Growing human and ecological costs due to increasing wildfire are an urgent concern in policy and management, particularly given projections of worsening fire conditions under climate change. Thus, understanding the relationship between climatic variation and fire activity is a critically important scientific question. Different factors limit fire behavior in different places and times, but most fire-climate analyses are conducted across broad spatial extents that mask geographical variation. This could result in overly broad or inappropriate management and policy decisions that neglect to account for regionally specific or other important factors driving fire activity. We developed statistical models relating seasonal temperature and precipitation variables to historical annual fire activity for 37 different regions across the continental United States and asked whether and how fire-climate relationships vary geographically, and why climate is more important in some regions than in others. Climatic variation played a significant role in explaining annual fire activity in some regions, but the relative importance of seasonal temperature or precipitation, in addition to the overall importance of climate, varied substantially depending on geographical context. Human presence was the primary reason that climate explained less fire activity in some regions than in others. That is, where human presence was more prominent, climate was less important. This means that humans may not only influence fire regimes but their presence can actually override, or swamp out, the effect of climate. Thus, geographical context as well as human influence should be considered alongside climate in national wildfire policy and management.
Climate change adaptation and mitigation require understanding of vegetation response to climate change. Using the MC2 dynamic global vegetation model (DGVM) we simulate vegetation for the Northwest United States using results from 20 different Climate Model Intercomparison Project Phase 5 (CMIP5) models downscaled using the MACA algorithm. Results were generated for representative concentration pathways (RCP) 4.5 and 8.5 under vegetation modeling scenarios with and without fire suppression for a total of 80 model runs for future projections. For analysis, results were aggregated by three subregions: the western Northwest (WNW), from the crest of the Cascade Mountains west; Northwest plains and plateau (NWPP), the non-mountainous areas east of the Cascade Mountains; and eastern Northwest mountains (ENWM), the mountainous areas east of the Cascade Mountains. In the WNW, mean fire interval (MFI) averaged over all climate projections decreases by up to 48%, and potential vegetation shifts from conifer to mixed forest under RCP 4.5 and 8.5 with and without fire suppression. In the NWPP MFI averaged over all climate projections decreases by up to 82% without fire suppression and increases by up to 14% with fire suppression resulting in woodier vegetation cover. In the ENWM, MFI averaged across all climate projections decreases by up to81%, subalpine communities are lost, but conifer forests continue to dominate the subregionin the future.
The dynamic global vegetation model (DGVM) MC2 was run over the conterminous USA at 30 arc sec (~800 m) to simulate the impacts of nine climate futures generated by 3GCMs (CSIRO, MIROC and CGCM3) using 3 emission scenarios (A2, A1B and B1) in the context of the LandCarbon national carbon sequestration assessment. It first simulated potential vegetation dynamics from coast to coast assuming no human impacts and naturally occurring wildfires. A moderate effect of increased atmospheric CO2 on water use efficiency and growth enhanced carbon sequestration but did not greatly influence woody encroachment. The wildfires maintained prairie-forest ecotones in the Great Plains. With simulated fire suppression, the number and impacts of wildfires was reduced as only catastrophic fires were allowed to escape. This greatly increased the expansion of forests and woodlands across the western USA and some of the ecotones disappeared. However, when fires did occur, their impacts (both extent and biomass consumed) were very large. We also evaluated the relative influence of human land use including forest and crop harvest by running the DGVM with land use (and fire suppression) and simple land management rules. From 2041 through 2060, carbon stocks (live biomass, soil and dead biomass) of US terrestrial ecosystems varied between 155 and 162 Pg C across the three emission scenarios when potential natural vegetation was simulated. With land use, periodic harvest of croplands and timberlands as well as the prevention of woody expansion across the West reduced carbon stocks to a range of 122-126 Pg C, while effective fire suppression reduced fire emissions by about 50%. Despite the simplicity of our approach, the differences between the size of the carbon stocks confirm other reports of the importance of land use on the carbon cycle over climate change.
Climate change has already affected southern California where regional increases in temperature and vegetation shifts have been observed. While all the CMIP5 temperature projections agree on a substantial level of warming throughout the year, there is fair bit of divergence in the magnitude and seasonality of projected changes in rainfall. While desert plants and animals are generally adapted to extreme conditions, some species may be approaching their physiological threshold. We calculated the climate velocity of both temperature and aridity (PPT/PET) in SE California to illustrate the spatial variability of climate projections and reported on the probable expansion of barren lands reducing current species survivorship. We used a vegetation model to illustrate both temporal and spatial shifts in land cover in response to changes in environmental conditions. Such information is useful to plan land use for renewable energy siting in the region.
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