Parameter settings for the three scenarios that almost meet normative targets.

<p>The minimum and maximum of the parameter range is shown, with the parameter value that would reproduce current trends (2000–2010) indicated in orange.</p

Global cropland area for simulation runs that meet normative targets.

<p>Global cropland area for simulations that meet the food-supply target (blue lines) and which are also below the planetary boundary for cropland area (yellow lines, planetary boundary for cropland illustrated by the black dashed line). The red line indicates the run that is closest to meeting all three targets, including the bioenergy-mitigation target (Food-Bioenergy-high-Natural-Vegetation). The grey shaded area indicates the range spanned by all runs. The acronyms shown are discussed in section 3.2.</p

Overview of PLUM parameters and uncertainty explored.

<p>Columns 3–5: Parameter setting that reproduces the average current trend, between 2000–2010, and the minimum and maximum settings of the uncertainty range for the parameter of interest. Column 6–8: Implications of current trend values (mean), minimum (min) and maximum values (max) for output in the year 2050 with other parameters held at mean values.</p

Global cropland area changes over time for the three focal scenarios.

<p>(A) Per country cropland area as a percentage of suitable land (moderate to very high suitability from the Global Agro-ecological Zone Data Portal; (FAO/IIASA, 2011). Changes in cropland area in 2050 compared to 2000 (% of suitable land) for (B) FB-highNV, (C) FC-lowNV and (D) FC-highNV. Countries displayed in grey are excluded from the analysis due to missing input data.</p

Global average yields for simulation runs that meet normative targets.

<p>Global average yields for simulations that meet the food-supply target (blue lines), and which are also below the planetary boundary for cropland area (yellow lines). The red line indicates the run that is closest to meeting all three targets, including the bioenergy-mitigation target (Food-Bioenergy-high-Natural-Vegetation). The grey shaded area indicates the range spanned by all simulations. The acronyms shown are discussed in section 3.2.</p

Estimating carbon emissions from African wildfires

We developed a technique for studying seasonal and interannual variation in pyrogenic carbon emissions from Africa using a modelling approach that scales burned area estimates from L3JRC, a map recently generated from remote sensing of burn scars instead of active fires. Carbon fluxes were calculated by the novel fire model SPITFIRE embedded within the dynamic vegetation model framework LPJ-GUESS, using daily climate input. For the time period from 2001 to 2005 an average area of 195.5±24×104 km2 was burned annually, releasing an average of 723±70 Tg C to the atmosphere; these estimates for the biomass burned are within the range of previously published estimates. Despite the fact that the majority of wildfires are ignited by humans, strong relationships between climatic conditions (particularly precipitation), net primary productivity and overall biomass burnt emerged. Our investigation of the relationships between burnt area and carbon emissions and their potential drivers available litter and precipitation revealed uni-modal responses to annual precipitation, with a maximum around 1000 mm for burned area and emissions, or 1200 mm for litter availability. Similar response patterns identified in savannahs worldwide point to precipitation as a chief determinant for short-term variation in fire regime. A considerable variability that cannot be explained by fire-precipitation relationships alone indicates the existence of additional factors that must be taken into account

An outlook on the Sub-Saharan Africa carbon balance

This study gives an outlook on the carbon balance of Sub-Saharan Africa (SSA) by presenting a summary of currently available results from the project CarboAfrica (namely net ecosystem productivity and emissions from fires, deforestation and forest degradation, by field and model estimates) supplemented by bibliographic data and compared with a new synthesis of the data from national communications to UNFCCC. According to these preliminary estimates the biogenic carbon balance of SSA varies from 0.16 Pg C y[Superscript: −1] to a much higher sink of 1.00 Pg C y[Superscript: −1] (depending on the source data). Models estimates would give an unrealistic sink of 3.23 Pg C y[Superscript: −1], confirming their current inadequacy when applied to Africa. The carbon uptake by forests and savannas (0.34 and 1.89 Pg C y[Superscript: −1], respectively,) are the main contributors to the resulting sink. Fires (0.72 Pg C y[Superscript: −1]) and deforestation (0.25 Pg C y[Superscript: −1]) are the main contributors to the SSA carbon emissions, while the agricultural sector and forest degradation contributes only with 0.12 and 0.08 Pg C y[Superscript: −1], respectively. Savannas play a major role in shaping the SSA carbon balance, due to their large extension, their fire regime, and their strong interannual NEP variability, but they are also a major uncertainty in the overall budget. Even if fossil fuel emissions from SSA are relative low, they can be crucial in defining the sign of the overall SSA carbon balance by reducing the natural sink potential, especially in the future. This paper shows that Africa plays a key role in the global carbon cycle system and probably could have a potential for carbon sequestration higher than expected, even if still highly uncertain. Further investigations are needed, particularly to better address the role of savannas and tropical forests and to improve biogeochemical models. The CarboAfrica network of carbon measurements could provide future unique data sets for better estimating the African carbon balance

The Sub-Saharan Africa carbon balance, an overview

This study presents a summary overview of the carbon balance of Sub-Saharan Africa (SSA) by synthesizing the available data from national communications to UNFCCC and first results from the project CarboAfrica (net ecosystem productivity and emis- sions from fires, deforestation and forest degradation, by field and model estimates). 5 According to these preliminary estimates the overall carbon balance of SSA varies from 0.43 Pg C y − 1 (using in situ measurements for savanna NEP) to a much higher sink of 2.53 Pg C y − 1 (using model estimates for savanna NEP). UNFCCC estimates lead to a moderate carbon sink of 0.58Pg C y − 1 . Excluding anthropogenic disturbance and intrinsic episodic events, the carbon uptake by forests (0.98 Pg C y − 1 ) and savannas 10 (from 1.38 to 3.48 Pg C y − 1 , depending on the used methodology) are the main com- ponents of the SSA sink e ff ect. Fires (0.72 Pg C y − 1 ), deforestation (0.25 Pg C y − 1 ) and forest degradation (0.77 Pg C y − 1 ) are the main contributors to the SSA carbon emis- sions, while the agricultural sector contributes only with 0.12 Pg C y − 1 . Notably, the impact of forest degradation is higher than that caused by deforestation, and the SSA 15 forest net carbon balance is close to equilibrium. Savannas play a major role in shap- ing the SSA carbon balance, due to their large areal extent, their fire regime, and their strong interannual NEP variability, but they are also a major uncertainty in the overall budget. This paper shows that Africa plays a key role in the global carbon cycle sys- tem and probably could have a potential for carbon sequestration higher than expected, 20 even if still highly uncertain. Further investigations are needed, particularly to better address the role of savannas and tropical forests. The current CarboAfrica network of carbon measurements could provide future unique data sets for better estimating the African carbon balance