Pyro-Ecophysiology: Shifting the Paradigm of Live Wildland Fuel Research

Plant hydraulics at the heart of plant, crops and ecosystem functions in the face of climate change

Plant hydraulics is crucial for assessing the plants' capacity to extract and transport water from the soil up to their aerial organs. Along with their capacity to exchange water between plant compartments and regulate evaporation, hydraulic properties determine plant water relations, water status and susceptibility to pathogen attacks. Consequently, any variation in the hydraulic characteristics of plants is likely to significantly impact various mechanisms and processes related to plant growth, survival and production, as well as the risk of biotic attacks and forest fire behaviour. However, the integration of hydraulic traits into disciplines such as plant pathology, entomology, fire ecology or agriculture can be significantly improved. This review examines how plant hydraulics can provide new insights into our understanding of these processes, including modelling processes of vegetation dynamics, illuminating numerous perspectives for assessing the consequences of climate change on forest and agronomic systems, and addressing unanswered questions across multiple areas of knowledge.

Integrating plant physiology into simulation of fire behavior and effects

Wildfires are a global crisis, but current fire models fail to capture vegetation response to changing climate. With drought and elevated temperature increasing the importance of vegetation dynamics to fire behavior, and the advent of next generation models capable of capturing increasingly complex physical processes, we provide a renewed focus on representation of woody vegetation in fire models. Currently, the most advanced representations of fire behavior and biophysical fire effects are found in distinct classes of fine-scale models and do not capture variation in live fuel (i.e. living plant) properties. We demonstrate that plant water and carbon dynamics, which influence combustion and heat transfer into the plant and often dictate plant survival, provide the mechanistic linkage between fire behavior and effects. Our conceptual framework linking remotely sensed estimates of plant water and carbon to fine-scale models of fire behavior and effects could be a critical first step toward improving the fidelity of the coarse scale models that are now relied upon for global fire forecasting. This process-based approach will be essential to capturing the influence of physiological responses to drought and warming on live fuel conditions, strengthening the science needed to guide fire managers in an uncertain future.

Plant hydraulic modelling of leaf and canopy fuel moisture content reveals increasing vulnerability of a Mediterranean forest to wildfires under extreme drought

Fuel moisture content (FMC) is a crucial driver of forest fires in many regions world-wide. Yet, the dynamics of FMC in forest canopies as well as their physiological and environmental determinants remain poorly understood, especially under extreme drought. We embedded a FMC module in the trait-based, plant-hydraulic SurEau-Ecos model to provide innovative process-based predictions of leaf live fuel moisture content (LFMC) and canopy fuel moisture content (CFMC) based on leaf water potential ( ψ Leaf ). SurEau-Ecos-FMC relies on pressure-volume (p-v) curves to simulate LFMC and vulnerability curves to cavitation to simulate foliage mortality. SurEau-Ecos-FMC accurately reproduced ψ Leaf and LFMC dynamics as well as the occurrence of foliage mortality in a Mediterranean Quercus ilex forest. Several traits related to water use (leaf area index, available soil water, and transpiration regulation), vulnerability to cavitation, and p-v curves (full turgor osmotic potential) had the greatest influence on LFMC and CFMC dynamics. As the climate gets drier, our results showed that drought-induced foliage mortality is expected to increase, thereby significantly decreasing CFMC. Our results represent an important advance in our capacity to understand and predict the sensitivity of forests to wildfires.

Estimation of moisture in live fuels in the mediterranean: Linear regressions and random forests

The live fuel moisture content is an important factor in estimating the risk of forest fires and their rate of spread. However, due to a lack of research, the FMC values in the Mediterranean region of Andalusia, Spain, must be obtained by sample collection. This study is therefore the first to provide tools for estimating the moisture content of the most widespread plant species in Andalusia. First, samples were collected to estimate the moisture content of the plants; these data were collected from May 2007 to the present. Each species has its own range of moistures that depend on the time of year and the physiological state in which they are found. Secondly, an extensive database was obtained for each day of sample collection from the nearest weather station with free access. The statistics are performed at 12 solar hours on the day of sample collection and 24 h before collection, and then at 7 days, 14 days, 1 month, 3 months and 6 months before the day of collection. Finally, this database was statistically analyzed in two ways: Multiple linear regressions and random forest for each species. The predictive capacity of random forest is superior (R² > 0.89) to that obtained in linear regression (R² < 0.86). The highest root mean square error obtained in the case of the random forest is 0.74479 while in the linear regressions it was 1.29184. Consequently, uncertainty regarding fire behavior in the case of forest fires is reduced.

Live Fuel Moisture Content Mapping in the Mediterranean Basin Using Random Forests and Combining MODIS Spectral and Thermal Data

Remotely sensed vegetation indices have been widely used to estimate live fuel moisture content (LFMC). However, marked differences in vegetation structure affect the relationship between field-measured LFMC and reflectance, which limits spatial extrapolation of these indices. To overcome this limitation, we explored the potential of random forests (RF) to estimate LFMC at the subcontinental scale in the Mediterranean basin wildland. We built RF models (LFMCRF) using a combination of MODIS spectral bands, vegetation indices, surface temperature, and the day of year as predictors. We used the Globe-LFMC and the Catalan LFMC monitoring program databases as ground-truth samples (10,374 samples). LFMCRF was calibrated with samples collected between 2000 and 2014 and validated with samples from 2015 to 2019, with overall root mean square errors (RMSE) of 19.9% and 16.4%, respectively, which were lower than current approaches based on radiative transfer models (RMSE ~74–78%). We used our approach to generate a public database with weekly LFMC maps across the Mediterranean basin.

Reimagine fire science for the anthropocene

Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the "firehose" of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.

Hydraulic segmentation does not protect stems from acute water loss during fire

The heat plume associated with fire has been hypothesized to cause sufficient water loss from trees to induce embolism and hydraulic failure. However, it is unclear whether the water transport path remains sufficiently intact during scorching or burning of foliage to sustain high water loss. We measured water uptake by branches of Magnolia grandiflora while exposing them to a range of fire intensities and examined factors influencing continued water uptake after fire. Burning caused a 22-fold mean increase in water uptake, with greatest rates of water loss observed at burn intensities that caused complete consumption of leaves. Such rapid uptake is possible only with steep gradients in water potential, which would likely result in substantial cavitation of xylem and loss of conductivity in intact stems. Water uptake continued after burning was complete and was greatest following burn intensities that killed leaves but did not consume them. This post-fire uptake was mostly driven by rehydration of the remaining tissues, rather than evaporation from the tissues. Our results indicate that the fire plume hypothesis can be expanded to include a wide range of burning conditions experienced by plants. High rates of water loss are sustained during burning, even when leaves are killed or completely consumed.

Prediction of regional wildfire activity in the probabilistic Bayesian framework of Firelihood

Modeling wildfire activity is crucial for informing science-based risk management and understanding the spatiotemporal dynamics of fire-prone ecosystems worldwide. Models help disentangle the relative influences of different factors, understand wildfire predictability, and provide insights into specific events. Here, we develop Firelihood, a two-component, Bayesian, hierarchically structured, probabilistic model of daily fire activity, which is modeled as the outcome of a marked point process: individual fires are the points (occurrence component), and fire sizes are the marks (size component). The space-time Poisson model for occurrence is adjusted to gridded fire counts using the integrated nested Laplace approximation (INLA) combined with the stochastic partial differential equation (SPDE) approach. The size model is based on piecewise-estimated Pareto and generalized Pareto distributions, adjusted with INLA. The Fire Weather Index (FWI) and forest area are the main explanatory variables. Temporal and spatial residuals are included to improve the consistency of the relationship between weather and fire occurrence. The posterior distribution of the Bayesian model provided 1,000 replications of fire activity that were compared with observations at various temporal and spatial scales in Mediterranean France. The number of fires larger than 1 ha across the region was coarsely reproduced at the daily scale, and was more accurately predicted on a weekly basis or longer. The regional weekly total number of larger fires (10-100 ha) was predicted as well, but the accuracy degraded with size, as the model uncertainty increased with event rareness. Local predictions of fire numbers or burned areas also required a longer aggregation period to maintain model accuracy. The estimation of fires larger than 1 ha was also consistent with observations during the extreme fire season of the 2003 unprecedented heat wave, but the model systematically underrepresented large fires and burned areas, which suggests that the FWI does not consistently rate the actual danger of large fire occurrence during heat waves. Firelihood enabled a novel analysis of the stochasticity underlying fire hazard, and offers a variety of applications, including fire hazard predictions for management and projections in the context of climate change.

Evaluation of microwave soil moisture data for monitoring live fuel moisture content (LFMC) over the coterminous United States

Live fuel moisture content (LFMC), which is the ratio of water in the fresh biomass to the dry biomass, is a key variable that affects wildfire behaviour. Previous studies have assessed soil moisture as a predictor of LFMC over small areas with limited data, but a comprehensive evaluation at sub-continental scale is still lacking, and the explanatory utility has not been evaluated under different aridity conditions. In this study, the utility was evaluated using microwave soil moisture data from the ESA ECV_SM product from 1979 to 2018 and LFMC data from over 1000 sites in the coterminous United States. A time-lagged robust linear regression model was adopted, and the results were compared with analysis from in situ soil moisture measurements at adjacent sites. The results suggested that at most sites the LFMC correlates best with soil moisture within 60 days prior to LFMC sampling, and that the correlation is lower in areas with complex terrain. LFMC can be estimated from soil moisture with a mean RMSE of around 20%. The correlation between LFMC and soil moisture is significant (p<0.01) in most regions, and is mostly stable in different years. The major fuel types with a high response to soil moisture include pine, redcedar, sagebrush, oak, manzanita, chamise, mesquite and juniper, depending on the region. The LFMC ~ soil moisture correlation varies with the aridity condition, and soil moisture has a higher explanatory utility on LFMC under dry conditions. An analysis using SMAP Level-4 product indicated that the surface and root-zone soil moisture perform similarly in LFMC estimation. This study suggests that microwave soil moisture data contain sufficient information on LFMC, and may serve as a reference for the development of more sophisticated LFMC estimation methods.

Short- and long-term effects of fire on stem hydraulics in Pinus ponderosa saplings

Understanding tree physiological responses to fire is needed to accurately model post-fire carbon processes and inform management decisions. Given trees can die immediately or at extended time periods after fire, we combined two experiments to assess the short- (one-day) and long-term (21-months) fire effects on Pinus ponderosa sapling water transport. Native percentage loss of conductivity (nPLC), vulnerability to cavitation and xylem anatomy were assessed in unburned and burned saplings at lethal and non-lethal fire intensities. Fire did not cause any impact on nPLC and xylem cell wall structure in either experiment. However, surviving saplings evaluated 21-months post-fire were more vulnerable to cavitation. Our anatomical analysis in the long-term experiment showed that new xylem growth adjacent to fire scars had irregular-shaped tracheids and many parenchyma cells. Given conduit cell wall deformation was not observed in the long-term experiment, we suggest that the irregularity of newly grown xylem cells nearby fire wounds may be responsible for decreasing resistance to embolism in burned plants. Our findings suggest that hydraulic failure is not the main short-term physiological driver of mortality for Pinus ponderosa saplings. However, the decrease in embolism resistance in fire-wounded saplings could contribute to sapling mortality in the years following fire.

Drought Increases Vulnerability of Pinus ponderosa Saplings to Fire-Induced Mortality

The combination of drought and fire can cause drastic changes in forest composition and structure. Given the predictions of more frequent and severe droughts and forecasted increases in fire size and intensity in the western United States, we assessed the impact of drought and different fire intensities on Pinus ponderosa saplings. In a controlled combustion laboratory, we exposed saplings to surface fires at two different fire intensity levels (quantified via fire radiative energy; units: MJ m−2). The recovery (photosynthesis and bud development) and mortality of saplings were monitored during the first month, and at 200- and 370-days post-fire. All the saplings subjected to high intensity surface fires (1.4 MJ m−2), regardless of the pre-fire water status, died. Seventy percent of pre-fire well-watered saplings recovered after exposure to low intensity surface fire (0.7 MJ m−2). All of the pre-fire drought-stressed saplings died, even at the lower fire intensity. Regardless of the fire intensity and water status, photosynthesis was significantly reduced in all saplings exposed to fire. At 370 days post-fire, burned well-watered saplings that recovered had similar photosynthesis rates as unburned plants. In addition, all plants that recovered or attempted to recover produced new foliage within 35 days following the fire treatments. Our results demonstrate that the pre-fire water status of saplings is an important driver of Pinus ponderosa sapling recovery and mortality after fire.

Linking Forest Flammability and Plant Vulnerability to Drought

Globally, fire regimes are being altered by changing climatic conditions. New fire regimes have the potential to drive species extinctions and cause ecosystem state changes, with a range of consequences for ecosystem services. Despite the co-occurrence of forest fires with drought, current approaches to modelling flammability largely overlook the large body of research into plant vulnerability to drought. Here, we outline the mechanisms through which plant responses to drought may affect forest flammability, specifically fuel moisture and the ratio of dead to live fuels. We present a framework for modelling live fuel moisture content (moisture content of foliage and twigs) from soil water content and plant traits, including rooting patterns and leaf traits such as the turgor loss point, osmotic potential, elasticity and leaf mass per area. We also present evidence that physiological drought stress may contribute to previously observed fuel moisture thresholds in south-eastern Australia. Of particular relevance is leaf cavitation and subsequent shedding, which transforms live fuels into dead fuels, which are drier, and thus easier to ignite. We suggest that capitalising on drought research to inform wildfire research presents a major opportunity to develop new insights into wildfires, and new predictive models of seasonal fuel dynamics.

Globe-LFMC, a global plant water status database for vegetation ecophysiology and wildfire applications

Globe-LFMC is an extensive global database of live fuel moisture content (LFMC) measured from 1,383 sampling sites in 11 countries: Argentina, Australia, China, France, Italy, Senegal, Spain, South Africa, Tunisia, United Kingdom and the United States of America. The database contains 161,717 individual records based on in situ destructive samples used to measure LFMC, representing the amount of water in plant leaves per unit of dry matter. The primary goal of the database is to calibrate and validate remote sensing algorithms used to predict LFMC. However, this database is also relevant for the calibration and validation of dynamic global vegetation models, eco-physiological models of plant water stress as well as understanding the physiological drivers of spatiotemporal variation in LFMC at local, regional and global scales. Globe-LFMC should be useful for studying LFMC trends in response to environmental change and LFMC influence on wildfire occurrence, wildfire behavior, and overall vegetation health.

Design Type(s)	database creation objective • cross validation objective • physiological process monitoring objective
Measurement Type(s)	moisture content trait
Technology Type(s)	digital curation
Factor Type(s)	geographic location • environmental feature
Sample Characteristic(s)	Earth (Planet) • United States of America • French Republic

Machine-accessible metadata file describing the reported data (ISA-Tab format)

The Survival of Pinus ponderosa Saplings Subjected to Increasing Levels of Fire Behavior and Impacts on Post-Fire Growth

Improved predictions of tree species mortality and growth metrics following fires are important to assess fire impacts on forest succession, and ultimately forest growth and yield. Recent studies have shown that North American conifers exhibit a ‘toxicological dose-response’ relationship between fire behavior and the resultant mortality or recovery of the trees. Prior studies have not been conclusive due to potential pseudo-replication in the experimental design and time-limited observations. We explored whether dose-response relationships are observed in ponderosa pine (Pinus ponderosa) saplings exposed to surface fires of increasing fire behavior (as quantified by Fire Radiative Energy—FRE). We confirmed equivalent dose-response relationships to the prior studies that were focused on other conifer species. The post-fire growth in the saplings that survived the fires decreased with increasing FRE dosages, while the percentage mortality in the sapling dosage groups increased with the amount of FRE applied. Furthermore, as with lodgepole pine (Pinus contorta), a low FRE dosage could be applied that did not yield mortality in any of the replicates (r = 10). These results suggest that land management agencies could use planned burns to reduce fire hazard while still maintaining a crop of young saplings. Incorporation of these results into earth-system models and growth and yield models could help reduce uncertainties associated with the impacts of fire on timber growth, forest resilience, carbon dynamics, and ecosystem economics.

Live Fuel Moisture Content: The ‘Pea Under the Mattress’ of Fire Spread Rate Modeling?

Currently, there is a dispute on whether live fuel moisture content (FMC) should be accounted for when predicting a real-world fire-spread rate (RoS). The laboratory and field data results are conflicting: laboratory trials show a significant effect of live FMC on RoS, which has not been convincingly detected in the field. It has been suggested that the lack of influence of live FMC on RoS might arise from differences in the ignition of dead and live fuels: flammability trials using live leaves subjected to high heat fluxes (80–140 kW m−2) show that ignition occurs before all of the moisture is vaporized. We analyze evidence from recent studies, and hypothesize that differences in the ignition mechanisms between dead and live fuels do not preclude the use of overall fine FMC for attaining acceptable RoS predictions. We refer to a simple theory that consists of two connected hypotheses to explain why the effect of live FMC on field fires RoS has remained elusive so far: H1, live tree foliage FMC remains fairly constant over the year; and H2, the seasonal variation of live shrubs’ FMC correlates with the average dead FMC. As a result, the effect of live FMC is not easily detected by statistical analysis.