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Results from an 25 regional climate model simulations from the Coordinated Regional Downscaling Experiment Africa initiative are used to assess the projected changes in temperature and precipitation over southern Africa at two global warming levels (GWLs), namely 1.5 °C and 2.0 °C, relative to pre-industrial values, under the Representative Concentration Pathway 8.5. The results show a robust increase in temperature compared to the control period (1971-2000) ranging from 0.5 °C-1.5 °C for the 1.5 °C GWL and from 1.5 °C-2.5 °C, for the 2.0 °C GWL. Areas in the south-western region of the subcontinent, covering South Africa and parts of Namibia and Botswana are projected to experience the largest increase in temperature, which are greater than the global mean warming, particularly during the September-October-November season. On the other hand, under 1.5 °C GWL, models exhibit a robust reduction in precipitation of up to 0.4 mm day−1 (roughly 20% of the climatological values) over the Limpopo Basin and smaller areas of the Zambezi Basin in Zambia, and also parts of Western Cape, South Africa. Models project precipitation increase of up to 0.1 mm day−1 over central and western South Africa and in southern Namibia. Under 2.0 °C GWL, a larger fraction of land is projected to face robust decreases between 0.2 and 0.4 mm day−1 (around 10%-20% of the climatological values) over most of the central subcontinent and parts of western South Africa and northern Mozambique. Decreases in precipitation are accompanied by increases in the number of consecutive dry days and decreases in consecutive wet days over the region. The importance of achieving the Paris Agreement is imperative for southern Africa as the projected changes under both the 1.5 °C, and more so, 2.0 °C GWL imply significant potential risks to agricultural and economic productivity, human and ecological systems health and water resources with implied increase in regional water stresses.

The Green Revolution, which bolstered agricultural yields and economic well-being in Asia and Latin America beginning in the 1960s, largely bypassed sub-Saharan Africa. We study the first randomized controlled trial of a government-implemented input subsidy program (ISP) in Africa intended to foment a Green Revolution. We find that this temporary subsidy for Mozambican maize farmers stimulates Green Revolution technology adoption and leads to increased maize yields. Effects of the subsidy persist in later unsubsidized years. In addition, social networks of subsidized farmers benefit from spillovers, experiencing increases in technology adoption, yields, and beliefs about the returns to the technologies. Spillovers account for the vast majority of subsidy-induced gains. ISPs alleviate informational market failures, stimulating learning about new technologies by subsidy recipients and their social networks.

Natural resources can have a negative impact on the economy through corruption and civil conflict. This paper tests whether information can counteract this political resource curse. We implement a large-scale field experiment following the dissemination of information about a substantial natural gas discovery in Mozambique. We measure outcomes related to the behavior of citizens and local leaders through georeferenced conflict data, behavioral activities, lab-in-the-field experiments, and surveys. We find that information targeting citizens and their involvement in public deliberations increases local mobilization and decreases violence. By contrast, when information reaches only local leaders, it increases elite capture and rent-seeking.

Fusarium oxysporum f.sp. cubense (Foc) is considered one of the most devastating soilborne fungal pathogens of banana worldwide. Foc causing mortality to Cavendish group bananas, and belonging to the unique vegetative compatibility group (VCG) 01213/16 has been termed tropical race 4 (TR4) and has currently been renamed F. odoratissimum . The pathogen that was first detected approximately 50 years ago in South East Asia, has since spread to countries within the greater Mekong subregion and to Australia. Recently, the pathogen disseminated to India, Pakistan, Oman and Mozambique (Africa) and was identified in the South American continent in Colombia in 2019. In the Middle East, TR4 was first reported from Jordan and Lebanon, and later from Israel in 2016. In Israel, the pathogen was identified as TR4 by VCG tests, pathogenicity assays and molecular verification. The complete genomes of five representative TR4 isolates including two from Israel, one from Jordan, one from the Philippines, and one from Indonesia were sequenced, and single nucleotide polymorphisms (SNPs) analyses were conducted. SNPs were compared to 11 additional sequenced TR4 isolates, to determine the origin of the Israeli isolates. SNP detection and phylogeographical analyses determined that the Middle Eastern isolates are closely related, indicating that the pathogen most likely spread to Israel from Jordan, while those from Colombia are related to a representative isolate from Indonesia.

Global flood models (GFMs) are becoming increasingly important for disaster risk management internationally. However, these models have had little validation against observed flood events, making it difficult to compare model performance. In this paper, we introduce the first collective validation of multiple GFMs against the same events and we analyse how different model structures influence performance. We identify three hydraulically diverse regions in Africa with recent large scale flood events: Lokoja, Nigeria; Idah, Nigeria; and Chemba, Mozambique. We then evaluate the flood extent output provided by six GFMs against satellite observations of historical flood extents in these regions. The critical success index of individual models across the three regions ranges from 0.45 to 0.7 and the percentage of flood captured ranges from 52% to 97%. Site specific conditions influence performance as the models score better in the confined floodplain of Lokoja but score poorly in Idah's flat extensive floodplain. 2D hydrodynamic models are shown to perform favourably. The models forced by gauged flow data show a greater level of return period accuracy compared to those forced by climate reanalysis data. Using the results of our analysis, we create and validate a three-model ensemble to investigate the usefulness of ensemble modelling in a flood hazard context. We find the ensemble model performs similarly to the best individual and aggregated models. In the three study regions, we found no correlation between performance and the spatial resolution of the models. The best individual models show an acceptable level of performance for these large rivers.

The Earth has experienced a global surface warming slowdown (GSWS) or so-called “global warming hiatus” since the end of the 20 th century. The GSWS was marked by a La Niña-like decadal cooling in the Pacific Ocean that subsequently generated an increase in the transfer of Pacific waters into the Indian Ocean via the Indonesian Throughflow (ITF). How the Pacific water spreads through the interior of the Indian Ocean and the impact of these decadal ITF transport changes on the Indian Ocean water mass transformation and circulation remain largely unknown. Here, we analyze the thermohaline structures and current systems at different depths in the Indian Ocean prior to and during the GSWS period. Our study shows that the GSWS involved extensive changes to the Indo-Pacific ocean teleconnection system, characterized by subsurface warming and freshening in the Indian Ocean. A hitherto unknown Indian Ocean pathway of the ITF was discovered off Sumatra associated with prolonged northwestward flow within the South Java Current. Our analysis uncovers a direct linkage of enhanced ITF waters with the Agulhas Current in the Mozambique Channel from thermocline depths down to intermediate depths, that freshened the Indian Ocean. These changes in the Indian Ocean circulation and water mass characteristics impact climate variability through changing the sea surface temperature (SST) and precipitation patterns that can subsequently affect regional economies.

This paper exploits quasi-experimental variation in tariffs in southern Africa to estimate trade elasticities. Traded quantities respond only weakly to a 30 percent reduction in the average nominal tariff rate. Trade flow data combined with primary data on firm behavior and bribe payments suggest that corruption is a potential explanation for the observed low elasticities. In contexts of pervasive corruption, even small bribes can significantly reduce tariffs, making tariff liberalization schemes less likely to affect the extensive and the intensive margins of firms ' import behavior. The tariff liberalization scheme is, however, still associated with improved incentives to accurately report quantities of imported goods, and with a significant reduction in bribe transfers from importers to public officials.

African elections often reveal low levels of political accountability. We assess different forms of voter education during an election in Mozambique. Three interventions providing information to voters and calling for their participation were randomized: an information campaign using SMS, an SMS hotline for electoral misconduct, and the distribution of a free newspaper. To measure impact, we look at official electoral results, reports by electoral observers, and behavioral and survey data. We find positive effects of all treatments on voter turnout. However, only the distribution of the free newspaper led to more accountability-based participation and to a decrease in electoral problems.

Mangroves are ecologically and economically important forested wetlands with the highest carbon (C) density of all terrestrial ecosystems. Because of their exceptionally large C stocks and importance as a coastal buffer, their protection and restoration has been proposed as an effective mitigation strategy for climate change. The inclusion of mangroves in mitigation strategies requires the quantification of C stocks (both above and belowground) and changes to accurately calculate emissions and sequestration. A growing number of countries are becoming interested in using mitigation initiatives, such as REDD+ (reducing emissions from deforestation and forest degradation), in these unique coastal forests. However, it is not yet clear how methods to measure C traditionally used for other ecosystems can be modified to estimate biomass in mangroves with the precision and accuracy needed for these initiatives. Airborne Lidar (ALS) data has often been proposed as the most accurate way for larger scale assessments but the application of ALS for coastal wetlands is scarce, primarily due to a lack of contemporaneous ALS and field measurements. Here, we evaluated the variability in field and Lidar-based estimates of aboveground biomass (AGB) through the combination of different local and regional allometric models and standardized height metrics that are comparable across spatial resolutions and sensor types, the end result being a simplified approach for accurately estimating mangrove AGB at large scales and determining the uncertainty by combining multiple allometric models. We then quantified wall-to-wall AGB stocks of a tall mangrove forest in the Zambezi Delta, Mozambique. Our results indicate that the Lidar H100 height metric correlates well with AGB estimates, with R2 between 0.80 and 0.88 and RMSE of 33% or less. When comparing Lidar H100 AGB derived from three allometric models, mean AGB values range from 192 Mg ha−1 up to 252 Mg ha−1. We suggest the best model to predict AGB was based on the East Africa specific allometry and a power-based regression that used Lidar H100 as the height input with an R2 of 0.85 and an RMSE of 122 Mg ha−1 or 33%. The total AGB of the Lidar inventoried mangrove area (6654 ha) was 1 350 902 Mg with a mean AGB of 203 Mg ha−1 ±166 Mg ha−1. Because the allometry suggested here was developed using standardized height metrics, it is recommended that the models can generate AGB estimates using other remote sensing instruments that are more readily accessible over other mangrove ecosystems on a large scale, and as part of future carbon monitoring efforts in mangroves.

This book investigates the Brazilian health cooperation in Mozambique looking at the interests of both actors and different power relations within this initiative. It counts with a case study looking at the implementation of SociedadeMocambicana de Medicamentos - a pharmaceutical factory that was implemented in Maputo as a result of the cooperation between the countries.