Fire-prone invasive grasses create novel ecosystem threats by increasing fine-fuel loads and continuity, which can alter fire regimes. While the existence of an invasive grass-fire cycle is well known, evidence of altered fire regimes is typically based on local-scale studies or expert knowledge. Here, we quantify the effects of 12 nonnative, invasive grasses on fire occurrence, size, and frequency across 29 US ecoregions encompassing more than one third of the conterminous United States. These 12 grass species promote fire locally and have extensive spatial records of abundant infestations. We combined agency and satellite fire data with records of abundant grass invasion to test for differences in fire regimes between invaded and nearby “uninvaded” habitat. Additionally, we assessed whether invasive grass presence is a significant predictor of altered fire by modeling fire occurrence, size, and frequency as a function of grass invasion, in addition to anthropogenic and ecological covariates relevant to fire. Eight species showed significantly higher fire-occurrence rates, which more than tripled for Schismus barbatus and Pennisetum ciliare. Six species demonstrated significantly higher mean fire frequency, which more than doubled for Neyraudia reynaudiana and Pennisetum ciliare . Grass invasion was significant in fire occurrence and frequency models, but not in fire-size models. The significant differences in fire regimes, coupled with the importance of grass invasion in modeling these differences, suggest that invasive grasses alter US fire regimes at regional scales. As concern about US wildfires grows, accounting for fire-promoting invasive grasses will be imperative for effectively managing ecosystems.

Large fires account for the majority of burned area and are an important focus of fire management. However, ‘large’ is typically defined by a fire size threshold, minimizing the importance of proportionally large fires in less fire-prone ecoregions. Here, we defined ‘large fires’ as the largest 10% of wildfires by ecoregion (n = 175,222 wildfires from 1992 to 2015) across the United States (U.S.). Across ecoregions, we compared fire size, seasonality, and environmental conditions (e.g., wind speed, fuel moisture, biomass, vegetation type) of large human- and lighting-started fires that required a suppression response. Mean large fire size varied by three orders of magnitude: from 1 to 10 ha in the Northeast vs. >1000 ha in the West. Humans ignited four times as many large fires as lightning, and were the dominant source of large fires in the eastern and western U.S. (starting 92% and 65% of fires, respectively). Humans started 80,896 large fires in seasons when lightning-ignited fires were rare. Large human-started fires occurred in locations and months of significantly higher fuel moisture and wind speed than large lightning-started fires. National-scale fire policy should consider risks to ecosystems and economies by these proportionally large fires and include human drivers in large fire risk assessment.

Humans have a profound effect on fire regimes by increasing the frequency of ignitions. Although ignition is an integral component of understanding and predicting fire, to date fire models have not been able to isolate the ignition location, leading to inconsistent use of anthropogenic ignition proxies. Here, we identified fire ignitions from the Moderate Resolution Imaging Spectrometer (MODIS) Burned Area Product (2000–2012) to create the first remotely sensed, consistently derived, and regionally comprehensive fire ignition data set for the western United States. We quantified the spatial relationships between several anthropogenic land‐use/disturbance features and ignition for ecoregions within the study area and used hierarchical partitioning to test how the anthropogenic predictors of fire ignition vary among ecoregions. The degree to which anthropogenic features predicted ignition varied considerably by ecoregion, with the strongest relationships found in the Marine West Coast Forest and North American Desert ecoregions. Similarly, the contribution of individual anthropogenic predictors varied greatly among ecoregions. Railroad corridors and agricultural presence tended to be the most important predictors of anthropogenic ignition, while population density and roads were generally poor predictors. Although human population has often been used as a proxy for ignitions at global scales, it is less important at regional scales when more specific land uses (e.g., agriculture) can be identified. The variability of ignition predictors among ecoregions suggests that human activities have heterogeneous impacts in altering fire regimes within different vegetation types and geographies.

Significance: International concern about the consequences of human-induced global environmental changes has prompted a renewed focus on reducing ecological effects of biological invasions, climate change, and nutrient pollution. Our results show that the combined effects of nonnative species invasions and abiotic global environmental changes are often negative but no worse than invasion impacts alone. Invasion impacts are also more strongly detrimental than warming temperatures or nitrogen deposition, two common stressors. Thus, reducing the spread of invasive species is critical for mitigating harms from anthropogenic changes to global ecosystems.

Non‐native, invasive Bromus tectorum (cheatgrass) is pervasive in sagebrush ecosystems in the Great Basin ecoregion of the western United States, competing with native plants and promoting more frequent fires. As a result, cheatgrass invasion likely alters carbon (C) storage in the region. Many studies have measured C pools in one or more common vegetation types: native sagebrush, invaded sagebrush and cheatgrass‐dominated (often burned) sites, but these results have yet to be synthesized. We performed a literature review to identify studies assessing the consequences of invasion on C storage in above‐ground biomass (AGB), below‐ground biomass (BGB), litter, organic soil and total soil. We identified 41 articles containing 386 unique studies and estimated C storage across pools and vegetation types. We used linear mixed models to identify the main predictors of C storage. We found consistent declines in biomass C with invasion: AGB C was 55% lower in cheatgrass (40 ± 4 g C/m²) than native sagebrush (89 ± 27 g C/m²) and BGB C was 62% lower in cheatgrass (90 ± 17 g C/m²) than native sagebrush (238 ± 60 g C/m²). In contrast, litter C was >4× higher in cheatgrass (154 ± 12 g C/m²) than native sagebrush (32 ± 12 g C/m²). Soil organic C (SOC) in the top 10 cm was significantly higher in cheatgrass than in native or invaded sagebrush. SOC below 20 cm was significantly related to the time since most recent fire and losses were observed in deep SOC in cheatgrass >5 years after a fire. There were no significant changes in total soil C across vegetation types. Synthesis and applications. Cheatgrass invasion decreases biodiversity and rangeland productivity and alters fire regimes. Our findings indicate cheatgrass invasion also results in persistent biomass carbon (C) losses that occur with sagebrush replacement. We estimate that conversion from native sagebrush to cheatgrass leads to a net reduction of C storage in biomass and litter of 76 g C/m², or 16 Tg C across the Great Basin without management practices like native sagebrush restoration or cheatgrass removal.