Plain Language Summary
Wildfire is a dominant disturbance agent that drives ecosystem change,
climate forcing, and carbon cycle in Arctic tundra. Tundra fires can
exert a considerable influence on the local ecosystem functioning and
contribute to climate change. However, the drivers and mechanisms of
tundra fires are still poorly understood. Research on modeling
contemporary fire occurrence in the tundra is also lacking. Here we
examined the key environmental factors that drive tundra fire occurrence
with numeric weather prediction and statistical models. We found that
tundra fire occurrence is primarily controlled by cloud-to-ground
lightning. Warmer and drier fire weather conditions also support
burnings in the tundra. We recommend the integration of lightning
modeling with numeric weather prediction model for fire monitoring and
forecasting in the data-scarce regions like the Arctic.
1 Introduction
Wildfire
plays an essential role in altering ecosystem functioning, driving land
cover change, and affecting carbon balance in boreal forest and tundra
ecosystems (Bret-Harte et al., 2013; Mack et al., 2011; Randerson et
al., 2006; Rocha and Shaver, 2011; van Wees et al., 2021; Wang et al.,
2021). Though typically less severe than the boreal forest fires, tundra
fires are widespread across the pan-Arctic region. Particularly, Alaskan
tundra burns more than any other tundra region across the globe,
according to satellite-based observations (He et al., 2019; Loboda et
al., 2017). In recent years, several large fire seasons have occurred in
Alaskan tundra, including the 2010 fire season in the Noatak River
Valley, the 2015 fire season in Southwest Alaska, and the now infamous
extreme 2007 Anaktuvuk River fire on the North Slope.
Tundra fires can lead to shrub expansion, alter organic soil properties
and affect the surface energy budget in the local ecosystems (Bret-Harte
et al., 2013; Frost et al., 2020; He et al., 2021; Rocha and Shaver,
2011). They also have the potential to release the ancient carbon stored
in the frozen organic soil and cause widespread permafrost degradation
and thermokarst development (Jones et al., 2015; Mack et al., 2011).
Moreover, habitat suitability and forage availability for numerous
wildlife species, e.g. caribou, are threatened by such fires, affecting
the living resources of local human societies (Gustine et al., 2014;
Joly et al., 2012). Under the rapid climate warming in the Arctic, the
tundra could become more vulnerable to burnings due to the increased
danger of lightning activity and extreme fire weather (French et al.,
2015; McCarty et al., 2021; Young et al., 2017), which will threaten
permafrost carbon and result in substantial feedbacks into regional to
global climate systems, and circumpolar indigenous and nonnative
communitites (Bogdanova et al., 2021; Chen et al., 2021; Forbes, 2013;
Hu et al., 2015). However, tundra fires attract less scientific
attention compared to fires in other ecosystems. Current research
primarily focuses on evaluating post-fire impacts with comparatively
little attention to understanding driving mechanisms and modeling tundra
fire occurrence.
Fire
occurrence results from a combination of ignition and propagation.
Cloud-to-ground (CG) lightning and, to a lesser extent, human activity
(due to minimal human presence) are the primary ignition sources in
tundra ecosystems. Three types of forces generally control fire
propagation: fuel, weather, and topography, as summarized by the “Fire
Environment Triangle” (Pyne et al., 1996). Fuel type, representing
properties of the fuel itself, and fuel moisture state, related to
vegetation moisture content, are critically important factors
controlling fire-environment interactions by affecting fuel flammability
and fire characteristics. Topography also influences fire propagation
directly by altering wind patterns or upslope preheating, and indirectly
by controlling fuel moisture state through exposure to sunlight and
moisture pooling. Finally, fire weather is frequently the dominant
contributor to wildfire occurrence across different temporal scales
through impacts on fuel moisture state and ignition source. Various fire
danger rating systems, that implicitly or explicitly bundle weather
impacts on fuel moisture, have been developed to capture the broader
impact of weather on expected fire growth and quantify the potential
fire risk. Specifically, the National Fire Danger Rating System (NFDRS)
implemented in the US and the Canadian Forest Fire Weather Index System
(CFFWIS) are the best known and most broadly used in the high northern
latitudes (HNL).
Previous studies in the HNL have not reached a consensus regarding the
relative impacts of various environmental factors on wildfire
occurrence. The majority of the existing studies focused on the boreal
forests when examining the environmental drivers of wildfire behaviors.
Liu et al. (2012) found out that lightning-ignited fires were controlled
by fuel moisture and vegetation type in the boreal forests of Northeast
China. While studies in North America emphasized the impacts of
atmospheric stability, count of lightning strikes, and dry weather on
boreal forest fires (Peterson et al., 2010). Veraverbeke et al. (2017)
suggested that lightning activity explained the burned area trends in
the boreal forests of North America during recent large fire years.
Though lightning characteristics like polarity and peak current were
found significant in modeling fire occurrences (Müller and Vacik, 2017;
Vecín-Arias et al., 2016), they did not function as major contributors
in other studies (Adámek et al., 2018; Pineda et al., 2014).
Nevertheless, these findings in the boreal forests are not readily
transferrable to the treeless tundra, as the land-atmosphere
interactions differ substantially between the two ecosystems (Chambers
et al., 2005; Dissing and Verbyla, 2003; Jiang et al., 2015; Van
Heerwaarden and Teuling, 2014). Previous studies have modeled historical
or future tundra fire regimes with ecosystem or statistical models
(Higuera et al., 2011; Joly et al., 2012; Sae-Lim et al., 2019; Young et
al., 2017). Specifically, Young et al. (2017) modeled future fire
occurrence probability in Alaska accounting for climate and landscape
features. Masrur et al. (2018) found that warm and dry conditions affect
the spatiotemporal patterns across the circumpolar Arctic tundra. Yet,
efforts on examining the driving mechanisms and contemporary modeling of
fire occurrence have been lacking in the tundra ecosystems in existing
research. Critical factors such as lightning, were not considered in
these studies.
This study investigates the key environmental factors controlling fire
occurrences in Arctic tundra via contemporary modeling during 2001 –
2019. We defined the wildfire occurrence as the start of an individual
fire event detected by satellite sensors. We developed an
empirical-dynamical framework to predict the fire occurrence probability
by combining numerical weather prediction (NWP) and machine learning
models. We considered factors that control wildfire behaviors, including
fuel, fire weather, topography, and ignition source.
2 Materials and Methods
2.1 Data and variable preparation