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Fish and wildlife agencies produce a bounty of information aimed at the public. Under the right circumstances, that information can be compiled into scientifically useful data to complement full scientific studies. This poster describes some preliminary results from a project to compile mentions of gamefish species, locations, and sizes throughout the Long Island Sound and surrounding waters from the Weekly Fishing Report (2006, 2008-2018) and the Trophy Fish Report (2009-2017), both produced by the Connecticut Dept. of Energy and Environmental Protection. The dataset consists of more than 20,000 entries from the reports collected weekly by DEEP employees from tackle shops and charter companies. The current portion of the analysis is to determine the characteristics of the dataset, such as entry types, species counts, and some general trends. Presented at the 2019 NEAFWA Conference in Groton, CT and the 2019 CSCU Faculty Research Conference at SCSU in New Haven, CT.
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Dataset of gamefish occurrences as compiled from the Connecticut Fishing Report (2006-2018) and Trophy Fish Report (2009-2018), both published by the Connecticut Department of Energy and Environmental Protection. Compiled as thesis project by Rebecca Hedreen for a Masters of Science in Biology from Southern Connecticut State University, with advisor Dr. Sean Grace.
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A Thesis Submitted to the School of Graduate and Professional Studies in Partial Fulfillment of the Requirements for the Degree of Master of Science in Biology Southern Connecticut State University New Haven, Connecticut December 2021 Abstract: In order to properly assess current ecological conditions, we need long-term ecological data. Historical ecology focuses on that long term, including the need to synthesize data from diverse sources. In the Long Island Sound, the Connecticut Department of Energy and Environmental Protection has been collecting data for both scientific and recreational purposes for decades, but the format of the recreational data (narrative) is not suitable for scientific analysis. This project is to collate and annotate game fish occurrence data from the Fishing Report newsletters put out by DEEP every week during the fishing season and the DEEP Trophy Fish annual reports, over a 12-year period. Species, location, and measurement data (as available) have been compiled into a data set, with geolocation coordinates added for the identifiable locations. This thesis consists of the machine-readable dataset, the protocol for collating this data, and an assessment of the suitability of the data for different kinds of analysis. The dataset will be published openly for reuse, reanalysis, and collaborative additions.
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