- Addressing critiques refines global estimates of reforestation potential for climate change mitigation. Better mapping shows there is less land available for reforestation than we thought, and there are limited opportunities for providing multiple benefits. Still, that’s an area the size of Mexico, and worth trying to get it right.
- Genomic approaches to accelerate American chestnut restoration. The American chestnut people seem to be getting it right.
- A native seed bank is restoring land in Canada’s north. Native people — and their genebanks — can help you get it right.
- Controlled Pollination and Reproductive Strategies in Coconut: A Framework for Farmer-Led Breeding, Seednut Production, and In Situ Conservation. Farmers can be helped to get it right.
- Dehulling the secret of the germination of crop wild relatives of Cenchrus, Digitaria, Echinochloa, Setaria and Urochloa. You need information on germination breaking to get it right. In the US Midwest, for example.
- How can Brazilian legislation on native seeds advance based on good practices of restoration in other countries? Not to mention the right policies.
A home for genebank training at last?
Long-time readers will know that I regularly try to roundup training opportunities in crop diversity conservation, basically because nobody else does it. Well, maybe I can stop doing that now.
Yes, it’s true, the Crop Trust has launched a Genebank Academy, which aggregates information on online training courses. Have they missed some? Let me know.
And completeness compels me to add that there is also a Landscape Academy. Though unfortunately none of the courses seem to feature genebanks. But then, I’m not sure that any of the genebank courses featured landscapes.
Crowdsourcing crop diversity, and information
A couple of crowd-sourcing initiatives caught my eye.
First, the good people at the COUSIN project want to expand genebank collections of wild relatives of wheat, barley, lettuce, brassica, and peas in Europe. And they have a pretty good idea where the collecting needs to be done. Think you can help? Check out the call for proposals.
And from a bit further south comes a plea on LinkedIn from Chris Jones of the ILRI genebank. He needs help getting stuff out of the genebank rather than into it.
As part of the ‘low-methane forages’ project, funded by the Gates Foundation and the Bezos Earth Fund, we have been screening the methane emission intensity of a range of forage accessions, in vitro, from the International Livestock Research Institute (ILRI) genebank. The aim is to screen approximately 10% of the accessions held in our genebank and, to date, we have assessed 155 herbaceous legumes towards this goal, including several of our lablab accessions. From these, we have identified two accessions of interest. The methane emission intensity of accession #14447 was 27.7 ml/g total digestible dry matter (TDDM), 43% lower than the highest ten legumes measured so far, and methane emission intensity of accession #14458 was 33.8 ml/g TDDM, 30% lower. So, assuming that similar differences in methane emission intensity are realised in vivo (and that is no guarantee), the preferred candidate seems obvious. However, in our field plots #14458 produced 60% more biomass than #14447, which was an ‘average’ yielder. This higher level of production should be attractive to farmers who currently struggle to incorporate much in the way of legumes in their feed rations. So, which one would you prioritise?
I’ve added the links to the Genesys entries for the accessions in questions for people who want a bit more data to base their decision on. You can provide your input on Chris’ post, or right here and I promise to pass it on.
Brainfood: Genetic erosion edition
- Crop diversity trends captured by Indigenous and local knowledge: introduction to the symposium. A whole symposium on how Indigenous knowledge reveals widespread loss of traditional crops and landraces, and the increasing adoption of high-yielding varieties, driven by economic, political, climatic, and sociocultural forces.
- Landraces and climate change: global trends through the lens of political agroecology. Structural forces (markets, policies) and unequal power in seed systems drive the decline of traditional varieties and marginalize Indigenous and local knowledge about crop diversity; climate change not so much.
- Smallholders farmers defying global genetic erosion: documenting 60 years of peanut landrace conservation in a South American diversity center. Well, not everywhere. I wonder why…
- Farmers hold diverse and connected values towards crops. The global literature shows that farmers value crops not just for yield and profit, but for a wide range of interconnected economic, agronomic, ecological, social, and cultural reasons that vary across farming systems, and recognizing these diverse values can improve research and policy on agricultural sustainability and crop diversity. So that’s why.
- Towards a holistic framework: Exploring the relationship between seed security and food security dynamics among smallholder farmers in Chimanimani, Zimbabwe. The link between smallholder seed and food security is complex, non-linear, and shaped by socio-economic, environmental, and policy factors, showing that having secure access to seed does not automatically translate into food security and that context-specific, systemic approaches are needed to understand and strengthen both.
- The local crop varieties (farmers’ varieties) registration system in Nepal: Past, present and future. It may all be very complex, but legally recognizing and protecting farmer-developed landraces within a formal seed regime can empower farmers, conserve agrobiodiversity, and strengthen seed system resilience.
- Leveraging Earth Observation Technologies to Monitor Essential Genetic Diversity. Nah, we can do it from space.
Another chance for Bambara groundnut
Yesterday’s Nibble on the annoyingly always-on-the-verge-of-breaking-through Bambara groundnut had me rummaging through the blog’s archives. Among dozens of references, I came across a post from almost 15 years ago that included some maps — of genebank accession localities and the distribution of the crop. On a whim, I downloaded the Genesys data and fed it into the maw of ChatGPT, asking it to identify gaps in the world’s ex situ holdings. For each of the top 10 priority collecting regions, I then asked for a best-bet locality for exploration. ChatGPT obliged with a KML file, which I then looked at in Google Earth, together with the accession localities.
This is the result.
And here’s close-up on West Africa, because that’s where accessions are densest, and the suggested “gaps” a little more difficult to understand.
Asked for a justification, this is what the LLM came up with.
Does it make any sense? Well, it’s not exactly where I would have plumped for, just eyeballing the data. But it is not complete nonsense. Maybe it was the prompt? Any ideas what that should look like to get the best results?
Not that any of this is going to help Bambara groundnut much, I suspect.