Biomass burning by wildland fires has significant ecological, social and economic impacts. Satellite remote sensing provides direct measurements of radiative energy released by the fire (i.e. fire intensity) and surrogate measures of ecological change due to the fire (i.e. fire or burn severity). Despite anecdotal observations causally linking fire intensity with severity, the nature of any relationship has not been examined over extended spatial scales. We compare fire intensities defined by Moderate Resolution Imaging Spectroradiometer Fire Radiative Power (MODIS FRP) products with Landsat-derived spectral burn severity indices for 16 fires across a vegetation structure continuum in the western United States. Per-pixel comparison of MODIS FRP data within individual fires with burn severity indices is not reliable because of known satellite temporal and spatial FRP undersampling. Across the fires, 69% of the variation in relative differenced normalized burn ratio was explained by the 90th percentile of MODIS FRP. Therefore, distributional MODIS FRP measures (median and 90th-percentile FRP) derived from multiple MODIS overpasses of the actively burning fire event may be used to predict potential long-term negative ecological effects for individual fires.

Although fire is a common disturbance in shrub–steppe, few studies have specifically tested burned area mapping accuracy in these semiarid to arid environments. We conducted a preliminary assessment of the accuracy of the Monitoring Trends in Burn Severity (MTBS) burned area product on four shrub–steppe fires that exhibited varying degrees of within-fire patch heterogeneity. Independent burned area perimeters were derived through visual interpretation and were used to cross-compare the MTBS burned area perimeters with classifications produced using set thresholds on the Relativised differenced Normalised Burn Index (RdNBR), Mid-infrared Burn Index (MIRBI) and Char Soil Index (CSI). Overall, CSI provided the most consistent accuracies (96.3–98.6%), with only small commission errors (1.5–4.4%). MIRBI also had relatively high accuracies (92.2–97.9%) and small commission errors (2.1–10.8%). The MTBS burned area product had higher commission errors (4.3–15.5%), primarily due to inclusion of unburned islands and fingers within the fire perimeter. The RdNBR burned area maps exhibited lower accuracies (92.9–96.0%). However, the different indices when constrained by the MTBS perimeter provided variable results, with CSI providing the highest and least variable accuracies (97.4–99.1%). Studies seeking to use MTBS perimeters to analyse trends in burned area should apply spectral indices to constrain the final burned area maps. The present paper replaces a former paper of the same title (http://dx.doi.org/10.1071/WF13206), which was withdrawn owing to errors discovered in data analysis after the paper was accepted for publication.

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There is a growing professional and public perception that ‘extreme’ wildland fires are becoming more common due to changing climatic conditions. This concern is heightened in the wildland–urban interface where social and ecological effects converge. ‘Mega-fires’, ‘conflagrations’, ‘extreme’ and ‘catastrophic’ are descriptors interchangeably used increasingly to describe fires in recent decades in the US and globally. It is necessary to have consistent, meaningful and quantitative metrics to define these perceived ‘extreme’ fires, given studies predict an increased frequency of large and intense wildfires in many ecosystems as a response to climate change. Using the Monitoring Trends in Burn Severity dataset, we identified both widespread fire years and individual fires as potentially extreme during the period 1984–2009 across a 91.2×106-ha area in the north-western United States. The metrics included distributions of fire size, fire duration, burn severity and distance to the wildland–urban interface. Widespread fire years for the study region included 1988, 2000, 2006 and 2007. When considering the intersection of all four metrics using distributions at the 90th percentile, less than 1.5% of all fires were identified as potentially extreme fires. At the more stringent 95th and 99th percentiles, the percentage reduced to <0.5% and 0.05%. Correlations between area burnt and climatic measures (Palmer drought severity index, temperature, energy release component, duff moisture code and potential evapotranspiration) were observed. We discuss additional biophysical and social metrics that could be included and recommend both the need for enhanced visualisation approaches and to weigh the relative strength or importance of each metric.

Model projections suggest that both climate and land-use changes have large effects on forest biomass and composition in the Cumberland forests of Tennessee and Kentucky. These forests have high levels of diversity, ecological importance, land-use changes, and pressures due to invasive herbivorous insects and climate change. Three general circulation models project warming for all months in 2030 and 2080 and complex patterns of precipitation change. Climate changes from 1980 to 2100 were developed from these projections and used in the forest ecosystem model LINKAGES to estimate transient changes in forest biomass and species composition over time. These projections show that climate changes can instigate a decline in forest stand biomass and then recovery as forest species composition shifts. In addition, a landscape model (LSCAP) estimates changes in land-cover types of the Cumberlands based on projected land-use changes and the demise of eastern hemlock (Tsuga canadensis (L.) Carrière) due to the spread of the hemlock adelgid (Adelges tsugae Annand). LSCAP suggests that land-cover changes can be quite large and can cause a decline not only in the area of forested lands but also in the size and number of large contiguous forest patches that are necessary habitat for many forest species characteristic of the Cumberlands.Résumé : Les projections des modèles indiquent que les changements tant climatiques que dans l'utilisation du sol ont des effets importants sur la composition et la biomasse des forêts des Cumberlands au Tennessee et au Kentucky. Ces forêts sont caractérisées par un degré élevé de diversité, d'importance écologique, de changements dans l'utilisation du sol et de pressions dues aux insectes herbivores invasifs et aux changements climatiques. Trois modèles de la circulation générale prédisent un réchauffement durant tous les mois en 2030 et 2080 et des changements complexes dans la configuration des précipitations. Les changements climatiques pour la période allant de 1980 à 2100 ont été élaborés à partir de ces projections et utilisés dans le modèle d'écosystème forestier LINKAGES pour estimer les changements passagers dans la biomasse forestière et la composition en espèces dans le temps. Ces projections montrent que les changements climatiques peuvent être à l'origine du déclin de la biomasse des peuplements forestiers et de sa récupération par la suite, à mesure que la composition en espèces forestières se modifie. De plus, un modèle de paysage (LSCAP) a été utilisé pour déter-miner les changements qui pourraient survenir dans le type de couvert forestier des Cumberlands sur la base des changements prévus dans l'utilisation du sol et de la mortalité de la pruche du Canada (Tsuga canadensis (L.) Carrière) due à la progression du puceron lanigère de la pruche (Adelges tsugae Annand). Le modèle LSCAP indique que les changements dans le couvert pourraient être très importants et causer une diminution non seulement de la superficie du territoire forestier mais aussi de la dimension et du nombre de p...

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