Advertisement

Topics

Spatiotemporal prediction of wildfire size extremes with Bayesian finite sample maxima.

08:00 EDT 13th April 2019 | BioPortfolio

Summary of "Spatiotemporal prediction of wildfire size extremes with Bayesian finite sample maxima."

Wildfires are becoming more frequent in parts of the globe, but predicting where and when wildfires occur remains difficult. To predict wildfire extremes across the contiguous United States, we integrate a 30 year wildfire record with meteorological and housing data in spatiotemporal Bayesian statistical models with spatially varying nonlinear effects. We compared different distributions for the number and sizes of large fires to generate a posterior predictive distribution based on finite sample maxima for extreme events (the largest fires over bounded spatiotemporal domains). A zero-inflated negative binomial model for fire counts and a lognormal model for burned areas provided the best performance. This model attains 99% interval coverage for the number of fires and 93% coverage for fire sizes over a six year withheld data set. Dryness and air temperature strongly predict extreme wildfire probabilities. Housing density has a hump-shaped relationship with fire occurrence, with more fires occurring at intermediate housing densities. Statistically, these drivers affect the chance of an extreme wildfire in two ways: by altering fire size distributions, and by altering fire frequency, which influences sampling from the tails of fire size distributions. We conclude that recent extremes should not be surprising, and that the contiguous United States may be on the verge of even larger wildfire extremes. This article is protected by copyright. All rights reserved.

Affiliation

Journal Details

This article was published in the following journal.

Name: Ecological applications : a publication of the Ecological Society of America
ISSN: 1051-0761
Pages: e01898

Links

DeepDyve research library

PubMed Articles [8775 Associated PubMed Articles listed on BioPortfolio]

Bayesian sample size determination for longitudinal studies with continuous response based on different scientific questions of interest.

Longitudinal study designs are commonly applied in much scientific research, especially in the medical, social, and economic sciences. Longitudinal studies allow researchers to measure changes in each...

Value of sample size for computation of the Bayesian information criterion (BIC) in multilevel modeling.

The Bayesian information criterion (BIC) can be useful for model selection within multilevel-modeling studies. However, the formula for the BIC requires a value for sample size, which is unclear in mu...

Bridging finite element and machine learning modeling: stress prediction of arterial walls in atherosclerosis.

Finite element and machine learning modeling are two predictive paradigms that have rarely been bridged. In this study, we develop a parametric model to generate arterial geometries and accumulate a d...

Variations of compound precipitation and temperature extremes in China during 1961-2014.

Concurrent precipitation and temperature extremes usually have significant impacts on the society, economy and ecosystem. Changes in precipitation or temperature extremes in China have been extensivel...

Accurately Predicting Total Knee Component Size without Preoperative Radiographs.

Preoperative templating of total knee arthroplasty (TKA) components can help in choosing appropriate implant size prior to surgery. While long limb radiographs have been shown to be beneficial in asse...

Clinical Trials [2582 Associated Clinical Trials listed on BioPortfolio]

OPTImization of the Dose of tacroliMUS by Bayesian Prediction

The pharmacokinetics of tacrolimus (TAC) are characterized by high inter- and intra-individual variability with narrow therapeutic range. Currently, the limiting point of Tac drug monitori...

Bayesian Hemodynamics Model for Personalized Monitoring of Congestive Heart Failure Patients

Heart failure (HF) is a serious and challenging syndrome. Globally 26 million people are living with this chronic disease and the prevalence is still increasing. Besides this growing numbe...

COmparison of MicroBiota AccordIng to Age in Crohn's Disease (COMeBACk)

The cause of CD could be different according to age at onset of CD symptoms. Indeed we know that some very young patients at CD diagnosis have particular genetic variants as abnormalities ...

Ultrasonography for Prediction of Difficult Intubation and Prediction of Endotracheal Tube Size

Aim of our study is to evaluate the predictive value of ultrasonographic (USG) measurement of thyrohyoid distance for difficult intubation and determination of optimal endotracheal tube si...

Variation of Spatiotemporal Parameters in School Children Carrying Different Backpack Loads

Backpacks (BP) represent the method most used by students to transport external cargo. Previous studies cite that between 4.7% and 38% of children carry daily BP loads greater than 20% of ...

Medical and Biotech [MESH] Definitions

Predicting the time of OVULATION can be achieved by measuring the preovulatory elevation of ESTRADIOL; LUTEINIZING HORMONE or other hormones in BLOOD or URINE. Accuracy of ovulation prediction depends on the completeness of the hormone profiles, and the ability to determine the preovulatory LH peak.

A computer based method of simulating or analyzing the behavior of structures or components.

Signaling ligands that act in opposition to NODAL PROTEIN. During vertebrate development they regulate the degree of left-right asymmetry by controlling the spatiotemporal influence of NODAL PROTEIN.

Relating to the size of solids.

The physical space or dimensions of a facility. Size may be indicated by bed capacity.

Advertisement
Quick Search
Advertisement
Advertisement

 


DeepDyve research library

Searches Linking to this Article