Abstract
Abstract Although non‐game fishes typically dominate lists of threatened and imperilled species, funding mechanisms for non‐game species are usually less robust than those for game species. This imbalance emphasizes the need for methodologies to identify imperilled species effectively and ensure efficient allocation of limited conservation resources. A database comprising >3,900 fisheries surveys conducted between 1905 and 2020 in Great Plains streams of Oklahoma (USA) was used to develop methodology for identifying species in need of conservation by assessing differences in species occurrences and trends in species ranges through time. Changes in occurrence for 92 species at both river catchment and ecoregion scales were assessed. Generalized linear models indicated significant differences between historical and contemporary fish communities at both scales. Univariate testing showed 84 instances of species occurrences changing in at least one catchment. Declines in occurrence were observed for eight species currently listed as species of greatest conservation need in Oklahoma and were used to identify five candidate species for listing. Family‐level trends in species occurrences suggested declines of native true minnow species and increases in generalist sunfishes and catfishes through time. Trends in detections within each hydrologic unit code sampled were used as a proxy for tracking changes in species range within each catchment. Various species were used as case studies to highlight this method. The results demonstrate how managers can apply an empirical methodology that extracts information from long‐term datasets to optimize conservation efforts for stream fishes and associated taxa.
Published Version
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