Spatial and temporal extremes of wildfire sizes in Portugal (1984–2004)

2009 ◽  
Vol 18 (8) ◽  
pp. 983 ◽  
Author(s):  
P. de Zea Bermudez ◽  
J. Mendes ◽  
J. M. C. Pereira ◽  
K. F. Turkman ◽  
M. J. P. Vasconcelos
Keyword(s):  
Generalized Pareto Distribution ◽  
Fire Regimes ◽  
Temporal Analysis ◽  
Extreme Value Statistics ◽  
Spatial And Temporal Patterns ◽  
Burned Areas ◽  
Environmental Correlates ◽  
Original Dataset ◽  
Large Fires ◽  
Landsat Satellite

Spatial and temporal patterns of large fire (>100 ha) incidence in Portugal over the period 1984–2004 were modeled using extreme value statistics, namely the Peaks Over Threshold approach, which uses the Generalized Pareto Distribution (GPD) as a model. The original dataset includes all fires larger than 5 ha (30 616 fires) that were observed in Portugal during the study period, mapped from Landsat satellite imagery. The country was divided into eight regions, considered internally homogeneous from the perspective of their fire regimes and respective environmental correlates. The temporal analysis showed that there does not appear to be any trend in the incidence of very large fires, but revealed a cyclical behavior in the values of the GPD shape parameter, with a period in the range of 3 to 5 years. Spatial analysis highlighted strong regional differences in the incidence of large fires, and allowed the calculation of return levels for a range of fire sizes. This analysis was affected by the presence of a few outlying observations, which may correspond to clusters of contiguous fire scars, resulting in artificially large burned areas. We discuss some of the implications of our findings in terms of consequences for fire management aimed at preventing the occurrence of extremely large fires, and present ideas for extending the present study.

Spatial pattern analyses of post-fire residual stands in the black spruce boreal forest of western Quebec

2010 ◽  
Vol 19 (8) ◽  
pp. 1110 ◽  
Author(s):  
Amar Madoui ◽  
Alain Leduc ◽  
Sylvie Gauthier ◽  
Yves Bergeron
Keyword(s):  
Black Spruce ◽  
Weather Conditions ◽  
Spatial Analyses ◽  
Fire Size ◽  
The West ◽  
Forest Patches ◽  
Burned Areas ◽  
Large Fires ◽  
The Many ◽  
Landsat Satellite

In this study, we characterised the composition and configuration of post-fire residual habitats belonging to two physiographic zones of the black spruce–moss domain in western Quebec. Thirty-three large fires (2000–52 000 ha) were selected and extracted on classified Landsat satellite imagery. The results show that a minimum of 2% and a maximum of 22% of burned areas escaped fire, with an overall average of 10.4%. The many forest patches that partially or entirely escaped fire formed residual habitats (RHs). It was found that although the area of RHs follows a linear relationship with fire size, their proportion appears relatively constant. Spatial analyses showed that the fires could be separated into two groups depending on the physiographic zones (East-Canadian Shield v. West-Clay Belt Lowlands). Fires in the west zone generate less RHs and appear to be associated with more extreme weather conditions. In most cases there was no association with water or wetlands; in some fires the presence of RHs is associated with the proximity of water bodies. The failure to find an association between RHs and wetlands suggests that this type of environment is part of the fuel. Coniferous woodland with moss appears particularly overrepresented within RHs. Our results suggest that the local and regional physiographic conditions strongly influence the creation of RHs; therefore, it is important to consider those differences when applying ecosystem-based management.

scholarly journals Analysis fire patterns and drivers with a global SEVER-FIRE model incorporated into Dynamic Global Vegetation Model and satellite and on-ground observations

2018 ◽  
Author(s):  
Sergey Venevsky ◽  
Yannick Le Page ◽  
José M. C. Pereira ◽  
Chao Wu
Keyword(s):  
Regional Scale ◽  
Atmospheric Composition ◽  
Spatial And Temporal Patterns ◽  
Dynamic Global Vegetation Model ◽  
Fire Model ◽  
Burned Areas ◽  
Large Fires ◽  
Vegetation Models ◽  
Global Vegetation ◽  
Fire Incidence

Abstract. Biomass burning is an important environmental process with a strong influence on vegetation and on the atmospheric composition. It competes with microbes and herbivores to convert biomass to CO2 and it is a major contributor of gases and aerosols to the atmosphere. To better understand and predict global fire occurrence, fire models have been developed and coupled to Dynamic Global Vegetation Models (DGVMs) and Earth System Models (ESMs). We present SEVER-FIRE (Socio-Economic and natural Vegetation ExpeRimental global fire model which is incorporated into the SEVER-DGVM. One of the major focuses of SEVER-FIRE model is an implementation of pyrogenic behaviour of humans (timing of their activities and their willingness/necessity to ignite or supress fire), related to socio-economic and demographic conditions in a geographical domain of the model application. Burned areas and emissions from the SEVER model are compared to the Global Fire Emission Database version 2 (GFED), derived from satellite observations, while number of fires are compared with regional historical fire statistics. We focus both on the model output accuracy and on its assumptions regarding fire drivers, and perform: 1– An evaluation of the predicted spatial and temporal patterns, focusing on fire incidence, seasonality and inter-annual variability. 2– Analyses to evaluate the assumptions concerning the etiology, or causation, of fire, including climatic and anthropogenic drivers, as well as the type and amount of vegetation. SEVER reproduces the main features of climate driven inter-annual fire variability at a regional scale, such as the large fires associated with the 1997–98 El Niño event in Indonesia, Central and South America, which had critical ecological and atmospheric impacts. Spatial and seasonal patterns of fire incidence reveal some model inaccuracies, and we discuss the implications of the distribution of vegetation types inferred by the DGVM, and of assumed proxies of human fire practices. We further suggest possible development directions, to enable such models to better project future fire activity.

scholarly journals Analysis fire patterns and drivers with a global SEVER-FIRE v1.0 model incorporated into dynamic global vegetation model and satellite and on-ground observations

2019 ◽  
Vol 12 (1) ◽  
pp. 89-110 ◽  
Author(s):  
Sergey Venevsky ◽  
Yannick Le Page ◽  
José M. C. Pereira ◽  
Chao Wu
Keyword(s):  
Regional Scale ◽  
Atmospheric Composition ◽  
Spatial And Temporal Patterns ◽  
Dynamic Global Vegetation Model ◽  
Burned Areas ◽  
Large Fires ◽  
Dynamic Global Vegetation Models ◽  
Vegetation Models ◽  
Global Vegetation ◽  
Fire Incidence

Abstract. Biomass burning is an important environmental process with a strong influence on vegetation and on the atmospheric composition. It competes with microbes and herbivores to convert biomass to CO2 and it is a major contributor of gases and aerosols to the atmosphere. To better understand and predict global fire occurrence, fire models have been developed and coupled to dynamic global vegetation models (DGVMs) and Earth system models (ESMs). We present SEVER-FIRE v1.0 (Socio-Economic and natural Vegetation ExpeRimental global fire model version 1.0), which is incorporated into the SEVER DGVM. One of the major focuses of SEVER-FIRE is an implementation of pyrogenic behavior of humans (timing of their activities and their willingness and necessity to ignite or suppress fire), related to socioeconomic and demographic conditions in a geographical domain of the model application. Burned areas and emissions from the SEVER model are compared to the Global Fire Emission Database version 2 (GFED), derived from satellite observations, while number of fires is compared with regional historical fire statistics. We focus on both the model output accuracy and its assumptions regarding fire drivers and perform (1) an evaluation of the predicted spatial and temporal patterns, focusing on fire incidence, seasonality and interannual variability; (2) analysis to evaluate the assumptions concerning the etiology, or causation, of fire, including climatic and anthropogenic drivers, as well as the type and amount of vegetation. SEVER reproduces the main features of climate-driven interannual fire variability at a regional scale, for example the large fires associated with the 1997–1998 El Niño event in Indonesia and Central and South America, which had critical ecological and atmospheric impacts. Spatial and seasonal patterns of fire incidence reveal some model inaccuracies, and we discuss the implications of the distribution of vegetation types inferred by the DGVM and of assumed proxies of human fire practices. We further suggest possible development directions to enable such models to better project future fire activity.

THE NEW RADIOCARBON DATASET FOR TRILITH MONUMENTS OF SOUTHEASTERN ARABIA

Radiocarbon ◽  
2020 ◽  
pp. 1-11
Author(s):  
R Garba ◽  
P Demján ◽  
I Svetlik ◽  
D Dreslerová
Keyword(s):  
Iron Age ◽  
Temporal Patterns ◽  
Temporal Analysis ◽  
Coastal Plains ◽  
Spatial And Temporal Patterns ◽  
Two Phase ◽  
Stone Monuments ◽  
South Central ◽  
Geographical Expansion ◽  
Spatio Temporal

ABSTRACT Triliths are megalithic monuments scattered across the coastal plains of southern and southeastern Arabia. They consist of aligned standing stones with a parallel row of large hearths and form a space, the meaning of which is undoubtedly significant but nonetheless still unknown. This paper presents a new radiocarbon (14C) dataset acquired during the two field seasons 2018–2019 of the TSMO (Trilith Stone Monuments of Oman) project which investigated the spatial and temporal patterns of the triliths. The excavation and sampling of trilith hearths across Oman yielded a dataset of 30 new 14C dates, extending the use of trilith monuments to as early as the Iron Age III period (600–300 BC). The earlier dates are linked to two-phase trilith sites in south-central Oman. The three 14C pairs collected from the two-phase trilith sites indicated gaps between the trilith construction phases from 35 to 475 years (2 σ). The preliminary spatio-temporal analysis shows the geographical expansion of populations using trilith monuments during the 5th to 1st century BC and a later pull back in the 1st and 2nd century AD. The new 14C dataset for trilith sites will help towards a better understanding of Iron Age communities in southeastern Arabia.

scholarly journals Spatial-Temporal Analysis of the Forest Fragments Surrounding a Conservation Unit in the Southern Region of Brazil

2020 ◽  
Vol 3 (1) ◽  
pp. 48
Author(s):  
Bianca Fernandes ◽  
Ligia Batista
Keyword(s):  
Nearest Neighbor ◽  
Temporal Analysis ◽  
Management Plan ◽  
Edge Density ◽  
Forest Fragments ◽  
Conservation Unit ◽  
Border Effect ◽  
Action Strategies ◽  
Landsat Satellite ◽  
High Degree

In recent years, anthropogenic actions have intensified forest fragmentation, causing several damages to the landscape’s natural components, propagating the loss of biodiversity. This study aims to present an analysis of the forest fragments in a conservation unit located at southern of Brazil. The evaluation was carried out for the years 1998, 2008, and 2018, by using landscape metrics and classification of remote sensing imagery of the Landsat satellite. The following metrics were analyzed: area and edge, shape, core area, and aggregation. The results indicated an increase of 16.88% in the total area of vegetation, and the percentage of fragments increased from 16.16% to 18.89%. The number of fragments decreased, resulting in an increase of the mean area in 5.4 ha. The percentage of vegetation under border effect changed from 40.2% to 37.1%. In 1998, the average nearest neighbor distance was 155.4 m, and in 2018, 149.7 m. However, this distance is still classified as a high degree of isolation, which hinders the movement of organisms and the dispersion of species. Thus, all the analyzed metrics indicated a decrease in the fragmentation, except for the edge density metric, in which its increase of 1.86 pointed to a lower degree of conservation during the analyzed period. A study of this nature is important as it provides subsidies for future researches and can contribute to action strategies to be adopted in the management plan of the area.

scholarly journals A Spatio‐Temporal Analysis of the Environmental Correlates of COVID‐19 Incidence in Spain

2020 ◽  
Author(s):  
Antonio Paez ◽  
Fernando A. Lopez ◽  
Tatiane Menezes ◽  
Renata Cavalcanti ◽  
Maira Galdino da Rocha Pitta
Keyword(s):  
Temporal Analysis ◽  
Environmental Correlates ◽  
Spatio Temporal

scholarly journals Avalanche risk evaluation and protective dam optimal design using extreme value statistics

2016 ◽  
Vol 62 (234) ◽  
pp. 725-749 ◽  
Author(s):  
PHILOMÈNE FAVIER ◽  
NICOLAS ECKERT ◽  
THIERRY FAUG ◽  
DAVID BERTRAND ◽  
MOHAMED NAAIM
Keyword(s):  
Optimal Design ◽  
Generalized Pareto Distribution ◽  
Sensitivity Study ◽  
Extreme Value Statistics ◽  
Generalized Pareto ◽  
Hazard Zoning ◽  
Design Values ◽  
Structure Flow ◽  
Long Term Forecasting ◽  
Interaction Law

ABSTRACTIn snow avalanche long-term forecasting, existing risk-based methods remain difficult to use in a real engineering context. In this work, we expand a quasi analytical decisional model to obtain simple formulae to quantify risk and to perform the optimal design of an avalanche dam in a quick and efficient way. Specifically, the exponential runout model is replaced by the Generalized Pareto distribution (GPD), which has theoretical justifications that promote its use for modelling the different possible runout tail behaviours. Regarding the defence structure/flow interaction, a simple law based on kinetic energy dissipation is compared with a law based on the volume stored upstream of the dam, whose flexibility allows us to cope with various types of snow. We show how a detailed sensitivity study can be conducted, leading to intervals and bounds for risk estimates and optimal design values. Application to a typical case study from the French Alps, highlights potential operational difficulties and how they can be tackled. For instance, the highest sensitivity to the runout tail type and interaction law is found at abscissas of legal importance for hazard zoning (return periods of 10–1000 a), a crucial result for practical purposes.

Effective fire suppression in boreal forests

2005 ◽  
Vol 35 (4) ◽  
pp. 772-786 ◽  
Author(s):  
S G Cumming
Keyword(s):  
Boreal Forests ◽  
Regression Models ◽  
Fire History ◽  
Fire Suppression ◽  
Fire Regimes ◽  
Operational Effectiveness ◽  
Logistic Regression Models ◽  
Area Burned ◽  
Large Fires ◽  
Northeastern Alberta

Fire suppression is (functionally) effective insofar as it reduces area burned. In North American boreal forests, fire regimes and historical records are such that this effect cannot be detected or estimated directly. I present an indirect approach, proceeding from the practice of initial attack (IA), which is intended to limit the proportion of "large" fires. I analysed IA's (operational) effectiveness by a controlled retrospective study of fire-history data for an approximately 86 000 km2 region of boreal forest in northeastern Alberta, Canada, from 1968 to 1998 (31 years). Over this interval, various improvements to IA practice, including a 1983 change in management strategy, created a natural experiment. I tested the results with multiple logistic regression models of the annual probabilities of a fire becoming larger than 3 and 200 ha. Annual fire counts (Nt) were a surrogate for fire weather and peak daily counts within years (arrival load). Measured by odds ratios, mean IA effectiveness against 3- and 200-ha fires increased in 1983 by factors of 2.02 (95% CI = 1.70–2.40) and 2.41 (95% CI = 1.69–3.45), respectively. Prior to 1983, the functional response to Nt was consistent with saturation of IA capacity at high arrival loads. From 1983–1998, effectiveness was independent of Nt. I introduce the proportional reduction in area burned (impact) as a measure of functional effectiveness and state conditions under which it can be estimated from the regression models. Over 1983–1998, if suppressed and actual fires were comparable, relative IA impact ([Formula: see text]) was 0.58 (95% CI = 0.34–0.74) and area burned was reduced by 457 500 ha. If fires larger than 1 × 105, 1 × 104, or 1 × 103 ha are assumed to be unpreventable, [Formula: see text] declines to 0.46, 025, or 0.08, respectively, but there is no evidence this is the case.

scholarly journals Effects of large fires on biodiversity in south-eastern Australia: disaster or template for diversity?

2008 ◽  
Vol 17 (6) ◽  
pp. 809 ◽  
Author(s):  
Ross A. Bradstock
Keyword(s):  
Large Scale ◽  
Fire Regimes ◽  
Ecological Communities ◽  
South Eastern ◽  
Habitat Variation ◽  
Eastern Australia ◽  
Rate Adaptive ◽  
Large Fires ◽  
South Eastern Australia

Large fires coincident with drought occurred in south-eastern Australia during 2001–2007. Perceptions of large, intense fires as being ecologically ‘disastrous’ are common. These are summarised by four hypotheses characterising large fires as: (i) homogenous in extent and intensity; (ii) causing large-scale extinction due to perceived lack of survival and regeneration capacity among biota; (iii) degrading due to erosion and related edaphic effects; (iv) unnatural, as a consequence of contemporary land management. These hypotheses are examined using available evidence and shown to inadequately account for effects of large fires on biodiversity. Large fires do not burn homogeneously, though they may produce intensely burnt patches and areas. The bulk of biota are resilient through a variety of in situ persistence mechanisms that are reinforced by landscape factors. Severe erosive episodes following fire tend to be local and uncertain rather than global and inevitable. Redistribution of soil and nutrients may reinforce habitat variation in some cases. Signals of fire are highly variable over prehistoric and historic eras, and, in some cases, contemporary and pre-European signal levels are equivalent. The most important effects of large fires in these diverse ecological communities and landscapes stem from their recurrence rate. Adaptive management of fire regimes rather than fire events is required, based on an understanding of risks posed by particular regimes to biota.

Big fires and their ecological impacts in Australian savannas: size and frequency matters

2008 ◽  
Vol 17 (6) ◽  
pp. 768 ◽  
Author(s):  
Cameron P. Yates ◽  
Andrew C. Edwards ◽  
Jeremy Russell-Smith
Keyword(s):  
Fire Regimes ◽  
Fire Frequency ◽  
Ecological Impacts ◽  
Thematic Mapper ◽  
Home Ranges ◽  
Size Distributions ◽  
Ecological Implications ◽  
Savanna Fires ◽  
Large Fires ◽  
Very High

Savannas are the most fire-prone of the earth’s major biomes. The availability of various broad-scale satellite-derived fire mapping and regional datasets provides a framework with which to examine the seasonality, extent and implications of large fires with particular reference to biodiversity values in the tropical savannas of northern Australia. We document the significance of savanna fires in the fire-prone ‘Top End’ region of the Northern Territory, Australia, using 9 years (1997–2005) of National Oceanic and Atmospheric Administration (NOAA)-Advanced Very High Resolution Radiometer (AVHRR)-, Landsat Thematic Mapper (TM)- and Enhanced Thematic Mapper (ETM+)-derived fire mapping. Fire (patch) sizes from both AVHRR- and Landsat-scale mapping increased through the calendar year associated with progressive curing of grass and litter fuels. Fire frequency data at both satellite sensor scales indicate that regional fire regimes in higher rainfall regions are dominated by large (>1000 km2) fires occurring typically at short (~2–3 years) fire return intervals. In discussion, we consider the ecological implications of these patch size distributions on regional fire-sensitive biota. Collectively, assembled data illustrate that many northern Australian savanna flora, fauna and habitats embedded within the savanna matrix are vulnerable to extensive and frequent fires, especially longer-lived obligate seeder plant taxa and relatively immobile vertebrate fauna with small home ranges.

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