Simulating the effects of frequent fire on southern California coastal shrublands.

Fire disturbance is a primary agent of change in the mediterranean-climate chaparral shrublands of southern California, USA. However, fire frequency has been steadily increasing in coastal regions due to ignitions at the growing wildland-urban interface. Although chaparral is resilient to a range of fire frequencies, successively short intervals between fires can threaten the persistence of some species, and the effects may differ according to plant functional type. California shrublands support high levels of biological diversity, including many endangered and endemic species. Therefore, it is important to understand the long-term effects of altered fire regimes on these communities. A spatially explicit simulation model of landscape disturbance and succession (LANDIS) was used to predict the effects of frequent fire on the distribution of dominant plant functional types in a study area administered by the National Park Service. Shrubs dependent on fire-cued seed germination were most sensitive to frequent fire and lost substantial cover to other functional types, including drought-deciduous subshrubs that typify coastal sage scrub and nonnative annual grasses. Shrubs that resprout were favored by higher fire frequencies and gained in extent under these treatments. Due to this potential for vegetation change, caution is advised against the widespread use of prescribed fire in the region.     

Hierarchical space-time models for fire ignition and percentage of land burned by wildfires

Policy responses for local and global fire management as well as international green-gas inventories depend heavily on the proper understanding of the annual fire extend as well as its spatial variation across any given study area. Proper statistical models are important tools in quantifying these fire risks. We propose Bayesian methods to model jointly the probability of ignition and fire sizes in Australia and New Zeland. The data set on which we base our model and results consists of annual observations of several meteorological and topographical explanatory variables, together with the percentage of land burned over a grid with resolution of 1° across Austalia and New Zealand. Our model and conclusions bring improvements on the results reported by Russell-Smith et al. in Int J Wildland Fire, 16:361–377 (2007) based on a similar data set.     

Mapping lightning/human-caused wildfires occurrence under ignition point location uncertainty

Fire managers need to study fire history in terms of occurrence in order to understand and model the spatial distribution of the causes of ignition. Fire atlases are useful open sources of information, recording each single fire event by means of its geographical position. In such cases the fire event is considered as point-based, rather than area-based data, completely losing its surface nature. Thus, an accurate method is needed to estimate continuous density surfaces from ignition points where location is affected by a certain degree of uncertainty. Recently, the fire scientific community has focused its attention on the kernel density interpolation technique in order to convert point-based data into continuous surface or surface-data. The kernel density technique needs a priori setting of smoothing parameters, such as the bandwidth size. Up to now, the bandwidth size was often based on subjective choices still needing expert knowledge, eventually supported by empirical decisions, thus leading to serious uncertainties. Nonetheless, a geostatistical model able to describe the point concentration and consequently the clustering degree is required. This paper tries to solve such issues by implementing the kernel density adaptive mode. Lightning/human-caused fires occurrence was investigated in the region of Aragón's autonomy over 19 years (1983–2001) using 3428 and 4195 ignition points respectively for the two causes of fire origin. An analytical calibration procedure was implemented to select the most reliable density surfaces to reduce under/over-density estimation, overcoming the current drawbacks to define it by visual inspection or personal interpretation. Besides, ignition point location uncertainty was investigated to check the sensitivity of the proposed model. The different concentration degree and the dissimilar spatial pattern of the two datasets, allow testing the proposed calibration methodology under several conditions. After having discovered the slight sensitivity of the model to the exact point position, the obtained density surfaces for the two causes were combined to discover hotspot areas and spatial patterns of the two causes. Evident differences in spatial location of the origin causes were noted and described. The general trend follows the geographical features and the human activity of the study areas. The proposed technique should be promising to support decision-making in wildfire prevention actions, because of the occurrence map can be used as a response variable in fire risk predicting models.     

Human influence on California fire regimes.

Periodic wildfire maintains the integrity and species composition of many ecosystems, including the mediterranean-climate shrublands of California. However, human activities alter natural fire regimes, which can lead to cascading ecological effects. Increased human ignitions at the wildland-urban interface (WUI) have recently gained attention, but fire activity and risk are typically estimated using only biophysical variables. Our goal was to determine how humans influence fire in California and to examine whether this influence was linear, by relating contemporary (2000) and historic (1960-2000) fire data to both human and biophysical variables. Data for the human variables included fine-resolution maps of the WUI produced using housing density and land cover data. Interface WUI, where development abuts wildland vegetation, was differentiated from intermix WUI, where development intermingles with wildland vegetation. Additional explanatory variables included distance to WUI, population density, road density, vegetation type, and ecoregion. All data were summarized at the county level and analyzed using bivariate and multiple regression methods. We found highly significant relationships between humans and fire on the contemporary landscape, and our models explained fire frequency (R2 = 0.72) better than area burned (R2 = 0.50). Population density, intermix WUI, and distance to WUI explained the most variability in fire frequency, suggesting that the spatial pattern of development may be an important variable to consider when estimating fire risk. We found nonlinear effects such that fire frequency and area burned were highest at intermediate levels of human activity, but declined beyond certain thresholds. Human activities also explained change in fire frequency and area burned (1960-2000), but our models had greater explanatory power during the years 1960-1980, when there was more dramatic change in fire frequency. Understanding wildfire as a function of the spatial arrangement of ignitions and fuels on the landscape, in addition to nonlinear relationships, will be important to fire managers and conservation planners because fire risk may be related to specific levels of housing density that can be accounted for in land use planning. With more fires occurring in close proximity to human infrastructure, there may also be devastating ecological impacts if development continues to grow farther into wildland vegetation.     

Modelling the effect of fire-exclusion and prescribed fire on wildfire size in Mediterranean ecosystems

There is a debate on which factor, fuel accumulation or meteorological variability, is the fundamental control of the occurrence of large fires in Mediterranean-type ecosystems. Its resolution has important management implications, because if the fuel hypothesis proves to be right, then fire-exclusion would enhance the occurrence of large wildfires, and prescribed-fires would be a useful tool to fight them. On the other hand, if large fires were just a direct consequence of some extreme weather situations, neither fire-exclusion nor prescribed fire would have any influence on the size of wildfires. Here we present a simple model of vegetation dynamics and fire spread over homogeneous areas intended to treat quantitatively this issue. In particular, we wanted to address the following questions: (1) What is the effect that different fire fighting capacities have on the total area burnt and, especially, on large fires? (2) What is the effect that different levels of prescribed fire have on the area burnt in wildfires and, especially, in large fires? The model incorporates meteorological variability, different rates of fuel accumulation, number of ignitions per year, fire-fighting capacity, and prescribed burning. The model was calibrated with fire regime data (mean fire size, annual area burnt, and fire size distribution) of Tarragona (NE Spain) and Coimbra (Central Portugal), and it accurately reproduced both data sets, while allowing for multiple behavioural models and prediction uncertainties within the GLUE methodology. Results showed that for a given region, with its particular characteristics of climate, number of ignitions, and vegetation flammability, there was a fairly constant annual area burnt for different fire-fighting capacities. However, higher fire-fighting capacities resulted in a slightly higher proportion of large fires. There was also a quite constant annual area burnt (prescribed and wild fires together) for different prescribed fire intensities in each region. However, the total amount and proportion of large fires decreased as the prescribed burning intensity increased. So, according to the model, it seems that the total area burnt will be more or less the same despite any effort to reduce it by extinguishing fires or by using prescribed burning. Nevertheless, the effect of the fire exclusion policy slightly enhances the dominance of large fires, whereas the use of prescribed fires greatly reduces the importance of large fires.     

Simulating a natural fire regime on an Atlantic coast barrier island complex in Florida, USA

The HFire fire regime model was used to simulate the natural fire regime (prior to European settlement) on Kennedy Space Center, Merritt Island National Wildlife Refuge, Canaveral National Seashore, and Cape Canaveral Air Force Station, Florida. Model simulations were run for 500 years and the model was parameterized using information generated from previously published empirical studies on these properties (e.g., lightning fire ignition frequencies and ignition seasonality). A mosaic pattern of frequent small fires dominated this fire regime with rare but extremely large fires occurring during dry La Niña periods. This simulated fire size distribution very closely matched the previously published fire size distribution for lightning ignitions on these properties. A sensitivity analysis was performed to establish which parameters were most influential and the range of variation surrounding empirically parameterized model output. Dead fuel moisture and wind speed had the largest influence on model outcome. A wide range of variance was observed surrounding the composite simulation with the least being 6% in total burn frequency and the greatest being 49% in total area burned. Because simulation modeling is the best option for fire regime reconstruction in many rapidly growing shrub dominated systems, these results will be of interest to scientists and fire managers for delineating the natural fire regime on these properties, the southeastern United States and other fire adapted shrub systems worldwide.     

Fire Regime Changes in La Michilía Biosphere Reserve, Durango, Mexico

Abstract: The ability of reserves to maintain natural ecosystem processes such as fire disturbance regimes is central to long-term conservation. Fire-scarred tree samples were used to reconstruct fire regimes at five study sites totaling approximately 230 ha in pine (   Pinus spp.) and oak ( Quercus spp.) forests of La Michilía Biosphere Reserve on the dry east slope of the Sierra Madre Occidental, Durango, Mexico. Study sites covered a 20-km environmental gradient of elevation, topography, and human land uses. Plant communities ranged from oak-pine to mixed conifer forests. Fires were frequent at all sites prior to 1930, when large-scale grazing of domestic livestock was initiated. Widespread fires have been excluded from four of the five sites since 1945, with an essentially uninterrupted regime of frequent fires continuing only in the reserve core. Xeric sites had many, smaller fires, whereas mesic sites had fewer but larger fires. On a reserve-wide scale, a fire burned on at least one site nearly every year, usually in the dry spring or early summer season, but fire years were rarely synchronous among the sites. Fire occurrence was weakly related to the Southern Oscillation climate pattern; major reserve-wide fire years almost never coincided with wet Southern Oscillation extremes but only occasionally matched dry extremes. Maintenance of the long-term frequent-fire regime in the reserve core is one indicator that the biosphere reserve model has been successful in conserving natural processes, but the protected area is small ( 7000 ha). Because of the key role of frequent-fire regimes in regulating ecosystem structure and function, restoration of the ecological role of fire disturbance is a desirable conservation strategy.     

Bandwidth determination for kernel density analysis of wildfire events at forest sub-district scale

Forest fire is regarded as one of the most significant factors leading to land degradation. While evaluating fire hazard or producing fire risk zone maps, quantitative analyses using historic fire data is often required, and during all these modeling and multi-criteria analysis processes, the fire event itself is taken as the dependent variable. However, there are two main problematic issues in analyzing historic fire data. The first difficulty arises from the fact that it is in point format, whereas a continuous surface is frequently needed for statistically analyzing the relationship of fire events with other factors, such as anthropogenic, topographic and climatic conditions. Another, and probably the most bothersome challenge is to overcome inaccuracy inherent in historic fire data in point format, since the exact coordinates of ignition points are mostly unknown. In this study, kernel density mapping, a widely used method for converting discrete point data into a continuous raster surface, was used to map the historic fire data in Mumcular Forest Sub-district in Mu?la, Turkey. The historic fire data was transferred onto the digital forest stand map of the study area, where the exact locations of ignition points are unknown; however, the exact number of ignition points in each compartment of the forest stand map is known. Different random distributions of ignition points were produced, and for each random distribution, kernel density maps were produced by applying two distinct kernel functions with several smoothing parameter options. The obtained maps were compared through correlation analysis in order to illustrate the effect of randomness, choice of kernel function and smoothing parameter. The proposed method gives a range of values rather than a single bandwidth value; however, it provides a more reliable way than comparing the maps with different bandwidths subjectively by eye.     

Knowing fire incidence through fuel phenology: A remotely sensed approach

Fire is a basic ecological factor that contributes to determine vegetation diversity and dynamics in time and space. Fuel characteristics play an essential role in fire ignition and propagation; at the landscape scale fuel availability and flammability are closely related to the vegetation phenology that directly affects wildfire pattern in time and space. In this view, the annual normalized difference vegetation index (NDVI) profiles derived from high temporal resolution satellites, like SPOT Vegetation, represent an effective tool for monitoring the coarse-scale vegetation seasonal timing. The objective of this study thus consists in quantifying the explanatory power of multitemporal NDVI profiles on the fire regime characteristics of the potential natural vegetation (PNV) types of Sardinia (Italy) over a 5-year period (2000-2004). The results obtained show a good association between the NDVI temporal dynamics of the PNV of Sardinia and the corresponding fire regime characteristics, emphasizing the role of the bioclimatic timing of the vegetation in controlling the coarse-scale wildfire spatio-temporal distribution of Sardinia. By providing a sound phytogeographical framework for describing different wildfire regimes, PNV maps can thus be considered helpful cartographic documents for fire management strategies at the landscape scale.     

Fire-climate history and landscape patterns of high burn severity areas on the California southern and central coast

There is mounting evidence that fire size and severity have been growing on the central and southern California coastal landscape over the past several decades. Landsat satellite data was analyzed for the 20 largest fires on the Central California coast since 1984 to determine the relationships between climate/weather conditions at the time of ignition and the size of high burn severity (HBS) areas. The study also examined the relationship between area burned and landscape patterns of HBS coverage, including patch size, edge complexity, perimeter-to-area ratio, and aggregation metrics. Results showed that climate conditions at the time of ignitions have been significant controllers of the total area of HBS and the complexity of HBS patches on the fire landscape. As maximum air temperatures for the month of ignition approached 40^o C, the percentage of HBS to total area burned frequently exceeded 20%. The percentage of HBS to total area burned also exceed 20% when the precipitation total recorded during the previous 12 months was less than 25% of the annual average precipitation. Landscape analysis results showed that, as the total area burned in fires on the Central California coast grows, the edge lengths and areas of HBS patches also grows at a rapid rate. At the same time, the perimeter-to-area ratio of HBS patches decreases gradually and the HBS patches become more aggregated as total burned area grows.     

Interpreting and using outputs from the Canadian Forest Fire Danger Rating System in research applications

Understanding and being able to predict forest fire occurrence, fire growth and fire intensity are important aspects of forest fire management. In Canada fire management agencies use the Canadian Forest Fire Danger Rating System (CFFDRS) to help predict these elements of forest fire activity. In this paper a review of the CFFDRS is presented with the main focus on understanding and interpreting Canadian Fire Weather Index (FWI) System outputs. The need to interpret the outputs of the FWI System with consideration to regional differences is emphasized and examples are shown of how the relationship between actual fuel moisture and the FWI System’s moisture codes vary from region to region. Examples are then shown of the relationship between fuel moisture and fire occurrence for both human- and lightning-caused fire for regions with different forest composition. The relationship between rate of spread, fuel consumption and the relative fire behaviour indices of the FWI System for different forest types is also discussed. The outputs of the CFFDRS are used every day across Canada by fire managers in every district, regional and provincial fire management office. The purpose of this review is to provide modellers with an understanding of this system and how its outputs can be interpreted. It is hoped that this review will expose statistical modellers and other researchers to some of the models used currently in forest fire management and encourage further research and development of models useful for understanding and managing forest fire activity.

Conservation Threats Due to Human-Caused Increases in Fire Frequency in Mediterranean-Climate Ecosystems

Periodic wildfire is an important natural process in Mediterranean-climate ecosystems, but increasing fire recurrence threatens the fragile ecology of these regions. Because most fires are human-caused, we investigated how human population patterns affect fire frequency. Prior research in California suggests the relationship between population density and fire frequency is not linear. There are few human ignitions in areas with low population density, so fire frequency is low. As population density increases, human ignitions and fire frequency also increase, but beyond a density threshold, the relationship becomes negative as fuels become sparser and fire suppression resources are concentrated. We tested whether this hypothesis also applies to the other Mediterranean-climate ecosystems of the world. We used global satellite databases of population, fire activity, and land cover to evaluate the spatial relationship between humans and fire in the world's five Mediterranean-climate ecosystems. Both the mean and median population densities were consistently and substantially higher in areas with than without fire, but fire again peaked at intermediate population densities, which suggests that the spatial relationship is complex and nonlinear. Some land-cover types burned more frequently than expected, but no systematic differences were observed across the five regions. The consistent association between higher population densities and fire suggests that regardless of differences between land-cover types, natural fire regimes, or overall population, the presence of people in Mediterranean-climate regions strongly affects the frequency of fires; thus, population growth in areas now sparsely settled presents a conservation concern. Considering the sensitivity of plant species to repeated burning and the global conservation significance of Mediterranean-climate ecosystems, conservation planning needs to consider the human influence on fire frequency. Fine-scale spatial analysis of relationships between people and fire may help identify areas where increases in fire frequency will threaten ecologically valuable areas.     

Modeling mammal response to fire based on species’ traits

Fire has shaped ecological communities worldwide for millennia, but impacts of fire on individual species are often poorly understood. We performed a meta-analysis to predict which traits, habitat, or study variables and fire characteristics affect how mammal species respond to fire. We modeled effect sizes of measures of population abundance or occupancy as a function of various combinations of these traits and variables with phylogenetic least squares regression. Nine of 115 modeled species (7.83%) returned statistically significant effect sizes, suggesting most mammals are resilient to fire. The top-ranked model predicted a negative impact of fire on species with lower reproductive rates, regardless of fire type (estimate = –0.68), a positive impact of burrowing in prescribed fires (estimate = 1.46) but not wildfires, and a positive impact of average fire return interval for wildfires (estimate = 0.93) but not prescribed fires. If a species’ International Union for Conservation of Nature Red List assessment includes fire as a known or possible threat, the species was predicted to respond negatively to wildfire relative to prescribed fire (estimate = –2.84). These findings provide evidence of experts’ abilities to predict whether fire is a threat to a mammal species and the ability of managers to meet the needs of fire-threatened species through prescribed fire. Where empirical data are lacking, our methods provide a basis for predicting mammal responses to fire and thus can guide conservation actions or interventions in species or communities.     

Assessing Wildfire Destruction Danger: a Decision Support System Incorporating Uncertainty

A composite index is proposed for fire destruction danger assessment. Wildfire incidence and fire severity (FS), in association with the values in threat and the sensitivity of these values to fire, are some of its constituent parameters. The index is computed by use of logic programming within a multi-criteria Decision Support System (DSS). It is applicable to either large or small areas and can be used for short and long-term prediction. The Decision Support System is also described along with the underlying reasoning assumptions. It incorporates mechanisms for the representation and handling of uncertainty and can reason with inexact or incomplete information. The building blocks of its architecture consist of hierarchically-structured rules, a scheme that offers a high degree of transparency. The system design provides a high degree of flexibility, and allows user-induced customisation. It can be used either as stand-alone or as a component of an integral software system, as it is a Fire and Forest Management Decision Support System, by the use of an appropriate interface.     

Weak climatic control of stand-scale fire history during the late holocene

Forest fire occurrence is affected by multiple controls that operate at local to regional scales. At the spatial scale of forest stands, regional climatic controls may be obscured by local controls (e.g., stochastic ignitions, topography, and fuel loads), but the long-term role of such local controls is poorly understood. We report here stand-scale (<100 ha) fire histories of the past 5000 years based on the analysis of sediment charcoal at two lakes 11 km apart in southeastern British Columbia. The two lakes are today located in similar subalpine forests, and they likely have experienced the same late-Holocene climatic changes because of their close proximity. We evaluated two independent properties of fire history: (1) fire-interval distribution, a measure of the overall incidence of fire, and (2) fire synchroneity, a measure of the co-occurrence of fire (here, assessed at centennial to millennial time scales due to the resolution of sediment records). Fire-interval distributions differed between the sites prior to, but not after, 2500 yr before present. When the entire 5000-yr period is considered, no statistical synchrony between fire-episode dates existed between the two sites at any temporal scale, but for the last 2500 yr marginal levels of synchrony occurred at centennial scales. Each individual fire record exhibited little coherency with regional climate changes. In contrast, variations in the composite record (average of both sites) matched variations in climate evidenced by late-Holocene glacial advances. This was probably due to the increased sample size and spatial extent represented by the composite record (up to 200 ha) plus increased regional climatic variability over the last several millennia, which may have partially overridden local, non-climatic controls. We conclude that (1) over past millennia, neighboring stands with similar modern conditions may have experienced different fire intervals and asynchronous patterns in fire episodes, likely because local controls outweighed the synchronizing effect of climate; (2) the influence of climate on fire occurrence is more strongly expressed when climatic variability is relatively great; and (3) multiple records from a region are essential if climate-fire relations are to be reliably described.     

Aggregation of positively charged polystyrene nanoplastics in soil–root systems

Environmental Chemistry Letters - The occurrence of nanoplastics in agricultural land is a potential threat to human health and food security, yet the fate of nanoplastics is soil–root...     

Evaluating the ecological benefits of wildfire by integrating fire and ecosystem simulation models

Fire managers are now realizing that wildfires can be beneficial because they can reduce hazardous fuels and restore fire-dominated ecosystems. A software tool that assesses potential beneficial and detrimental ecological effects from wildfire would be helpful to fire management. This paper presents a simulation platform called FLEAT (Fire and Landscape Ecology Assessment Tool) that integrates several existing landscape- and stand-level simulation models to compute an ecologically based measure that describes if a wildfire is moving the burning landscape towards or away from the historical range and variation of vegetation composition. FLEAT uses a fire effects model to simulate fire severity, which is then used to predict vegetation development for 1, 10, and 100 years into the future using a landscape simulation model. The landscape is then simulated for 5000 years using parameters derived from historical data to create an historical time series that is compared to the predicted landscape composition at year 1, 10, and 100 to compute a metric that describes their similarity to the simulated historical conditions. This tool is designed to be used in operational wildfire management using the LANDFIRE spatial database so that fire managers can decide how aggressively to suppress wildfires. Validation of fire severity predictions using field data from six wildfires revealed that while accuracy is moderate (30-60%), it is mostly dictated by the quality of GIS layers input to FLEAT. Predicted 1-year landscape compositions were only 8% accurate but this was because the LANDFIRE mapped pre-fire composition accuracy was low (21%). This platform can be integrated into current readily available software products to produce an operational tool for balancing benefits of wildfire with potential dangers.     

Fire Management,Managed Relocation,and Land Conservation Options for Long‐Lived Obligate Seeding Plants under Global Changes in Climate,Urbanization, and Fire Regime

Most species face multiple anthropogenic disruptions. Few studies have quantified the cumulative influence of multiple threats on species of conservation concern, and far fewer have quantified the potential relative value of multiple conservation interventions in light of these threats. We linked spatial distribution and population viability models to explore conservation interventions under projected climate change, urbanization, and changes in fire regime on a long‐lived obligate seeding plant species sensitive to high fire frequencies, a dominant plant functional type in many fire‐prone ecosystems, including the biodiversity hotspots of Mediterranean‐type ecosystems. First, we investigated the relative risk of population decline for plant populations in landscapes with and without land protection under an existing habitat conservation plan. Second, we modeled the effectiveness of relocating both seedlings and seeds from a large patch with predicted declines in habitat area to 2 unoccupied recipient patches with increasing habitat area under 2 projected climate change scenarios. Finally, we modeled 8 fire return intervals (FRIs) approximating the outcomes of different management strategies that effectively control fire frequency. Invariably, long‐lived obligate seeding populations remained viable only when FRIs were maintained at or above a minimum level. Land conservation and seedling relocation efforts lessened the impact of climate change and land‐use change on obligate seeding populations to differing degrees depending on the climate change scenario, but neither of these efforts was as generally effective as frequent translocation of seeds. While none of the modeled strategies fully compensated for the effects of land‐use and climate change, an integrative approach managing multiple threats may diminish population declines for species in complex landscapes. Conservation plans designed to mitigate the impacts of a single threat are likely to fail if additional threats are ignored. Manejo de Incendios, Reubicación Administrada y Opciones de Conservación de Suelo para Plantas de Vida Larga con Sembrado Obligado bajo los Cambios Globales en el Clima, la Urbanización y el Régimen de Incendios     

Understanding Interaction Effects of Climate Change and Fire Management on Bird Distributions through Combined Process and Habitat Models

Abstract: Avian conservation efforts must account for changes in vegetation composition and structure associated with climate change. We modeled vegetation change and the probability of occurrence of birds to project changes in winter bird distributions associated with climate change and fire management in the northern Chihuahuan Desert (southwestern U.S.A.). We simulated vegetation change in a process‐based model (Landscape and Fire Simulator) in which anticipated climate change was associated with doubling of current atmospheric carbon dioxide over the next 50 years. We estimated the relative probability of bird occurrence on the basis of statistical models derived from field observations of birds and data on vegetation type, topography, and roads. We selected 3 focal species, Scaled Quail (Callipepla squamata), Loggerhead Shrike (Lanius ludovicianus), and Rock Wren (Salpinctes obsoletus), that had a range of probabilities of occurrence for our study area. Our simulations projected increases in relative probability of bird occurrence in shrubland and decreases in grassland and Yucca spp. and ocotillo (Fouquieria splendens) vegetation. Generally, the relative probability of occurrence of all 3 species was highest in shrubland because leaf‐area index values were lower in shrubland. This high probability of occurrence likely is related to the species’ use of open vegetation for foraging. Fire suppression had little effect on projected vegetation composition because as climate changed there was less fuel and burned area. Our results show that if future water limits on plant type are considered, models that incorporate spatial data may suggest how and where different species of birds may respond to vegetation changes.