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Ricinodendron heudelotii (Baill.) Heckel is an important nutraceutical reservoir. Its Sustainable exploitation requires information on its potential distribution in the current context of rapid population growth and climate change threats. This study aimed to map the suitable areas for its domestication and conservation under current and future climate conditions in Benin. Occurrence data were recorded and combined with the environmental layers of two climatic scenarios (optimistic RCP 4.5 and pessimistic RCP 8.5) following the biodiversity modelling approach (biomod2). Currently, about four percent (5082 Km2) of the country's area mainly located in the sub-humid and the humid zones were potentially suitable for R. heudelotii distribution. Under future climatic conditions the potentially suitable areas were mainly in the sub-humid zone, but almost all the highly suitable areas located in the humid zone will become medium suitable areas by the years 2055 and 2085 horizons. This study shows that, whatever the future climatic scenarios, R. heudelotii will substantially maintain the size of its range across the country. These findings allow undertaking anticipated actions to better adapt to the potential effects of climate change and to better guide policies for the conservation and development of forest resources.

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Modern breeding methods integrate next-generation sequencing and phenomics to identify plants with the best characteristics and greatest genetic merit for use as parents in subsequent breeding cycles to ultimately create improved cultivars able to sustain high adoption rates by farmers. This data-driven approach hinges on strong foundations in data management, quality control, and analytics. Of crucial importance is a central database able to (1) track breeding materials, (2) store experimental evaluations, (3) record phenotypic measurements using consistent ontologies, (4) store genotypic information, and (5) implement algorithms for analysis, prediction, and selection decisions. Because of the complexity of the breeding process, breeding databases also tend to be complex, difficult, and expensive to implement and maintain. Here, we present a breeding database system, Breedbase (https://breedbase.org/, last accessed 4/18/2022). Originally initiated as Cassavabase (https://cassavabase.org/, last accessed 4/18/2022) with the NextGen Cassava project (https://www.nextgencassava.org/, last accessed 4/18/2022), and later developed into a crop-agnostic system, it is presently used by dozens of different crops and projects. The system is web based and is available as open source software. It is available on GitHub (https://github.com/solgenomics/, last accessed 4/18/2022) and packaged in a Docker image for deployment (https://hub.docker.com/u/breedbase, last accessed 4/18/2022). The Breedbase system enables breeding programs to better manage and leverage their data for decision making within a fully integrated digital ecosystem., (© The Author(s) 2022. Published by Oxford University Press on behalf of Genetics Society of America.)