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Dryness thresholds for fire occurrence vary by forest type along an aridity gradient: evidence from Southern Australia

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Abstract

Context

Wildfires are common in localities where there is sufficient productivity to allow the accumulation of biomass combined with seasonality that allows this to dry and transition to a flammable state. An understanding of the conditions under which vegetated landscapes become flammable is valuable for assessing fire risk and determining how fire regimes may alter with climate change.

Objectives

Weather based metrics of dryness are a standard approach for estimating the potential for fires to occur in the near term. However, such approaches do not consider the contribution of vegetation communities. We aim to evaluate differences in weather-based dryness thresholds for fire occurrence between vegetation communities and test whether these are a function of landscape aridity.

Methods

We analysed dryness thresholds (using Drought Factor) for fire occurrence in six vegetation communities using historic fires events that occurred in South-eastern Australia using logistic regression. These thresholds were compared to the landscape aridity for where the communities persist.

Results

We found that dryness thresholds differed between vegetation communities, and this effect could in part be explained by landscape aridity. Dryness thresholds for fire occurrence were lower in vegetation communities that occur in arid environments. These communities were also exposed to dry conditions for a greater proportion of the year.

Conclusions

Our findings suggest that vegetation driven feedbacks may be an important driver of landscape flammability. Increased consideration of vegetation properties in fire danger indices may provide for better estimates of landscape fire risk and allow changes to fire regimes to be anticipated.

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Data availability

Fire and vegetation data can be accessed at http://www.data.vic.gov.au. Aridity data can be accessed at http://www.cgiar-csi.org/data/global-aridity-and-pet-database. Australian rainfall data can be accessed at http://www.bom.gov.au/jsp/ncc/climate_averages/rainfall/index.jsp.

References

  • Archibald S, Roy DP, vanWilgen BW, Scholes RJ (2009) What limits fire? An examination of drivers of burnt area in Southern Africa. Global Change Biol 15(3):613–630

    Article  Google Scholar 

  • Barbet-Massin M, Jiguet F, Albert Cécile H, Thuiller W (2012) Selecting pseudo-absences for species distribution models: how, where and how many? Methods Ecol Evol 3(2):327–338

    Article  Google Scholar 

  • Barton K (2018) MuMIn: Multi-Model Inference. R package version 1.40.4 edn

  • Bates D, Mächler M, Bolker B, Walker S (2015) Fitting linear mixed-effects models using lme4. J Stat Softw 67(1):48

    Article  Google Scholar 

  • Beverly JL, Wotton BM (2007) Modelling the probability of sustained flaming: predictive value of fire weather index components compared with observations of site weather and fuel moisture conditions. Int J Wildland Fire 16(2):161–173

    Article  Google Scholar 

  • Birk EM, Simpson RW (1980) Steady state and the continuous input model of litter accumulation and decomposition in Australian Eucalypt forests. Ecology 61(3):481–485

    Article  Google Scholar 

  • Bond WJ, Keeley JE (2005) Fire as a global `herbivore’: the ecology and evolution of flammable ecosystems. Trends Ecol Evol 20(7):387–394

    Article  PubMed  Google Scholar 

  • Bowman DMJS, French BJ, Prior LD (2014a) Have plants evolved to self-immolate? Front Plant Sci 5:590

    Article  PubMed  PubMed Central  Google Scholar 

  • Bowman DMJS, Murphy BP, Neyland DLJ, Williamson GJ, Prior LD (2014b) Abrupt fire regime change may cause landscape-wide loss of mature obligate seeder forests. Glob Change Biol 20(3):1008–1015

    Article  Google Scholar 

  • Bowman DMJS, Murphy BP, Williamson GJ, Cochrane MA (2014c) Pyrogeographic models, feedbacks and the future of global fire regimes. Glob Ecol Biogeogr 23(7):821–824

    Article  Google Scholar 

  • Bradstock RA (2010) A biogeographic model of fire regimes in Australia: current and future implications. Glob Ecol Biogeogr 19(2):145–158

    Article  Google Scholar 

  • Brown JK, Marsden MA, Ryan KC, Reinhardt ED (1985) Predicting duff and woody fuel consumed by prescribed fire in the northern Rocky Mountains. In: Intermountain Forest and Range Experiment Station (ed), Research Paper, INT-337. Forest Service, U.S. Department of Agriculture, Ogden, Utah

  • Brown T, Mills G, Harris S, Podnar D, Reinhold H, Fearon M (2016) A bias corrected WRF mesoscale fire weather dataset for Victoria, Australia 1972-2012. J South Hemisph Earth Syst Sci 66(3):281–313

    Google Scholar 

  • Burnham KP (2004) Multimodel inference—understanding AIC and BIC in model selection. Sociol Methods Res 33(2):261–304

    Article  Google Scholar 

  • Byram GM (1959) Forest fire behavior. In: Davis KP (ed) Forest fire: control and use. McGraw Hill Book Company Inc, New York, pp 90–123

    Google Scholar 

  • Caccamo G, Chisholm LA, Bradstock RA, Puotinen ML (2012) Using remotely-sensed fuel connectivity patterns as a tool for fire danger monitoring. Geophys Res Lett 39(1):L01302

    Article  Google Scholar 

  • Cawson JG, Duff TJ, Swan MH, Penman TD (2018) Wildfire in wet sclerophyll forests: the interplay between disturbances and fuel dynamics. Ecosphere 9(5):e02211

    Article  Google Scholar 

  • Cawson JG, Duff TJ, Tolhurst KG, Baillie CC, Penman TD (2017) Fuel moisture in Mountain Ash forests with contrasting fire histories. For Ecol Manag 400:568–577

    Article  Google Scholar 

  • Cheal DC (2010) Growth stages and tolerable fre intervals for Victoria’s native vegetation data sets. In: Department of Sustainability and Environment (ed), Research Report 84, 84. Arthur Rylah Institute for Environmental Research Melbourne

  • Chuvieco E, Aguado I, Dimitrakopoulos AP (2004) Conversion of fuel moisture content values to ignition potential for integrated fire danger assessment. Can J For Res 34(11):2284–2293

    Article  Google Scholar 

  • Clark JS (1988) Effect of climate change on fire regimes in northwestern Minnesota. Nature 334(6179):233–235

    Article  Google Scholar 

  • Cohen JD, Deeming JE (1985) The national fire danger rating system: basic equations. In: Pacific Southwest Forest and Range Experiment Station (ed), General Technical Report, PSW-82. Forest Service, U.S. Department of Agriculture, Berkeley, California

  • Collins KM, Price OF, Penman TD (2015) Spatial patterns of wildfire ignitions in south-eastern Australia. Int J Wildland Fire 24(8):1098–1108

    Article  Google Scholar 

  • Costermans L (2009) Native trees and shrubs of South-Eastern Australia. New Holland Chatswood, Australia

    Google Scholar 

  • Cruz MG, McCaw WL, Anderson WR, Gould JS (2012a) Fire behaviour modelling in semi-arid mallee-heath shrublands of southern Australia. Environ Model. Software(0)

  • Cruz MG, Sullivan AL, Gould JS, Sims NC, Bannister AJ, Hollis JJ, Hurley RJ (2012b) Anatomy of a catastrophic wildfire: the Black Saturday Kilmore East fire in Victoria, Australia. For Ecol Manage (284):269–285

    Article  Google Scholar 

  • Davies C (1997) Analysis of fire causes on or threathening public land in Victoria, 1977—1996. In: environment D. o. N. r. a. (ed), Fire management branch research report

  • Davies JB, Oates AM, Trumbull-Ward AV (2002) Ecological Vegetation Class mapping at 1:25 000 in Gippsland: final report. Department of Natural Resources and Environment, East Melbourne, Victoria

  • Dennison PE, Moritz MA (2009) Critical live fuel moisture in chaparral ecosystems: a threshold for fire activity and its relationship to antecedent precipitation. Int J Wildland Fire 18(8):1021–1027

    Article  Google Scholar 

  • Dimitrakopoulos AP (2001) A statistical classification of Mediterranean species based on their flammability components. Int J Wildland Fire 10(2):113–118

    Article  Google Scholar 

  • Dimitrakopoulos AP, Mitsopoulos ID, Gatoulas K (2010) Assessing ignition probability and moisture of extinction in a Mediterranean grass fuel. Int J Wildland Fire 19(1):29–34

    Article  Google Scholar 

  • Dimitrakopoulos AP, Papaioannou KK (2001) Flammability assessment of Mediterranean forest fuels. Fire Technol 37(2):143–152

    Article  Google Scholar 

  • Department of Environment Land Water and Planning (DELWP) (2016) EVC benchmarks. Department of Environment Land Water and Planning, Melbourne, Australia

    Google Scholar 

  • Dowdy AJ, Mills GA, Finkele K, de Groot W (2009) Australian fire weather as represented by the McArthur forest fire danger index and the Canadian forest fire weather index. The Centre for Australian Weather and Climate Research, Melbourne

    Google Scholar 

  • Duff TJ, Bell TL, York A (2012) Predicting continuous variation in forest fuel load using biophysical models: a case study in south-eastern Australia. Int J Wildland Fire 22:318–332

    Article  Google Scholar 

  • Duff TJ, Keane RE, Penman TD, Tolhurst KG (2017) Revisiting wildland fire fuel quantification methods: the challenge of understanding a dynamic, biotic entity. Forests 8(9):351

    Article  Google Scholar 

  • Fagg P, Lutze M, Slijkerman C, Ryan M, Bassett O (2013) Silvicultural recovery in ash forests following three recent large bushfires in Victoria. Aust For 76(3–4):140–155

    Article  Google Scholar 

  • Fawcett T (2006) An introduction to ROC analysis. Pattern Recog Lett 27(8):861–874

    Article  Google Scholar 

  • Fernandes PM, Cruz MG (2012) Plant flammability experiments offer limited insight into vegetation–fire dynamics interactions. 3. New Phytologist Trust, pp. 606

  • Finkele K, Mills GA, Beard G, Jones DA (2006) National daily gridded soil moisture deficit and drought factors for use in prediction of Forest Fire Danger Index in Australia. BMRC research report: no. 119 (June 2006). Melbourne : Bureau of Meteorology, 2006

  • Finney MA, Cohen JD, McAllister SS, Jolly WM (2013) On the need for a theory of wildland fire spread. Int J Wildland Fire 22(1):25–36

    Article  Google Scholar 

  • Fletcher M-S, Wood SW, Haberle SG (2014) A fire-driven shift from forest to non-forest: evidence for alternative stable states? Ecology 95(9):2504–2513

    Article  Google Scholar 

  • Gill AM, McCarthy MA (1998) Intervals between prescribed fires in Australia: what intrinsic variation should apply? Biol Conserv 85:161–169

    Article  Google Scholar 

  • Gill AM, Moore PH (1996) The ignitability of leaves of australian plants. Canberra, ACT

    Google Scholar 

  • Gould JS, McCaw LW, Cheney PN (2011) Quantifying fine fuel dynamics and structure in dry eucalypt forest (Eucalyptus marginata) in Western Australia for fire management. For Ecol Manage 262(3):531–546

    Article  Google Scholar 

  • Hantson S, Pueyo S, Chuvieco E (2015) Global fire size distribution is driven by human impact and climate. Glob Ecol Biogeogr 24(1):77–86

    Article  Google Scholar 

  • Harris S, Mills G, Brown T (2017) Variability and drivers of extreme fire weather in fire-prone areas of south-eastern Australia. Int J Wildland Fire 26(3):177–190

    Article  Google Scholar 

  • Hennessy K, Lucas C, Nicholls N, Bathols J, Suppiah R, Ricketts J (2005) Climate change impacts on fire-weather in south-east Australia. In: CSIRO (ed), CSIRO. Aspendale, Victoria

  • Holgate CM, van Dijk AIJM, Cary GJ, Yebra M (2017) Using alternative soil moisture estimates in the McArthur Forest Fire Danger Index. Int J Wildland Fire 26(9):806–819

    Article  Google Scholar 

  • Hoyer S, Hamman J (2017) xarray: N-D labeled arrays and datasets in python. J Open Res Softw 5:10–16

    Article  Google Scholar 

  • Keane RE (2015) Wildland Fuel Fundamentals and Applications. Springer, New York

    Book  Google Scholar 

  • Keetch JJ, Byram GM (1968) A drought index for forest fire control. In: Southeastern Forest Experiment Station (ed), Reseach paper, SE-38. Forest Service, U.S. Department of Agriculture, Ashville, North Carolina

  • Kitzberger T, Perry GLW, Paritsis J, Gowda JH, Tepley AJ, Holz A, Veblen TT (2016) Fire–vegetation feedbacks and alternative states: common mechanisms of temperate forest vulnerability to fire in southern South America and New Zealand. N Z J Bot 54(2):247–272

    Article  Google Scholar 

  • Knowles JE, Frederick C (2016) merTools: tolls for analyzing mixed effect regression models

  • Krawchuk MA, Moritz MA (2011) Constraints on global fire activity vary across a resource gradient. Ecology 92(1):121–132

    Article  PubMed  Google Scholar 

  • Krueger ES, Ochsner TE, Carlson JD, Engle DM, Twidwell D, Fuhlendorf SD (2016) Concurrent and antecedent soil moisture relate positively or negatively to probability of large wildfires depending on season. Int J Wildland Fire 25(6):657–668

    Article  Google Scholar 

  • Larjavaara M, Kuuluvainen T, Tanskanen H, Venäläinen A (2004) Variation in forest fire ignition probability in Finland. Silva Fenn Monogr 38(3):253–256

    Google Scholar 

  • Long M (2006) A climatology of extreme fire weather days in Victoria. Aust Meteorol Mag 55:3–18

    Google Scholar 

  • Matthews S (2009) A comparison of fire danger rating systems for use in forests. Aust Met Ocean J 58(1):41–48

    Google Scholar 

  • Matthews S (2013) Dead fuel moisture research: 1991–2012. Int J Wildland Fire 23(1):78–92

    Article  Google Scholar 

  • Matthews S, Sullivan AL, Watson P, Williams RJ (2012) Climate change, fuel and fire behaviour in a eucalypt forest. Glob Change Biol 18(10):3212–3223

    Article  Google Scholar 

  • McAllister S, Finney M Convection ignition of live forest fuels. In: Fire safety science-proceedings of the eleventh international symposium Canterbury, New Zealand. 2014. International association for fire safety science, p. 1312–1325

  • McArthur AG (1967) Fire behaviour in Eucalypt forests. Leaflet 107. Forestry and Timber Bureau, Department of National Development, Canberra, Australia

  • McCarthy MA, Gill AM, Bradstock RA (2001) Theoretical fire interval distributions. Int J Wildland Fire 10:73–77

    Article  CAS  Google Scholar 

  • McCarthy GJ, Plucinski M, Gould J (2012) Analysis of the resourcing and containment of multiple remote fires: the Great Divide Complex of fires, Victoria, December 2006. Aust For 75(1):54–63

    Article  Google Scholar 

  • McCarthy GJ, Tolhurst KG, Wouters M (2003) Prediction of firefighting resources for suppression operations in Victorias parks and forests. Fire Management Research Report, 56. Department of Sustainability and Environment

  • McWethy DB, Higuera PE, Whitlock C, Veblen TT, Bowman DMJS, Cary GJ, Haberle SG, Keane RE, Maxwell BD, McGlone MS, Perry GLW, Wilmshurst JM, Holz A, Tepley AJ (2013) A conceptual framework for predicting temperate ecosystem sensitivity to human impacts on fire regimes. Global Ecol Biogeogr 22(8):900–912  

    Article  Google Scholar 

  • Mooney H, Dunn L (1970) Convergent evolution of Mediterranean climate evergreen sclerophyll shrubs. Evolution 42(2):292–303

    Article  Google Scholar 

  • Murphy BP, Bradstock RA, Boer MM, Carter J, Cary GJ, Cochrane MA, Fensham RJ, Russell-Smith J, Williamson GJ, Bowman DMJS (2013) Fire regimes of Australia: a pyrogeographic model system. J Biogeogr 40(6):1048–1058  

    Article  Google Scholar 

  • 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(11):1–8

    Article  CAS  Google Scholar 

  • Noble IR, Gill AM, Bary GAV (1980) McArthur’s fire-danger meters expressed as equations. Austral Ecol 5(2):201–203

    Article  Google Scholar 

  • Nolan RH, Boer MM, Resco de Dios V, Caccamo G, Bradstock RA (2016) Large-scale, dynamic transformations in fuel moisture drive wildfire activity across southeastern Australia. Geophys Res Lett 43(9):4229–4238

    Article  Google Scholar 

  • Nowacki GJ, Abrams MD (2008) The demise of fire and “mesophication” of forests in the eastern United States. Bioscience 58(2):123–138

    Article  Google Scholar 

  • Nyman P, Baillie CC, Duff TJ, Sheridan GJ (2018) Eco-hydrological controls on microclimate and surface fuel evaporation in complex terrain. Agric For Meteorol 252:49–61

    Article  Google Scholar 

  • Nyman P, Metzen D, Hawthorne SND, Duff TJ, Inbar A, Lane PNJ, Sheridan GJ (2017) Evaluating models of shortwave radiation below Eucalyptus canopies in SE Australia. Agric For Meteorol 246:51–63

    Article  Google Scholar 

  • Olson JS (1963) Energy storage and the balance of producers and decomposers in ecological systems. Ecology 44(2):322–331

    Article  Google Scholar 

  • Pausas JG (2004) Changes in fire and climate in the eastern Iberian Peninsula (Mediterranean Basin). Clim Change 63(3):337–350

    Article  Google Scholar 

  • Pausas JG, Keeley JE, Schwilk DW (2016) Flammability as an ecological and evolutionary driver. J. Ecol 105(2):289–297

    Article  Google Scholar 

  • Pausas JG, Paula S (2012) Fuel shapes the fire-climate relationship: evidence from Mediterranean ecosystems. Global Ecol. Biogeogr 11:1074

    Article  Google Scholar 

  • Pausas JG, Ribeiro E (2013) The global fire-productivity relationship. Glob Ecol Biogeogr 22(6):728–736

    Article  Google Scholar 

  • Penman TD, York A (2010) Climate and recent fire history affect fuel loads in Eucalyptus forests: implications for fire management in a changing climate. For Ecol Manage 260(10):1791–1797

    Article  Google Scholar 

  • Perry GLW (1998) Current approaches to modelling the spread of wildland fire: a review. Prog Phys Geogr 22(2):222–245

    Article  Google Scholar 

  • Podur J, Wotton M (2010) Will climate change overwhelm fire management capacity? Ecol Model 221(9):1301–1309

    Article  Google Scholar 

  • R Development Core Team (2017) R: A language and environment for statistical computing. 3.4.2 edn. R Foundation for Statistical Computing, Vienna, Austria

  • Raupach MR, Briggs PR, Haverd V, King EA, Paget M, Trudinger CM (2009) Australian Water Availability Project (AWAP): CSIRO Marine and Atmospheric Research Component: Final Report for Phase 3. Melbourne, Australia

  • Riccardi CL, Ottmar RD, Sandberg DV, Andreu A, Elman E, Kopper K, Long J (2007) The fuelbed: a key element of the Fuel Characteristic Classification System. Can J For Res 37(12):2394–2412  

    Article  Google Scholar 

  • Riley KL, Abatzoglou JT, Grenfell IC, Klene AE, Heinsch FA (2013) The relationship of large fire occurrence with drought and fire danger indices in the western USA, 1984–2008: the role of temporal scale. Int J Wildland Fire 22(7):894–909

    Article  Google Scholar 

  • Rossa CG (2017) The effect of fuel moisture content on the spread rate of forest fires in the absence of wind or slope. Int J Wildland Fire 26(1):24–31

    Article  Google Scholar 

  • Rousseeuw PJ, Ruts I, Tukey JW (1999) The bagplot: a bivariate boxplot. American Stat 53(4):382–387

    Google Scholar 

  • Schunk C, Wastl C, Leuchner M, Menzel A (2017) Fine fuel moisture for site- and species-specific fire danger assessment in comparison to fire danger indices. Agric For Meteorol 234–235:31–47

    Article  Google Scholar 

  • Simpson KJ, Ripley BS, Christin P-A, Belcher CM, Lehmann CER, Thomas GH, Osborne CP (2016) Determinants of flammability in savanna grass species. J. Ecol. 104(1):138–148

    Article  PubMed  Google Scholar 

  • Sullivan AL (2009) Wildland surface fire spread modelling, 1990–2007. 2: empirical and quasi-empirical models. Int J Wildland Fire 18(4):369–386

    Article  Google Scholar 

  • Sullivan AL (2017) Inside the Inferno: Fundamental Processes of Wildland Fire Behaviour. Part 2: heat transfer and interactions. Curr For Rep 3(2):150–171

  • Taylor SW, Alexander ME (2006) Science, technology, and human factors in fire danger rating: the Canadian experience. Int J Wildland Fire 15(1):121–135

    Article  Google Scholar 

  • Tepley AJ, Thomann E, Veblen TT, Perry GL, Holz A, Paritsis J, Kitzberger T, Anderson-Teixeira KJ (2018) Influences of fire–vegetation feedbacks and post-fire recovery rates on forest landscape vulnerability to altered fire regimes. J. Ecol. https://doi.org/10.1111/1365-2745.12950

    Article  Google Scholar 

  • Tepley AJ, Veblen TT, Perry GLW, Stewart GH, Naficy CE (2016) Positive feedbacks to fire-driven deforestation following human colonization of the South Island of New Zealand. Ecosystems 19(8):1325–1344

    Article  Google Scholar 

  • van Wagner CE (1974) Structure of the Candadian forest fire weather index. Fo47-1333. Canadian Forestry Service, Ottawa, Canada

  • Venables WN, Ripley BD (2002) Modern applied statistics with S. Springer, New York

    Book  Google Scholar 

  • Walsh SF, Nyman P, Sheridan GJ, Baillie CC, Tolhurst KG, Duff TJ (2017) Hillslope-scale prediction of terrain and forest canopy effects on temperature and near-surface soil moisture deficit. Int. J. Wildland Fire 26(3):191–208

    Article  Google Scholar 

  • Weise DR, Zhou X, Sun L, Mahalingam S (2005) Fire spread in chaparral—‘go or no-go?’. Int J Wildland Fire 14(1):99–106

    Article  Google Scholar 

  • Wickham H (2011) The split-apply-combine strategy for data analysis. J Stat Softw 1(1):1–29

    Google Scholar 

  • Wolf HP, Bielefeld U (2014) aplpack: Another Plot PACKage: stem.leaf, bagplot, faces, spin3R, plotsummary, plothulls, and some slider functions. R package version 1.3.0 edn

  • Wood SW, Bowman DMJS (2012) Alternative stable states and the role of fire–vegetation–soil feedbacks in the temperate wilderness of southwest Tasmania. Landscape Ecol 27(1):13–28

    Article  Google Scholar 

  • Wotton BM, Nock CA, Flannigan MD (2010) Forest fire occurrence and climate change in Canada. Int J Wildland Fire 19(3):253–271

    Article  Google Scholar 

  • Wyse SV, Perry GLW, O’Connell DM, Holland PS, Wright MJ, Hosted CL, Whitelock SL, Geary IJ, Maurin KJL, Curran TJ (2016) A quantitative assessment of shoot flammability for 60 tree and shrub species supports rankings based on expert opinion. Int J Wildland Fire 25(4):466–477

    Google Scholar 

  • Xu CY, Singh VP (2000) Evaluation and generalization of radiation-based methods for calculating evaporation. Hydrol Process 14(2):339–349

    Article  Google Scholar 

  • Zomer RJ, Trabucco A, Bossio DA, van Straaten O, Verchot LV (2008) Climate change mitigation: a spatial analysis of global land suitability for clean development mechanism afforestation and reforestation. Agr Ecosyst Environ 126:67–80

    Article  Google Scholar 

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Acknowledgements

This work was undertaken as part of the project ‘Flammability of Tall Mist Forests’ which was funded via the Victorian Department of Environment, Land, Water and Planning (DELWP) and the Bushfire Climatology Project funded by DELWP and managed and administered by the Bushfire and Natural Hazards Cooperative Research Centre. Data were sourced from the Victorian Government data repository and the Department of Environment, Land, Water and Planning. We gratefully acknowledge the contribution of Miguel Cruz and Trent Penman in improving this manuscript, as well as the contribution of our anonymous referees.

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  1. Faculty of Science, School of Ecosystem and Forest Sciences, The University of Melbourne, Burnley, 3121, Australia

    Thomas J. Duff & Jane G. Cawson

  2. Faculty of Science, School of Earth, Atmosphere and Environment, Monash University, Clayton, 3168, Australia

    Sarah Harris

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  1. Thomas J. Duff
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TD and JC conceived the ideas and designed methodology; TD and SH collected and analysed the data; TD led the writing of the manuscript. All authors contributed critically to the drafts and gave final approval for publication. All data will be archived on University servers.

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Correspondence to Thomas J. Duff.

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Duff, T.J., Cawson, J.G. & Harris, S. Dryness thresholds for fire occurrence vary by forest type along an aridity gradient: evidence from Southern Australia. Landscape Ecol 33, 1369–1383 (2018). https://doi.org/10.1007/s10980-018-0655-7

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