Category: GIS

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Mapping Australian biodiversity

I finally got around to having a go at the Atlas of Living Australia. Very nice. You can make, and download images of, pretty maps of species distributions, Glycine in this case.

And you can mash that up with lots of different environmental layers, such as protected areas, as below.

There are nifty spatial analysis tools built in, to help you predict species distributions based on climate, for example, or explore the range of adaptation of a taxon. You can contribute to the data through citizen science projects. And much more. Well worth exploring.

What you can’t do — or at least I couldn’t find a way of doing it — is export the species distribution data to a kmz for use in Google Earth. Something I’ve complained about before for other biodiversity portals. Maybe someone out there will tell us why that is. ((Ok, well, actually there’s another thing. It would be nice to be able to separate taxa by colour in the scattergrams. The one above shows the whole Glycine genus, but I’m sure the different species will cluster separately to some extent. And downloading the data doesn’t help, as for some reason taxon name didn’t come along with the environmental data. Teething problems?))

One final thing. It’s a great idea to feature a number of “themes” on the atlas website, to get people started. At the moment it is things like wattles, “iconic species” and ants. Why not crop wild relatives?

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Nibbles: Cryo, Tree diversity, Agroforestry, Seed industry, Trigonella, Ancient MesoAmerica, Niche models

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Wallow Fire (may) threaten (some) wild beans. Maybe.

There’s a really bad fire spreading in Arizona. ((NASA Earth Observatory image created by Jesse Allen, using data provided courtesy of the University of Wisconsin’s Space Science and Engineering Center MODIS Direct Broadcast system. Caption by Holli Riebeek.))

You can donwload all kinds of stuff about it, and even post your experiences of it on Facebook. But can you find out whether any crop wild relatives are threatened by it? Well, sure: all you have to do is go off to GBIF, and choose a likely genus (Phaseolus, say), and download the records, and mash them up in Google Earth with the latest fire perimeter data or whatever. ((And can I take this opportunity of thanking Google for the Google Earth license?)) Like I’ve done here:

Coming in closer, and using the NASA GeoTIFF instead of the normal Google Earth imagery, you can put yourself in the position of being able to make some reasonably intelligent guesses about what might be happening to some of these populations, and the genepool as a whole in the area:

But what I really meant is that there ought to be a way to do this automagically, or something. Anyway, it is sobering to reflect that while all hell is breaking loose in Arizona, not that far away to the northeast, in the peaceful surroundings of the Denver Botanical Garden, Anasazi beans are enjoying their day in the sun, utterly oblivious of the mortal threat faced by some of their wild cousins. It’s a cruel world. And there’s a point in all this about the need for complementary conservation strategies that’s just waiting to be made. Isn’t there?

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More on visualizing collecting localities

Clearly short of something to say after the almighty media circus generated by the climate change hotspots publication, our friend Andy Jarvis is reduced to celebrating an embarassingly artificial milestone on the DAPA blog today. Normally I would treat such awkward space filling with the contempt it deserves, but today I’m in the mood to, well, fill space. So here goes.

Andy’s post is about the 90m-resolution digital elevation dataset he and his colleagues have been working on for ages. The milestone he trumpets is 750,000 visitors, but more important is the fact that the data is now visible in Google Earth, which I didn’t know. Here’s what a bit of Spain looks like with the normal Google Earth imagery, the records on show being from Genesys. ((BTW, thanks to Google for the Google Earth license.))

And this is what the same area looks like using the SRTM data:

Advantages to both, I suppose, from a purely aesthetic point of view.

Incidentally, some further playing around with Google Earth revealed a couple of collecting localities for Beta maritima (from GBIF this time) that are easily visible in Street View. Here’s an example, featuring a record from France’s Inventaire national du Patrimoine naturel (INPN), catalogue number INPN_21204166 in case you’re interested. ((Their website is worth exploring. If you do, you’ll find out, among other things, that Beta maritima, is found near the sea significantly more frequently than the average French plant. Unfortunately, the nifty plots and maps are not easily downloadable.))

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Brainfood: Cabbages, Crops in Darfur, Sowing dates, People and biodiversity, Honeybees, Rhizobium, Figs, Urban ag, Wild olives, Ancient textiles, Ducks, Wheat introgression, Food citizenship, Crop models, Trifolium, Variety choice