
Political affiliation predicts public attitudes toward gray wolf ( Canis lupus ) conservation and management
Author(s) -
Eeden Lily M.,
Rabotyagov Sergey,
Kather Morgan,
Bogezi Carol,
Wirsing Aaron J.,
Marzluff John
Publication year - 2021
Publication title -
conservation science and practice
Language(s) - English
Resource type - Journals
ISSN - 2578-4854
DOI - 10.1111/csp2.387
Subject(s) - social psychology , canis , structural equation modeling , framing (construction) , politics , ideology , gray wolf , latent class model , public opinion , psychology , latent variable , wildlife , political science , geography , ecology , statistics , mathematics , archaeology , artificial intelligence , computer science , law , biology
Controversial wildlife conservation and management, such as that involving gray wolves ( Canis lupus ), can be symbolic of broader social conflicts. We conducted an online survey ( N = 420) to determine factors shaping public attitudes toward wolf management among residents of Washington state, United States. We used 12 Likert‐type statements to form a single latent construct that represented attitudes toward wolf management in a multi‐use landscape and fit a simple structural equation model to identify demographic predictor variables. The strongest predictors were that voters self‐identifying as Democrats were more likely to hold positive attitudes toward wolves and management to conserve them than those identifying with other political parties (standardized latent variable coefficient = 0.585) and women were more likely than men to hold negative attitudes (−0.459). Older respondents were also more likely to hold negative attitudes (−0.015) and respondents who tried to stay informed about wolf issues were more likely to hold positive attitudes (0.172). Perceived links between wildlife management issues and political ideology may exacerbate community disagreements, hindering coexistence between rural livelihoods and wolves. We recommend appropriate framing and messengers to account for this linkage and improve communication of policy and promote science‐based decision‐making.