Aim: While chaparral communities have historically been considered resistant to invasion and type conversion into grasslands, interacting global changes such as increased drought and anthropogenic disturbance may have reduced this resistance. Existing monitoring methods are not well‐suited to evaluate the distribution of invasive herbs and grasses within chaparral at regional scales. In this study, we determine the extent of invasions by forbs and grasses into formerly chaparral vegetation and evaluate contributions of moisture, disturbance and anthropogenic activity and topography to the distribution of herbaceous cover throughout chaparral‐dominated communities.Location: The Angeles National Forest (ANF), California,USA.Methods: We developed a remote‐sensing method to estimate the distribution of herbaceous cover within chaparral by leveraging intra‐annual phenological differences in normalized difference vegetation index (NDVI) between herbaceous forbs and grasses and evergreen shrublands using Landsat remote‐sensing imagery. The distribution of herbaceous cover was then related to multiple spatially explicit variables describing individual and interactive effects of local moisture availability and anthropogenic disturbance.Results: Herbaceous cover represents approximately 31% of theANFwithin the elevation range typically dominated by chaparral. Disturbance‐related and anthropogenic factors explained 17% of observed variation, while differences in moisture availability explained 47% of observed variation in herbaceous cover and were associated with increased invasive cover.Main conclusions: Landscapes historically dominated by chaparral may exhibit high degrees of herbaceous cover. While fire frequency and other anthropogenic disturbances are likely the primary catalyst for invasion of chaparral by herbaceous species, this study shows that moisture availability is a more important factor in determining which locations are successfully invaded. These results indicate that chaparral vulnerability to invasion in southern California may increase in the next century due to reduced precipitation associated with projected climate change.

In the face of recent wildfires across the Western United States, it is essential that we understand both the dynamics that drive the spatial distribution of wildfire, and the major obstacles to modeling the probability of wildfire over space and time. However, it is well documented that the precise relationships of local vegetation, climate, and ignitions, and how they influence fire dynamics, may vary over space and among local climate, vegetation, and land use regimes. This raises questions not only as to the nature of the potentially nonlinear relationships between local conditions and the fire, but also the possibility that the scale at which such models are developed may be critical to their predictive power and to the apparent relationship of local conditions to wildfire. In this study we demonstrate that both local climate–through limitations posed by fuel dryness (CWD) and availability (AET)–and human activity–through housing density, roads, electrical infrastructure, and agriculture, play important roles in determining the annual probabilities of fire throughout California. We also document the importance of previous burn events as potential barriers to fire in some environments, until enough time has passed for vegetation to regenerate sufficiently to sustain subsequent wildfires. We also demonstrate that long-term and short-term climate variations exhibit different effects on annual fire probability, with short-term climate variations primarily impacting fire probability during periods of extreme climate anomaly. Further, we show that, when using nonlinear modeling techniques, broad-scale fire probability models can outperform localized models at predicting annual fire probability. Finally, this study represents a powerful tool for mapping local fire probability across the state of California under a variety of historical climate regimes, which is essential to avoided emissions modeling, carbon accounting, and hazard severity mapping for the application of fire-resistant building codes across the state of California.