This paper focuses on the aspects related to improving the conservation and use of neglected and underutilized crops through the experiences of the International Plant Genetic Resources Institute and the International Centre for Underutilized crops, both of which have been directly involved with these species since their establishment.

The baobab tree, with more than 300 uses and commercial value in EU and United States, has been identified as one of the most important trees to be conserved and domesticated in Africa. A decline in baobab populations because of changes in climate could have a negative effect on African livelihoods. Therefore, it is important to study the potential future distribution of this species and determine strategies for conservation. We used Maxent, 480 geo-referenced records, present and future climatic and soil layers. Different general circulation models and scenarios were selected. Models were simulated for (i) All records, (ii) East Africa and (iii) West Africa species records. For each combination, the proportion of the present habitat that might remain suitable in the future was determined. These habitat proportions were compared with the Protected Areas in Africa. Although potential future distributions were different depending on model, scenario and records used, in all cases only a percentage of the present distribution was predicted to remain suitable in the future. Some countries were found to have no suitable habitat in the future. Recommendations for different conservation strategies include in situ conservation in Protected Areas; ex situ conservation in seed banks; and conservation through 'sustainable utilization'. RésuméLe baobab, pour lequel on connaît 300 utilisations et valeurs commerciales dans l'UE et les U.S.A., a été identifié comme l'un des arbres dont la conservation et la domestication sont les plus importantes en Afrique. Un déclin des populations de baobabs dû aux changements climatiques pourrait avoir un impact négatif sur les moyens de subsistance des Africains. Il est dès lors important d'étudier la future distribution potentielle de cette espèce et de déterminer des stratégies pour sa conservation. Nous avons utilisé Maxent, 480 données géoréférencées, des couches de données sur l'étude et la prédiction du climat, ainsi que sur les sols. Nous avons choisi différents modèles de circulation générale et différents scénarios. Nous avons créé des modèles pour (i) l'ensemble des données et (ii) les données sur l'espèce en Afrique de l'Est et (iii) en Afrique de l'ouest. Pour chaque combinaison, la proportion de l'habitat actuel qui pourrait rester propice à l'avenir a été déterminée. Ces différentes proportions ont été comparées avec les aires protégées africaines. Bien que les distributions futures potentielles soient différentes selon les modèles, les scénarios et les données utilisées, l'on prédisait dans tous les cas que seul un certain pourcentage de la distribution actuelle resterait adapté à l'avenir. Pour certains pays, on a trouvé qu'il ne resterait aucun habitat propice dans le futur. Les recommandations en matière de stratégies de conservation incluent : la conservation in situ dans des aires protégées, la conservation in situ dans des banques de semences et la conservation par une 'utilisation durable'.Climate change and the African baobab (Adansonia digitata L.) 243

The benefits provided by underutilised fruit tree species such as baobab (Adansonia digitata L.) in combating increasing malnutrition and poverty become more apparent as awareness grows regarding concerns of climate change and food security. Due to its multiple uses, its high nutritional and medicinal value, drought tolerance and relatively easy cultivation, baobab has been identified as one of the most important edible forest trees to be conserved, domesticated and valued in Africa. In order to contribute towards the cultivation of the species, suitability of sites in Africa and worldwide was evaluated for potential cultivation using species' locality data and spatial environmental data in MAXENT modelling framework. A total of 450 geo-referenced records of the baobab tree were assembled from herbarium records, commercial firm's databases and fieldwork for modelling site suitability for global cultivation of the baobab tree. Climatic and topographic data were acquired from the Worldclim data while soil data was obtained from the Harmonized World Soil Database. MAXENT was found to be a successful modelling method for studying cultivation potential. The main variables that contributed towards predicting baobab's global cultivation potential were annual precipitation and temperature seasonality. Results suggest that baobab tree could be widely cultivated in most countries in southern Africa and in the Sudano-Sahelian zone of West Africa from Senegal to Sudan. Angola and Somalia were found to be highly suitable for cultivating baobab in Africa. Model suggests, India, where the baobab tree already exists and is used, to be the most suitable country for baobab cultivation outside Africa. North-west Australia, Madagascar, north-east Brazil and Mexico resulted to be other suitable places for cultivating the tree species. Although it is recommended model results be validated with in situ seedling experiments, there seems to be a great potential for the cultivation of this species globally.

Many food legumes are underutilized, although these could provide even better food products, more balanced natural diets, better pharmaceutical products, natural insecticides and flavouring, dyes, as well as their usage for the preparation of beverages. This chapter discusses the potential of selected legume species with diverse uses. These legumes, including jack bean (Canavalia ensiformis), lablab bean (Lablab purpureus), tarwai or pearl lupin (Lupinus mutabilis), horse gram (Macrotyloma uniflorum), velvet bean (Mucuna pruriens), tepary bean (Phaseolus acutifolius) and lima bean (Phaseolus lunatus), were selected because of recent research interest and their potential suitability in various cropping systems and adaptation to a range of climates in sustainable agricultural production systems.

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