Incidence Of Wildfires Research Articles

A review of applications of remote sensing for drought studies in the Andes region

Study regionAs climate change intensifies, drought events are becoming more frequent and intense in the Andes region. Remote sensing offers new opportunities to characterize and monitor drought and its impacts for the benefit of disaster risk reduction, water governance, and climate change adaptation. However, it remains to be seen the extent to which remotely-sensed data has been integrated into the Andes regional drought literature. Study focusThrough a semi-systematic literature review, this study evaluates the existing literature in the Andes on the topic, assesses how, where, and the extent to which remote sensing is being deployed in drought studies in the region, and points to key gaps in our regional understanding of this topic of high societal and environmental concern. New hydrological insight for the regionRemote sensing applications in drought studies remain limited in the Andes but have grown substantially since 2020. The reviewed studies concentrate on Chile and offer new insight into the impact of drought on vegetation, water bodies, the cryosphere, and wildfire incidence. Human activity, through agricultural decision-making and other socioeconomic dimensions, plays a role in propagating or deepening drought in the region. This literature offers new insight into the interplay between different drought types and the role of remote sensing in social-environmental research, although further research across geographies and drought types in the Andes region is urgently needed.

Impact of wildfires on ecosystems and bird communities on designated areas of blanket bog and heath

ABSTRACT Capsule Wildfires on moorland reduced bird species richness and abundance, along with the seedbank and abundance of ground beetles and spiders. The effects were detectable three years after the fires took place. Aims To describe the effects of wildfires during the breeding season on moorland birds, their habitat and ecosystem characteristics, by comparing burnt with adjacent unburnt areas in six designated sites up to three years post-fire. Methods Point counts of birds, vegetation height and cover, soil seedbank and pitfall traps were used to examine differences between areas burnt by wildfires and unburnt areas. Results One year after wildfire, bird species richness was 50% lower and abundance 32% lower on burnt compared to adjacent unburnt areas. Wildfire burnt areas had 80% of the species richness and 94% of the abundance of unburnt areas three years after wildfire. Bird species associated with upland moorland, including European Stonechat Saxicola rubicola, Common Redshank Tringa tetanus and Hen Harrier Circus cyaneus, were recorded exclusively in unburnt areas. Wildfire burnt areas were characterized by habitat generalist species and community composition in burnt areas remained distinct from unburnt areas three years after burning. Heather Calluna vulgaris and Erica spp. regenerated to 59% of the height of heather on unburnt areas three years after burning. Compared to unburnt areas, burnt areas had a reduced seedbank (22% lower), and reduced ground beetle (15% lower) and spider abundance (31% lower). Conclusion The immediate impacts of wildfire may differ from managed fires due to their indiscriminate character, where they occur, extent, duration and temperature. Wildfire incidence is likely to increase in cool temperate areas due to climate change and likely to undermine the characteristic features of designated areas. Research should focus on preventing wildfires, reducing their impact and accelerating the recovery of burnt moorland.

Climate predicts wildland fire extent across China

Wildland fire extent varies seasonally and interannually in response to climatic and landscape-level drivers, yet predicting wildfires remains a challenge. Existing linear models that characterize climate and wildland fire relationships fail to account for non-stationary and non-linear associations, thus limiting prediction accuracy. To account for non-stationary and non-linear effects, we use time-series climate and wildfire extent data from across China with unit root methods, thus providing an approach for improved wildfire prediction. Results from this approach suggest that wildland area burned is sensitive to vapor pressure deficit (VPD) and maximum temperature changes over short and long-term scenarios. Moreover, repeated fires constrain system variability resulting in non-stationarity responses. We conclude that an autoregressive distributed lag (ARDL) approach to dynamic simulation models better elucidates interactions between climate and wildfire compared to more commonly used linear models. We suggest that this approach will provide insights into a better understanding of complex ecological relationships and represents a significant step toward the development of guidance for regional planners hoping to address climate-driven increases in wildfire incidence and impacts.

Broadleaf tree phenology and springtime wildfire occurrence in boreal Canada.

Although broadleaf tree species of the boreal biome have a lower flammability compared to conifers, there is a period following snow melt and prior to leaf flush (i.e., greenup), termed the "spring window" by fire managers, when these forests are relatively conducive to wildfire ignition and spread. The goal of this study was to characterize the duration, timing, and fire proneness of the spring window across boreal Canada and assess the link between these phenologicalvariables and the incidence of springtime wildfires. We used remotely sensed snow cover and greenup data to identify the annual spring window for five boreal ecozones from 2001 to 2021 and then compared seasonality of wildfire starts (by cause) and fire-conducive weather in relation to this window, averaged over the 21-year period. We conducted a path analysis to concomitantly evaluate the influence of the spring window's duration, the timing of greenup, and fire-conducive weather on the annual number and the seasonality of spring wildfires. Results show that the characteristics of spring windows vary substantially from year to year and among geographic zones, with the interior west of Canada having the longest and most fire-conducive spread window and, accordingly, the greatest springtime wildfire activity. We also provide support for the belief that springtime weather generally promotes wind-driven, rather than drought-driven wildfires. The path analyses show idiosyncratic behavior among ecozones, but, in general, the seasonality of the wildfire season is mainly driven by the timing of the greenup, whereas the number of spring wildfires mostly responds to the duration of the spring window and the frequency of fire-conducive weather. The results of this study allows us to better understand and anticipate the biome-wide changes projected for the northern forests of North America.

Assessing public preferences for a wildfire mitigation policy in Crete, Greece

The increased frequency and severity of wildfires in the Mediterranean region generates significant damages in ecosystems and landscapes while harming human populations. Institutional complexities, along with socioeconomic and demographic changes encouraging development into the wildland-urban interface, rural abandonment, and focus on fire suppression, are increasing the vulnerability and flammability of Mediterranean ecosystems. Developing effective strategies for managing wildfire incidence and its aftermath requires understanding of the public preferences for wildfire policy characteristics. Here we elicit public preferences for wildfire mitigation policies employing a stated choice experiment applied in Crete, Greece. A region with typical Mediterranean landscape experiencing significant development and rural-to-urban migration that disrupts existing fire regimes. We estimate conditional logit, mixed logit and latent class models to study the general public's preferences and willingness to pay for limiting wildfire frequency and agricultural land burnt, maintaining landscape features, and managing post-wildfire recovery. Results of our study show that measures to manage post-wildfire damage are consistently valued as the most positive amongst the sampled respondents, achieving values that range between €25.92 in conditional logit model to €46 in one of the latent classes identified. Improving the landscape quality follows in importance, although it shows more heterogeneity in the responses. The latent class approach allowed to identify that those associated with either the agricultural or the tourism sector of the sampled individuals, displayed significantly different preferences for the proposed attributes. Overall, our findings indicate that there is a strong preference amongst the general public to shift current policies based on suppression towards more integrated approaches dealing both with prevention and post-fire management. The outcomes of this study serve to guide decision makers on targeted management plans based on their audience.

Measuring the Distance between Trees and Power Lines under Wind Loads to Assess the Heightened Potential Risk of Wildfire

The incidence of wildfires caused by tree contact with high-voltage power lines has become an increasingly pressing issue in the United States. To prevent such incidents, local safety councils have established minimum clearance regulations between trees and power lines. While most studies have focused on the tree encroachment around power lines during normal weather conditions, recent catastrophic fires have been caused by strong winds. To address this gap in knowledge, we investigated the critical wind speed that heightens the risk of wildfires by calculating the distance between trees and wires. To conduct this study, we used airborne LiDAR data collected from Sonoma County in northern California and analyzed the behavior of a sample tree having a height of 19.2 m under wind loads. Our analysis showed that the main factor determining tree deflection is the ratio of the tree height to the trunk diameter. We also found that, although the probability of fire ignition is typically low under normal conditions, it is likely to increase at a wind speed of approximately 40.3 m/s. In conclusion, this research demonstrates the utility of point cloud data in identifying potentially dangerous trees and reducing the risk of fires.

Estimating Climate-Sensitive Wildfire Risk and Tree Mortality Models for Use in Broad-Scale U.S. Forest Carbon Projections

This study utilizes forest inventory and climate attributes as the basis for estimating models of wildfire risk and associated biomass loss (tree mortality) and then demonstrates how they can be applied in calculating CO2 emissions related to the incidence of wildfires from U.S. forests. First, we use the full set of over 150,000 FIA plots of national forest inventory and climatic parameters to estimate models of the annual probability of wildfire occurrence and loss of live tree biomass. Then, maps of the spatial allocation of both the model-derived probability of wildfire occurrences and tree mortality are presented at the national level. The probability of wildfire occurrences and tree mortality were defined by a complex non-linear association of climatic conditions and forest ownerships, available aboveground biomass, and the age of the stand. Then, we provide an example of how these models can estimate potential CO2 emissions from wildfires by using FIA inventory data. We estimated 6.10, 16.65, 22.75, and 31.01 million metric tons of annual CO2 emissions with low, medium, high, and catastrophic combustion rates, respectively, from forests due to wildfire in the continental U.S. The wildfire risk and biomass loss due to tree mortality maps can be used by landowners, managers, public agencies, and other stakeholders in identifying high-risk wildfire zones and the potential CO2 emissions. These equations can also help estimate fire risk and associated CO2 emissions for future climate conditions to provide insight into climate change-related wildfire occurrences.

Detecting patterns of post-fire pine regeneration in a Madrean Sky Island with field surveys and remote sensing

The American Southwest is experiencing drastic increases in aridity and wildfire incidence, triggering conversion of some frequent surface forests to non-forest. Extensive research has focused on these dynamics in regional ponderosa pine forests, but we know much less about Madrean pine-oak forests, which are broadly distributed from the Sierra Madre in Mexico to the Sky Island mountain ranges in the U.S. Increased fire incidence and drought in these forests are limiting pine regeneration and driving conversion of biodiverse forests to oak shrublands. We investigated regeneration patterns in Pinus engelmannii and P. leiophylla during severe drought 10 years after the Horseshoe Two Megafire in the Chiricahua Mountains, Arizona—a follow-up to an assessment five years post-fire. In long-term plots, we examined changes in pine seedling and resprout recruitment. Past research demonstrated that topography and fire severity influenced pine recruitment across environmental gradients. We investigated here whether Landsat-8 normalized difference vegetation index (NDVI) and evapotranspiration estimated by the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) added explanatory value to our understanding of these patterns. Conversion of Madrean pine-oak forest to oak shrublands continued 6–10 years post-fire. A dense, low oak canopy continued to coalesce in sites subject to severe fire. The importance of resprouts in P. leiophylla regeneration accelerated because these plants outgrew competing oak resprouts. Topography and fire severity (dNBR) were important predictors of 2021 patterns of pine recruitment. NDVI added explanatory value to these models, suggesting its potential in tracking forest dynamics. Evapotranspiration did not add value, likely because ECOSTRESS' larger pixel sizes and moving pixel locations created excessive subpixel heterogeneity in this highly dissected landscape. These models suggest that P. engelmannii is more drought sensitive, was more negatively affected by drought and fire, and is more at risk to shifts in climate and wildfires than P. leiophylla.

Exploring the influence of the Keetch–Byram Drought Index and McArthur’s Drought Factor on wildfire incidence in Victoria, Australia

Background Wildfires are thought to become more prevalent during periods of extended dry weather. This issue is examined using two dryness metrics commonly applied in Australian fire management agencies. Aims This paper investigated links between wildfire incidence and the Keetch–Byram Drought Index (KBDI) and McArthur’s Drought Factor (DF) across the state of Victoria, Australia. Methods Weather records and data from 41 418 wildfires that occurred across the State over a 17-year period were compiled to examine the distributions of KBDI and DF on days with fires smaller and larger than 5 ha in area and all days, using kernel density plots. Key results Days with fires, particularly days with fires that escaped initial attack, have higher DFs and KBDIs compared with all days. These differences vary between regions and are greatest in areas with moist climates. Conclusions and implications An appreciation of dryness conditions using tools such as KBDI and DF is useful for understanding fire potential, particularly in areas that experience higher and more regular rainfall.

The threatened Gouldian finch preferentially forages in prescribed burnt savannas

Background The granivorous finches of Australia’s tropical savannas heavily rely on a sequence of perennial and annual grass seed production to feed throughout the year. An increase in late dry season wildfires has been suggested to detrimentally effect seed production sequence and has been attributed to poor physiological condition and a reduction in fitness of granivorous finches. Early dry season prescribed burning is an asset protection management strategy often implemented to reduce the incidence of late dry season wildfire, but has also been shown to improve the abundance and nutritional quality of grass seed Aims To assess whether the Gouldian finch (Chloebia gouldiae) preferentially used areas that were subject to early dry season prescribed burning over areas that were not burnt. Methods The creation of a landscape mosaic across the landscape with varying fire histories. Then the assessment of individual finch movement and site utilisation using VHF-radio telemetry transmitters, detected by an array of static receivers deployed across the landscape. Key results Finches significantly preferred to forage in areas burnt in the early season every 2–3 years. Conclusions The study demonstrates that early dry season prescribed burning creates preferred foraging habitat patches for Gouldian finches within savanna fire mosaics.

Risk Factors and Prediction of the Probability of Wildfire Occurrence in the China–Mongolia–Russia Cross-Border Area

Wildfire is essential in altering land ecosystems’ structures, processes, and functions. As a critical disturbance in the China–Mongolia–Russia cross-border area, it is vital to understand the potential drivers of wildfires and predict where wildfires are more likely to occur. This study assessed factors affecting wildfire using the Random Forest (RF) model. No single factor played a decisive role in the incidence of wildfires. However, the climatic variables were most critical, dominating the occurrence of wildfires. The probability of wildfire occurrence was simulated and predicted using the Adaptive Network-based Fuzzy Inference System (ANFIS). The particle swarm optimization (PSO) model and genetic algorithm (GA) were used to optimize the ANFIS model. The hybrid ANFIS models performed better than single ANFIS for the training and validation datasets. The hybrid ANFIS models, such as PSO-ANFIS and GA-ANFIS, overcome the over-fitting problem of the single ANFIS model at the learning stage of the wildfire pattern. The high classification accuracy and good model performance suggest that PSO-ANFIS can be used to predict the probability of wildfire occurrence. The probability map illustrates that high-risk areas are mainly distributed in the northeast part of the study area, especially the grassland and forest area of Dornod Province of Mongolia, Buryatia, and Chita state of Russia, and the northeast part of Inner Mongolia, China. The findings can be used as reliable estimates of the relative likelihood of wildfire hazards for wildfire management in the region covered or vicinity.

Family forest owner perceptions of wildfire and invasive pest risk: The role of interpersonally-produced risks

Societal risks associated with natural hazards are largely determined by human decision-making and risk mitigation behaviors. While much is known about individual risk perception, there is a gap in understanding interpersonal risk production (IPR), defined as the decision to prepare for an environmental threat/hazard which influences the risk faced by others. This study considers IPR for two forest-based hazards: wildfires and invasive insects. We surveyed private landowners in Colorado and Massachusetts, two states with high incidence of wildfire, and invasive insects, respectively. Results suggest that the threat of both wildfire and invasive species hazards may be less relevant to private forest owners and thus not conducive to promoting present action. Land managers and policymakers can better leverage efficacy beliefs to encourage risk reduction behaviors if they can communicate the benefit of promoting cross-boundary cooperation and inter-personally produced risks when confronting forest hazards.

Burn Severity Drivers in Italian Large Wildfires

The increase of wildfire incidence in highly populated areas significantly enhances the risk for ecosystems and human lives, activities and infrastructures. In central and southern Italy, recent decades’ fire records indicate that 2007 and 2017 were extreme years in terms of the number of fires and total burned area. Among them, we selected large fire events and explored their features and drivers of burn severity. We used a standardized extraction procedure to identify large wildfires (>100 ha) from the MODIS burned areas database and Landsat multi-spectral images. We mapped burn severity with the Relative Difference Normalized Burn Ratio index and explored the main drivers of severity using topographic, land-cover and anthropogenic predictors. We selected 113 wildfires for a collective total burned area of over 100,000 ha. Large fires were more frequent in the southern than in the central and northern regions, especially in July and August. The average fire size was about 900 ha and occurred mainly in shrublands (30.4%) and broadleaf forests (19.5%). With a random forest model, we observed that the highest severity occurred in conifer plantations and shrublands, in highly populated areas and at lower elevations. Burn severity models, at the landscape or regional scales, can be very useful tools for pre- and post-fire forest management planning.

Where There's Smoke, There's Fuel: Dynamic Vegetation Data Improve Predictions of Wildfire Hazard in the Great Basin

Wildfires are a growing management concern in western US rangelands, where invasive annual grasses have altered fire regimes and contributed to an increased incidence of catastrophic large wildfires. Fire activity in arid, nonforested ecosystems is thought to be largely controlled by interannual variation in fuel amount, which in turn is controlled by antecedent weather. Thus, long-range forecasting of fire activity in rangelands should be feasible given annual estimates of fuel quantity. Using a 32-yr time series of spatial data, we employed machine learning algorithms to predict the relative probability of large (> 405 ha) wildfire in the Great Basin based on fine-scale annual and 16-d estimates of cover and production of vegetation functional groups, weather, and multitemporal scale drought indices. We evaluated the predictive utility of these models with a leave-1-yr-out cross-validation, building spatial hindcasts of fire probability for each year that we compared against actual footprints of large wildfires. Herbaceous aboveground biomass production, bare ground cover, and long-term drought indices were the most important predictors of burning. Across 32 fire seasons, 88% of the area burned in large wildfires coincided with the upper 3 deciles of predicted fire probabilities. At the scale of the Great Basin, several metrics of fire activity were moderately to strongly correlated with average fire probability, including total area burned in large wildfires, number of large wildfires, and maximum fire size. Our findings show that recent years of exceptional fire activity in the Great Basin were predictable based on antecedent weather-driven growth of fine fuels and reveal a significant increasing trend in fire probability over the past 3 decades driven by widespread changes in fine fuel characteristics.

Wildfire Incidence throughout the Brazilian Pantanal Is Driven by Local Climate Rather Than Bovine Stocking Density

The Pantanal is the world’s largest and most biodiverse continental sheet-flow wetland. Recently, vast tracts of the Pantanal have succumbed to the occurrence of fires, raising serious concerns over the future integrity of the biodiversity and ecosystem services of this biome, including revenues from ecotourism. These wildfires degrade the baseline of natural ecosystems and the ecotourism economy across the region. Local residents (“Pantaneiros”) anecdotally state that extensive cattle herbivory can solve the contemporary flammability problem of the Pantanal by controlling vegetation biomass, thereby preventing or reducing both fuel loads and fires across the region. Here, we examine the covariation between the presence and density of cattle and the incidence of fires across the Brazilian Pantanal. Variables assessed included bovine cattle density, SPI (Standardized Precipitation Index), GPP (Gross Primary Productivity)/biomass estimate, and fire foci along a 19-year time series (2001 to 2019). Our findings show that fire foci across the Pantanal biome are related to climatic variables, such as lower annual precipitation and higher annual drought indices (SPI) rather than to cattle stocking rates. Therefore, the notion of “cattle firefighting”, a popular concept often discussed in some academic circles, cannot be validated because cattle numbers are unrelated to aboveground phytomass. Gross primary productivity further invalidated the “cattle herbivory” hypothesis because GPP was found to be strongly correlated with cattle density but not with the spatial distribution of fires. Fires throughout the Pantanal are currently aggravated by the presence of livestock and result from a combination of extreme weather events and outdated agricultural practices.

Holocene fire history in southwestern China linked to climate change and human activities

Global warming and human activities have significantly increased the wildfire risk in highly populated subtropical East Asia over recent decades; however, the factors driving fire occurrence on multiple timescales remain unclear. We present and analyze an observational dataset of fire for the Yunnan Plateau in southwestern China for the past 20 years, together with a Holocene fire history documented by four sedimentary black carbon records from four lakes on the Yunnan Plateau: lakes Dian, Xingyun, Qilu, and Yilong. Our aims were to explore the linkage between wildfires and natural and anthropogenic variables driving wildfire occurrence on multiple timescales. The results show that on a short timescale, more wildfires occurred in drier seasons, and on a longer timescale, more wildfires occurred during 6–2.8 cal kyr BP, when humidity decreased. In contrast, there was a moderate wildfire incidence during the relatively humid interval from 11.7 to 6 cal kyr BP. These observations indicate that fire activity is controlled by the humidity, against the background of the abundance of biofuel. The lowest degree of biomass burning occurred after ∼2.8 cal kyr BP and was linked to an anthropogenic reduction of biomass availability, despite an increase in drought. This suggests the importance of active fire management and prescribed clearance measures, especially given projections of continued drought and increased vegetation cover.

Climate-Driven Changes in High-Intensity Wildfire on Orbital Timescales in Eurasia since 320 ka

Abstract Wildfire is an integral part of the Earth’s climate system and plays an important role in shaping terrestrial ecosystems and biodiversity, atmospheric chemistry, regional climate, and the carbon cycle in the Earth’s history. However, the lack of high-resolution records of long wildfires limits our understanding of the natural variability, long-term trends of wildfire activity, and the reasons behind the changes in wildfire on orbital timescales. Here, a 320 ka long high-resolution wildfire record from the subarctic North Pacific is reconstructed with black carbon (BC), including its two subtypes char and soot. A 7-day-long back trajectory simulation analysis reveals the higher frequency of trajectories comes from Siberia. Our data show that continuous incidence of wildfire on a continental scale over the last 320 ka was higher during glacial periods than during the interglacial periods. The increase in wildfire frequency during glacial periods is ascribed to less precipitation. Contrasting patterns of wildfire incidence between marine isotope stages 2 and 6 may be ascribed to different fuel availability, which is related to contrasting configurations of the Northern Hemisphere ice sheet between glacial periods. A significant periodicity of 23 ka of our wildfire record suggests the precession of the Earth’s orbit pace wildfire development. The tight coupling of intensified wildfire and enhanced nutrient utilization efficiency suggests a nontrivial role of fire in the climate system.

Evaluating the effect of prescribed burning on the reduction of wildfire extent in Portugal

Prescribed burning (PB) is increasingly recognised as a viable, cost-effective technique for reducing wildfire risk. Yet, quantification of the effect of PB on the reduction of wildfire extent in southern Europe is non-existent. We used 35 years of fire mapping data in Portugal to analyse wildfire regime metrics in nine landscapes before (1985–2004) and during (2005–2020), the period when systematic use of PB to reduce fuel load began. We employed robust linear mixed models and generalized linear mixed models to examine the role of annual wildfire extent drivers at landscape scales and quantified the effect of PB on the reduction of subsequent wildfire extent, i.e., leverage. We found evidence of larger wildfires during the PB era, suggesting that other influences are counteracting its putative effect. The most important variables explaining wildfire extent were fire weather and ignition density, with positive effect, and past wildfire and PB extent, with negative effect, corresponding to leverage. We obtained a total past fire (PB and wildfire) leverage of 0.28, i.e., approximately 4 ha of past fire decrease subsequent wildfire by 1 ha, increasing to 0.84 if only landscapes with high wildfire incidence are considered. The analyses failed to unequivocally identify a direct leverage effect of PB but a 1:5 return-for-effort is reasonable as a conservative estimate. Increasing the size of PB treatments and treatment effort in the landscape in combination with fire-modelling assisted planning would enhance PB leverage, making it more effective at reducing wildfire extent, rather than functioning only as a supplement to the effect of previous wildfires.

Environmental indicators combined with risk analysis to evaluate potential wildfire incidence on the Dadu Plateau in Taiwan

Wildfire is a common disaster in the world, and it has a considerable impact on the safety of residents and ecological disturbance. Periodic wildfires are an urgent problem to be solved. This research uses big data from relevant departments to extract environmental indicators that affect wildfires, including satellite images, meteorological observations, and field surveys and establishes a risk model for the Spatio-temporal distribution of wildfires based on risk analysis. Previous studies using Differenced Normalized Burn Ratio (dNBR) to assess fire severity and distinguish wildfire ruins did not deal with the impact of atmospheric humidity on dNBR values. In this study, an adjustable fire threshold was developed to enable dNBR to improve the accuracy of identifying wildfire locations. Regarding the temporal distribution of wildfire risks, environmental vulnerability cannot specifically reflect the frequency of actual wildfires. If the hazard degree is introduced to calculate the wildfire risk, the coefficient of determination can be increased from 0.49 to 0.79. The verification of the village boundary zone depicts that the risk analysis can effectively show the temporal and spatial distribution of wildfire hotspots. On this basis, a village-level wildfire disaster prevention strategy can be formulated.

Livestock Management for the Delivery of Ecosystem Services in Fire-Prone Shrublands of Atlantic Iberia

In the northwest of the Iberian Peninsula, characterized by its humid climate, large rural areas are being abandoned, mostly in less-favoured areas covered by heathlands, which present a low nutritive quality for livestock production. The high combustibility of these shrublands is driving a high wildfire incidence with negative environmental and economic effects. In this review, some aspects on wildfire occurrence and the potential of grazing livestock to reduce woody phytomass and fire risk in heathland-dominated areas whilst maintaining quality production and preserving biodiversity are summarized. Heathlands may be partially improved—converted to grassland—to better meet animals’ nutritional requirements while acting as ‘natural’ firebreaks. The specific grazing behaviour offers the opportunity to combine different domestic herbivores (mixed grazing) to achieve sustainable systems utilizing heterogeneous resources. Cattle, sheep, goats, and horses may have a role in the provision of different ecosystem services such as food production and biodiversity conservation. Genotype x environment interactions shape the ability of animals to cope with poor vegetation conditions, with smaller species and breeds performing better than larger animals. Goats and horses are indicated to arrest woody encroachment. Sustainable grazing systems are affordable in heathland–grassland mosaics by selecting appropriate livestock species and breeds for quality production, thus favouring rural economies and lowering fire risk.