A recent paper (Sharkey et al. 2021a) describing 416 new species of Braconidae parasitoid wasps (Hymenoptera) from Area de Conservación Guanacaste in Costa Rica has reignited the debate about taxonomic best practices when describing species. The new species were treated in a minimalist way, as stated in the very title of the paper and this quote from their abstract: “Most descriptions consist of a lateral or dorsal image of the holotype, a diagnostic COI consensus barcode, the Barcode Index Number (BIN) code with a link to the Barcode of Life Database (BOLD), and the holotype specimen information required by the International Code of Zoological Nomenclature” (Sharkey et al. 2021a: 2).

Sharkey et al. (2021a) is but the latest example of a growing list of papers that aim to accelerate the description of species on a planet facing a biodiversity crisis in which species may become extinct before they are even described. “Turbo taxonomy” is a catchy name proposed by Butcher et al. (2012) to qualify such papers, and it has been rather enthusiastically applied since then – a Google Scholar search for “turbo taxonomy” retrieved 135 results since 2012 through January 2022. A similar concept “fast-track taxonomy” was proposed around the same time by Riedel et al. (2013a); I consider them as equivalent and for the sake of simplicity I will use “turbo taxonomy” henceforth.

Although somewhat subjective, turbo taxonomy can be characterized as the rapid description of many species in “fast” papers (as compared to the “slower” pace of traditionally produced taxonomic papers). This is usually accomplished using a combination of tools and approaches to automate and expedite dealing with the material examined, e.g., morphological traits quickly assessed and scored, often with brief descriptions and/or descriptions generated using software packages, high-quality illustrations, a heavy reliance on molecular and other data (e.g., biological, distributional) to differentiate and diagnose species. The combination of techniques for species recognition and description at least partially intersects with another concept, that of “integrative taxonomy”, sensu Dayrat (2005), and perhaps sometimes both terms have been used interchangeably, although integrative taxonomic papers are not necessarily “rapidly produced” as is claimed for the turbo-taxonomy ones.

The main difference between Sharkey et al. (2021a) relative to previous turbo-taxonomy papers, and the reason for the present discussions within the scientific community is that they chose to describe the new species based almost exclusively on DNA barcodes.

Describing new species based only or mostly on molecular data is not new. Hibbett et al. (2011) discussed prospects for sequence-based taxon discovery and description in fungi (see also Taylor 2011; Kõljalg et al. 2013); and Renner (2016) compiled a list of at least 98 names of species of acoels, lichens, angiosperms, annelids, alveolates, arachnids, centipedes, turtles, fishes, butterflies, mollusks, nematodes, and pathogenic fungi that have been published based on diagnostic mitochondrial, plastid, or nuclear DNA substitutions, indels, or rarely genetic distances, with or without the addition of morphological features. Even within Braconidae, some of the coauthors of Sharkey et al. (2021a) had recently published a similar, albeit much smaller paper (Meierotto et al. 2019).

Thus, the novelty of the Sharkey et al. paper is hardly the approach itself but rather the scaling up of the work to a mammoth monograph in which more than 400 new species were described. That is indeed a first. And, as quoted from the very first sentence of their introduction, the authors presented their article as a way to “further refine methods to overcome the taxonomic impediment of ichneumonoid biodiversity” (Sharkey et al. 2021a: 6).

In the months following that paper, the scientific community has engaged in lively discussions about “how useful” such descriptions are, whether they in fact impede the cataloguing of biodiversity, “how valid” (from the ICZN perspective) those species are, and general issues about the future of taxonomy, and the shortcomings of BINs and even BOLD (e.g., Ahrens et al. 2021; Engel et al. 2021; Meier et al. 2021).

In this Forum Paper I discuss some of the above issues, present alternative/complementary ideas from my perspective, and include a detailed proposal on how to approach turbo taxonomy in a hyperdiverse group such as braconid parasitoid wasps balancing rapid descriptions of species while also keeping a higher use value of the final product(s). I do not claim to have better or newer insights than others, and I certainly do not pretend to have any definitive answers, but perhaps my comments could be useful because a) I am a braconid researcher, like the main authors of the Sharkey et al. (2021a) paper, b) I have published several papers that could be considered as turbo taxonomy and have long been interested in ways to speed up species descriptions, c) I was actually one of the reviewers of Sharkey et al. (2021a) (and for full disclosure, I recommended its acceptance, although I also added many opinions on its taxonomic approach and how it could have been improved, with many of my suggestions being ignored by the authors in the final version), and d) perhaps more importantly, because I think that Sharkey et al. (2021a), even if arguably flawed, demonstrate opportunities that can and should be used by the taxonomic community to improve and speed up work in the future. In that sense, what follows below is less of another critical view of that paper and more of a complementary proposal to improve turbo taxonomic methods.

There are many published papers that discuss the need to and possibilities of speeding up taxonomy by using newer technologies such as DNA barcoding. Unfortunately, most of those papers present somewhat general discussions or are intended just as a proof of concept, without actually applying it to describing new species. In many cases, DNA barcoding is presented as a useful and comparatively rapid tool to rapidly distinguish species, often revealing a much higher species diversity than previously thought based on morphological study and/or revealing complexes of cryptic species. However, usually things stop there, and the next step is not made, i.e., the new taxa are not described in those papers praising how much DNA barcoding brings to the taxonomist’s table. I would consider those papers examples of “talking the talk” but not necessarily “walking the walk” (in the sense presented here: https://knowyourphrase.com/talk-the-talk). It is important to stress that this statement does not apply to the four braconid experts and coauthors of the Sharkey et al. (2021a) paper (Michael Sharkey, Scott Shaw, Donald Quicke, and Kees van Achterberg) all of whom are world-renowned taxonomists. Altogether they have described more than three thousand new species in hundreds of published papers (e.g., see Yu et al. 2016), and their contributions to our knowledge of Braconidae and other Hymenoptera groups has been outstanding. They have certainly walked the walk!

But the truth is that comparatively few works could have the turbo taxonomy label applied to them. Examples include lichens (Lücking et al. 2017), annelids (Summers et al. 2014), dragonflies (Dijkstra et al. 2015), frogs (Rakotoariso et al. 2017), phorid flies (Hartop and Brown 2014; Hartop et al. 2015, 2016), histers beetles (Caterino and Tishechkin 2013), weevils (Riedel et al. 2013b, 2014; Riedel and Tänzler 2016; Riedel and Narakusumo 2019), and several papers on braconids (Table 1). There is no doubt that other papers than the ones I list can be found in the literature, but they still constitute a minority of published taxonomic revisions. [Srivathsan et al. (2019) could also be considered here, albeit only partially, because they discuss and present novel methodologies for rapid description of species (= turbo taxonomy) but only describe one new species as an example].

What is somewhat surprising (or worrisome?) is the realization that few of the researchers who have published a paper that could be considered as turbo taxonomy have continued to do afterwards, i.e., they have not produced additional monographs in the same turbo taxonomy style. Based on my, admittedly non-exhaustive, online searches, I can only mention Riedel and colleagues for weevils (Riedel et al. 2013b, 2014; Riedel and Tänzler 2016; Riedel and Narakusumo 2019) and a series of papers on Braconidae (see Table 1 and discussion below) as two examples of researchers doing turbo taxonomy on a more sustained basis.

One may then ask, if turbo taxonomy is touted as “the way to move forward” in taxonomy, why are there so few adopters of the approach, and even fewer who repeat their efforts in subsequent papers? In my opinion the answer is simple: because turbo taxonomy still requires a significant amount of invested work and time, and it is not as easy and rapid as one might think or as it is purported to be in papers advocating for those revolutionary taxonomic approaches. A simple search of author names reveals that most of the published turbo taxonomy papers have been done primarily by graduate students (M.Sc. and Ph.D.) or postdoctoral fellows. They represent some of the more enthusiastic, hard-working, and “overperformer” researchers in the taxasphere, a great combination of youth, energy, and a desire/need to advance their careers. They certainly put in the effort needed to accomplish their turbo taxonomy feats, and they deserve all the praise for that. But could those papers become the “new normal” for taxonomy? I would argue that it is unrealistic to expect that turbo taxonomy papers can be produced effortlessly and quickly, much less in a sustained way, at least those closer to “traditional taxonomy” in the sense of providing keys and morphological descriptions.

I believe that Meierotto et al. (2019), Sharkey et al. (2021a), and others before them (see Introduction for non-Braconidae examples) are probably correct in their claim that a shift of paradigms is possible and needed to increase the speed of taxonomic results. I also agree that DNA-based species recognition should be one of the major driving forces to speed up the cataloguing of biodiversity. Where I disagree with such authors is in the way to implement turbo taxonomy because I believe that this can and should include components other than DNA that increase the “use value” of the paper while not taking much extra time or resources.

First let us look at what has been accomplished with turbo taxonomy relative to Braconidae during the past 15 years or so (2005–present). Table 1 presents basic data on some papers, divided in two somewhat arbitrary categories. The first five rows include papers with the largest numbers of treated species (approximately 100–400 species each), to serve as a direct comparison with Sharkey et al. (2021a) which is, by far, the largest paper discussed here. Included are all the large monographs in Braconidae I am aware of that could be considered as examples of turbo taxonomy. The remaining rows contain a sample of papers with fewer treated species overall (approximately 30–80 each), which are comparable in size species-wise with Meierotto et al. (2019). There are certainly more examples of revisions of Braconidae in this second category than those I have listed.

Four of the large papers provide identification keys, “traditional” (i.e., morphology-based) species descriptions (as opposed to only DNA-based ones), and multiple illustrations of all or most species. The only exception to this is the paper of Sharkey et al. (2021a), which does not provide keys or traditional descriptions and includes only a single image per species (usually a lateral habitus). Molecular data to recognize, differentiate, and/or describe species was used in all papers except Marsh et al. (2013) and Liu et al. (2020). Other data, mostly biological information, usually host data but also number and shape of wasp cocoons, host plant, microhabitat, etc., were less prevalent, and mostly restricted to those papers treating the Area de Conservación de Guanacaste, Costa Rica (ACG) fauna because of the wealth of biological and ecological information available for Braconidae and other taxa obtained in that area (e.g., Janzen and Hallwachs 2011, 2016, 2020; see also http://janzen.sas.upenn.edu/caterpillars/database.lasso).

The pattern among the shorter papers is mostly similar, with Meierotto et al. (2019) being the only one not to include differential keys or morphological descriptions. All the other papers are more complete from the perspective of morphology, and many also included molecular, biological, and ecological data although, again, the ACG papers were more comprehensive because the authors had access to more information.

An interesting comparison can be drawn between the Meierotto et al. (2019) and Sharkey et al. (2018) papers: both treat a single genus of Agathidinae (Braconidae) but the latter is much more comprehensive in its use of features/traits to recognize, identify, and describe the species.

The examples in Table 1 are comprehensive taxonomic revisions that treated dozens and sometimes even hundreds of species each; they included at least some basic morphological data, usually more. Indeed, if a taxon could claim the crown of turbo taxonomy, Braconidae would be a strong candidate. In just one subfamily, Microgastrinae, a total of 720 new species was described between 2014 and 2019 (Fernandez-Triana et al. 2020), the vast majority in papers that would qualify as turbo taxonomy.

There is no question that these papers could have been produced faster and easier if a minimalistic approach, such as those of Meierotto et al. (2019) and Sharkey et al. (2021a), had been adopted. How fast and how easy are, however, complicated questions to answer. And how “useful” those papers would be for potential users is an even more difficult one.

Sharkey et al. (2021a), and for that matter many other papers, my own included, that have treated the ACG fauna benefited immensely from the work previously done by Daniel Janzen, Winnie Halwachs, and their team (e.g., Janzen et al. 2009; Janzen and Hallwachs 2011, 2016, 2020). Thanks to herculean efforts (including their amazing parataxonomists and technicians, mostly in Costa Rica but also in USA and Canada), thousands of specimens have been collected, reared, labelled, and databased with recorded host data, and DNA has been extracted, with the available sequences and additional information readily accessible in the Barcode of Life Data System (BOLD). Some of that work is highly technical, and all of it took a lot of time and significant resources, including financial. All or most of that was done before the actual work of the taxonomists started, and in fact was of critical importance or else it would have taken much more time and considerably more resources to produce those taxonomic papers, whether traditional or turbo taxonomy.

Thus, when considering papers that claim to be “fast” because they only rely on DNA-based descriptions, one must also consider hidden but significant amounts of work done prior to the taxonomy study. If time, expertise, and resources needed to obtain all the previous information on which the taxonomy is based were accounted for, then those papers would suddenly appear less quick and easy to produce than as advertised, at least relative to ACG studies.

Beyond time and resources not being properly assessed in a paper employing only DNA-based descriptions, there is a bigger issue. And that is the fact that any user of such a paper must, by default, obtain DNA data for their own specimens before any meaningful comparison can be made with the species dealt with in that paper. Otherwise, it is not possible to conclude if a specimen at hand belongs to a previously “DNA-described” species or is new. Thus, “DNA-only description” papers force users to do “DNA-only identifications”.

There is no problem with that, say some enthusiastic supporters of turbo taxonomy and DNA barcoding. It will actually democratize taxonomy because technical knowledge of a taxon, including the associated morphological jargon used to described it (e.g., number of setae on propodeum or sculpture on mesoscutum), would no longer be required. What used to be the domain of a relatively few taxonomists would become mostly unnecessary, because “soon” everyone would be able to use a device, à la Star Trek tricorder (https://en.wikipedia.org/wiki/Tricorder), to identify species. It would allow even school children to rapidly identify the caterpillar they found in their backyard or farmers in Central America to recognize which pest or parasitoid wasps are found in their crops. It all looks so nice and promising!

I fully agree that DNA barcoding democratizes taxonomy because indeed it reduces somehow the need for trained taxonomists to do routine identifications (e.g., Janzen et al. 2009; Janzen and Hallwachs 2001, 2016). But, while I have no doubts that technology ultimately will be developed to allow fast, easy, and cheap devices to obtain and analyse DNA, and access the comprehensive DNA databases that are necessary to determine whether a specimen at hand represents a described species, that scenario is not yet here (but see Srivathsan et al. 2021 for some new developments that could become viable alternatives in the near future). We are still far from being able to download a “Taxonomy for Dummies” app.

Meanwhile, what we have is the fact that DNA-based taxonomy is not accessible or affordable to everyone (see further analyses and/or other perspectives in Pinheiro et al. 2019; Dupérré 2020; Ahrens et al. 2021; Meier et al. 2021; Srivathsan et al. 2021). At present, it is not possible to obtain a DNA barcode from a single specimen unless the individual has access to a molecular lab, whether this is their own or “one for hire”. As an example of the latter, one of the most commonly used such labs is the Canadian Center for DNA Barcoding (formerly the Biodiversity Institute of Ontario), which charges $1,250 Canadian dollars for a single plate of 95 specimens (http://ccdb.ca/pricing/). However, in addition to that cost, single images of every submitted specimen and an Excel file with some basic information are also required when samples are submitted, which will take additional time and money; factors also to consider are the shipping costs and dealing with national/international laws regulating access, sharing, and exportation of genetic resources.

Never mind the school children or farmers, arguably most world researchers cannot afford the current costs and associated logistic challenges mentioned above to obtain DNA-based identifications for every specimen they may need or want to identify (e.g., Srivathsan et al. 2021). If the route of having to obtain DNA barcodes (or any other molecular marker) to identify species becomes the only route to a scientific name, then this could make taxonomy even less accessible and democratic than using “traditional” techniques such as microscopes and dichotomous keys. At present is certainly valid to argue that the cost of traditional, morphology-based taxonomy is largely a “front end” cost mainly borne by the taxonomist, whereas DNA-only taxonomy necessitates high and significant “back end” user costs.

In addition to cost and who pays this, there is also the problem of the almost two million species described in the pre-molecular era, many with no DNA associated. Those species cannot simply be ignored, as it has been claimed to be the case in the Meierotto et al. (2019) paper. Zamani et al. (2020) thoroughly discussed that problem, although Sharkey et al. (2021a, b) gave some counter replies.

In the end, it comes down to the practicality and benefits/damages that minimalistic (extreme?) taxonomic approaches, such as those relying only on DNA barcodes for species description and recognition, bring. Do future revisions to be produced really need to ignore morphology and previously described species to instead rely entirely or almost exclusively on DNA barcodes, with the “justification” of describing species faster because of the biodiversity crisis? Or is it possible to build upon the works of Meierotto et al. (2019), Sharkey et al. (2021a), and others to try finding a middle-of-the-road approach, where speed and practicality are attained while significantly minimizing efforts and cost?

What I propose below is a workflow and guidelines for preparing turbo taxonomy papers, including estimated times for each task. The main motivation is to provide an alternative to Meierotto et al. (2019) and Sharkey et al. (2021a) but with the addition of some features that I hope would increase the applicability of the work (from a user perspective) while still maintaining a relatively fast pace. I have based this proposal on my personal experience preparing Braconidae turbo taxonomy papers, but it could be adapted for other taxa, i.e., used like a “cookbook recipe” that can be modified and changed as needed or desired.

I do not pretend to reinvent the wheel, e.g., see Reidel et al. (2013), Hartop and Brown (2014), Srivathsan et al. (2019) for earlier turbo taxonomy proposals and even nicer workflow diagrams (although my proposal includes more detailed analyses of time involved with each task and consideration of other factors). I also strongly recommend checking the new guidelines for species descriptions posted by ZooKeys: https://zookeys.pensoft.net/about#TaxonomicTreatments), which in some ways intersects what I write below. And it may also be fruitful to check the many exchanged messages in the email list for biological systematics Taxacom (http://mailman.nhm.ku.edu/cgi-bin/mailman/listinfo/taxacom), where the Meierotto and Sharkey papers were vigorously discussed in 2019 and 2021 (while I have refrained from commenting on Taxacom about Sharkey et al. (2021a), in 2019 I did share my opinion about Meierotto et al. (2019), and some of the ideas presented here are based on what I wrote to that list at that time).

i) Overall estimate time to deal with one species

The sum of all the time estimates above renders a total of 15 hours per species. That is roughly two days of work per species, or 2.5 species per week. Rounding down to 2 species per week and 50 weeks per year, one arrives at an estimate of 100 new species described in one full-time year of work by a turbo taxonomy practitioner.

However, how accurate is this estimate? Are there examples of this in the real world, or is the above just a theoretical, futile exercise?

It is difficult to get actual data from previous turbo taxonomy papers as to the time it took to complete the work because this is rarely (or never) stated by the author(s). But some information is available and other can be guessed.

I have no exact knowledge of how much time it took Sharkey et al. (2021a) to prepare their paper, but from correspondence with some of the coauthors I know that it took at least two years. Assuming that was the case (and not longer), it would mean a rate of 200 new species per year, an impressive number. But one needs to factor in how much time was spent by the other three coauthors of that paper who are braconid taxonomists, in addition to the primary author. As such, I suspect that the actual number is below 200 species described per year.

Many of the other larger papers listed in Table 1 represent the work of a Ph.D. thesis or postdoctoral research, each of which probably included at least 3 years of work with the specimens. Based on the total number of species for those revisions, that would give values between 40 and 100 species per year per paper.

Fortunately, I can provide a more accurate estimate for my own work revising Apanteles (Braconidae) in Mesoamerica (Fernandez-Triana et al. 2014), which took two years to complete. The revision treated 205 species and at the time I was working full time on the project. Consequently, the pace was approximately 100 species per year. But, very importantly, I benefited greatly from previous work accomplished by Dan Janzen and Winnie Hallwachs in ACG, and some preliminary sorting of species by James Whitfield (University of Illinois at Urbana-Champaign) and his students before I started – all those contributors were rightfully included as coauthors. Thus, the pace to produce that paper is not as fast as it would first appear, and it underscores the difficulties in calculating the actual amount of time it takes to produce comprehensive taxonomic revisions. If anything, I cannot take much credit for the results of that paper (more criticism of my own work below).

Another factor to consider is that a rate of 100 species/year can only be accomplished if treating species “in bulk”, i.e., if the purported review would include many new species. But not all taxonomic groups to be studied have hundreds of undescribed species and a taxonomic revision of “just” a dozen species would not be as time efficient. Furthermore, most people cannot spend 100% of their time doing taxonomic revisions. Even Ph.D. students have other things to do than just taxonomic revisions! Thus, a rate of 100 species/year is, in my opinion, a very high and somewhat unfair standard to expect, much less to meet on a consistent, year to year, basis; at least with current technology.

However, regardless of the actual time used for any taxonomic revision, efficiencies can be realized, such as including brief descriptions instead of traditional, longer, and more comprehensive ones, as proposed above. Going back to the real-world example of my own Apanteles paper, for that work I measured and scored 49 morphological characters (altogether more than 15,000 measurements). Many of those characters ultimately proved to be uninformative to distinguish species, being repetitive, too variable, or too subjective or complex to assess. In retrospect, the keys were also unnecessarily long, and some species almost impossible to tell apart based on the keys only (Eduardo Shimbori, pers. comm.). Looking back, eight years after I completed that paper in 2013, I see many inefficiencies in my work, and much superfluous data that could have been eliminated. Had I chosen a lower number of morphological characters and simplified the keys, it could have been completed quicker, without diminishing the final quality of the work. Had I assumed an approach similar to my proposed “cookbook recipe” above, the species would have been mostly recognized by DNA and host data, and the keys would have been constructed to serve a more basic and limited function than what I had intended, while still retaining some utility to recognize basic species-groups. Of course, one could argue that the potential value of any character cannot be comprehended until it has been analyzed. One cannot know that there are “x” number of useful characters, and what they are, prior to studying them. This is what research is all about. Perhaps the “useless” time spent on some measurements is actually an example of what is necessary and a part of all taxonomic revisions, unless morphological features are completely ignored.

One example of how work can be reduced and made faster but still retain value is the case of the Apanteles leucostigmus species group, which comprises 39 species and is, by far, the largest and most difficult group of Apanteles to recognize and separate species in Mesoamerica. The key from Fernandez-Triana et al. (2014) for that group (reproduced here in Fig. 1) starts by dealing with a species that cannot be keyed out due to lack of data, with only one specimen known, and is an actual example on how to deal with historical species where information is not available. The remaining 38 species are keyed out using some characters difficult to assess and at some points the differences between halves of the same couplet are very subtle (the paper also included 4–8 images each of the adult wasps for every species). This key may look good on paper, but in practice it is very difficult and prone to error. Indeed, morphology does not work well for this group, which is suspected to include several morphologically cryptic species. Instead, I could have prepared a much simpler key that only used a few characters that are relatively easy to assess. Obviously, some species would end in the same point of the key, and thus could only be reliably identified by molecular and biological data. Such a “new” key (Fig. 2) would be much shorter and thus faster to prepare. As for the user of such key, there would still be the need of obtaining DNA barcodes and/or host data to obtain species identifications, but even if the user does not have such data, specimens could still be placed at least in some sub-group.

Figure 1. 

Details of the key to the Apanteles leucostigmus species group as it appeared in Fernandez-Triana et al. (2014). The plate shows a composite image of the key in the same format it appeared in the online version of that key (https://zookeys.pensoft.net/articles.php?id=3394).

Figure 2. 

Details of the key to the Apanteles leucostigmus species group as it would look based on modifications detailed in the present paper (see section “h) Overall estimated time to deal with one species” in the current manuscript).

The above example, which I chose because it was the most difficult and problematic group of the Apanteles revision, illustrates how a mostly-but-not-only DNA based paper could be constructed in a more time-effective way. Other Apanteles groups from that Fernandez-Triana et al. (2014) revision (and indeed many groups in other taxa) might work even better. The proposed methods could shorten the time to produce a taxonomic revision while still providing some basic elements of more traditional papers.

I do not pretend that my suggestions above will “solve” the problem of describing millions of additional species in a short period of time. Even a “fast” pace of 100 species/year per taxonomist would still take a few hundred years to finish the task, a luxury we cannot afford, or would require a significant increase in the number of professional taxonomists (an unlikely scenario). There is no easy or simple answer to the necessity (and urgency!) of accelerating taxonomic inventories. My opinion is that it will require a wide embracement of current and additional technology advances, but also some consensus-building among the taxonomic community on how to move forward, and perhaps even a broader involvement of citizen science. The present paper must be seen only as a modest attempt to provide some alternatives, even if insufficient. For some different perspectives and opinions on these topics, I recommend the reading of what the reviewers of the present paper had to say (Suppl. material 1).

It is very telling to see how many strong reactions a single paper has awakened in just a few months after its publication (or two papers, if we account for Meierotto et al. 2019), and the reasoning and pleas of other colleagues to avoid a future à la Sharkey et al. (2021a). I strongly recommend the reading of papers such as Pinheiro et al. (2019), Dupérré (2020), Zamani et al. (2020), Ahrens et al. (2021), Engel et al. (2021), Meier et al. (2021), Srivathsan et al. (2021), and references cited therein (other papers providing slightly different alternatives or approaches are also recommended reading, e.g., Brower (2010), Blaxter (2016), Goulding and Dayrat (2016), Renner (2016), Brown and Wong (2020), Vences (2020); this list is not exhaustive). And to present a more complete and fairer picture, the reader should also consider a second paper by Sharkey et al. (2021b) which tried to provide counterarguments to some of the received criticism, although that paper has also been met with additional counterarguments on its own, e.g., Ahrens et al. (2021), Engel et al. (2021), and Meier et al. (2021).

The authors cited in the previous paragraph have discussed in a more coherent, compelling, and convincing way that I probably could about the dangers and shortcomings of approaches such as those of Meierotto et al. (2019) and Sharkey et al. (2021a). While I agree with most of those arguments, I also think that the Meierotto and Sharkey papers provide an opportunity to critically look at and improve our own work. In that sense I prefer to be optimistic and focus on examples and the potential of what could be done (or has already been done by other authors) so that future turbo taxonomy papers can accomplish the (very much needed) dual goal of being fast and useful for the scientific community and the general public.

I want to acknowledge the reviewers Marko Mutanen (University of Oulu, Oulu, Finland), Stefan Schmidt (Bavarian State Collection, Munich, Germany), Brian V. Brown (Natural History Museum of Los Angeles County, Los Angeles, USA), and Istvan Miko (University of New Hampshire, Durham, USA), as well as the subject editor Lyubo Penev (Pensoft) for providing additional ideas and suggestions that not only improved the final version of this paper, but also significantly contributed to the wider dialogue about taxonomy and biodiversity crisis. I am also very grateful to John Huber and Gary Gibson (Canadian National Collection of insects, Ottawa, Canada) for their excellent reviews of earlier versions of the manuscript. This work was supported by Project J-002276 “Systematics of beneficial arthropods in support of resilient agroecosystems”, from Agriculture and Agri-Food Canada.