The Challenge of Genomic Forecasting in an Era of Global Change

AbstractGenomic forecasting is an emerging area of predictive ecology and evolution that leverages high-throughput sequencing to incorporate information on genomic variation into quantitative predictions of biological responses to environmental change. A central and increasingly applied concept in this field is genomic offset, a measure of the mismatch between current genomic composition and that predicted in new environments. This special issue brings together six studies spanning theoretical and methodological development, empirical evaluation, time series analysis, and conservation applications aimed at advancing the potential of genomic offset and related forecasting approaches for predicting population responses to environmental change. Contributions explore how genomic offset relates to stabilizing selection, compare individual- versus population-level offset models, and evaluate predictions using common garden experiments, long-term forest inventories, genomic time series, and conservation-relevant taxa. Collectively, the articles underscore both the promise and the current limitations of genomic forecasting while emphasizing that model predictive performance is often context dependent and influenced by statistical method, loci choice, and fitness proxies. Future progress will require rigorous validation, theory and methods development, and broader taxonomic coverage to ensure that genomic forecasting can realize its potential for informing biodiversity management in a rapidly changing world.