Incomes from the forest: methods for the development and conservation of forest products for local communities

Wollenberg, Eva K.; Ingles, A. W.

doi:10.17528/cifor/000483

Cited by 21 publications

(1 citation statement)

References 44 publications

(70 reference statements)

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“…In the Congo Basin, people live in and around national parks and other protected forest landscapes and depend on those ecosystems [20,[34][35][36][37]. Income estimation for people whose livelihoods depend on forests is central to understanding their wellbeing and the use of forests [38]. The analysis of forest resources used by forest dwellers can provide relevant insights to their management and design of effective development and conservation strategies [2,6,18,20,[39][40][41][42][43].…”

Section: Introductionmentioning

confidence: 99%

Assessing the Economic Contribution of Forest Use to Rural Livelihoods in the Rubi-Tele Hunting Domain, DR Congo

Mendako

Tian

Ullah

et al. 2022

Forests

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Forest utilization makes a significant economic contribution to the livelihoods of rural households, especially those living in developing countries. This study was conducted to determine the absolute and relative forest income and measure the distributional impact of forest income on economic inequalities among rural households in the Rubi-Tele Hunting Domain (RTHD), Democratic Republic of the Congo (DR Congo). Household socioeconomic data and other qualitative informations were collected using structured household-level surveys, focus group discussions, and key informant interviews. The study used descriptive statistical analysis, Gini coefficient, and Lorenz curve computation. Additionally, the non-parametric alternative Kruskal–Wallis Test was also used. Findings revealed that 89.76% of the households’ sample were involved in forest-based activities. The annual average income from these forest-based activities was estimated at CDF 1,219,951.58 (USD 659.08) per household, contributing 32.46% to total annual household income. Other income sources share constituted 37.09%, 10.04%, 8.30%, 7.63%, 2.41%, and 2.08% from crop, livestock keeping, business activities, fishing, and non-forest environmental activities, paid employment, and other income sources, respectively. There was a significant difference between annual household income in terms of income sources (p < 0.5). Forest income constituted the second most crucial income portfolio after crop income. Bushmeat income share was higher than other forest products income share. However, the proportion of households involved in firewood extraction was substantial (80.70%). Gini coefficient and Lorenz curve analysis proved that forest income helped reduce economic inequality among the sampled households by 11%. Therefore, reducing access to forest would significantly impact rural households’ welfare and could increase income disparities. The present study provides valuable information for developing sustainable forest management policies and strategies to maintain and enhance the economic benefit of forest use without damaging biodiversity conservation.

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