The increasing scarcity of environmental resources and competition among forest, water, food and energy coupled with the ever-growing population and climate change pose a serious threat to natural ecosystems. In an effort to provide an integrated approach towards forest conservation as well as energy, water and food security within the broader context of climate change and variability, this study sought to undertake a literature and data review to provide a critical analysis and synthesis of the baseline and trends of the forest- water-food- energy security nexus in East Africa.

Water quality amelioration is one of the key ecosystem services provided by forests in the catchment areas of water supply systems. In this study, we applied random effect models and the least absolute shrinkage and selection regression method of machine learning to South African panel data to estimate the causal effect of natural forest cover on municipalities’ water treatment cost. We controlled for a range of confounding covariates including other land cover variables including wetlands, plantation forests, grassland, woodland etc.

Abstract

Abstract