Cultural Knowledge of On-farm Tree Plantation in Rural Communities of Gurez Himalaya

Abstract

People’s perceptions on cultural knowledge of on-farm tree plantation have become fundamental elements of sustainable forest resource management. The study examined the people’s knowledge on cultural practices of on-farm tree plantation and their socioeconomic determinants in rural communities of Gurez Himalaya. Multistage random sampling technique was used to select 337 households from 18 sample villages for field survey. Data were collected through personal interviews administering structured interview schedule and non-participant observations. Data were analyzed using simple descriptive statistics. Results indicated that majority of the people were belonged to low socioeconomic status class as reflected by their household characteristics. Among the ten selected major cultural practices about on-farm tree plantation the ‘spot weeding’ (WMS, 2.87; priority percentage, 12.83%) was ranked 1st while ‘thinning’ (WMS= 1.31; priority percentage, 5.85%) was ranked 10th. Majority of the respondents (54.88%) had medium knowledge on cultural practices for on-farm tree plantation followed by high (23.78%) and low (21.34%) classes. Adoption of tree plantation, problem faced in tree cultivation, experience in tree cultivation, training exposure on tree cultivation and level of education had significant contribution on people’s knowledge on cultural practices about on-farm tree plantation. The findings suggested that the trainings on cultural practices about on-farm tree plantation is the crucial intervention for livelihood diversification, socioeconomic development and forest conservation; hence, need-based trainings must be planned and imparted to the individuals for improving the tree resource production, harvesting and marketing.

People's perception of the impacts of drivers of degradation on Hokersar Wetland in Kashmir Himalaya

“…To accomplish the objectives and to get meaningful results the data were analyzed by the descriptive statistics viz., frequency, percentage, average and rank order (Snedecor and Cochran 1967) [25] after coding with numerals using scoring techniques (Islam et al, 2022) [7] . The findings were calculated as weighted mean score (WMS) for each of the fringe villages using simple ranking technique.…”