The Congo Basin in Central Africa is home to the second largest rainforest in the world after the Amazon. These forests sequester more carbon than any other tropical forest both in the above‐ground biomass and in the world's largest peat deposits, located in the Cuvette Centrale. These ecosystems are important for biodiversity and the livelihoods and wellbeing of local people, and they play a crucial role in local, regional and global water cycles. This interdisciplinary analysis of climate change and biodiversity sciences was used to bring together multiple sources of information to assesses the hazard, exposure and vulnerability dimensions of climate risks to Central Africa's forests and the people who live there. Tailored climate information was developed by integrating multiple sources of climate data and literature reviews. This information was analysed alongside a review of biological diversity in the Congo Basin forests so that climate risks to the functioning of forest ecosystems could be assessed. It is clear that the possible impacts of climate change need to be understood alongside and in terms of interactions with a wide range of anthropic pressures in Central Africa. The ecosystem services of Central Africa's forests are globally essential but face competing pressures and are undervalued in conventional economic terms. Oil and gas exploration is a challenge to global climate change mitigation agreements and to biodiversity. Hunting has led to defaunation in some areas, disturbing ecosystems and threatening iconic species. Unregulated logging and forest clearance for agriculture and oil palm plantations are also major threats to forest ecology and biodiversity. The joint approach of this study demonstrates that integration of expertise is necessary to support climate mainstreaming and to meet the growing demand for evidence to inform protection strategies for biodiverse regions worldwide, particularly in observation sparse areas such as Central African forests.

Pan-Africa convection-permitting regional climate model simulations have been performed to study the impact of high resolution and the explicit representation of atmospheric moist convection on the present and future climate of Africa. These unique simulations have allowed European and African climate scientists to understand the critical role that the representation of convection plays in the ability of a contemporary climate model to capture climate and climate change, including many impact-relevant aspects such as rainfall variability and extremes. There are significant improvements in not only the small-scale characteristics of rainfall such as its intensity and diurnal cycle, but also in the large-scale circulation. Similarly, effects of explicit convection affect not only projected changes in rainfall extremes, dry spells, and high winds, but also continental-scale circulation and regional rainfall accumulations. The physics underlying such differences are in many cases expected to be relevant to all models that use parameterized convection. In some cases physical understanding of small-scale change means that we can provide regional decision-makers with new scales of information across a range of sectors. We demonstrate the potential value of these simulations both as scientific tools to increase climate process understanding and, when used with other models, for direct user applications. We describe how these ground-breaking simulations have been achieved under the U.K. Government’s Future Climate for Africa Programme. We anticipate a growing number of such simulations, which we advocate should become a routine component of climate projection, and encourage international coordination of such computationally and human-resource expensive simulations as effectively as possible.

We introduce the concept of Climate Risk Narratives (CRNs), their origin, and their evolution through a trans-disciplinary engaged research activity around urban climate resilience. While the use of narratives as a communication and engagement device is well established and similar concepts such as scenarios and storylines exist, we describe the learning and value that this specific formulation of narratives has brought to an in-depth engagement process. In particular, we describe and explore how different types of uncertainty can be represented, how narratives can be co-produced, the value they bring to integration and interrogation of relevant knowledge, and the emerging role of narratives as trans-disciplinary engagement devices or boundary objects. The value of CRNs in producing climate knowledge and integrating it into decision-making is demonstrated through case study examples. Principles for developing CRNs and good practice in their use are proposed before mapping out future directions for research and practice.

The stories on the infographic and detailed in the accompanying brief describe three possible futures for rural East Africa in 2050. How the climate will change in the coming decades is uncertain, so three different plausible futures are included to demonstrate this range. These futures do not cover every possible outcome projected by climate models. The stories also describe some of the resulting impacts that could be experienced in rural areas. However, these impacts will vary across the region due to a range of local factors.

Abstract Surveillance of adult Culicoides biting midge flight activity is used as an applied ecological method to guide the management of arbovirus incursions on livestock production in Europe and Australia. To date the impact of changes in the phenology of adult vector activity on arbovirus transmission has not been defined. We investigated this at two sites in the UK, identifying 150,000 Culicoides biting midges taken from 2867 collections over a nearly 40 year timescale. Whilst we recorded no change in seasonal activity at one site, shifts in first adult appearance and last adult appearance increased the seasonal activity period of Culicoides species at the other site by 40 days over the time period. Lengthening of the adult activity season was driven by an increase in abundance of Culicoides and correlated with local increases in temperature and precipitation. This diversity in responses poses significant challenges for predicting future transmission and overwintering risk. Policy implications. Our analysis not only shows a dramatic and consistent increase in the adult active period of Culicoides biting midges, but also that this varies significantly between sites. This suggests broad‐scale analyses alone are insufficient to understand the potential impacts of changes in climate on arbovirus vector populations. Understanding the impact of climate change on adult Culicoides seasonality and transmission of arboviruses requires the context of changes in a range of other local ecological drivers.

Integrating Hydro-Climate Science into Policy Decisions for Climate-Resilient Infrastructure and Livelihoods in East Africa (HyCRISTAL) is a Future Climate for Africa (FCFA) project funded to deliver new understanding of East African climate change and its impacts, and to demonstrate use of climate change information in long-term decision-making in the region. Here, we briefly summarise key findings from HyCRISTAL so far on climate change, as well as key findings from the pan-African FCFA project “IMPALA” relevant to East Africa, both in the context of previous literature on the topic.

Wheat rust diseases pose one of the greatest threats to global food security, including subsistence farmers in Ethiopia. The fungal spores transmitting wheat rust are dispersed by wind and can remain infectious after dispersal over long distances. The emergence of new strains of wheat rust has exacerbated the risks of severe crop loss. We describe the construction and deployment of a near realtime early warning system (EWS) for two major wind-dispersed diseases of wheat crops in Ethiopia that combines existing environmental research infrastructures, newly developed tools and scientific expertise across multiple organisations in Ethiopia and the UK. The EWS encompasses a sophisticated framework that integrates field and mobile phone surveillance data, spore dispersal and disease environmental suitability forecasting, as well as communication to policy-makers, advisors and smallholder farmers. The system involves daily automated data flow between two continents during the wheat season in Ethiopia. The framework utilises expertise and environmental research infrastructures from within the cross-disciplinary spectrum of biology, agronomy, meteorology, computer science and telecommunications. The EWS successfully provided timely information to assist policy makers formulate decisions about allocation of limited stock of fungicide during the 2017 and 2018 wheat seasons. Wheat rust alerts and advisories were sent by short message service and reports to 10 000 development agents and approximately 275 000 smallholder farmers in Ethiopia who rely on wheat for subsistence and livelihood security. The framework represents one of the first advanced crop disease EWSs implemented in a developing country. It provides policy-makers, extension agents and farmers with timely, actionable information on priority diseases affecting a staple food crop. The framework together with the underpinning technologies are transferable to forecast wheat rusts in other regions and can be readily adapted for other wind-dispersed pests and disease of major agricultural crops.

Integrating Hydro-Climate Science into Policy Decisions for Climate-Resilient Infrastructure and Livelihoods in East Africa (HyCRISTAL) is a Future Climate for Africa (FCFA) project funded to deliver new understanding of East African climate change and its impacts, and to demonstrate use of climate change information in long-term decision-making in the region. Here, we briefly summarise key findings from HyCRISTAL so far on climate change, as well as key findings from the pan-African FCFA project “IMPALA” relevant to East Africa, both in the context of previous literature on the topic.

The stories on the infographic and detailed in the accompanying brief describe three possible futures for rural East Africa in 2050. How the climate will change in the coming decades is uncertain, so three different plausible futures are included to demonstrate this range. These futures do not cover every possible outcome projected by climate models. The stories also describe some of the resulting impacts that could be experienced in rural areas. However, these impacts will vary across the region due to a range of local factors.

The impacts of climate change will vary across the region according to a range of local factors. This infographic represents the impacts that may be felt in Urban East Africa under three different possible climate futures. Which of these impacts could be felt in your community in these three different climates?

The climate system comprises multiple components, primarily the atmosphere, ocean and cryosphere, each incorporating physical processes that interact across scales. To help understand the behaviour of this complex system, and evaluate climate model simulations, researchers typically take a reductionist approach, focusing on individual climate processes and studying their relationships with weather and climate in different regions. While more holistic approaches, such as climate networks, have been developed to explicitly address the complexity of the climate, here we argue for the use of a new approach that accounts for multiple cross-scale process interactions, framed with respect to specific climate outcomes of societal importance. We introduce and explore the concept of "climate process chains" (CPCs), describing their potential application using examples determined for southern Africa. Building on related theoretical concepts, and through reviewing literature on climate processes and teleconnections to southern Africa, we identify candidate CPCs for two outcomes of societal interest; a regional-scale drought and local-scale heavy rainfall. Focusing on such outcomes means that CPC investigations have more relevance to climate risk management contexts, as well as providing a constraint on the exploration of climate uncertainties for a region. We argue that CPCs may help to articulate relationships amongst regionally relevant climate processes across temporal and spatial scales, and discuss their potential utility in climate research, including in the evaluation of climate models and their simulations.

We have implemented dynamical downscaling of the Met Office GloSea5 global seasonal forecasting system and analysed its ability to generate skilful forecasts of characteristics of the June-September rainy season in Ethiopia that are of societal relevance. The downscaling used a regional model with a resolution of 25 km, and the same atmosphere and land configuration as the global model, to produce a 3-member ensemble of seasonal hindcasts for the period 1991-2011 and a larger 15-member ensemble for four of these years comprising two anomalously dry and two anomalously wet years. The regional model was also driven by the quasi-observed ERA-Interim dataset. To provide context for the assessment of the downscaled seasonal forecasts and to show the limit for the skill of a global seasonal forecast downscaling system for the region. A mainly qualitative assessment of GloSea5 and downscaled GloSea5 forecasts demonstrated that the downscaled forecasts could be considered a faithful disaggregation of the coarse resolution GloSea5 forecasts. Forecasts of average seasonal rainfall anomalies in the three regions of Ethiopia studied were captured in three of the four years with the wet season of 2006 incorrectly forecast in all three regions, and the 21 year 3-member hindcast had a correlation of 0.65 with observations. Whilst exploring the potential for the downscaled GloSea5 to generate skillful forecasts of rainy season onset and dry spells we note that both the global and regional model have skill with onset correctly predicted as being early or late in more than 75% of cases for some regions.

The Australian wheat stem rust (Puccinia graminis f. sp. tritici) population was shaped by the introduction of four exotic incursions into the country. It was previously hypothesized that at least two of these (races 326-1,2,3,5,6 and 194-1,2,3,5,6 first detected in 1969) had an African origin and moved across the Indian Ocean to Australia on high-altitude winds. We provide strong supportive evidence for this hypothesis by combining genetic analyses and complex atmospheric dispersion modeling. Genetic analysis of 29 Australian and South African P. graminis f. sp. tritici races using microsatellite markers confirmed the close genetic relationship between the South African and Australian populations, thereby confirming previously described phenotypic similarities. Lagrangian particle dispersion model simulations using finely resolved meteorological data showed that long distance dispersal events between southern Africa and Australia are indeed possible, albeit rare. Simulated urediniospore transmission events were most frequent from central South Africa (viable spore transmission on approximately 7% of all simulated release days) compared with other potential source regions in southern Africa. The study acts as a warning of possible future P. graminis f. sp. tritici dispersal events from southern Africa to Australia, which could include members of the Ug99 race group, emphasizing the need for continued surveillance on both continents.

Infectious crop diseases spreading over large agricultural areas pose a threat to food security. Aggressive strains of the obligate pathogenic fungus Puccinia graminis f.sp. tritici (Pgt) , causing the crop disease wheat stem rust, have been detected in East Africa and the Middle East, where they lead to substantial economic losses and threaten livelihoods of farmers. The majority of commercially grown wheat cultivars worldwide are susceptible to these emerging strains, which pose a risk to global wheat production, because the fungal spores transmitting the disease can be wind-dispersed over regions and even continents 1 – 11 . Targeted surveillance and control requires knowledge about airborne dispersal of pathogens, but the complex nature of long-distance dispersal poses significant challenges for quantitative research 12 – 14 . We combine international field surveys, global meteorological data, a Lagrangian dispersion model and high-performance computational resources to simulate a set of disease outbreak scenarios, tracing billions of stochastic trajectories of fungal spores over dynamically changing host and environmental landscapes for more than a decade. This provides the first quantitative assessment of spore transmission frequencies and amounts amongst all wheat producing countries in Southern/East Africa, the Middle East and Central/South Asia. We identify zones of high air-borne connectivity that geographically correspond with previously postulated wheat rust epidemiological zones (characterized by endemic disease and free movement of inoculum) 10 , 15 , and regions with genetic similarities in related pathogen populations 16 , 17 . We quantify the circumstances (routes, timing, outbreak sizes) under which virulent pathogen strains such as ‘Ug99’ 5 , 6 pose a threat from long-distance dispersal out of East Africa to the large wheat producing areas in Pakistan and India. Long-term mean spore dispersal trends (predominant direction, frequencies, amounts) are summarized for all countries in the domain (Supplementary Data). Our mechanistic modelling framework can be applied to other geographic areas, adapted for other pathogens and used to provide risk assessments in real-time 3 .

Bluetongue, an economically important animal disease, can be spread over long distances by carriage of insect vectors (Culicoides biting midges) on the wind. The weather conditions which influence the midge's flight are controlled by synoptic scale atmospheric circulations. A method is proposed that links wind-borne dispersion of the insects to synoptic circulation through the use of a dispersion model in combination with principal component analysis (PCA) and cluster analysis. We illustrate how to identify the main synoptic situations present during times of midge incursions into the UK from the European continent. A PCA was conducted on high-pass-filtered mean sea-level pressure data for a domain centred over north-west Europe from 2005 to 2007. A clustering algorithm applied to the PCA scores indicated the data should be divided into five classes for which averages were calculated, providing a classification of the main synoptic types present. Midge incursion events were found to mainly occur in two synoptic categories; 64.8% were associated with a pattern displaying a pressure gradient over the North Atlantic leading to moderate south-westerly flow over the UK and 17.9% of the events occurred when high pressure dominated the region leading to south-easterly or easterly winds. The winds indicated by the pressure maps generally compared well against observations from a surface station and analysis charts. This technique could be used to assess frequency and timings of incursions of virus into new areas on seasonal and decadal timescales, currently not possible with other dispersion or biological modelling methods.

In recent years, severe wheat stem rust epidemics hit Ethiopia, sub-Saharan Africa’s largest wheat-producing country. These were caused by race TKTTF (Digalu race) of the pathogen Puccinia graminis f. sp. tritici, which, in Ethiopia, was first detected at the beginning of August 2012. We use the incursion of this new pathogen race as a case study to determine likely airborne origins of fungal spores on regional and continental scales by means of a Lagrangian particle dispersion model (LPDM). Two different techniques, LPDM simulations forward and backward in time, are compared. The effects of release altitudes in time-backward simulations and P. graminis f. sp. tritici urediniospore viability functions in time-forward simulations are analyzed. Results suggest Yemen as the most likely origin but, also, point to other possible sources in the Middle East and the East African Rift Valley. This is plausible in light of available field surveys and phylogenetic data on TKTTF isolates from Ethiopia and other countries. Independent of the case involving TKTTF, we assess long-term dispersal trends (>10 years) to obtain quantitative estimates of the risk of exotic P. graminis f. sp. tritici spore transport (of any race) into Ethiopia for different ‘what-if’ scenarios of disease outbreaks in potential source countries in different months of the wheat season.

Andalusia (Southern Spain) is considered one of the main routes of introduction of bluetongue virus (BTV) into Europe, evidenced by a devastating epidemic caused by BTV-1 in 2007. Understanding the pattern and the drivers of BTV-1 spread in Andalusia is critical for effective detection and control of future epidemics. A long-standing metric for quantifying the behaviour of infectious diseases is the case-reproduction ratio (Rt), defined as the average number of secondary cases arising from a single infected case at time t (for t>0). Here we apply a method using epidemic trees to estimate the between-herd case reproduction ratio directly from epidemic data allowing the spatial and temporal variability in transmission to be described. We then relate this variability to predictors describing the hosts, vectors and the environment to better understand why the epidemic spread more quickly in some regions or periods. The Rt value for the BTV-1 epidemic in Andalusia peaked in July at 4.6, at the start of the epidemic, then decreased to 2.2 by August, dropped below 1 by September (0.8), and by October it had decreased to 0.02. BTV spread was the consequence of both local transmission within established disease foci and BTV expansion to distant new areas (i.e. new foci), which resulted in a high variability in BTV transmission, not only among different areas, but particularly through time, which suggests that general control measures applied at broad spatial scales are unlikely to be effective. This high variability through time was probably due to the impact of temperature on BTV transmission, as evidenced by a reduction in the value of Rt by 0.0041 for every unit increase (day) in the extrinsic incubation period (EIP), which is itself directly dependent on temperature. Moreover, within the range of values at which BTV-1 transmission occurred in Andalusia (20.6°C to 29.5°C) there was a positive correlation between temperature and Rt values, although the relationship was not linear, probably as a result of the complex relationship between temperature and the different parameters affecting BTV transmission. Rt values for BTV-1 in Andalusia fell below the threshold of 1 when temperatures dropped below 21°C, a much higher threshold than that reported in other BTV outbreaks, such as the BTV-8 epidemic in Northern Europe. This divergence may be explained by differences in the adaptation to temperature of the main vectors of the BTV-1 epidemic in Andalusia (Culicoides imicola) compared those of the BTV-8 epidemic in Northern Europe (Culicoides obsoletus). Importantly, we found that BTV transmission (Rt value) increased significantly in areas with higher densities of sheep. Our analysis also established that control of BTV-1 in Andalusia was complicated by the simultaneous establishment of several distant foci at the start of the epidemic, which may have been caused by several independent introductions of infected vectors from the North of Africa. We discuss the implications of these findings for BTV surveillance and control in this region of Europe.

The role of the northward expansion of Culicoides imicola Kieffer in recent and unprecedented outbreaks of Culicoides-borne arboviruses in southern Europe has been a significant point of contention. We combined entomological surveys, movement simulations of air-borne particles, and population genetics to reconstruct the chain of events that led to a newly colonized French area nestled at the northern foot of the Pyrenees. Simulating the movement of air-borne particles evidenced frequent wind-transport events allowing, within at most 36 hours, the immigration of midges from north-eastern Spain and Balearic Islands, and, as rare events, their immigration from Corsica. Completing the puzzle, population genetic analyses discriminated Corsica as the origin of the new population and identified two successive colonization events within west-Mediterranean basin. Our findings are of considerable importance when trying to understand the invasion of new territories by expanding species.