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Happy International Day for Biological Diversity

Once again, May 22 rolls around as an opportunity “to increase understanding and awareness of biodiversity issues,” as the Convention on Biological Diversity puts it. This year the focus is on marine biodiversity. So we’re going to look at rainforests. And agriculture.

The Copenhagen Consensus is an interesting attempt to have a bunch of economists (usually) work out where to find the best return on investments in development. The deal is that people write a paper examining interventions designed to tackle a development problem (nutrition, AIDS, clean water …) and a bunch of other experts decide which interventions make most economic sense, given a limited pot of money. The big list of “16 investments worthy of investment” came out a week ago, with better nutrition at No. 1. At No. 6 is “creating an increase in agricultural productivity through research and development,” one of three policy options offered in response to the challenge to reduce the loss of biodiversity.

Here is Copenhagen Consensus Capo Bjorn Lomborg’s summary of the value of that:

The authors estimate that with a $14.5 billion annual infusion into research we can achieve 20 percent higher annual growth rates for crops and 40 percent higher growth rates for livestock, which over the next 40 years will significantly reduce pressures on nature and hence help biodiversity.

The other favoured option to reduce biodiversity loss is to “prevent all dense forests from being converted to agriculture”. Preventing deforestation has a benefit:cost ratio of between 3 and 30, while the benefit:cost ratio for increased agricultural R&D is between 3 and 20. (A third option — “increasing the amount of protected areas globally to around 20 percent” — is barely worth trying because it seldom reaches break-even, with benefit:cost ratios of between 0.2 and 1.4)

There’s a lot one could (but won’t) say about the Conpenhagen Consensus approach and assumptions; it is odd that investing in agriculture is part of the solution to biodiversity loss, although it is not a big part of solutions to undernutrition. And the value of agricultural biodiversity specifically is nowhere to be seen.

Which will do as our contribution to increasing understanding and awareness of biodiversity issues.

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Featured: Livestock data jungle

Tim Robinson updates us on livestock data at FAO:

…We had, of course, been working on the collection of the underlying livestock statistics, and the spatial modelling to produce the maps, for many years prior to them being published on the FAO website … but that is all quickly forgotten when they are re-distributed by a third party.

For your information, we have been beavering away since then, collecting more recent and detailed sub-national livestock statistics and disaggregating these using a slightly modified modelling approach, and 1 km multi-temporal, Fourier-processed MODIS imagery from the University of Oxford…

Global datasets coming soon, apparently. We’ll keep you posted.

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Brainfood: Spanish emmer, Lathyrus breeding, Vitis in N Africa, European tree niche models over time

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Tracking down those sodium exclusion genes in wheat: Part 2

The story thus far: Our plucky heroes have traced Triticum monococcum C68-101, the wild parent of a tetraploid wheat (Line 149) with interesting salinity tolerance genes, to the University of Sydney. Maybe. Kinda. Sort of. But they keep digging, and their perseverance is not long in being rewarded. We hear again from Ray Hare.

You may remember that you asked me back in March to track down the source details of the T. monococcum used as the donor of the sodium exclusion genes Nax1 and 2. At last after some detective work I have a fairly good set of identifiers that match up.

The original seed, that was obtained by the University of Sydney, came as part of a collection of monococcums from Dr Ralph Riley of the Plant Breeding Institute, Cambridge. Prof. Eldrid Baker assembled this collection of Triticum species back in the 1960’s. C68-101 is an accession identifier in the University of Sydney Wheat register with the accession number NS 3637. It is also known as “Triticum aegilopoides – 3″. All of the entries in the University species collection have now been lodged with the Australian Winter Cereals Collection where this monococcum accession has the AUS number 98382.

I have not been able to trace the original collection location. It is likely to be Israel or a neighbouring country. PBI Cambridge had links with the Hebrew University. I have seen no shortage of all manner of Triticum species in Syria, Lebanon, Jordan and Israel.

I would be fairly confident that other monococcums have these Nax genes. We checked out two others from this set and each one showed Na exclusion activity. We simply had to select one accession to conduct our studies.

As I said before, the A genome diploids remain rather under researched. Who knows what may come from this ploidy level. It is quite possible that few diploids were involved in the original formation of the progenitor tetraploids and some of this A genome variation has been lost in the formation of the hexaploids. The total variation in the A genome in hexaploids is likely to be small when referenced back to that in the monococcums. I have seen good isozyme variation evidence that clearly supports this belief, in the order of a few orders of magnitude.

I am happy to be of additional assistance.

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Featured: Old Tanzanian sorghum

Mark Nesbitt knows who the Director of Agriculture is Tanzania was in 1934:

The sorghum collection – all 956 accessions – was acquired by J.D. Snowden while working on his 1936 book (still in print!) “Cultivated Races of Sorghum”. It’s a perfect example of a collection that 20 years ago would have seemed useless (old seeds, mostly dead) but thanks to new techniques (DNA analysis) suddenly looks very interesting as a record of landrace distribution before the Green Revolution.

So, any gene jockeys out there interested in extracting DNA from old seeds? Just for information, there are 1058 sorghum accessions from Tanzania in Genesys. How much can it cost to run a bunch of microsatellites on 2,000 samples?