Radiative forcing of natural forest disturbances

Forest disturbances are major sources of carbon dioxide to the atmosphere, and therefore impact global climate. Biogeophysical attributes, such as surface albedo (reflectivity), further control the climate‐regulating properties of forests. Using both tower‐based and remotely sensed data sets, we show that natural disturbances from wildfire, beetle outbreaks, and hurricane wind throw can significantly alter surface albedo, and the associated radiative forcing either offsets or enhances the CO₂ forcing caused by reducing ecosystem carbon sequestration over multiple years. In the examined cases, the radiative forcing from albedo change is on the same order of magnitude as the CO₂ forcing. The net radiative forcing resulting from these two factors leads to a local heating effect in a hurricane‐damaged mangrove forest in the subtropics, and a cooling effect following wildfire and mountain pine beetle attack in boreal forests with winter snow. Although natural forest disturbances currently represent less than half of gross forest cover loss, that area will probably increase in the future under climate change, making it imperative to represent these processes accurately in global climate models.     

Bayesian prediction of wildfire event probability using normalized difference vegetation index data from an Australian forest

Wildfires are impactful natural disasters, creating a significant impact across many rural communities. Predicting wildfire probability provides authorities with invaluable information to take preventive measures at the early stages. This study establishes Bayesian modelling for predicting the wildfire event probability based on a set of environmental predictors and forest vulnerability, represented by the normalized difference vegetation index. Prior information about the impact of these predictors on the likelihood of wildfire is available in the reports on the past major wildfire events. In that sense, the use of prior information in the Bayesian models has the potential to provide accurate predictions for the wildfire probability. Moreover, the relationship between the predictors creates mediating effects on the likelihood of a wildfire event. A multivariate prior distribution in the Bayesian modelling can capture the mediating effects. In this study, Bayesian models with informative and noninformative priors are considered with independent and multivariate prior distributions to utilize the available prior information and handle the mediating effects between the predictors using the normalized difference vegetation index data provided by Google Earth Engine. Nine years of data were gathered across 9841 sampled areas in a forested land of Australia. Modelling results concluded that forest vulnerability is found to be the dominant predictor of wildfire probability. This modelling can help create a Wildfire Warning Index based on climate data and forest vulnerability measurements, enabling preventative actions in high-risk and targeted areas.     

Pockets of resistance: Response of arid‐land fish communities to climate,hydrology, and wildfire

相似文献   

树轮数据揭示的强火山喷发对青藏高原地区气候的影响

强火山喷发是影响全球气候变化的重要因素。过去几十年,不同学者基于青藏高原地区树木年轮重建了多条气候变化序列,并依据这些序列研究了全球强火山喷发对青藏高原地区气候的影响。结果表明: 探讨强火山喷发对青藏高原气候影响的树轮序列主要分布在青藏高原东部。利用序列对比法和时序叠加法分析发现,中低纬度的强火山喷发对青藏高原地区温度和干湿变化影响显著,并在强火山喷发后的1～2年内出现降温或者发生干旱,而高纬度的强火山喷发影响较小。此外,连续的多次强火山喷发能导致该区出现年代际的冷期。影响强火山喷发气候效应的因素主要包括火山喷发位置、喷发强度、大气环流等。最后结合国内外研究现状,对未来需要开展的研究方向进行了展望。     

Adapting to global environmental change in Patagonia: What role for disturbance ecology?

Research from the Patagonian‐Andean region is used to explore challenges and opportunities related to the integration of research on wildfire activity into a broader earth‐system science framework that views the biosphere and atmosphere as a coupled interacting system for understanding the causes and consequences of future wildfire activity. We examine how research in disturbance ecology can inform land‐use and other policy decisions in the context of probable future increases in wildfire activity driven by climate forcing. Climate research has related recent warming and drying trends in much of Patagonia to an upward trend in the Southern Annular Mode which is the leading pattern of extratropical climate variability in the southern hemisphere. Although still limited in spatial extent, tree‐ring fire history studies are beginning to reveal regional patterns of the top‐down climate influences on temporal and spatial pattern of wildfire occurrence in Patagonia. Knowledge of relationships of fire activity to climate variability in the context of predicted future warming leads to the hypothesis that wildfire activity in Patagonia will increase substantially during the first half of the 21st century. In addition to this anticipated increase in extreme fire events due to climate forcing, we further hypothesize that current land‐use trends will increase the extent and/or severity of fire events through bottom‐up (i.e. land surface) influences on wildfire potential. In particular, policy discussions of how to mitigate impacts of climate warming on fire potential need to consider research results from disturbance ecology on the implications of continued planting of flammable non‐native trees and the role of introduced herbivores in favouring vegetation changes that may enhance landscape flammability.     

Topographic information improves simulated patterns of post-fire conifer regeneration in the southwest United States

The western United States is projected to experience more frequent and severe wildfires in the future due to drier and hotter climate conditions, exacerbating destructive wildfire impacts on forest ecosystems such as tree mortality and unsuccessful post-fire regeneration. While empirical studies have revealed strong relationships between topographical information and plant regeneration, ecological processes in ecosystem models have either not fully addressed topography-mediated effects on the probability of plant regeneration, or the probability is only controlled by climate-related factors, for example, water and light stresses. In this study, we incorporated seedling survival data based on a planting experiment in the footprint of the 2011 Las Conchas Fire into the Photosynthesis and EvapoTranspiration (PnET) extension of the LANDIS-II model by adding topographic and an additional climatic variable to the probability of regeneration. The modified algorithm included topographic parameters such as heat load index and ground slope and spring precipitation. We ran simulations on the Las Conchas Fire landscape for 2012–2099 using observed and projected climate data (i.e., Representative Concentration Pathway 4.5 and 8.5). Our modification significantly reduced the number of regeneration events of three common southwestern conifer tree species (piñon, ponderosa pine, and Douglas-fir), leading to decreases in aboveground biomass, regardless of climate scenario. The modified algorithm decreased regeneration at higher elevations and increased regeneration at lower elevations relative to the original algorithm. Regenerations of three species also decreased in eastern aspects. Our findings suggest that ecosystem models may overestimate post-fire regeneration events in the southwest United States. To better represent regeneration processes following wildfire, ecosystem models need refinement to better account for the range of factors that influence tree seedling establishment. This will improve model utility for projecting the combined effects of climate and wildfire on tree species distributions.     

Using the noninformative families in family-based association tests: a powerful new testing strategy

For genetic association studies with multiple phenotypes, we propose a new strategy for multiple testing with family-based association tests (FBATs). The strategy increases the power by both using all available family data and reducing the number of hypotheses tested while being robust against population admixture and stratification. By use of conditional power calculations, the approach screens all possible null hypotheses without biasing the nominal significance level, and it identifies the subset of phenotypes that has optimal power when tested for association by either univariate or multivariate FBATs. An application of our strategy to an asthma study shows the practical relevance of the proposed methodology. In simulation studies, we compare our testing strategy with standard methodology for family studies. Furthermore, the proposed principle of using all data without biasing the nominal significance in an analysis prior to the computation of the test statistic has broad and powerful applications in many areas of family-based association studies.     

Wildfire–vegetation dynamics affect predictions of climate change impact on bird communities

Community‐level climate change indicators have been proposed to appraise the impact of global warming on community composition. However, non‐climate factors may also critically influence species distribution and biological community assembly. The aim of this paper was to study how fire–vegetation dynamics can modify our ability to predict the impact of climate change on bird communities, as described through a widely‐used climate change indicator: the community thermal index (CTI). Potential changes in bird species assemblage were predicted using the spatially‐explicit species assemblage modelling framework – SESAM – that applies successive filters to constrained predictions of richness and composition obtained by stacking species distribution models that hierarchically integrate climate change and wildfire–vegetation dynamics. We forecasted future values of CTI between current conditions and 2050, across a wide range of fire–vegetation and climate change scenarios. Fire–vegetation dynamics were simulated for Catalonia (Mediterranean basin) using a process‐based model that reproduces the spatial interaction between wildfire, vegetation dynamics and wildfire management under two IPCC climate scenarios. Net increases in CTI caused by the concomitant impact of climate warming and an increasingly severe wildfire regime were predicted. However, the overall increase in the CTI could be partially counterbalanced by forest expansion via land abandonment and efficient wildfire suppression policies. CTI is thus strongly dependent on complex interactions between climate change and fire–vegetation dynamics. The potential impacts on bird communities may be underestimated if an overestimation of richness is predicted but not constrained. Our findings highlight the need to explicitly incorporate these interactions when using indicators to interpret and forecast climate change impact in dynamic ecosystems. In fire‐prone systems, wildfire management and land‐use policies can potentially offset or heighten the effects of climate change on biological communities, offering an opportunity to address the impact of global climate change proactively.     

Cenozoic mean greenhouse gases and temperature changes with reference to the Anthropocene

Cenozoic greenhouse gases (GHG) variations and warming periods underscore the extreme rates of current climate change, with major implications for the adaptability and survivability of terrestrial and marine habitats. Current rise rate of greenhouse gases, reaching 3.3 ppm CO₂ per year during March 2015–2016, is the fastest recorded since the Paleocene‐Eocene Thermal Event (PETM) when carbon release to the atmosphere was about an order of magnitude less than at present. The ice core evidence of concentration of (GHG) and temperatures in the atmosphere/ocean/cryosphere system over the last 740 kyr suggests that the rate of rise in GHG over the last ~260 years, CO₂ rates rising from 0.94 ppm yr^?1 in 1959 (315.97 ppm) to 1.62 ppm yr^?1 in 2000 (369.52 ppm) to 3.05 ppm yr^?1 in 2015 (400.83 ppm), constitutes a unique spike in the history of the atmosphere. The reliance of pre‐740 kyr paleoclimate estimates on multiple proxies, including benthic and plankton fossils, fossil plants, residual organic matter, major and trace elements in fossils, sediments and soils, place limits on the resolution of pre‐upper Pleistocene paleoclimate estimates, rendering it likely recorded mean Cenozoic paleoclimate trends may conceal abrupt short‐term climate fluctuations. However, as exemplified by the Paleocene–Eocene thermal maximum (PETM) and earlier GHG and temperature spikes associated with major volcanic and asteroid impact events, the long‐term residence time of CO₂ in the atmosphere extends the signatures of abrupt warming events to within detection limits of multiple paleoproxies. The mean post‐1750 temperature rise rate (approximately ~0.0034 °C per yr, or ~0.008 °C per yr where temperature is not masked by sulfur aerosols) exceeds those of the PETM (approximately ~0.0008–0.0015 °C per yr) by an order of magnitude and mean glacial termination warming rates (last glacial termination [LGT] ~ 0.00039; Eemian ~0.0004 °C per yr) by near to an order of magnitude. Consistent with previous interglacial peaks an increasing likelihood of collapse of the Atlantic Meridional Ocean Circulation is threatening a severe stadial event.     

A Bayesian modeling of wildfire probability in the Zagros Mountains,Iran

The preparation of probability distribution maps is the first important step in risk assessment and wildfire management. Here we employed Weights-of-Evidence (WOE) Bayesian modeling to investigate the spatial relationship between historical fire events in the Chaharmahal-Bakhtiari Province of Iran, using a wide range of binary predictor variables (i.e., presence or absence of a variable characteristic or condition) that represent topography, climate, and human activities. Model results were used to produce distribution maps of wildfire probability. Our modeling approach is based on the assumption that the probabilities reflect the observed proportions of the total landscape area occupied by the corresponding events (i.e., fire incident or no fire) and conditions (i.e., classes) of predictor variables. To assess the effect of each predictor variable on model outputs, we excluded each variable in turn during calculations. The results were validated and compared by the receiver operating characteristic (ROC) using both success rate and prediction rate curves. Seventy percent of fire events were used for the former, while the remainder was used for the latter. The validation results showed that the area under the curves (AUC) for success and prediction rates of the model that included all thirteen predictor variables that represent topography, climate, and human influences were 84.6 and 80.4%, respectively. The highest AUC for success and prediction rates (86.8 and 84.6%) were achieved when the altitude variable was excluded from the analysis. We found slightly decreased AUC values when the slope-aspect and proximity to settlements variables were excluded. These findings clearly demonstrate that the probability of a fire is strongly dependent upon the topographic characteristics of landscapes and, perhaps more importantly, human infrastructure and associated human activities. The results from this study may be useful for land use planning, decision-making for wildfire management, and the allocation of fire resources prior to the start of the main fire season.     

Wildfire potential evaluation during a drought event with a regional climate model and NDVI

Regional climate modeling is a technique for simulating high-resolution physical processes in the atmosphere, soil and vegetation. It can be used to evaluate wildfire potential by either providing meteorological conditions for computation of fire indices or predicting soil moisture as a direct measure of fire potential. This study examines these roles using a regional climate model (RCM) for the drought and wildfire events in 1988 in the northern United States. The National Center for Atmospheric Research regional climate model (RegCM) was used to conduct simulations of a summer month in each year from 1988 to 1995. The simulated precipitation and maximum surface air temperature were used to calculate the Keetch–Byram Drought Index (KBDI), which is a popular fire potential index. We found that the KBDI increased significantly under the simulated drought condition. The corresponding fire potential was upgraded from moderate for a normal year to high level for the drought year. High fire potential is often an indicator for occurrence of intense and extensive wildfires. Fire potential changed in the opposite direction for the 1993 flood event, indicating little possibility of severe wildfires. The soil moisture and KBDI evaluations under the drought and flood conditions are in agreement with satellite remotely sensed vegetation conditions and the actual wildfire activity. The precipitation anomaly was a more important contributor to the KBDI changes than temperature anomaly. The small magnitude of the simulated soil moisture anomalies during the drought event did not provide sufficient evidence for the role of simulated soil moisture as a direct measure of wildfire potential.     

The adaptive potential of plant populations in response to extreme climate events

The frequency and magnitude of extreme climate events are increasing with global change, yet we lack predictions and empirical evidence for the ability of wild populations to persist and adapt in response to these events. Here, we used Fisher's Fundamental Theorem of Natural Selection to evaluate the adaptive potential of Lasthenia fremontii, a herbaceous winter annual that is endemic to seasonally flooded wetlands in California, to alternative flooding regimes that occur during El Niño Southern Oscillation (ENSO) events. The results indicate that populations may exhibit greater adaptive potential in response to dry years than wet years, and that the relative performance of populations will change across climate scenarios. More generally, our findings show that extreme climate events can substantially change the potential for populations to adapt to climate change by modulating the expression of standing genetic variation and mean fitness.     

全球变化背景下野火研究进展

野火是森林和多种植被生态系统面临的最重要自然干扰,也是一种重要的自然灾害;而人类活动已在全球范围内显著影响了野火的发生与分布,因此野火成为全球变化及其环境影响研究的关键议题之一。本文基于国际野火研究的文献搜索和统计分析,从野火的观测-评估-预警技术、野火时空格局研究、气候变化和人类活动对野火的影响、野火的环境-生态-进化效应等方面入手,综述了自21世纪以来的国际野火研究进展。概括起来,遥感技术的快速发展,推动了野火观测的时空分辨率不断提高,对野火时空格局的刻画从单一因子向多重指标的火烧体系评估转变。气候变化在某些区域已经显著影响了野火的发生频率,预计随着全球变暖野火风险将进一步加大,并且极端大火的发生机制和生态影响越来越受到关注。人类活动一方面通过增加火源提高了野火频率,另一方面又通过提高生态系统管理的强度、扑救火灾以及降低可燃物的连通性抑制了野火的发生。植被在长期演化过程中形成了一系列适应火的功能机制,这些功能属性影响着生态系统对野火的响应,并对火后生态恢复和重建具有科学指导价值。未来野火研究将向跨时空尺度、观测和模拟深度融合、典型机制和大尺度效应相结合的方向发展。     

Climatic thresholds shape northern high‐latitude fire regimes and imply vulnerability to future climate change

Boreal forests and arctic tundra cover 33% of global land area and store an estimated 50% of total soil carbon. Because wildfire is a key driver of terrestrial carbon cycling, increasing fire activity in these ecosystems would likely have global implications. To anticipate potential spatiotemporal variability in fire‐regime shifts, we modeled the spatially explicit 30‐yr probability of fire occurrence as a function of climate and landscape features (i.e. vegetation and topography) across Alaska. Boosted regression tree (BRT) models captured the spatial distribution of fire across boreal forest and tundra ecoregions (AUC from 0.63–0.78 and Pearson correlations between predicted and observed data from 0.54–0.71), highlighting summer temperature and annual moisture availability as the most influential controls of historical fire regimes. Modeled fire–climate relationships revealed distinct thresholds to fire occurrence, with a nonlinear increase in the probability of fire above an average July temperature of 13.4°C and below an annual moisture availability (i.e. P‐PET) of approximately 150 mm. To anticipate potential fire‐regime responses to 21st‐century climate change, we informed our BRTs with Coupled Model Intercomparison Project Phase 5 climate projections under the RCP 6.0 scenario. Based on these projected climatic changes alone (i.e. not accounting for potential changes in vegetation), our results suggest an increasing probability of wildfire in Alaskan boreal forest and tundra ecosystems, but of varying magnitude across space and throughout the 21st century. Regions with historically low flammability, including tundra and the forest–tundra boundary, are particularly vulnerable to climatically induced changes in fire activity, with up to a fourfold increase in the 30‐yr probability of fire occurrence by 2100. Our results underscore the climatic potential for novel fire regimes to develop in these ecosystems, relative to the past 6000–35 000 yr, and spatial variability in the vulnerability of wildfire regimes and associated ecological processes to 21st‐century climate change.     

Characterizing differences in precipitation regimes of extreme wet and dry years: implications for climate change experiments

Climate change is intensifying the hydrologic cycle and is expected to increase the frequency of extreme wet and dry years. Beyond precipitation amount, extreme wet and dry years may differ in other ways, such as the number of precipitation events, event size, and the time between events. We assessed 1614 long‐term (100 year) precipitation records from around the world to identify key attributes of precipitation regimes, besides amount, that distinguish statistically extreme wet from extreme dry years. In general, in regions where mean annual precipitation (MAP) exceeded 1000 mm, precipitation amounts in extreme wet and dry years differed from average years by ~40% and 30%, respectively. The magnitude of these deviations increased to >60% for dry years and to >150% for wet years in arid regions (MAP<500 mm). Extreme wet years were primarily distinguished from average and extreme dry years by the presence of multiple extreme (large) daily precipitation events (events >99th percentile of all events); these occurred twice as often in extreme wet years compared to average years. In contrast, these large precipitation events were rare in extreme dry years. Less important for distinguishing extreme wet from dry years were mean event size and frequency, or the number of dry days between events. However, extreme dry years were distinguished from average years by an increase in the number of dry days between events. These precipitation regime attributes consistently differed between extreme wet and dry years across 12 major terrestrial ecoregions from around the world, from deserts to the tropics. Thus, we recommend that climate change experiments and model simulations incorporate these differences in key precipitation regime attributes, as well as amount into treatments. This will allow experiments to more realistically simulate extreme precipitation years and more accurately assess the ecological consequences.     

不同径级油松径向生长对气候的响应

建立了黑里河自然保护区油松年轮宽度年表,通过不同径级油松径向生长对逐月气候因子的响应关系,研究了干旱对不同径级油松径向生长的影响。结果表明:两个径级油松的年轮宽度指数达到极显著相关(R=0.943,P<0.01),其中小径级(平均胸径20 cm)油松年表的平均敏感度显著高于大径级(平均胸径43 cm)油松年表(P<0.01)。不同径级油松均与上年9月、当年2月及当年5—6月的降水显著正相关(P<0.05),与当年6月的平均温度显著负相关(P<0.05),此外,小径级油松还与当年7月的降水显著正相关(P<0.05);降水是影响油松生长的主要气候因子。不同径级油松的径向生长量在干旱年份均显著降低(P<0.01)且小径级油松的生长降低量显著高于大径级油松(P<0.01);不同径级油松生长量在干旱发生后1年左右的时间内均恢复正常且小径级油松恢复速度更快。     

Volcanic explosive eruptions of the Vesuvio decrease tree-ring growth but not photosynthetic rates in the surrounding forests

Volcanic eruptions impact the global and the hemispheric climate, but it is still unknown how and to what degree they force the climate system and in particular the global carbon cycle. In this paper, the relationships between individual eruptions (reconstructed for the past using written records), tree primary productivity (estimated using ring widths), photosynthetic rate and stomatal conductance (assessed by carbon and oxygen isotope data) are investigated, to understand the impact of volcanic eruptions on net primary production. Data from a mixed stand of Fagus sylvatica L. and Acer pseudoplatanus L. located in the area of the Vesuvio volcanic complex (Southern Italy) showed a significant decrease in ring width following each eruption. Isotope analyses indicate a change in climatic conditions after such events. Specifically, the lower oxygen isotope ratio in the tree‐ring cellulose strongly suggests an increase in relative humidity and a decrease in temperature, with the latter resulting in a strong limitation to tree‐ring growth. The carbon isotope ratio was only moderately but not significantly reduced in the years of volcanic eruption, suggesting no major changes in C fixation rates. This work is a case study on the effects of volcanic eruptions resulting in strong climatic changes on the local scale. This is an opportunity to explore the process and causal relationships between climatic changes and the response of the vegetation. Thus, we propose here a realistic model scenario, from which we can extrapolate to global scales and improve our interpretations of results of global studies.     

Responses of Bacterial Communities to Simulated Climate Changes in Alpine Meadow Soil of the Qinghai-Tibet Plateau

The soil microbial community plays an important role in terrestrial carbon and nitrogen cycling. However, microbial responses to climate warming or cooling remain poorly understood, limiting our ability to predict the consequences of future climate changes. To address this issue, it is critical to identify microbes sensitive to climate change and key driving factors shifting microbial communities. In this study, alpine soil transplant experiments were conducted downward or upward along an elevation gradient between 3,200 and 3,800 m in the Qinghai-Tibet plateau to simulate climate warming or cooling. After a 2-year soil transplant experiment, soil bacterial communities were analyzed by pyrosequencing of 16S rRNA gene amplicons. The results showed that the transplanted soil bacterial communities became more similar to those in their destination sites and more different from those in their “home” sites. Warming led to increases in the relative abundances in Alphaproteobacteria, Gammaproteobacteria, and Actinobacteria and decreases in Acidobacteria, Betaproteobacteria, and Deltaproteobacteria, while cooling had opposite effects on bacterial communities (symmetric response). Soil temperature and plant biomass contributed significantly to shaping the bacterial community structure. Overall, climate warming or cooling shifted the soil bacterial community structure mainly through species sorting, and such a shift might correlate to important biogeochemical processes such as greenhouse gas emissions. This study provides new insights into our understanding of soil bacterial community responses to climate warming and cooling.     

Regeneration and invasion of cottonwood riparian forest following wildfire

Populus deltoides is considered to be a weak resprouter and highly susceptible to wildfire, but few post‐wildfire studies have tracked P. deltoides response and resprouting within the Great Plains of North America. Following a wildfire in southwestern Kansas, U.S.A., we surveyed burned and unburned areas of a cottonwood riparian forest along the Cimarron River that included a major understory invader, tamarisk (Tamarix ramosissima Ledeb.). We tested the following hypotheses, which are consistent with the current understanding of P. deltoides response to wildfire in the Great Plains: (1) regeneration of P. deltoides will be low in areas burned by the wildfire; (2) the number of dead P. deltoides individuals will be greater in the wildfire than unburned areas; and (3) tamarisk regeneration will be higher than P. deltoides regeneration in the wildfire areas because tamarisk is considered a stronger resprouter. We found evidence contrary to two of our hypotheses 3 years following the wildfire. (1) P. deltoides regeneration was high following the wildfire, averaging 692 individuals/ha. (2) The number of dead mature cottonwood trees was greater in wildfire plots than in unburned plots. (3) There was more P. deltoides regeneration than tamarisk regeneration following wildfire. These findings, which diverge from the majority of studies examining P. deltoides regeneration in the Great Plains, suggest that differing local environmental and forest stand conditions, coupled with the timing and intensity of the fire, could be important determinants of riparian forest species' responses to wildfire.     

Privatization, Drought, and Fire Exclusion in the Tuul River Watershed, Mongolia

Global wildfire frequency and extent are expected to increase under projected climate change in the twenty-first century, yet little is known about how human activities might affect this trend. In central Mongolia, there has been a 2.5°C rise in spring and summer temperatures during the last 40 years and a decrease in moisture availability during the latter half of the twentieth century. Concurrently, Mongolia has experienced multiple shifts in socioeconomic systems during the twentieth century, most notably the establishment of a Soviet-backed communist economy in the 1920s and a rapid transition to privatization in the 1990s. Observed records of fire in the late twentieth century suggested that fire activity had increased, but no long-term data existed to place these trends in a historical context. Our objective was to identify spatial and temporal patterns in fire occurrence in the forest-steppe ecotone of the Tuul River watershed in the context of changing climatic and social conditions since 1875. We used fire-scarred trees to reconstruct past fire occurrence during the period 1875–2009. Our results indicate a significant association between human activity and fire occurrence independent of climatic variables. The greatest evidence for an anthropogenic fire regime exists following the transition to a free market economy during the early 1990s when land-use intensification near the capital city of Ulaanbaatar resulted in fire exclusion. We emphasize the importance of including socio-political variables in global models of wildfire potential, particularly where fuels limit fire activity.