ABSTRACT:

Unprecedented environmental changes challenge our understanding of the natural world, yet critical environmental decisions are made every day. Ecological forecasting provides a mechanism to inform science-based decision making amidst accelerating environmental uncertainties by using foundational forecasting principles to anticipate ecological unknowns. However, as an emerging and interdisciplinary field, ecological forecasting lacks unified terminology, limiting cohesion and hindering communication across other forecasting sub-disciplines. Here, we examined current use of common forecasting terms using a survey of forecasting professionals (n=109), and syntheses of literature trends (Scopus; 1970-2025) and internet search queries (Google Trends; 2004-2024). Results informed development of standardized definitions for “forecast”, “prediction”, and “projection” and illuminate a disconnect between the goal of aiding decision making and the inclusion of decision science in the forecasting process. This work promotes participation and growth in ecological forecasting, helping ecological forecasters meet priority end goals by facilitating communication across forecasting disciplines and within forecasting processes.

ABSTRACT:

This dataset corresponds with the inland fisheries collaboration between the Land and Water Lab at the University of Florida and Food and Agriculture Organization of the United Nations. An online survey of fisheries professionals distributed in June-September 2020 yielded 536 responses from 93 unique hydrological basins across most major freshwater habitat types. Provided here are the raw survey dataset generated from participant responses, a formatted dataset intended for reuse, a reference key to numeric values and column headers, a reference key to region identifiers, and the script used to generate the formatted dataset and figures used in the paper titled, "A global dataset of inland fisheries expert knowledge."