Using Spatial Validity and Uncertainty Metrics to Determine the Relative Suitability of Alternative Suites of Oceanographic Data for Seabed Biotope Prediction. A Case Study from the Barents Sea, Norway

The use of habitat distribution models (HDMs) has become common in benthic mapping for combining limited seabed observations with full-coverage environmental data to produce classified maps showing predicted an entire study area. However, relatively few HDMs include oceanographic predictors, or present spatial validity uncertainty analyses support the predictions. Without reference studies it can be challenging assess which type model should used, developed, this purpose. In study, we compare biotope built using predictor variable suites from three different differing levels detail on near-bottom conditions. These results are compared a baseline without predictors. We associated and may best suited mapping. Our show how metrics capture differences between HDM outputs otherwise not apparent standard non-spatial accuracy assessments themselves. conclude that incorporating high-resolution, preferably bottom-optimised, oceanography minimise maximise validity. Furthermore, our suggest coarser lead more than omitting such data.