Richard K. Mendako

Environmental regulatory instruments are key to achieving synergy between high-quality economic development and ecological civilization construction. This paper measures the green overall factor productivity of the forestry in the Yangtze River Economic Belt by using the super-efficient nonexpected output SBM-ML index model. Additionally, it investigates the environmental regulation’s impact on forestry’s overall green factor productivity by using the conventional panel regression and panel smooth transformation model. The model was based on the relevant data obtained from eleven provinces along the Yangtze River Economic Belt in China from 2006 to 2021. This study concludes that command-and-control regulation of the environment and public engagement with environmental regulation can significantly promote the forestry green overall factor productivity in the Yangtze River Economic Belt, and the environmental regulation’s effects on the forestry green overall efficiency in the economic region of the Yangtze River are regionally and temporally heterogeneous. The command-and-control environmental regulation also needs to exceed a certain level of regulatory coercion to promote the forestry green overall factor productivity positively. The effects of market-incentive environmental regulation were more pronounced with the increase in the regulatory intensity. When the regulation intensity surpasses the threshold, the public participation form of environmental regulation has a depressing impact on the forestry green overall factor output. To promote the development of the forestry industry in the Yangtze River Economic Zone, it is therefore necessary to strengthen the coordination of different environmental regulations, implement measures in each region, build a market-oriented green innovation system, and promote the structuralization and upgrading of the forestry industry.

(1) This study aims to solve the problems of sustainable development in the forestry tertiary industry, to address the imbalanced state of natural environmental resources and the forestry industry, to improve ecological and environmental management, and to prepare for carbon peak and carbon neutral goals. (2) Using panel data from forest park tourism in 30 provinces and cities in China from 2010 to 2019, the DEA game cross-efficiency model is adapted to evaluate its tourism eco-efficiency, and the primary factors affecting forestry tourism eco-efficiency are selected; additionally, a panel tobit regression model is established for analysis to find policy entry points for enhancing forestry tourism eco-efficiency through empirical analysis. (3) The results show that transportation network construction and tourism input have a negative impact on the eco-efficiency of forestry tourism in China, while ecological construction, economic level, and environmental regulations are positively correlated with the eco-efficiency of forestry tourism. (4) Therefore, suggestions are made to optimize the allocation of tourism resource inputs and adopt appropriate development models, and to promote the interactive development of forestry industries.

Rural households depend on forest resources for cash and subsistence needs. Thus, forests represent a valuable natural capital for the rural economy, particularly in developing countries. However, depending on various factors, there are dissimilarities in the rural livelihoods’ reliance on forests. Therefore, this study attempted to determine and characterize the level of forest dependence and identify the demographic and socioeconomic factors influencing the households’ dependence on forests in the Rubi-Tele Hunting Domain (RTHD)/Democratic Republic of the Congo (DR Congo). Demographic and socioeconomic data of forest dependents and other qualitative information were collected through structured household-level surveys, focus group discussions, and key informant interviews. Descriptive statistical analysis, Kruskal–Wallis Test, χ² test of independence, and binary logistic regression model were used for data analysis. The findings revealed that the forest dependence index varied from 0.01 to 1 (Mean = 0.46, SD = 0.30). The distribution of forest-dependent households by wealth status (income tercile) and level of forest dependence differs significantly. Logistic regression revealed that household size and non-forest income were significant determinants of forest dependence and had the theoretically expected signs. The household size was in a positive association with forest dependence. Large families tended to depend more on forest resources. On the other hand, the non-forest income was inversely related to forest dependence, implying that forest-dependent households with non-forest income sources were less dependent on forest resources extraction. Other selected variables were not statistically significant while showing positive and negative associations with the reliance on forests. Achieving the balance between forest dependence and conservation requires promoting incentive policies to diversify livelihood opportunities and environmental education.

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.

Forests across the world are considered to be a huge socio-economic and environmental benefit to host and adjacent communities. This study focuses on assessing the impacts of fuelwood and timber consumption on the livelihood of households in the Baltistan region in Pakistan. Primary and secondary sources of data were employed for the study. The primary sources involved the use of questionnaire survey and interview while the secondary sources involved the use of documented information in textbooks and internet materials. The study revealed that 82% of the people within the region were involved in agricultural activities, 71% depended on the extraction of forest resources for their livelihood, while 18% depended on off-farm activities for their livelihood. The study also observed that among the number that depended on forest resources for their livelihood, 59% were involved in the extraction of non-timber forest products while 41% were involved in the extraction of timber forest resources. The study further revealed that there was no significant difference in the level of benefits from the forest across the seven districts under investigation with a chi square value. The volume of forest products extraction was found to be high closest to the forest and to be low with increasing distance from the communities. The major benefits from the forest range were due to employment that increases the individual and family income. Forest also helps to control erosion and enhances aesthetic beautification and temperature regulation. The research suggests that the policy makers must provide a sustainable solution to reduce the overexploitation of the forest resources by providing better alternative earning resources to the resident communities.