- New evidence of plant food processing in Italy before 40ka. Did modern humans outcompete Neanderthals in Italy by grinding up and eating wild cereals? No, probably not, but still.
- Early Dalmatian farmers specialized in sheep husbandry. Did early Dalmatian farmers outcompete local hunter gatherers by eating sheep? No, probably not, but still.
- Northwest African Neolithic initiated by migrants from Iberia and Levant. Iberians brought farming to the Maghreb, where local hunter-gatherers were both outcompeted and enticed to change their lifestyles, and the whole thing happened again later when pastoralism arrived from the Levant.
- Genetic continuity, isolation, and gene flow in Stone Age Central and Eastern Europe. This outcompeting thing happened to different extents in different parts of Europe.
- Why did foraging, horticulture and pastoralism persist after the Neolithic transition? The oasis theory of agricultural intensification. Lower rainfall and lower biodiversity allowed early intensive agriculture around the world to outcompete other lifestyles.
- New research on crop diversity of the early farmers in southeastern Europe (ca. 6400-5700 BCE). Some crops were outcompeted by others as agriculture spread into Europe.
- The early adoption of East Asian crops in West Asia: rice and broomcorn millet in northern Iran. Starting in East Asia, broomcorn millet reached the Caspian Sea’s southern coast by 2050 BC by infiltrating and rice by 120 BC by leapfrogging. No word on what they outcompeted.
- Redefining the timing and circumstances of the chicken’s introduction to Europe and north-west Africa. It took a long time for chickens to outcompete other sources of food. For a long time they were just exotic pets.
- Pre-Columbian legacy and modern land use in the Bolivian Amazon. Modern farming practices are taking advantage of ancient farming practices in the Llanos de Moxos. Unclear who is outcompeting whom.
Brainfood: Private finance, Public finance, Land sparing, Land sharing, Trade-offs, Ecological intensification, Metaverse, Crop failure
- Finance for food systems transformation. “Financial institutions with significant portfolio exposure to the agrifood sector” need to step up.
- Heavy reliance on private finance alone will not deliver conservation goals. We can’t trust financial institutions with significant portfolio exposure to the agrifood sector.
- Current conservation policies risk accelerating biodiversity loss. Spare the land for biodiversity, don’t share it. Financial institutions with significant portfolio exposure to the agrifood sector would probably agree. But that’s ok.
- Scientific evidence showing the impacts of nature restoration actions on food productivity. Land sharing isn’t all that bad actually.
- Biodiversity and pollination benefits trade off against profit in an intensive farming system. Land sharing needs financial incentives. Here we go again.
- Ecological intensification of agriculture through biodiversity management: introduction. Yeah but that’s only one example. Check out these 5 reviews and then let’s talk about financial incentives.
- The Meta-universe Platform Roblox for the Conservation of the Globally Important Agricultural Heritage Systems (GIAHS): The Case of the Floating Garden Agricultural Practices. Can they charge for it though?
- Risks of synchronized low yields are underestimated in climate and crop model projections. Meanwhile, the world burns…
Brainfood: PGRFA prioritization, Endangerment value, Geo-genetic visualization tool, USDA quinoa collection, Wild sesame conservation, USDA genebanks & climate change, Clover genetic changes, Collecting Comoros cassava, Sunflower breeding history, Durum breeding, Rice genebank tools
- Prioritizing Colombian plant genetic resources for investment in research using indicators about the geographic origin, vulnerability status, economic benefits, and food security importance. Out of 345 species, 25 were high priority, including 15 potatoes, 3 tomatoes, 2 tree tomatoes, pineapple, cocoa, papaya, yacon and coffee.
- Quantifying Endangerment Value: a Promising Tool to Support Curation Decisions. Looks a bit like an extreme form of “vulnerability status” above.
- GGoutlieR: an R package to identify and visualize unusual geo-genetic patterns of biological samples. Looks a bit like a fancy version of “geographic origin” above.
- Phenotypic and genotypic resources for the USDA quinoa (Chenopodium quinoa) genebank accessions. The geo-genetic pattern was not particularly unusual, but still useful.
- Trans situ conservation strategies to conserve the extinction risk species, Sesamum prostratum Retz., a crop wild relative of sesame being endemic to coastal strand habitat: a case study. Ticks all the prioritization boxes I guess.
- Safeguarding plant genetic resources in the United States during global climate change. We should probably apply vulnerability assessments to stuff already in genebanks too.
- Limited genetic changes observed during in situ and ex situ conservation in Nordic populations of red clover (Trifolium pratense). Though if conservation is done right the stuff in genebanks should be fine.
- Collection and characterization of cassava germplasm in Comoros. Turned out to be a high priority for collecting.
- Fifty years of collecting wild Helianthus species for cultivated sunflower improvement. Good thing all this stuff was prioritized 50 years ago.
- The opportunity of using durum wheat landraces to tolerate drought stress: screening morpho-physiological components. 3 out of 8 Tunisian landraces tested are drought-tolerant. Prioritize for use?
- Tools for using the International Rice Genebank to breed for climate-resilient varieties. How to prioritize for use among 130,000 accessions rather than 8. No word on unusual geo-genetic patterns.
Brainfood: Croplands, Satellite phenotyping, Farm size, Bt double, Scaling up, Opinion leaders, Gendered knowledge, OFSP, Ethiopia sorghum diversity, Banana bunchy top, Climate change & pathogens, Bean pathogens, Mixtures, Rewards
- CROPGRIDS: A global geo-referenced dataset of 173 crops circa 2020. It’s great to finally know where crops are grown. Thanks, satellites!
- Satellite imagery for high-throughput phenotyping in breeding plots. Ok, so now we could theoretically also say where landraces are grown around the world? Thanks, satellites!
- Likely decline in the number of farms globally by the middle of the century. Wait, you have to model this, you can’t figure it out from space? Thanks, satellites.
- Just agricultural science: The green revolution, biotechnologies, and marginalized farmers in Africa. Looks like you can’t predict the success of pest resistant Bt cowpea in Burkina Faso from space.
- Dried up Bt cotton narratives: climate, debt and distressed livelihoods in semi-arid smallholder India. Likewise Bt cotton in India. In both cases, fancy technology is not enough.
- Scaling Up Pro-Poor Agrobiodiversity Interventions as a Development Option. Turns out it’s not just a matter of transferring technology, satellite or otherwise. If only they had had this analytical framework when they thought of Bt crops.
- Male and stale? Questioning the role of “opinion leaders” in agricultural programs. Yes indeed, upscaling needs changes in behaviours and attitudes, and for that you need those social networks, but “key farmers” are overrated as drivers of change.
- Gendered Knowledge, Conservation Priorities and Actions: A Case Study of On-Farm Conservation of Small Millets Among Malayalar of Kolli Hills, South India. And here’s another example, if more were needed.
- Assessment of seed system interventions for biofortified orange-fleshed sweet potato (OFSP) in Malawi. Not clear if this is another example, but I suspect it is. Can you tell OFSP from space?
- Inventory of on-farm sorghum landrace diversity and climate adaptation in Tigray, Northern Ethiopia: implications for sorghum breeding and conservation. No opinion leaders nor satellites were used in this work.
- Banana bunchy top disease in Africa: Predicting continent-wide disease risks by combining survey data and expert knowledge. Both opinion leaders and satellites were used in this work. Well, not really but I couldn’t resist it.
- Climate change impacts on plant pathogens, food security and paths forward. Doesn’t cover banana bunchy top but I’m sure the main conclusion that better modelling and monitoring are needed applies. Using satellites, no doubt.
- Understanding farmer knowledge and site factors in relation to soil-borne pests and pathogens to support agroecological intensification of smallholder bean production systems. Sure, better modelling and monitoring are great, but in the end you have to bring it down to earth.
- Crop Diversity Experiment: towards a mechanistic understanding of the benefits of species diversity in annual crop systems. Diversification of arable crop systems through mixtures need not be bad for yields. I wonder if you can see crop mixtures from space.
- Bending the curve of biodiversity loss requires rewarding farmers economically for conservation management. This does not cover crop biodiversity, but I guess the above does, to a degree. If there were money on the table, you probably wouldn’t need social networks, let alone opinion leaders.
Brainfood: Domestication treble, Introgression treble, Biodiversity mapping double, Oak conservation, Niche modelling double
- Plant domestication: setting biological clocks. Domestication changed plants’ timekeeping and made them less resilient, but there is variation among the biological clocks of different organs that could tapped in breeding.
- Plant domestication and agricultural ecologies. There have been 7 main paths to plant domestication, or commonalities in the ways that plants were domesticated by people in different parts of the world in the past: ecosystem engineering, ruderal, tuber, grain, segetal, fibre, fruit tree.
- Plants cultivated for ecosystem restoration can evolve toward a domestication syndrome. Ok, maybe 8.
- Diamonds in the Not-So-Rough: Wild Relative Diversity Hidden in Crop Genomes. The cool alleles you spotted in wild relatives may already be in cultivated genomes, and that can save breeders some time and effort.
- Finding needles in a haystack: identification of inter-specific introgressions in wheat genebank collections using low-coverage sequencing data. Ah, here they are.
- Interspecific common bean population derived from Phaseolus acutifolius using a bridging genotype demonstrate useful adaptation to heat tolerance. I guess this is an example of the time that could be saved.
- Mapping potential conflicts between global agriculture and terrestrial conservation. A third of agricultural production occurs in sites of high biodiversity conservation priority, with cattle, maize, rice, and soybean posing the greatest threat and sugar beet, pearl millet, and sunflower the lowest. No word on how many crop wild relatives are threatened, but there’s a cool online mapping tool that could I suppose be used to mash things up.
- Assessing habitat diversity and potential areas of similarity across protected areas globally. At a pinch, this could be used to identify backups for any threatened sites of high biodiversity conservation priority.
- Ex situ conservation of two rare oak species using microsatellite and SNP markers. Watch out for the creeping domestication syndrome though, if these ever get used for restoration :)
- TreeGOER: a database with globally observed environmental ranges for 48,129 tree species. Even more than all the CWRs we did. But no, I don’t know if those oaks are included…
- Ecological Niche Models using MaxEnt in Google Earth Engine: Evaluation, guidelines and recommendations. …but if not you can always work their ranges out for yourself.