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

What we expect is often what we get …

In a recent post I posed the question of whether healthy ecology in rivers could be considered to be a “steady state” (see “Making what is important measurable …”). I asked this question because, following pioneering work by Brian Moss and others on the Norfolk Broads, the idea of “alternative steady states” in shallow lakes is well established. However, there is a deep-seated assumption that changes in rivers, and many other ecosystems, are gradual shifts along a continuous gradient: increase the “dose” of a pollutant or other pressure, and there is a concomitant “response” in the biology.   My earlier post referred to “good ecological status” as the goal of water management in Europe – implying that we should be trying to achieve a “state”.   Most of the approaches to ecological assessment define this state simply in terms of a threshold on a gradient but could there be other ways of interpreting such data?

Suppose that, for the sake of argument, algae in rivers exist in three “states” with respect to nutrients:

  • Low nutrients, high oxygen concentration – the natural “state” in most cases, where the river is naturally nutrient-poor and algae adapted to living with low concentrations of nutrients are selected.
  • High nutrients, high oxygen concentration – concentrations of inorganic nutrients are elevated due to agricultural or other enrichment, and conditions now favour competitive algae such as Cladophora over algae adapted to living in nutrient-stressed conditions.
  • High nutrients, low oxygen concentration – conditions associated with organic pollution, where there is substantial heterotrophic activity using up dissolved oxygen; conditions favour species of algae (such as some Nitzschia species) that can tolerate reducing conditions and which are facultative heterotrophs.   As this state is often associated with highly polluted conditions, nutrient concentrations will be higher than in the “high nutrient, high oxygen concentration” state.

If this model is true and we sampled diatoms across a number of similar rivers along a phosphorus gradient, then we might expect similar results from locations that shared the same state, as illustrated in the Fig. 1.   Note how the ranges for the different states overlap along our nutrient gradient.   Changes from one state to another are not driven solely by nutrient concentrations but may be induced by changes in other factors (e.g. grazing intensity).


Fig. 1.   Hyptothetical data assuming that algae in rivers exist in three alternative but overlapping “states”, which are expressed as three values of the Trophic Diatom Index (TDI): low nutrient, high oxygen (closed circles); high nutrient, high oxygen (open circles) and high nutrient, low oxygen (closed squares). Arrows indicate changes between the overlapping states.

Now let us assume that there is a second factor that can influence the composition of the diatom assemblage and, therefore, indices such as the TDI.   Local geology is known to have such effects, and can be summarised in terms of variables such as alkalinity or calcium concentration.   Let’s apply this variable at random by up to six TDI units to each level and plot the results:


Fig. 2. The same data as for Fig. 1 but this time with TDI values varying by ± 6 units due to a random variable.   Regression statistics: F: 48.8; P < 0.001; adjusted r2: 0.77.

This now looks less like three distinct stable states and more like the gradients that most stream ecologists like to see (especially if you ignore the three different symbols that I used to define the stable states). Gradients are, after all, amenable to all sorts of statistical methods including regression analysis and it is even possible to start contemplating predicting how the diatom assemblage might change if the phosphorus concentration was reduced by a known amount.   Of course, good ecologists should be aware of such factors, and control for them in any models that they construct but this does not always happen …

Finally, let’s assume that our second variable does not vary randomly but is, itself, weakly correlated with nutrients.   This time, the scatterplot looks even more impressive (see below). Yet it is the same scenario as in Fig. 1, only with some additional “noise” stirred in.   And I have only included a single additional factor when, in reality, there will be a number of different physical, chemical and biological factors working to influence the composition of the algal assemblage at any point in time and disguise the existence of three states.


Fig. 3. The same data as Figs 1 and 2 but this time with TDI values varying by ± 6 units due to a variable that is correlated with the x axis. Regression statistics: F: 152; P < 0.001; adjusted r2: 0.92.

As I said earlier, a good ecologist should understand these factors and control for them when building a model. However, this only ever works up to a point. Firstly, we can only control for what can be measured, and these additional measurements are limited by the resources available to a researcher as well as by the assumptions that s/he brings to the study design.   But this leads into my second point: we too often bring the assumption that we are observing changes along a gradient which, in turn, can make us blind to the possibility that the situation is more complex, and that we may be dealing with alternative stable states. The final point is that most of the studies from which inferences about algal ecology are made are based on spatial surveys with limited temporal coverage.   Any community that we observe in a river is the product both of the environment that we can try to capture with our measurements, but also of its history, and of events that may have taken place upstream. As Louis Pasteur once said, “fortune favours the prepared mind”. If we approach our data expecting to see a gradient then we are not surprised when, after some gentle cosseting with statistical package, a gradient usually appears.


I should point out, for the sake of completeness, that there is also a significant relationship between TDI and P for the data plotted in Fig. 1 (F: 46; P < 0.001; adjusted r2: 0.77).   My point is that it does not look like a gradient and a viewer is more likely to contemplate the possibility of alternative stable states.

I also suspect that these states can co-exist at the same site but more about this in a future post.

A good introduction to the application of alternative stable states to shallow lakes can be found in: Moss, B. (2010). Ecology of Freshwaters: A View for the Twenty-first Century. 4th Edition. Wiley-Blackwell, Chichester.

Baffled by the benthos (2)

So what can we learn from studying the diversity of stream ecosystems? First of all, I don’t think that we gain very much from using conventional “diversity indices”.   These have been explored ad nauseum by ecologists, usually for no better reason than that they are easy to calculate. I pointed out in a post in December 2013 (see “A Christmas turkey …”) that calculating diversity of just the diatoms was, in any case, a meaningless exercise as diatoms are part of a community that includes many other algae as well (a paper demonstrating this is referenced below).

As I was thinking about this, I remembered reading an insightful book by an anthropologist, Paul Richards on traditional farming methods in Sierra Leone.   He pointed out that subsistence farmers were not impressed by the modern varieties of rice that promised high yields and, instead, preferred traditional “land races”. These had a broader genetic base and, though they may not yield as much in a good year, there was a good chance that there were enough seeds with some drought resistance, flood-resistance, pest resistance and so on to ensure that they would always get a harvest, regardless of any unexpected events that may occur during the farming year. The land race, in other words, was resilient in a way that the highly-bred varieties were not.

Much has been written about how all diatoms have a unique niche and how this makes them extremely sensitive environmental indicators. The problem is that there is not much hard evidence to support such assertions.   I do not doubt that most diatoms do have unique requirements; however, there is no particular reason why these niches have to be determined solely by human pressures. Is it not also possible that factors such as fungal resistance might not apply to diatoms just as it does to crop plants?   There are a few tantalising hints that this might be the case but what would this mean for ecological status assessment?

The graphs below come from a study I was involved with, in which samples were collected from streams with different levels of human impact. We’ve divided them into two groups: those that are as close to pristine as you can get (“reference”) and those that have a measurable human impact (“non-reference”).   The left-hand plots show the number of species belonging to two common diatom genera, Achnanthidium and Gomphonema. The right-hand plots show the percent of the total number of diatoms recorded that belong to these two genera. In both of these instances, the number of species within the two genera is significantly higher (Wicoxon test) in reference sites.   I chose these two taxa because I have noticed that they do tend to be more diverse in cleaner sites, which makes it unlikely that we can explain differences in distributions purely in terms of different preferences for chemical variables.   My suggestion is that this diversity reflects a more fundamental resilience in the reference assemblages that is lacking in the impacted sites.


Differences in the number of taxa of Achnanthidium and Gomphonema recorded at reference and non-reference sites in an unpublished study of ecological conditions in streams in an EU Member State.

I have used the game Jenga as a visual analogy of what I think is happening in these samples.  The left-hand image below shows an intact tower of bricks which is equivalent, in this parable, to an unimpacted community (“high ecological status”).   The objective in this game is to remove bricks from the tower without it collapsing.   The EU’s definition of “good ecological status” is a slight change in composition and abundance which, in my analogy, equates to having a few bricks removed (as in the middle photograph). The ecosystem continues to function in a near-natural manner because the remaining taxa can fulfil the “services” that the missing taxa once provided.   However, if too many bricks are removed (the right hand image), the tower collapses.   This is equivalent to lower classes of ecological status (moderate, poor or bad).   Other organisms will move in to occupy the space and use the available resources, but this new community will be very different to that expected under natural conditions.


Jenga as a metaphor for ecological status: a. an intact tower of bricks, equivalent to pristine conditons, “high ecological status”; b. a few bricks are missing but the tower is still intact: “good ecological status”; c. several bricks have been removed and the tower has collapsed: “moderate ecological status” or worse.

The previous post described diversity in terms of a huge variety of microhabitats that are difficult for us to comprehend due to the differences in scale.   This post has taken a broader view of that hypothesis, suggesting that microhabitats will vary not just in space but also in time and, therefore, that the ecosystem can “bounce back” from short-term shocks rapidly, because other organisms can occupy the spaces left by those that cannot thrive and, as a result, higher trophic levels are still able to feed. In the same way that being able to recover from a cold or other bug is a characteristic of the healthy human, so having “resilience” to a short-term perturbation, whether natural or human-induced, is one property of a healthy ecosystem.


DeNicola, D.M. & Kelly, M.G. (2014). Role of periphyton in ecological assessment of lakes. Freshwater Science 33: 619-638.

Richards, P. (1985). Indigenous Agricultural Revolution. Ecology and Food Crops in West Africa. Hutchinson, London.

More about ecosystem services

The ideas discussed at last week’s conference on Ecosytem Services are still reverberating through my mind, particularly as I try to reconcile the competing needs of different water users.  It is not enough just to argue that managing towards a healthy “good status” ecosystem will bring undoubted benefits to all, as I tried to illustrate using the competing needs of wildlife and rowers on the River Wear in Durham.   Hard-line ecologists tend to think that the Water Framework Directive places an obligation on governments to manage towards Good Ecological Status in all water bodies but, in fact, there are clauses in the Directive which require governments to balance “costs” and “benefits”, which brings complications to any debates.

With these thoughts in mind, I put together a chart to illustrate how different activities which are grouped under the broad heading of “cultural ecosystem services” may relate to the general Water Framework Directive objectives of Good Ecological Status.  “Recreation” is one “cultural service” that we obtain from ecosystems, and “contact water sports” should, in theory, be one beneficiary of any investment in improved water quality (swimmers and canoeists have no desire to swallow mouthfuls of polluted water).  But what about those who just want to walk on the banks of lakes and rivers and enjoy the view?   I suspect that, so long as large-scale landscape features are intact (overhanging vegetation, some meanders) and the river does not have an unpleasant smell, the public would probably accept less than good status (or, at least, not see the need to spend the extra needed to achieve good status).


A diagram illustrating the relationship between recreational activities and ecological status.  The EU’s Water Framework Directive expresses the quality of an ecosystem in terms of five classes, from “high” to “bad”, with good status being the theoretical target that all water bodies should achieve.

And what about angling?  This is an activity where views will differ, even within the fishing community.   Game fishermen, in pursuit of salmon and trout, should benefit from efforts to improve rivers.  However, many coarse fish are less fussy about their habitats and there are even anecdotal accounts of fishermen complaining that the angling is poorer after water quality improvements.   Many types of pollution are the equivalent of spraying manure onto a pasture, fertilising the water and thereby enabling it to support a larger mass of fish.   Specialist carp fishermen represent the extreme position: their target species love rooting around in the bottom of shallow nutrient-rich lakes and ponds, so it is possible that they might even be happy with conditions  well below good status.   I might be wrong, but it would be interesting to compare angler’s perceptions of river and lake quality with the data that our current status assessments are based.   This is not to say that any particular user group is “right” or “wrong”, only that we may need to approach discussions about benefits of healthier ecosystems with our eyes wide open.

La Grand Assiette de Lac Léman


Lake Geneva / Lac Léman from the marina at Thonon-les-Bains in the early morning.

From Lyon, I travelled about 200 km along the course of the Rhône to Thonon-les-Bains, a resort beside Lake Geneva (“Lac Léman” in French) to join a meeting of diatom specialists.  There are few more appropriate places for me to give a talk on the need for intercalibration as we were just 500 metres or so from a large water body shared by two countries.   And this is not just a theoretical exercise as the many restaurants bordering were proudly serving lake fish.   Management of the lake, therefore, has direct consequences for local livelihoods.

Remember, too, that this lake is bordered by some large communities, most notably Geneva itself (just under 200,000 people), so there have been substantial inputs of pollution over the years.   As far back as 1880 Switzerland and France shared a common fisheries management policy but this broke down in 1911, after which a combination of overexploitation and pollution hit the fisheries hard.  Indeed, the most highly-prized fish in the restaurants in Thonon-les-Bains was “fera”, a member of the genus Corygonus, a member of the salmon family that is found in only a few lakes in the UK.  Corygonus fera, which was indigenous to Lake Geneva is, in fact, thought to be extinct.  It had a very distinct habitat in the deeper waters of the lake but as pollution increased, so the oxygen levels in these regions decreased.

Pollution levels have now decreased again and, since 1980,  Switzerland and France again have an agreement on management of the fishery.  The fera we were eating last week was a testament to the success of this policy.   It was not C. fera, but a close relative that had been introduced. The sheer quantity that was available around the lake suggests a highly productive fishery although it did lead me to wonder whether this would be sustained if the lake quality continued to improve.


La Grand Assiette de Lac Léman from Le Beau Rivage restaurant in Thonon-les-Bains, featuring a salmon tartare, smoked fera and a mousse also made from fera.  Plate of frites just visible on the right hand side of the picture and a glass of Chimay behind.

Think of the pollution in the lake as being equivalent to the manure you put on your garden.   In the lake this “feeds” the algae which, in turn, are eaten by the zooplankton, the main food of Corygonus.   If there is too much pollution/manure, the lake/garden suffers as the bacteria suck the oxygen out of the water/soil.   However, if lake / garden had just the “natural” nutrients, there would be a much lower quantity of produce available for the fishermen / gardener to remove.   Somewhere in between, there is a state with just enough nutrients to support a productive fishery / garden.  It may not be “natural”, but it does represent a balance, of sorts, between nature and economy.  I can’t, in other words, extol the beauty of the environment, and the virtues of conservation and, simultaneously, praise the local delicacies without at least a minor twinge of conscience.


Buttiker, B. (2005). Evolution of fish and crayfish, and of fishery in Lake Geneva.   Archives des Sciences 58: 183-191.

Laurent, P.J. (1972). Lac Léman: effect of exploitation, eutrophication, and introductions on the salmonid community.   Journal of the Fisheries Research Board of Canada 29: 867-875.

Lake Geneva / Lac Léman also feature in William Boyd’s recent novel Waiting for Sunrise.