Morpho: Establishing core data standards for climate-resilient inland fisheries

Inland fisheries are important contributors of nutrition, livelihoods, and well-being for millions of people worldwide, yet they face increasing threats from habitat degradation, hydrological alterations, and climate variability. Sustaining and effectively managing inland fisheries amidst these changes requires an understanding of the threats to, and status of, fisheries, and ideally having reliable, consistent, and accessible data across spatiotemporal scales—something that is currently lacking in many regions. To address this need, the U.S. Geological Survey National Climate Adaptation Science Center and Food and Agriculture Organization of the United Nations developed a proxy index ('Findex'), which leverages remotely sensed data, literature synthesis, and expert opinion to estimate potential threats to inland fisheries. The next critical step is to link 'Findex' to in-situ data and identify which in-situ data are irreplaceable from earth observation data and thus a priority for fishery managers to collect and report. Ultimately, this collaborative effort aims to develop core (minimum) data standards for inland fisheries reporting. Using five case studies (Lake Victoria, Lake Tanganyika, Paraná River, Amazon River, Mekong River), representing the world’s most data-rich, productive, and biologically diverse inland fisheries, we will collate field-based data with satellite-based data, run validation and integration algorithms, then conduct a degradation analysis to determine the essential in-situ data required for robust basin-level assessments. Using artificial intelligence and machine learning approaches, this effort will streamline data collection, reduce redundancy, and ultimately improve the capacity of fishery managers to safeguard climate-resilient fisheries.