NEW PAPER: A taxonomic resolution assessment for deep-pelagic fish assemblage analysis in a high-diversity ecosystem

I am delighted to announce that we have a new published paper from Krista Sheuerman, one of my lab's MS student alumni! Krista's paper examines how taxonomic resolution and data transformations affect our interpretation of patterns in assemblage-level data using a series of large-net trawls from the Gulf as a case study. By testing cases where we expect to see strong, clear patterns of change in the assemblage (i.e., over the diel cycle and over two different depths), we examine how well the different analyses do at detecting those differences, and when they fail. We also directly correlate the similarity matrices from the different multivariate datasets to determine how similar or different they are from each other.

Sheuerman et al (2026): Figure 3. The relative effects of taxonomic rank and data transformation on multivariate similarity in a midwater datasets.

Overall, Krista determined that species and genus level data give generally similar results from these tested data, especially when weak transformations are used. As the degree of transformation increases, the similarity between taxonomic levels diverges and will likely give rise to different patterns and affect our interpretation of the assemblage-level data. These results highlight just how important it is to understand how our data treatments and early analytical choices affect our ecological understanding and interpretations.

The paper is published in Frontiers in Marine Science and is available to read (for free!) at this link: https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2026.1788097/full