Research Article: Climatic and Landscape Influences on Fire Regimes from 1984 to 2010 in the Western United States

Date Published: October 14, 2015

Publisher: Public Library of Science

Author(s): Zhihua Liu, Michael C. Wimberly, Lucas C.R. Silva.

http://doi.org/10.1371/journal.pone.0140839

Abstract

An improved understanding of the relative influences of climatic and landscape controls on multiple fire regime components is needed to enhance our understanding of modern fire regimes and how they will respond to future environmental change. To address this need, we analyzed the spatio-temporal patterns of fire occurrence, size, and severity of large fires (> 405 ha) in the western United States from 1984–2010. We assessed the associations of these fire regime components with environmental variables, including short-term climate anomalies, vegetation type, topography, and human influences, using boosted regression tree analysis. Results showed that large fire occurrence, size, and severity each exhibited distinctive spatial and spatio-temporal patterns, which were controlled by different sets of climate and landscape factors. Antecedent climate anomalies had the strongest influences on fire occurrence, resulting in the highest spatial synchrony. In contrast, climatic variability had weaker influences on fire size and severity and vegetation types were the most important environmental determinants of these fire regime components. Topography had moderately strong effects on both fire occurrence and severity, and human influence variables were most strongly associated with fire size. These results suggest a potential for the emergence of novel fire regimes due to the responses of fire regime components to multiple drivers at different spatial and temporal scales. Next-generation approaches for projecting future fire regimes should incorporate indirect climate effects on vegetation type changes as well as other landscape effects on multiple components of fire regimes.

Partial Text

Fire is an integral component of the earth system and plays a key role in regulating vegetation structure and ecosystem function [1–3]. Understanding the relative influences of multiple controlling factors on fire regimes is one of the fundamental objectives of fire ecology, and this knowledge is critical for improving our ability to anticipate future fire regime changes. Climatic variability is a major driver of fire in many terrestrial ecosystems, as reflected in Bradstock’s conceptual model of four climatic ‘switches’ that influence fire regimes by controlling fuel amount, fuel moisture, and fire weather at contrasting temporal scales [4]. However, fire regimes are also affected by other controls such as landscape-scale patterns of vegetation, topography, and human activities [5]. For example, recent analyses in boreal Canada found that vegetation and fuels influenced the spatial and temporal patterns of fires, even in systems where climate was considered the most limiting factor [6, 7]. Topography also influences fire regimes through its effects on fuel loads and fuel moisture via site productivity and microclimate [8]. Humans can modify fire regimes by changing ignition patterns [9] and by altering fuel amount and continuity [10]. Therefore, understanding how fire regimes respond to landscape controls in addition to climatic shifts is critical in this era of unprecedented global change, and will require research that explores the effects of multiple, interacting drivers of fire regimes [11].

The 6071 large fires reported in the MTBS database burned 24 265 610 ha over 1984–2010 (10.6% of the total burnable area of the western US), of which 2 979 817 ha (12.3% of the area burned and 1.3% of the total burnable area of the western US) was high severity. Fire rotations, defined as the estimated time required to burn an area of interest, were 254 and 2077 years for all fire and high severity fire, respectively, based on the total burnable area of the western US. The mean fire occurrence density was 1.37 large fires per million ha per year, and the median fire size was 1207 ha. Smoothed maps revealed that the three fire regime components were spatially heterogeneous, and their spatial patterns were not entirely concordant, suggesting they were potentially influenced by different sets of spatial controls (Fig 2a, 2b, and 2d). Spearman’s rank correlation of the spatial patterns of fire regime components showed fire occurrence and size had a positive correlation (r = 0.34, p<0.001), whereas fire occurrence and percent high severity had a negative correlation (r = -0.30, p<0.001). There was a weak positive correlation between fire size and percent of high severity burning (r = 0.04, p<0.001). Spatial and spatio-temporal patterns of large-fire occurrence differed from patterns of fire size and severity in the western US, and these differences can be explained by the distinctive effects of key environmental drivers on various components of the fire regime. In particular, large fire occurrence had higher spatial synchrony and was most strongly associated with short-term climatic anomalies. This finding is supported by previous analyses in the western US, which found that large fires were often preconditioned by frequent or more numerous consecutive days of hot and dry climatic conditions which result in lower fuel moisture, particularly for live fuels and larger dead fuels [39, 50, 51]. These droughts are often associated with climate patterns such as the Pacific Decadal Oscillation and El Niño Southern Oscillation, and can affect regional, inter-annual fluctuations in large fire occurrence of western North America [52, 53]. Our results are also consistent with studies employing different analytical methods based on the MTBS data in the western US. For example, Riley et al [39] found that precipitation during the past 1–3 months was a strong predictor of large fire occurrence because dead fuel moisture is strongly influenced by short-term antecedent climate conditions. Similarly, Abatzoglou and Kolden [18] found that climatic indices of drought during the current fire season had stronger relationships with area burned than antecedent climate variables from previous years, and that these regional anomalies synchronized the area burned across both forested and non-forested sub-regions of the western United States. However, our results further suggested that the short-term antecedent climatic anomalies interact with vegetation type to influence patterns of fire occurrence and have stronger influences on fire occurrence than on fire size or fire severity (Fig 5a). In this analysis, we characterized climate and landscape effects on fire regimes across the western United States using a consistent analytical framework to produce general insights about the environmental factors that control the spatial and temporal patterns of major fire regime components. Our results showed that landscape and climatic factors had varied effects on fire occurrence, size, and severity. In particular, the spatio-temporal patterns of fire size and severity exhibited weaker spatial synchrony than fire occurrence, and were more strongly constrained by spatial patterns of vegetation, topography, and human activities. In contrast, the probability of fire occurrence was mainly influenced by recent climate anomalies, and showed a stronger spatial synchrony. These findings underscore the value of studying individualistic response of different fire regime components and ultimately incorporating multiple environmental drivers of different fire regime components into projections of future fire regimes. In particular, our results suggest the possibility that fire regimes with novel combinations of frequency, severity, and size may emerge as a result of the interacting effects of changes in climate, shifts in vegetation distributions, and continuing expansion of the human footprint. Ongoing efforts to project the effects of future global change on regional fire regimes should therefore incorporate the indirect effects of climate on vegetation type, as well as other types of landscape controls on multiple fire regime components.   Source: http://doi.org/10.1371/journal.pone.0140839