Burn less, baby, burn less: Humans have, and always have had, a major impact on wildfire activity, which is expected to increase in our warming world. Andela et al. use satellite data to show that, unexpectedly, global burned area declined by ∼25% over the past 18 years, despite the influence of climate. The decrease has been largest in savannas and grasslands because of agricultural expansion and intensification. The decline of burned area has consequences for predictions of future changes to the atmosphere, vegetation, and the terrestrial carbon sink. Science , this issue p. 1356

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.

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.

Ecosystem services (ES) were conceived to emphasize the role of ecological processes in supporting societal needs and to allow their inclusion in the decision-making process. Currently climate change mitigation is one of the most important services ecosystems can provide to enhance sinks of greenhouse gas emissions as the planet warms and related extreme events take their toll on societies. Because ES cannot always be directly measured and because measurements are often cost prohibitive, process-based models are used to estimate their supply, delivery and/or value. We ran the MC2 dynamic global vegetation model for the conterminous US with/without land use for several future scenarios. We translated results into key ES such as carbon sequestration, which contributes to climate regulation, into a regulatory service or aboveground forest carbon into timber biomass, a provisioning service, and evaluated constraints to maintain them. By comparing projections with/without land use we illustrated differences between managed and natural lands and provided information to help the valuation of societally relevant services.

Conservation Biology Institute (CBI) has been developing web applications to centralize and serve credible and usable information that allows natural resource managers, as well as the general public, to better understand the challenges posed by on-going environmental change. In particular CBI has designed a series of climate consoles that provide natural resource managers the most recent 5th Climate Model Intercomparison Program (CMIP5) climate projections, landscape intactness, and soil sensitivity for a series of reporting units over the western United States. The publically available web sites were refined based on feedback from a variety of users. In this paper, we describe each of the tools developed as open-source applications and provide details of their infrastructure in the hope they can be used and possibly modified by a wider audience. They were designed to be used as stepping-stones towards planning effective climate change adaptation strategies.