Increasing trends in high-severity fire in the southwestern USA from 1984 to 2015
Introduction
Fire is an important and dynamic disturbance process, yet concerns over increasing extent and severity are reaching new urgency. Recent work across the globe has quantified trends in high-severity fire using remotely sensed technology in attempt to determine if historical fire patterns are changing (Archibald et al., 2010, Dennison et al., 2014, Kasischke and Turetsky, 2006, Picotte et al., 2016, Riaño et al., 2007, Rivera-Huerta et al., 2016). Shifts in fire regimes, especially in high-severity fire, can result in significant consequences to landscape processes and ecosystem function and the identification of such shifts are important for forest conservation and sustainability. In the western United States, land-use practices i.e., fire suppression and logging as well as climate change are frequently cited as the primary drivers of increasing fire severity (Dillon et al., 2011, Fulé et al., 2009, Fulé et al., 1997, Jolly et al., 2015, Moore et al., 2004, Reilly et al., 2017, Williams et al., 2013). The southwestern US, namely Arizona and New Mexico, is a semi-arid region where forest structure has dramatically changed since Euro-American settlement (Moore et al., 2004, White and Vankjat, 1993) and where increased wildfire activity is known to be driven by climate change (Crimmins, 2011, Grissino-Mayer and Swetnam, 2000). The southwestern US has been recently affected by large and intense wildfires where 4.1 million hectares have burned in all vegetation types in the past three decades and the largest fires in documented history have occurred in the past two decades. Fires regimes may be shifting in the Southwest yet this phenomena has been largely undocumented. Severity is fundamental to understanding how fire patterns are changing and ultimately, in understanding the ecological implications of altered fire regimes.
Here we present a comprehensive region-wide trend analysis of high-severity fire in Arizona and New Mexico forest and woodland ecosystems over a 32 year time span using data from the Monitoring Trends in Burn Severity (MTBS) project. The MTBS project uses Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM + ), and Operational Land Imager (OLI) imagery to produce burn severity data for fires greater than 404 ha in the western US and 202 ha in the eastern US from 1984 to the present (Eidenshink et al., 2007). Dillon et al. (2011) examined temporal trends from 1984 to 2006 in high-severity fire for parts of the Southwest, but excluded large areas of New Mexico and fires that occurred in unique areas of Southern Arizona (e.g., the Sky Islands). Dillon et al. (2011) also did not include MTBS products with post-fire images acquired less than 6 months from the fire ignition date (i.e., initial assessments [IA]) and thus, an estimated 43% of burned area was excluded from their analysis in the time frame of their study. There is a need to broaden the work of Dillon et al. (2011) by updating the time period, expanding the study area to encompass all of Arizona and New Mexico, and including all fires >404 ha that burned since 1984 in order to provide a more complete and accurate burn severity dataset for the Southwest. There is also a need to evaluate temporal trends in high-severity fire within specific forest and woodland vegetation types to understand how recent wildfires have impacted individual ecosystems and to understand how fire patterns may be changing. Such information is critical in developing management strategies to increase the sustainability for each forest type.
Our objectives were to assess, from 1984 to 2015 in Arizona and New Mexico, if there were increasing trends in (1) number of fires and total area burned in all vegetation types; (2) area burned, area of high-severity fire, and percent of high-severity fire in all forested and woodland vegetation types (Ecological Response Units [ERU] Fire Regime Types); and (3) area burned, area of high-severity fire, and percent of high-severity fire in seven forest and woodland ERU Fire Regime Types.
Section snippets
Study area
Our study area encompassed all fires from 1984 to 2015 greater than 404 ha that burned within Arizona and New Mexico (Fig. 1). We included all fires that burned on private, state, and federal lands including Forest Service (FS), National Park Service (NPS), Bureau of Land Management (BLM), Fish and Wildlife Service (FWS), Department of Defense (DOD), and Bureau of Indian Affairs (BIA) managed lands (Table 1). We assessed 1621 fires that burned in all vegetation types and 1143 fires that burned
Trends in all fires from 1984 to 2015
In fires that occurred in all vegetation types, both fire count and area burned showed a significant increase from 1984 to 2015 (P < 0.011, P ≤ 0.001) (Table 3, Figs. 3A/B, S2A/B). The average annual increase for area burned was 8373 ha (Table S1).
In forests and woodlands, ARMA and linear models for area burned, area burned severely, and percent burned severely showed significant increasing trends (P < 0.044) (Table 3). The average annual increase of area burned and area of high-severity fire
Discussion
Over the last three decades, fires are more frequent, larger, and more severe in the Southwest. The number of large fires (>404 ha) and area burned increased from 1984 to 2015 across the Southwest regardless of vegetation type. The significant increasing trends held for area burned, area of high-severity fire, and percent of high-severity fire in forested and woodland ecosystems. In ERU Fire Regime Types, we found significant increases in area burned and area of high-severity fire across all
Acknowledgements
Funding provided by Rocky Mountain Research Station, Forest Service, U.S. Department of Agriculture. We thank Eric Gdula for providing access to the Grand Canyon National Park’s Composite Burn Index dataset. We wish to thank Stephen Howard and Josh Picotte for additional burn severity data needed for this project and their helpful advice as well as Stephanie Mueller for her help in processing Landsat scenes. We also wish to thank Pete Fulé, Doug Cram, and Zander Evans for helpful comments on
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