Economic, land use, and ecosystem services impacts of Rwanda's Green Growth Strategy: An application of the IEEM+ESM platform.

We develop and link the Integrated Economic-Environmental Modeling (IEEM) Platform to ecosystem services modeling (ESM). The IEEM+ESM Platform is an innovative decision-making framework for exploring complex public policy goals and elucidating synergies and trade-offs between alternative policy portfolios. The IEEM+ESM approach is powerful in its ability to shed light on (i) change in land use and ecosystem services driven by public policy and the supply and demand responses of businesses and households; and (ii) impacts on standard economic indicators of concern to Ministries of Finance such as gross domestic product and employment, as well as changes in wealth and ecosystem services. The IEEM+ESM approach is being adopted rapidly and by the end of 2020, IEEM+ESM Platforms will be implemented for about 25 countries. To demonstrate the insights generated by the IEEM+ESM approach, we apply it to the analysis of alternative green growth strategies in Rwanda, a country that has made strong progress in reducing poverty and enhancing economic growth in the last 15 years. The case of Rwanda is particularly compelling as it faces intense pressure on its natural capital base and ecosystem services, already with the highest population density in Africa, which is projected to double by 2050. In applying IEEM+ESM and comparing the outcomes of Rwanda's green growth policies, increasing fertilization of agricultural crops shows the largest economic gains but also trade-offs in environmental quality reflected through higher nutrient export and reduced water quality. Combining crop fertilization with forest plantations better balances critical ecosystem services and their role in underpinning economic development as Rwanda progresses toward its target of middle-income status by 2035. This application to Rwanda's green growth strategy demonstrates the value-added of the IEEM+ESM approach in generating results that speak to both economic outcomes and impacts on market and non-market ecosystem services.

Hb Amsterdam-A1 [α32(B13)Met→Ile; HBA1: c.99G>A]: A Hyperunstable Variant Due to a New Mutation on the α1 Gene.

Patients with hyperunstable α chain variants usually present with a thalassemic, rather than hemolytic, phenotype. Electrophoretic, ion exchange and reverse phase separations usually fail to detect the variant and when DNA sequencing identifies a 'silent' substitution it is usually presumed to be hyperunstable. We report the identification of such a variant, α32(B13)Met→Ile; HBA1: c.99G>A, arising from a new mutation on the α1 gene. The hemoglobin (Hb) was unequivocally detected by the isopropanol stability test and confirmed as hyperunstable by mass spectrometry (MS) of the precipitate and lysate, which showed proportions of 55% and 2.5% of α chains, respectively. The instability appears to be driven by perturbation of globin-heme, and possibly α1ß1 subunit, interactions.