Marine ecosystem health is frequently monitored by using marine benthic macroinvertebrates as indicators. Complex biological information such as community composition is summarized in benthic indices and marine conservation initiatives often rely on such assessments of ecological integrity and health status. They allow managers to identify impacted sites and enable them to make decisions on habitat restoration measures.
A plethora of different benthic indices have been proposed over the years. One of the more successful indices is the AZTI's Marine Biotic Index (AMBI), which is officially used in many European countries and has been tested in America, Africa, Asia and Oceania. It is based on abundance-weighted pollution tolerances of species present in a sample. Tolerance is categorized into five groups (sensitive to pressure, indifferent, tolerant, second order opportunist, first order opportunist). The system currently contains about 6000 species with assigned tolerance but this index - as most others - requires taxonomic assignment of specimens, which typically involves a time and resource consuming visual identification of each sample.
Reason enough for the researchers that developed AMBI to have a closer look into alternatives. They tested DNA barcoding and more specifically metabarcoding as these methods have the potential to increase speed, accuracy and resolution of species identification, while decreasing its cost in biodiversity monitoring. Quite often molecular methods are incorrectly perceived as costly although large scale morphology-based species identification requires a lot of expert time and thereby becomes more costly than any molecular alternative.
The goal of the study was to analyze the genetic resources available for the AMBI species, and determine the minimum reference library size and content required to calculate an accurate index. Additionally, we identify the best primers to retrieve the most complete representation of the AMBI taxonomic diversity and provide sequences for 22 species for which no genetic resources were available.
This publication represents a very nice proof of concept and I found the results very promising. What I like in particular is the approach to the problem of incompleteness. Instead of claiming that the DNA Barcode library is incomplete and leaving it at that (there are many studies doing just that) the colleagues try to find ways to deal with the current shortage by estimating the minimum of species necessary to calculate accurate indices:
Overall, our results place DNA barcoding as a viable alternative to visual species identification in the context of taxonomic assignment for gAMBI [gene-based AMBI] calculation; though, this viability is subject to increasing the number of sequences in the reference library. According to our results, this increase should be performed focusing on the most frequently occurring species, as their presence in the reference library, even in a small percentage, is enough for an accurate gAMBI calculation.
Here, we have focused on the use of (meta) barcoding techniques to ease the first step for the calculation of AMBI: taxonomic identification. However, it could be possible to think about a new version of gAMBI based on total biodiversity metabarcoding profile that would not require finding a particular set of species previously defined. Therefore, besides working on increasing the gAMBI reference library, we are also focusing on comparing samples analyzed by visual taxonomy and by metabarcoding in order to explore more practical genetics based alternatives to AMBI.