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Root and tuber online mapping bags award

Congratulations to the GIS folks at CGIAR:

RTBMaps — a web-based GIS (Geographic Information Systems) tool to help planners visualize data and analyze options for using roots, tubers and bananas to improve food security, nutrition and income — has been selected for a Special Achievement in GIS (SAG) Award, presented today at the 2013 Esri International User Conference.

The thing is still in Beta, and there’s a lot more to come, both data and functionality:

RTBMaps is being launched with approximately 25 map layers, which are based on data for RTB crop distribution, indicators for poverty and food-security and some production constraints. However, the number of layers will grow as the GIS specialists at the research centers upload maps for additional pests and diseases, social indicators and other pertinent data. The RTB GIS team will also add applications for simple functions such as printing, or downloading maps for use in presentations. The team has also developed a priority setting application that allows users to weight the importance of different criteria — based on their own research, or consultations — and run analyses that result in unique maps.

Actually that priority-setting bit seems to be already there (more on this below). But for sure it will be nice to be able to share the results, which you can’t really do easily at the moment. And to import your own data, like localities of germplasm accessions, say. Which you also can’t do right now.

What can you do? Well, I couldn’t find much in the way of documentation, but playing around on the site suggests that basically what you can do is display those 25 layers in whatever combination you want on a map of the world. The layers include harvested area for potato, sweet potato, cassava, yam, banana and plantain, and a bunch of other variables: biotic (e.g. cassava mealybug climatic suitability), abiotic (e.g. length of growing period), socio-economic (e.g. % children underweight) and management (e.g. N fertilizer application). Each layer comes with a little pop-up which gives you the legend and lets you change its transparency, so that you could, for example, display cassava area together with climatic suitability for the cassava mealybug, and figure out where that pest is likely to do the most harm. You’d have to do that by eye, mind you, by tweaking the transparency settings. Tricky, and not hugely satisfying, but possible.

No, but wait. There’s a “Tools” tab: always a good sign. That allows you to run something called Multi-Criteria Decision Analysis, or MCDA. I think that’s the priority-setting application mentioned above. The way it works is that you choose a crop, then choose from a list of six criteria, and I quote: reduce poverty, food insecurity, nutrition and health, sustainability of natural resources, increase productivity and profit 1, and increase market conditions. So I chose cassava as my crop, and reducing poverty plus nutrition and health as my criteria. You then give a weight to each criterion, 50% each in my case.

Ok, so the next step is to choose indicators for each of your criteria. You’re presented with the same list of 12 indicators for each of the criteria, 2 the first six simply the harvested areas for all the crops in the system 3, the others the following, and again I quote: stunting among children under 5, poverty headcount at USD2 a day, absolute number of poors (sic.) at USD2 a day, irrigation areas, failed season, and accessibility. So I chose the poverty headcount as my indicator for reducing poverty, and stunting as my indicator for nutrition and health. If I had chosen more than one indicator for any of my criteria, I would have been able to give each a weight. But frankly, I was confused enough. Fortunately, I got a little reminder of what I’d done:

rtbmaps

So I clicked on “Run analysis…”, though more in hope than expectation…

I am absolutely convinced that it is a huge technical achievement that the resulting analysis took only about 30 seconds. As my friend Glenn Hyman, one of the people involved, said in the press release already quoted above:

…RTBMaps is the most comprehensive and collaborative GIS web-mapping project to be undertaken within the CGIAR system to date. He noted that the cloud technology that it is based on has only become available in recent years.

I have no doubt all of that is true, and admirable. However, I also have to admit that I have little idea what the map produced by this cloud-technological, and most comprehensive and collaborative, web-mapping project actually means. Here is that map:

rtbmapsresult

Let me hazard a guess. What I think the map may mean is that if your goal is to reduce poverty and improve nutrition and health, in equal measure, and you want to do this via cassava, the areas in red are…what? The places where you would have the best chance of succeeding? The places where you’re going to have the biggest impact? The places where you should go on holiday?

I should have gone to the workshop, I guess. Maybe if I had, I’d be able to understand the whole thing more, and explain it better. And it is still in Beta, so there’s stuff in the pipeline, including documentation, no doubt. The idea of providing diverse maps online, and allowing users to combine them in fancy ways in support of decision-making, is certainly a great one. I really hope to see the promise of RTBMaps fulfilled.

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Is this automated Musa phylogeny any good?

PhyloGenerator is “an open-source, stand-alone Python program, that makes use of pre-existing sequence data and taxonomic information to largely automate the estimation of phylogenies.” Sounds intriguing, no? I found out about it via this Twitter exchange with Rich Grenyer:

He very kindly shared his automatically generated Musa phylogeny, which is reproduced below. I’m afraid you’ll have to click on the image to read the species names.

banana phylogeny

So now I’m reaching out to all you banana taxonomists out there. Does this make any sense?

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The Indonesian fires and crop wild relatives

I know what you’re wondering. You’re wondering whether those fires in Indonesia which are causing so much trouble with haze in Singapore and other neighbouring places are also endangering any crop wild relatives back home. Well, thanks to the following Twitter exchange with the GIS people at Kew, I now know (or have been reminded, actually) that NASA makes available global data on active fires:

We can of course mash that up in Google Earth with, say, the distribution of wild rice (Oryza spp) from Genesys. That would be the little pale blue circles in the map reproduced below.

wild rice indonesia

Which does suggest that at least some of the Indonesian fires may be occurring in wild rice habitats. They may actually be beneficial to some of the weedier species, though, for all I know. Anyway, as ever, it’s nice to have the data. And, just as importantly, be able to play with it.

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Some reaction to ILRI call for global livestock genebank

A recent Q&A with Jimmy Smith, Director General of the International Livestock Research Center (ILRI), included this exchange:

Q. ILRI is calling for the creation of a livestock gene bank. What would it look like and how could it benefit people?

A. There are many gene banks for crops around the world, but we have no such facility for livestock breeds native to developing countries, even though animal diversity in those countries is being eroded in the same way as plant diversity…

That’s only the beginning of a longish answer, which you can read in full on SciDevNet. It elicited the following response on the DAD-Net (Domestic Animal Diversity Network) mailing list from Michèle Tixier-Boichard, chair of the French cryobank at INRA, which we quote here in full with her permission.

The advertisement for the ‘first world gene bank’ at ILRI deserves some remarks.

It is generally an excellent idea to set up genebanks for livestock, both for research and for the management of animal genetic diversity in complementarity with in situ management of populations.

Fortunately, it is not the first time that some countries think of that. For instance in Europe, several countries have a cryobank coupled with DNA samples. 4

In France, a national infrastructure project called ‘CRB-Anim’ has been funded from 2012 to 2019 to set up a network of biological resources centers for 22 species of livestock and companion animals. The aim is to collect, characterize, secure and distribute semen, embryos, DNA, RNA, tissues, for research as well as for the management of genetic diversity of livestock species.

In order to go beyond the national scale, a bottom-up approach is generally preferable to set up a regional network between national gene banks, with harmonisation and standardisation of procedures, sharing of technologies, distribution of samples… The system of automatic delivery which has been set up for some plant genetic resources by CGIAR international centers does not meet the current requirements of the livestock community. Ownership and principles for access and benefit sharing are not considered by the livestock community in the same terms as they are by the plant community, animal breeds are generally considered as club goods rather than public goods, particularly local breeds. So, there is a need for coordination and exchange of knowledge and practise between livestock gene banks, including the possibility of duplication for safety, rather than for systematic globalisation.

Centralisation of resources in a unique gene bank raises a number of major issues that may trigger opposition from many stakeholders, that must consider the Nagoya protocol, and, in any case, will require thorough discussions that should take place under the leadership of FAO.

Some interesting points there, in particular highlighting the differences that exist at the policy level between crop and livestock genetic resources conservation. I suspect that what is meant by the “automatic delivery which has been set up for some plant genetic resources by CGIAR international centers” is the “facilitated access” allowed for under the Multilateral System of the International Treaty, and I confess I had no idea that the livestock conservation community had such reservations about that approach. Dr Smith did not mention the Global Plan of Action for Animal Genetic Resources process being led by FAO in his answers, but one of the key people involved, Irene Hoffmann, chief of Animal Genetic Resources at FAO, is quoted in an accompanying SciDevNet piece on the technical challenges involved in setting up a global livestock bank. However, it’s not quite clear whether the following statement on the possible policy hurdles, which comes right after that quote, reflects Dr Hoffman’s views or is an impression gathered by the writer of the article from other sources.

There is also the issue of ownership, as some countries do not want to deposit what they consider their national heritage into a global genebank.

Either way, ILRI will have its work cut out.