Conceptual analysis uncovers shifting historical pressures in black bass fisheries, highlighting the need for genetic and conflict resolution tools.
Objectives A number of key factors are important to bass fisheries management. To adapt to a changing socioeconomic landscape and fish practices, bass fisheries managers can learn from past and current actions in an effort to incorporate new tools that are suitable for management in a changing landscape. Methods From existing generalized life cycles of fisheries coupled with the hierarchy of needs model of human development, I developed a life cycle of bass fisheries, which incorporates major trends in bass science, management, and utility over time. By visualizing past trends, one can visualize potential futures from which managers can proactively plan for management. Results The bass fisheries life cycle illustrates the change in perspective over time relative to bass utility in concert with the change in society from colonization to industrialization and modernization. Throughout this life cycle, science has had an interest in defining black bass species, with resolution affecting management. Over time, commercial interests in black bass as a food source predominated, followed by recreational interests. However, at the current stage, black bass fisheries appear to be dominated by two potentially conflicting interests: eradication–control of invasive bass populations and trophy-seeking. Using this model, I identified toolsets for black bass managers to incorporate into their toolboxes for the future. Conclusions The black bass life cycle suggests an increased emphasis in the future on managing for native populations in their natural habitat simultaneously with trophy fish management. In both cases, genetics tools will be necessary to aid their management. New population and habitat assessment tools will also likely be required beyond what has been currently typical. Additionally, human dimensions and conflict resolution skills will further enable black bass managers to work more efficiently in an increasingly dynamic landscape.
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James M. Long (2026) studied this question.
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