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The pleasures and frustrations of combining biodiversity data

This website provides information on recommended locations, mainly in protected areas, suited for the establishment of genetic reserves for Avena, Beta, Brassica and Prunus targeted crop wild relative taxa across Europe, in the context of the AEGRO project. Available information includes ecogeographical data as well as an inventory of crop wild relatives belonging to the four target genera occurring at each location.

This is the map of the recommended sites:

Which is great, and even greater is the fact that you can look at individual species, and the suggested protected areas, using a nifty Google Maps plugin. This, for example, is the Estrecho site in southern Spain, which is where you find an endemic wild oat (among other things).

The problem is 1 that I can find no way of mashing these data up with anything else. For example, say you want to add Genesys data to see if any other species occur in this, or any other, protected area. I don’t see how. You know where those Genesys accessions are:

But there’s no way to combine the two. Or maybe you want to see if the area was affected by fires last summer. Can’t be done. You know where the fires occurred:

But there’s no way to combine the two. Whereas of course you can easily combine that NASA fire data with the Genesys data, simply by bringing both into Google Earth. 2

So I guess my plea is: if you’re going to use Google Maps or Google Earth to display your biodiversity data, please also make it downloadable. Maybe there was a reason why this couldn’t be done in this project. I’m all ears.

Oh, and there’s another thing while I’m indulging my hobbyhorses. Can’t we use some innovative approaches to add to these kinds of datasets? I mean, if it can be done for amphibians…

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Snow White and the Four Coconut Types

Over at the Coconut Google Group, Hugh Harris has had enough.

Snow White had no problem – not only was the name of each Disney dwarf carved on the end of the bed, they were identified by easily distinguished features: Happy, Sleepy, Bashful, Sneezy, Dopey, Grumpy and Doc.

Dwarf coconut names are not so simple.

  • Dr Nair is looking for a source of green Malayan Dwarf
  • Roland thinks there may be half a dozen green dwarf populations in Malaysia, not just one, pure green dwarf
  • Dr Srinivasan calls for more insights on the distribution pattern of Malayan Green Dwarf, Brazil Green Dwarf etc.
  • Elan Star wants to know about the Samoan or Tongan dwarf in Hawaii.

So perhaps this is a good time to suggest that what is needed now is a Global Coconut Genome Consortium.

For a fee, anyone should be able to send a coconut tissue sample (dwarf, tall, hybrid or unknown) to a collaborating laboratory for a DNA analysis that would identify that sample in terms of its similarity to, or difference from, all previously analysed samples.

The technology is available in many countries on all continents (except Africa?); there are already laboratories able to handle coconut samples in Australia, China, Europe, the USA and Brazil, and probably elsewhere (and the cost is coming down).

There is an International Botanical Congress in Melbourne, Australia, this July. If anyone reading this email is going to that meeting, or knows someone who will be there, please make an opportunity to talk about starting a Global Coconut Genome Consortium (GCGC or GC^2).

In the meantime, returning to the subject of dwarf coconuts, there can never be a 100% “pure” green dwarf or any other coconut (until in vitro propagation methods are a practical possibility).

Indeed, all coconut “varieties” are no more or less than local populations that look phenotypically similar to other populations that share a recent common ancestor.

At the risk of causing more, not less, confusion, I would like to suggest that the commonplace distinction of “tall or dwarf” should be forgotten and replaced. Instead we should recognise four “basic” plant habit phenotypes:

  1. the tall wild type (with large and small fruited sub-types)
  2. the tall domestic type (with different fruit-colour sub-types)
  3. the dwarf domestic type (with different fruit-size and -colour sub-types)
  4. the compact-habit dwarf (which has all the tall features except internode length)

But each of these basic phenotypes, and particularly the first two, are locally introgressed, so that there appears to be a fifth, intermediate, phenotype. For want of any accepted term, this can be thought of as the common cultivated coconut.

And, Elan, your dwarf is number 4 but if you look around you will certainly see number 3 as well.

So, a Global Coconut Genome Consortium. Any takers?

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Featured: Livestock data

Many thanks to Susan MacMillan of ILRI for facilitating one of the authors of a paper we nibbled, Dr Delia Grace, to respond to a couple of queries we had yesterday:

As you pointed out, the data on livestock is SSA is very poor. As a result our reasoning was deductive rather than inductive, based on evidence on the links between system change, genetic homogeneity, population density, transmission opportunities, species diversity etc. on disease emergence and endemicity; it was also based on our own experience (between us multiple decades) of livestock epidemiology in Africa. I can’t speak to use in FARA but the thinking around hot and cold spots is feeding into the CGIAR Consortium Research Program on Agriculture, Nutrition and Health. We are hoping this “megaprogram” will give us the opportunity of ground-truthing and quantifying these disease dynamics trajectories.

We really appreciate it when people respond to what we say here. We know they don’t have to. We know they have better things to do. We really appreciate it very much.