Last Updated 03 Jan 2023

Approaches, Theories, And Management Issues Of Feral Swine And Invasive Species

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important tool for communicating about feral swine issues and building greater public support for management strategies. Social identity theory is a relevant theoretical approach to use in review because it allows for exploration of tolerance toward management issues of invasive species within various groups.

Theoretical Approach

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The cognitive hierarchy framework lays out a theoretical and conceptual approach to understanding human behavior in the context of wildlife management (Manfredo, 2008). The framework includes psychological aspects like values, emotions, attitudes and beliefs, and norms (Figure 3). The social identity theory model (Figure 4) includes self-identity leading to social identity and social categorization. The two theories listed will be explained more in depth within this review.  Attitude Theory

Attitudes by Fazio (Fazio, Chen, McDonel, & Sherman, 1982) are defined as “an association, in memory, of an evaluation with an object’’ (p. 341). Attitudes are one of the most studied theories in Human Dimensions research because they’re the basis to predict and understand human behavior, as well as to understand an individual’s thought processes (Don Carlos, Bright, Teel, & Vaske, 2009). It’s imperative to be as specific as possible to understand attitudes, therefore researchers break them down contextually by topics of interest, specifically by category (Ajzen & Fishbein, 1980). Attitudes are evaluated categorically by positive or negative sentiment toward a specific object (Krosnick & Petty, 1995; Manfredo, 2008; Vaske & Donnelly, 1999). The stronger one’s attitude toward something is, the more likely it will guide someone’s behavior and create self-awareness toward the evaluation of the subject – directly linking attitiudes and how they tranfers over to an individual’s behavior. (Manfredo, 2008 & Figure 3).

The evaluation of a subject or statement can range from strongly agree to strongly disagree, positive and negative respectively. Attitude strength can then be used to evaluate how the public will vote on a management issue (Bright, 1997) which can lead to new management for a spepecific species. As displayed in the cognitive hierarchy above, values are the basis to attitudes yet are more transient and welcoming to change. Therefore, where there are areas of conflict within a community, if general attitudes are well understood there may be opportunity to mitigate context-specific conflicts, like non-native feral swine management issues. The acceptability of management strategies in communities with human-wildlife conflicts are highly influenced by attitudes (Whittaker, Vaske, & Manfredo, 2006)

The biggest impact of evaluating public attitudes is the ability to communicate management findings to the general public, identify areas of misconceptions, recognize areas of common beliefs between conflicting factions, and public preference may be the best management route to take regardless of agency recommendations (Manfredo, 2008). For example, in a study focused on human-black bear conflict, Don Carlos (2009) and colleagues examined a community’s attitudes toward black bears in west central Colorado. They noted that long-term biological and social factors were needed to ensure effective human-black bear management. Overall, people’s attitudes toward bears were positive, yet beliefs varied among different groups of people. Social identity theory could have played a role in identifying what types of people had negative views toward bears and the tolerance surrounding bear management, in turn allowing for more education and outreach within those diverse faction.

Tolerance is “the ability of an individual to bear losses caused by wildlife.” which have direct implications if an individual’s attitude will be positive or negative toward wildlife (Gofoi, 2018, pg.214).  Occasionally, attitudes do not predict behavior. In some situations, if an individual is not thinking deliberately about attitude objects, such that it will not affect behavior. The model predicting how attitudes influence behavior without deliberate thinking is called MODE. MODE represents motivation and opportunity and are determinants of attitude-behavior influences in an individual (Manfredo, 2008). The examination of attitudes is specific to individuals; however, social identity theory can be used more broadly to investigate how individual views themselves within a social group setting, drawing on another piece of the cognitive hierarchy – norms.

Social Identity Theory

Social identity theory (SIT) as described by Tajfel (Tajfel, 2010) is “part of the individuals’ self-concept which derives from their knowledge of their membership of a social group (or groups) together with the value and emotional significance attached to that membership” (pg. 2). SIT originated to examine intergroup relations like race and gender, yet the theory has branched out to inform other types of research (Tajfel, 2010). Self-concept of an individual consists of multiple well-defined group identities which vary in importance in certain situations (Hogg, 1996). The underlying cognitive assessment behind social identity is the idea of categorization, like that of attitudes. Categorization defined by Hogg (1996) is a process by which individuals assign people to relevant categories. Assessments can be self-identified and involved two assumptions: a). a person or contextual item of interest possess characteristics of the category and b). Impressions are made rapidly and efficiently. These groups and organizational memberships can be used to analyze social media platforms like Twitter or Facebook of specific factions by parceling people into categorizes to better understand intergroup boundaries, stereotypes, and perceptions/actions (Jones & Volpe, 2011; Ross-Winslow, 2013).

SIT is generally a new and innovative theoretical approach in which specific types of people can be targeted to fill areas of misconception between individuals in intergroup situations such that it reduces conflict and provide new unique outreach techniques and approaches for wildlife management. Assessing social identity of organizational members using social media can predict tolerance of various management options (NAUGHTON‐TREVES, Grossberg, & Treves, 2003). For example, one study showed that people who had deeply rooted social identities correlated to how tolerant they were of wolf opposition or support (NAUGHTON‐TREVES et al., 2003). People who identified as female, young and middle-aged, and wealthy urban residents supported wolf reintroduction. People who opposed wolves and their recovery were mostly ranchers and farmers that lived within range of wolf populations (Bright & Manfredo, 1996; NAUGHTON‐TREVES et al., 2003). Extrapolating the social identity categorically allowed multiple conclusions to be drawn including various types of tolerance preferences toward wolves and wolf reintroductions. The same concept can be applied to feral swine management techniques including the acceptance of lethal and non-lethal methods.

By using both the frameworks described above, attitude theory and SIT, researchers and wildlife managers will be able to better predict public behaviors and tolerance toward management actions and create uniquely tailored outreach approaches that benefit the community, respectively.

The Role of Social Media

Social media are “forms of electronic communication (such as websites for social networking and microblogging) through which users create online communities to share information, ideas, personal messages, and other content (such as videos)” (Merriam-Webster Dictionary, 2018). Social media platforms include Twitter, Facebook, Instagram, YouTube, Flickr and Pinterest. Content from social media sites can be used to predict attitudes, behaviors and tolerance of a subject and show real-time opinions. Specifically, social media and content analysis have been used broadly over various disciplines to determine multiple facets and objectives for researchers such as policy information, public health, disease outbreaks, to increase business value, and to communicate the importance of conservation science to professionals (Bombaci, Farr, Gallo, Mangan, Stinson, Kaushik, & Pejchar,2016; Chew & Eysenbach, 2010; Culnan, McHugh, & Zubillaga, 2010; Merchant, Elmer, & Lurie, 2011; Paul & Dredze, 2011). Social media posts contain a collective amount of information that can be extrapolated in many ways to include the utility of spatial and temporal metadata (Di Minin, Tenkanen, & Toivonen, 2015; Longley, Adnan, & Lansley, 2015).

A Social media post can include when and where the picture or tweet was taken/written, respectively. A unique aspect of Social Media data is that it provides personal information about the individual via their profiles, allowing a more indepth understanding of who each individual is and what’s important to them. For example, Twitter can be used to communicate science and is a subject area where Social media can be of significant use within wildlife management of invasive species. Twitter allows for a maximum of 140-character tweet, which encourages the user to summarize ideas and thoughts into short yet explicit posts. Explicit communication has the potential to reduce any misconceptions between the public and state and government wildlife agencies. Twitter also allows the user to attach a photo or link within the tweet creating an added benefit for the work produced, which arguably makes a greater impact for conservation science in the long run and increases the amount in which an article is cited (Parsons, Shiffman, Darling, Spillman, & Wright, 2014). Social media can be another way to reduce self-reporting errors from traditional methods used in social science such as surveys and it can be a way to validate data previously collected (Di Minin et al., 2015).

Analyzing such large datasets from social media platform can be cumbersum, but fortunately there are wide variety of pre-made analysis packages and tools created to analyze data, such as TwitteR (R Package), Gnip, and Nvivo (Di Minin et al., 2015; Gibbs, 2002). One common tool used in the social science realm to analyze datasets is the Social Media Content Analysis. Content analysis defined by Riff (2014) and colleagues, includes collecting content data, applying categorical rules that measure non-mutually exclusive differences between data subjects. The objective of categorically organizing data sets is to discover patterns or characteristics between relationships of the content. If the patterns within the dataset are reliable, the validity of the study can be justified. How attitudes and tolerance are identified in social science reearch, is the same type of method used in content media analysis, making it a valuable source of comparison for researchers. For example, in Human Dimensions research, social media-generated content is analyzed by measuring sentiment regarding a wildlife management related issue such as feral swine or reintroduction of a species coupled by categorical statements or comments on social media platforms. Social media data can be analyzed by comment, tweets or posts generated by the social media user.

Scientists can understand a variety of objectives based on the vast variety of data that can then be incorporated into management decisions and programs. Specifically, analysis of the data can formulate what type of management actions may be acceptable. Several successful studies, such as the one by Barry (2014), showcase how social media has been useful in understanding the public’s values and perceptions of recreationalist toward cows and grazing. Barry (2014) notes that most research executed through surveys or public comments tend to lean toward negative feedback. Managers can identify which comments lead toward negative perceptions or attitudes of the topic at interests, and then educate on that specific topic.

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