1. Conventional approaches to palaeoclimate reconstruction from deep-sea sediments often fail to distinguish between provenance and dispersal-related variations.
2. A conceptual model of spatio-temporal grain-size variation based on dynamic populations is proposed, which can be obtained by means of the end-member-modelling algorithm EMMA.
3. Palaeoclimate reconstructions of a high- and low-latitude basin illustrate the common degree of complexity of deep-sea grain-size records.
The article “Muddled or mixed? Inferring palaeoclimate from size distributions of deep-sea clastics” provides an overview of the challenges associated with palaeoclimate reconstruction from physico-chemical properties of terrigenous deep-sea sediments. The article presents a conceptual model for spatio-temporal grain size variation based on dynamic populations, as well as applications to several ocean basins and methods to examine the validity of grain size based palaeoclimate reconstructions.
The article is generally reliable in its presentation, providing evidence for its claims and exploring counterarguments where appropriate. The authors provide a critical review of past achievements in grain size analysis, which serves as a basis for their proposed model. They also discuss potential risks associated with their approach, such as the difficulty in distinguishing between provenance and dispersal related variations in sediment properties. Furthermore, they present both high and low latitude basin reconstructions to illustrate the complexity of deep sea grain size records.
However, there are some areas that could be improved upon in terms of trustworthiness and reliability. For example, while the authors provide evidence for their claims, they do not explore all possible counterarguments or consider alternative explanations for their findings. Additionally, there is no discussion about potential biases or sources of error that could affect their results or conclusions. Finally, it would be beneficial if the authors provided more detail about how their proposed model can be applied in practice to improve palaeoclimate reconstructions from deep sea sediments.