Follow the data, stupid …

A perennial problem with ecology is that it is a discipline that is far better at describing problems than it is at solving them. The Water Framework Directive (WFD) encapsulates this: after nineteen years, we have a pretty good idea of the condition of Europe’s waters but have made very little progress in restoring the half that do not yet achieve good ecological status.

The reason for this is, I suspect, because describing the problem is a task that lies squarely within the remit of a scientist whilst finding solutions requires interactions that go beyond the boundaries of science, encountering vested interests along the way.   The agricultural sector’s enthusiasm for the environment is tempered by their desire to maximise yield and earn a living from the land, politicians are wary of regulations that may deter business or raise prices for the consumer and all of us are too wedded to the luxuries that the modern world offers.

The WFD can be seen as an embodiment of the social contract, articulated by philosophers such as Thomas Hobbes whereby individuals forego some rights in order to transcend the state of nature (“… nasty, brutish and short.”) and give us access to the benefits of an ordered society.  In this case, we all consent to forego some freedoms in return for a share in the benefits that a healthy aquatic environment will bring to all of us.   “Freedom” might seem like a weighty word in this context but anyone who has watched their sewerage charges creep steadily upwards over the past twenty years should recognise this as the price we pay for the freedom to flush away life’s less desirable by-products.

The problem is defining the point at which we hand over our natural rights to a higher authority.   We understand this when driving: an urban speed limit of 30 miles per hour reflects the point at which the risk we pose to other road users are deemed societally unacceptable and our right to drive as fast as we wish has to be curtailed.  If we can translate that principle into environmental governance then we can set “speed limits” for the major pressures that impact on the aquatic environment.   How do we get from an ecologist’s understanding of a “healthy” river (“good ecological status”, in WFD parlance) to the “speed limit” for nutrients, widely recognised as one of the major pressures affecting both freshwater and marine systems?

That’s been the focus of some work I’ve been doing under the auspices of the European Commission’s Joint Research Centre, one strand of which has just been published in Science of the Total Environment.  This paper looked at the threshold concentrations for nutrients (phosphorus and nitrogen) used by EU countries, noting the very wide range of values chosen as the national “speed limit”.   The situation is complicated because, just as is the case for roads, different types of rivers require different limits and we had to look for variation between countries amidst an array of variation within countries.   What emerged, however, was a clear relationship between the threshold values and the method used to set the standard.  Those that had applied statistical or modelling techniques to national data generally had tighter thresholds than those that relied upon “expert judgement”.  I’ve included the two figures from this paper that make this point.

Poikane_et_al_2019_Fig7

Range of good/moderate lake phosphorus (a) and nitrogen (b) threshold values grouped by method used to determine the value. Different letters indicate groups that are statistically different (p ≤ 0.05).   Fig. 7 from Poikane et al. (2019).

“Expert judgement” is one of those slippery terms that often creeps into official reports.   There needs to be space within a decision-making process for an experienced professional to see through the limitations of available evidence and present a reasoned alternative.  However, “expert judgement” too often becomes a shorthand for cutting corners and, in this case, grabbing numbers from the published literature that seem vaguely plausible.  There is also a darker side because, having unhitched decision-making from the evidence, “expert judgement” can become a euphemism for the “art of the possible”.  I have seen this occur during discussions around setting and revising river phosphorus standards in the UK: the regulators themselves are under pressure to balance environmental protection with economic development and tight standards can potentially limit what can be done in a catchment.

Another of our recent papers (this one’s not open-access, I’m afraid) shows that setting standards using empirical models is far from straightforward and we also recognise that standard setting is just one part of a longer process of nutrient management.   However, setting inappropriate standards simply as an expedience seems completely barmy, as you are never going to attain your desired ecological benefits.   The cynical view might be that, as the process of environmental change is invariably greater than the electoral cycle, there is limited accountability associated with such decisions, compared with more immediate political capital kudos from bringing investment and jobs to a region.

Poikane_et_al_2019_Fig8

Range of good/moderate river phosphorus (a) and nitrogen (b) threshold values grouped method used to determine the value. Different letters indicate groups that are statistically different (p ≤ 0.05).   Fig. 8 from Poikane et al. (2019).

All of our work has shown that, in most cases, the relationship between biology and nutrients is weak and, for this reason, large datasets are needed if robust inferences are to be drawn.  This leads to one further consequence of our work: setting environmental standards may only be possible if countries pool their data in order to produce big enough datasets with which to work.  This is particularly the case for smaller countries within the EU, but also applies to water body types that may be relatively infrequent in one country but are more widespread elsewhere.   I had recent experience of this when working on the Romanian stretches of the Danube: they simply did not have a wide enough gradient of conditions in their own territory, and we had to incorporate their data into a larger dataset in order to see the big picture (see “Beyond the Tower of Babel …”).    Writing about the benefits of international collaboration as the Brexit deadline looms obviously has a certain irony, but it needs to be said.  Far from being the distant and unaccountable law maker of Brexiteer mythology, in this field the European Commission has been quietly encouraging Member States to share experience and promote best practice.  One can only speculate about the future of the UK environment once free of Brussels oversight.

References

Philips, G., Teixeira, H., Poikane, S., Salas, F. & Kelly, M.G. (2019).   Establishing nutrient thresholds in the face of uncertainty and multiple stressors: a comparison of approaches using simulated data sets.   Science of the Total Environment684: 425-433.

Poikane, S., Kelly, M.G., Salas Herrero, F., Pitt, J.-A., Jarvie, H.P., Claussen, U., Leujak, W., Solheim, A.L., Teixera, H. & Phillips, G. (2019).  Nutrient criteria for surface waters under the European Water Framework Directive: Current state-of-the-art, challenges and future outlook.  Science of the Total Environment 695.  

Note on figures:

The methods used by Member States to derive nutrient thresholds are described in more detail in Poikane et al. (2019).   In brief, the approaches are:

1 – regression between nutrient and biological response;

2 – modelling;

3 – distribution of nutrient concentrations in water bodies classified (using ecological criteria) as high, good or moderate status;

4 – distribution of nutrient concentrations in all water bodies using an arbitrary percentile;

5 – expert judgement.  This includes values taken from the literature or from older European Directives. For example, for nitrate, the common use of the value 5.65 mg-N L−1 in freshwaters is likely to be derived from the guideline value of 25 mg L−1 of nitrate in the Nitrates Directive (91/676/EEC) or now repealed Drinking Water Directive (80/778/EC).

6 – The so-called OSPAR Comprehensive Procedure is used widely in coastal and transitional waters. In this, a water body is considered to be an ‘Eutrophication Problem Area’ if actual status deviates 50% or more from reference conditions.

7 – insufficient information.

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Tales from prehistory

Stonehenge_Aug19

Microscopes and Monsters has been quiet for a couple of weeks, as I have been on holiday, part of which was spent “off grid” at the Green Man Festival in Wales.  From there, we headed to London for a Proms concert (two music festivals in a week!) via the Cotswolds and the ancient landscapes of Salisbury Plain.

My first visit to Stonehenge was 50 years ago, at which time you could pull off the A303 and wander amongst the columns unconstrained by fences and barriers.   Now the visitors are guided to a visitor centre two kilometres from the site, and offered a shuttle bus after being relieved of £20.  Or, if you prefer, you can walk across Salisbury Plain to the monument.  On a sunny afternoon in August this becomes part of the experience as there are ancient burial mounds (some pre-dating Stonehenge) both alongside the path and dotted around the horizon.   Stonehenge itself gradually rose up ahead of us, and we experienced a little of what the ancients must have felt as they approached Stonehenge along the processional way.

The last time that I was here was a stop off between field work on the nearby River Wylye and a meeting in Reading.   At the time I was engaged with two separate projects concerned with the health of chalk streams, which are characteristic of this part of southern England.   The approach we used elsewhere in the country was to compare what we found in samples we collected with what we expected to find if that site was in a pristine condition.

There was, at the time, a vigorous debate about how this “reference condition” should be defined.   This debate had a theoretical component (epitomised by Brian Moss’ paper in the reference list) but also a more pragmatic element (encapsulated by the other paper).  This was necessary because an ultra-strict, but theoretically sound, approach might not yield enough data from which a robust prediction of the “expected” ecology could be derived.   In essence, we searched out remote regions of the UK where population density was low and agriculture was not intensive and used these to derive our understanding of what to expect in the more densely-populated regions of the country.

Avebury_Aug19

Part of Avebury stone circle, Wiltshire, August 2019.  The photograph at the top of the post shows Stonehenge.

This worked quite well (although Brian Moss, predictably, had his own pithy thoughts on the approach).  However,  we simply could not find any sites that fulfilled our criteria of low population density and a low intensity of farming in those parts of lowland Britain where the underlying geology was Jurassic limestone, Cretaceous chalk or another formation that resulted in very hard water.  Our estimates of ecological health in such regions depend, as a result, on extrapolation and judgement rather than evidence.   That is all well and good for an academic journal but, in the case of the River Wylye, Wessex Water were being asked to spend hundreds of thousands of pounds to upgrade sewage works and, rightly, felt that they needed something more in order to explain the consequent price rises to their customers.

The OS maps of the region around my sampling points on the Wylye were dotted with symbols marking ancient monuments (long and round barrows, in particular) and the huge, mysterious religious sites of Stonehenge and Avebury lie just to the east.  Together, they point to continuous occupation of the area for over four thousand years, which means that it is hardly a surprise that we found no sites that met our criteria for a “pristine” stream.   The chalk streams of southern England are famous and rightly regarded as a threatened habitat, but they are not natural.  It is better to think of them as aquatic equivalents to hay meadows or hedgerows: ecologically-rich habitats that have been created by human activity, rather than as a result of “natural” ecological processes.

That means that it we need to diverge from a strict definition of “reference conditions” in order to set a baseline for ecological expectations in such circumstances.  For macrophytes – the larger aquatic plants – there is an expectation that the flora in this baseline state will be rich; however,  this assumption does not work for the microscopic algae in chalk streams.  We also found that river stretches where the macrophytes are thriving and, apparently, healthy, often have diatoms that suggest nutrient enrichment.  That is a puzzle for which we think we may have a solution, and which I will write about in a future post.

Silbury_Hill_Aug19

Silbury Hill, part of the Avebury World Heritage Site.  It is a Neolithic site whose original purpose is unknown though, to a visitor from north-east England, it looks remarkably like a slag heap.

We use low population density and absence of intensive agriculture as a proxy for “natural” in the uplands but need to treat this assumption with care too.  There might be fewer grand Neolithic monuments in the north of England or Scotland but signs of ancient habitation are there if you care to look (see “More reflections from the dawn of time”).   The moorland where these streams rise is, itself, an artificial habitat, created when early agriculturalists removed the natural tree cover.  Modern streams in these areas are, therefore, exposed to more light than in their primeval states and that will have important consequences for the plant life that lives within them.  They may be the best we have, but are hardly “natural”.

Two factors, both highly pragmatic, brought this debate to a close.   The first was realisation that, whatever the rights and wrongs of purist versus practical standpoints, most of our rivers are very degraded and alterations in the approach used to define the “expected” condition would be unlikely to change this broad scale picture.   About sixty-five per cent of our rivers fail to achieve good ecological status despite the flaws in the reference concept.  The second factor was simply that, since the financial crisis in the 2008-2010, the UK environment agencies have had too few resources to improve the reference concept.   As any such “improvement” will almost certainly make the true state of UK rivers look even worse than it does at the moment, a more cynical argument is that few of the bureaucrats involved in the process have any great enthusiasm for the task anyway.

References

Moss, B. (2008).  The Water Framework Directive: total environment or political compromise.  Science of the Total Environment400: 32-41.

Pardo, I., Gómez-Rodríguez, C., Wasson, J.G., Owen, R., van de Bund, W., Kelly, M., Bennett, C., Birk, S., Buffagni, A., Erba, S., Mengin, N., Murray-Bligh, J. & Ofenböeck, G. (2012).  The European reference condition concept: A scientific and technical approach to identify minimally-impacted river ecosystems.  Science of the Total Environment420: 33-42.

 

The Imitation Game

About a year ago, I made a dire prediction about the future of diatom taxonomy in the new molecular age (see “Murder on the barcode express …“).   A year on, I thought I would return to this topic from a different angle, using the “Turing Test” in Artificial Intelligence as a metaphor.   The Turing Test (or “Imitation Game”) was derived by Alan Turing in 1950 as a test of a machine’s ability to exhibit intelligent behaviour, indistinguishable from that of a human (encapsulated as “can machines do what we [as thinking entities] can do?”).

My primary focus over the past few years has not been the role of molecular biology in taxonomy, but rather the application of taxonomic information to decision-making by catchment managers.   So my own Imitation Game is not going to ask whether computers will ever identify microscopic algae as well as humans, but rather can they give the catchment manager the information they need to make a rational judgement about the condition of a river and the steps needed to improve or maintain that condition as well as a human biologist?

One of the points that I made in the earlier post is that current approaches based on light microscopy are already highly reductionist: a human analyst makes a list of species and their relative abundances which are processed using standardised metrics to assign a site to a status class. In theory, there is the potential for the human analysts to then add value to that assignment through their interpretations.  The extent to which that happens will vary from country to country but there two big limitations: first, our knowledge of the ecology of diatoms is meagre (see earlier post) and, in any case, diatoms represent only a small part of the total diversity of microscopic algae and protists present in any river.   That latter point, in particular, is spurring some of us to start exploring the potential of molecular methods to capture this lost information but, at the same time, we expect to encounter even larger gaps in existing taxonomic knowledge than is the case for diatoms.

One very relevant question is whether this will even be perceived as a problem by the high-ups.  There is a very steep fall-off in technical understanding as one moves up through the management tiers of environmental regulators.   That’s inevitable (see “The human ecosystem of environmental management…“) but a consequence is that their version of the Imitation Game will be played to different rules to that of the Environment Agency’s Poor Bloody Infantry whose game, in turn, will not be the same as that of academic taxonomists and ecologists.  So we’ll have to consider each of these versions separately.

Let’s start with the two extreme positions: the traditional biologist’s desire to retain a firm grip on Linnaean taxonomy versus the regulator’s desire for molecular methods to imitate (if not better) the condensed nuggets of information that are the stock-in-trade of ecological assessment.   If the former’s Imitation Game consists of using molecular methods to capture the diversity of microalgae at least as well as human specialists, then we run immediately into a new conundrum: humans are, actually, not very good at doing this, and molecular taxonomy is one of the reasons we know this to be true.  Paper after paper has shown us the limitations of taxonomic concepts developed during the era of morphology-based taxonomy.  In the case of diatoms we are now in the relatively healthy position of a synergy between molecular and morphological taxonomy but the outcomes usually indicate far more diversity than we are likely to be able to catalogue using formal Linnaean taxonomy to make this a plausible option in the short to medium-term.

If we play to a set of views that is interested primarily in the end-product, and is less interested in how this is achieved, then it is possible that taxonomy-free approaches such as those advocated by Jan Pawlowski and colleagues, would be as effective as methods that use traditional taxonomy.   As no particular expertise is required to collect a phytobenthos sample, and the molecular and computing skills required are generic rather than specific to microalgae, the entire process could by-pass anyone with specialist understanding altogether.  The big advantages are that it overcomes the limitations of a dependence on libraries of barcodes of known species and, as a result, that it does not need to be limited to particular algal groups.  It also has the greatest potential to be streamlined and, so, is likely to be the cheapest way to generate usable information.   However, two big assumptions are built into this version of the Imitation Game: first, there is absolutely no added value from knowing what species are present in a sample and, second, that it is, actually, legal. The second point relates to the requirement in the Water Framework Directive to assess “taxonomic composition” so we also need to ask whether a list of “operational taxonomic units” (OTUs) meets this requirement.

In between these two extremes, we have a range of options whereby there is some attempt to align molecular barcode data with taxonomy, but stopping short of trying to catalogue every species present.  Maybe the OTUs are aggregated to division, class, order or family rather than to genus or species?   That should be enough to give some insights into the structure of the microbial world (and be enough to stay legal!) and would also bring some advantages. Several of my posts from this summer have been about the strange behavior of rivers during a heatwave and, having commented on the prominence and diversity of green algae during this period, it would be foolish to ignore a method that would pick up fluctuations between algal groups better than our present methods.   On the other hand, I’m concerned that an approach that only requires a match to a high-level taxonomic group will enable bioinformaticians and statisticians to go fishing for correlations with environmental variables without needing a strong conceptual behind their explorations.

My final version of the Imitation Game is the one played by the biologists in the laboratories around the country who are simultaneously generating the data used for national assessments and providing guidance on specific problems in their own local areas.   Molecular techniques may be able to generate the data but can it explain the consequences?  Let’s assume that method in the near future aggregates algal barcodes into broad groups – greens, blue-greens, diatoms and so on, and that some metrics derived from these offer correlations with environmental pressures as strong or stronger than those that are currently obtained.   The green algae are instructive in this regard: they encompass an enormous range of diversity from microscopic single cells such as Chlamydomonas and Ankistrodesmus through colonial forms (Pediastrum) and filaments, up to large thalli such as Ulva.   Even amongst the filamentous forms, some are signs of a healthy river whilst others can be a nuisance, smothering the stream bed with knock-on consequences for other organisms.   A biologist, surely, wants to know whether the OTUs represent single cells or filaments, and that will require discrimination of orders at least but in some cases this level of taxonomic detail will not be enough.   The net alga, Hydrodictyon(discussed in my previous post) is in the same family as Pediastrumso we will need to be able to discriminate separate genera in this case to offer the same level of insight as a traditional biologist can provide.   We’ll also need to discriminate blue-green algae (Cyanobacteria) at least to order if we want to know whether we are dealing with forms that are capable of nitrogen fixation – a key attribute for anyone offering guidance on their management.

The primary practical role of Linnaean taxonomy, for an ecologist, is to organize data about the organisms present at a site and to create links to accumulated knowledge about the taxa present.    For many species of microscopic algae, as I stressed in “Murder on the barcode express …”, that accumulated knowledge does not amount to very much; but there are exceptions.  There are 8790 records on Google Scholar for Cladophora glomerata, for example, and 2160 for Hydrodictyon reticulatum.  That’s a lot of wisdom to ignore, especially for someone who has to answer the “so what” questions that follow any preliminary assessment of the taxa present at a site.  But, equally, there is a lot that we don’t know and molecular methods might well help us to understand this.   There will be both gains and losses as we move into this new era but, somehow, blithely casting aside hard-won knowledge seems to be a retrograde step.

Let’s end on a subversive note: I started out by asking whether “machines” (as a shorthand for molecular technology) can do the same as humans but the drive for efficiency over the last decade has seen a “production line” ethos creeping into ecological assessment.   In the UK this has been particularly noticeable since about 2010, when public sector finances were squeezed.   From that point on, the “value added” elements of informed biologists interpreting data from catchments they knew intimately started to be eroded away.   I’ve described three versions of the Imitation Game and suggested three different outcomes.  The reality is that the winners and losers will depend upon who makes the rules.  It brings me back to another point that I have made before (see “Ecology’s Brave New World …”): that problems will arise not because molecular technologies are being used in ecology, but due to how they are used.   It is, in the final analysis, a question about the structure and values of the organisations involved.

References

Apothéloz-Perret-Gentil, L., Cordonier, A., Straub, F., Iseili, J., Esling, P. & Pawlowksi, J. (2017).  Taxonomy-free molecular diatom index for high-throughput eDNA monitoring.   Molecular Ecology Resources17: 1231-1242.

Turing, A. (1950).  Computing machinery and intelligence.  Mind59: 433-460.

The Catchment Data Explorer

One of the things I like to do on this blog is to draw out the links between the microscopic and human worlds, and also to explain how we measure the extent of human impacts on the aquatic environment, and what we can do to reverse significant negative impacts.   My professional life is largely concerned with how the evidence for these evaluations is gathered and used to arrive at decisions.  Lip service has always been paid to the importance of transparency in this process but it has not always been easy to find information about the condition of your local environment.  So a few months ago I was pleased to find a new website from the Environment Agency that makes this process a lot easier.

The Catchment Data Explorer starts with some intuitive navigation panes that let you search for your part of England, and then to locate particular streams, rivers and lakes and see how these match up to current environmental targets.   Navigating to my local river, the River Wear, and, more specifically, to the section closest to my house (“Croxdale Beck to Lumley Park Burn”), I find a table with drop-down tabs that give a brief overview of its state.    I see from this that the overall condition of the river is “moderate” and, then, by opening-up further levels, see that the various components of the ecology are all good (I’m not sure that I agree with that for the microscopic algae but that’s a story for another day) but that “physico-chemical supporting elements” are “moderate”.   Classification of rivers and lakes follows the “one out, all out” rule, so it is the lowest class that is measured that determines overall status.   In this case, opening up the physico-chemical elements levels in the table, I see that all is well, except for phosphorus, which is moderate and, therefore, determines the classification.

The home page of the Catchment Data Explorer

From here we can also download a file of “reasons for not achieving good status” in order to understand why phosphorus levels are elevated which tells us that it is waste water treatment and urban drainage that is the most likely source of phosphorus in the catchment.    Control that and, in theory, all should be well.   However, these are just two rows of 147 in a spreadsheet which deals with the lower Wear catchment and its tributaries, so the scale of overall challenge facing the Environment Agency becomes clear.    Moreover, the Wear has already had over £7M investment to install phosphorus stripping from the larger sewage works, to comply with the Urban Wastewater Treatment Directive, so the potential for further improvement is already limited.   Go back to the original table and look at the right hand column, which is labelled “objectives”.   The ecological target is “good by 2027”; however, if you hover the cursor over this, a box pops up telling you that this is “disproportionately expensive” and “technically infeasible”, invoking the WFD’s notorious “Get Out of Jail Free” card which lets countries bypass the need to achieve good status in certain specified situations (clause 4 paragraph 5 – “Less Stringent Objectives”).

Water body classification information from the Catchment Data Explorer for the River Wear, between Croxdale Beck and Lumley Park Burn.

All good so far.   The problems come when you start burrowing deeper into the Catchment Data Explorer and, in particular, when you download data.   There is a lot of information in Excel spreadsheets (which is great); however, it is riddled with jargon and not very well interpreted.   Then there are some apparent contradictions that are not explained. I searched for one stream that interested me, and found the overall ecological status to be moderate, despite the status of the fish being poor.  There is probably a good reason for this (perhaps there was low confidence in the data for fish, for example) but, again, it is not very well explained.

Then there are those water bodies that are, apparently, “good status” but, when you delve deeper into the Catchment Data Explorer, you find that there is no evidence to support this.   This is a surprisingly common situation, not just in the UK but across Europe.  The phrase “expert judgement” is invoked : probably meaning that someone from the local Environment Agency office went along for a look around and could not see any obvious problems.   It seems to be used, in the UK at least, mostly for smaller water bodies and is probably a pragmatic decision that limited resources can be better used elsewhere.

These are relatively minor niggles when set against the positives that the Catchment Data Explorer offers.   There is already quite a lot of information in the Help pages, and there is also a Glossary, so you should be able to work out the situation for your local water bodies with a little patience.   A struggle with terminology is, perhaps, inevitable, given the complexities of managing the environment.  We would all do well to remember that.

 

A brief history of time-wasting …*

Having talked about diversity on a microscale in the previous post, I thought it would be interesting to place this in context by looking at the variations that I have observed in the River Wear at Wolsingham over the past decade or so.   The River Wear has seen some significant improvements in water quality over this period, but those have mainly affected sections of the river downstream from Wolsingham.  Most of the changes at Wolsingham are, therefore, giving us some insights into the range of natural variation that we should expect to see in a river.

I’ve got 31 samples from the River Wear at Wolsingham on my database, collected since 2005.  Over this period, nine different diatom species have dominated my counts: Achnanthidium minutissimum on 21 occasions, Nitzschia dissipata twice and Cocconeis euglypta, Encyonema silesiacum, Gomphonema calcifugum, Navicula lanceolata, Nitzshia archibaldii, N. paleacea and Reimeria sinuata once each.   I also have records for non-diatoms during 2009, during which time the green alga Ulothrix zonata, and two Cyanobacteria, Phormidium retzii and Homeothrix varians were the dominant alga on one occasion each.   In total, I have recorded 131 species of diatom from this one reach, although only I’ve only found 91 of them more than once, and only 59 have ever formed more than one percent of the total.   I’ve also got records of 22 species other than diatoms.

This – along with my comments in “The mystery of the alga that wasn’t there …” raises questions about just how effective a single sample is at capturing the diversity of algae present at a site.  .    In 2009 I collected a sample every month from Wolsingham and the graph below shows how the total number of species recorded increased over that period.   Typically, I find between 20 and 30 species in a single sample, and each subsequent month revealed a few that I had not seen in earlier samples.   Importantly, no single sample contained more than 40 per cent of the total diversity I observed over the course of the year.  Part of this high diversity is because of the greater effort invested but there is also a seasonal element, as I’ve already discussed.   The latter, in particular, means that we need to be very careful about making comments about alpha diversity of microalgae if we only have a single sample from a site.

Increase in the number of diatom taxa recorded in successive samples from the River Wear at Wolsingham.  In 2009 samples were collected monthly between January and December whilst in 2014 samples were collected quarterly. 

This seasonal pattern in the algal community also translates into variation in the Trophic Diatom Index, the measure we use to evaluate the condition of streams and rivers.  The trend is weak, for reasons that I have discussed in earlier posts, but it is there, nonetheless.   Not every river has such a seasonal trend and, in some cases, the community dynamics results in the opposite pattern: higher values in the summer and lower values in the winter.  It is, however, something that we have to keep in mind when evaluating ecological status.

Variation in the Trophic Diatom Index in the River Wear at Wolsingham between 2005 and 2015, with samples organised by month, from January (1) to December (12).   The blue line shows a LOESS regression and the grey band is the 95% confidence limits around this line.

All of these factors translate into uncertainty when evaluating ecological status.   In the case of the River Wear at Wolsingham, this is not particularly serious as most of the samples indicate “high status” and all are to the right of the key regulatory boundary of “good status”.  However, imagine if the histogram of EQRs was slid a little to the left, so that it straddled the good and moderate boundaries, and then put yourself in the position of the people who have to decide whether or not to make a water company invest a million pounds to improve the wastewater coming from one of their sewage treatment plants.

At this point, having a long-term perspective and knowing about the ecology of individual species may allow you to explain why an apparent dip into moderate status may not be a cause for concern.  Having a general sense of the ecology of the river – particularly those aspects not measured during formal status assessments – should help too.  It is quite common for the range of diatom results from a site to encompass an entire status class or more so the interpretative skills of the biologists play an important role in decision-making.   Unfortunately, if anything the trend is in the opposite direction: fewer samples being collected per site due to financial pressures, more automation in sample and data analysis leading to ecologists spending more time peering at spreadsheets than peering at stream beds.

I’ve never been in the invidious position of having to make hard decisions about how scarce public sector resources are used.  However, it does strike me that the time that ecologists used to spend in the field and laboratory, though deemed “inefficient” by middle managers trying to find cost savings, was the time that they learned to understand the rivers for which they were responsible.  The great irony is that, in a time when politicians trumpet the virtues of evidence-led policy, there is often barely enough ecological data being collected, and not enough time spent developing interpretative skills, for sensible decisions to be made.   Gathering ecological information takes time.   But if that leads to better decisions, then that is not time wasted …

Ecological Quality Ratio (EQR: observed TDI / expected TDI) of phytobenthos (diatoms) at the River Wear, Wolsingham) between 2005 and 2015.   Blue, green, orange and red lines show the positions of high, good, moderate and poor status class boundaries respectively.

* the title is borrowed from the late Linda Smith’s BBC Radio 4 comedy series

Winning hearts and minds …

I write several of my posts whilst travelling, though am always conscious of the hypocrisy of writing an environmentally-themed blog whilst, at the same time, chalking up an embarrassing carbon footprint.  Last month, however, I participated in my first “eConference”, in which the participants were linked by the internet.  With over 200 people from all over Europe, and beyond, attending for all or part of the three days, there was a substantial environmental benefit and whilst there was little potential for the often-useful “off-piste” conversations that are often as useful as the formal programme of a conference, there were some unexpected benefits.  I, for example, managed to get the ironing done whilst listening to Daniel Hering and Annette Battrup-Pedersen’s talks.

You can find the presentations by following this link: https://www.ceh.ac.uk/get-involved/events/future-water-management-europe-econference.   My talk is the first and, in it, I tried to lay out some of the strengths and weaknesses of the ways that we collect and use ecological data for managing lakes and rivers.  I was aiming to give a high level overview of the situation and, as I prepared, I found myself drawing, as I often seem to do, on medical and health-related metaphors.

At its simplest, ecological assessment involves looking at a habitat, collecting information about the types of communities that are present and match the information we collect to knowledge that we have obtained from outside sources (such as books and teachers) and from prior experience in order to guide decisions about future management of that habitat. At its simplest, this may involve categoric distinctions (“this section of a river is okay, but that one is not”) but we often find that finer distinctions are necessary, much as when a doctor asks a patient to articulate pain on a scale of one to ten.  The doctor-patient analogy is important, because the outcomes from ecological assessment almost always need to be communicated to people with far less technical understanding than the person who collected the information in the first place.

I’ve had more opportunity than I would have liked to ruminate on these analogies in recent years as my youngest son was diagnosed with Type I diabetes in 2014 (see “Why are ecologists so obsessed with monitoring?”).   One of the most impressive lessons for me was how the medical team at our local hospital managed to both stabilise his condition and teach him the rudiments of managing his blood sugar levels in less than a week.   He was a teenager with limited interest in science so the complexities of measuring and interpreting blood sugar levels had to be communicated in a very practical manner.  That he now lives a pretty normal life stands testament to their communication, as much to their medical, skills.

The situation with diabetes offers a useful parallel to environmental assessment: blood sugar concentrations are monitored and evaluated against thresholds.  If the concentration crosses these thresholds (too high or too low), then action is taken to either reduce or increase blood sugar (inject insulin or eat some sugar or carbohydrates, respectively).   Blood sugar concentrations change gradually over time and are measured on a continuous scale.  However, for practical purposes they can be reduced to a simple “Goldilocks” formula (“too much”, “just right”, “not enough”).  Behind each category lie, for a diabetic, powerful associations that reinforce the consequences of not taking action (if you have even seen a diabetic suffering a “hypo”, you’ll know what I mean).

Categorical distinctions versus continuous scales embody the tensions at the heart of contemporary ecological assessment: a decision to act or not act is categorical yet change in nature tends to be more gradual.   The science behind ecological assessment tends to favour continuous scales, whilst regulation needs thresholds.  This is, indeed, captured in the Water Framework Directive (WFD): there are 38 references to “ecological status”, eight in the main text and the remainder in the annexes.  By contrast, there are just two references to “ecological quality ratios” – the continuous scale on which ecological assessment is based – both of which are in an annex.   Yet, somehow, these EQRs dominate conversation at most scientific meetings where the WFD is on the agenda.

You might think that this is an issue of semantics.  For both diabetes and ecological assessment, we can simply divide a continuous measurement scale into categories so what is the problem?   For diabetes, I think that the associations between low blood sugar and unpleasant, even dangerous consequences are such that it is not a problem.  For ecological assessment, I’m not so sure.  Like diabetes, our methods are able to convey the message that changes are taking place.  Unlike diabetes, they are often failing to finish the sentence with “… and bad things will happen unless you do something”.   EQRs can facilitate geek-to-geek interactions but often fail to transmit the associations to non-technical audiences – managers and stakeholders – that make them sit up and take notice.

I’d like to think that we can build categorical “triggers” into methods that make more direct links with these “bad things”.  In part, this would address the intrinsic uncertainty in our continuous scales (see “Certainly uncertain …”) but it would also greatly increase the ability of these methods to communicate risks and consequences to non-technical audiences (“look – this river is full of sewage fungus / filamentous algae – we must do something!”).   That’s important because, whilst I think that the WFD is successful at setting out principles for sustainable management of water, it fails if considered only as a means for top-down regulation.   In fact, I suspect that Article 14, which deals with public participation, is partly responsible for regulators not taking action (because “costs” are perceived as disproportionate to “benefits”) than for driving through improvements.   We need to start thinking more about ensuring that ecologists are given the tools to communicate their concerns beyond a narrow circle of fellow specialists (see also “The democratisation of stream ecology?”).   Despite all the research that the WFD has spawned, there has been a conspicuous failure to change “hearts and minds”.  In the final analysis, that is going to trump ecological nuance in determining the scale of environmental improvement we should expect.

It’s all about the algae

Just a short post to point you all towards an article I wrote for Royal Society of Biology’s magazine The Biologist.  It is a broad overview of the reasons why we use algae to assess the condition of our lakes and rivers in Europe and is illustrated with three of Chris Carter’s beautiful images, and the print edition will have even more of these.  Take the figure legends with a pinch of salt (we didn’t write these!): neither Tolypella nor Chaetophora are particularly common in the UK.   Navicula, on the other hand, is common but the legend makes no mention of this.

Whilst I have your attention, I will also point you towards a short article that I wrote for the most recent Phycological Bulletin, the newsletter of the Phycological Society of America.  This offers a few more hints to anyone thinking about entering the Hilda Canter-Lund competition next year.