How do we best organise studies of long-term change?

Time and again people stress the usefulness of long-term records and bemoan their lack. Yet at a recent conference , organised by the UK Earth Observation Forum, monitoring and long-term surveillance were described as the Cinderella subjects. It is generally much more exciting for funders, and often for the researchers themselves, to set-up new measurements than to repeat those done in the past. Repeating a past survey will often involve old-fashioned methods and mostly what you record will be similar to what was recorded before: not much chance of a paper in Nature from that approach!

The first 19 years of recording ground flora in Sheephouse Wood showed no change, thereafter just a slow decline!

Remote sensing is opening up new opportunities for looking at whole landscapes, the whole country, or the world. At the same time there are aspects, such as the species composition of the forest floor, which cannot be easily assessed in this way. Moreover, if we want to look at longer-term trends we need to compare the current state with past records – which will probably have been collected by someone with their boots on the ground, decades perhaps even a century ago. The methods may not be quite how we would do things now and the results may only partially address today’s hot question, but they are the baselines from which we must work – we cannot go back and change them. How do we best combine ancient and modern data?

Drone images capture the varying tree composition in this part of Wytham brilliantly (image @Yadvinder Malhi), but do not show the ground flora patterns beneath.

When resources are stretched can we make more use of Citizen Science as a way of collecting large amounts of data compared to more detailed recording by specialists. In many cases, yes, but Citizen Science is not free: there are costs involved in training and supervision, even excluding the usually hidden cost of the volunteers’ time. There may also be a hidden cost in increased analytical time, because the records may have more errors and inconsistencies.

Hayley Wood Deer Court People 10-82

Citizen Science 1980s style – a deer count at Hayley Wood.

To build on past records we need access to the past data, which is not always as straightforward as it should be. The published results rarely contain the full data and the methods will not be completely described. For example, a paper may contain the mean species-richness for a set of plots across a wood, but not the species lists for each plot. Increasingly journals require that the raw data are available in an electronic data archive, but are there caveats on their interpretation that the original researchers were aware of but which are not that obvious in the meta-data account?

Moreover the raw data from many past studies will not be in any modern electronic archive, so then the fun begins. Are they in some electronic form and is that still readable with current programmes? I recently tried to read an old data file in Minitab 10 with Minitab 18 to no avail (fortunately I still had access to an old version of the programme).

Are the records only available as paper copies and, if so, who holds them and where? Organisations are not necessarily good at retaining data safely over long periods, as anyone who has engaged in office ‘paper clearance’ weeks will know. Fortunately individual researchers can become very attached to their data, even if legally it may belong to the organisation that employed them when they were collecting it. However records may end up in shoe-boxes under beds and in attics, and risk being thrown-out when the researcher next moves or passes on.

At Wytham Woods there has been a recent project to create a data-base of past and present research with an archive of data-sets that still survive (not all do) from the early 1940s when the University first acquired the site.  This includes the option of putting an embargo on the release of current data, so that the original researcher has time to write the results up and get the kudos of first publication. My long-term plot records are gradually going into the Archive, but at some stage I have to decide how much of three years of bramble records from the 1970s (my D.Phil. study) should go in as well – assuming I can still understand my field notes.

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Is this really all that remains from 3 years of bramble study?

The conference concluded that we need to get better at integrating past and present data, remotely-sensed and ground-based records; be more innovative in how we collect and analyse results; but perhaps most importantly get better at communicating those results.  It was pointed out that a good infographic or striking image may have far more influence than a pile of reports or journal articles – just think Greta Thunberg. So how much more data do we actually need or do we just need to sell the messages from them better?

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