04732nam 2201225z- 450 991055738710332120231214132816.0(CKB)5400000000042027(oapen)https://directory.doabooks.org/handle/20.500.12854/76454(EXLCZ)99540000000004202720202201d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierForest Fire Risk PredictionBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 electronic resource (235 p.)3-0365-1474-0 3-0365-1473-2 Globally, fire regimes are being altered by changing climatic conditions and land use changes. This has the potential to drive species extinctions and cause ecosystem state changes, with a range of consequences for ecosystem services. Accurate prediction of the risk of forest fires over short timescales (weeks or months) is required for land managers to target suppression resources in order to protect people, property, and infrastructure, as well as fire-sensitive ecosystems. Over longer timescales, prediction of changes in forest fire regimes is required to model the effect of wildfires on the terrestrial carbon cycle and subsequent feedbacks into the climate system.This was the motivation to publish this book, which is focused on quantifying and modelling the risk factors of forest fires. More specifically, the chapters in this book address four topics: (i) the use of fire danger metrics and other approaches to understand variation in wildfire activity; (ii) understanding changes in the flammability of live fuel; (iii) modeling dead fuel moisture content; and (iv) estimations of emission factors.The book will be of broad relevance to scientists and managers working with fire in different forest ecosystems globally.Research & information: generalbicsscBiology, life sciencesbicsscForestry & related industriesbicsscfire danger ratingfire managementfire regimefire sizefire weatherPortugalcritical LFMC thresholdforest/grassland fireradiative transfer modelremote sensingsouthwest Chinaacid rainaerosolbiomass burningforest firePM2.5direct estimationmeteorological factor regressionmoisture contenttime lagforest fire driving factorsforest fire occurrencerandom forestforest fire managementChinaCupressus sempervirensfire riskfuelsfuel moisture contentmass loss calorimeterSeiridium cardinalevulnerability to wildfiresdiseasealien pathogenallochthonous speciesintroduced fungusdrying testshumidity diffusion coefficientswildfireprescribed burningmodelingdroughtflammabilityfuel moistureleaf water potentialplant traitsclimate changeMNIfire seasonfire behaviorcrown firefire modelingsenescencefoliar moisture contentcanopy bulk densityfire dangerfire weather patternsRCPFWI systemSSRoccurrence of forest firemachine learningvariable importanceprediction accuracyepicormic resproutereucalyptusfire severityflammability feedbackstemperate forestResearch & information: generalBiology, life sciencesForestry & related industriesNolan Rachaeledt1311915Resco de Dios VíctoredtNolan RachaelothResco de Dios VíctorothBOOK9910557387103321Forest Fire Risk Prediction3030555UNINA