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Dry and wet miombo woodlands of south-central Africa respond differently to climate change

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It is important to understand how species distributions will shift under climate change. While much focus has been on species tracking temperature changes in the northern hemisphere, changing precipitation patterns… Click to show full abstract

It is important to understand how species distributions will shift under climate change. While much focus has been on species tracking temperature changes in the northern hemisphere, changing precipitation patterns in tropical regions have received less attention. The aim of the study was to estimate the current distribution of wet and dry miombo woodlands of sub-Saharan Africa and to predict their distributions under different climate change scenarios. A maximum entropy method (Maxent) was used to estimate the distributions and for projections. Occurrence records of dominant tree species in each woodland were used for modeling, together with altitude, soil characteristics, and climate variables as the environmental variables. Modeling was done under all four representative concentration pathways (RCPs) and three general circulation models. Three dominant tree species were used in models of dry miombo while seven were used for wet miombo. Models estimated dry miombo to cover almost the entire known distribution of miombo woodlands while wet miombo were estimated to predominate in parts of Angola, southern Democratic Republic of Congo, Malawi, Tanzania, Zambia, and Zimbabwe. Future climate scenarios predict a drier climate in sub-Saharan Africa, and as a result, the range of dry miombo will expand. Dry miombo were predicted to expand by up to 17.3% in 2050 and 22.7% in 2070. In contrast, wet miombo were predicted to contract by up to − 28.6% in 2050 and − 41.6% in 2070. A warming climate is conducive for the proliferation of dry miombo tree species but unfavorable for wet miombo tree species.

Keywords: dry miombo; miombo woodlands; climate change; wet miombo; miombo

Journal Title: Environmental Monitoring and Assessment
Year Published: 2020

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