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Analysis Tools

A suite of analysis tools utilising data from the Data Centre's repository and elsewhere.

Species composition visualization

A common form of ecological data is that of species abundances, collected from a number of sample sites. Typically, the investigator is interested in how those species abundance patterns change in time and space.

Map of transect

The Southern Ocean Continuous Plankton Recorder (SO-CPR) project collects data in just this form. Here, we use data from 291 sample sites, located along a transect that started near Tasmania, headed due south nearly to the Antarctic continent, and then returned (Fig 1). Although there was a large number of different zooplankton taxa observed during this transect (93 in total), we will concentrate on the 8 most-abundant of those taxa.

 

What is a useful format for displaying the variation in species composition over time?

Simple visualization

A simple approach might be to use a coloured matrix plot, with time on the y-axis and our 8 taxa on the x-axis. The colour of each segment of the plot indicates the relative abundance of that taxon at that time. (Note that the segments are not equally sized over time, because the samples were not collected at uniform intervals in time.)
However, this plot is not particularly attractive, or easy to interpret. Relying entirely on colour to indicate abundances is probably not a good idea.

 
Better visualization

Instead, we could use the width of each segment to indicate relative abundance, and use colour simply to discriminate between taxa. In this representation it is much easier to compare relative abundances between taxa, and to track the variations in the abundance of a particular taxon over time. However, the "stepped" nature of the plot (which occurs because the samples are discrete in time and space) is distracting.

 
Visualization with polygons

We could use non-rectangular polygons, but this doesn't really help all that much. One of the problems is that the abundances change linearly between sample times, leading to sharp changes that are probably more distracting that useful.

 
Visualization with smooth interpolation

An alternative is to smooth the original data prior to plotting. Here, we use a fairly heavy smoothing to reduce the detail. This is probably appropriate for the large spatial scales we are considering here, but could be adjusted to show more or less of the smaller-scale detail in the data if necessary.

 
Visualization with smooth interpolation, and latitude

Finally, we could also show the patterns in relation to latitude, along the x-axis of the graph. The background grey colours show the different oceanographic zones along the transect. These zones are defined by the various fronts of the Southern Ocean. It is clear that some of the large-scale patterns in species abundance are related to these oceanographic zones — for example, calanoid copepodites and Ctenocalanus citer tend to found in the zone between the Polar Front and the Subantarctic Circumpolar Current Front (the "Polar Front/Antarctic zone" on the figure). Foraminifera, in contrast, are most abundant in waters to the north of the Polar Front.

References

  • Hunt, B.P.V. and Hosie, G.W. (2005) Zonal structure of zooplankton communities in the Southern Ocean South of Australia: results from a 2150km continuous plankton recorder transect. Deep-Sea Research I 52: 1241—1271
  • Raymond, B. and Hosie, G. (2009) Network-based exploration and visualisation of ecological data. Ecological Modelling 220:673—683. Preprint