Friday, 27 July 2018

Phenology histograms - are they an over-simplification?

I had quite a lot of correspondence yesterday on interpreting phenology histograms with two separate research teams. It got me thinking about the HRS data and how we present such data. In the developing HRS website, it is possible to change the date range and lattitude range to interrogate the phenology of particular species. This should make life a lot easier but, even then, I have spotted problems.

Cheilosia albipila is a classic example. The phenology histogram (Figure 1) suggests that it is double brooded, but we know that this is not the case. The adults fly relatively early in the spring and by June the larvae are big enough to record by splitting thistle stems. So, a representation of all records will give the impression that it is multi-brooded. This is clearly wrong, so what should we make of the histogram?

Figure 1. Cheilosia albipila - all records
I think a number of interpretations are needed.

Firstly, we need to interrogate the database and work out which records are of larvae and which are of adults. Where no stage is given and the record falls outside the main flight time I think we need to be somewhat sceptical about it unless we know the recorder and the sort of fieldwork they do. We might well have to go back to the original recorders too.

This is a species that is relatively infrequently recorded, so the histogram is composed of a comparatively small number of data points. The coarser the data, the more care must be taken in interpreting the outputs, but it seems that flight times have not changed markedly. Most records will be of adults at spring flowers but there may be occasional ones of adult females sitting on marsh thistle rosettes.

We get data from a lot of sources, including Mapmate synchs, so it is not possible to scan every record before it is uploaded. That means we have got to do some retrospective analysis and adjustment to the data. It looks like it could be a very big job!

Secondly, there are species where we know comparatively little about the larvae and can be fairly sure that larval records don't make up much of the data. The phenology histogram for Cheilosia pubera seems to confirm this (Figure 2). There are a couple of questionable outliers that might be larvae, but they might equally be misidentifications. In my experience C. pubera has a pretty short emergence period and is gone by the end of June.
Figure 2. Cheilosia pubera - all records
The above are two quite simple cases because the larvae are plant miners and coincide their development with optimum plant growth and nutrient mobilisation. It becomes a lot more complicated when investigating species whose larvae live in nutrient-poor rot holes or within decaying timber. In these cases it is quite likely that larvae may take two or more years to develop. What can we make of the histograms in these cases?

Callicera aurata provides a nice example because we know quite a lot about it from people who investigate rot holes. It seems that larvae in Callicera pass at least one winter as a larva and possibly more than one winter as such. So, we can say that it is almost certainly not multi-brooded or even with a partial second brood. Yet, its phenology (Figure 3) certainly implies that there are two emergence peaks. I don't think this involves full or partial second generations, but simply means that emergence is staggered. The dip in late July might simply reflect regular hot periods that reduce hoverfly activity? The lack of winter records of larvae might also beg the question whether we have got all of the data - clearly we don't!
Figure 3. Callicera aurata - all records
Callicera rufa is a species that has been studied in far more detail and we know quite a lot about larval colonisation of freshly created artificial rot holes. So what can we make of the phenology histogram (Figure 4)?

Figure 4. Callicera rufa - all records

This histogram is very misleading because most of the records are of larvae found in Scotland. It is often possible to find several different age clasess in the same rot hole, and clearly they can be found at most times of the year. In the last ten years, however, new populations have been found in England, with lots of data coming from several sites in Shrophsire and Norfolk.

The histogram of data from England (Figure 4) is largely free of larval records (not entirely) and the histogram reflects this. It also tells me that there must be a data glitch because I know there are records from the Saddleworth area later in the year but these don't show up because I have set the lattitude too far south!
Figure 4. Callicera rufa English Midlands only
These few examples highlight some of the challenges that exist in presenting and interpreting data. As the dataset increases in volume and complexity, we will need to provide detailed interpretations because the majority of readers will not have access to raw data and many will not know much about the biology of the animals in question.

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