A Case Study of the Quality and Availability of Online Data about Feral Swine (Sus scrofa) population in the United States

I began my literature review by examining publicly available resources on feral swine populations across the United States. My search focused on government agencies, university websites, and specialized hunting resources that provide population data.

Online literature reveals a lack of methodological consistency in how feral swine populations are monitored and reported. While the biological and ecological dimensions of the feral swine lifecycle have received substantial scholarly attention, considerably less research has focused on the methodological challenges inherent in population monitoring and the resulting data inconsistencies.

Studies have attempted to quantify feral swine populations at state or regional levels using various methodologies, including camera trapping (Massei et al., 2018), mark-recapture techniques (Hanson et al., 2008), and aerial surveys (Campbell et al., 2010). However, these approaches vary significantly in their implementation, accuracy, and geographic coverage. The resulting heterogeneity in population estimation methodologies must create substantial challenges for policymakers and wildlife managers attempting to allocate resources effectively or evaluate management success (or failure) across jurisdictional boundaries.[4,5,6]

Federal and State agencies vary dramatically in their approaches, with some providing detailed population estimates (Texas, Florida) while others offer only vague qualitative assessments (North Carolina, Oklahoma). Lack of consistent standards to determine how population data for feral swine should be collected, reported, and utilized across different states and agencies impedes the development of coordinated management strategies and prevents accurate assessment of population trends at regional or national scales. It also prevents researchers from effectively combining their data and perhaps reaching useful conclusions.

This review identified a significant gap in the literature regarding standardized methodologies for feral swine population assessment across jurisdictional boundaries, highlighting the need for improved coordination between researchers and management agencies, and opportunities to expand the most successful of the approaches that I found.

Data for this case study was collected online, from websites that are freely available to the general public. The goal was to be inclusive in my approach, and determine if useful data about feral swine (Sus scrofa (feral type) Linnaeus) populations across the United States exists online, or if the means to create such data could be developed. The selection of this invasive species as an analytical object was especially interesting because their population exceeds 6 million individuals and causes extensive ecological and economic disruption, but approaches to data gathering and study of the subject by different knowledge systems are inconsistent and often ineffective.

The methodological approach was informed by Collins' conceptualization of evidential cultures as socially-constructed frameworks governing what counts as legitimate knowledge. Feral swine data provides a particularly illuminating case for such analysis precisely because it exists at the intersection of multiple institutional domains—state wildlife management, academic research, agricultural policy, and recreational hunting—each with distinct epistemic commitments and data practices. This diversity of approaches creates natural variation in evidential standards that can be analyzed and compared.

I systematically reviewed publicly-available online resources produced by state wildlife agencies, research universities, and specialized hunting resources with online records of feral swine populations. For each source, I reviewed the type of population data provided, the methodology used for estimation (if disclosed), the frequency of updates, and the accessibility of raw data- testing the hypothesis that democratized access to knowledge might reveal alternative evidential regimes outside traditional mechanisms. I looked at the content of population estimates, and also the material practices through which such estimates were generated, including: the explicit and implicit methodologies deployed for population assessment, the technical and social infrastructures governing data accessibility, and the rhetorical framing of certainty and uncertainty within different knowledge communities.

This investigation reveals not merely technical inconsistencies but a fundamental fragmentation in the evidential cultures that shape our collective knowledge of feral swine populations across the United States. This epistemic fragmentation manifests in what Collins would recognize as competing "truth regimes"—different institutional frameworks that establish incompatible standards for what constitutes valid knowledge. The consequence is not simply a lack of standardization but a more profound inability to establish a coherent collective understanding of a significant ecological phenomenon.

When examined through Collins' conceptual framework, the current landscape reveals a productive tension between closed evidential cultures (typified by state wildlife agencies that restrict access to raw data, or designate the importance of data differently) and more open frameworks (represented by hunting organizations and citizen science platforms that prioritize geographic coverage and observational volume). These are not merely different approaches to the same epistemic project but represent fundamentally different conceptions of how knowledge about ecological systems should be constituted and validated. In practical terms, this epistemic fragmentation helps explain why coordinated management efforts have struggled despite decades of institutional attention—without shared evidential standards, collective action becomes unsustainable.

While information is readily accessible on the internet, its superabundance can cause valuable insights to be buried beneath mountains of low-quality content. Algorithms that point researchers to the information that is most popular might miss the information that is most valid. To address this issue, I propose developing expert-curated lists that connect users to reliable information vetted by specialists in the field. Academic institutions could play a crucial role in this epistemic architecture, allowing students to make meaningful contributions to ongoing research initiatives that continue beyond their academic tenure. Eventually, these efforts would accumulate into comprehensive databases housing years of consistently formatted data—something we currently lack in today's information ecosystem.

Future research should focus not merely on standardizing technical protocols but on fostering what Collins terms "interactional expertise"—the capacity to move productively between different knowledge communities without requiring their complete integration. The University of Georgia's EDDMapS exemplifies this approach, creating mechanisms for knowledge exchange while preserving the distinct contributions of different evidential cultures.

Universities are uniquely positioned to function as epistemic mediators in this process, possessing both the scientific authority to validate methodological approaches and the institutional capacity to engage diverse stakeholder communities. By creating platforms for interdisciplinary collaboration that explicitly acknowledge rather than suppress evidential differences, academic institutions could foster a more robust collective understanding of complex ecological phenomena like feral swine populations—simultaneously accommodating the scientific rigor privileged by academic research, the geographical coverage enabled by citizen observation, and the practical knowledge embedded in hunting and agricultural communities.