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Table 1 Description of independent variables used in ordinal logistic regression model

From: Perception and attitude of pastoralists on livestock-wildlife interactions around Awash National Park, Ethiopia: implication for biodiversity conservation

Independent variables

Description of variables

Value label

Age range

CV; age range of households

1 = 20–40; 2 = 41–60; 3 = >60

Sex

BV; sex of household

1 = female; 2 = male

Family size

Continues variable; number of individuals in the household

 

Ethnic group

CV; ethnic group of the household

1 = Afar; 2 = Ittu; 3 = Kereyu

Education

CV; educational status of household

1 = elementary school; 2 = high school, 3 = illiterate, and 4 = able to read and write.

Primary source of income

BV; primary source of income to household

1 = crop production; 2 = livestock production

TLU

Continues variable; total livestock holding

 

Distance

CV; distance of household from park head quarter

1 = far; 2 = close; 3 = very close

Private grazing

BV; presence/absence of private grazing land

1 = yes; 2 = no

Communal grazing

BV; presence/absence of private grazing land

1 = yes; 2 = no

Awash National Park (ANP) grazing

BV; presence/absence of grazing in the park

1 = yes; 2 = no

Interaction with wildlife

CV; level of interaction with wildlife

1 = low; 2 = high, 3 = very high

Any benefit from ANP

BV; presence/absence of benefit from the park

1 = yes; 2 = no

Wildlife problem

BV; presence/absence of problem from wildlife

1 = yes; 2 = no

Problem type

CV; type of problem due to wildlife

1 = crop damage; 2 = livestock predation; 3 = disease transmission

Relation

BV; relation of household to the park

1 = positive; 2 = negative

Livestock problem

BV; presence/absence of problem on wildlife due to livestock

1 = yes; 2 = no

Conflict

BV; presence/absence of conflict with the park

1 = yes; 2 = no

Management park

BV; presence/absence of experience in park management

1 = yes; 2 = no

Harmony

BV; want to live in harmony with the park/not

1 = yes; 2 = no

  1. CV categorical variable, BV binary variable