Dependency, Distribution and Diversification (3Ds) of livelihoods in the Miombo woodlands: learning from Tanzania

ABSTRACT

The Miombo woodlands that cover around 93% of forested area in Tanzania are central to livelihoods of rural dwellers. Nevertheless, there is paucity of scientific studies and associated knowledge on the dependence, distribution, and diversification aspects of livelihoods in such ecosystems. Our empirical case-based findings indicate the dependence on Miombo woodlands was relatively high contributing 33.8% to total annual household income after tobacco cultivation at 39.6%. As such, forest incomes are vital for rural households living around such ecosystems. Among the poorest groups, forest income contributed to 40% of the total annual income whilst decreasing slightly as wealth increased reaching 32% among the better-off. On issues of livelihood distribution, forest incomes played a role in equalizing income distribution with a Gini change of about 0.05, however, it was tobacco cultivation that was more responsible for lowering the gap between income inequality levels with a Gini change of 0.08. In terms of diversification, rural households displayed a high level of diversity of livelihood options at a diversity index of 0.7 and forests were a diversification option. These findings contribute a policy lesson that reduced access to the miombo woodlands through exclusionary conservation mechanisms would result in considerable negative impacts on rural households’ welfare and exacerbate income differentiation in the area.

KEYWORDS:

• Miombo woodlands
• livelihoods
• dependence
• distribution
• diversification

Acknowledgments

Through the scholarship attained, this study was partially funded by the German Academic Exchange Service (DAAD) as part of M.Sc. work in line with their goals for climate change and sustainable development for Africa. The corresponding author is grateful for the overall support received from the DAAD.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

b. Regression computations involving incomes were carried out using the local currency Tshs. 1US$=2,300 Tshs (GDP per capita (current US$), 2019)

c. Regression computations involving incomes were carried out using the local currency Tshs. 1US$= 2,300 Tshs (GDP per capita (current US$), 2019)