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HIV prevalence varies markedly throughout Africa, and it is often presumed areas of higher HIV prevalence (i.e., hotspots) serve as sources of infection to neighboring areas of lower prevalence. However, the small-scale geography of migration networks and movement of HIV-positive individuals between communities is poorly understood. Here, we use population-based data from ~22,000 persons of known HIV status to characterize migratory patterns and their relationship to HIV among 38 communities in Rakai, Uganda with HIV prevalence ranging from 9 to 43%. We find that migrants moving into hotspots had significantly higher HIV prevalence than migrants moving elsewhere, but out-migration from hotspots was geographically dispersed, contributing minimally to HIV burden in destination locations. Our results challenge the assumption that high prevalence hotspots are drivers of transmission in regional epidemics, instead suggesting that migrants with high HIV prevalence, particularly women, selectively migrate to these areas. HIV prevalence varies throughout Africa, but the contribution of migration remains unclear. Using population-based data from ~22,000 persons, Grabowski et al. show that HIV-positive migrants selectively migrate to high prevalence areas and that out-migrants from these areas geographically disperse. [ABSTRACT FROM AUTHOR]

Savanna fires produce significant emissions globally, but if managed effectively could provide an important mitigation opportunity, particularly in African least developed countries. Here we show global opportunities for emissions reductions through early dry season burning for 37 countries including: 29 countries in Africa (69.1 MtCO2-e yr-1), six countries in South America (13.3 MtCO2-e yr-1), and Australia and Papua New Guinea (6.9 MtCO2-e yr-1). Emissions reduction estimates are based on the successful approach developed in Australia to reduce emissions from savanna fires using global-scale, remotely sensed estimates of monthly emissions. Importantly, 20 least developed countries in Africa account for 74% of the mitigation potential (60.2 MtCO2-e yr-1). More than 1.02 million km2 of savanna dominated protected areas within these countries could be used as pilot sites to test and advance a regional approach to mitigation efforts for savanna fires in Africa. Potential versus actual abatement opportunities are discussed. [ABSTRACT FROM AUTHOR]

Organic matter and nutrient loading into aquatic ecosystems affects ecosystem structure and function and can result in eutrophication and hypoxia. Hypoxia is often attributed to anthropogenic pollution and is not common in unpolluted rivers. Here we show that organic matter loading from hippopotami causes the repeated occurrence of hypoxia in the Mara River, East Africa. We documented 49 high flow events over 3 years that caused dissolved oxygen decreases, including 13 events resulting in hypoxia, and 9 fish kills over 5 years. Evidence from experiments and modeling demonstrates a strong mechanistic link between the flushing of hippo pools and decreased dissolved oxygen in the river. This phenomenon may have been more widespread throughout Africa before hippopotamus populations were severely reduced. Frequent hypoxia may be a natural part of tropical river ecosystem function, particularly in rivers impacted by large wildlife. [ABSTRACT FROM AUTHOR]

Pathogens compete for hosts through patterns of cross-protection conferred by immune responses to antigens. In Plasmodium falciparum malaria, the var multigene family encoding for the major blood-stage antigen PfEMP1 has evolved enormous genetic diversity through ectopic recombination and mutation. With 50-60 var genes per genome, it is unclear whether immune selection can act as a dominant force in structuring var repertoires of local populations. The combinatorial complexity of the var system remains beyond the reach of existing strain theory and previous evidence for non-random structure cannot demonstrate immune selection without comparison with neutral models. We develop two neutral models that encompass malaria epidemiology but exclude competitive interactions between parasites. These models, combined with networks of genetic similarity, reveal non-neutral strain structure in both simulated systems and an extensively sampled population in Ghana. The unique population structure we identify underlies the large transmission reservoir characteristic of highly endemic regions in Africa. [ABSTRACT FROM AUTHOR]

Volcanic eruptions provide tests of human and natural system sensitivity to abrupt shocks because their repeated occurrence allows the identification of systematic relationships in the presence of random variability. Here we show a suppression of Nile summer flooding via the radiative and dynamical impacts of explosive volcanism on the African monsoon, using climate model output, ice-core-based volcanic forcing data, Nilometer measurements, and ancient Egyptian writings. We then examine the response of Ptolemaic Egypt (305-30 BCE), one of the best-documented ancient superpowers, to volcanically induced Nile suppression. Eruptions are associated with revolt onset against elite rule, and the cessation of Ptolemaic state warfare with their great rival, the Seleukid Empire. Eruptions are also followed by socioeconomic stress with increased hereditary land sales, and the issuance of priestly decrees to reinforce elite authority. Ptolemaic vulnerability to volcanic eruptions offers a caution for all monsoon-dependent agricultural regions, presently including 70% of world population. [ABSTRACT FROM AUTHOR]

Sub-Saharan Africa (SSA) is home to approximately ¼ of the global livestock population, which in the last 60 years has increased by factors of 2.5–4 times for cattle, goats and sheep. An important resource for pastoralists, most livestock live in semi-arid and arid environments, where they roam during the day and are kept in enclosures (or bomas) during the night. Manure, although rich in nitrogen, is rarely used, and therefore accumulates in bomas over time. Here we present in-situ measurements of N2O fluxes from 46 bomas in Kenya and show that even after 40 years following abandonment, fluxes are still ~one magnitude higher than those from adjacent savanna sites. Using maps of livestock distribution, we scaled our finding to SSA and found that abandoned bomas are significant hotspots for atmospheric N2O at the continental scale, contributing ~5% of the current estimate of total anthropogenic N2O emissions for all of Africa. Africa houses approximately one third of the global cattle, sheep and goat population. Here the authors show that manure accumulation in livestock enclosures can emit significant quantities of the greenhouse gas N2O for decades after abandonment, totaling 5% of continental anthropogenic N2O emissions. [ABSTRACT FROM AUTHOR]

Mapping aboveground forest biomass is central for assessing the global carbon balance. However, current large-scale maps show strong disparities, despite good validation statistics of their underlying models. Here, we attribute this contradiction to a flaw in the validation methods, which ignore spatial autocorrelation (SAC) in data, leading to overoptimistic assessment of model predictive power. To illustrate this issue, we reproduce the approach of large-scale mapping studies using a massive forest inventory dataset of 11.8 million trees in central Africa to train and validate a random forest model based on multispectral and environmental variables. A standard nonspatial validation method suggests that the model predicts more than half of the forest biomass variation, while spatial validation methods accounting for SAC reveal quasi-null predictive power. This study underscores how a common practice in big data mapping studies shows an apparent high predictive power, even when predictors have poor relationships with the ecological variable of interest, thus possibly leading to erroneous maps and interpretations. Mapping ecological variables using machine-learning algorithms based on remote-sensing data has become a widespread practice in ecology. Here, the authors use forest biomass mapping as a study case to show that the most common model validation approach, which ignores data spatial structure, leads to overoptimistic assessment of model predictive power. [ABSTRACT FROM AUTHOR]

Continental-scale models of malaria climate suitability typically couple well-established temperature-response models with basic estimates of vector habitat availability using rainfall as a proxy. Here we show that across continental Africa, the estimated geographic range of climatic suitability for malaria transmission is more sensitive to the precipitation threshold than the thermal response curve applied. To address this problem we use downscaled daily climate predictions from seven GCMs to run a continental-scale hydrological model for a process-based representation of mosquito breeding habitat availability. A more complex pattern of malaria suitability emerges as water is routed through drainage networks and river corridors serve as year-round transmission foci. The estimated hydro-climatically suitable area for stable malaria transmission is smaller than previous models suggest and shows only a very small increase in state-of-the-art future climate scenarios. However, bigger geographical shifts are observed than with most rainfall threshold models and the pattern of that shift is very different when using a hydrological model to estimate surface water availability for vector breeding. Prior studies mapping climatologically suitable areas for malaria transmission have used relatively simple thresholds for precipitation. Here the authors show that when models incorporate hydrological processes a more complex pattern of malaria suitability emerges in Africa and future shifts in suitability are more pronounced. [ABSTRACT FROM AUTHOR]

Recent outbreaks of animal-borne emerging infectious diseases have likely been precipitated by a complex interplay of changing ecological, epidemiological and socio-economic factors. Here, we develop modelling methods that capture elements of each of these factors, to predict the risk of Ebola virus disease (EVD) across time and space. Our modelling results match previously-observed outbreak patterns with high accuracy, and suggest further outbreaks could occur across most of West and Central Africa. Trends in the underlying drivers of EVD risk suggest a 1.75 to 3.2-fold increase in the endemic rate of animal-human viral spill-overs in Africa by 2070, given current modes of healthcare intervention. Future global change scenarios with higher human population growth and lower rates of socio-economic development yield a fourfold higher likelihood of epidemics occurring as a result of spill-over events. Our modelling framework can be used to target interventions designed to reduce epidemic risk for many zoonotic diseases. The capacity to predict zoonotic disease outbreaks is hampered by data availability and complex relationships between humans, wildlife, and the environment. Here the authors present a modelling framework that identifies potential high-risk locations for Ebola outbreaks under various climatic, demographic, and land use scenarios. [ABSTRACT FROM AUTHOR]

Tropical ecosystems are large carbon stores that are vulnerable to climate change. The sparseness of ground-based measurements has precluded verification of these ecosystems being a net annual source (+ve) or sink (−ve) of atmospheric carbon. We show that two independent satellite data sets of atmospheric carbon dioxide (CO2), interpreted using independent models, are consistent with the land tropics being a net annual carbon emission of ( median minimum maximum ) 1.0 3 - 0.20 + 1.73 and 1.6 0 + 1.39 + 2.11 petagrams (PgC) in 2015 and 2016, respectively. These pan-tropical estimates reflect unexpectedly large net emissions from tropical Africa of 1.4 8 + 0.80 + 1.95 PgC in 2015 and 1.6 5 + 1.14 + 2.42 PgC in 2016. The largest carbon uptake is over the Congo basin, and the two loci of carbon emissions are over western Ethiopia and western tropical Africa, where there are large soil organic carbon stores and where there has been substantial land use change. These signals are present in the space-borne CO2 record from 2009 onwards. Tropical land ecosystems contain vast carbon reservoirs, but their influence on atmospheric CO2 is poorly understood. Here the authors use new carbon-observing satellites to reveal a large emission source over northern tropical Africa, where there are large soil carbon stores and substantial land use changes. [ABSTRACT FROM AUTHOR]