A B S T R A C T Greenhouse gas emissions have significantly altered global climate, and will continue to do so in the future. Increases in the frequency, duration, and/or severity of drought and heat stress associated with climate change could fundamentally alter the composition, structure, and biogeography of forests in many regions. Of particular concern are potential increases in tree mortality associated with climateinduced physiological stress and interactions with other climate-mediated processes such as insect outbreaks and wildfire. Despite this risk, existing projections of tree mortality are based on models that lack functionally realistic mortality mechanisms, and there has been no attempt to track observations of climate-driven tree mortality globally. Here we present the first global assessment of recent tree mortality attributed to drought and heat stress. Although episodic mortality occurs in the absence of climate change, studies compiled here suggest that at least some of the world's forested ecosystems already may be responding to climate change and raise concern that forests may become increasingly vulnerable to higher background tree mortality rates and die-off in response to future warming and drought, even in environments that are not normally considered water-limited. This further suggests risks to ecosystem services, including the loss of sequestered forest carbon and associated atmospheric feedbacks. Our review also identifies key information gaps and scientific uncertainties that currently hinder our ability to predict tree mortality in response to climate change and emphasizes the need for a globally coordinated observation system. Overall, our review reveals the potential for amplified tree mortality due to drought and heat in forests worldwide.Published by Elsevier B.V.

Fire is an essential Earth system process that alters ecosystem and atmospheric composition. Here we assessed long-term fire trends using multiple satellite data sets. We found that global burned area declined by 24.3 ± 8.8% over the past 18 years. The estimated decrease in burned area remained robust after adjusting for precipitation variability and was largest in savannas. Agricultural expansion and intensification were primary drivers of declining fire activity. Fewer and smaller fires reduced aerosol concentrations, modified vegetation structure, and increased the magnitude of the terrestrial carbon sink. Fire models were unable to reproduce the pattern and magnitude of observed declines, suggesting that they may overestimate fire emissions in future projections. Using economic and demographic variables, we developed a conceptual model for predicting fire in human-dominated landscapes.

Abstract. Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.

Net primary production (NPP), the difference between CO2 fixed by photosynthesis and CO2 lost to autotrophic respiration, is one of the most important components of the carbon cycle. Our goal was to develop a simple regression model to estimate global NPP using climate and land cover data. Approximately 5600 global data points with observed mean annual NPP, land cover class, precipitation, and temperature were compiled. Precipitation was better correlated with NPP than temperature, and it explained much more of the variability in mean annual NPP for grass- or shrub-dominated systems (r2 = 0.68) than for tree-dominated systems (r2 = 0.39). For a given precipitation level, tree-dominated systems had significantly higher NPP (approximately 100-150 g C m(-2) yr(-1)) than non-tree-dominated systems. Consequently, previous empirical models developed to predict NPP based on precipitation and temperature (e.g., the Miami model) tended to overestimate NPP for non-tree-dominated systems. Our new model developed at the National Center for Ecological Analysis and Synthesis (the NCEAS model) predicts NPP for tree-dominated systems based on precipitation and temperature; but for non-tree-dominated systems NPP is solely a function of precipitation because including a temperature function increased model error for these systems. Lower NPP in non-tree-dominated systems is likely related to decreased water and nutrient use efficiency and higher nutrient loss rates from more frequent fire disturbances. Late 20th century aboveground and total NPP for global potential native vegetation using the NCEAS model are estimated to be approximately 28 Pg and approximately 46 Pg C/yr, respectively. The NCEAS model estimated an approximately 13% increase in global total NPP for potential vegetation from 1901 to 2000 based on changing precipitation and temperature patterns.

The important role of fire in regulating vegetation community composition and contributions to emissions of greenhouse gases and aerosols make it a critical component of dynamic global vegetation models and Earth system models. Over 2 decades of development, a wide variety of model structures and mechanisms have been designed and incorporated into global fire models, which have been linked to different vegetation models. However, there has not yet been a systematic examination of how these different strategies contribute to model performance. Here we describe the structure of the first phase of the Fire Model Intercomparison Project (FireMIP), which for the first time seeks to systematically compare a number of models. By combining a standardized set of input data and model experiments with a rigorous comparison of model outputs to each other and to observations, we will improve the understanding of what drives vegetation fire, how it can best be simulated, and what new or improved observational data could allow better constraints on model behavior. In this paper, we introduce the fire models used in the first phase of FireMIP, the simulation protocols applied, and the benchmarking system used to evaluate the models. We have also created supplementary tables that describe, in thorough mathematical detail, the structure of each model

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The objective of this study was to dynamically simulate the response of vegetation distribution, carbon, and fire to the historical climate and to two contrasting scenarios of climate change in California. The results of the simulations for the historical climate compared favorably to independent estimates and observations, but validation of the results was complicated by the lack of land use effects in the model. The response to increasing temperatures under both scenarios was characterized by a shift in dominance from needle-leaved to broad-leaved life-forms and by increases in vegetation productivity, especially in the relatively cool and mesic regions of the state. The simulated response to changes in precipitation were complex, involving not only the effect of changes in soil moisture on vegetation productivity, but also changes in tree-grass competition mediated by fire. Summer months were warmer and persistently dry under both scenarios, so the trends in simulated fire area under both scenarios were primarily a response to changes in vegetation biomass. Total ecosystem carbon increased under both climate scenarios, but the proportions allocated to the wood and grass carbon pools differed. The results of the simulations underscore the potentially large impact of climate change on California ecosystems, and the need for further use and development of dynamic vegetation models using various ensembles of climate change scenarios.

The response of vegetation distribution, carbon, and fire to three scenarios of future climate change was simulated for California using the MC1 Dynamic General Vegetation Model. Under all three scenarios, Alpine/Subalpine Forest cover declined, and increases in the productivity of evergreen hardwoods led to the displacement of Evergreen Conifer Forest by Mixed Evergreen Forest. Grassland expanded, largely at the expense of Woodland and Shrubland, even under the cooler and less dry climate scenario where increased woody plant production was offset by increased wildfire. Increases in net primary productivity under the cooler and less dry scenario contributed to a simulated carbon sink of about 321 teragrams for California by the end of the century. Declines in net primary productivity under the two warmer and drier scenarios contributed to a net loss of carbon ranging from about 76 to 129 teragrams. Total annual area burned in California increased under all three scenarios, ranging from 9-15% above the historical norm by the end of the century. Annual biomass consumption by fire by the end of the century was about 18% greater than the historical norm under the more productive cooler and less dry scenario. Under the warmer and drier scenarios, simulated biomass consumption was initially greater, but then at, or below, the historical norm by the end of the century.