Assessing the conservation of Miombo timber species through an integrated index of anthropogenic and climatic threats.

ABSTRACT

AIM: Angolan Miombo woodlands, rich in timber species of the Leguminosae family, go through one of the highest rates of deforestation in sub-Saharan Africa. This study presents, on the basis of updated information of the distribution of Leguminosae timber species native to Angola, an integrated index framing the main threats for trees, which aims to support new conservation measures. LOCATION Sub-Saharan Africa, Republic of Angola. METHODS: The current distribution areas of six Leguminosae timber species (i.e., Afzelia quanzensis, Brachystegia spiciformis, Guibourtia coleosperma, Isoberlinia angolensis, Julbernardia paniculata, and Pterocarpus angolensis) were predicted through ensemble modeling techniques. The level of threat to each species was analyzed, comparing the species potential distribution with a threat index map and with the protected areas. The threat index of anthropogenic and climatic factors encompasses the effects of population density, agriculture, proximity to roads, loss of tree cover, overexploitation, trends in wildfires, and predicted changes in temperature and precipitation. RESULTS: Our results revealed that about 0.5% of Angola's area is classified as of "Very high" threat, 23.9% as "High" threat, and 66.5% as "Moderate" threat. Three of the studied species require special conservation efforts, namely B. spiciformis and I. angolensis, which have a large fraction of predicted distribution in areas of high threat, and G. coleosperma since it has a restricted distribution area and is one of the most valuable species in international markets. The priority areas for the conservation of Leguminosae timber species were found in Benguela and Huíla. MAIN CONCLUSIONS: This study provides updated data that should be applied to inform policymakers, contributing to national conservation planning and protection of native flora in Angola. Moreover, it presents a methodological approach for the predictions of species distribution and for the creation of a threat index map that can be applied in other poorly surveyed tropical regions.