Context
Fish biomass is estimated in MERMAID for each individual fish observed using the following length-weight relationship:
W = a x Lb
where W is weight (grams), L is total length (centimetres), and a and b are species-specific coefficients sourced from FishBase (see documentation here).
This article shows how to retrieve and compare MERMAID’s current biomass conversion coefficients with a previous version, explores the consequences of any differences across fish size ranges, and demonstrates how you can apply your own custom coefficients to recalculate biomass estimates at the transect and sample event level.
Comparing current and past versions of coefficients
The linked full resource shows how to access MERMAID's latest biomass conversion coefficients as well as past versions. The current version can be accessed using the mermaid_get_reference function in the mermaidr package. Past versions can be accessed by downloading from a URL - this example code shows specifically how to download the version from Feb. 25, 2026 using the following URL: https://public.datamermaid.org/mermaid_attributes_26-02-25.xlsx.
Differences in the coefficients between these versions are visualized, as well as the implications of those differences across the size range for fish, in a series of plots (see below). If there are many species with differences, only the top 12 are shown, but the code could be adapted to show more.
Applying custom coefficients and exploring sample event differences
The full resource also contains code showing how custom coefficients can be applied to your MERMAID projects. In this example data is exported from a public project in Belize, but I have included code that can be used to access your own projects instead. The code generates simulated "dummy" custom coefficients by adding random adjustments to the current coefficients for the top 5 fish species in the project. However, I also provide instructions for how you can apply a table of your own custom coefficients instead.
After applying the custom coefficients to each of the relevant observations, the code shows how the sample unit and sample event level biomasses can be re-calculated. Horizontal bar plots then show how the custom coefficients scale up to differences among sites on sampling dates (i.e. among sample events). An example of this is shown below.
At the end of the example there is a summary of all the differences found and their implications.
