The hidden variable: Impacts of human decision-making on prescribed fire outcomes.

Dead fuel moisture content (DFMC) is essential for assessing wildfire danger, fire behavior, and fuel consumption. Several process-based models have been proposed to estimate DFMC. Previous studies have employed process-based models to estimate DFMC, solely relying on meteorological data obtained from meteorological stations. Satellite data can offer higher spatial resolution compared to meteorological data, with the potential to enhance the process-based DFMC estimates. Within this content, we aimed to improve the DFMC estimates by consideration of geostationary meteorological satellite-derived key variable (relative humility, RH) into the Fuel Stick Moisture Model (FSMM). The RH was derived from Himawari-8 geostationary satellite data, and other variables required by FSMM were obtained from Global Forecast System (GFS). As comparison, an equilibrium moisture content (EMC) model, Simard, and random forest regression were also used for the DFMC estimates. DFMC field measurement from the southwest China validate the DFMC from these three models. Results show that the DFMC estimated from the FSMM and Himawari-8 derived RH reached to a reasonable accuracy (R 2 = 0.73, RMSE = 3.60%, MAE = 2.69%). The comparison between FSMM and the other two models also confirmed the superior performance of the process-based model. A wildfire case over this region also confirmed that the DFMC continuous decreasing trends until the fire outbreak, highlighting the applicability of our approach in contributing to fire risk assessment.

Background Dead fuel moisture content (DFMC) is crucial for quantifying fire danger, fire behaviour, fuel consumption, and smoke production. Several previous studies estimating DFMC employed robust process-based models. However, these models can involve extensive computational time to process long time-series data with multiple iterations, and are not always practical at larger spatial scales. Aims Our aim was to provide a more time-efficient method to run a previously established process-based model and apply it to Pinus yunnanensis forests in southwest China. Methods We first determined the minimum processing time the process-based model required to estimate DFMC with a range of initial DFMC values. Then a long time series process was divided into parallel tasks. Finally, we estimated 1-h DFMC (verified with field-based observations) at regional scales using minimum required meteorological time-series data. Key results The results show that the calibration time and validation time of the model-in-parallel are 1.3 and 0.3% of the original model, respectively. The model-in-parallel can be generalised on regional scales, and its estimated 1-h DFMC agreed well with field-based measurements. Conclusions Our findings indicate that our model-in-parallel is time-efficient and its application in regional areas is promising. Implications Our practical model-in-parallel may contribute to improving wildfire risk assessment.

A Technique for Quantifying Fire Behavior in Grassland Fire Ecology Studies

RESUMO A modelagem do comportamento do fogo consiste em uma importante tarefa que pode ser utilizada para atividades de prevenção e combate. Entretanto, com base em estudos anteriores, os modelos comumente utilizados em outros países não o estimam corretamente nos plantios de eucalipto híbrido no Brasil. Sendo assim, este estudo teve por objetivo construir novos modelos empíricos para estimar a velocidade de propagação, comprimento das chamas e consumo do material combustível para o fogo dentro da respectiva vegetação em questão. Para tal, 105 queimas laboratoriais foram realizadas em que as principais características meteorológicas e do material combustível que poderiam interferir no comportamento do fogo foram controladas e/ou medidas. Variáveis dependentes e independentes foram correlacionadas por meio da regressão multivariada. O modelo para a velocidade de propagação proposto baseou-se na velocidade do vento, densidade do leito e no teor de umidade do material combustível de 1h de timelag (r2 = 0,86); o modelo para o comprimento das chamas baseou-se na espessura do leito, no teor de umidade do material combustível de 1h de timelag e na velocidade do vento (r2 = 0,72); o modelo para o consumo do material combustível teve como variáveis independentes o teor de umidade do material combustível de 1h de timelag, a densidade do leito e a carga do material combustível de 1h de timelag (r2 = 0,80). Os modelos construídos serviram de base para o desenvolvimento do software “Eucalyptus Fire Safety System”.

Forest fine fuels are a crucial component of surface fuels and play a key role in igniting forest fires. However, despite nearly 20 years of long-term prescribed burning management on Zhaobi Mountain in Xinping County, Yunnan Province, China, there remains a lack of specific quantification regarding the effectiveness of fine fuel management in Pinus yunnanensis forests. In this study, 10 m × 10 m sample plots were established on Zhaobi Mountain following one year of growth after prescribed burning. The plots were placed in a prescribed burning (PB) area and an unburned control (UB) area. We utilized indicators such as forest stand characteristics, fine fuel physicochemical properties, and potential fire behavior parameters for evaluation. The results indicate that prescribed burning at one-year intervals significantly affects stand characteristics, particularly in metrics such as crown base height, diameter breast height, and fuel load (p < 0.05). However, the physical and chemical properties of fine fuels did not show significant differences. Notably, the mean range of spread (RS) of PB fuels downhill was 43.3% lower than that of UB fuels, and the mean flaming height (FH) was 35.2% lower. The fire line intensity was <750 kW/m, categorizing it as a low-intensity fire. These findings provide data on the composition of fine fuels and the variables of fire behavior affected by prescribed burning, demonstrating that low-intensity prescribed burns can regulate fine fuels in the understory and maintain a stable regional fire risk level.

Fuel age (time since last fire) is often used to approximate fire hazard and informs decisions on placement of shrubland management burns worldwide. However, uncertainty remains concerning the relative importance of fuel age and weather conditions as predictors of fire hazard and behaviour. Using data from 35 experimental burns across three types of shrublands in Western Australia, we evaluated importance of fuel age and fire weather on probability of fire propagation (hazard) and four metrics of fire behaviour (rate of spread, fireline intensity, residence time, surface temperature) under moderate to high fire danger weather conditions. We found significant support for a threshold effect of fuel age for fire propagation but limited evidence for an effect of fuel age or fire weather on rates of spread or fireline intensity, although surface heating and heating duration were significantly related to fuel age and shrubland type. Further analysis suggested that dead fuel mass and accumulation rate rather than live fuels were responsible for this relationship. Using BEHAVE, predicted spread rates and intensities were consistently lower than observed values, suggesting further refinement is needed in modelling shrubland fire behaviour. These data provide important insight into fire behaviour in globally significant, fire-adapted shrublands, informing fire management and relationships between fire frequency and fire intensity.

BackgroundPrescribed burning plays an important role in the management of many ecosystems and can also be used to mitigate landscape-scale fire risk. Safe and effective application of prescribed fire requires that managers have a robust understanding of potential fire behavior in order to decide on the appropriate tools and tactics for any burning operation. Shrubland ecosystems, including heaths and moors, are known to exhibit intense fire behavior under marginal burning conditions under which fire would not be expected to spread in other vegetation types. This makes developing fire behavior predictions for such systems important. Traditional managed burning is widely used as a tool in Calluna vulgaris (L.) Hull-dominated heath and moorland landscapes in northwest Europe, but in some regions, especially the United Kingdom, there is significant debate over fire use. Despite the controversy, there is general agreement on the need to (1) understand relationships between fuel structure and potential fire behavior, and (2) improve burning practice to optimize potential trade-offs between different ecosystem services. Our aim was to provide knowledge to improve management practice by developing models of potential fireline intensity and flame length. We conducted 27 burns in three developmental stages of Calluna with different stand structures and estimated fireline intensity, flame length, flame height, and flame angle. Flame properties were assessed using photographs and visual observation. We evaluated our models using a participatory research approach for which conservation and land managers submitted basic observations on fire behavior and fire weather for their burns.ResultsFireline intensity and flame height increased significantly across age-related Calluna phases. Regression modeling revealed that fireline intensity could be adequately estimated by a combination of fuel height and wind speed, with taller fuels and higher wind speeds related to more intense fires. Predictions were, however, improved by accounting for live fuel moisture content. Flame length and height were modeled as a function of fireline intensity using standard approaches, but adequately performing models for flame angle could not be established. Evaluation data provided by land managers was noisy, but their qualitative assessments of fire behavior and estimates of flame length were significantly correlated with predictions from our models.ConclusionsFire intensities and flame properties seen in northern Calluna heathlands are similar to those encountered in shrublands associated with climates and fuels more commonly perceived as representing high fire danger. The results demonstrated that our models perform tolerably well although there is substantial uncertainty in their predictions. The models were used to develop a fire behavior nomogram that can provide an indication of potential fireline intensity and flame length prior to commencing a burn.

Changes in fire behavior caused by fire exclusion and fuel build-up vary with topography in California montane forests, USA

Using custom fuel models developed for use with Rothermel's surface fire spread model, we predicted and compared fire behavior in lodgepole pine (Pinus contorta Dougl. var. latifolia Engelm.) stands with endemic, current epidemic, and postepidemic mountain pine beetle (Dendroctonus ponderosae Hopkins) populations using standardized sets of wind speeds and fuel moistures. We also compared our fire behavior results with those from standard fuel models. Results indicated that for surface fires both rates of fire spread and fireline intensities were higher in the current epidemic stands than in the endemic stands owing to increases in the amounts of fine surface fuels. In the postepidemic stands, rates of surface fire spread and fireline intensities were higher than in the endemic stands owing to decreased vegetative sheltering and its effect on mid-flame wind speed. Total heat release of surface fires, including postfrontal combustion, was also higher in the postepidemic stands owing to heavy accumulations of large diameter fuels. Crown fires were more likely to initiate in the postepidemic stands owing to greater fireline intensities and lower crown base heights. However, the critical rate of spread needed to sustain an active crown fire was higher in the postepidemic stands owing to decreased aerial fuel continuity. We suggest here that crown fire initiation in the current epidemic stands was also greater because of an abundance of dead aerial fuels; although this relationship is unclear.

Mid-term effects of a thin-only treatment on fuel complex, potential fire behaviour and severity and post-fire soil erosion protection in fast-growing pine plantations

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Bark beetles, fuels, fires and implications for forest management in the Intermountain West

QuestionsHow does potential fire behaviour differ in grass‐invaded non‐native forests vs open grasslands? How has land cover changed from 1950–2011 along two grassland/forest ecotones in Hawaii with repeated fires?LocationNon‐native forest with invasive grass understory and invasive grassland (Megathyrsus maximus) ecosystems on Oahu, Hawaii, USA.MethodsWe quantified fuel load and moisture in non‐native forest and grassland (Megathyrsus maximus) plots (n = 6) at Makua Military Reservation and Schofield Barracks, and used these field data to model potential fire behaviour using the BehavePlus fire modelling program. Actual rate and extent of land‐cover change were quantified for both areas from 1950–2011 with historical aerial imagery.ResultsLive and dead fuel moisture content and fine fuel loads did not differ between forests and grasslands. However, mean surface fuel height was 31% lower in forests (72 cm) than grasslands (105 cm; P < 0.02), which drove large differences in predicted fire behaviour. Rates of fire spread were 3–5 times higher in grasslands (5.0–36.3 m·min−1) than forests (0–10.5 m·min−1; P < 0.001), and flame lengths were 2–3 times higher in grasslands (2.8–10.0 m) than forests (0–4.3 m; P < 0.01). Between 1950 and 2011, invasive grassland cover increased at both Makua (320 ha) and Schofield (745 ha) at rates of 2.62 and 1.83 ha·yr−1, respectively, with more rapid rates of conversion before active fire management practices were implemented in the early 1990s.ConclusionsThese results support accepted paradigms for the tropics, and demonstrate that type conversion associated with non‐native grass invasion and subsequent fire has occurred on landscape scales in Hawaii. Once forests are converted to grassland there is a significant increase in fire intensity, which likely provides the positive feedback to continued grassland dominance in the absence of active fire management.

Dead fine fuel moisture content (FM) is one of the most important determinants of fire behavior. Fire scientists have attempted to effectively estimate FM for nearly a century, but we are still lacking broad scale evaluations of the different approaches for prediction. Here we tackle this problem by taking advantage or a recently compiled global fire behavior database (BONFIRE) gathering 1603 records of 1h (i.e., <6 mm diameter or thickness) dead fuel moisture content from measurements before experimental fires. We compared the results of models routinely used by different agencies worldwide, empirical models, semi-mechanistic models and also non-linear and machine learning approaches based on either temperature and relative humidity or vapor pressure deficit (VPD). A semi-mechanistic model based on VPD showed the best performance across all FM ranges and a historical model developed in Australia (MK5) was additionally recommended for low fuel moisture estimations. We also observed significant differences in FM dynamics between vegetation types with FM in grasslands more responsive to changes in atmospheric dryness than woody ecosystems. The addition of computational complexity through machine learning is not recommended since the gain in model fit is small relative to the increase in complexity. Future research efforts should concentrate on predictions at low FM (<10 %) as this is the range most significant for fire behavior and where the poorest model performance was observed. Model predictions are available from https://hcfm.shinyapps.io/shinyfmd/.

This state-of-knowledge review examines some of the underlying assumptions and limitations associated with the inter-relationships among four widely used descriptors of surface fire behaviour and post-fire impacts in wildland fire science and management, namely Byram's fireline intensity, flame length, stem-bark char height and crown scorch height. More specifically, the following topical areas are critically examined based on a comprehensive review of the pertinent literature: (i) estimating fireline intensity from flame length; (ii) substituting flame length for fireline intensity in Van Wagner's crown fire initiation model; (iii) the validity of linkages between the Rothermel surface fire behaviour and Van Wagner's crown scorch height models; (iv) estimating flame height from post-fire observations of stem-bark char height; and (v) estimating fireline intensity from post-fire observations of crown scorch height. There has been an overwhelming tendency within the wildland fire community to regard Byram's flame length–fireline intensity and Van Wagner's crown scorch height–fireline intensity models as universal in nature. However, research has subsequently shown that such linkages among fire behaviour and post-fire impact characteristics are in fact strongly influenced by fuelbed structure, thereby necessitating consideration of fuel complex specific-type models of such relationships.