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.

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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 Janet 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.

The way things were …

Writing the previous post led me to contemplate how much things had changed over the time that I have been working in this field.  Back in the early 1990s when I first set out to look at the response of diatoms to nutrients in streams, few in the National Rivers Authority (NRA, predecessor to the Environment Agency) regarded phosphorus as a serious pollutant in rivers, and most biologists thought about ecological quality solely in terms of organic pollution and invertebrates.   In order to investigate the effect of nutrients, I wanted to visit sites where organic pollution was not a problem.

I was helped in this task by the work done by biologists at the then Institute for Freshwater Ecology (now Centre for Ecology and Hydrology) who had just developed the early versions of RIVPACS (“River Invertebrate Prediction and Classification System”) which established the principle of expressing ecological quality as the observed quality / expected quality.  This, in turn, required an ability to predict the “expected” condition for any stream.   The work that had developed these equations started from a dataset of invertebrate and environmental data collected from a wide range of “unpolluted” running water sites which, in those far off days, was compiled by asking biologists working for the Regional Water Authorities (predecessors to the NRA) for their recommendations of sites that were of “good” or “fairly good” quality.  Nowadays, screening sites to be used for calibrating ecological methods is a much more rigorous procedure but this was the first tentative step on a long journey and “expert judgement” was as good a place to start as any.

The paper that emerged from this exercise (see reference below) analysed data from these “unpolluted” sites and classified them into eight groups.  Each of these groups consisted of sites that shared similar invertebrate assemblages which reflected similarities in the habitat, from upland, fast flowing becks to deep, wide slow-flowing rivers in the lowlands.  The authors included a useful table that listed the physical and chemical characteristics of each of these groups and I noticed that the phosphorus concentrations reported for these spanned a very wide range.   This meant that I could use these as the basis for putting together a sampling program that spanned a long gradient of nutrient pressure without the complications of organic pollution.   The outcome of that work was the first of the two papers referenced in my previous post.

Time has moved on and I thought it would be interesting to revisit these “unpolluted” sites to see how they would be classified using the UK’s current standards for phosphorus.  This highlights a striking difference between the prevailing idea of “unpolluted” in the early 1980s and the present day, as all of these groups had average concentrations that equate to substantial enrichment by modern standards; in half the groups this average concentration would be classified as “poor status” whilst the maximum concentrations in three groups equates to “bad status”.   Whatever way you look at it now, these sites were far from “unpolluted”.

Classification of TWINSPAN end-groups of unpolluted river sites in Great Britain based on Armitage et al. (1984) along with average and maximum phosphorus concentrations recorded in each group and the phosphorus status based on current environmental standards.  M = moderate status; P = poor status; B = bad status.

I am not being critical of the approach taken by Patrick Armitage and colleagues.  In many ways, I regard the work of this group as one of the most significant contributions to the science of ecological assessment in my lifetime.   I am just intrigued to see how the thinking of ecologists and regulators has moved on in the thirty years or so since this paper was published.  I know from my own early conversations with NRA biologists that inorganic nutrients were not perceived as a problem in rivers until the early 1990s.   It was probably the European Community’s Urban Wastewater Treatment Directive (UWWTD) that started to draw the attention of biologists in the UK to these problems, and which led to the development of stricter environmental standards for nutrients, though not without opposition from several quarters.

This, then is a situation where good legislation provided the impetus needed to start the process.  There were places in the UK – rivers in the Norfolk Broads, for example – where nutrients were already being regulated, but these were special circumstances and nutrient problems in most rivers were largely ignored. Indeed, as I said in my previous post, phosphorus was not even measured routinely in many rivers.   I heard via my professional grapevine that it was the Netherlands who had made the case for the clauses in the UWWTD concerning regulating nutrients, as their stretches of the lower Rhine were subject to numerous problems caused by unregulated inputs of nutrients from countries upstream.   I do not know if this is true, but it is certainly plausible.   However, once the need to control eutrophication in rivers was codified in UK law, then the debate about how to evaluate it started, one of the outcomes of which was more funding for me to develop the Trophic Diatom Index (referenced in the previous post).  And, gradually, over time, concentrations in rivers really did start to fall (see “The state of things, part 2”).   I’d like to think the TDI played a small part in this; though this might also mean that I am partially responsible for the steep increase in water charges that everyone endured in order to pay for better water quality …

Reference

Armitage, P.D., Moss, D., Wright, J.F. & Furse, M.T. (1984).  The performance of a new biological water quality score system based on macroinvertebrates over a wide range of unpolluted running-water sites.  Water Research 17: 333-347.

An open letter to Andrea Leadsom

You said something in your speech to the Conservative Party conference earlier this week that intrigued me, and I wondered if you would mind explaining exactly what you meant?  Of course, I may be reading too much into your words, which I only heard your talk because I was up stupidly early, and listened to Farming Today over breakfast.

My ears pricked up when I heard you say: “I’m truly excited that our departure from the EU means we can develop policies that are tailored to our most precious habitats and wildlife not a one-size-fits-approach for 28 Member States.”   Those are fine words but, I’m afraid I need to push you for some details.   I’ve done a lot of work on the implementation of EU environment policies over the past quarter of a century and I’m not absolutely sure where your idea that EU environment policy adopts a “one-size-fits-all approach” comes from.   The Water Framework Directive, for example, sets out general principles to ensure sustainable water supplies for Europe in the main text, but the extensive annexes give considerable scope for each Member State to tailor these principles to their own circumstances.   Even to drop the phrase “one-size-fits-all” into your talk suggests to me that you have not mastered your brief and that fills me – and other environmental professionals – with a sense of foreboding about the future of the UK environment.

However, you have not been doing the job for very long so we should give you the benefit of the doubt.   Your talk was strong on fine-sounding words but rather short on specifics.  So an easy solution to the problem may be for you to give us just one example from each of the Habitats and Water Framework Directives explaining the type of changes that your department will be looking to enact to strengthen environmental protection over and above the provisions of existing legislation.   Of course, I note that you said “… we can develop policies…” rather than “… we are developing policies …” but I am sure that you would not have said this if there were not civil servants within DEFRA currently considering just this type of option.   It is hardly an issue that is going to affect Brexit negotiations so you don’t need to resort to Theresa May’s argument of the need for discretion, and it will surely enhance your credibility among those voters who are genuinely concerned about wildlife and the environment.

One problem that I have is that you, and fellow Brexiteers, put a lot of emphasis on the red tape that Brussels generates.    Environmental and wildlife legislation often needs a “carrot” and a “stick” and that “stick” can very easily be interpreted by those on the receiving end as “red tape”.   A legitimate reading of your suggestion is that farmers and water companies may be subject to more, not less, regulation as a result of our exit from the EU.   That is counter-intuitive, given all that you, Farage, Gove and others claimed during the referendum campaign and is going to take some explaining, if it really is the case.  Once again, a couple of examples of what these new policies will look like will reassure us all.

And this brings me onto my final point: enactment of both EU policy and of your vision will only work if there are properly resourced regulators and, in my experience, the Environment Agency and Natural England have been struggling over the last few years.  Better environmental management will, of course, need more high calibre and well-resourced staff in both agencies.    Please don’t roll out that tired old mantra of greater efficiency: there is only a finite number of times this can be used before it loses credibility and, I am afraid, your predecessors have squeezed this particular argument dry.

Credibility is, unfortunately, the key word here.   Environmental professionals were very strongly in favour of “remain”, recognising the high quality of the legislation that comes out of Brussels in this field.   You came into this job without any strong track record in environment or agriculture and, I suggest, maybe you need to temper your enthusiasm for changing the status quo at least until you have mastered your brief.   An assurance that current EU legislation will not be revoked or watered down would be a good first step.   Despite claims by some of your colleagues that there was a decisive vote in favour of leaving, 48 per cent of voters want to remain.   That’s a lot of people who will be looking hard at your government’s performance come the next General Election.   Remember, too, that wildlife and conservation charities can run very effective campaigns when they think politicians are making a hash of things and that you only have a slim majority at the moment.   In other words, get this wrong and things can only end badly for you …