Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A Sensitive Analysis of Drivers and Impact of Deforestation in Uganda's Virgin Tropical Rainforests Using Regression Analysis: Efforts Towards Zero Deforestation by 2030

Version 1 : Received: 24 April 2022 / Approved: 25 April 2022 / Online: 25 April 2022 (05:24:42 CEST)

How to cite: Bamwesigye, D.; Yeboah, E.; Šafařík, D. A Sensitive Analysis of Drivers and Impact of Deforestation in Uganda's Virgin Tropical Rainforests Using Regression Analysis: Efforts Towards Zero Deforestation by 2030. Preprints 2022, 2022040218 (doi: 10.20944/preprints202204.0218.v1). Bamwesigye, D.; Yeboah, E.; Šafařík, D. A Sensitive Analysis of Drivers and Impact of Deforestation in Uganda's Virgin Tropical Rainforests Using Regression Analysis: Efforts Towards Zero Deforestation by 2030. Preprints 2022, 2022040218 (doi: 10.20944/preprints202204.0218.v1).

Abstract

Uganda possesses natural rainforests that serve enormous environmental ecosystems and biodiversity services. Moreover, the country is known for its various tropical rainforest hardwoods, birds, and animal species. Over the years, the trend in the natural forest land has declined at an alarming rate; hence need to investigate the possible drivers. The loss of such biodiversity and ecosystems risks desertification and extreme climatic condition. As the world moves towards Zero Deforestation 2030, understanding the determinants of deforestation and forest degradation is paramount. Therefore, the main objective of this study was to understand the impact and relationships between net forest conversion, energy emission, agriculture, and forest production of Roundwood. We used data from FAO for the period 2004-2016. Using the ADF and KPSS test, we checked for the unit root presence in the variables. Also, the study used two different regression models: multiple linear regression and dynamic linear model. To analyze the determinants of deforestation, we used net forest conversion in Uganda. There was 94 % variation in the dependent variable (Net Forest conversion). The outcome of the dynamic linear regression showed that agriculture and energy emission positively impact net forest conversion. Based on our findings, this study recommended the modernization of agriculture by the government of Uganda to stop cutting down the forests on a big scale. Also, the study suggested that the government strictly legislate Roundwood and wood fuels/charcoal and firewood to reduce huge dependency on forests toward Zero-Deforestation by 2030. If well-structured and implemented, government policies could solve the unnecessary over dependency on the rainforest, the heart of the region's climatic conditions.

Keywords

Agriculture; climate change; energy emission; forest transformation; policy actions; livelihood; wood fuel; Zero-Deforestation

Subject

EARTH SCIENCES, Environmental Sciences

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