RivFishTIME: A global database of fish time-series to study global change ecology in riverine systems

Abstract

Motivation: We compiled a global database of long-term riverine fish surveys from 46 regional and national monitoring programmes and from individual academic research efforts, with which numerous basic and applied questions in ecology and global change research can be explored. Such spatially and temporally extensive datasets have been lacking for freshwater systems in comparison to terrestrial ones. Main types of variables contained: The database includes 11,386 time-series of riverine fish community catch data, including 646,270 species-specific abundance records, together with metadata related to the geographical location and sampling methodology of each time-series. Spatial location and grain: The database contains 11,072 unique sampling locations (stream reach), spanning 19 countries, five biogeographical realms and 402 hydrographical basins world-wide. Time period and grain: The database encompasses the period 1951–2019. Each time-series is composed of a minimum of two yearly surveys (mean = 8 years) and represents a minimum time span of 10 years (mean = 19 years). Major taxa and level of measurement: The database includes 944 species of ray-finned fishes (Class Actinopterygii). Software format: csv. Main conclusion: Our collective effort provides the most comprehensive long-term community database of riverine fishes to date. This unique database should interest ecologists who seek to understand the impacts of human activities on riverine fish biodiversity and to model and predict how fish communities will respond to future environmental change. Together, we hope it will promote advances in macroecological research in the freshwater realm.