scholarly journals STUDY ON THE INFLUENTIAL FACTORS OF THE INVOLVEMENT OF LOCAL PEOPLE IN PARTICIPATORY FOREST MANAGEMENT: THE CASE OF WOF-WASHA DISTRICT, ETHIOPIA

2021 ◽  
pp. 102-115
Author(s):  
Demissew Wondafrash Kura ◽  
Huajing Li ◽  
Di Shang
Keyword(s):  
Logistic Regression ◽  
Forest Management ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Influential Factors ◽  
Policy Advice ◽  
Local People ◽  
Economic Factors ◽  
Participatory Forest Management ◽  
Socio Economic Factors

Participatory Forest Management (PFM) is crucial to the implementation of effective forest management and improvement in the living conditions of local communities. But local people involvement in PFM practice is affected by demographic, biophysical, institutional, and socio-economic factors. A cross-sectional survey research design was employed to collect information from 295 households (127 participants and 168 non-participants) by stratified sampling technique followed by a random sampling method. Both qualitative and quantitative data were collected from primary and secondary sources through structured interview schedules, Focused Group Discussion (FGD), Key Informant Interviews (KII) and field observation. The study employed both descriptive statistic and logistic regression model to compute the socio-economic characteristics and to identify influential factors that affect the community’s involvement in PFM practice respectively. The results of the logistic regression model revealed that household’s family size, educational status, training, benefits derived from the forest, and the number of livestock were positively affected local people’s participation in PFM activities, whereas the distance of the forest from household resident was negatively affected. Apart from demographic, biophysical, institutional, and socio-economic factors granting ownership right, improved awareness, fear of displaced from the forest area, fear of forest lose and moral obligation were enhancing factors while the expansion of agricultural land and settlement, illegal logging, weak punishment, the insufficient fund or lack of incentives, poor forest management trend, conflict of interest, and doubt on the continuity of PFM program were some influential factors that hinder local people’s participation in PFM activities. The study assisted policymakers to inform the influential factors that affect local people’s participation in the study area and formulate effective policy advice to promote PFM practice in the region. KEYWORDS: Participatory forest management; Influential factors; Household; Socio-economics; Wof-Washa District; Policy advice

scholarly journals Factors Affecting on Participatory Forest Management in Kavrepalanchok District, Nepal

2018 ◽  
Vol 41 (1-2) ◽  
pp. 1-17
Author(s):  
Yogesh Ranjit
Keyword(s):  
Household Income ◽  
Correlation Coefficients ◽  
Forest Products ◽  
Local People ◽  
Poor People ◽  
Economic Factors ◽  
Forest Protection ◽  
Factors Affecting ◽  
Participatory Forest Management ◽  
Socio Economic Factors

The paper deals with major factors affecting on people’s participation in forest protection and management activities in the Hill area of Nepal. Local people participate in forestry programmes basically for improving quality, quantity, and density of forests that ultimately help in continuously availability of the basic forest products for their livelihood and socio-economic development. The nature and level of people’s participation is highly determined by gross household income and socio-economic factors. A multiple log regression analysis used to examine the level of people’s participation as dependent variable and gross household income along with other socio-economic factors as independent variables. Correlation coefficients, coefficient of determinants, adj-coefficient of determinants, t-test, F-test and D-W test are major tools used for data analyses. The study found that as people received more forest products and other benefits from forest protection and management in short and long term, local people significantly participate in forestry programs. As women, poor people and disadvantage groups (DAGs) of the society are the prime users of forests and forest products, they have been directly involved and also gradually increasing in forestry activities in the study area.

Dynamics of ecosystem services and their driving factors in China’s Beijing-Tianjin-Hebei regional development

2020 ◽  
Author(s):  
Suxiao Li ◽  
Guangchun Lei ◽  
Xiubo Yu
Keyword(s):  
Logistic Regression ◽  
Ecosystem Services ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Arable Land ◽  
Influential Factors ◽  
Driving Factors ◽  
Multivariate Logistic Regression Model ◽  
Multivariate Logistic Regression ◽  
Urbanization Rate

<p><strong>Abstract:</strong> A comprehensive study on the dynamics of ecosystem services and their driving factors is the key prerequisite for enhancing local ecological sustainability. Based on relevant sets of big data, including spatial land data, soil data, DEM, climatic data and social-economic data, using InVEST model and multivariate logistic regression model, the study firstly assessed the spatiotemporal variation of ecosystem services for China’s Beijing-Tianjin-Hebei (Jing-Jin-Ji) region from 1990 to 2015. The study then analyzed the natural and socioeconomic factors affecting the ecosystem services. The results show that large spatial and quantitative differences exist in the supply of multiple ecosystem services, and the changes of different types of ecosystem services are driven by different factors. For water yield, the areas of arable land, wetland and built-up land and precipitation are the most influential factors; The areas of arable land, precipitation, temperature, altitude, urbanization rate and amount of nutrient applied per unit area are determinants of changes in nutrient retention; The areas of grassland and forest, temperature, altitude, GDP per capita and urbanization rate affect the soil retention to great extent; for carbon storage, its key influential factors are the areas of different land use types and urbanization rate. The study can facilitate identification of where and how to enhance multiple ecosystem services.</p><p><strong>Keywords:</strong> dynamics of ecosystem services, driving factors, InVEST, multivariate logistic regression model</p>

scholarly journals Work absence and multimorbidity in Portugal: results from the 1st National Health Examination Survey

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
J Matos ◽  
C Matias Dias ◽  
A Félix
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Chronic Diseases ◽  
National Health ◽  
Logistic Regression Model ◽  
Health Examination ◽  
Work Absence ◽  
Health Examination Survey ◽  
Absence From Work ◽  
The Impact

Abstract Background Studies on the impact of patients with multimorbidity in the absence of work indicate that the number and type of chronic diseases may increase absenteeism and that the risk of absence from work is higher in people with two or more chronic diseases. This study analyzed the association between multimorbidity and greater frequency and duration of work absence in the portuguese population between the ages of 25 and 65 during 2015. Methods This is an epidemiological, observational, cross-sectional study with an analytical component that has its source of information from the 1st National Health Examination Survey. The study analyzed univariate, bivariate and multivariate variables under study. A multivariate logistic regression model was constructed. Results The prevalence of absenteeism was 55,1%. Education showed an association with absence of work (p = 0,0157), as well as professional activity (p = 0,0086). It wasn't possible to verify association between the presence of chronic diseases (p = 0,9358) or the presence of multimorbidity (p = 0,4309) with absence of work. The prevalence of multimorbidity was 31,8%. There was association between age (p < 0,0001), education (p < 0,001) and yield (p = 0,0009) and multimorbidity. There is no increase in the number of days of absence from work due to the increase in the number of chronic diseases. In the optimized logistic regression model the only variables that demonstrated association with the variable labor absence were age (p = 0,0391) and education (0,0089). Conclusions The scientific evidence generated will contribute to the current discussion on the need for the health and social security system to develop policies to patients with multimorbidity. Key messages The prevalence of absenteeism and multimorbidity in Portugal was respectively 55,1% and 31,8%. In the optimized model age and education demonstrated association with the variable labor absence.

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