[This dataset is embargoed until August 31, 2025]. This dataset contains monthly/annual time series of species-specific abundances and covariates for 137 targeted larval/juvenile fish surveys at sites in a range of English lowland rivers. Larval/juvenile fish data come from two different sources: The Environment Agency’s (EA) National Fish Population Database (NFPD) between 1974 and 2017 and a dataset created by the University of Hull (UoH) between 1984 and 2017 inclusive. Biological data consists of density estimates of each fish species from each survey (per metre squared) and also the average length of specified species at the end of their first year of growth. Covariate data include habitat quality indicator (River Habitat Survey), climatic variables (Gulf Stream and North Atlantic Oscillation indices), land-use change, river hydrology, water temperature, effluent dilution factor and concentrations of chemical determinands. This dataset was created as larvae and juveniles may be particularly useful indicators and respond differently than older fish to environmental stressors. The work was supported by the Natural Environment Research Council (Grant NE/S000100/2). Full details about this dataset can be found at https://doi.org/10.5285/c904c5f0-7f21-4759-a7d4-c262da230b53

This dataset contains a time series of species-specific fish abundances and covariates for 1180 fish sites in English rivers. Sites with at least ten annual fish surveys in the Environment Agency’s (EA) National Fish Population Database (NFPD) between 1975 and 2017 inclusive were selected. Covariate data include habitat quality indicators (River Habitat Survey and HABSCORE outputs), climatic variables (Gulf Stream and North Atlantic Oscillation indices), land-use change, river hydrology, water temperature, effluent dilution factor and concentrations of chemical determinands. The work was supported by the Natural Environment Research Council (Grant NE/S000100/2). Full details about this dataset can be found at https://doi.org/10.5285/b0afb78e-a0cb-4762-9220-659211ae3a5e