Is burn severity related to fire intensity? Observations from landscape scale remote sensing

Heward, Heather; Smith, Alistair M. S.; Roy, David P.; Tinkham, Wade T.; Hoffman, Chad; Morgan, Penelope; Lannom, K. O.

doi:10.1071/wf12087

Cited by 64 publications

(38 citation statements)

References 59 publications

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“…The resulting range of FRP for all fires was comparable to FRP observed in other closed-canopy temperate forests (Giglio et al, 2006;Heward et al, 2013). We used MTBS fire perimeters and metadata to screen any fire detections that were not co-located with recorded fire events spatially and temporally.…”

Section: Modis Datasetsmentioning

confidence: 75%

“…FRP is the 5 instantaneous radiative flux, which is strongly related to common field-based fire intensity metrics (Kaufman et al, 1996;Kremens et al, 2012;Sparks et al, 2017), and its temporal integral is FRE. These are two of the most commonly used metrics to quantify fire intensity from satellite remote sensing products (Andela et al, 2015;Freeborn et al, 2016;Heward et al, 2013;Roberts et al, 2011;Smith and Wooster, 2005). Under controlled experiments on saplings, a toxicological "dose-response" relationship was observed, whereby increasing FRE resulted in decreasing net photosynthesis in surviving Pinus contorta and 10…”

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confidence: 99%

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Fire intensity impacts on post-fire temperate coniferous forest net primary productivity

Sparks¹,

Kolden²,

Smith³

et al. 2017

Preprint

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Abstract.Fire is a dynamic ecological process in forests and impacts the carbon (C) cycle through direct combustion emissions, tree mortality, and by impairing the ability of surviving trees to sequester carbon. While studies on young trees have demonstrated that fire intensity is a determinant of post-fire net primary productivity, wildland fires at landscape to 10 regional scales have largely been assumed to either cause tree mortality, or conversely, cause no physiological impact, ignoring the impacted but surviving trees. Our objective was to understand how fire intensity affects post-fire net primary productivity in conifer-dominated forested ecosystems at the spatial scale of large wildland fires. We examined the relationships between fire radiative power (FRP), its temporal integral (fire radiative energy -FRE), and net primary productivity (NPP) using 16 years of data from the MOderate Resolution Imaging Spectrometer (MODIS) for 15 large fires in western United States 15 coniferous forests. The greatest NPP post-fire loss occurred one year post-fire and ranged from -67 to -312 g C m -2 yr -1 (-13 to -54%) across all fires. Forests dominated by fire-resistant species (species that typically survive low intensity fires) experienced the lowest relative NPP reductions compared to forests with less resistant species. Post-fire NPP in forests that were dominated by fire-susceptible species were not as sensitive to FRP or FRE, indicating that NPP in these forests may be reduced to similar levels regardless of fire intensity. Conversely, post-fire NPP in forests dominated by fire resistant and mixed species decreased 20 with increasing FRP or FRE. In some cases, this dose-response relationship persisted for more than a decade post-fire, highlighting a legacy effect of fire intensity on post-fire C dynamics in these forests.

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Section: Modis Datasetsmentioning

confidence: 75%

mentioning

confidence: 99%

Fire intensity impacts on post-fire temperate coniferous forest net primary productivity

Sparks¹,

Kolden²,

Smith³

et al. 2017

Preprint

Self Cite

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“…The maximum FRP value within a 1 km buffer around the center of the active fire detection location over the previous 365 days was derived (MaxFRP365d, Table 1). The maximum FRP is of interest also as the maximum fire intensity affects vegetation processes like grass and tree response to fires (Archibald et al 2010;Heward et al 2013).…”

Section: Fire Radiative Powermentioning

confidence: 99%

Multi-year MODIS active fire type classification over the Brazilian Tropical Moist Forest Biome

Roy

Kumar

2016

International Journal of Digital Earth

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The Brazilian Tropical Moist Forest Biome (BTMFB) spans almost 4 million km 2 and is subject to extensive annual fires that have been categorized into deforestation, maintenance, and forest fire types. Information on fire types is important as they have different atmospheric emissions and ecological impacts. A supervised classification methodology is presented to classify the fire type of MODerate resolution Imaging Spectroradiometer (MODIS) active fire detections using training data defined by consideration of Brazilian government forest monitoring program annual land cover maps, and using predictor variables concerned with fuel flammability, fuel load, fire behavior, fire seasonality, fire annual frequency, proximity to surface transportation, and local temperature. The fire seasonality, local temperature, and fuel flammability were the most influential on the classification. Classified fire type results for all 1.6 million MODIS Terra and Aqua BTMFB active fire detections over eight years (2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) are presented with an overall fire type classification accuracy of 90.9% (kappa 0.824). The fire type user's and producer's classification accuracies were respectively 92.4% and 94.4% (maintenance fires), 88.4% and 87.5% (forest fires), and, 88.7% and 75.0% (deforestation fires). The spatial and temporal distribution of the classified fire types are presented and are similar to patterns reported in the available recent literature. ARTICLE HISTORY

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“…[51][52][53][54][55] Fire intensity A description of fire behavior quantified by energy release, such as temperature and heat from burning organic matter. [16,20,[56][57][58] Post-environment:…”

Section: Forest Fire and Forest Pattern Terminologymentioning

confidence: 99%

Remote Sensing Techniques in Monitoring Post-Fire Effects and Patterns of Forest Recovery in Boreal Forest Regions: A Review

2013

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Abstract:The frequency and severity of forest fires, coupled with changes in spatial and temporal precipitation and temperature patterns, are likely to severely affect the characteristics of forest and permafrost patterns in boreal eco-regions. Forest fires, however, are also an ecological factor in how forest ecosystems form and function, as they affect the rate and characteristics of tree recruitment. A better understanding of fire regimes and forest recovery patterns in different environmental and climatic conditions will improve the management of sustainable forests by facilitating the process of forest resilience. Remote sensing has been identified as an effective tool for preventing and monitoring forest fires, as well as being a potential tool for understanding how forest ecosystems respond to them. However, a number of challenges remain before remote sensing practitioners will be able to better understand the effects of forest fires and how vegetation responds afterward. This article attempts to provide a comprehensive review of current research with respect to remotely sensed data and methods used to model post-fire effects and forest recovery patterns in boreal forest regions. The review reveals that remote sensing-based monitoring of post-fire effects and forest recovery patterns in boreal forest regions is not only limited by the gaps in both field data and remotely sensed data, but also the complexity of far-northern fire regimes, climatic conditions and environmental conditions. We expect that the integration of different remotely sensed data coupled with field campaigns can provide an important data source to support the monitoring of post-fire effects and forest recovery patterns. Additionally, the variation and stratification of pre-and post-fire vegetation and environmental conditions should be considered to achieve a reasonable, operational model for monitoring post-fire effects and forest patterns in boreal regions.

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Is burn severity related to fire intensity? Observations from landscape scale remote sensing

Cited by 64 publications

References 59 publications

Fire intensity impacts on post-fire temperate coniferous forest net primary productivity

Fire intensity impacts on post-fire temperate coniferous forest net primary productivity

Multi-year MODIS active fire type classification over the Brazilian Tropical Moist Forest Biome

Remote Sensing Techniques in Monitoring Post-Fire Effects and Patterns of Forest Recovery in Boreal Forest Regions: A Review

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