Rebeka Sultana
Rural Development Academy (RDA), Bogura, Bangladesh.
Md. Shafiqul Bari
Hajee Mohammad Danesh Science and Technology University, Dinajpur, Bangladesh.
Agroforestry; Livelihood; River basins
Kazipur Upazilla under Sirajgong district and Shariakandi Upazilla under Bogura district
Socio-economic and Policy
Socio-economic status
The study was conducted at four Upazillas covering four districts: two from Jamuna river basin (Kazipur Upazilla under Sirajgong district and Shariakandi Upazilla under Bogura district) and the other two from Teesta basin (Kaunia Upazilla under Rangpur district) and Dimla Upazilla under Nilphamari district. Preliminary information on agroforestry in the study area was collected from the district Department of Agricultural Extension office. Randomly selected two unions from each of the four Upazilla and 15 farmers from each union. Thus 30 farmers were surveyed from each of the four Upazillas. A total of 120 respondents were included in the survey of which 30.83 percent are females and 69.17 percent are males. Data on annual income from crops and horticultural produces, farm production costs, the monetary value of agroforestry products and services, livestock size, and household size are collected from sampled households in the study areas. A mixed approach of data collection methods was used for the study. The questionnaire was pre-tested before the final interviews. The interviews were conducted with the head of households. Species composition, including trees, shrubs and agricultural crops, of each selected cropland, were recorded through direct agroforestry plot visits with the assistance of the farmers. Farmers replied to open questions about the source of planting materials, tending operations, nutrient supply and plant protection measures carried out in their croplands, which were also be recorded during the field visit. Secondary information was also being collected from the internet, DAE reports, statistical yearbooks, and other sources. These helped to cross-check the data collection during the direct interviews. Interviews with the farmers were conducted at a convenient time for the farmers, and they responded freely to each topic. Livelihood improvement status of the farmers in char areas was measured by computing a composite livelihood improvement score based on each of the five components of ‘livelihood asset pentagon: (i) human capital (ii) social capital (iii) financial capital (iv) physical capital and (v) natural capital. The capitals were measured against fifteen statements. Each of the statements was put against 4 point rating scale: highly increased, increased, slightly increased, and no change and score given as 4, 3, 2 and 1, respectively for positive statements and the scoring technique were reversed for the negative statements. The total scores for each of the livelihood capital could range from 15 to 60, where 15 indicated no improvement and 60 indicated high improvement regarding the concerned livelihood capital. The overall score for livelihood improvement was computed by adding the scores obtained by all of the capitals of the livelihood asset pentagon. Thus, total scores for overall livelihood improvement status could vary from 60 to 240, where 60 indicated no improvement and 240 indicated very high improvement of overall livelihood status of the farmers through practicing agroforestry.
Data were arranged in MS Excel. Age, family size, and farming experience of the farmers were categorized based on an overall distribution of the respective data while educational qualifications of the farmers were categorized based on years of schooling. A four-point scale was used for computing the extent of adoption to homestead agroforestry practices. Weights of responses against the applicable ones of the 25 practices were assigned in the following way. A score of 3, 2, 1 and 0 was assigned for high use, medium use, low use and no use respectively. The weights of responses of all homestead agroforestry practices were added together to obtain the extent of use of homestead agroforestry practice and the score of the respondents could range from 0 to 75 where 0 indicates no use and 75 indicating high use of agroforestry practices. Responses on types of agroforestry systems practiced and the purpose of AGF was expressed as a percentage. In addition, the extent of livelihood improvement of the farmers practicing agroforestry was measured following the sustainable livelihoods (SL) framework. A number of possible problems were selected to measure the extent of problems faced by farmers in practicing agroforestry. The extent of problems faced by the farmers was recorded on a four-point Likert scale. In a similar way, the responses of farmers were taken to evaluate the extent of livelihood improvement through DFID’s livelihood (Human, Social, Physical, Natural, and Financial) capitals. The Problem Facing Index (PFI) and Livelihood Improvement Index (LII) were then calculated based on the individual and overall responses of the farmers on each statement of problems and livelihood capitals. Conversely, for the LII, higher values were indicating livelihood improvement and smaller values had lower livelihood improvement. Statistical analysis (multiple response and descriptive statistics) was performed using SPSS statistical software.
Asian Journal of Research in Agriculture and Forestry- 7(1): 10-27, 2021
Journal