Data & MethodsWhat Does a High R² Actually Tell You? Model Evaluation Metrics from Soil Carbon to Tree Biomass
Most validation tables report three or four metrics and let them speak for themselves. R², RMSE, model efficiency, KGE, Lin's concordance and RPD mostly recombine three properties of the errors, and each one is blind to something. This piece follows the conditions under which a good score misleads: a wide validation range, a log-scale allometry, stocks scored in place of change, an error below the measurement noise, a threshold borrowed from hydrology. Ends with a minimum score sheet for any validation table. Three interactive tools.


















