Wednesday, September 14, 2022

DNA barcoding as intergenerational transfer of taxonomic knowledge

I tweeted about this but want to bookmark it for later as well. The paper “A molecular-based identification resource for the arthropods of Finland” doi:10.1111/1755-0998.13510 contains the following:

…the annotated barcode records assembled by FinBOL participants represent a tremendous intergenerational transfer of taxonomic knowledge … the time contributed by current taxonomists in identifying and contributing voucher specimens represents a great gift to future generations who will benefit from their expertise when they are no longer able to process new material.

I think this is a very clever way to characterise the project. In an age of machine learning this may be commonest way to share knowledge , namely as expert-labelled training data used to build tools for others. Of course, this means the expertise itself may be lost, which has implications for updating the models if the data isn’t complete. But it speaks to Charles Godfrey’s theme of “Taxonomy as information science”.

Note that the knowledge is also transformed in the sense that the underlying expertise of interpreting morphology, ecology, behaviour, genomics, and the past literature is not what is being passed on. Instead it is probabilities that a DNA sequence belongs to a particular taxon.

This feels is different to, say iNaturalist, where there is a machine learning model to identify images. In that case, the model is built on something the community itself has created, and continues to create. Yes, the underlying idea is that same: “experts” have labelled the data, a model is trained, the model is used. But the benefits of the iNaturalist model are immediately applicable to the people whose data built the model. In the case of barcoding, because the technology itself is still not in the hands of many (relative to, say, digital imaging), the benefits are perhaps less tangible. Obviously researchers working with environmental DNA will find it very useful, but broader impact may await the arrival of citizen science DNA barcoding.

The other consideration is whether the barcoding helps taxonomists. Is it to be used to help prioritise future work (“we are getting lots of unknown sequences in these taxa, lets do some taxonomy there”), or is it simply capturing the knowledge of a generation that won’t be replaced:

The need to capture such knowledge is essential because there are, for example, no young Finnish taxonomists who can critically identify species in many key groups of ar- thropods (e.g., aphids, chewing lice, chalcid wasps, gall midges, most mite lineages).

The cycle of collect data, test and refine model, collect more data, rinse and repeat that happens with iNaturalist creates a feedback loop. It’s not clear that a similar cycle exists for DNA barcoding.

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