Fighting fire with food: Assessing the flammability of crop plant species for building fire resilient agroforestry systems

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Given the negative impact of fires on the livelihoods of farmers, it is crucial to assess the flammability of crop species and find ways of mitigating risk of fire in agricultural lands. We quantify the flammability of 66 tropical species of fiber, food, and spice crops by assessing maximum temperature, burn time, and burned biomass and assessed key leaf traits from a subset of these species to look at the interaction of leaf area (LA) and leaf dry matter content (LDMC) with life form type. We found groundcover, shrubs, and vines to be generally less flammable than canopy and subcanopy plants. We also found LDMC to be a consistent and significant predictor of all three flammability measures regardless of plant life form. Our results equips farmers and policy makers with information for constructing more fire resilient agricultural landscapes and pursuing nature-based solutions to mitigate fire risk, such as by planting green firebreaks with fire retardant species. food forest green firebreaks leaf traits plant flammability Syntropics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Demand for agricultural products is expected to increase by an estimated 1.1% per year until 2050 due to drivers such as population growth, increases in per capita consumption, and diet changes (Alexandratos and Bruinsma 2012 ). Meanwhile, trends in global climate change are exacerbating drought frequency and posing a challenge to food security (Jones et al. 2020 ). Climate change can also elevate fire risk by increasing the number of days with fire risk and length of fire risk season, etc. (Moriondo et al. 2006 ). There has already been a global increase in incidences of wildlifes, with potentially devastating impacts on both natural and agricultural landscapes (Lozano et al. 2017 ). Wildlifes in 2003 burnt 1.12 million ha of public and private forests and agricultural lands in the state of Victoria, Australia (Tibbits and Whittaker 2007 ; Ribeiro et al. 2020 ), leading to loss of property, livestock and agricultural equipment amounting to 300 million AUD (Ashe et al. 2009 ). Even humid tropical forest regions, once thought of as “fire-proof”, are now subject to higher incidence of catastrophic fire events (Withey et al. 2018 ). These environmental challenges are compounded by ongoing conversion of forested land for farming and modern large-scale agricultural practices. Tropical forests play a key role in regulating regional climate processes and fire weather risk, and when cleared for agricultural land leads to a fourfold increase in wildfires (Trancoso et al. 2022 ). Additionally, the modern monocultures of single genetically homogeneous crops that tropical forests are typically cleared for use large quantities of fertilizer and pesticides (Malézieux et al. 2009 ). This results in a simplified agricultural landscape with reduced biodiversity that is vulnerable to disturbances like pest outbreaks, rainfall fluctuations and climate change, and as a consequence may shift into a new and less resilient type of landscape with subsequent loss of ecosystem services (Foley et al. 2005 ; Gordon et al. 2008 ). Monoculture farms and intensively cultivated timber plantations are especially vulnerable to disrupted hydrologic regimes and fire damage (Bowman et al. 2021 ; Giller et al. 2021 ), or even deliberately-lit fires in acts of arson (Strydom and Schutte 2005 ). Given the trends in agricultural intensification in the tropics, it is necessary to equip agricultural landowners with information and resources on mitigating fires to protect their livelihoods (Keys and McConnell 2005 ). Establishing agroforestry systems is an economically feasible means to maintain agricultural production and critical ecosystem services, and an adaptive strategy for farmers to mitigate fire risk in fire-prone areas (Lin 2007 ). Agroforestry involves the deliberate integration of woody vegetation (trees and/or shrubs) to establish multi-tiered crop rows and uses little to no herbicide inputs. Multi-tiered crop rows promote favorable microclimate conditions by influencing radiation flux, air temperature, and wind speed, all of which can help mitigate fire risk (Ewel 1999 ). Reduced herbicide inputs promote healthier microbial communities, improving carbon sequestration and cycling, thus helping manage fuel build-up (Andrade et al. 2020 ; Damianidis et al. 2021 ). Although the presence of trees and/or shrubs in agroforestry crop rows may generate microclimates resistant to high fire risk conditions, farms cultivating flammable crops may still be vulnerable to wildfires and arson. Agroforest farm managers as well as conventional farmers can implement various measures to optimize fire safety on their farms. One such measure is to incorporate “green firebreaks”, strips of low-flammability vegetation installed at strategic locations to suppress fires (Curran et al. 2017 ; Cui et al. 2019 ). Green firebreaks are garnering increased attention as a nature-based solution and complementary strategy for managing fire risk in urban-wildland interfaces and agricultural landscapes (Curran et al. 2017 ; Le Breton et al. 2022 ). Moreover, because green firebreaks do not involve fuel reduction burns, they have added benefits such as public health protection (Johnston 2020 ) and aesthetic value (Bowman et al. 2018 ; Murray et al. 2018 ). Selecting cultivation plants for the purpose of improving fire resilience in agricultural landscapes should be firmly grounded in the experimental testing of species-level plant flammability (Wyse et al. 2016 ; Murray et al. 2018 , 2020 ). Plant flammability is a multidimensional trait comprising various components including maximum temperature attained during the burning of plant matter, sustainability of the burn or the duration that the plant matter burns after ignition, and amount of biomass consumed (Schwilk 2015 ). Moreover, flammability is also influenced by leaf traits (Krix & Murray 2018 , 2022 ; Popović et al. 2021 ; Potts et al. 2022 ), plant architecture (Jaureguiberry et al. 2011 ; Alam et al. 2020 ), growth form (Potts et al. 2022 ) and habitat type (Pausas et al. 2017 ). Using a standardized technique to evaluate the flammability of a broad range of crop plant species and examining how leaf traits that drive the differences in flammability could provide useful information for farm managers wanting to design fire resilient agroforestry systems or green firebreaks. With this objective in mind, we evaluate the shoot level flammability of a broad range of tropical fiber, food, and spice crops of different growth forms and model how their leaf traits influence their flammability. Methods Study site The study was conducted in Petals in the Park, a privately owned and run regenerative agroforestry farm located in Tolga, Northeast Queensland, Australia (145°28.8′E, 17°13.86′S, at 770 m a.s.l.). The area has a tropical climate with two distinct seasons, the wet season occurring from December to April and the dry season from May to November. The farm cultivates a mix of fiber, fruit and spice crop plants that they supply to local markets in Atherton and Cairns. The owners of Petals in the Park practice a form of regenerative agroforestry known as “syntropics”, which incorporates successional principles in crop rotation and management as well as planting crop species in their ideal light environment within the agroforest system for optimal growth (Andrade et al. 2020 ). Typical syntropic agroforest rows consist of a mix of trees, shrubs, groundcover plants, and vine crops from different plant families grown in rows or patches. In Petals in the Park, crops include avocado, banana, cassava, eucalyptus, ginger, mango, soursop and turmeric grown at regular intervals along 20m − 25m crop rows (Fig. 1 ). Like other forms of regenerative agriculture, Syntropics aims to reestablish healthy soil microcosms and sequester carbon in the ground (Andrade et al. 2020 ), emphasizing the importance of soil coverage either by ground cover crops or through mulching. Additionally, syntropic systems avoid herbicide, pesticide or chemical fertilizer use, with the only significant inputs being compost, mulch and lime which are used during the set up of new rows. Intense pruning regimes are used to stimulate plant growth and rapid decomposition within the soil system, speeding up nutrient cycles and allowing the agroforest to maintain soil humidity and decomposition rates comparable to forest systems (Schulz et al. 1994 ; Damant and Villela 2018 ). Study species and sampling For flammability measurements, we collected 70 cm long shoots from 66 species occurring in the Petals in the Park regenerative agroforest farm (see Supplementary Table S1). The collected plants were then broken up into subcategories based on their lifeforms: canopy (20%), sub-canopy (29%), shrub (21%), groundcover (26%), and vine (4%). Although our aim was to evaluate the flammability of as many commercially important crop species as possible, we also sampled a number of species that may be considered crop species of minor importance, and some ornamental species that were planted as ornamentals but which may be potential candidates for planting in green firebreaks. Some species occurred sparingly within the farm so we had to make supplementary collections from a neighboring home garden to obtain sufficient replicates. We strived to sample widely from plants that would fit within different vegetation strata (Fig. 1 ). Hence, we distinguished five plant life form groups: canopy trees; subcanopy trees;shrubs; groundcover herbs and scramblers, and; vines. For trees and shrubs, shoots were collected from the outer canopy with a pole pruner. For scrambling ground cover herbs and vines, we collected leading shoots. For a subset of 35 species, we collected additional 20 cm long shoot subsamples for leaf trait measurements from the same individual from which we collected the 70 cm shoots. All samples were transported back to the School for Field Studies laboratory for subsequent processing. All vegetation and trait sampling was conducted between 31 October to 18 November during the dry season of 2022. Flammability measurements The 70 cm long shoot samples were air-dried at room temperature for 24 hr prior to flammability measurements. We conducted plant flammability measurements largely following the methods described by Jaureguiberry et al. ( 2011 ) and Potts et al. ( 2022 ), burning the plant samples and recording three flammability measurements: maximum temperatures (°C), burn time (s), and burnt biomass (%). The burning apparatus has been described in detail previously (see Potts et al. 2022 ) but briefly, it consists of a grill with gas burners which serve as a safe and standardized way to measure shoot-level flammability (Jaureguiberry et al. 2011 ). Ambient air temperature was recorded using Digitech QM-1602 Digital Thermometer with K-Type thermocouples to ensure radiant heat was maintained between 100°C − 150°C before each burn. Samples were laid horizontally and preheated for two minutes on the grill, after which a blowtorch flame was applied on the leafy end of the sample for ten seconds, and any visible flames were recorded as burn time. The maximum temperature was recorded with a Fluke 572–2 High Temperature Infrared Thermometer (-30°C − 900°C, ± 1◦C) held roughly 30 cm away from the burning sample. After burning each sample, the burnt biomass was estimated visually by two to three observers. To aid in biomass estimation, we placed a metal grid over the sample before and after burn tests. When observers proposed differing percentages, the average of these values was recorded. Leaf trait measurements Leaf traits were measured from the 20cm long shoot subsamples following standardized protocols (Pérez-Harguindeguy et al. 2013). In most cases, we measured all the leaves on the 20 cm long shoot subsample, with the exception of agave, banana and papaya which had leaves that were too large for us to measure replicate leaves. In these instances, we measured leaf traits from a single leaf per individual. Where species had compound leaves, we regarded leaflets as the functional equivalent of the leaves. We obtained the fresh weights (g) from all the leaves from each subsample branch using a precision balance (accurate to three decimal points). The leaves were then laid on a white background, flattened with a glass slab and photographed with a scale. We used the magic wand function in the photo editing software paint.net to measure the total leaf area and subsequently obtained the average leaf area (LA: cm²) by dividing total leaf area by the number of leaves photographed. The fresh leaves were oven dried at 75°C for 72 hours, and the dry leaves were weighed. Leaf dry matter content (LDMC: %) was leaf dry weight divided by fresh weight expressed as a percentage ; and leaf mass per area (SLA: m²/g) was calculated by dividing leaf area by dried leaf mass. Statistical Analysis To test for differences in flammability traits between life forms, we fitted linear mixed effects models for maximum temperature and burn time as response variables, lifeform as a fixed effect, using the lme() function in the nlme package in R (version 4.1.2; R Core Team, 2021). The response variable burnt biomass consists of proportional data with non-normal distributions, necessitating a binomial generalized linear mixed model (GLMM) approach, which we fitted via the glmer() function (link = “logit”) in package lme4 (Bates et al. 2015 ). We tested how leaf traits influenced flammability measures by fitting lme models for maximum temperature and burn time and a glmer for burnt biomass, and using lifeform and leaf traits as fixed effects. In all models, we included phylogenetic relatedness as a random effect by nesting species in genus and family. We used the emmeans package (Lenth 2021 ) to perform post hoc comparisons. For models with only life form as a fixed effect, we did post hoc pairwise comparisons to determine life form differences using the lsmeans() function, and for models with both lifeform and leaf traits as fixed factors, we used the Estimated Marginal Means for post hoc analyses of fixed factor combinations. To visualize species flammabilities and to provide a useful fire management resource for farm managers, we ordinated the flammability measures of the 66 plant species using a non-metric multidimensional scaling (NMDS) ordination and a Euclidean distance measure. We also produced a heat map, which is co-plotted with a cluster analysis which was also performed on the species-level mean values for the three standardized flammability measures based on a group average linking strategy, where the dissimilarity – determined by Euclidean distance – between groups is computed as the average distance between each of their members. Based on the resulting clusters, we designated clusters of plants to be of very low, low, moderate, high or very high flammability. The ordination was run in Past 4.02 (Hammer et al. 2001 ) and the heat map was constructed using the heatmap2() function in the gplots package in R. Results Maximum Temperature of Burning Shoots Maximum temperature of shoots burned ranged from 141.7°C to 892.1°C (X̄ = 575.7°C). Among the different lifeforms, shrub species had the largest range of maximum temperatures (319.24–785.5°C) while canopy species had the smallest range, although the range was clustered towards the higher end of temperatures (578–832.2°C). Canopy species had both the highest mean (677.1°C) maximum temperature, while groundcover had both the lowest (456.7°C). Both canopy and subcanopy lifeforms had outliers, moringa and olive respectively. Pairwise comparisons showed that canopy species significantly differed from ground cover (P = 0.0001) and shrubs (P = 0.022). Ground cover also was significantly different from subcanopy (P < 0.0001), while subcanopy also differed significantly from shrubs (P = 0.021). Burn Time of Shoots Samples burned from 0 seconds to 105 seconds (X̄ = 15 seconds). Canopy species had the greatest range of burn times (4.8–51.9 seconds) as well as the longest average burn time (25.55s) in contrast to groundcover (0-14.14 s, X̄ = 4.62s). Shrub and groundcover burn times were similar. Several outliers were noted within subcanopy, shrub and groundcover lifeforms. For subcanopy, lychee and macadamia had much longer burn times on average at 73.7s and 56 s, respectively. For shrub lifeforms, curry leaf and pigeon pea also had longer average burn times at 81s and 37.8s, respectively. The lone outlier for ground cover is sugar cane, burning for an average of 28.4 seconds. Our pairwise comparison showed that the canopy was significantly different from groundcover (P < 0.0001) and shrubs (P = 0.022), groundcover differed significantly from subcanopy (P < 0.0001) and subcanopy differed significantly from shrubs (P = 0.009). Proportion of Shoot Burnt Biomass Total burnt biomass of the shoot samples ranged from 0-100% (X̄ = 24.19%). In a pairwise comparison, canopy was significantly different from groundcover (P = 0.0012) and shrub (P = 0.019) (Fig. 2 c). Subcanopy differed significantly from ground cover (P = 0.031), which overall lost the least amount of biomass on average (X̄ = = 9.30%) and had the smallest range. On the other hand, canopy species had the most variable amount of burn mass lost with the largest range (6–92%) and the highest average (X̄ = 40.24%). Of the lifeforms studied, we found that a higher proportion of canopy species were more likely to be consumed by fire compared to groundcover and shrubs. Outliers include lychee for subcanopy (97.29%), curry leaf for shrub (75%), and asparagus (37.14%) and galangal (26.2%) for groundcover. Leaf Traits and Their Relation with Flammability Our models showed that leaf area is negatively related with maximum temperature (P = 0.0071; Fig. 3 a; Table S2). We did not find any significant relationships between leaf area and burn time or burnt biomass (Fig. 3 b, c; Tables S3, S4). Leaf Dry Matter Content (LDMC) is a significant leaf trait predictor of maximum temperature (P = < 0.0001; Fig. 3 d; Table S2) burn time (P = 0.0001; Fig. 3 e; Table S3), burnt biomass (P = 0.004; Fig. 3 f; Table S4). Pairwise comparisons examining interaction effects between leaf traits and life forms yielded no significant interactions across all burn traits (P > 0.05). Specific leaf area (not plotted) was not a significant predictor of any flammability measure (Tables S2, S3, S4). Overall Flammability An ordination of all of the flammability measurements for the study species showed that species arrayed themselves along a gradient of high to low flammability represented by axis 1. Axis 1 explains 93.9% of the variation and is significantly correlated with maximum temperature, burned biomass, and burn time (Fig. 4 ). Axis 2 explained 6% the variation and was significantly correlated with maximum temperature (Fig. 4 ). Canopy and subcanopy overall tended to have higher maximum temperatures, higher burnt biomasses, and longer burn times while shrubs, groundcover, and vines tended to burn at lower temperatures, have less biomass consumed, and burned for shorter amounts of time (Fig. 4 ). Our heat map shows that lychee, rose gum, curry leaf and white sapote were among the most flammable of species, while dragonfruit, snake plant, aloe, tree tomato and dogbane were the least flammable (Fig. 5 ). Discussion Understanding the species level flammability of plants within agroforestry systems can enable us to design more fire resilient agricultural landscapes. We evaluated the shoot level flammability of 353 individuals from 66 species and 43 families, with species replication within life form categories. Using a subset of our data, we also examined how leaf traits influence plant flammability. Of these lifeforms we found that there was a significant difference in the flammability measures of upper strata life forms (canopy and subcanopy) and lower strata life forms (groundcover, shrub, and vine). Lower strata life forms tend to have lower maximum temperatures, shorter burn times, and less biomass loss while taller plants experienced a converse of these measurements. A recent study by Potts et al. ( 2022 ) similarly showed that tree lifeforms are more flammable than shrub lifeforms, potentially because tree canopies experience higher temperatures. Various authors have proposed that plant flammability is influenced by leaf traits (Krix and Murray 2018 ; Potts et al. 2022 ), and our results are in agreement. A recent study by Potts et al. ( 2022 ) similarly showed that tree lifeforms are more flammable than shrub lifeforms, potentially because tree canopies experience higher temperatures. Previous studies have shown that leaf area (LA) is a strong predictor of flammability with leaves that are longer, wider, and have a larger area more likely to ignite (Murray et al. 2013 ). Our results appear contrary to this observation and this could be because some of the larger leafed species such as mulberry, tree tomato and banana were not very flammable. While LA impacts the flammability of the plant itself, it can also influence flammability of an area in general as leaf litter can be a source of fuel for low intensity fires (Burton et al. 2021 ). Leaf litter that has a larger LA tends to be less compact and therefore contributes to more aeration and a higher likelihood of fire (Schwilk 2015 ). Another leaf trait, specific leaf area (SLA) is negatively associated with leaf flammability (Burton et al. 2021 ). However, we did not find SLA to be a significant predictor of any flammability measure. As a follow up study, it would be interesting to examine how leaf traits influence the flammability of the leaf litter in agroforestry systems. This is particularly important to consider in Syntropic agroforestry given the importance of the “chop-and-drop” practice to produce mulch that is laid down on the crop rows. In order to counteract the effect of leaf litter in agroforests, the inclusion of a healthy ground cover is recommended as ground cover plants have a lower flammability and contribute to a higher moisture content in the soil and leaf litter that can prevent fire. Our study also shows that leaf dry matter content (LDMC) is a significant predictor of burn time for groundcover and shrub as well as a significant predictor of the burnt biomass of groundcover and shrubs. This is consistent with the literature showing that leaves with a higher water content are more resistant to burning (Gill 1996 ; Potts et al. 2022 ). Implications for Farming Practices Regenerative farming is one way in which flammability of an agroforest can be reduced as growing low flammability species together will greatly decrease the chance of fire and growing low flammability species alongside more flammable ones can add a level of protection to more vulnerable plants. Syntropic agriculture is a good example of how less flammable and more flammable species can be grown together as there is a fairly even distribution of plants of each life form in a row due to the way syntropic farmers set up their rows following the principles of light stratification and succession (Andrade et al. 2020 ). However, perhaps a better alternative would be to find less flammable canopy species to take the place of the highly flammable Eucalyptus spp that is commonly grown in agroforestry systems. The predominant function of Eucalyptus spp. is a fast-growing and biomass-producing plant that is frequently pruned for mulch that could be filled by other non-flammable species such as moringa, jackfruit, or milky pine. Alternatively, management pruning of these plants should coincide with dry periods where fire risk is higher. Monoculture farmers can also benefit from having an awareness of low flammability plants. Even if the creation of a regenerative forest is not in order, having non-flammable species growing among already established monoculture farms could greatly reduce the risk of fire. By planting non-flammable ground cover plants in the inter-row spaces among more flammable cash crop species such as mango and avocado, farmers can reduce the risk of fire spreading throughout their farms. One fire mitigation technique that may be helpful for both polyculture and monoculture systems would be the implementation of green firebreaks. Green firebreaks have long been used in China and have been shown to be highly effective in preventing high intensity fires (Cui et al. 2019 ). When green firebreaks are placed strategically around a property they act as barricades against oncoming fires, protecting properties and livelihoods. Construction of green firebreaks could also greatly improve safety of Australian civilians as research shows that many people, especially in rural areas, often choose to stay in their homes during wildfires in order to protect their property from damage (McGee and Russell 2003 ). Establishment of green firebreaks based on low flammability food plants could serve simultaneously as insurance against property damage and an economic resource for farmers. Given the increasing frequency and intensity of wildfires across Australia it is imperative that proactive steps are taken in order to lower the risk of fire spreading into agricultural and other human inhabited areas. Implementation of green firebreaks and inclusion of fire resistant species into agricultural lands, whether it be through the establishment of regenerative agroforests or the inclusion of non-flammable species in monoculture, will be necessary steps in moving toward fire resistant landscapes and protection of food systems. Conclusion Agricultural landscapes are facing increasing stresses from climate change, and elevated fire risk is one concerning trend in tropical agricultural regions. Establishing agroforestry systems can be a means of mitigating fire risk on farms, and our study has provided novel insights into the flammability of a number of tropical crop plants. By identifying a range of flammable and non-flammable plants of different lifeforms, we hope that farmers will be equipped with knowledge on selecting plants to grow that can help reduce the fire risk on their farms. Follow up studies on a wider range of crops plants from different growing zones, and particularly in dry tropical and semi-arid zones is imperative, and will enable us to tailor fire mitigation measures to suit specific climate settings. Declarations Acknowledgments We thank Neil & Jane Hawkes for their hospitality and permission to sample from their property. Thank you also to Margaret Moui, the staff of SFS, and Charlie Almeida. Data availability The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Conflict of interests The authors declare no conflict of interests. Funding The authors acknowledge internal funding from the School for Field Studies which supported the project. References Alam MA, Wyse SV, Buckley HL, Perry GL, Sullivan JJ, Mason NW, Buxton R, Richardson SJ, Curran TJ (2020) Shoot flammability is decoupled from leaf flammability, but controlled by leaf functional traits. 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Risk Anal 37:1898–1916. https://doi.org/10.1111/risa.12739 Malézieux E, Crozat Y, Dupraz C, Laurans M, Makowski D, Ozier-Lafontaine H, Rapidel B, Tourdonnet SD, Valantin-Morison M (2009) Mixing plant species in cropping systems: concepts, tools and models: a review. Agron Sustain Dev 29:43-62. https://doi.org/10.1051/agro:2007057 McGee TK, Russell S (2003) “It’s just a natural way of life…” an investigation of wildfire preparedness in rural Australia Environ Hazards 5:1–12.https://doi.org/10.1016/j.hazards.2003.04.001 Moriondo M, Good P, Durao R, Bindi M, Giannakopoulos C, Corte-Real J (2006) Potential impact of climate change on fire risk in the Mediterranean area. Clim Res 31:85–95. https://doi.org/10.3354/cr031085 Murray BR, Hardstaff LK, Phillips ML (2013) Differences in leaf flammability, leaf traits and flammability-trait relationships between native and exotic plant species of dry sclerophyll forest. PloS One 8: e79205. https://doi.org/10.1371/journal.pone.0079205 Murray BR, Martin LJ, Brown C, Krix DW, Phillips ML (2018) Selecting low-flammability plants as green firebreaks within sustainable urban garden design. Fire 1:15. https://doi.org/10.3390/fire1010015 Murray BR, Brown C, Murray ML, Krix DW, Martin LJ, Hawthorne T, Wallace MI, Potvin SA, Webb JK (2020) An integrated approach to identify low-flammability plant species for green firebreaks. Fire 3:9. https://doi.org/10.3390/fire3020009 Pausas JG, Keeley JE, Schwilk DW (2017) Flammability as an ecological and evolutionary driver. J of Ecol 105:289-297. https://doi.org/10.1111/1365-2745.12691 Perez-Harguindeguy N, Diaz S, Garnier E, Lavorel S, Poorter H, Jaureguiberry P, ... & Cornelissen, J. H. C. (2016) Corrigendum to: New handbook for standardised measurement of plant functional traits worldwide. Aust J Bot 64: 715-716. doi:10.1071/BT12225_CO Popović Z, Bojović S, Marković M, Cerdà A (2021). Tree species flammability based on plant traits: A synthesis. Sci of the Total Environ 800:149625. https://doi.org/10.1016/j.scitotenv.2021.149625 Potts E, Tng D, Apgaua D, Curran TJ, Engert J, Laurance SG (2022) Growth form and functional traits influence the shoot flammability of tropical rainforest species. For Ecol and Manag 522:120485.https://doi.org/10.1016/j.foreco.2022.120485 Ribeiro, LM, Viegas, DX, Almeida M,, McGee TK, Pereira MG, Parente J, Xanthopoulos G, Leone V, Delogu GM, Hardin, H. (2020). Extreme wildfires and disasters around the world: Lessons to be learned. In Extreme wildfire events and disasters. Elsevier:31-51. https://doi.org/10.1016/B978-0-12-815721-3.00002-3 Schulz B, Becker B, Götsch E (1994) Indigenous knowledge in a ’modern’ Sustainable agroforestry system - a case study from eastern Brazil. Agrofor Syst 25:59–69. https://doi.org/10.1007/BF00705706 Schwilk DW (2015) Dimensions of plant flammability. New Phytol 206:486-488. https://doi.org/10.1111/nph.13372 Strydom H, Schutte SC (2005). A theoretical perspective on farm attacks in the South African farming community. Acta Criminologica: African J of Criminol & Vict 18:115-125. Tibbits A, Whittaker J (2007) Stay and defend or leave early: policy problems and experiences during the 2003 Victorian bushfires. Environ. Hazards 7:283-290. https://doi.org/10.1016/j.envhaz.2007.08.001 Trancoso R, Syktus J, Salazar A, Thatcher M, Toombs N, Wong KK, Meijaard E, Sheil D, McAlpine CA (2022) Converting tropical forests to agriculture increases fire risk by fourfold. Environ Res Lett 17:1-16 https://doi.org/10.1088/1748-9326/ac8f5c Withey K, Berenguer E, Palmeira AF, Espírito-Santo FD, Lennox GD, Silva CV, Aragão LE, Ferreira J, França F, Malhi Y, Rossi LC (2018) Quantifying immediate carbon emissions from El Niño-mediated wildfires in humid tropical forests. Phil. Trans. R. Soc. B 373:1-11. https://doi.org/10.1098/rstb.2017.0312 Wyse SV, Perry GL, O’Connell DM, Holland PS, Wright MJ, Hosted CL, Whitelock SL, Geary IJ, Maurin KJ, Curran TJ (2016) A quantitative assessment of shoot flammability for 60 tree and shrub species supports rankings based on expert opinion. Int J of Wildland Fire 25:466-477. https://doi.org/10.1071/WF15047 Additional Declarations No competing interests reported. Supplementary Files Appendix1.docx Appendix2.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2357569","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":158762803,"identity":"df75c833-86eb-4fa8-a059-f23e6539ea85","order_by":0,"name":"Ashley Stephanie Pacheco","email":"","orcid":"","institution":"Grinnell College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ashley","middleName":"Stephanie","lastName":"Pacheco","suffix":""},{"id":158762804,"identity":"9faaf02f-b748-49ad-8f81-f2450aef1803","order_by":1,"name":"Hannah Danaë Goodman","email":"","orcid":"","institution":"Reed 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Diego","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Alejandro","middleName":"","lastName":"Ortiz","suffix":""},{"id":158762812,"identity":"948e23ea-e318-4f33-b18e-83cac462df1c","order_by":5,"name":"Henry Maxwell Marinace","email":"","orcid":"","institution":"Clark University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Henry","middleName":"Maxwell","lastName":"Marinace","suffix":""},{"id":158762814,"identity":"4b57657c-8c72-4cdc-a9e9-6f9ba59219d1","order_by":6,"name":"Emily Anne Bischoff","email":"","orcid":"","institution":"School for Field Studies","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Emily","middleName":"Anne","lastName":"Bischoff","suffix":""},{"id":158762818,"identity":"36f58a3d-9d9c-401f-b03a-98cba0e00d03","order_by":7,"name":"Victoria Frances Holman","email":"","orcid":"","institution":"School for Field 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Apgaua","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABE0lEQVRIie3PMUvDQBTA8SsH6fLSrClo/QpXAgGX+FXuCKRL4yJIwcGAcFPs7uB38Bt48oYs0aydROniEOSkkxDBq+KkVzsK3n+548iPl0eIy/UXU5/HqH9GegrWV9ySRGC+NIRtT0Spvoj6RQyqW3x6lcmk7FOl2q4T84qiJrP7pLCQYX2Y7Z/LNC+px28uJRMX6GUhqY9SG2FqGjNf0vyaAkO/YOIKISY9yVPbj7Gmjcdv8nQCNNAI3ZoEK72RLKbR0pfIgQJB8D6mkNCQxEaGi+eM7txVY7MLM7tEkdklDnnNuY0Mmhxf2uOTPQjw8aHtRrvzBpdaz/iBjRACXvj90YwQhZ1Q/eP7hikul8v1z3oHskJg9wuZGMcAAAAASUVORK5CYII=","orcid":"","institution":"School for Field Studies","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Deborah","middleName":"Mattos Guimaraes","lastName":"Apgaua","suffix":""},{"id":158762824,"identity":"0903596b-901c-48c7-8fbf-e29f51cb1a1a","order_by":10,"name":"David Yue Phin Tng","email":"","orcid":"","institution":"School for Field Studies","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"David","middleName":"Yue Phin","lastName":"Tng","suffix":""}],"badges":[],"createdAt":"2022-12-08 11:14:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2357569/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2357569/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":30280919,"identity":"4d75bcff-455b-4867-a049-e6ba4b12b886","added_by":"auto","created_at":"2022-12-13 19:26:04","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":549611,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic of an idealized regenerative agroforest row showing a tiered vegetation structure with canopy, subcanopy, shrub and groundcover layers. Vines are depicted (dragonfruit), but not labeled.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-2357569/v1/fd3629041e55e5b860d81764.jpeg"},{"id":30280404,"identity":"376ee9ea-f06d-4626-be52-2f4f4acc3787","added_by":"auto","created_at":"2022-12-13 19:18:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":283312,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e Comparison of maximum temperature that shoots burn, \u003cstrong\u003eb\u003c/strong\u003e length of time a shoot has flames, and \u003cstrong\u003ec\u003c/strong\u003e the percentage of biomass burned for different life forms. Vines are not considered due to small sample sizes.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-2357569/v1/754cf0b94fbc720445ea2b1c.png"},{"id":30280407,"identity":"59eef691-38ca-4cc8-91aa-75ae0122dcc1","added_by":"auto","created_at":"2022-12-13 19:18:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":793128,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between leaf area vs. \u003cstrong\u003ea\u003c/strong\u003e maximum temperature, \u003cstrong\u003eb\u003c/strong\u003e burn time, and \u003cstrong\u003ec\u003c/strong\u003e burnt biomass; and leaf dry matter content vs. \u003cstrong\u003ed\u003c/strong\u003e maximum temperature, \u003cstrong\u003ee\u003c/strong\u003e. burn time, and \u003cstrong\u003ef\u003c/strong\u003e burnt biomass.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-2357569/v1/a15d760ea3fc1774bf2452fa.png"},{"id":30280410,"identity":"82eb581e-3ca9-4bf3-93a9-1f125b2535ff","added_by":"auto","created_at":"2022-12-13 19:18:05","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":198472,"visible":true,"origin":"","legend":"\u003cp\u003eTwo dimensional ordination of 66 species showing how each lifeform interacts with flammability measures\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-2357569/v1/987cd1bca62e6b0ec6634516.png"},{"id":30280406,"identity":"6a5db9c3-f121-4a80-9697-19d112ea94f5","added_by":"auto","created_at":"2022-12-13 19:18:05","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":287800,"visible":true,"origin":"","legend":"\u003cp\u003eFlammability analysis heat map for sampled species co-plotted with a cluster analysis based on burnt biomass, burn time, and maximum temperature of shoots from the study species\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-2357569/v1/a9aa0303c618f6dab8eeef70.png"},{"id":38580720,"identity":"10075b9e-0dcf-4922-8845-dcdc9d53d554","added_by":"auto","created_at":"2023-06-15 06:59:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1308946,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2357569/v1/9d3b112a-4022-49c9-a174-6b3f81781d36.pdf"},{"id":30280920,"identity":"bd1fd3e5-815e-47d2-a670-38c204ea8f5c","added_by":"auto","created_at":"2022-12-13 19:26:05","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":23639,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix1.docx","url":"https://assets-eu.researchsquare.com/files/rs-2357569/v1/4ae1dd5f23d92ad9589711a6.docx"},{"id":30280409,"identity":"1ce982de-125b-4f3a-8bb8-5609a04e1764","added_by":"auto","created_at":"2022-12-13 19:18:05","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":100963,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix2.docx","url":"https://assets-eu.researchsquare.com/files/rs-2357569/v1/f6fe7c66032619f5d128b273.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Fighting fire with food: Assessing the flammability of crop plant species for building fire resilient agroforestry systems","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDemand for agricultural products is expected to increase by an estimated 1.1% per year until 2050 due to drivers such as population growth, increases in per capita consumption, and diet changes (Alexandratos and Bruinsma \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Meanwhile, trends in global climate change are exacerbating drought frequency and posing a challenge to food security (Jones et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Climate change can also elevate fire risk by increasing the number of days with fire risk and length of fire risk season, etc. (Moriondo et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). There has already been a global increase in incidences of wildlifes, with potentially devastating impacts on both natural and agricultural landscapes (Lozano et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Wildlifes in 2003 burnt 1.12\u0026nbsp;million ha of public and private forests and agricultural lands in the state of Victoria, Australia (Tibbits and Whittaker \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Ribeiro et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), leading to loss of property, livestock and agricultural equipment amounting to 300\u0026nbsp;million AUD (Ashe et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Even humid tropical forest regions, once thought of as \u0026ldquo;fire-proof\u0026rdquo;, are now subject to higher incidence of catastrophic fire events (Withey et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThese environmental challenges are compounded by ongoing conversion of forested land for farming and modern large-scale agricultural practices. Tropical forests play a key role in regulating regional climate processes and fire weather risk, and when cleared for agricultural land leads to a fourfold increase in wildfires (Trancoso et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Additionally, the modern monocultures of single genetically homogeneous crops that tropical forests are typically cleared for use large quantities of fertilizer and pesticides (Mal\u0026eacute;zieux et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). This results in a simplified agricultural landscape with reduced biodiversity that is vulnerable to disturbances like pest outbreaks, rainfall fluctuations and climate change, and as a consequence may shift into a new and less resilient type of landscape with subsequent loss of ecosystem services (Foley et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Gordon et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Monoculture farms and intensively cultivated timber plantations are especially vulnerable to disrupted hydrologic regimes and fire damage (Bowman et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Giller et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), or even deliberately-lit fires in acts of arson (Strydom and Schutte \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGiven the trends in agricultural intensification in the tropics, it is necessary to equip agricultural landowners with information and resources on mitigating fires to protect their livelihoods (Keys and McConnell \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Establishing agroforestry systems is an economically feasible means to maintain agricultural production and critical ecosystem services, and an adaptive strategy for farmers to mitigate fire risk in fire-prone areas (Lin \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Agroforestry involves the deliberate integration of woody vegetation (trees and/or shrubs) to establish multi-tiered crop rows and uses little to no herbicide inputs.\u003c/p\u003e \u003cp\u003eMulti-tiered crop rows promote favorable microclimate conditions by influencing radiation flux, air temperature, and wind speed, all of which can help mitigate fire risk (Ewel \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Reduced herbicide inputs promote healthier microbial communities, improving carbon sequestration and cycling, thus helping manage fuel build-up (Andrade et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Damianidis et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough the presence of trees and/or shrubs in agroforestry crop rows may generate microclimates resistant to high fire risk conditions, farms cultivating flammable crops may still be vulnerable to wildfires and arson. Agroforest farm managers as well as conventional farmers can implement various measures to optimize fire safety on their farms. One such measure is to incorporate \u0026ldquo;green firebreaks\u0026rdquo;, strips of low-flammability vegetation installed at strategic locations to suppress fires (Curran et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Cui et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Green firebreaks are garnering increased attention as a nature-based solution and complementary strategy for managing fire risk in urban-wildland interfaces and agricultural landscapes (Curran et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Le Breton et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Moreover, because green firebreaks do not involve fuel reduction burns, they have added benefits such as public health protection (Johnston \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and aesthetic value (Bowman et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Murray et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSelecting cultivation plants for the purpose of improving fire resilience in agricultural landscapes should be firmly grounded in the experimental testing of species-level plant flammability (Wyse et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Murray et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Plant flammability is a multidimensional trait comprising various components including maximum temperature attained during the burning of plant matter, sustainability of the burn or the duration that the plant matter burns after ignition, and amount of biomass consumed (Schwilk \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Moreover, flammability is also influenced by leaf traits (Krix \u0026amp; Murray \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Popović et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Potts et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), plant architecture (Jaureguiberry et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Alam et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), growth form (Potts et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and habitat type (Pausas et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUsing a standardized technique to evaluate the flammability of a broad range of crop plant species and examining how leaf traits that drive the differences in flammability could provide useful information for farm managers wanting to design fire resilient agroforestry systems or green firebreaks. With this objective in mind, we evaluate the shoot level flammability of a broad range of tropical fiber, food, and spice crops of different growth forms and model how their leaf traits influence their flammability.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy site\u003c/h2\u003e \u003cp\u003eThe study was conducted in Petals in the Park, a privately owned and run regenerative agroforestry farm located in Tolga, Northeast Queensland, Australia (145\u0026deg;28.8\u0026prime;E, 17\u0026deg;13.86\u0026prime;S, at 770 m a.s.l.). The area has a tropical climate with two distinct seasons, the wet season occurring from December to April and the dry season from May to November. The farm cultivates a mix of fiber, fruit and spice crop plants that they supply to local markets in Atherton and Cairns.\u003c/p\u003e \u003cp\u003eThe owners of Petals in the Park practice a form of regenerative agroforestry known as \u0026ldquo;syntropics\u0026rdquo;, which incorporates successional principles in crop rotation and management as well as planting crop species in their ideal light environment within the agroforest system for optimal growth (Andrade et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Typical syntropic agroforest rows consist of a mix of trees, shrubs, groundcover plants, and vine crops from different plant families grown in rows or patches. In Petals in the Park, crops include avocado, banana, cassava, eucalyptus, ginger, mango, soursop and turmeric grown at regular intervals along 20m \u0026minus;\u0026thinsp;25m crop rows (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Like other forms of regenerative agriculture, Syntropics aims to reestablish healthy soil microcosms and sequester carbon in the ground (Andrade et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), emphasizing the importance of soil coverage either by ground cover crops or through mulching. Additionally, syntropic systems avoid herbicide, pesticide or chemical fertilizer use, with the only significant inputs being compost, mulch and lime which are used during the set up of new rows. Intense pruning regimes are used to stimulate plant growth and rapid decomposition within the soil system, speeding up nutrient cycles and allowing the agroforest to maintain soil humidity and decomposition rates comparable to forest systems (Schulz et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Damant and Villela \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy species and sampling\u003c/h2\u003e \u003cp\u003eFor flammability measurements, we collected 70 cm long shoots from 66 species occurring in the Petals in the Park regenerative agroforest farm (see Supplementary Table S1). The collected plants were then broken up into subcategories based on their lifeforms: canopy (20%), sub-canopy (29%), shrub (21%), groundcover (26%), and vine (4%). Although our aim was to evaluate the flammability of as many commercially important crop species as possible, we also sampled a number of species that may be considered crop species of minor importance, and some ornamental species that were planted as ornamentals but which may be potential candidates for planting in green firebreaks. Some species occurred sparingly within the farm so we had to make supplementary collections from a neighboring home garden to obtain sufficient replicates.\u003c/p\u003e \u003cp\u003eWe strived to sample widely from plants that would fit within different vegetation strata (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Hence, we distinguished five plant life form groups: canopy trees; subcanopy trees;shrubs; groundcover herbs and scramblers, and; vines. For trees and shrubs, shoots were collected from the outer canopy with a pole pruner. For scrambling ground cover herbs and vines, we collected leading shoots. For a subset of 35 species, we collected additional 20 cm long shoot subsamples for leaf trait measurements from the same individual from which we collected the 70 cm shoots. All samples were transported back to the School for Field Studies laboratory for subsequent processing. All vegetation and trait sampling was conducted between 31 October to 18 November during the dry season of 2022.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eFlammability measurements\u003c/h2\u003e \u003cp\u003eThe 70 cm long shoot samples were air-dried at room temperature for 24 hr prior to flammability measurements. We conducted plant flammability measurements largely following the methods described by Jaureguiberry et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and Potts et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), burning the plant samples and recording three flammability measurements: maximum temperatures (\u0026deg;C), burn time (s), and burnt biomass (%).\u003c/p\u003e \u003cp\u003eThe burning apparatus has been described in detail previously (see Potts et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) but briefly, it consists of a grill with gas burners which serve as a safe and standardized way to measure shoot-level flammability (Jaureguiberry et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Ambient air temperature was recorded using Digitech QM-1602 Digital Thermometer with K-Type thermocouples to ensure radiant heat was maintained between 100\u0026deg;C \u0026minus;\u0026thinsp;150\u0026deg;C before each burn. Samples were laid horizontally and preheated for two minutes on the grill, after which a blowtorch flame was applied on the leafy end of the sample for ten seconds, and any visible flames were recorded as burn time. The maximum temperature was recorded with a Fluke 572\u0026ndash;2 High Temperature Infrared Thermometer (-30\u0026deg;C \u0026minus;\u0026thinsp;900\u0026deg;C, \u0026plusmn;\u0026thinsp;1◦C) held roughly 30 cm away from the burning sample. After burning each sample, the burnt biomass was estimated visually by two to three observers. To aid in biomass estimation, we placed a metal grid over the sample before and after burn tests. When observers proposed differing percentages, the average of these values was recorded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eLeaf trait measurements\u003c/h2\u003e \u003cp\u003eLeaf traits were measured from the 20cm long shoot subsamples following standardized protocols (P\u0026eacute;rez-Harguindeguy et al. 2013). In most cases, we measured all the leaves on the 20 cm long shoot subsample, with the exception of agave, banana and papaya which had leaves that were too large for us to measure replicate leaves. In these instances, we measured leaf traits from a single leaf per individual. Where species had compound leaves, we regarded leaflets as the functional equivalent of the leaves.\u003c/p\u003e \u003cp\u003eWe obtained the fresh weights (g) from all the leaves from each subsample branch using a precision balance (accurate to three decimal points). The leaves were then laid on a white background, flattened with a glass slab and photographed with a scale. We used the magic wand function in the photo editing software paint.net to measure the total leaf area and subsequently obtained the average leaf area (LA: cm\u0026sup2;) by dividing total leaf area by the number of leaves photographed. The fresh leaves were oven dried at 75\u0026deg;C for 72 hours, and the dry leaves were weighed. Leaf dry matter content (LDMC: %) was leaf dry weight divided by fresh weight expressed as a percentage ; and leaf mass per area (SLA: m\u0026sup2;/g) was calculated by dividing leaf area by dried leaf mass.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eTo test for differences in flammability traits between life forms, we fitted linear mixed effects models for maximum temperature and burn time as response variables, lifeform as a fixed effect, using the lme() function in the \u003cem\u003enlme\u003c/em\u003e package in R (version 4.1.2; R Core Team, 2021). The response variable burnt biomass consists of proportional data with non-normal distributions, necessitating a binomial generalized linear mixed model (GLMM) approach, which we fitted via the glmer() function (link = \u0026ldquo;logit\u0026rdquo;) in package \u003cem\u003elme4\u003c/em\u003e (Bates et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). We tested how leaf traits influenced flammability measures by fitting lme models for maximum temperature and burn time and a glmer for burnt biomass, and using lifeform and leaf traits as fixed effects. In all models, we included phylogenetic relatedness as a random effect by nesting species in genus and family. We used the \u003cem\u003eemmeans\u003c/em\u003e package (Lenth \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) to perform post hoc comparisons. For models with only life form as a fixed effect, we did post hoc pairwise comparisons to determine life form differences using the lsmeans() function, and for models with both lifeform and leaf traits as fixed factors, we used the Estimated Marginal Means for post hoc analyses of fixed factor combinations.\u003c/p\u003e \u003cp\u003eTo visualize species flammabilities and to provide a useful fire management resource for farm managers, we ordinated the flammability measures of the 66 plant species using a non-metric multidimensional scaling (NMDS) ordination and a Euclidean distance measure. We also produced a heat map, which is co-plotted with a cluster analysis which was also performed on the species-level mean values for the three standardized flammability measures based on a group average linking strategy, where the dissimilarity \u0026ndash; determined by Euclidean distance \u0026ndash; between groups is computed as the average distance between each of their members. Based on the resulting clusters, we designated clusters of plants to be of very low, low, moderate, high or very high flammability. The ordination was run in Past 4.02 (Hammer et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) and the heat map was constructed using the heatmap2() function in the \u003cem\u003egplots\u003c/em\u003e package in R.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eMaximum Temperature of Burning Shoots\u003c/h2\u003e \u003cp\u003eMaximum temperature of shoots burned ranged from 141.7\u0026deg;C to 892.1\u0026deg;C (X̄ = 575.7\u0026deg;C). Among the different lifeforms, shrub species had the largest range of maximum temperatures (319.24\u0026ndash;785.5\u0026deg;C) while canopy species had the smallest range, although the range was clustered towards the higher end of temperatures (578\u0026ndash;832.2\u0026deg;C). Canopy species had both the highest mean (677.1\u0026deg;C) maximum temperature, while groundcover had both the lowest (456.7\u0026deg;C). Both canopy and subcanopy lifeforms had outliers, moringa and olive respectively. Pairwise comparisons showed that canopy species significantly differed from ground cover (P\u0026thinsp;=\u0026thinsp;0.0001) and shrubs (P\u0026thinsp;=\u0026thinsp;0.022). Ground cover also was significantly different from subcanopy (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), while subcanopy also differed significantly from shrubs (P\u0026thinsp;=\u0026thinsp;0.021).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eBurn Time of Shoots\u003c/h2\u003e \u003cp\u003eSamples burned from 0 seconds to 105 seconds (X̄ = 15 seconds). Canopy species had the greatest range of burn times (4.8\u0026ndash;51.9 seconds) as well as the longest average burn time (25.55s) in contrast to groundcover (0-14.14 s, X̄ = 4.62s). Shrub and groundcover burn times were similar. Several outliers were noted within subcanopy, shrub and groundcover lifeforms. For subcanopy, lychee and macadamia had much longer burn times on average at 73.7s and 56 s, respectively. For shrub lifeforms, curry leaf and pigeon pea also had longer average burn times at 81s and 37.8s, respectively. The lone outlier for ground cover is sugar cane, burning for an average of 28.4 seconds. Our pairwise comparison showed that the canopy was significantly different from groundcover (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and shrubs (P\u0026thinsp;=\u0026thinsp;0.022), groundcover differed significantly from subcanopy (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and subcanopy differed significantly from shrubs (P\u0026thinsp;=\u0026thinsp;0.009).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eProportion of Shoot Burnt Biomass\u003c/h2\u003e \u003cp\u003eTotal burnt biomass of the shoot samples ranged from 0-100% (X̄ = 24.19%). In a pairwise comparison, canopy was significantly different from groundcover (P\u0026thinsp;=\u0026thinsp;0.0012) and shrub (P\u0026thinsp;=\u0026thinsp;0.019) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Subcanopy differed significantly from ground cover (P\u0026thinsp;=\u0026thinsp;0.031), which overall lost the least amount of biomass on average (X̄ = = 9.30%) and had the smallest range. On the other hand, canopy species had the most variable amount of burn mass lost with the largest range (6\u0026ndash;92%) and the highest average (X̄ = 40.24%). Of the lifeforms studied, we found that a higher proportion of canopy species were more likely to be consumed by fire compared to groundcover and shrubs. Outliers include lychee for subcanopy (97.29%), curry leaf for shrub (75%), and asparagus (37.14%) and galangal (26.2%) for groundcover.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLeaf Traits and Their Relation with Flammability\u003c/h2\u003e \u003cp\u003eOur models showed that leaf area is negatively related with maximum temperature (P\u0026thinsp;=\u0026thinsp;0.0071; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea; Table S2). We did not find any significant relationships between leaf area and burn time or burnt biomass (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb, c; Tables S3, S4).\u003c/p\u003e \u003cp\u003eLeaf Dry Matter Content (LDMC) is a significant leaf trait predictor of maximum temperature (P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed; Table S2) burn time (P\u0026thinsp;=\u0026thinsp;0.0001; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee; Table S3), burnt biomass (P\u0026thinsp;=\u0026thinsp;0.004; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef; Table S4). Pairwise comparisons examining interaction effects between leaf traits and life forms yielded no significant interactions across all burn traits (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Specific leaf area (not plotted) was not a significant predictor of any flammability measure (Tables S2, S3, S4).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eOverall Flammability\u003c/h2\u003e \u003cp\u003eAn ordination of all of the flammability measurements for the study species showed that species arrayed themselves along a gradient of high to low flammability represented by axis 1. Axis 1 explains 93.9% of the variation and is significantly correlated with maximum temperature, burned biomass, and burn time (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Axis 2 explained 6% the variation and was significantly correlated with maximum temperature (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Canopy and subcanopy overall tended to have higher maximum temperatures, higher burnt biomasses, and longer burn times while shrubs, groundcover, and vines tended to burn at lower temperatures, have less biomass consumed, and burned for shorter amounts of time (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOur heat map shows that lychee, rose gum, curry leaf and white sapote were among the most flammable of species, while dragonfruit, snake plant, aloe, tree tomato and dogbane were the least flammable (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eUnderstanding the species level flammability of plants within agroforestry systems can enable us to design more fire resilient agricultural landscapes. We evaluated the shoot level flammability of 353 individuals from 66 species and 43 families, with species replication within life form categories. Using a subset of our data, we also examined how leaf traits influence plant flammability.\u003c/p\u003e \u003cp\u003eOf these lifeforms we found that there was a significant difference in the flammability measures of upper strata life forms (canopy and subcanopy) and lower strata life forms (groundcover, shrub, and vine). Lower strata life forms tend to have lower maximum temperatures, shorter burn times, and less biomass loss while taller plants experienced a converse of these measurements. A recent study by Potts et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) similarly showed that tree lifeforms are more flammable than shrub lifeforms, potentially because tree canopies experience higher temperatures.\u003c/p\u003e \u003cp\u003eVarious authors have proposed that plant flammability is influenced by leaf traits (Krix and Murray \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Potts et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and our results are in agreement. A recent study by Potts et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) similarly showed that tree lifeforms are more flammable than shrub lifeforms, potentially because tree canopies experience higher temperatures. Previous studies have shown that leaf area (LA) is a strong predictor of flammability with leaves that are longer, wider, and have a larger area more likely to ignite (Murray et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Our results appear contrary to this observation and this could be because some of the larger leafed species such as mulberry, tree tomato and banana were not very flammable. While LA impacts the flammability of the plant itself, it can also influence flammability of an area in general as leaf litter can be a source of fuel for low intensity fires (Burton et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Leaf litter that has a larger LA tends to be less compact and therefore contributes to more aeration and a higher likelihood of fire (Schwilk \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Another leaf trait, specific leaf area (SLA) is negatively associated with leaf flammability (Burton et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, we did not find SLA to be a significant predictor of any flammability measure. As a follow up study, it would be interesting to examine how leaf traits influence the flammability of the leaf litter in agroforestry systems. This is particularly important to consider in Syntropic agroforestry given the importance of the \u0026ldquo;chop-and-drop\u0026rdquo; practice to produce mulch that is laid down on the crop rows. In order to counteract the effect of leaf litter in agroforests, the inclusion of a healthy ground cover is recommended as ground cover plants have a lower flammability and contribute to a higher moisture content in the soil and leaf litter that can prevent fire.\u003c/p\u003e \u003cp\u003eOur study also shows that leaf dry matter content (LDMC) is a significant predictor of burn time for groundcover and shrub as well as a significant predictor of the burnt biomass of groundcover and shrubs. This is consistent with the literature showing that leaves with a higher water content are more resistant to burning (Gill \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Potts et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eImplications for Farming Practices\u003c/h2\u003e \u003cp\u003eRegenerative farming is one way in which flammability of an agroforest can be reduced as growing low flammability species together will greatly decrease the chance of fire and growing low flammability species alongside more flammable ones can add a level of protection to more vulnerable plants. Syntropic agriculture is a good example of how less flammable and more flammable species can be grown together as there is a fairly even distribution of plants of each life form in a row due to the way syntropic farmers set up their rows following the principles of light stratification and succession (Andrade et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, perhaps a better alternative would be to find less flammable canopy species to take the place of the highly flammable \u003cem\u003eEucalyptus spp\u003c/em\u003e that is commonly grown in agroforestry systems. The predominant function of \u003cem\u003eEucalyptus spp.\u003c/em\u003e is a fast-growing and biomass-producing plant that is frequently pruned for mulch that could be filled by other non-flammable species such as moringa, jackfruit, or milky pine. Alternatively, management pruning of these plants should coincide with dry periods where fire risk is higher.\u003c/p\u003e \u003cp\u003eMonoculture farmers can also benefit from having an awareness of low flammability plants. Even if the creation of a regenerative forest is not in order, having non-flammable species growing among already established monoculture farms could greatly reduce the risk of fire. By planting non-flammable ground cover plants in the inter-row spaces among more flammable cash crop species such as mango and avocado, farmers can reduce the risk of fire spreading throughout their farms.\u003c/p\u003e \u003cp\u003eOne fire mitigation technique that may be helpful for both polyculture and monoculture systems would be the implementation of green firebreaks. Green firebreaks have long been used in China and have been shown to be highly effective in preventing high intensity fires (Cui et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). When green firebreaks are placed strategically around a property they act as barricades against oncoming fires, protecting properties and livelihoods. Construction of green firebreaks could also greatly improve safety of Australian civilians as research shows that many people, especially in rural areas, often choose to stay in their homes during wildfires in order to protect their property from damage (McGee and Russell \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Establishment of green firebreaks based on low flammability food plants could serve simultaneously as insurance against property damage and an economic resource for farmers.\u003c/p\u003e \u003cp\u003eGiven the increasing frequency and intensity of wildfires across Australia it is imperative that proactive steps are taken in order to lower the risk of fire spreading into agricultural and other human inhabited areas. Implementation of green firebreaks and inclusion of fire resistant species into agricultural lands, whether it be through the establishment of regenerative agroforests or the inclusion of non-flammable species in monoculture, will be necessary steps in moving toward fire resistant landscapes and protection of food systems.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAgricultural landscapes are facing increasing stresses from climate change, and elevated fire risk is one concerning trend in tropical agricultural regions. Establishing agroforestry systems can be a means of mitigating fire risk on farms, and our study has provided novel insights into the flammability of a number of tropical crop plants. By identifying a range of flammable and non-flammable plants of different lifeforms, we hope that farmers will be equipped with knowledge on selecting plants to grow that can help reduce the fire risk on their farms. Follow up studies on a wider range of crops plants from different growing zones, and particularly in dry tropical and semi-arid zones is imperative, and will enable us to tailor fire mitigation measures to suit specific climate settings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Neil \u0026amp; Jane Hawkes for their hospitality and permission to sample from their property. Thank you also to Margaret Moui, the staff of SFS, and Charlie Almeida.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interests \u003c/strong\u003eThe authors declare no conflict of interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge internal funding from the School for Field Studies which supported the project.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlam MA, Wyse SV, Buckley HL, Perry GL, Sullivan JJ, Mason NW, Buxton R, Richardson SJ, Curran TJ (2020) Shoot flammability is decoupled from leaf flammability, but controlled by leaf functional traits. 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Int J of Wildland Fire 25:466-477. https://doi.org/10.1071/WF15047\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"food forest, green firebreaks, leaf traits, plant flammability, Syntropics","lastPublishedDoi":"10.21203/rs.3.rs-2357569/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2357569/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eClimate change has increased drought and wildfire frequency in recent decades and poses a significant risk to agricultural lands and private property. Given the negative impact of fires on the livelihoods of farmers, it is crucial to assess the flammability of crop species and find ways of mitigating risk of fire in agricultural lands. We quantify the flammability of 66 tropical species of fiber, food, and spice crops by assessing maximum temperature, burn time, and burned biomass and assessed key leaf traits from a subset of these species to look at the interaction of leaf area (LA) and leaf dry matter content (LDMC) with life form type. We found groundcover, shrubs, and vines to be generally less flammable than canopy and subcanopy plants. We also found LDMC to be a consistent and significant predictor of all three flammability measures regardless of plant life form. Our results equips farmers and policy makers with information for constructing more fire resilient agricultural landscapes and pursuing nature-based solutions to mitigate fire risk, such as by planting green firebreaks with fire retardant species.\u003c/p\u003e","manuscriptTitle":"Fighting fire with food: Assessing the flammability of crop plant species for building fire resilient agroforestry systems","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-12-13 19:18:00","doi":"10.21203/rs.3.rs-2357569/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2aea91dc-27a0-405c-884c-1c1d597d04df","owner":[],"postedDate":"December 13th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-06-15T06:59:26+00:00","versionOfRecord":[],"versionCreatedAt":"2022-12-13 19:18:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2357569","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2357569","identity":"rs-2357569","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}