| 13 Apr 2026
Harmonising and mapping Patagonian Shelf seabed sediment data
Abstract. Maps of seabed sediment distribution on global continental shelves are useful for a wide range of applications, including for habitat mapping, predicting sedimentary carbon stocks, and providing insight into past and present oceanographic conditions and the processes influencing sediment transport and deposition. Whilst some continental shelves have relatively well mapped seabed sediments, others lack publicly available, harmonised datasets. The Patagonian Shelf, also known as the Argentine Shelf, is one of the world’s largest continental shelves, but there is currently no database that has compiled publicly available seabed sediment data. In this paper we collate and harmonise existing published and open-access seabed grain size data for the Patagonian Shelf. The paper combines both quantitative and qualitative data from published and grey literature and translates these data into two modified Folk sediment classification schemes. Ordinary Kriging is used to map the spatial distribution of different sediment classes across the shelf and allows us to assess uncertainty in the predictions of seabed sediment type. Overall, our sediment maps agree well with previously published maps over the central and northern shelf. Key differences are the classification of shell-rich sediments, and the spatial distribution of coarse sediments, particularly over the southern shelf. The latter would be further resolved with greater sampling of seabed sediments in the region. The data products produced for this study are grain size point data for the shelf and interpolated Geographic Information System (GIS) layers of seabed sediments and associated prediction errors. These are freely available for download via Zenodo (Roseby et al., 2026; https://doi.org/10.5281/zenodo.19111158).
The manuscript entitled “Harmonising and mapping Patagonian Shelf seabed sediment data” gathers about 500 surface sediment data to provide a reliable map of the Argentinean shelf. Worth noting that those types of mapping are crucial for several studies, such as habitat mapping and geohazards. Nevertheless, the authors make a major mistake when they treat the Patagonian shelf as a synonym for the Argentinean shelf. In fact, the Argentine shelf is much larger than the Patagonian area, and the manuscript must be corrected accordingly.
The second aspect deals with Table 1. It is not clear which data were obtained from the samples in which the GSA method was classified as a “description”. Indeed, most of the samples fall into this GSA method. In the case of Oliva (2020), the GSA method is “NA” (not available). Which data were used in this case?
Concerning the kriging interpolation, I wonder which semivariogram model was used. I am not familiar with ArcGIS, and I do not know whether there is a basic model for determining the extent of a zone of influence for a given georeferenced value.
In summary, the manuscript has value, but some methodological aspects need clarification before acceptance.