Joe R. Melton

A human-driven decline in global burned area

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 Global burned area has declined by ~25% over the past 18 years. 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.

A multiyear estimate of methane fluxes in Alaska from CARVE atmospheric observations

Methane (CH4) fluxes from Alaska and other arctic regions may be sensitive to thawing permafrost and future climate change, but estimates of both current and future fluxes from the region are uncertain. This study estimates CH4 fluxes across Alaska for 2012-2014 using aircraft observations from the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) and a geostatistical inverse model (GIM). We find that a simple flux model based on a daily soil temperature map and a static map of wetland extent reproduces the atmospheric CH4 observations at the state-wide, multi-year scale more effectively than global-scale, state-of-the-art process-based models. This result points to a simple and effective way of representing CH4 flux patterns across Alaska. It further suggests that contemporary process-based models can improve their representation of key processes that control fluxes at regional scales, and that more complex processes included in these models cannot be evaluated given the information content of available atmospheric CH4 observations. In addition, we find that CH4 emissions from the North Slope of Alaska account for 24% of the total statewide flux of 1.74 ± 0.44 Tg CH4 (for May-Oct.). Contemporary global-scale process models only attribute an average of 3% of the total flux to this region. This mismatch occurs for two reasons: process models likely underestimate wetland area in regions without visible surface water, and these models prematurely shut down CH4 fluxes at soil temperatures near 0°C. As a consequence, wetlands covered by vegetation and wetlands with persistently cold soils could be larger contributors to natural CH4 fluxes than in process estimates. Lastly, we find that the seasonality of CH4 fluxes varied during 2012-2014, but that total emissions did not differ significantly among years, despite substantial differences in soil temperature and precipitation; year-to-year variability in these environmental conditions did not affect obvious changes in total CH4 fluxes from the state.

Reduction in global area burned and wildfire emissions since 1930s enhances carbon uptake by land

The terrestrial biosphere currently absorbs about 30% of anthropogenic CO2 emissions. This carbon uptake over land results primarily from vegetation’s response to increasing atmospheric CO2 but other factors also play a role. Here we show that since the 1930s increasing population densities and cropland area have decreased global area burned, consistent with the charcoal record and recent satellite-based observations. The associated reduced wildfire emissions from increase in cropland area do not enhance carbon uptake since natural vegetation that is spared burning was deforested anyway. However, reduction in fire CO2 emissions due to fire suppression and landscape fragmentation associated with increases in population density is calculated to enhance land carbon uptake by 0.13 Pg C yr−1, or ~19% of the global land carbon uptake (0.7 ± 0.6 Pg C yr−1), for the 1960–2009 period. These results identify reduction in global wildfire CO2 emissions as yet another mechanism that is currently enhancing carbon uptake over land.Anthropogenic influences alter natural fire regimes in multiple ways but the resulting effect on the land carbon budget has not been quantified. Here the authors show that the reduction in global area burned and wildfire emissions due to anthropogenic influences is currently enhancing carbon uptake over land.

An improved parameterization of leaf area index (LAI) seasonality in the Canadian Land Surface Scheme (CLASS) and Canadian Terrestrial Ecosystem Model (CTEM) modelling framework

The study by Asaadi et al. aims to improve the seasonal timing of LAI simulated by the CTEM model by including a representation of non-structural carbon (NSC) pools and fluxes in the model (in addition to a few other modifications). The new developments in the model are tested at three temperate broadleaved deciduous sites against LAI, carbon and energy flux observations. They show an improvement in the timing of

Emergent relationships on burned area in global satellite observations and fire-enabled vegetation models

Abstract. Recent climate changes increases fire-prone weather conditions and likely affects fire occurrence, which might impact ecosystem functioning, biogeochemical cycles, and society. Prediction of how fire impacts may change in the future is difficult because of the complexity of the controls on fire occurrence and burned area. Here we aim to assess how process-based fire-enabled Dynamic Global Vegetation Models (DGVMs) represent relationships between controlling factors and burned area. We developed a pattern-oriented model evaluation approach using the random forest (RF) algorithm to identify emergent relationships between climate, vegetation, and socioeconomic predictor variables and burned area. We applied this approach to monthly burned area time series for the period 2005–2011 from satellite observations and from DGVMs from the Fire Model Inter-comparison Project (FireMIP) that were run using a common protocol and forcing datasets. The satellite-derived relationships indicate strong sensitivity to climate variables (e.g. maximum temperature, number of wet days), vegetation properties (e.g. vegetation type, previous-season plant productivity and leaf area, woody litter), and to socioeconomic variables (e.g. human population density). DGVMs broadly reproduce the relationships to climate variables and some models to population density. Interestingly, satellite-derived responses show a strong increase of burned area with previous-season leaf area index and plant productivity in most fire-prone ecosystems which was largely underestimated by most DGVMs. Hence our pattern-oriented model evaluation approach allowed to diagnose that current fire-enabled DGVMs represent some controls on fire to a large extent but processes linking vegetation productivity and fire occurrence need to be improved to accurately simulate the role of fire under global environmental change.

An assessment of natural methane fluxes simulated by the CLASS-CTEM model

Natural methane emissions from wetlands and fire, and soil uptake of methane, simulated using the Canadian Land Surface Scheme and Canadian Terrestrial Ecosystem (CLASS-CTEM) modelling framework, over the historical 1850–2008 period, are assessed by using a one-box model of atmospheric methane burden. This one-box model also requires anthropogenic emissions and the methane sink in the atmosphere to simulate the historical evolution of global methane burden. For this purpose, global anthropogenic methane emissions for the period 1850–2008 were reconstructed based on the harmonized representative concentration pathway (RCP) and Emission Database for Global Atmospheric Research (EDGAR) data sets. The methane sink in the atmosphere is represented using biascorrected methane lifetimes from the Canadian Middle Atmosphere Model (CMAM). The resulting evolution of atmospheric methane concentration over the historical period compares reasonably well with observation-based estimates (correlation = 0.99, root mean square error= 35 ppb). The modelled natural emissions are also assessed using an inverse procedure where the methane lifetimes required to reproduce the observed year-to-year increase in atmospheric methane burden are calculated based upon the specified global anthropogenic and modelled natural emissions that we have used here. These calculated methane lifetimes over the historical period fall within the uncertainty range of observation-based estimates. The present-day (2000– 2008) values of modelled methane emissions from wetlands (169 Tg CH4 yr−1) and fire (27 Tg CH4 yr−1), methane uptake by soil (29 Tg CH4 yr−1), and the budget terms associated with overall anthropogenic and natural emissions are consistent with estimates reported in a recent global methane budget that is based on top-down approaches constrained by observed atmospheric methane burden. The modelled wetland emissions increase over the historical period in response to both increases in precipitation and in atmospheric CO2 concentration. This increase in wetland emissions over the historical period yields evolution of the atmospheric methane concentration that compares better with observation-based values than the case when wetland emissions are held constant over the historical period.