, in turn, controlled by climate/weather and vegetation/topography, respectively. From 1984 to 2010, the proportion of stand-replacing fire within burn perimeters increased from 0.22 to 0.27. Trends for other landscape metrics were not significant, but may respond to further increases proportion stand-replacing fire.

Conclusions

Fires from 1984 to 2010 exhibited tremendous heterogeneity in landscape patterns of stand-replacing fire, likely promoting resilience in burned areas. If trends continue on the current trajectory, however, fires may produce larger and simpler shaped patches of stand-replacing fire with more burned area far from seed sources.

     

Spatial patterns of large natural fires in Sierra Nevada wilderness areas

The effects of fire on vegetation vary based on the properties and amount of existing biomass (or fuel) in a forest stand, weather conditions, and topography. Identifying controls over the spatial patterning of fire-induced vegetation change, or fire severity, is critical in understanding fire as a landscape scale process. We use gridded estimates of fire severity, derived from Landsat ETM+ imagery, to identify the biotic and abiotic factors contributing to the observed spatial patterns of fire severity in two large natural fires. Regression tree analysis indicates the importance of weather, topography, and vegetation variables in explaining fire severity patterns between the two fires. Relative humidity explained the highest proportion of total sum of squares throughout the Hoover fire (Yosemite National Park, 2001). The lowest fire severity corresponded with increased relative humidity. For the Williams fire (Sequoia/Kings Canyon National Parks, 2003) dominant vegetation type explains the highest proportion of sum of squares. Dominant vegetation was also important in determining fire severity throughout the Hoover fire. In both fires, forest stands that were dominated by lodgepole pine (Pinus contorta) burned at highest severity, while red fir (Abies magnifica) stands corresponded with the lowest fire severities. There was evidence in both fires that lower wind speed corresponded with higher fire severity, although the highest fire severity in the Williams fire occurred during increased wind speed. Additionally, in the vegetation types that were associated with lower severity, burn severity was lowest when the time since last fire was fewer than 11 and 17 years for the Williams and Hoover fires, respectively. Based on the factors and patterns identified, managers can anticipate the effects of management ignited and naturally ignited fires at the forest stand and the landscape levels.     

Normalized burn ratios link fire severity with patterns of avian occurrence

Context

Remotely sensed differenced normalized burn ratios (DNBR) provide an index of fire severity across the footprint of a fire. We asked whether this index was useful for explaining patterns of bird occurrence within fire adapted xeric pine-oak forests of the southern Appalachian Mountains.

Objectives

We evaluated the use of DNBR indices for linking ecosystem process with patterns of bird occurrence. We compared field-based and remotely sensed fire severity indices and used each to develop occupancy models for six bird species to identify patterns of bird occurrence following fire.

Methods

We identified and sampled 228 points within fires that recently burned within Great Smoky Mountains National Park. We performed avian point counts and field-assessed fire severity at each bird census point. We also used Landsat? imagery acquired before and after each fire to quantify fire severity using DNBR. We used non-parametric methods to quantify agreement between fire severity indices, and evaluated single season occupancy models incorporating fire severity summarized at different spatial scales.

Results

Agreement between field-derived and remotely sensed measures of fire severity was influenced by vegetation type. Although occurrence models using field-derived indices of fire severity outperformed those using DNBR, summarizing DNBR at multiple spatial scales provided additional insights into patterns of occurrence associated with different sized patches of high severity fire.

Conclusions

DNBR is useful for linking the effects of fire severity to patterns of bird occurrence, and informing how high severity fire shapes patterns of bird species occurrence on the landscape.

     

Landscape heterogeneity and fire behavior: scale-dependent feedback between fire and grazing processes

Fire and grazing are ecological processes that frequently interact to modify landscape patterns of vegetation. There is empirical and theoretical evidence that response of herbivores to heterogeneity is scale-dependent however the relationship between fire and scale of heterogeneity is not well defined. We examined the relationship between fire behavior and spatial scale (i.e., patch grain) of fuel heterogeneity. We created four heterogeneous landscapes modeled after those created by a fire–grazing interaction that differed in grain size of fuel patches. Fire spread was simulated through each model landscape from 80 independent, randomly located ignition points. Burn area, burn shape complexity and the proportion of area burnt by different fire types (headfire, backfire and flankfire) were all affected by the grain of fuel patch. The area fires burned in heterogeneous landscapes interacted with the fuel load present in the patch where ignition occurred. Burn complexity was greater in landscapes with small patch grain than in landscapes with large patch grain. The proportion of each fire type (backfire, flankfire and headfire) was similar among all landscapes regardless of patch grain but the variance of burned area within each of the three fire types differed among treatments of patch grain. Our landscape fire simulation supports the supposition that feedbacks between landscape patterns and ecological processes are scale-dependent, in this case spatial scale of fuel loading altering fire spread through the landscape.     

Temporal patterns of ecosystem processes on simulated landscapes in Glacier National Park,Montana, USA

The mechanistic, spatially-explicit fire succession model, Fire-BGC (a Fire BioGeoChemical succession model) was used to investigate long-term trends in landscape pattern under historical and future fire regimes and present and future climate regimes for two 46000 ha landscapes in Glacier National Park, Montana, USA. Fire-BGC has two spatial and temporal resolutions in the simulation architecture where ecological processes that act at a landscape level, such as fire, are simulated annually from information contained in spatial data layers, while stand-level processes such as photosynthesis, transpiration, and decomposition are simulated both daily and annually. Fire is spread across the landscape using the FARSITE fire growth model and subsequent fire effects are simulated at the stand-level. Fire-BGC was used to simulate changes in landscape pattern over 250 years under four scenarios: (1) complete fire exclusion under current climate, (2) historical wildfire occurrence and current climate, (3) complete fire exclusion under a possible future climate, (4) future wildfire occurrence and future climate. Simulated maps of dominant tree species, aboveground standing crop, leaf area index, and net primary productivity (NPP) were contrasted across scenarios using the metrics of patch density, edge density, evenness, contagion, and interspersion. Simulation results indicate that fire influences landscape pattern metrics more that climate alone by creating more diverse, fragmented, and disconnected landscapes. Fires were more frequent, larger, and more intense under a future climate regime. Landscape metrics showed different trends for the process-based NPP map when compared to the cover type map. It may be important to augment landscape analyses with process-based layers as well as structural and compositional layers.     

Landscape dynamics in crown fire ecosystems

Crown fires create broad-scale patterns in vegetation by producing a patch mosaic of stand age classes, but the spread and behavior of crown fires also may be constrained by spatial patterns in terrain and fuels across the landscape. In this review, we address the implications of landscape heterogeneity for crown fire behavior and the ecological effects of crown fires over large areas. We suggest that fine-scale mechanisms of fire spread can be extrapolated to make broad-scale predictions of landscape pattern by coupling the knowledge obtained from mechanistic and empirical fire behavior models with spatially-explicit probabilistic models of fire spread. Climatic conditions exert a dominant control over crown fire behavior and spread, but topographic and physiographic features in the landscape and the spatial arrangement and types of fuels have a strong influence on fire spread, especially when burning conditions (e.g., fuel moisture and wind) are not extreme. General trends in crown fire regimes and stand age class distributions can be observed across continental, latitudinal, and elevational gradients. Crown fires are more frequent in regions having more frequent and/or severe droughts, and younger stands tend to dominate these landscapes. Landscapes dominated by crown fires appear to be nonequilibrium systems. This nonequilibrium condition presents a significant challenge to land managers, particularly when the implications of potential changes in the global climate are considered. Potential changes in the global climate may alter not only the frequency of crown fires but also their severity. Crown fires rarely consume the entire forest, and the spatial heterogeneity of burn severity patterns creates a wide range of local effects and is likely to influence plant reestablishment as well as many other ecological processes. Increased knowledge of ecological processes at regional scales and the effects of landscape pattern on fire dynamics should provide insight into our understanding of the behavior and consequences of crown fires.     

Use of artificial landscapes to isolate controls on burn probability

Techniques for modeling burn probability (BP) combine the stochastic components of fire regimes (ignitions and weather) with sophisticated fire growth algorithms to produce high-resolution spatial estimates of the relative likelihood of burning. Despite the numerous investigations of fire patterns from either observed or simulated sources, the specific influence of environmental factors on BP patterns is not well understood. This study examined the relative effects of ignitions, fuels, and weather on mean BP and spatial patterns in BP (i.e., BP variability) using highly simplified artificial landscapes and wildfire simulation methods. Our results showed that a limited set of inputs yielded a wide range of responses in the mean and spatial patterning of BP. The input factors contributed unequally to mean BP and to BP variability: so-called top-down controls (weather) primarily influenced mean BP, whereas bottom-up influences (ignitions and fuels) were mainly responsible for the spatial patterns of BP. However, confounding effects and interactions among factors suggest that fully separating top-down and bottom-up controls may be impossible. Furthermore, interactions among input variables produced unanticipated but explainable BP patterns, hinting at complex topological dependencies among the main determinants of fire spread and the resulting BP. The results will improve our understanding of the spatial ecology of fire regimes and help in the interpretation of patterns of fire likelihood on real landscapes as part of future wildfire risk assessments.     

Comparison of the Sensitivity of Landscape-fire-succession Models to Variation in Terrain, Fuel Pattern, Climate and Weather

The purpose of this study was to compare the sensitivity of modelled area burned to environmental factors across a range of independently-developed landscape-fire-succession models. The sensitivity of area burned to variation in four factors, namely terrain (flat, undulating and mountainous), fuel pattern (finely and coarsely clumped), climate (observed, warmer & wetter, and warmer & drier) and weather (year-to-year variability) was determined for four existing landscape-fire-succession models (EMBYR, FIRESCAPE, LANDSUM and SEM-LAND) and a new model implemented in the LAMOS modelling shell (LAMOS(DS)). Sensitivity was measured as the variance in area burned explained by each of the four factors, and all of the interactions amongst them, in a standard generalised linear modelling analysis. Modelled area burned was most sensitive to climate and variation in weather, with four models sensitive to each of these factors and three models sensitive to their interaction. Models generally exhibited a trend of increasing area burned from observed, through warmer and wetter, to warmer and drier climates with a 23-fold increase in area burned, on average, from the observed to the warmer, drier climate. Area burned was sensitive to terrain for FIRESCAPE and fuel pattern for EMBYR. These results demonstrate that the models are generally more sensitive to variation in climate and weather as compared with terrain complexity and fuel pattern, although the sensitivity to these latter factors in a small number of models demonstrates the importance of representing key processes. The models that represented fire ignition and spread in a relatively complex fashion were more sensitive to changes in all four factors because they explicitly simulate the processes that link these factors to area burned. The US Government's and the Canadian Government's right to retain a non-exclusive, royalty-free license is acknowledged     

Climatic, landform, microtopographic, and overstory canopy controls of tree invasion in a subalpine meadow landscape, Oregon Cascades, USA

Tree invasions have been documented throughout Northern Hemisphere high elevation meadows, as well as globally in many grass and forb-dominated ecosystems. Tree invasions are often associated with large-scale changes in climate or disturbance regimes, but are fundamentally driven by regeneration processes influenced by interactions between climatic, topographic, and biotic factors at multiple spatial scales. The purpose of this research was to quantify spatiotemporal patterns of meadow invasion; and how climate, larger landforms, topography, and overstory trees have interactively influenced tree invasion. We combined airborne Light Detection and Ranging (LiDAR) characterizations of landforms, topography, and overstory vegetation with historical climate, field measurements of snow depth, tree abundance, and tree ages to reconstruct spatial and temporal patterns of tree invasion over five decades in a subalpine meadow complex in the Oregon Cascade Range, USA. Proportion of meadow occupied by trees increased from 8?% in 1950 to 35?% in 2007. Larger landforms, topography, and tree canopies interactively mediated regional climatic controls of tree invasion by modifying depth and persistence of snow pack, while tree canopies also influenced seed source availability. Landscape context played an important role mediating snow depth and tree invasion; on glacial landforms tree invasion was negatively associated with spring snowfall, but on debris flows tree invasion was not associated with snow fall. The importance of snow, uncertain climate change impacts on snow, and mediation of snow by interacting and context dependent factors in complex mountain terrain poses substantial hurdles for understanding how these ecotones may respond to future climate conditions.     

Landscape-scale controls over 20th century fire occurrence in two large Rocky Mountain (USA) wilderness areas

Topography, vegetation, and climate act together to determine thespatial patterns of fires at landscape scales. Knowledge oflandscape-fire-climate relations at these broad scales (1,000s hato 100,000s ha) is limited and is largely based on inferences andextrapolations from fire histories reconstructed from finer scales. In thisstudy, we used long time series of fire perimeter data (fire atlases) and datafor topography, vegetation, and climate to evaluate relationships between large20^thcentury fires and landscape characteristics in two contrastingareas: the 486,673-ha Gila/Aldo Leopold Wilderness Complex (GALWC)in New Mexico, USA, and the 785,090-ha Selway-BitterrootWilderness Complex (SBWC) in Idaho and Montana, USA. There were importantsimilarities and differences in gradients of topography, vegetation, andclimatefor areas with different fire frequencies, both within and between study areas.These unique and general relationships, when compared between study areas,highlight important characteristics of fire regimes in the Northern andSouthernRocky Mountains of the Western United States.Results suggest that amount and horizontal continuity of herbaceous fuels limitthe frequency and spread of surface fires in the GALWC, while the moisturestatus of large fuels and crown fuels limits the frequency of moderate-to-highseverity fires in the SBWC. These empirically described spatial and temporalrelationships between fire, landscape attributes, and climate increaseunderstanding of interactions among broad-scale ecosystem processes. Resultsalso provide a historical baseline for fire management planning over broadspatial and temporal scales in each wilderness complex.This revised version was published online in May 2005 with corrections to the Cover Date.     

Using a stochastic model and cross-scale analysis to evaluate controls on historical low-severity fire regimes

Fire-scarred trees provide a deep temporal record of historical fire activity, but identifying the mechanisms therein that controlled landscape fire patterns is not straightforward. We use a spatially correlated metric for fire co-occurrence between pairs of trees (the Sørensen distance variogram), with output from a neutral model for fire history, to infer the relative strength of top-down vs. bottom-up controls on historical fire regimes. An inverse modeling procedure finds combinations of neutral-model parameters that produce Sørensen distance variograms with statistical properties similar to those observed from two landscapes in eastern Washington, USA, with contrasting topography. We find the most parsimonious model structure that is able to replicate the observed patterns and the parameters of this model provide surrogates for the predominance of top-down vs. bottom-up controls. Simulations with relatively low spread probability produce irregular fire perimeters and variograms similar to those from the topographically complex landscape. With higher spread probabilities fires exhibit regular perimeters and variograms similar to those from the simpler landscape. We demonstrate that cross-scale properties of the fire-scar record, even without historical fuels and weather data, document how complex topography creates strong bottom-up controls on fire spread. This control is weaker in simpler topography, and may be compromised in a future climate with more severe weather events.     

Effects of landscape patterns of fire severity on regenerating ponderosa pine forests (<Emphasis Type="Italic">Pinus ponderosa</Emphasis>) in New Mexico and Arizona,USA

Much of the current effort to restore southwestern ponderosa pine forests to historical conditions is predicated upon assumptions regarding the catastrophic effects of large fires that are now defining a new fire regime. To determine how spatial characteristics influence the process of ponderosa pine regeneration under this new regime, we mapped the spatial patterns of severity at areas that burned in 1960 (Saddle Mountain, AZ) and (La Mesa, NM) 1977 using pre- and post-fire aerial photography, and quantified characteristics of pine regeneration at sample plots in areas where all trees were killed by the fire event. We used generalized linear models to determine the relationship of ponderosa pine stem density to three spatial burn pattern metrics: (1) distance to nearest edge of lower severity; (2) neighborhood severity, measured at varying spatial scales, and (3) scaled seed dispersal kernel surfaces. Pine regeneration corresponded most closely with particular scales of measurement in both seed dispersal kernel and neighborhood severity. Spatial patterns of burning remained important to understanding regeneration even after consideration of subsequent disturbance and other environmental variables, with the exception of a few cases in which simpler models were equally well-supported by the data. Analysis of tree ages revealed slow progress in early post-fire years. Our observations suggest that populations spread in a moving front, as well as by remotely dispersed individuals. Based on our results, recent large fires cannot be summarily dismissed as catastrophic. We conclude that management should focus on the value and natural recovery of post-fire landscapes. Further, process centered restoration efforts could utilize our findings in formulating reference dynamics under a changing fire regime.     

Land cover influences boreal-forest fire responses to climate change: geospatial analysis of historical records from Alaska

Context

Wildfire activity in boreal forests is projected to increase dramatically in response to anthropogenic climate change. By altering the spatial arrangement of fuels, land-cover configuration may interact with climate change to influence fire-regime dynamics at landscape and regional scales.

Objectives

We evaluate how land cover interacts with weather conditions to influence boreal-forest burning from 2012 to 2014 in Alaska.

Methods

Using geospatial fire and land-cover data, we quantify relationships between area burned and land cover, and test whether observed patterns of burning differ from random under varying weather conditions and fire sizes.

Results

Mean summer moisture index was correlated with annual area burned (ρ = ?0.78, p < 0.01), the total number of fires (ρ = ?0.68, p = 0.01), and the number of large fires (>500 km²; ρ = ?0.58, p = 0.04). Area burned was related positively to percent cover of coniferous forest and woody wetlands, and negatively to percent cover of shrub scrub, dwarf scrub, and open water and barren areas. Fires preferentially burned coniferous forest, which represented 50.1 % of the area burned in warmer/drier summers and 40.3 % of area burned in cooler/wetter summers, compared to the 34.5 % (±4.2 %) expected by random selection of land-cover classes. Overall vegetation tended to burn more similarly to random in warmer/drier than cooler/wetter years.

Conclusions

Land cover exerted greater influences on boreal fire regimes when weather conditions were less favorable for forest burning. Reliable projections of boreal fire-regime change thus require consideration of the interactions between climate and land cover, as well as feedbacks from land-cover change.

     

Topographic variation in the climatic change response of a larch forest in Northeastern China

Context

Due to the spatial heterogeneity of the disturbance regimes and community assemblages along topoclimatic gradients, the response of forest ecosystem to climate change varies at the landscape scale.

Objectives

Our objective was to quantify the possible changes in forest ecosystems and the relative effects of climate warming and fire regime changes in different topographic positions.

Methods

We used a spatially explicit model (LANDIS PRO) combined with a gap model (LINKAGES) to predict the possible response of boreal larch forests to climate and fire regime changes, and examined how this response would vary in different topographic positions.

Results

The result showed that the proportion of landscape occupied by broadleaf species increased under warming climate and frequent fires scenarios. Shifts in species composition were strongly influenced by both climate warming and more frequent fires, while changes in age structure were mainly controlled by shifts in fire regime. These responses varied in the different topographic positions, with forests in valley bottoms being most resilient to climate-fire changes and forests in uplands being more likely to shift their composition from larch-dominant to mixed forests. Such variation in the topographic response may be induced by the heterogeneities of the environmental conditions and fire regime.

Conclusions

Fire disturbance could alter the equilibrium of ecosystems and accelerate the response of forests to climate warming. These effects are largely modulated by topographic variations. Our findings suggest that it is imperative to consider topographic complexities when developing appropriate fire management policies for mitigating the effects of climate change.

     

Habitat selection by spotted owls after a megafire reflects their adaptation to historical frequent-fire regimes

Context

Climate and land-use change have led to disturbance regimes in many ecosystems without a historical analog, leading to uncertainty about how species adapted to past conditions will respond to novel post-disturbance landscapes.

Objectives

We examined habitat selection by spotted owls in a post-fire landscape. We tested whether selection or avoidance of severely burned areas could be explained by patch size or configuration, and whether variation in selection among individuals could be explained by differences in habitat availability.

Methods

We applied mixed-effects models to GPS data from 20 spotted owls in the Sierra Nevada, California, USA, with individual owls occupying home ranges spanning a broad range of post-fire conditions after the 2014 King Fire.

Results

Individual spotted owls whose home ranges experienced less severe fire (<?5% of home range severely burned) tended to select severely burned forest, but owls avoided severely burned forest when more of their home range was affected (~ 5–40%). Owls also tended to select severe fire patches that were smaller in size and more complex in shape, and rarely traveled?>?100-m into severe fire patches. Spotted owls avoided areas that had experienced post-fire salvage logging but the interpretation of this effect was nuanced. Owls also avoided areas that were classified as open and/or young forest prior to the fire.

Conclusions

Our results support the hypothesis that spotted owls are adapted to historical fire regimes characterized by small severe fire patches in this region. Shifts in disturbance regimes that produce novel landscape patterns characterized by large, homogeneous patches of high-severity fire may negatively affect this species.

     

Spatial attributes of fire regime in eastern Canada: influences of regional landscape physiography and climate

The characterization of the fire regime in the boreal forest rarely considers spatial attributes other than fire size. This study investigates the spatial attributes of fires using the physiography of the landscape as a spatial constraint at a regional scale. Using the Canadian National Fire Database, the size, shape, orientation and eccentricity were assessed for 1,136 fires between 1970 and 2010 in Quebec’s boreal forest and were summarized by ecodistrict. These spatial metrics were used to cluster 33 ecodistricts into homogeneous fire zones and then to determine which environmental variables (climate, topography, hydrography, and surficial deposits) influence the spatial attributes of fires. Analyses showed that 28 out of 33 ecodistricts belonging to a given fire zone were spatially contiguous, suggesting that factors driving the spatial attributes of fire are acting at a regional scale. Indeed, the orientation and size of fires vary significantly among the zones and are driven by the spatial orientation of the landscape and the seasonal regional climate. In some zones, prevailing winds during periods conducive to fire events parallel to the orientation of the landscape may favour the occurrence of very large fires (>100,000 ha). Conversely, an orientation of the landscape opposite to the prevailing winds may act as a natural firebreak and limit the fire size and orientation. This study highlights the need to consider the synergistic relationship between the landscape spatial patterns and the climate regime over the spatial attributes of fire at supra-regional scale. Further scale-dependant studies are needed to improve our understanding of the spatial factors controlling the spatial attributes of fire.     

Probabilistic models of fire occurrence across National Park Service units within the Mojave Desert Network,USA

The frequency and size of wildfires within the Mojave Desert are increasing, possibly due to climate and land cover changes and associated increases in non-native invasive plant biomass, as measured by normalized difference vegetation index (NDVI). These patterns are of particular concern to resource managers in regions where native plant communities are not well adapted to fire. We used an information-theoretic and mixed-model approach to quantify the importance of multiple environmental variables in predicting, separately, the probabilities of occurrence of all fires and the occurrence large (>20 ha) fires in five management units administered by the National Park Service in the Mojave Desert Network and based on fire ignition data obtained for the period 1992–2011. Fire occurrence was strongly associated with areas close to roads, high maximum NDVI values in the year preceding ignition, the desert montane ecological zone, and high topographic roughness. Large fire probability was strongly associated with lightning-caused ignition events, high maximum NDVI values in the spring preceding ignition, high topographic roughness, the middle-elevation shrubland ecological zone, and areas further from roads. Our probabilistic models and maps can be used to explore patterns of fire occurrence based upon variability in NDVI values and to assess the vulnerability of Mojave Desert protected areas to undesirable fire events.