Before the flood

So, three years back, I posted about the floods in Pakistan, and how genebanks could potentially help farmers recover any crop diversity they lost because of them. But wouldn’t it be even better if the danger of flooding could be predicted? That way crop diversity from at-risk areas could be collected, if not already in genebanks, and multiplied up ready to be distributed should disaster strike.

Well, a recent paper does just that, using AI, no less: “We use our model predictions to identify historically flood-prone areas in Ethiopia and demonstrate real-time disaster response capabilities during the May 2024 floods in Kenya.”

I’ve managed to geo-reference a screen grab of the Ethiopia map provided in the paper using MapWarper, import it into Google Earth, and add the locations of sorghum landraces as reported in Genesys. Here’s what I got.

Unlike in the Pakistan example, there’s not much in the way of genebank accessions from areas of Ethiopia that are particularly at risk from flooding, it seems from this. However, Genesys does not (yet) include geographic provenance data for sorghum from the national genebank of Ethiopia. The 4000-odd sorghum accession from Ethiopia currently in Genesys are conserved at ICRISAT.

Brainfood: EcoregionsTreeFinder, Microbe niches, Herbarium phenology, Green Status Index of Species Recovery, Feral pigs, Trade & biodiversity, African cereal self-sufficiency, Plant protection, Ugandan seed systems, Grasspea breeding, Indigenous knowledge

Modified ecosystems and the conservation of crop diversity

A new global assessment of the state of terrestrial ecosystems has just been published, focusing on the extent of human modification due to “industrial pressures based on agriculture, forestry, transportation, mining, energy production, electrical infrastructure, dams, pollution and human accessibility.” 1

As is my wont, I tried to find a form of the data that I could shoehorn into Google Earth, but I failed. Fortunately GIS guru Kai Sonder of CIMMYT was able to snip out a kml file of overall human transformation as of 2020 covering Kenya — don’t ask me how. But thanks, Kai. I put on top of it genebank accessions from Kenya classified as wild or weedy in Genesys.

I don’t know quite what to make of this. The wild populations seem to have been mainly collected in areas that in 2020 were very highly affected by human activity. But is that good or bad?

It could be good — in a sense — if the high degree of human transformation means that the original populations are not there any more. 2 Phew, good thing they were collected! On the other hand, it could be bad if the concentration on easily accessible and modified areas means that the genetic diversity currently being conserved is not representative of what’s out there.

What do you think?

But of course what I really want is a version of this which focuses on agricultural areas and is updated in real time. Yes, a perennial favourite here: a real early warning system for erosion of crop diversity.

Brainfood: Complementarity, Temporality, Communality, Fonio trifecta, Atriplex domestication, Egyptian clover in India, Genebank information systems