What’s a pretty diatom like you doing in a place like this?

Whilst looking at some samples from an experiment conducted on mesocosms beside a chalk stream, Candover Brook in Hampshire for Mark Ledger and colleagues, I came across a diatom that I had not seen before and which, at first glance, was out of place.   As the images above show, it is a diatom whose cells join together to form chains which, in turn, means that they typically present their sides to the viewer rather than the valve face, which is the way that the writers of identification guides generally assume that we can see. It took some time to track down a couple of cells that were lying face-upwards so that I could try to name the species and some of the few that were lying this way were damaged (see left hand image), perhaps itself a consequence of the naturally strong links between the cells.

Naming the genus was relatively straightforward: the valve shape, fine striae and very narrow axial area (the gap along the median line of the valve face between the two rows of striae) coupled with the tendency to form chains all pointed to Fragilariforma.   However, most of the Fragilariforma that  I encounter are in soft water, often acid habitats whilst this sample was from a flume beside a chalk stream in southern England.   After scratching my head a little more, and sending images to my friend Lydia in Germany, I eventually decided that Fragilariforma nitzschioides was the most likely name for this diatom.  Searching through my records, I found only one other record for this species: from the River Itchen (into which Candover Brook drains) in the mid-1990s.  That must be more than coincidence.   Interestingly, Hoffman et al. (2011) describe the species as “rare” and say that its ecological preferences are “difficult to define”.

The limited records that we have show that this species does not behave in the same way as most other representatives of the genus.   The weighted average of pH for the genus is 6.6 (see graph below), but there are plenty of records extending into more acid waters.  By contrast, the River Itchen population was recorded at pH 8.1 and the pH in Candover Brook will be very similar.   Most of the records for the genus came from relatively soft water, in contrast to the very hard water found in a chalk stream.  The scarcity of records of a species that is well described in the literature also suggests that this might be a genuinely rare diatom (see “A “red list” of endangered British diatoms”).

One other peculiarity of this species is the name itself.   Fragilariforma was one of a number of genera split away from Fragilaria by Dave Williams and Frank Round in 1986, originally as “Neofragilaria”.  Fragilaria nitzschoides, was not formally transferred at the time, presumably because the authors did not have access to the type material.  They presented good evidence for this new genus but a few people – notably Horst Lange-Bertalot – have continued to group these species under Fragilaria.   This is the situation in Diatomeen im Süsswasser-Benthos von Mitteleuropa but, curiously, for Fragilaria nitzschoides, he created the new combination of “Fragilariforma nitzschoides” purely as a synonym (see p. 268).   The good news is that the next version of this book (see “Tales of Hoffman”) does use these new names.

The relationship between Fragilariforma spp and pH (left) and alkalinity (right) in UK rivers, based on the mid-1990s dataset described in “The challenging ecology of a freshwater diatom”.  Vertical lines show the boundaries for high (blue), good (green), moderate (orange) and poor (red) status classes based on current UK standards and the arrows show the location of the River Itchen population of Fragilariforma nitzschoides along these gradients. 

References

Hofmann, G., Werum, M. & Lange-Bertalot, H. (2011).   Diatomeen im Süßwasser-Benthos von Mitteleuropa. A.R.G. Gantner Verlag K.G., Rugell.

Williams, D.M. & Round, F.R. (1987).  Revision of the genus Fragilaria.  Diatom Research 2: 267-288.

Williams, D.M. & Round, F.R. (1988).  Fragilariforma nom nov., a new generic name for Neofragilaria Williams & Round.  Diatom Research 3: 265-267.

Comparing comparisons …

Several of the speakers at the DNAqua-net meeting in Essen described work that, essentially, produced a molecular genetic-based “mirror” of current assessment procedures.  That is what we have done and it is a sensible first step because it helps us to understand how the data produced by Next Generation Sequencing (NGS) relate to our current understanding, based on traditional ecological methods.   The obvious way to make such a comparison is to generate both “old” and “new” indices from samples collected from a range of sites spread out along an environmental gradient, and then to look at the relationship between these.   A scatter plot gives you a good visual indication of the nature of the relationship whilst the correlation coefficient indicates its strength.  All well and good but consider the two plots below.   These are based on artificial data that I generated in such a way that both had a Pearson’s correlation coefficient of about 0.95, indicating a highly significant relationship between the two variables.   However, the two plots differ in one important respect: points on the left hand plot are scattered around the diagonal line (indicating slope = 1, i.e. both indices give the same outcome) whilst those on the right hand plot are mostly below this line.

The work that we have done over the past ten years or so means that we are fairly confident that we understand the performance of our traditional indices and, more importantly, that we can relate these to the concepts of ecological status as set out in the Water Framework Directive.   This means that we need to be able to translate these concepts across to any new indices that might replace our existing approaches and the right hand plot indicates one potential problem: at high values, in particular, the new method consistently under-estimates condition compared with the old method.   Note, however, that this has not been picked up by the correlation coefficient, which is the same for both comparisons and, in this post, I want to suggest a better way of comparing two indices.

I made some comparisons of this nature in a paper that I wrote a few years ago and one of the peer reviewers suggested that, rather than use a correlation coefficient I should, in fact, use Lin’s concordance correlation coefficient, which measures the relationship between two variables in terms of their deviation from a 1:1 ratio.  This is an approach widely used in pharmacology and epidemiology to ensure that drugs give equivalent performance to any that they might replace and there is, as a result, a command for performing this calculation within a library of statistical methods for epidemiologists written for R: epiR.   Having downloaded and installed this library, calculation is straightforward:

The standard Pearson’s correlation coefficient can be computed from a base function in R as:

> cor.test(x,y)

And then we load the epiR library:

> library (epiR)

before calculating Lin’s concordance correlation coefficient as:

> epi.ccc(x,y)

If we calculate this coefficient of concordance on the data used to generate each of the plots above we see that it is 0.95 for the left-hand plot (i.e. very similar to Pearson’s correlation coefficient) but only 0.74 for the right hand plot: quite a different result.

Having identified a deviation from a 1:1 relationship, discussion can spin off in several directions.   For the diatoms, for example, we are recognising that data produced by NGS is fundamentally different to that produced by traditional methods and that the number of “reads” associated with a cell does not necessarily align with our traditional counting unit of the frustule (cell wall) or valve.   It is a product partly of cell size, partly of the number of chloroplasts and partly, I suspect, on a variety of environmental factors that we have not yet started to investigate.   The NGS data are not “wrong”, but they are different and using these data without cognisance of the problem might lead to an erroneous conclusion about the state of a site.   So we then have to think about how to rectify this problem, which might involve applying correction factors so that “traditional” indices can continue to be used or deriving new NGS-specific coefficients, which is the approach we have adopted in the UK.   Both approaches have pros and cons but that is a subject for another day …

References

Kelly, M.G. & Ector, L. (2012) Effect of streamlining taxa lists on diatom-based indices: implications for intercalibrating ecological status.  Hydrobiologia 695: 253-263.

Lin, L. I.-K., 1989. A concordance correlation coefficient to evaluate reproducibility. Biometrics 45: 255–268.

Ecology’s Brave New World …

My travels have brought me to the kick-off conference of DNAqua-net at the University of Duisburg-Essen in Germany, to give a plenary talk on our progress towards using high throughput next generation sequencing (NGS) for ecological assessment.   I went into the meeting feeling rather nervous as I have never given a full length talk to an audience of molecular ecologists before but it was clear, even before I stood up, that we were in the almost unique position of having a working prototype that was under active consideration by our regulatory bodies.   Lots of the earlier speakers showed promising methods but few had reached the stage where adoption for nationwide implementation was a possibility.   There was, as a result, audible intake of breath as I mentioned, during my talk, that, from 2017, samples would no longer be analysed by light microscopy but only by NGS.

That, in turn, brought some earlier comments by Florian Leese, DNAqua-net chair, into sharp focus.  He had talked about managing the transition from “traditional” ecology to the Brave New World of molecular techniques; something that weighs heavily on my mind at the moment.   In fact, I said, in my own talk, that the structures and the values of the organisations that were implementing NGS were as important as the quality of the underlying science.   And this, in turn, raised another question: what is an ecologist?

If that sounds too easy, try this: is an ecologist more than just someone who collects ecological data?   I have put the question like this because one likely scenario for routine use of environmental DNA, once in routine use, is that sampling will be delegated to lowly technicians who will dispatch batches to large laboratories equipped with the latest technology for DNA extraction, amplification and sequencing on an enormous scale (see “Replaced by a robot?”) and the results will be fed into computer programs that generate the answer to the question that is being posed.

The irony, for me, is that the leitmotif of my consultancy since I started has been helping organisations apply ecological methods consistently across the whole country so that the results generate represent real differences in the state of the environment and not variations in the practice or competence of the ecologists who collected the data.  Over the past decade, I helped co-ordinate the European Commission’s intercalibration exercise, which extended the horizons of this endeavour to the extremities of the European Union.   The whole process of generating ecological information had to be broken down into steps, each has been taken apart and examined and put back together to, we hoped, produce a more effective outcome.  There was, nonetheless, ample opportunity for the ecologist to bring higher cognitive skills to the process, in sampling and surveying, species identification and, ultimately, in interpreting the data.

I often use the example of McDonalds as a model for what we are trying to achieve, simply because it is a brand with which everyone is familiar and we all know that their products will taste the same wherever we go (see “Simplicity is the ultimate sophistication …“).   I admire them for that because they have achieved what ecologists involved in applying EU legislation should desire most: a completely consistent approach to a task across a territory.   But that same consistency means that one is never tempted to pop into a McDonalds on the off chance that the chef has popped down to the market to buy some seasonal vegetables with which to whip up a particularly appetising relish.   If you want the cook to have used his or her higher cognitive abilities to enhance your dining experience you do not go to a McDonalds.

But that is where we could end up as we go down the road of NGS.  A reader of my post “A new diatom record from West Sussex” commented tartly that there would be no chance of that diatom being spotted once the Environment Agency replaced their observant band of diatom analysts by NGS and he was right.   Another mentioned that he had recently passed on a suspicion of a toxic pollution event to the local staff based on observations on the sample that were not captured by the metrics that are used to classify ecological status.  Again, those insights will not be possible in our Brave New World.

Suppose we were somehow able to run a Monte-Carlo permutation test on all the possible scenarios of where we might be in twenty years, in terms of the application of NGS to ecological assessment.  Some of those outcomes will correspond to Donald Baird’s vision of “Biomonitoring 2.0” but some will not and here, for the sake of playing Devil’s Advocate, is a worst-case scenario:

In an effort to reduce costs, a hypothetical environmental regulator outsources eDNA sampling to a business service company such as Group 4 or Capita.   They batch the samples up and dispatch them to the high throughput laboratory that provides the lowest quote.   The sequencing results are uploaded straight to the Cloud and processed according to an automated “weight of evidence” template by data analysts working out of Shanghai, Beijing or Hyderabad before being passed back to staff in the UK.   At no point is a trained ecologist ever required to actually look at the river or stream.  I should stress that this “year zero” scenario will not come about because NGS is being used but because of how it is used (and a post in the near future will show how it is possible to use NGS to enhance our understanding of the UK’s biodiversity).   It brings us back to the question of the structure and values of the organisation.

What I would like to see is a system of ecological assessment that makes full use of the higher cognitive abilities of the biologists responsible for ecological assessment.  Until now a lot of a biologist’s skill goes into identifying organisms in order to make the list of species upon which assessments are based.  It should be possible to use the new genetic technologies to free ecologists to play a greater role in interpretation and decision-making.  However, that will not come about when they are being used in situations where there is an overwhelming desire to reduce costs.  One of the lessons that we need to learn, in other words, is that there is more to applying molecular ecology than simply developing the method itself.

Reference

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

 

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.

The challenging ecology of a freshwater diatom?

amp_pedi_pollybrook

Amphora pediculus from Polly Brook, Devon, December 2016. Scale bar: 10 micrometres (= 1/100th of a millimetre).

The images above show one of the commonest diatoms that I find in UK waters.  It is a tiny organism, often less than 1/100th of a millimetre long, which means that it tests the limits of the camera on my microscope.  In recent months, however, it is not just the details on Amphora pediculus’ cell wall that I am struggling to resolve: I also find myself wondering how well we really understand its ecology.

The received wisdom is that Amphora pediculus favours hard water, does not like organic pollution and is relatively tolerant of elevated concentrations of inorganic nutrients.  This made it a very useful indicator species in a period of my career when we were using diatoms to identify sewage work s where investment in nutrient-removal technology might yield ecological benefits.  There were many nutrient-rich rivers, particularly in the lowlands, where any sample scraped from the upper surface of a stone was dominated by these tiny orange-segment-shaped diatom valves.   Unfortunately, twenty years on, many of those same rivers have much lower concentrations of nutrients (see “The state of things, part 2”) but still have plenty of Amphora pediculus.   Did I get the ecology of this species wrong?

The graph below shows some data from the early- and mid- 1990s showing how the abundance of Amphora pediculus was related to phosphorus.   The vertical lines on this graph show the average position of the boundaries between phosphorus classes based on current UK standards.   Records for A. pediculus are clustered in the “moderate” and “poor” classes, supporting my initial assertion that this species is a good indicator of nutrient-enriched conditions, but there are also samples outside this range where it is also abundant, so A. pediculus is only really useful when it is one of a number of strands of evidence.

aped_v_p

The relationship between Amphora pediculus and reactive phosphorus in UK rivers, based on data collected in the early-mid 1990s.  Vertical lines show the average boundaries between high and good (blue), good and moderate (green), moderate and poor (orange) and poor and bad (red) status classes based on current UK standards and the two arrows show the optima based on this dataset (right) and data collected in the mid-2000s (left).

If we weight each phosphorus measurement in the dataset by the proportion of Amphora pediculus at the same site (i.e. so that sites where A. pediculus is abundant are given greater weight), we get an idea of the point on the phosphorus gradient where A. pediculus is most abundant.   We can then infer that this is the point at which conditions are most suitable for the species to thrive.  In ecologist’s shorthand, this is called the “optimum” and, based on these data, we can conclude that the optimum for A. pediculus is 154 ug L-1 phosphorus.  The right hand arrow indicates this point on the graph below. However, I then repeated this exercise using another, larger, dataset, collected in the mid-2000s.   This yielded an optimum of 57 ug L-1 phosphorus (the left hand arrow on the graph), less than half of that suggested by the 1990s dataset.   There are, I think, two possible explanations:

First, the 1990s phosphorus gradient was based on single phosphorus samples collected at the same time that the diatom sample was collected (mostly spring, summer and autumn) whilst the mid-2000s phosphorus gradient was based (mostly) on the average of 12 monthly samples.  As phosphorus concentrations, particularly in lowland rivers, tend to be higher in summer than at other times of the year, it is possible that part of the difference between the two arrows is a result of different approaches.  (For context, in the 1990s, when I first started looking at the effect of nutrients in rivers, phosphorus was not routinely measured in many rivers, so we had no option but to do the analyses ourselves, and certainly did not have the budget or time to collect monthly samples).

However, another possibility is that the widespread introduction of phosphorus stripping in lowland rivers in the period between the mid-1990s and mid-2000s means that the average concentration of phosphorus in the rivers where conditions favour Amphora pediculus have fallen.   In other words, A. pediculus is tolerant of high nutrient conditions but is not that bothered about the actual concentration.   My guess is that it thrives under nutrient-rich conditions so long as the water is well-oxygenated and, as biochemical oxygen demand is generally falling, and dissolved oxygen concentrations rising (see “The state of things, part 1”), this criterion, too is widely fulfilled.   I suspect that both factors probably contribute to the change in optima.

But the second point in particular raises a different challenge:  We often slip into casual use of language that implies a causal relationship between a pressure such as phosphorus and biological variables whereas, in truth, we are looking at correlations between two variables.   Causal relationships are, in any case, quite hard to establish and the effect that we call “eutrophication” is really the result of interactions between a number of factors acting on the biology.   All of these simplifications mean that it is useful, from time to time, to look back to see if assumptions made in the past still hold.   In this case, I suspect that some of our indices might need a little fine-tuning.  There is no disgrace in this: the evidence we had in the 1990s led us to both to a conclusion about the relative sensitivity of Amphora pediculus to nutrients but also fed into a large-scale “natural experiment” in which nutrient levels in UK rivers were steadily reduced.   When we evaluate the results of that natural experiment we see we need to adjust our hypotheses.  That’s the nature of science.  As the sign on the door of a friend who is a parasitologist reads: “if we knew what we were doing, it wouldn’t be research”.

References

The 1990s dataset (89 records) is mostly based on data used in:

Kelly M.G. & Whitton B.A. (1995).   A new diatom index for monitoring eutrophication in rivers.   Journal of Applied Phycology 7: 433-444.

The mid-2000s dataset (1145 records) comes from:

Kelly, M.G., Juggins, S., Guthrie, R., Pritchard, S., Jamieson, B.J., Rippey, B, Hirst, H & Yallop, M.L. (2008).   Assessment of ecological status in UK rivers using diatoms.   Freshwater Biology 53: 403-422.

Tales of Hofmann …

freshwater_benthic_diatoms_

For the past five years or so the constant companion on my desk whilst I stare down my microscope has been a thick tome (2.8 kg) entitled Diatomeen im Süßwasser-Benthos von Mitteleuropa by Gabi Hofmann and colleagues.  It serves as my aide-mémoire when I am analysing freshwater diatoms, jogging my memory when I see a diatom that I recognise but whose name I have forgotten.  Before this was published, I used a French publication Guide Méthodologique pour la mise en oeuvre de l’Indice Biologique Diatomées which was free to download (I cannot find a link on the web any longer, unfortunately).   Neither of these is the last word in diatom taxonomy, but that was not the point: a lot of the time, I just need a gentle reminder of the right name for the species I am looking at, and I don’t want to have to pore through a pile of books in order to find this.

One of the strong points of both books is that they are copiously illustrated, and the plates are arranged very logically so that similar-shaped diatoms are together, making it easy to pick out differences.   For most routine identification, this is exactly what is needed: we may pretend that we are logical people but, in truth, pattern matching beats using a key nine times out of ten.   The 133 plates in Diatomeen im Süßwasser … act as a visual index and, to make life even easier, the species descriptions are arranged alphabetically and cross-referenced in the plates.  Having found an image that resembles the diatom I am trying to identify, it is straightforward to flick to the description to check the details.

There is just one problem: Diatomeen im Süßwasser-Benthos von Mitteleuropa is in German, and quite technical German at that.   I tell people not to worry because all the images are in English but, in truth, I worry that I may lose some of the nuances due to my linguistic limitations.   I was delighted, then, to be asked by Marco Cantonati to help produce an English version of the book.  Marco is half-German so reads and speaks the language fluently, and I was able to work on his first drafts in English to produce the final text.   Conscious that translating a German book into English is only a partial solution for the almost 70% of the EU who have neither as their first language, we also unpicked the prose in order to put the information about each species into a series of “bullet points” so that it was more accessible and we also took the opportunity to update some of the taxonomy.   A large part of last weekend was spent poring over the proofs so it should not be long now before it is available to purchase.

The great irony for me is that I am putting the finishing touches to this book at the same time as I am helping the Environment Agency to move away from using the light microscope to identify diatoms altogether.   I am just finalising the last of the regular competency tests that I organise in which, Environment Agency staff will participate, after which routine samples will be sent off for Next Generation Sequencing rather than being analysed by light microscope.  I’ve written about the pros and cons of this before (see “Primed for the unexpected …”) but there is a funny side.   After over a decade of struggling with identification literature in a language that almost none of them spoke my dedicated band of Environment Agency analysts get the book they dreamed about two months after their last diatom slide is packed away.   My sense of timing is, as ever, impeccable …

Hofmann, G., Werum, M. & Lange-Bertalot, H. (2011).   Diatomeen im Süßwasser-Benthos von Mitteleuropa. A.R.G. Gantner Verlag K.G., Rugell.

Prygiel, J.  & Coste, M. (2000).   Guide Méthodologique pour la mise en oeuvre de l’Indice Biologique Diatomées.   NF T 90-354.  Cemagref, Bordeaux.

The Water Cycle

“…every time you drink a glass of water, the odds are good that you will imbibe at least one molecule that passed through the bladder of Oliver Cromwell.  It’s just elementary probability theory”

Richard Dawkins, The God Delusion (2006)

Oliver Cromwell once drunk this stuff
then went and had a pee.
It trickled to a nearby stream
then meandered to the sea.
It evaporated to the clouds
which wandered far and free.
Not lonely, as Wordsworth said,
but quite companionably.

Orographic uplift is a phrase
to make a poet cry
so let’s skip the explanation
and watch the clouds float by.
But when they meet the distant hills
they’ll dump their load as rain.
And this collects in a reservoir
to become a drink again.

This cycle was repeated
in perpetuity
until we reach the modern age
where it was drunk by … me.