Aim:We developed a new technique, utilizing species-specific counts of individuals from historical fish community samples, to examine landscape-level, spatio-temporal trends in relative abundance distributions. Abundance-based historical distribution analyses are often plagued by data comparability issues, but provide critical information about community composition trends inaccessible to those using analyses based only on species presence-absence. We established trends in native and non-native fish abundance and community homogenization, uniqueness and diversity to help local conservation managers prioritize targets and motivate similar studies globally to support fish conservation.Location: Upper and middle New River (UMNR) basin, Appalachian Mountains, USA. Methods:We compiled catch data from 61 years of fish community surveys and tested for community homogenization by comparing data from repeatedly sampled sites (1900s versus 2000s samples) using dispersion analyses. We measured community uniqueness (site contributions to beta diversity) and species diversity (Shannon index) at sampled streams to identify potential conservation hotspots. We then used regression analyses and Wilcoxon signed-rank tests to examine speciesspecific basin-wide and local abundance trends and identify species of potential conservation concern.Results: Dispersion of sites in species abundance space was significantly greater in the 1900s compared with the 2000s, indicating homogenization had occurred.Of 36 native species analysed, 44.4% ( 16) showed basin-wide declines. Non-native species exhibited mixed patterns; site-level abundance increased in 2 of 15 species analysed (13%). Main conclusions:Our results indicate basin-wide community homogenization has occurred within the UMNR, but many unique and diverse communities persist. If conserved, these could help maintain regional fish diversity. We found basin-wide declines in four endemic species, as well as spread patterns of non-native and native species that were not detected by a presence-absence analysis applied within the | 2137 SLEEZER Et aL.