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Mar 25 2020

Spatiotemporal patterns of overwintering fire in Alaska

This Fire Science Highlight is available as a standalone PDF

Spatiotemporal patterns of overwintering fire in Alaska 

Rebecca Scholten and Sander Veraverbeke – Vrije Universiteit Amsterdam

What are holdover and overwintering fires?

Fires can appear to be out, but retain smoldering combustion deep in the fuelbed and flare up again when the weather favors flaming behavior and fire spread. This phenomenon occurs not unfrequently in boreal forests of North America, and presents a well-known challenge to firefighters. Over the last two decades, fire managers noted increasing occurrences where fires survive the cold and wet boreal winter months by smoldering, and re-emerged in the subsequent spring.

Scientists and managers seek better understanding of how these fires sustain during such unfavorable conditions. Fire managers have already started targeting locations where they expect fires to flare up again. However, they are missing detailed information on the environmental and climatic factors that facilitate these fires. This information is crucial to detect fires at an early stage and keep firefighting costs low. A research group at Vrije Universiteit Amsterdam is studying when and where these holdover fires emerge and how their occurrence is tied to specific geographic locations.

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Mapping overwintering fires from satellite data
Since 2005, fire managers reported data on 39 holdover fires that survived winter in Alaska. However, the location and emergence date of these fires were used in conjunction with satellite data to develop an algorithm for overwintering holdover detection. From satellite imagery, we can only observe fires that are large enough to generate a considerable amount of heat and burn a large enough area. Consequently, 32 out of 39 reported overwintering fires were too small (all smaller than 11 ha, 25 out of 32 smaller than 1 ha) to be detected from space. The location and emergence date of these small overwintering fires were used for the calibration of an algorithm focused on large overwintering fires. From the remaining seven large reported overwintering fires, our algorithm classified 6 out of 7 as overwintering fire. In addition, our approach revealed 9 large overwintering fires that were not reported by agencies between 2002 and 2018 in Alaska. A results paper is currently in preparation.

The spread rate of smoldering fires is known to be very low, and a smoldering fire would spread only between 100 and 250 m in an entire year (Rein, 2013). So, overwintered fires usually emerge within or close to the previous year fire (Fig.1) and can re-emerge with flaming behaviour as soon as favourable burning conditions appear in spring develop in to flaming forest fires before the major lightning-induced fire season. The onset of warm and dry conditions varies from year to year depending on the winter and spring temperatures and precipitation. These variables also shape the regional snowmelt day, which can be inferred from satellite observations. Indeed, our research indicates that holdover fires usually re-emerge within 50 days after the regional snowmelt. Overwintering fires are more likely to occur the year after a large fire
year (Fig. 2).

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Can we predict where overwintering may re-emerge?

It is not only important to know when these fires emerge, but also where. We therefore analyzed spatial drivers of the overwintering fires we detected. Our research indicates that holdover fires are facilitated in those regions of a fire perimeter that had burned deeper into the organic soil the year before. Deep burning is a characteristic of a high severity fire. We also observed that overwintering fires were more likely to emerge in lowland areas with black spruce-dominated forest. Overwintering fires thus have some temporal and spatial predictability. Monitoring the edges of fire perimeters from the preceding year in lowland forested peatlands early in the fire season, and especially after a year with large burned area, may prove beneficial to extinguish flare-ups from overwintering fires before they develop into a large flaming forest fire. This could be a cost-efficient strategy for fire management agencies. In addition, this would preserve terrestrial carbon by safeguarding it from combustion.

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Figure 2: Years with a large burned area (grey bars) are more likely to generate
overwintering flare-ups (orange bars) than years with less burned area

References:

Rein, G. (2013). Smouldering Fires and Natural Fuels. In C. M. Belcher (Ed.), Fire Phenomena and the Earth System: An Interdisciplinary Guide to Fire Science (pp. 15–34). https://doi.org/10.1002/9781118529539

Turetsky, M. R., Benscoter, B., Page, S., Rein, G., Van Der Werf, G. R., & Watts, A. (2015). Global vulnerability of peatlands to fire and carbon loss. Nature Geoscience, 8(1), 11–14. https://doi.org/10.1038/ngeo2325
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Feb 21 2020

Upgrading Satellite Mapping of Burn Severity

As discussed in the Feb. 7 Fire Science Highlight, burn severity in Alaska is best related to the amount of consumption of the forest floor—not the degree of tree canopy mortality as is in temperate pine and fir forest.  Yet the most commonly applied metric to map burn severity using satellite remote sensing does not correlate well with substrate burn severity.  The change in Normalized Burn Ratio (dNBR; Key and Benson 2003) is based on comparing a pre- and a post-fire image. However, NBR thresholds for severity differ from one fire to another and among different years: similar numbers don’t indicate the same severity levels (D. Chen et al. 2020).  And with tundra fires, sometimes it works, other times not.  This problem has dogged fire effects and ecology studies in Alaska for some time (see list of papers in Sean Parks November 2019 presentation) leading French et al. (2008) to conclude: “Satellite remote sensing of post-fire effects alone without proper field calibration should be avoided.”

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2008 Transect photo from Anaktuvuk River tundra fire (R. Jandt)

Recently, we’ve seen some promising new methods used to improve satellite remote sensing of burn severity in boreal forest.  Whitman et al. compared several indices including a relativized index that facilitated comparisons between different fires in Canada.  She told us about it at the Opportunities to Apply Remote Sensing in Boreal/Arctic Wildfire Management and Science Workshop in 2017—here’s her presentation if you missed it: Improving Remotely Sensed Multispectral Estimations of Burn Severity in Western Boreal Forests.  Loboda et al. ( 2020) found single images using just NIR (near-infrared) bands of Landsat did better than NBR in discriminating tundra fire severity.  Sean Parks is attempting to harness the power of Google Earth Engines and cloud-based computing to use multiple images to further define the ecological burn severity (Parks et al. 2019)—this work is kicking off at the University of Montana.  He also found that unusual aspects of some fires in Alaska (pre-existing beetle kill, short fire return interval) contribute to poor performance of the standard index (see his recorded November, 2019, Association of Fire Ecology meeting presentation HERE).  And Yaping Chen, from the University of Illinois, explored using indices based on Visible and NIR bands (which have a large archive of available imagery going back to the early 1970’s) to evaluate tundra fire severity.  Her paper (Y. Chen et al. 2020) points to a VNIR index called GEMI as a “robust surrogate to NBR in Arctic tundra ecosystems, capable of accurately estimating fire severity across fire seasons, tundra fires, ecoregions, and vegetation types.”  The fact that GEMI is not as influenced by different vegetation types as dNBR gives it a distinct advantage mapping tundra burn severity.

Being able to more accurately map burn severity levels from space would give ecologists a boost for understanding why fires sometimes induce radical changes in ecosystems while other times the system self-replaces in a very short span.  For example, Yaping Chen used GEMI to reconstruct burn severity on older tundra fires like the 1977 example below and tie it to thermokarst effects (like catastrophic lake drainage or ponding) resulting from the fires (poster presented at AGU meeting December 2019).  We look forward to more exciting products and tools coming from these research teams!

Y. Chen et al. 2020, Fig. 7

Reconstructed fire severity map of the 1977 OTZNNW 38 tundra fire computed with dGEMI using Landsat MSS imagery.

Citations:

Chen, Yaping; Lara, Mark J.; Hu, Feng Sheng. 2020. A robust visible near-infrared index for fire severity mapping in Arctic tundra ecosystems. ISPRS Journal of Photogrammetry and Remote Sensing 159:101-113.

Chen, Dong; Loboda, TV.; Hall, JV. 2020. A systematic evaluation of influence of image selection process on remote sensing-based burn severity indices in North American boreal forest and tundra ecosystems. ISPRS Journal of Photogrammetry and Remote Sensing 159:63-77.

French, NHF.; Kasischke, ES.; Hall, RJ.; Murphy, KA.; Verbyla, DL.; Hoy, EE.; Allen, JL. 2008. Using Landsat data to assess fire and burn severity in the North American boreal forest region: an overview and summary of results. International Journal of Wildland Fire 17(4): 443-462.

Key, Carl H.; Benson, NC. 2003. The normalized burn ratio (NBR): A Landsat TM radiometric measure of burn severity. US Geological Survey Northern Rocky Mountain Science Center.

Loboda, Tatiana V.; Hoy, EE.; Giglio, L; Kasischke, ES. 2011. Mapping burned area in Alaska using MODIS data: a data limitations-driven modification to the regional burned area algorithm. International Journal of Wildland Fire 20(4):487-496.

Parks, SA.; Holsinger, LM.; Koontz, MJ.; Collins, L; Whitman, E; Parisien, MA; Loehman, RA.; Barnes, JL.; Bourdon, JF; Boucher, J; Boucher, Y; Caprio, AC.; Collingwood, A; Hall, RJ.; Park, J; Saperstein, LB.; Smetanka, C; Smith, RJ.; Soverel, NO. 2019. Giving ecological meaning to satellite-derived fire severity metrics across North American forests. Remote Sensing 11(14):1735.

Whitman, E, MA Parisien, DK Thompson, RJ Hall, RS Skakun, and MD Flannigan. 2018. Variability and drivers of burn severity in the northwestern Canadian boreal forest. Ecosphere 9(2):e02128. 10.1002/ecs2.2128

Feb 7 2020

Stand Conversion or Back to Black Spruce? Key New Findings

In Alaska, we know that post-fire recovery of spruce forest generally takes one of two major pathways.  Fires in spruce forest burn with high intensity and it is typical for 90-100% of the standing trees to be killed in the fire, so trees primarily regenerate by seeds released from the cones—often preserved and dried in the dead snags with the heat of the fire.  What happens next is largely dependent on the amount of forest floor moss layers consumed in the blaze:  if much is consumed, maybe even leaving patches of mineral soil, we consider this a high severity fire, whereas if only a few centimeters of moss duff have been removed, we consider the fire severity to be low.  Black spruce

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Photo by USFS, PNW (2004).

readily re-establishes itself after low-to-moderate severity fires because its abundant and relatively large seeds can germinate and survive a few dry spells in the peat-like substrate of the remaining organic forest floor.  This is called “self-replacement”.  Other tree species, including white spruce and the deciduous trees prefer a more exposed mineral seed bed, which may offer more consistent moisture and nutrient availability. After higher severity fires, grass and fireweed are notable early on and followed by a period of shrub and deciduous tree seedlings and re-sprouts.  The dominance of the forest may then shift to aspen, birch and/or poplar for a period of years.  Ultimately, more shade-tolerant but slow-growing spruce will again dominate, but this may take 50-100 years.  This pattern of recovery is termed “relay succession”. The moisture available at the site and pre-fire species composition also influence recovery, as illustrated by Johnstone, Hollingsworth and Chapin in the Key for Predicting Postfire Successional Trajectories in Black Spruce that they prepared for managers in 2008 (below).

Now, here’s the punch line:  Alaska ecologists have long been asking themselves what percent of the time, over the whole landscape, does self-replacement vs. relay succession occur?  For many modeling efforts to date (LANDFIRE, for example) we had only our best guesses.  At a scientific meeting in December 2020 (American Geophysical Union) Jennifer Baltzer, a Canadian forest ecologist, related the findings of a large ecological study with over 1,538 burn study plots across Alaska and western Canada (1,140 of the plots were black spruce forest).  Her team demonstrated that about 62% of the time burned black spruce forest recovers by self-replacement (73% for all conifer forest types), while approximately 20% of the plots were headed for a relay type succession.  Another 20% or so of the plots were showing little forest regeneration (regeneration “failure”)—which seemed to be more likely after repeat burns in a fairly short time period. The exciting thing about this research is that it provides—for the first time–quantitative estimates for these competing post-fire pathways. The research is being reviewed for publication now–we’ll let you know!

 

Dec 1 2019

Will Forest Change Counteract Climate-Driven Increase in Fire?

At the 2019 Fall Fire Science Workshop, we had a great presentation by Jill Johnstone on the concept of fire self-regulation in the boreal forest*.  This theory holds that as fire becomes more frequent and/or severe, spruce forests will increasingly convert to mixed and deciduous forests and provide negative feedback to burn extent even as the climate warms.

Hotspotting in Hardwoods

Fire A121, 2008, Midnight Sun Hotshots fight a fire in Alaska paper birch. (D. Jandt)

As you heard there, Jill is spearheading an effort to do a synthesis of findings of many studies in AK/Canada. At last week’s Association of Fire Ecology (AFE) Congress meeting, team member Xanthe Walker shared preliminary findings of the search for evidence of the effects of stand age and alternative vegetation types on probability of burning.  Do fires seem to “prefer” or “avoid” areas which burned in recent history?  In short, several studies across Canada, and a couple from Alaska, provide evidence for some level of self-regulation.  That begs the question:  how important are fuels vs. weather?  Will the self-regulation effect be enough to moderate the influence of higher fire indices in the future on acres burned?

Recall that fairly rigid self-regulatory feedbacks were programmed into the Boreal ALFRESCO model that has been used by Rupp, Duffy, Shultz, and others to build scenarios for Alaska’s land managers on how much burning will occur in the future and how much that will cost in suppression effort.  (See Implications of Climate and Management Options on Wildland Fire in Alaska: Exploring Future Fire Scenarios, a presentation by Courtney Schultz and Tait Rutherford at the 2017 Alaska Fall Fire Science Workshop, October 10, 2017.)  But, can we count on this?  Xanthe’s presentation (which AFSC recorded at the meeting and will soon be posting for you on our Vimeo site) concluded there will be SOME moderation of increased burning but also that these fuel effects can be overwhelmed by weather.  The latter is no surprise to fire practitioners in Alaska, i.e. young stands burn in extreme fire years and deciduous stand burn more during drought years. Quantifying this effect is what we need, and some good studies are starting to emerge.  Across the North American boreal forest, it appears that the strongest self-regulation occurs when weather is not extreme and where deciduous forests dominate to begin with.  It’s great to have a start on the answer to our burning questions about re-burn—there is clearly more to discover and we’re tickled to have this power-house team of researchers working on the problem.  You better believe we’ll be keeping in touch and watching for their publications.  We’re also happy they have welcomed the participation of agency fire ecologists and other local practitioners into the studies, because folks in the field have a lot to bring to the observational table.

*See Fire Self-Regulation, Evaluating the Current State of Understanding from Published Studies Presented by: Jill Johnstone, University of Alaska Fairbanks and University of Saskatchewan at the October 2019 AWFCG Fall Fire Review

List of selected citations used in Walker presentation: 

Beverly, J. L. 2017. Time since prior wildfire affects subsequent fire containment in black spruce. International Journal of Wildland Fire 26:919–929.  (Assesses whether stand age of black spruce forests has a detectable effect on the success of initial attack on fires <2 ha size in Alberta.)

Boulanger, Y. et al. 2017.  Changes in mean forest age in Canada’s forests could limit future increases in area burned but compromise potential harvestable conifer volumes. Canadian Journal of Forest Research 47(6): 755-764. (Modeled fire occurrence in the face of climate change with inclusion of self-regulation due to vegetation change across fire regimes of Canada.  Self-regulation substantially moderated the climate-driven fire increases but did not fully compensate for it – so fire activity will still increase even with the inclusion of these feedbacks).

Dash, C. B., J. M. Fraterrigo, and F. S. Hu. 2016. Land cover influences boreal-forest fire responses to climate change: geospatial analysis of historical records from Alaska. Landscape Ecology 31:1781–1793. (Large fires had a greater proportion of conifer forests than small fires, suggesting preferential rapid fire spread in conifer forests, but the effect of land cover on burning is less in years with extreme fire weather, when vegetation types burn at a rate close to that expected in the random model.)

Erni, S., D. Arseneault, M.-A. Parisien, and Y. Begin. 2017. Spatial and temporal dimensions of fire activity in the fire‐prone eastern Canadian taiga. Global Change Biology 23:1152–1166. (Firescar study of reconstructed 300 years of fire activity in Quebec to examine relative effects of climate/ weather vs. forest age controls on fire activity. In younger stands, burn rate was lower for up to 50 years, depending on landscape).

Hely, C., M. D. Flannigan, Y. Bergeron, and D. J. McRae. 2001. Role of vegetation and weather on fire behavior in the Canadian mixedwood boreal forest using two fire behavior prediction systems. Canadian Journal of Forest Research, v. 31, no. 3, p. 430-441.  (Compared FBP and Behave performance in boreal mixedwood in Quebec.  Although weather was overall more influential than fuel type, expected ROS was lower in deciduous that coniferous stands, and FBP performed better than Behave in this fueltype).

Parks, S. A., M.-A. Parisien, C. Miller, L. M. Holsinger, and L. S. Baggett. 2018. Fine-scale spatial climate variation and drought mediate the likelihood of reburning. Ecological Applications 28:573–586. (Fire spread was retarded by presence of previous fires for about 33 years in Wood Buffalo Park, Alberta, but the drought reduced the self-limiting effect of previous fire).

 

Nov 24 2018

Research Brief on What NASA is Contributing to Alaska Fire Science

Capture-thumbRB2018-4It’s hard to keep up with the myriad investigations NASA ABoVE campaign is working on in Alaska.  This short research brief is a round-up of recently published fire effects field studies and remote sensing products research and has some LINKS to show you where to access some intriguing new datasets and project results.  The “Big Data” coming from ABoVE is going to be a big boost to conducting regional or state-wide fire trends and assessments–you’ll want to know where that data lives. Access the Research Brief at:

https://www.frames.gov/catalog/56894

Oct 8 2018

Why Alaska Fire Potential Assessments are Different

There are at least 5 important factors that lead Alaska fire managers to continue their use of the Canadian CFFDRS system of fire danger and fire behavior tools for fire potential assessments in Alaska.  Fire behavior expert Robert “Zeke” Ziel gives a succinct review of them in this illustrated 3-page report.  Essential reading for anyone involved in fire management here in the 49th state! Download it <<HERE>>

AFSC Fact Sheet

Why Alaska Fire Potential Assessments are Different, Robert Ziel, 2018

Oct 3 2018

Wildland fire in boreal and arctic North America

The editors of the State of the Climate in 2017 invited AFSC and our collaborators Uma Bhatt and Rick Thoman to contribute a sidebar on wildland fire in boreal and arctic North America to the chapter on the Arctic. We were excited at the chance to share information about the region with an international audience. Check out a PDF of our contribution here: York et al_wildlandfire_Ch05_Arctic.

Jun 4 2018

How much sprinkling is enough?

Reading today’s update from AKFireInfo about the Livingston Fire, it mentions smokejumpers setting up sprinklers around 5 cabins about a mile from the head of the fire. This is a common tactic for protecting isolated values at risk, but we did not have good information on how much sprinkling was needed and how long wetting down an area would last. Until now.

Devon Barnes, a graduate student at the University of Alberta, worked with BLM-Alaska Fire Service Fire Ecologist Eric Miller to measure the effect of sprinkling on interior Alaska feathermoss fuel beds. Their work found that it takes 0.8 inches (20 mm) of sprinkled water to bring the top 5 inches of duff to saturation. This takes about 7 hours of sprinkling with a Mark 3 pump at a low throttle, and uses about 2 gallons of gas. Devon and Eric estimate that the sprinkled area can resist ignition by firebrands and surface spread for about 3 days in typical summer weather. The area may of course dry more quickly in very hot and windy conditions.

You can find more details on the project and its results in this new AFSC research summary.

May 1 2017

You asked: what happened with IFTDSS? Here’s the answer:

That would be the Interagency Fuels Treatment Decision Support System–you know–that’s been in development and then beta-testing since 2006?  Well, the good news is they’ve officially released it now as a finished tool and it’s free and available to everyone.  See the new official IFTDSS webpage to review the history and capabilities.  For the uninitiated, IFTDSS is a web-based software and data integration framework that organizes fire and fuels software applications to make fuels treatment planning and analysis more efficient.

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Ft. Richardson and BLM personnel conduct a prescribed burn on military training facility in 2006.  (R. Jandt)

We’ve had the beta-test version available for a while but funding availability to maintain the web-based tool has been a subject of debate so it’s nice to see this 2017 roll-out!  If you haven’t checked out IFTDSS, one of it’s strengths is enabling you to complete an analysis using “cloud”-power without loading a lot of disparate pieces of software for project definition, fuel types, fire behavior and spread rate, etc. onto your personal or government computer.  The platform has integrated links to sources of vegetation data (LANDFIRE), topography, etc. making them easy to upload.  The proliferation of different software systems, by different entities, to “help” managers plan fuel treatments was identified as a source of confusion and inefficiency by the national fuels management committee, which spurred the initial development of IFTDSS.  So check it out–they offer both training and a help center, and IFTDSS is now included in the training for Prescribed Fire Planner (aka Burn Boss) RX341 class.

Jan 31 2017

Call for Data: US Post-Fire Tree Mortality

We seek data contributions to a Joint Fire Sciences Program project examining tree mortality due to wildland fire in the U.S. We are interested in U.S. datasets that at minimum include year of fire, county, state, and individual tree records of species, DBH and crown injury (some measure of crown scorch, kill, and/or consumption).

These datasets will be aggregated into an archived database of post-fire tree mortality and used to:

  1. validate existing predictive post-fire mortality models and
  2. examine the influence of pre-fire climate to improve predictions of post-fire tree mortality.

The archived data product will be made publicly available within one year of project completion (approximately 2020). Additional project detail from JFSP »

Contributors will receive authorship of the formally published archived data product and, at minimum, acknowledgement of contribution in published articles.

Please contact C. Alina Cansler via ccansler@fs.fed.us or (406) 829-6980 for additional information or questions. Thank you for your interest.