Appendix A. Fire–climate correlations for the period 1977–2003.

Fire–climate correlations for the period 1977–2003

Appendix B. Fire–climate correlations for the period 1916–2003.

Fire–climate correlations for the period 1916–2003

Projected change in AAB.

<p>Projections rates are for the period 2010–2039 compared to the period 1961–2004 based on ensemble of A1B emission scenarios. (a) Percent change in AAB resulting from stepwise selection of individual cell-based models, based on AIC model selection criteria; (b) proportion of variance explained (<i>R</i>²). Only significant models (<i>p</i> < 0.05) are plotted.</p

Results of PCA analysis of <i>z</i> coefficients of a complete multiple regression model in each grid cell.

<p>Panels show the first four principal components and percent in variation in AAB explained. Seasonal climate variables correlated with PC loadings at <i>r</i> ≥ 0.5 are listed including the sign of the correlation with AAB. (a) PC1, summer temperature (+) and spring precipitation (-); (b) PC2, spring temperature (+); (c) PC3, winter temperature (-); (d) PC4, preceding year summer temperature (+). Red (blue) colors indicate increases (decreases) in log-transformed AAB with increases in variables correlating positively/negatively with PC scores. Note that PC3 is inverted in sign for ease in interpretation. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0188486#pone.0188486.s001" target="_blank">S1 Fig</a> for PC5.</p

Temporal trends (1972–2006) in instrumental seasonal climate and snow cover duration.

<p>(a) Winter (JFM) temperature (°C), (b) spring (AMJ) temperature (°C), (c) summer (JAS) temperature (°C), and (d) LDPS (days/decade), based on the Theil-Sen median slope estimator.</p

Changes in AAB across United States and Canada by state/province.

<p>(a) Boxplot of percent change in AAB (2010–2039 <i>vs</i>.1961-2004, SRES A1B scenario) binned by US state or Canadian province, based on significant models with <i>p</i> < 0.05. Sharing of any letter (below the graph) indicates lack of significant differences in medians of percent change in AAB based on Bonferroni-corrected <i>a posteriori</i> comparisons of a Kruskal-Wallis median test. Colored boxes indicate groups of states/regions with statistically similar medians ordered from low (green) through high median values (red). (b) States/regions ordered by increasing median change in AAB. Histograms are model projections based on the 1976–2006 baseline period; red dots are extrapolated increases in median AAB and bars are 95% confidence intervals estimated from Theil-Sen trends (1972–2015).</p

Projected Effects of Climate and Development on California Wildfire Emissions through 2100

Changing climatic conditions are influencing large wildfire frequency, a globally widespread disturbance that affects both human and natural systems. Understanding how climate change, population growth, and development patterns will affect the area burned by and emissions from wildfires and how populations will in turn be exposed to emissions is critical for climate change adaptation and mitigation planning. We quantified the effects of a range of population growth and development patterns in California on emission projections from large wildfires under six future climate scenarios. Here we show that end-of-century wildfire emissions are projected to increase by 19–101% (median increase 56%) above the baseline period (1961–1990) in California for a medium-high temperature scenario, with the largest emissions increases concentrated in northern California. In contrast to other measures of wildfire impacts previously studied (e.g., structural loss), projected population growth and development patterns are unlikely to substantially influence the amount of projected statewide wildfire emissions. However, increases in wildfire emissions due to climate change may have detrimental impacts on air quality and, combined with a growing population, may result in increased population exposure to unhealthy air pollutants

Direct and indirect effects of climate and snow cover on AAB by LDPS regions.

<p>Spring (a) and winter (b) mean (± SE) path coefficients averaged over areas of boreal and western North America with areas of similar snow cover duration (monthly classes of long-term (1972–2006) mean LDPS. Black bars indicate direct effects of temperature on log-AAB; grey bars indirect effects on log-AAB mediated by variation in LDPS. (c) Geographic distribution of monthly mean LDPS.</p