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1.
Glob Chang Biol ; 27(18): 4339-4351, 2021 Sep.
Article in English | MEDLINE | ID: mdl-34213047

ABSTRACT

Changing climate and disturbance regimes are increasingly challenging the resilience of forest ecosystems around the globe. A powerful indicator for the loss of resilience is regeneration failure, that is, the inability of the prevailing tree species to regenerate after disturbance. Regeneration failure can result from the interplay among disturbance changes (e.g., larger and more frequent fires), altered climate conditions (e.g., increased drought), and functional traits (e.g., method of seed dispersal). This complexity makes projections of regeneration failure challenging. Here we applied a novel simulation approach assimilating data-driven fire projections with vegetation responses from process modeling by means of deep neural networks. We (i) quantified the future probability of regeneration failure; (ii) identified spatial hotspots of regeneration failure; and (iii) assessed how current forest types differ in their ability to regenerate under future climate and fire. We focused on the Greater Yellowstone Ecosystem (2.9 × 106  ha of forest) in the Rocky Mountains of the USA, which has experienced large wildfires in the past and is expected to undergo drastic changes in climate and fire in the future. We simulated four climate scenarios until 2100 at a fine spatial grain (100 m). Both wildfire activity and unstocked forest area increased substantially throughout the 21st century in all simulated scenarios. By 2100, between 28% and 59% of the forested area failed to regenerate, indicating considerable loss of resilience. Areas disproportionally at risk occurred where fires are not constrained by topography and in valleys aligned with predominant winds. High-elevation forest types not adapted to fire (i.e., Picea engelmannii-Abies lasiocarpa as well as non-serotinous Pinus contorta var. latifolia forests) were especially vulnerable to regeneration failure. We conclude that changing climate and fire could exceed the resilience of forests in a substantial portion of Greater Yellowstone, with profound implications for carbon, biodiversity, and recreation.


Subject(s)
Pinus , Wildfires , Climate , Climate Change , Ecosystem , Forests
2.
PLoS One ; 12(12): e0188486, 2017.
Article in English | MEDLINE | ID: mdl-29244839

ABSTRACT

Predicting wildfire under future conditions is complicated by complex interrelated drivers operating across large spatial scales. Annual area burned (AAB) is a useful index of global wildfire activity. Current and antecedent seasonal climatic conditions, and the timing of snowpack melt, have been suggested as important drivers of AAB. As climate warms, seasonal climate and snowpack co-vary in intricate ways, influencing fire at continental and sub-continental scales. We used independent records of seasonal climate and snow cover duration (last date of permanent snowpack, LDPS) and cell-based Structural Equation Models (SEM) to separate direct (climatic) and indirect (snow cover) effects on relative changes in AAB under future climatic scenarios across western and boreal North America. To isolate seasonal climate variables with the greatest effect on AAB, we ran multiple regression models of log-transformed AAB on seasonal climate variables and LDPS. We used the results of multiple regressions to project future AAB using GCM ensemble climate variables and LDPS, and validated model predictions with recent AAB trends. Direct influences of spring and winter temperatures on AAB are larger and more widespread than the indirect effect mediated by changes in LDPS in most areas. Despite significant warming trends and reductions in snow cover duration, projected responses of AAB to early-mid 21st century are heterogeneous across the continent. Changes in AAB range from strongly increasing (one order of magnitude increases in AAB) to moderately decreasing (more than halving of baseline AAB). Annual wildfire area burned in coming decades is likely to be highly geographically heterogeneous, reflecting interacting regional and seasonal climate drivers of fire occurrence and spread.


Subject(s)
Models, Statistical , Weather , Wildfires/statistics & numerical data , Climate , Forecasting , Humans , Regression Analysis , Trees/growth & development , United States
3.
Environ Sci Technol ; 48(4): 2298-304, 2014 Feb 18.
Article in English | MEDLINE | ID: mdl-24443984

ABSTRACT

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.


Subject(s)
Air Pollutants/analysis , Climate Change , Fires , California , Computer Simulation , Forecasting , Humans , Particulate Matter/analysis
4.
Proc Natl Acad Sci U S A ; 108(32): 13165-70, 2011 Aug 09.
Article in English | MEDLINE | ID: mdl-21788495

ABSTRACT

Climate change is likely to alter wildfire regimes, but the magnitude and timing of potential climate-driven changes in regional fire regimes are not well understood. We considered how the occurrence, size, and spatial location of large fires might respond to climate projections in the Greater Yellowstone ecosystem (GYE) (Wyoming), a large wildland ecosystem dominated by conifer forests and characterized by infrequent, high-severity fire. We developed a suite of statistical models that related monthly climate data (1972-1999) to the occurrence and size of fires >200 ha in the northern Rocky Mountains; these models were cross-validated and then used with downscaled (~12 km × 12 km) climate projections from three global climate models to predict fire occurrence and area burned in the GYE through 2099. All models predicted substantial increases in fire by midcentury, with fire rotation (the time to burn an area equal to the landscape area) reduced to <30 y from the historical 100-300 y for most of the GYE. Years without large fires were common historically but are expected to become rare as annual area burned and the frequency of regionally synchronous fires increase. Our findings suggest a shift to novel fire-climate-vegetation relationships in Greater Yellowstone by midcentury because fire frequency and extent would be inconsistent with persistence of the current suite of conifer species. The predicted new fire regime would transform the flora, fauna, and ecosystem processes in this landscape and may indicate similar changes for other subalpine forests.


Subject(s)
Ecosystem , Fires , Global Warming , Computer Simulation , History, 21st Century , Wyoming
5.
Ecol Appl ; 19(4): 1003-21, 2009 Jun.
Article in English | MEDLINE | ID: mdl-19544740

ABSTRACT

The purpose of this paper is to quantify climatic controls on the area burned by fire in different vegetation types in the western United States. We demonstrate that wildfire area burned (WFAB) in the American West was controlled by climate during the 20th century (1916-2003). Persistent ecosystem-specific correlations between climate and WFAB are grouped by vegetation type (ecoprovinces). Most mountainous ecoprovinces exhibit strong year-of-fire relationships with low precipitation, low Palmer drought severity index (PDSI), and high temperature. Grass- and shrub-dominated ecoprovinces had positive relationships with antecedent precipitation or PDSI. For 1977-2003, a few climate variables explain 33-87% (mean = 64%) of WFAB, indicating strong linkages between climate and area burned. For 1916-2003, the relationships are weaker, but climate explained 25-57% (mean = 39%) of the variability. The variance in WFAB is proportional to the mean squared for different data sets at different spatial scales. The importance of antecedent climate (summer drought in forested ecosystems and antecedent winter precipitation in shrub and grassland ecosystems) indicates that the mechanism behind the observed fire-climate relationships is climatic preconditioning of large areas of low fuel moisture via drying of existing fuels or fuel production and drying. The impacts of climate change on fire regimes will therefore vary with the relative energy or water limitations of ecosystems. Ecoprovinces proved a useful compromise between ecologically imprecise state-level and localized gridded fire data. The differences in climate-fire relationships among the ecoprovinces underscore the need to consider ecological context (vegetation, fuels, and seasonal climate) to identify specific climate drivers of WFAB. Despite the possible influence of fire suppression, exclusion, and fuel treatment, WFAB is still substantially controlled by climate. The implications for planning and management are that future WFAB and adaptation to climate change will likely depend on ecosystem-specific, seasonal variation in climate. In fuel-limited ecosystems, fuel treatments can probably mitigate fire vulnerability and increase resilience more readily than in climate-limited ecosystems, in which large severe fires under extreme weather conditions will continue to account for most area burned.


Subject(s)
Climate , Ecosystem , Fires/history , History, 20th Century , History, 21st Century , Regression Analysis , United States
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