Finding the balance …

Gammarus fossarum (Scale bar: 1 millimetre).  Photograph: Drew Constable.

Back in March I wrote about the challenges facing those who planned to implement Next Generation Sequencing (NGS) methods for ecological assessment (see “Ecology’s Brave New World”).  In that post I argued that the success (or otherwise) of using DNA for ecological assessment was as much down to the structure and values of the organisation implementing the method as to the method itself.   More particularly, there were likely to be problems if the process was viewed primarily as a means of gathering ecological data rather than for enhancing the capabilities of ecologists.

This is an important distinction.  Much of an ecologist’s time is spent collecting the basic data, whether in the field or laboratory, from which the condition of a particular habitat can be inferred.   But, with traditional methods, there was always a possibility that this basic data collection could be supplemented by observations and insights made by the ecologist that would inform their judgements.  These people have also added to our knowledge of the UK’s biodiversity over the years (see “A new diatom record from Sussex” for an example).   My fear is that adoption of NGS approaches in order to reduce costs will limit the potential for ecologists to make these serendipitous additions to our understanding of a habitat.

A recent paper by Rosie Blackman and colleagues from the University of Hull and Environment Agency offers a good example of how traditional and DNA-based methods can be complementary.  Rosie had looked at invertebrate assemblages in rivers in England using both approaches and discovered that some of the DNA in her samples came from a species, Gammarus fossarum, not previously recorded in the UK.  Other representatives of this genus of small crustaceans, including the extremely common G. pulex, had been abundant in her samples.  Now, however, going back to her sites with the knowledge that G. fossarum might also be present, she was on the lookout for the subtle differences in morphology that separated G. fossarum from other Gammarus species.  She found it in large numbers at 23 out of 28 sites, spread around the country, and in historical material stored at the Natural History Museum dating back to 1964, suggesting that it has been overlooked by those identifying it by traditional means.

This is a great example of biologists working in the sweet zone where traditional and molecular methods combine to give us new insights that are greater than the sum of their parts.   The shortcomings of traditional morphology-based taxonomy in the past are clear but, at the same time, this was essential for verification step once the presence of Gammarus fossarum had been detected by molecular approaches.   The obvious conclusion is that regulatory organisations should move into the future using both traditional and molecular methods in a complementary manner.   Yet, if you look at that statement from another perspective, I have just advocated increasing the cost of ecological assessment at a time when budgets for such assessments are under extreme pressure.

The likelihood is that, as molecular methods are developed (and if they are shown to be substantially cheaper), traditional approaches to ecological assessment will be dropped.  That would not be a problem were it not that the hours spent in the field and laboratory are an important pathway for graduate ecologists to deepen their understanding of organisms and habitats.   Shifting wholesale to molecular methods without retaining at least some infrastructure for traditional methods will mean first, that future discoveries such as Rosie’s will be harder to validate and, second, that the next generation of ecologists will first encounter these organisms not in a pond net but on a spreadsheet.  That link between a name and an organism with distinctive qualities, and between that organism and particular habitats or conditions, will be lost.

Equally, it is unrealistic to assume that complementary use of both approaches will be the norm.   That will place yet more pressure on already tight budgets and could only happen if everyone was happy to accept that monitoring networks could be much smaller (see “Primed for the unexpected?”).  So how do we retain this “sweet zone” between old and new?   I have not yet heard a satisfactory answer to that question so perhaps we should return to the point I made earlier about the structure and values of the organisations that take on these new methods.  Broadly speaking, the adoption of these methods purely to save money is likely to be the road to perdition, because these savings will look most impressive to the senior levels of management (who are probably not biologists) only if there is a wholesale move to the new methods with no retention of traditional infrastructure.

The tragedy is that, within a decade, molecular technology may have moved on to such an extent that it is possible for a biologist to detect invasive species and make other assessments in real time, rather than having to send samples off to remote high-throughput laboratories in order to maximise economies of scale.  Instruments such as Oxford Nanopore’s Minion are still not the finished article from the point of view of ecological end-users, but it is only a matter of time.   Unfortunately, in the here and now, the infrastructure that generates ecological data is already being dismantled in order to squeeze cost-savings from the shift to NGS.   Whether there will be anyone left to inherit this Brave New World is, I am afraid, open to debate.

Two examples of Oxford Nanopore’s Minion portable DNA analysis systems, which can be plugged into the USB port of a laptop.

Reference

Blackman, R.C., Constable, D., Hahn, C., Sheard, A.M., Durkota, J., Hänfling, B. & Lawson Handley, L. (2017).  Detection of a new non-native freshwater species by DNA metabarcoding of environmental samples – first record of Gammarus fossarum in the UK.  Aquatic Invasions 12 (in press)

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It’s just a box …

illumina_MiSeq_linocut

Today’s post starts with a linocut of an Illumina MiSeq Next Generation Sequencer (NGS), as part of an ongoing campaign to demystify these state-of-the-art £80,000 pound instruments. It’s just a box stuffed with clever electronics.   The problem is that tech-leaning biologists go misty-eyed at the very mention of NGS, and start to make outrageous claims for what it can do.   But how much are they actually going to change the way that we assess the state of the environment?   I approach this topic as an open-minded sceptic (see “Replaced by a robot?” and “Glass half full or glass half empty?” and other posts) but I have friends who know what buttons to press, and in what order. Thanks to them, enough of my samples have been converted into reams of NGS data for me now to be in a position to offer an opinion on their usefulness.

So here are three situations where I think that that NGS may offer advantages over “traditional” biology:

  1. reducing error / uncertainty when assessing variables with highly-contagious distributions.
    Many of the techniques under consideration measure “environmental DNA” (“eDNA”) in water samples. eDNA is DNA released into water from skin, faeces, mucus, urine and a host of other ways.   In theory, we no longer need to hunt for Great Crested Newts in ponds (a process with a high risk of “type 2 errors” – “false negatives”) but can take water samples and detect the presence of newts in the pond directly from these.  The same logic applies to lake fish, many of which move around the lake in shoals, which may be missed by sampler’s nets altogether or give false estimates of true abundance.   In both of these cases, the uncertainties in traditional methods can be reduced by increasing effort, but this comes at a cost, so methods based on eDNA show real potential (the Great Crested Newt method is already in use).
  2. Ensuring consistency when dealing with cryptic / semi-cryptic species
    I’ve written many posts about the problems associated with identifying diatoms.   We have ample evidence, now, that there are far more species than we thought 30 years ago. This, in turn, is challenging the ability to create consistent datasets when analysts spread around several different laboratories are trying to make fine distinctions between species based on a very diffuse literature.   Those of us who study diatoms now work at the very edge of what can be discriminated with the light microscope and the limited data we do now have from molecular studies suggests that there are sometimes genetic differences even when it is almost impossible to detect variation in morphology.   NGS has the potential for reducing the analytical error that results from these difficulties although, it is important to point out, many other factors (spatial and temporal) contribute to the overall variation between sites and, therefore, to our understanding of the effect of human pressures on diatom assemblages.
  3. Reducing costs
    This is one of the big benefits of NGS in the short term.   The reduction in cost is partly a result of the expenses associated with tackling the first two points by conventional means.   You can usually reduce uncertainty by increasing effort but, as resources are usually limited, this increase in effort means channelling funds that could be used more profitably elsewhere.   However, there will also be a straightforward time saving, because of the economies of scale that accompanies high-throughput NGS.   A single run of an Illumina MiSeq can process 96 samples in a few hours, whereas each would have required one to two hours for analysis by light microscope. Even when the costs of buying and maintaining the NGS machines are factored in, NGS still offers a potential cost saving over conventional methods.

It is worth asking whether these three scenarios – statistical, taxonomic and financial – really amount to better science, or whether NGS is just a more efficient means of applying the same principles (“name and count”) that underpins most ecological assessment at present.   From a manager’s perspective, less uncertainty and lower cost is a beguiling prospect.   NGS may, as a result, give greater confidence in decision making, according to the current rules. That may make for better regulation, but it does not really represent a paradigm shift in the underlying science.

The potential, nonetheless, is there. A better understanding of genetic diversity, for example, may make it easier to build emerging concepts such as ecological resilience into ecological assessment (see “Baffled by the benthos (2)” and “Making what is important measurable”). Once we have established NGS as a working method, maybe we can assess functional genes as well as just taxonomic composition?   The possibilities are endless.  The Biomonitoring 2.0 group is quick to make these claims.   But it is important to remember that, at this stage, they are no more than possibilities   So far, we are still learning to walk …

Reference

Baird, D.J. & Hajibabaei, M. (2012). Biomonitoring 2.0: a new paradigm in ecosystem assessment made possible by next-generation DNA sequencing. Molecular Ecology 21: 2039-2044.

Glass half full or glass half empty?

UKeDNAWG_Bangor

I’m tapping away at the back of a conference hall during the UK eDNA working group at the University of Bangor, absorbing the latest developments in the use of molecular technologies for applied ecology. Things have moved fast over the last couple of years, with one method, for the detection of Great Crested Newt, having moved out of the research laboratory and into widespread use. Several other methods – including our own method for ecological assessment using diatoms – are drawing close to the stage where their adoption by end-users is a real possibility, and lots more good ideas were bouncing around during the sessions and during the breaks.

The fascination of much of this work lies in the interplay between the new and the old, using the sensitivity of molecular tools to push our understanding of what traditional methods have told us. At the same time, the new methods are largely underpinned by libraries of reference barcode sequences that provide the essential link between the ‘old’ and the ‘new’, and these are wholly dependent upon specialists rooted in old-school taxonomy.

Here’s the rub: if the goal is to produce methods for ecological assessment, then the point will come when the research scientists step back and the end-users start to use it.   At this point, real world exigencies take over and, with the public sector battered by funding cuts, any opportunity to save money will be grasped. What this means is that we cannot assume the same depth of ecological knowledge in the users as in the developers. This was not always the case as the Environment Agency had a cadre of extremely capable ecologists, with a deep knowledge their local rivers and broad understanding of ecology. I don’t believe that this was knowledge that they were taught, rather that they learnt it on the job, seeing streams in all of their moods as they collected samples, poring over identification guides as they named their specimens and sharing knowledge with colleagues.   The result was a depth of understanding which, in turn, they drew upon to advise colleagues involved in regulation and catchment management.

In the last few years this system has come under scrutiny as managers have searched for cost savings. Environment Agency biologists are no longer expected to collect their own samples, which are taken for them by a separate team in the misguided assumption that highly-trained biologist will be more productive if they stay in the laboratory and focus on using their specialist identification skills. Moving to molecular techniques will just continue this process.   Once the excitement of the research is over, the methods will be ripe for economies of scale; sample processing will be a task for molecular biological technicians, and the first time an ecologist encounters the sample it will be as processed output from a Next Generation Sequencing machine.

The function of the laborious process of collecting and analysing ecological samples is not just to produce the data that underpins evidence-driven catchment management. It also allows biologists to acquire the experience that lets them interpret these data sensitively and wisely.   The urge to find short-term savings has focussed on the quantifiable (how many samples can a laboratory process) and ignored the unquantifiable (how good is the advice that they offer their colleagues?).   I don’t think the full calamity of what we are seeing will hit for a few years because most of the ecology staff in the Environment Agency have done their apprenticeships in the field. Over time, however, a new generation will join the organisation for whom computer print-outs may be the closest they get to encountering river and stream life.

I am basically enthusiastic about the potential that molecular technologies can offer to the applied ecologist but we do need to be aware that implications of these approaches extend beyond issues of analytical performance characteristics and cost. This is because ecology is more about making lists of what organisms we find at a particular location (and, judging by the presentations, this seems to be the focus of most current studies) but about what those organisms do, and how they fit together to form ecosystems and food webs. OK, so you can read about Baetis rhodani in a textbook, but that is never going to be the same experience as watching it scuttle across the tray where you’ve dumped the contents of your pond net, or of observing a midge larva graze on algae under a microscope. The problem is that we cannot put a value on those experiences, in the same way that the cost of processing a sample can be calculated.

This is a theme that I’ve explored several times already (see “When a picture is worth a thousand base-pairs …”, “Simplicity is the ultimate sophistication: McEcology and the dangers of call centre ecology” and “Slow science and streamcraft”) but it bears repeating, simply because it is an issue that falls through the cracks of most objective appraisals of ecological assessment.   The research scientists tend to see purely in terms of the objective collection and interpretation of data, whilst managers look at it in terms of the cost to produce an identifiable product.   It is more than both of these: it is a profession.   The challenge now is to integrate molecular methods into the working practices of professional “frontline” ecologists, and how we prevent this professionalism being degraded to a series of technical tasks, simply because the bean counters have worked out that this is the most efficient way to distribute their scarce resources around the organisation.

Notes

Biggs, J., Ewald, N., Valentini, A., Gaboriaud, C., Dejean, T., Griffiths, R.A., Fosterd, J., Wilkinson, J.A., Arnell, A., Brothertone, P., Williams, P. & Dunna, F. (2015). Using eDNA to develop a national citizen science-based monitoring programme for the great crested newt (Triturus cristatus). Biological Conservation 183: 19-28.