Comparisons of Morone saxatilis catch variables from a research effort intended to bridge the scientific and angling communities: From the lens of environmental sustainability education

The computational thinking to learn sustainability learning progression aided in the development of a striper (Morone saxatilis) fishing project through standardized hook and line practices performed by students and researchers at a small liberal arts University in the Northeast United States. Computational thinking at a simple level supported the intersections of sustainability spheres (environmental and social) and problem-solving concepts (regulation, education and research) toward an interdisciplinary, literature-based framework. The objective of this project was the synthesis of new variables that contributed to Morone saxatilis catch efficiency through the assessment of relationships based on semi standardized angler logs in ways that are appealing and of service to both anglers and researchers as there is a need to bridge these stakeholder groups. The new variables of fish length, structural location, water body location, season, time of day, water temperature, moon phase, wind speed, wind direction and tide all showed some significance in that specific combinations resulted in higher probability of anglers catching striped bass. The findings define the overlap of variables of use to both communities and validate angler knowledge. We present new relationships of highest catch efficiency of our specific locale, including items such as larger fish tended to be caught at dusk, on bridges with low northwest wind during the fall. Implications of these findings provide a foundation of language and shared goals between recreational anglers and the scientific community particularly to support citizen science projects aimed at sustainable fisheries. Implications of bridging these communities include increased knowledge and collaboration on catch variables, appreciation for species specific research endeavors, and trust; all of which directly impact local ecological sustainability.