. New burned area datasets and top-down constraints from atmospheric concentration measurements of pyrogenic gases have decreased the large uncertainty in fire emissions estimates. However, significant gaps remain in our understanding of the contribution of deforestation, savanna, forest, agricultural waste, and peat fires to total global fire emissions. Here we used a revised version of the Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model and improved satellite-derived estimates of area burned, fire activity, and plant productivity to calculate fire emissions for the 1997–2009 period on a 0.5° spatial resolution with a monthly time step. For November 2000 onwards, estimates were based on burned area, active fire detections, and plant productivity from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor. For the partitioning we focused on the MODIS era. We used maps of burned area derived from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and Along-Track Scanning Radiometer (ATSR) active fire data prior to MODIS (1997–2000) and estimates of plant productivity derived from Advanced Very High Resolution Radiometer (AVHRR) observations during the same period. Average global fire carbon emissions according to this version 3 of the Global Fire Emissions Database (GFED3) were 2.0 Pg C year−1 with significant interannual variability during 1997–2001 (2.8 Pg C year−1 in 1998 and 1.6 Pg C year−1 in 2001). Globally, emissions during 2002–2007 were relatively constant (around 2.1 Pg C year−1) before declining in 2008 (1.7 Pg C year−1) and 2009 (1.5 Pg C year−1) partly due to lower deforestation fire emissions in South America and tropical Asia. On a regional basis, emissions were highly variable during 2002–2007 (e.g., boreal Asia, South America, and Indonesia), but these regional differences canceled out at a global level. During the MODIS era (2001–2009), most carbon emissions were from fires in grasslands and savannas (44%) with smaller contributions from tropical deforestation and degradation fires (20%), woodland fires (mostly confined to the tropics, 16%), forest fires (mostly in the extratropics, 15%), agricultural waste burning (3%), and tropical peat fires (3%). The contribution from agricultural waste fires was likely a lower bound because our approach for measuring burned area could not detect all of these relatively small fires. Total carbon emissions were on average 13% lower than in our previous (GFED2) work. For reduced trace gases such as CO and CH4, deforestation, degradation, and peat fires were more important contributors because of higher emissions of reduced trace gases per unit carbon combusted compared to savanna fires. Carbon emissions from tropical deforestation, degradation, and peatland fires were on average 0.5 Pg C year−1. The carbon emissions from these fires may not be balanced by regrowth following fire. Our results provide the first global assessment of the contribution of different sources to total global fire emissions for the past decade, and supply the community with an improved 13-year fire emissions time series.

/pdf/global-fire-emissions-and-the-contribution-of-deforestation-r24zw2ke8k.pdf

Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997-2009)

Developing countries are required to produce robust estimates of forest carbon stocks for successful implementation of climate change mitigation policies related to reducing emissions from deforestation and degradation (REDD). Here we present a “benchmark” map of biomass carbon stocks over 2.5 billion ha of forests on three continents, encompassing all tropical forests, for the early 2000s, which will be invaluable for REDD assessments at both project and national scales. We mapped the total carbon stock in live biomass (above- and belowground), using a combination of data from 4,079 in situ inventory plots and satellite light detection and ranging (Lidar) samples of forest structure to estimate carbon storage, plus optical and microwave imagery (1-km resolution) to extrapolate over the landscape. The total biomass carbon stock of forests in the study region is estimated to be 247 Gt C, with 193 Gt C stored aboveground and 54 Gt C stored belowground in roots. Forests in Latin America, sub-Saharan Africa, and Southeast Asia accounted for 49%, 25%, and 26% of the total stock, respectively. By analyzing the errors propagated through the estimation process, uncertainty at the pixel level (100 ha) ranged from ±6% to ±53%, but was constrained at the typical project (10,000 ha) and national (>1,000,000 ha) scales at ca. ±5% and ca. ±1%, respectively. The benchmark map illustrates regional patterns and provides methodologically comparable estimates of carbon stocks for 75 developing countries where previous assessments were either poor or incomplete.

/pdf/benchmark-map-of-forest-carbon-stocks-in-tropical-regions-38530jv6g9.pdf

Benchmark map of forest carbon stocks in tropical regions across three continents.

Reducing carbon emissions from deforestation and degradation in developing countries is of central importance in efforts to combat climate change. Key scientific challenges must be addressed to prevent any policy roadblocks. Foremost among the challenges is quantifying nations' carbon emissions from deforestation and forest degradation, which requires information on forest clearing and carbon storage. Here we review a range of methods available to estimate national-level forest carbon stocks in developing countries. While there are no practical methods to directly measure all forest carbon stocks across a country, both ground-based and remote-sensing measurements of forest attributes can be converted into estimates of national carbon stocks using allometric relationships. Here we synthesize, map and update prominent forest biomass carbon databases to create the first complete set of national-level forest carbon stock estimates. These forest carbon estimates expand on the default values recommended by the Intergovernmental Panel on Climate Change's National Greenhouse Gas Inventory Guidelines and provide a range of globally consistent estimates.

https://iopscience.iop.org/article/10.1088/1748-9326/2/4/045023/pdf

Monitoring and estimating tropical forest carbon stocks: making REDD a reality

/pdf/remote-sensing-of-the-environment-4yfxjaaswe.pdf

Remote sensing of the environment

Agricultural expansion and climate variability have become important agents of disturbance in the Amazon basin. Recent studies have demonstrated considerable resilience of Amazonian forests to moderate annual drought, but they also show that interactions between deforestation, fire and drought potentially lead to losses of carbon storage and changes in regional precipitation patterns and river discharge. Although the basin-wide impacts of land use and drought may not yet surpass the magnitude of natural variability of hydrologic and biogeochemical cycles, there are some signs of a transition to a disturbance-dominated regime. These signs include changing energy and water cycles in the southern and eastern portions of the Amazon basin.

/pdf/the-amazon-basin-in-transition-3au6enmu0k.pdf

The Amazon basin in transition

Influence of Heating on Nutritive Value of Alfalfa-Bromegrass Hay for Sheep

/pdf/erratum-to-simulating-cold-season-snowpack-impacts-of-snow-3a8j01j5he.pdf

Erratum to: Simulating cold season snowpack: Impacts of snow albedo and multi-layer snow physics

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2017JG003966

Mechanistic Processes Controlling Persistent Changes of Forest Canopy Structure After 2005 Amazon Drought

The structure of forests, in terms of mass and the three-dimensional arrangement of individual trees, is a direct indicator of how much carbon is stored in the ecosystem, which in turn, has a profound effect on how the ecosystem functions and cycles carbon, water, and nutrients ( Shugart et al., 2010 ). There is an increased need to understand local to global storage and dynamics of carbon in terrestrial vegetation, as carbon storage is a prerequisite to understanding the coupling of the biosphere to other components of Earth systems including the climate ( Luyssaert et al., 2008 ). By focusing on live carbon pool, the above ground biomass (AGB) can be estimated from algorithmic modeling using remote sensing data. Low-frequency Radar backscatter, among others, has unique advantages due to its sensitivity to forest AGB and potentially at fine spatial and temporal resolutions ( Le Toan et al., 2011 ; Mitchard et al., 2009 ).

Y. Yu

Papers

Influence of Heating on Nutritive Value of Alfalfa-Bromegrass Hay for Sheep

Erratum to: Simulating cold season snowpack: Impacts of snow albedo and multi-layer snow physics

Mechanistic Processes Controlling Persistent Changes of Forest Canopy Structure After 2005 Amazon Drought

Evaluation of NISAR Biomass Algorithm in Temperate and Boreal Forests