Africa and the global carbon cycle

Environmentally Just Futures: A Collection of Community-Driven African Environmental Education and Improvement Initiatives

Advocating for healthy environments is a matter of justice. Changes in environments have tremendous impacts on the health of communities, and oftentimes, individuals are unable to safeguard themselves through individual actions alone. Efforts frequently require collective action and are often most effective when led by the communities most impacted. In this spirit, we launched “Vibrations”, an African environment photo essay contest. Through funding and publicity, we aimed to support community-led environmental improvement and education initiatives presently taking place on the continent. We received nearly two dozen submissions and selected eight winners. The winners come from five countries (Ghana, Kenya, Mozambique, Nigeria, and South Africa) and have taken on a range of projects aimed at improving environments across a variety of African regions. Projects included efforts to combat pollution, create environmentally conscious school curricula, utilize clean energy sources, and spread awareness about environmental justice concerns in local communities. It is our hope that this report highlights these transformative community-driven efforts, promotes continued conversations on environmental justice in Africa, and encourages meaningful action via policy changes and collaborations throughout the African continent and beyond.

Characterizing the Response of Vegetation Cover to Water Limitation in Africa Using Geostationary Satellites

Hydrological interactions between vegetation, soil, and topography are complex, and heterogeneous in semi-arid landscapes. This along with data scarcity poses challenges for large-scale modeling of vegetation-water interactions. Here, we exploit metrics derived from daily Meteosat data over Africa at ca. 5 km spatial resolution for ecohydrological analysis. Their spatial patterns are based on Fractional Vegetation Cover (FVC) time series and emphasize limiting conditions of the seasonal wet to dry transition: the minimum and maximum FVC of temporal record, the FVC decay rate and the FVC integral over the decay period. We investigate the relevance of these metrics for large scale ecohydrological studies by assessing their co-variation with soil moisture, and with topographic, soil, and vegetation factors. Consistent with our initial hypothesis, FVC minimum and maximum increase with soil moisture, while the FVC integral and decay rate peak at intermediate soil moisture. We find evidence for the relevance of topographic moisture variations in arid regions, which, counter-intuitively, is detectable in the maximum but not in the minimum FVC. We find no clear evidence for wide-spread occurrence of the "inverse texture effect" on FVC. The FVC integral over the decay period correlates with independent data sets of plant water storage capacity or rooting depth while correlations increase with aridity. In arid regions, the FVC decay rate decreases with canopy height and tree cover fraction as expected for ecosystems with a more conservative water-use strategy. Thus, our observation-based products have large potential for better understanding complex vegetation-water interactions from regional to continental scales.

Machine Learning Methods and Synthetic Data Generation to Predict Large Wildfires

Wildfires are becoming more frequent in different parts of the globe, and the ability to predict when and where they will occur is a complex process. Identifying wildfire events with high probability of becoming a large wildfire is an important task for supporting initial attack planning. Different methods, including those that are physics-based, statistical, and based on machine learning (ML) are used in wildfire analysis. Among the whole, those based on machine learning are relatively novel. In addition, because the number of wildfires is much greater than the number of large wildfires, the dataset to be used in a ML model is imbalanced, resulting in overfitting or underfitting the results. In this manuscript, we propose to generate synthetic data from variables of interest together with ML models for the prediction of large wildfires. Specifically, five synthetic data generation methods have been evaluated, and their results are analyzed with four ML methods. The results yield an improvement in the prediction power when synthetic data are used, offering a new method to be taken into account in Decision Support Systems (DSS) when managing wildfires.

High photosynthetic capacity of Sahelian C3 and C4 plants

The semi-arid ecosystems of the African Sahel play an important role in the global carbon cycle and are among the most sensitive ecosystems to future environmental pressures. Still, basic data of photosynthetic characteristics of Sahelian vegetation are very limited, preventing us to properly understand these ecosystems and to project their response to future global changes. Here, we aim to study and quantify key leaf traits, including photosynthetic parameters and leaf nutrients (N_leaf and P_leaf), of common C₃ and C₄ Sahelian plants (trees, lianas, and grasses) at the Dahra field site (Senegal). Dahra is a reference site for grazed semi-arid Sahelian savannah ecosystems in carbon cycle studies. Within the studied species, we found that photosynthetic parameters varied considerably between functional types. We also found significant relationships between and within photosynthetic parameters and leaf traits which mostly differed in their slopes from C₃ to C₄ plants. In agreement with the leaf economic spectrum, strong relationships (R² = 0.71) were found between SLA and N_leaf whereby C₃ and C₄ plants showed very similar relationships. By comparing our data to a global dataset of plant traits, we show that measured Sahelian plants exhibit higher photosynthetic capacity (A_sat) compared to the non-Sahelian vegetation, with values that are on average a fourfold of the global average. Moreover, Sahelian C₃ plants showed photosynthetic nutrient use efficiencies that were on average roughly twice as high as global averages. We interpreted these results as the potential adaptation of Sahelian plants to short growing season lengths via an efficient nutrient allocation to optimize photosynthesis during this period. Our study provides robust estimates of key functional traits, but also traits relationships that will help to calibrate and validate vegetation models over this data-poor region.

Woody-biomass projections and drivers of change in sub-Saharan Africa

Africa's ecosystems have an important role in global carbon dynamics, yet consensus is lacking regarding the amount of carbon stored in woody vegetation and the potential impacts to carbon storage in response to changes in climate, land use, and other Anthropocene risks. Here, we explore the socio-environmental conditions that shaped the contemporary distribution of woody vegetation across sub-Saharan Africa and evaluate ecosystem response to multiple scenarios of climate change, anthropogenic pressures, and fire disturbance. Our projections suggest climate change will have a small but negative effect on above ground woody biomass at the continental scale, and the compounding effects of population growth, increasing human pressures, and socio-climatic driven changes in fire behavior further exacerbate climate-driven trends. Relatively modest continental-scale trends obscure much larger regional perturbations, with climatic and anthropogenic factors leading to increased carbon storage potential in East Africa, offset by large deficits in West, Central, and Southern Africa.

Airborne Lidar Sampling Pivotal for Accurate Regional AGB Predictions from Multispectral Images in Forest-Savanna Landscapes

Precise accounting of carbon stocks and fluxes in tropical vegetation using remote sensing approaches remains a challenging exercise, as both signal saturation and ground sampling limitations contribute to inaccurate extrapolations. Airborne LiDAR Scanning (ALS) data can be used as an intermediate level to radically increase sampling and enhance model calibration. Here we tested the potential of using ALS data for upscaling vegetation aboveground biomass (AGB) from field plots to a forest-savanna transitional landscape in the Guineo–Congolian region in Cameroon, using either a design-based approach or a model-based approach leveraging multispectral satellite imagery. Two sets of reference data were used: (1) AGB values collected from 62 0.16-ha plots distributed both in forests and savannas; and (2) an AGB map generated form ALS data. In the model-based approach, we trained Random Forest models using predictors from recent sensors of varying spectral and spatial resolutions (Spot 6/7, Landsat 8, and Sentinel 2), along with biophysical predictors derived after pre-processing into the Overland processing chain, following a forward variable selection procedure with a spatial 4-folds cross validation. The models calibrated with field plots lead to a systematic overestimation in AGB density estimates and a root mean squared prediction error (RMSPE) of up to 65 Mg.ha−1 (90%), whereas calibration with ALS lead to low bias and a drop of ~30% in RMSPE (down to 43 Mg.ha−1, 58%) with little effect of the satellite sensor used. Decomposing bias along the AGB density range, we show that multispectral images can (in some specific cases) be used for unbiased prediction at landscape scale on the basis of ALS-calibrated statistical models. However, our results also confirm that, whatever the spectral indices used and attention paid to sensor quality and pre-processing, the signal is not sufficient to warrant accurate pixelwise predictions, because of large relative RMSPE, especially above (200–250 t/ha). The design-based approach, for which average AGB density values were attributed to mapped land cover classes, proved to be a simple and reliable alternative (for landscape to region level estimations), when trained with dense ALS samples.

Carbon dynamics, net primary productivity and human-appropriated net primary productivity across a forest-cocoa farm landscape in West Africa

Terrestrial net primary productivity (NPP) is an important metric of ecosystem functioning; however, there are little empirical data on the NPP of human-modified ecosystems, particularly smallholder, perennial crops like cocoa (Theobroma cacao), which are extensive across the tropics. Human-appropriated NPP (HANPP) is a measure of the proportion of a natural system's NPP that has either been reduced through land-use change or harvested directly and, previously, has been calculated to estimate the scale of the human impact on the biosphere. Additionally, human modification can create shifts in NPP allocation and decomposition, with concomitant impacts on the carbon cycle. This study presents the results of 3 years of intensive monitoring of forest and smallholder cocoa farms across disturbance, management intensity, distance from forest and farm age gradients. We measured among the highest reported NPP values in tropical forest, 17.57 ± 2.1 and 17.7 ± 1.6 Mg C ha^-1  year^-1 for intact and logged forest, respectively; however, the average NPP of cocoa farms was still higher, 18.8 ± 2.5 Mg C ha^-1  year^-1 , which we found was driven by cocoa pod production. We found a dramatic shift in litterfall residence times, where cocoa leaves decomposed more slowly than forest leaves and shade tree litterfall decomposed considerably faster, indicating significant changes in rates of nutrient cycling. The average HANPP value for all cocoa farms was 2.1 ± 1.1 Mg C ha^-1  year^-1 ; however, depending on the density of shade trees, it ranged from -4.6 to 5.2 Mg C ha^-1  year^-1 . Therefore, rather than being related to cocoa yield, HANPP was reduced by maintaining higher shade levels. Across our monitored farms, 18.9% of farm NPP was harvested (i.e., whole cocoa pods) and only 1.1% (i.e., cocoa beans) was removed from the system, suggesting that the scale of HANPP in smallholder cocoa agroforestry systems is relatively small.

The variation of vegetation productivity and its relationship to temperature and precipitation based on the GLASS-LAI of different African ecosystems from 1982 to 2013

In recent years, many studies have focused on the changes of partial or single African ecosystems and the drivers of those changes. However, focusing only on partial or single ecosystems has limited the understanding of the relationships between the vegetation and climate changes in all of the African ecosystems. In this study, the temporal trends of the satellite-derived annual mean leaf area index (GLASS-LAI) were analyzed, and the inter-annual relationships were developed between the annual mean LAI and the climate variables (precipitation and temperature) for the time period ranging from 1982 to 2013. Additionally, this study applied seasonal curves and step-wise multiple regression methods to investigate the relationships between intra-annual LAI and climate changes. It was found that the GLASS-LAI over half of Africa had shown general significant greening or browning trends during the period from 1982 to 2013. From the results of inter-annual analysis, with mean annual precipitation lower than 600 mm, the greening of the savannas and grasslands in the Sahel was found to highly correspond with the increased precipitation. In contrast, the evergreen broadleaf forests in the Gulf of Guinea and Congo Basin showed strongly positive responses to the annual temperature when the mean annual temperature was below 25 °C. In regard to the intra-annual responses, the precipitation with 1-month lags was found to be helpful for the vegetation growth, with the exception of the evergreen broadleaf. The results of this research study indicated that the different land-covers in Africa had displayed clear differences in their annual trends during the examined 32-year period and had responded differently to the inter- and intra-annual climate drivers. This difference was evident by the characteristics of the vegetation covers and the geographic distributions. Therefore, further examinations of these differences can potentially improve the understanding of the land surface-atmosphere interactions among the different African ecosystems.

Refining Species Traits in a Dynamic Vegetation Model to Project the Impacts of Climate Change on Tropical Trees in Central Africa

African tropical ecosystems and the services they provide to human society suffer from an increasing combined pressure of land use and climate change. How individual tropical tree species respond to climate change remains relatively unknown. In this study, we refined the species characterization in the CARAIB (CARbon Assimilation In the Biosphere) dynamic vegetation model by replacing plant functional type morpho-physiological traits by species-specific traits. We focus on 12 tropical tree species selected for their importance in both the plant community and human society. We used CARAIB to simulate the current species net primary productivity (NPP), biomass and potential distribution and their changes in the future. Our results indicate that the use of species-specific traits does not necessarily result in an increase of predicted current NPPs. The model projections for the end of the century highlight the large uncertainties in the future of African tropical species. Projected changes in species distribution vary greatly with the general circulation model (GCM) and, to a lesser extent, with the concentration pathway. The question about long-term plant response to increasing CO2 concentrations also leads to contrasting results. In absence of fertilization effect, species are exposed to climate change and might lose 25% of their current distribution under RCP8.5 (12.5% under RCP4.5), considering all the species and climatic scenarios. The vegetation model projects a mean biomass loss of −21.2% under RCP4.5 and −34.5% under RCP8.5. Potential range expansions, unpredictable due to migration limitations, are too limited for offsetting range contraction. By contrast, if the long-term species response to increasing [CO2] is positive, the range reduction is limited to 5%. However, despite a mean biomass increase of 12.2%, a positive CO2 feedback might not prevent tree dieback. Our analysis confirms that species will respond differently to new climatic and atmospheric conditions, which may induce new competition dynamics in the ecosystem and affect ecosystem services.

Fire Activity and Fuel Consumption Dynamics in Sub-Saharan Africa

African landscape fires are widespread, recurrent and temporally dynamic. They burn large areas of the continent, modifying land surface properties and significantly affect the atmosphere. Satellite Earth Observation (EO) data play a pivotal role in capturing the spatial and temporal variability of African biomass burning, and provide the key data required to develop fire emissions inventories. Active fire observations of fire radiative power (FRP, MW) have been shown to be linearly related to rates of biomass combustion (kg s−1). The Meteosat FRP-PIXEL product, delivered in near real-time by the EUMETSAT Land Surface Analysis Satellite Applications Facility (LSA SAF), maps FRP at 3 km resolution and 15-min intervals and these data extend back to 2004. Here we use this information to assess spatio-temporal variations in fire activity across sub-Saharan Africa, and identify an overall trend of decreasing annual fire activity and fuel consumption, agreeing with the widely-used Global Fire Emissions Database (GFEDv4) based on burned area measures. We provide the first comprehensive assessment of relationships between per-fire FRE-derived fuel consumption (Tg dry matter, DM) and temporally integrated Moderate Resolution Imaging Spectroradiometer (MODIS) net photosynthesis (PSN) (Tg, which can be converted into pre-fire fuel load estimates). We find very strong linear relationships over southern hemisphere Africa (mean r = 0.96) that are partly biome dependent, though the FRE-derived fuel consumptions are far lower than those derived from the accumulated PSN, with mean fuel consumptions per unit area calculated as 0.14 kg DM m−2. In the northern hemisphere, FRE-derived fuel consumption is also far lower and characterized by a weaker linear relationship (mean r = 0.76). Differences in the parameterization of the biome look up table (BLUT) used by the MOD17 product over Northern Africa may be responsible but further research is required to reconcile these differences. The strong relationship between fire FRE and pre-fire fuel load in southern hemisphere Africa is encouraging and highlights the value of geostationary FRP retrievals in providing a metric that relates very well to fuel consumption and fire emission variations. The fact that the estimated fuel consumed is only a small fraction of the fuel available suggests underestimation of FRE by Spinning Enhanced Visible and Infrared Imager (SEVIRI) and/or that the FRE-to-fuel consumption conversion factor of 0.37 MJ kg−1 needs to be adjusted for application to SEVIRI. Future geostationary imaging sensors, such as on the forthcoming Meteosat Third Generation (MTG), will reduce the impact of this underestimation through its ability to detect even smaller and shorter-lived fires than can the current second generation Meteosat.

Estimating terrestrial gross primary productivity in water limited ecosystems across Africa using the Southampton Carbon Flux (SCARF) model

The amount of carbon uptake by vegetation is an important component to understand the functioning of ecosystem processes and their response/feedback to climate. Recently, a new diagnostic model called the Southampton Carbon Flux (SCARF) Model driven by remote sensing data was developed to predict terrestrial gross primary productivity (GPP) and successfully applied in temperate regions. The model is based on the concept of quantum yield of plants and improves on the previous diagnostic models by (i) using the fraction of photosynthetic active radiation absorbed by the photosynthetic pigment (FAPAR_ps) and (ii) using direct quantum yield by classifying the vegetation into C₃ or C₄ classes. In this paper, we calibrated and applied the model to evaluate GPP across various ecosystems in Africa. The performance of the model was evaluated using data from seven eddy covariance flux tower sites. Overall, the modelled GPP values showed good correlation (R>0.59, p<0.0001) with estimated flux tower GPP at most sites (except at a tropical rainforest site, R=0.38, p=0.02) in terms of their seasonality and absolute values. Mean daily GPP across the investigated period varied significantly across sites depending on the vegetation types from a minimum of 0.44gCm^-2day^-1 at the semi-arid and sub-humid savanna grassland sites to a maximum of 9.86gCm^-2day^-1 at the woodland and tropical rain forest sites. Generally, strong correlation is observed in savanna woodlands and grasslands where vegetation follows a prescribed seasonal cycle as determined by changes in canopy chlorophyll content and leaf area index. Finally, the mean annual GPP value for Africa predicted by the model was 35.25PgCyr^-1. The good performance of the SCARF model in water-limited ecosystems across Africa extends its potential for global application.

Satellite passive microwaves reveal recent climate-induced carbon losses in African drylands

The African continent is facing one of the driest periods in the past three decades as well as continued deforestation. These disturbances threaten vegetation carbon (C) stocks and highlight the need for improved capabilities of monitoring large-scale aboveground carbon stock dynamics. Here we use a satellite dataset based on vegetation optical depth derived from low-frequency passive microwaves (L-VOD) to quantify annual aboveground biomass-carbon changes in sub-Saharan Africa between 2010 and 2016. L-VOD is shown not to saturate over densely vegetated areas. The overall net change in drylands (53% of the land area) was -0.05 petagrams of C per year (Pg C yr^-1) associated with drying trends, and a net change of -0.02 Pg C yr^-1 was observed in humid areas. These trends reflect a high inter-annual variability with a very dry year in 2015 (net change, -0.69 Pg C) with about half of the gross losses occurring in drylands. This study demonstrates, first, the applicability of L-VOD to monitor the dynamics of carbon loss and gain due to weather variations, and second, the importance of the highly dynamic and vulnerable carbon pool of dryland savannahs for the global carbon balance, despite the relatively low carbon stock per unit area.

Cambial pinning relates wood anatomy to ecophysiology in the African tropical tree Maesopsis eminii

A better understanding and prediction of the impact of changing climate on tree stem growth could greatly benefit from the combination of anatomical and ecophysiological knowledge, yet the majority of studies focus on one research field only. We propose an approach that combines the method of pinning (cambial wounding) to timestamp anatomical X-ray computed microtomography images with continuous measurements of sap flow and stem diameter variations. By pinning the cambium of well-watered and drought-treated young African tropical trees of the species Maesopsis eminii Engl. we could quantify wood formation during a specific period of time and relate it to tree physiology and prevailing microclimate. Integrating continuous plant measurements and high-frequency pinning proved very useful to visualize and quantify the effects on stem growth of drought in M. eminii. Wood formation completely stopped during drought, and was associated with a strong shrinkage in stem diameter. Next, an unexpected increase in stem diameter was observed during drought, probably caused by root pressure, but not accompanied by wood formation. Our proposed approach of combining continuous plant measurements with cambial pinning is very promising to relate ecophysiology to stem anatomy and to understand the mechanisms underlying tree stem growth and bridge the gaps between the two research fields.

Comparison between remote sensing and a dynamic vegetation model for estimating terrestrial primary production of Africa

BACKGROUND

Africa is an important part of the global carbon cycle. It is also a continent facing potential problems due to increasing resource demand in combination with climate change-induced changes in resource supply. Quantifying the pools and fluxes constituting the terrestrial African carbon cycle is a challenge, because of uncertainties in meteorological driver data, lack of validation data, and potentially uncertain representation of important processes in major ecosystems. In this paper, terrestrial primary production estimates derived from remote sensing and a dynamic vegetation model are compared and quantified for major African land cover types.

RESULTS

Continental gross primary production estimates derived from remote sensing were higher than corresponding estimates derived from a dynamic vegetation model. However, estimates of continental net primary production from remote sensing were lower than corresponding estimates from the dynamic vegetation model. Variation was found among land cover classes, and the largest differences in gross primary production were found in the evergreen broadleaf forest. Average carbon use efficiency (NPP/GPP) was 0.58 for the vegetation model and 0.46 for the remote sensing method. Validation versus in situ data of aboveground net primary production revealed significant positive relationships for both methods. A combination of the remote sensing method with the dynamic vegetation model did not strongly affect this relationship.

CONCLUSION

Observed significant differences in estimated vegetation productivity may have several causes, including model design and temperature sensitivity. Differences in carbon use efficiency reflect underlying model assumptions. Integrating the realistic process representation of dynamic vegetation models with the high resolution observational strength of remote sensing may support realistic estimation of components of the carbon cycle and enhance resource monitoring, providing suitable validation data is available.

Biomass Increases Go under Cover: Woody Vegetation Dynamics in South African Rangelands

Woody biomass dynamics are an expression of ecosystem function, yet biomass estimates do not provide information on the spatial distribution of woody vegetation within the vertical vegetation subcanopy. We demonstrate the ability of airborne light detection and ranging (LiDAR) to measure aboveground biomass and subcanopy structure, as an explanatory tool to unravel vegetation dynamics in structurally heterogeneous landscapes. We sampled three communal rangelands in Bushbuckridge, South Africa, utilised by rural communities for fuelwood harvesting. Woody biomass estimates ranged between 9 Mg ha(-1) on gabbro geology sites to 27 Mg ha(-1) on granitic geology sites. Despite predictions of woodland depletion due to unsustainable fuelwood extraction in previous studies, biomass in all the communal rangelands increased between 2008 and 2012. Annual biomass productivity estimates (10-14% p.a.) were higher than previous estimates of 4% and likely a significant contributor to the previous underestimations of modelled biomass supply. We show that biomass increases are attributable to growth of vegetation <5 m in height, and that, in the high wood extraction rangeland, 79% of the changes in the vertical vegetation subcanopy are gains in the 1-3 m height class. The higher the wood extraction pressure on the rangelands, the greater the biomass increases in the low height classes within the subcanopy, likely a strong resprouting response to intensive harvesting. Yet, fuelwood shortages are still occurring, as evidenced by the losses in the tall tree height class in the high extraction rangeland. Loss of large trees and gain in subcanopy shrubs could result in a structurally simple landscape with reduced functional capacity. This research demonstrates that intensive harvesting can, paradoxically, increase biomass and this has implications for the sustainability of ecosystem service provision. The structural implications of biomass increases in communal rangelands could be misinterpreted as woodland recovery in the absence of three-dimensional, subcanopy information.

Perturbations in the carbon budget of the tropics

The carbon budget of the tropics has been perturbed as a result of human influences. Here, we attempt to construct a 'bottom-up' analysis of the biological components of the budget as they are affected by human activities. There are major uncertainties in the extent and carbon content of different vegetation types, the rates of land-use change and forest degradation, but recent developments in satellite remote sensing have gone far towards reducing these uncertainties. Stocks of carbon as biomass in tropical forests and woodlands add up to 271 ± 16 Pg with an even greater quantity of carbon as soil organic matter. Carbon loss from deforestation, degradation, harvesting and peat fires is estimated as 2.01 ± 1.1 Pg annum(-1); while carbon gain from forest and woodland growth is 1.85 ± 0.09 Pg annum(-1). We conclude that tropical lands are on average a small carbon source to the atmosphere, a result that is consistent with the 'top-down' result from measurements in the atmosphere. If they were to be conserved, they would be a substantial carbon sink. Release of carbon as carbon dioxide from fossil fuel burning in the tropics is 0.74 Pg annum(-1) or 0.57 MgC person(-1) annum(-1) , much lower than the corresponding figures from developed regions of the world.

African tropical rainforest net carbon dioxide fluxes in the twentieth century

The African humid tropical biome constitutes the second largest rainforest region, significantly impacts global carbon cycling and climate, and has undergone major changes in functioning owing to climate and land-use change over the past century. We assess changes and trends in CO₂ fluxes from 1901 to 2010 using nine land surface models forced with common driving data, and depict the inter-model variability as the uncertainty in fluxes. The biome is estimated to be a natural (no disturbance) net carbon sink (−0.02 kg C m⁻² yr⁻¹ or −0.04 Pg C yr⁻¹, p < 0.05) with increasing strength fourfold in the second half of the century. The models were in close agreement on net CO₂ flux at the beginning of the century (σ₁₉₀₁ = 0.02 kg C m⁻² yr⁻¹), but diverged exponentially throughout the century (σ₂₀₁₀ = 0.03 kg C m⁻² yr⁻¹). The increasing uncertainty is due to differences in sensitivity to increasing atmospheric CO₂, but not increasing water stress, despite a decrease in precipitation and increase in air temperature. However, the largest uncertainties were associated with the most extreme drought events of the century. These results highlight the need to constrain modelled CO₂ fluxes with increasing atmospheric CO₂ concentrations and extreme climatic events, as the uncertainties will only amplify in the next century.

It is getting hotter in here: determining and projecting the impacts of global environmental change on drylands

Drylands occupy large portions of the Earth, and are a key terrestrial biome from the socio-ecological point of view. In spite of their extent and importance, the impacts of global environmental change on them remain poorly understood. In this introduction, we review some of the main expected impacts of global change in drylands, quantify research efforts on the topic, and highlight how the articles included in this theme issue contribute to fill current gaps in our knowledge. Our literature analyses identify key under-studied areas that need more research (e.g. countries such as Mauritania, Mali, Burkina Faso, Chad and Somalia, and deserts such as the Thar, Kavir and Taklamakan), and indicate that most global change research carried out to date in drylands has been done on a unidisciplinary basis. The contributions included here use a wide array of organisms (from micro-organisms to humans), spatial scales (from local to global) and topics (from plant demography to poverty alleviation) to examine key issues to the socio-ecological impacts of global change in drylands. These papers highlight the complexities and difficulties associated with the prediction of such impacts. They also identify the increased use of long-term experiments and multidisciplinary approaches as priority areas for future dryland research. Major advances in our ability to predict and understand global change impacts on drylands can be achieved by explicitly considering how the responses of individuals, populations and communities will in turn affect ecosystem services. Future research should explore linkages between these responses and their effects on water and climate, as well as the provisioning of services for human development and well-being.

Long-term variability and rainfall control of savanna fire regimes in equatorial East Africa

Fires burning the vast grasslands and savannas of Africa significantly influence the global carbon cycle. Projecting the impacts of future climate change on fire-mediated biogeochemical processes in these dry tropical ecosystems requires understanding of how various climate factors influence regional fire regimes. To examine climate-vegetation-fire linkages in dry savanna, we conducted macroscopic and microscopic charcoal analysis on the sediments of the past 25 000 years from Lake Challa, a deep crater lake in equatorial East Africa. The charcoal-inferred shifts in local and regional fire regimes were compared with previously published reconstructions of temperature, rainfall, seasonal drought severity, and vegetation dynamics to evaluate millennial-scale drivers of fire occurrence. Our charcoal data indicate that fire in the dry lowland savanna of southeastern Kenya was not fuel-limited during the Last Glacial Maximum (LGM) and Late Glacial, in contrast to many other regions throughout the world. Fire activity remained high at Lake Challa probably because the relatively high mean-annual temperature (~22 °C) allowed productive C₄ grasses with high water-use efficiency to dominate the landscape. From the LGM through the middle Holocene, the relative importance of savanna burning in the region varied primarily in response to changes in rainfall and dry-season length, which were controlled by orbital insolation forcing of tropical monsoon dynamics. The fuel limitation that characterizes the region's fire regime today appears to have begun around 5000-6000 years ago, when warmer interglacial conditions coincided with prolonged seasonal drought. Thus, insolation-driven variation in the amount and seasonality of rainfall during the past 25 000 years altered the immediate controls on fire occurrence in the grass-dominated savannas of eastern equatorial Africa. These results show that climatic impacts on dry-savanna burning are heterogeneous through time, with important implications for efforts to anticipate future shifts in fire-mediated ecosystem processes.

Rate of belowground carbon allocation differs with successional habit of two afromontane trees

BACKGROUND

Anthropogenic disturbance of old-growth tropical forests increases the abundance of early successional tree species at the cost of late successional ones. Quantifying differences in terms of carbon allocation and the proportion of recently fixed carbon in soil CO(2) efflux is crucial for addressing the carbon footprint of creeping degradation.

METHODOLOGY

We compared the carbon allocation pattern of the late successional gymnosperm Podocarpus falcatus (Thunb.) Mirb. and the early successional (gap filling) angiosperm Croton macrostachyus Hochst. es Del. in an Ethiopian Afromontane forest by whole tree (13)CO(2) pulse labeling. Over a one-year period we monitored the temporal resolution of the label in the foliage, the phloem sap, the arbuscular mycorrhiza, and in soil-derived CO(2). Further, we quantified the overall losses of assimilated (13)C with soil CO(2) efflux.

PRINCIPAL FINDINGS

(13)C in leaves of C. macrostachyus declined more rapidly with a larger size of a fast pool (64% vs. 50% of the assimilated carbon), having a shorter mean residence time (14 h vs. 55 h) as in leaves of P. falcatus. Phloem sap velocity was about 4 times higher for C. macrostachyus. Likewise, the label appeared earlier in the arbuscular mycorrhiza of C. macrostachyus and in the soil CO(2) efflux as in case of P. falcatus (24 h vs. 72 h). Within one year soil CO(2) efflux amounted to a loss of 32% of assimilated carbon for the gap filling tree and to 15% for the late successional one.

CONCLUSIONS

Our results showed clear differences in carbon allocation patterns between tree species, although we caution that this experiment was unreplicated. A shift in tree species composition of tropical montane forests (e.g., by degradation) accelerates carbon allocation belowground and increases respiratory carbon losses by the autotrophic community. If ongoing disturbance keeps early successional species in dominance, the larger allocation to fast cycling compartments may deplete soil organic carbon in the long run.

The carbon balance of Africa: synthesis of recent research studies

The African continent contributes one of the largest uncertainties to the global CO(2) budget, because very few long-term measurements are carried out in this region. The contribution of Africa to the global carbon cycle is characterized by its low fossil fuel emissions, a rapidly increasing population causing cropland expansion, and degradation and deforestation risk to extensive dryland and savannah ecosystems and to tropical forests in Central Africa. A synthesis of the carbon balance of African ecosystems is provided at different scales, including observations of land-atmosphere CO(2) flux and soil carbon and biomass carbon stocks. A review of the most recent estimates of the net long-term carbon balance of African ecosystems is provided, including losses from fire disturbance, based upon observations, giving a sink of the order of 0.2 Pg C yr(-1) with a large uncertainty around this number. By comparison, fossil fuel emissions are only of the order of 0.2 Pg C yr(-1) and land-use emissions are of the order of 0.24 Pg C yr(-1). The sources of year-to-year variations in the ecosystem carbon-balance are also discussed. Recommendations for the deployment of a coordinated carbon-monitoring system for African ecosystems are given.

Responses of ecosystem carbon dioxide fluxes to soil moisture fluctuations in a moist Kenyan savanna

Measurements were conducted within a fence-exclosure between February 2008 and July 2009 to investigate the influence of soil moisture on ecosystem CO2 fluxes in a Themeda triandra-dominated grassland of a humid Kenyan savanna. Rainout shelters were constructed to reduce ambient rainfall by 0%, 10% and 20% respectively to attain variable soil water content (SWC) during plant growth. SWC within the top 30 cm layer, above-ground biomass, soil and plant nitrogen (N) concentrations were assessed monthly alongside CO2 fluxes. Net ecosystem CO2 exchange (NEE) and ecosystem respiration (Reco) were measured with closed chambers while carbon (C) partitioning during the wet and dry seasons were assessed through pulse 13C labelling. There were significant seasonal and between plot differences in SWC, above-ground biomass, canopy light utilization efficiency (α), CO2 fluxes and C allocation pattern resulting from differences in SWC. The ecosystem was a net C sink during the wet and C neutral during the dry seasons. The study showed strong seasonal fluctuations in ecosystem CO2 fluxes and underscores the significant role of the savanna grasslands in regional C balance due to its expansive nature. The savanna grassland is however vulnerable to low soil moisture, with significant reduction in CO2 uptake during drought.

Mapping and monitoring carbon stocks with satellite observations: a comparison of methods

Mapping and monitoring carbon stocks in forested regions of the world, particularly the tropics, has attracted a great deal of attention in recent years as deforestation and forest degradation account for up to 30% of anthropogenic carbon emissions, and are now included in climate change negotiations. We review the potential for satellites to measure carbon stocks, specifically aboveground biomass (AGB), and provide an overview of a range of approaches that have been developed and used to map AGB across a diverse set of conditions and geographic areas. We provide a summary of types of remote sensing measurements relevant to mapping AGB, and assess the relative merits and limitations of each. We then provide an overview of traditional techniques of mapping AGB based on ascribing field measurements to vegetation or land cover type classes, and describe the merits and limitations of those relative to recent data mining algorithms used in the context of an approach based on direct utilization of remote sensing measurements, whether optical or lidar reflectance, or radar backscatter. We conclude that while satellite remote sensing has often been discounted as inadequate for the task, attempts to map AGB without satellite imagery are insufficient. Moreover, the direct remote sensing approach provided more coherent maps of AGB relative to traditional approaches. We demonstrate this with a case study focused on continental Africa and discuss the work in the context of reducing uncertainty for carbon monitoring and markets.

Mapping and monitoring carbon stocks with satellite observations: a comparison of methods

Mapping and monitoring carbon stocks in forested regions of the world, particularly the tropics, has attracted a great deal of attention in recent years as deforestation and forest degradation account for up to 30% of anthropogenic carbon emissions, and are now included in climate change negotiations. We review the potential for satellites to measure carbon stocks, specifically aboveground biomass (AGB), and provide an overview of a range of approaches that have been developed and used to map AGB across a diverse set of conditions and geographic areas. We provide a summary of types of remote sensing measurements relevant to mapping AGB, and assess the relative merits and limitations of each. We then provide an overview of traditional techniques of mapping AGB based on ascribing field measurements to vegetation or land cover type classes, and describe the merits and limitations of those relative to recent data mining algorithms used in the context of an approach based on direct utilization of remote sensing measurements, whether optical or lidar reflectance, or radar backscatter. We conclude that while satellite remote sensing has often been discounted as inadequate for the task, attempts to map AGB without satellite imagery are insufficient. Moreover, the direct remote sensing approach provided more coherent maps of AGB relative to traditional approaches. We demonstrate this with a case study focused on continental Africa and discuss the work in the context of reducing uncertainty for carbon monitoring and markets.

Mapping and monitoring carbon stocks with satellite observations: a comparison of methods

Mapping and monitoring carbon stocks in forested regions of the world, particularly the tropics, has attracted a great deal of attention in recent years as deforestation and forest degradation account for up to 30% of anthropogenic carbon emissions, and are now included in climate change negotiations. We review the potential for satellites to measure carbon stocks, specifically aboveground biomass (AGB), and provide an overview of a range of approaches that have been developed and used to map AGB across a diverse set of conditions and geographic areas. We provide a summary of types of remote sensing measurements relevant to mapping AGB, and assess the relative merits and limitations of each. We then provide an overview of traditional techniques of mapping AGB based on ascribing field measurements to vegetation or land cover type classes, and describe the merits and limitations of those relative to recent data mining algorithms used in the context of an approach based on direct utilization of remote sensing measurements, whether optical or lidar reflectance, or radar backscatter. We conclude that while satellite remote sensing has often been discounted as inadequate for the task, attempts to map AGB without satellite imagery are insufficient. Moreover, the direct remote sensing approach provided more coherent maps of AGB relative to traditional approaches. We demonstrate this with a case study focused on continental Africa and discuss the work in the context of reducing uncertainty for carbon monitoring and markets.

Increasing carbon storage in intact African tropical forests

The response of terrestrial vegetation to a globally changing environment is central to predictions of future levels of atmospheric carbon dioxide. The role of tropical forests is critical because they are carbon-dense and highly productive. Inventory plots across Amazonia show that old-growth forests have increased in carbon storage over recent decades, but the response of one-third of the world's tropical forests in Africa is largely unknown owing to an absence of spatially extensive observation networks. Here we report data from a ten-country network of long-term monitoring plots in African tropical forests. We find that across 79 plots (163 ha) above-ground carbon storage in live trees increased by 0.63 Mg C ha(-1) yr(-1) between 1968 and 2007 (95% confidence interval (CI), 0.22-0.94; mean interval, 1987-96). Extrapolation to unmeasured forest components (live roots, small trees, necromass) and scaling to the continent implies a total increase in carbon storage in African tropical forest trees of 0.34 Pg C yr(-1) (CI, 0.15-0.43). These reported changes in carbon storage are similar to those reported for Amazonian forests per unit area, providing evidence that increasing carbon storage in old-growth forests is a pan-tropical phenomenon. Indeed, combining all standardized inventory data from this study and from tropical America and Asia together yields a comparable figure of 0.49 Mg C ha(-1) yr(-1) (n = 156; 562 ha; CI, 0.29-0.66; mean interval, 1987-97). This indicates a carbon sink of 1.3 Pg C yr(-1) (CI, 0.8-1.6) across all tropical forests during recent decades. Taxon-specific analyses of African inventory and other data suggest that widespread changes in resource availability, such as increasing atmospheric carbon dioxide concentrations, may be the cause of the increase in carbon stocks, as some theory and models predict.

Increasing carbon storage in intact African tropical forests

The response of terrestrial vegetation to a globally changing environment is central to predictions of future levels of atmospheric carbon dioxide. The role of tropical forests is critical because they are carbon-dense and highly productive. Inventory plots across Amazonia show that old-growth forests have increased in carbon storage over recent decades, but the response of one-third of the world's tropical forests in Africa is largely unknown owing to an absence of spatially extensive observation networks. Here we report data from a ten-country network of long-term monitoring plots in African tropical forests. We find that across 79 plots (163 ha) above-ground carbon storage in live trees increased by 0.63 Mg C ha(-1) yr(-1) between 1968 and 2007 (95% confidence interval (CI), 0.22-0.94; mean interval, 1987-96). Extrapolation to unmeasured forest components (live roots, small trees, necromass) and scaling to the continent implies a total increase in carbon storage in African tropical forest trees of 0.34 Pg C yr(-1) (CI, 0.15-0.43). These reported changes in carbon storage are similar to those reported for Amazonian forests per unit area, providing evidence that increasing carbon storage in old-growth forests is a pan-tropical phenomenon. Indeed, combining all standardized inventory data from this study and from tropical America and Asia together yields a comparable figure of 0.49 Mg C ha(-1) yr(-1) (n = 156; 562 ha; CI, 0.29-0.66; mean interval, 1987-97). This indicates a carbon sink of 1.3 Pg C yr(-1) (CI, 0.8-1.6) across all tropical forests during recent decades. Taxon-specific analyses of African inventory and other data suggest that widespread changes in resource availability, such as increasing atmospheric carbon dioxide concentrations, may be the cause of the increase in carbon stocks, as some theory and models predict.

Seasonal variation of carbon fluxes in a sparse savanna in semi arid Sudan

BACKGROUND

Large spatial, seasonal and annual variability of major drivers of the carbon cycle (precipitation, temperature, fire regime and nutrient availability) are common in the Sahel region. This causes large variability in net ecosystem exchange and in vegetation productivity, the subsistence basis for a major part of the rural population in Sahel. This study compares the 2005 dry and wet season fluxes of CO2 for a grass land/sparse savanna site in semi arid Sudan and relates these fluxes to water availability and incoming photosynthetic photon flux density (PPFD). Data from this site could complement the current sparse observation network in Africa, a continent where climatic change could significantly impact the future and which constitute a weak link in our understanding of the global carbon cycle.

RESULTS

The dry season (represented by Julian day 35-46, February 2005) was characterized by low soil moisture availability, low evapotranspiration and a high vapor pressure deficit. The mean daily NEE (net ecosystem exchange, Eq. 1) was -14.7 mmol d-1 for the 12 day period (negative numbers denote sinks, i.e. flux from the atmosphere to the biosphere). The water use efficiency (WUE) was 1.6 mmol CO2 mol H2O-1 and the light use efficiency (LUE) was 0.95 mmol CO2 mol PPFD-1. Photosynthesis is a weak, but linear function of PPFD. The wet season (represented by Julian day 266-273, September 2005) was, compared to the dry season, characterized by slightly higher soil moisture availability, higher evapotranspiration and a slightly lower vapor pressure deficit. The mean daily NEE was -152 mmol d-1 for the 8 day period. The WUE was lower, 0.97 mmol CO2 mol H2O-1 and the LUE was higher, 7.2 mumol CO2 mmol PPFD-1 during the wet season compared to the dry season. During the wet season photosynthesis increases with PPFD to about 1600 mumol m-2s-1 and then levels off.

CONCLUSION

Based on data collected during two short periods, the studied ecosystem was a sink of carbon both during the dry and wet season 2005. The small sink during the dry season is surprising and similar dry season sinks have not to our knowledge been reported from other similar savanna ecosystems and could have potential management implications for agroforestry. A strong response of NEE versus small changes in plant available soil water content was found. Collection and analysis of flux data for several consecutive years including variations in precipitation, available soil moisture and labile soil carbon are needed for understanding the year to year variation of the carbon budget of this grass land/sparse savanna site in semi arid Sudan.