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Dedicated to the social and political aspects–the so-called "human dimensions"–of wildlife management
My colleagues and I tackled this question in a recent article published in the journal, Human Dimensions of Wildlife. Unfortunately, data do not exist that allow us to answer this question in a conventional manner (i.e., via survey). Consequently, we chose to conduct a content analysis of the US and Canadian print news media. I have made a pre-publication draft of the article available here:
What follows is a brief summary of this study’s findings…
Several prior studies attempted to address the same central research questions with mixed findings. For example, Kellert (1999) found evidence for a slight increase in “affection” for wolves in Minnesota over a 15-year time frame while, in contrast, Enck and Brown (2002) found a substantial decline in support for wolf reintroduction in the Adirondacks. Still other research found no measurable change in attitudes toward wolves over time (Bruskotter et al. 2007; Williams et al. 2002).
We used computer-aided content analysis to assess to code nearly 30,000 paragraphs that appeared in more than 6,000 stories about wolves published in the US and Canada from 1999 to 2008. We only included news media sources that published continuously throughout the time period of interest in order to rule out the possibility that our results would be biased by new media sources.
Coding. We developed a conceptual framework that classified paragraphs into one of five types of evaluative statements. Each evaluation was also classified as either positive or negative with respect to wolves; thus, there were 10 concepts coded in total. The goal of our approach was to “capture” any evaluative statements about wolves or wolf management.
Roughly 72% of all expressions we coded over the 10 year time frame were negative. The most prevalent type of expression was the belief that “wolves negatively impact human activities” which accounted for roughly 31% of all of the paragraphs we coded. The second most prevalent expression was the judgment that “wolves should be killed or controlled” which accounted for roughly 28% of all of the paragraphs we coded. The most prevalent positive expression was that “wolves should be protected”, which accounted for 15% of all paragraphs coded.
Regression analyses. Next, we used linear regression in order to determine if there were significant trends within each of the concept-categories. Trends were determined by calculating the percentage of paragraphs per year accounted for by each concept, and fitting a line through the 10-year trend. Results show that three of 10 concepts: (a) there was a significant decrease in the percentage of paragraphs expressing the idea that “wolves positively impact human activities” (B = -.18, p = .01), (b) a significant decrease in the percentage of paragraphs expressing the idea that “wolves should be protected (B = -.45, p = .04), and a significant increase in the percentage of paragraphs expressing the idea that “wolves negatively impact ecosystems” (B = .17, p = .05). We then created a summary index where each concept was coded as either positive or negative. Regressing a line through each year of data suggested in increase in the percent of negative news coverage about wolves in the US and Canada (B = .72, p = .04).
Are attitudes toward wolves changing
This is a complicated question which our data only begin to address. Our data clearly exhibit a negative trend in news coverage concerning wolves; however, news media coverage is merely a rough proxy for measuring actual attitudes. In this respect, our data are suggestive of a change. However, whether one views the news media as a cause or consequence of public opinion (or more realistically, both), this trend does not bode well for wolves.
A second problem with these analyses is that the overall trend may obscure regional variation; that is, it is possible that, in some places attitudes are becoming more negative while in others they are becoming more positive. We examined this issue more closely in subsequent analyses…[stay tuned for an update!]