User’s opinion in scientific forest management implementation in Nepal – a case study from Nawalparasi district

Figures & data

Figure 1. Map of the study area.

Table 1. Description of study sites

S.N.	Particulars	Janajaagaran CFUG	Madhyabindu CFUG	Nawadurga CFUG
1	Address (VDC-ward)	New Belhani-7	Kawasoti-16	Kawasoti-2
2	Date of handover of SciFM Plan	2073–01-12 BS (April, 2016)	2073–10-28 BS (January, 2017)	2073–10-28 BS (January, 2017)
3	Total Area (hectares)	232.87	369.23	151.41
4	Area under SciFM (hectares)	113.38	359.37	148.26
5	Household number	278	717	317
6	Total population	1522	3383	1666
7	Forest type	Mixed sal forest	Mixed sal forest	Mixed sal forest
8	Major forest species in CF	Shorea robusta, Terminalia tomentosa, Tectona grandis	Shorea robusta, Terminalia tomentosa,	Shorea robusta, Tectona grandis, Dalbergia sissoo

(Source: Field survey, 2019)

Figure 2. Methodological flow chart.

Table 2. List of final selected factors with their respective criteria

Criteria	Selected factors
Ecological	Loss of forest biodiversity
	Increased forest produce
	Increased environmental risk
	Reduced fire and risk of hazards
Social	Community development
	Corruption
	Lower user involvement
	Inadequate efficient workers
Economic	Employment opportunities (wood-based)
	Increased cost on maintenance of forest
	Increased income of user groups
	High cost on extraction
Technical	Lack of technology for harvesting
	Based on science and sustainability
	Intense silvicultural management
	Loss of traditional management system

Table 3. Random consistency index values

n	1	2	3	4	5	6	7	8	9	10
RI	0	0	0.58	0.9	1.12	1.24	1.32	1.41	1.45	1.49

Table 4. Different factors with their values (λ_max = maximum eigenvalue, CR =consistency ratio)

S.N.	Factors	Factor priority	Scaling factor	Overall priority
	Ecological criteria (${\lambda }_{max}$= 4.191), CR =0.07		0.095
A1	Loss of Forest Biodiversity	0.11		0.010
A2	Increased Forest produce	0.58		0.055
A3	Increased environmental risk	0.07		0.007
A4	Reduced fire and risk of hazards	0.24		0.023
	Social criteria (${\lambda }_{max}$=4.234), CR = 0.089		0.332
B1	Community development	0.55		0.183
B2	Corruption	0.12		0.040
B3	Low user involvement	0.28		0.093
B4	Inadequate manpower (efficient)	0.05		0.017
	Economic criteria (${\lambda }_{max}$= 4.205), CR = 0.08		0.519
C1	Employment opportunities	0.65		0.337
C2	Increased cost on maintenance of forest	0.05		0.026
C3	Increased income of user group	0.17		0.088
C4	High cost on extraction	0.13		0.067
	Technical criteria (${\lambda }_{max}$= 4.202), CR = 0.074		0.054
D1	Lack of technology for harvesting	0.07		0.004
D2	Based on science and sustainability	0.11		0.006
D3	Intense Silviculture management	0.51		0.028
D4	Loss of traditional management system	0.31		0.017

Figure 3. AHP analysis among different factors within four criteria.

Figure 4. Priority between criteria.

Figure 5. Overall priority.