DOI: 10.5061/dryad.wm37pvmhr
title: Wolves are back: Sociopolitical identity and opinions on management of Canis lupus

description: In 2010 an interdisciplinary team of social and natural scientists began a
 project to study society–environment interactions in northeast Oregon. At
 first, the Communities and Forests in Oregon (CAFOR) project focused on
 Baker, Union and Wallowa Counties. Subsequently the project’s scope
 expanded to cover Crook, Grant, Umatilla and Wheeler
 Counties. One part of the CAFOR research involved a series of
 telephone surveys carried out in four stages over 2011 to 2018. The
 surveys employed consistent methods with landline or cell telephone
 interviews of independent random samples conducted by trained personnel
 from the Survey Center of the University of New Hampshire. Questions
 covered a range of topics related to environment and community change.
 Some questions were repeated with identical wording on two, three or four
 surveys, watching for continuity and change in public opinion. The survey
 design involved stratification with oversampling of smaller-population
 counties, and in some cases also of forest landowners. To adjust for both
 design and response bias, probability weights (inverse of the probability
 of selection) are applied for all graphs and statistical analyses in this
 paper. Effects of this weighting on variables of interest here are not
 large, but make the results more representative with respect to county
 populations and age/sex distributions. Geographic coverage varied
 across the four surveys. The initial stage in 2011 sampled residents from
 three counties: Baker, Union and Wallowa. Subsequently, the 2014 and 2015
 surveys expanded to seven contiguous counties, including those three. The
 project’s final survey in 2018 refocused on the original three. A total of
 5,085 interviews had been conducted, 3,782 of them involving residents of
 Baker, Union or Wallowa County. To maintain comparability, our analysis in
 this dataset concerns only that three-county subset, although findings
 remain broadly similar in analyses using the complete seven-county
 dataset.
description: <b>Survey Questions.</b>  The return of wolves has
 been controversial in this region, particularly with ranchers and hunters.
 To measure views among the general public, we asked on all four CAFOR
 surveys:  Which of the following four statements about wolves in eastern
 Oregon comes closest to your personal beliefs?”. Respondents could choose
 eliminating wolves from the region, limited hunting, or no hunting with or
 without compensation for livestock losses. Telephone interviewers rotated
 the order of these response choices. The simple, un-nuanced choices by no
 means exhaust the possible views on wolf management, but only three
 percent of our respondents were unable to choose between them. As will be
 seen, responses were highly structured in terms of individual
 characteristics and location, and highly replicable across survey
 years—suggesting high validity despite or because of the question’s
 simplicity. <b>Data Selection</b>. Four
 CAFOR surveys conducted over 2011 to 2018 interviewed a combined total of
 more than 5,000 northeast Oregon respondents. The surveys employed similar
 methods and asked many of the same questions, so in principle they could
 be integrated into one dataset. In practice, however, secondary variations
 in questions asked or geographic coverage restrict us to subsets where
 these factors are consistent, for purposes of a particular analysis. Three
 such subsets are employed in this paper. (1) Interviews from all four
 survey years (2011, 2014, 2015, 2018; <i>n</i> = 3,782) from
 Baker, Union and Wallowa counties. A simple 3-party political question was
 asked in 2011; all later surveys asked two political questions, permitting
 construction of a 4-party indicator as described by Hamilton &
 Saito (2015), but to maintain consistency with 2011 we use only the
 3-party version for analysis of this subset. (2) Interviews from 2018
 only, also in Baker, Union and Wallowa counties (<i>n</i> =
 1,097). The 2018 survey for the first time asked about political
 identification of the respondent’s friends, so its effects are tested only
 with these data. The more detailed 4-party indicator also can be used for
 this analysis; in terms of respondents, the 2018 survey comprises a subset
 of the 2011–2018 dataset. (3) About 1,300 respondents in four additional
 counties (Crook, Grant, Umatilla and Wheeler) were interviewed in 2014 or
 2015 only. These geographically distinct data and non-overlapping
 interviews are not mixed into the main three-county analyses here, but
 provide an independent replication for several if its key findings, as
 mentioned in the discussion.
 <b>Statistical Methods.</b> Statistical analyses were
 performed using Stata version 16, applying probability weights
 consistently for percentages, graphs and modeling. Models shown involve
 weighted logit regression, a method appropriate for binary dependent
 variables such as elimination/no elimination of wolves. The original
 <i>wolves</i> survey question offered respondents four
 choices, so an alternative approach could use multinomial logit
 regression. The corresponding multinomial models, however, are three times
 more complicated (i.e., three parameters are estimated for each predictor
 variables, against a reference value), while reaching substantially the
 same conclusions. Other coding choices specified in Table 2, for use in
 modeling, similarly provide the most clear, replicable and robust results.
 Political party is treated as an ordinal predictor due to its consistently
 monotonic and close to linear effects on environmental topics, in the
 present datasets and many others (for examples see Hamilton and Saito
 2015; Hamilton et al. 2018a, 2018b).  
description: The Communities and Forests in Oregon (CAFOR) project is
 supported by the Agricultural and Food Research Initiative, U.S.
 Department of Agriculture (2014-68002-21782 and 2010-67023-21705). Any
 opinions, findings, and conclusions or recommendations derived from these
 data are those of the authors and do not necessarily reflect the views of
 the US Department of Agriculture. For further questions about the data,
 please contact authors.