- Plant diversity modifies multi-trophic interactions in croplands, grasslands and forests. Increasing plant diversity changes the interactions between plants, herbivores and their natural enemies, but exactly how depends on the ecosystem. Diversification’s pest-suppression magic looks like a farming-specific trick, not a universal law.
- High-resolution carbon and biodiversity mapping shows correlated losses across space and agricultural products. Carbon loss and biodiversity loss from farming turn out to hit the same ground: two-thirds of both concentrated on one-third of agricultural land, with beef and milk alone responsible for 41% of the biodiversity damage. Good news for anyone hoping one policy lever could do double duty.
- Harnessing agri-food system microbiomes for sustainability and human health. Soil to gut, it’s all one network, linking ecosystem function, food production and human health across the entire agri-food system.
- Breeding for beneficial microbial associations. If microbiomes matter that much, why not breed for them? A proposed framework pairs crop traits that recruit good microbes (root exudates, architecture) with soil practices that keep those microbes around, since good genetics on ruined soil gets you nowhere. This means designing crops as participants in ecological networks rather than as isolated organisms.
- Host genetics and social relationships jointly shape fitness-associated microbiome variation in a population of feral horses. Nature’s own microbiome-breeding program: seven years of horse poop from Sable Island shows gut microbes predict winter survival, and related horses share microbes more than chance allows. So the functional unit of adaptation is the animal plus its microbiome.
Conserving the tangle of grapevines
I think we may have already pointed to Conservation gap analysis for wild grapevines (Vitis L.) of the Americas, the latest in a series of papers by our friend Colin Khoury and a rotating assortment of colleagues on the conservation status of the crop wild relatives of the Americas, genepool by genepool. The authors compiled occurrence records for 38 wild American grapevine taxa, and used fancy GIS to infer the overall distribution and environmental niche of each. They then assessed the degree of representation of each taxon in genebanks and protected areas, and hence any remaining conservation gaps. Here’s the headline finding:
We categorize 25 of 38 of the taxa as urgent priority and 10 as high priority for improving ex situ conservation representation. Three taxa are assessed as urgent and 29 as high priority for enhancing in situ conservation. Further action, with emphasis on conservation gap hotspots, is needed to more comprehensively conserve wild Vitis native to the Americas.
Which is pretty clear.
Or is it?
What if “taxa” are perhaps not always the best units of conservation to use in assessing conservation efforts?
That may in fact be one of the implications of a paper that came out just a few weeks after that of Colin and friends: The dynamics of introgression and parallel adaptation across North American Vitis species.
These authors show that introgression and hybridization are pervasive and evolutionarily important across North American Vitis, based on genomic analysis of 639 accessions representing 48 species. About 14% of the average genome shows evidence of introgression, particularly associated with areas where species come into contact. Some taxa usually regarded as hybrid species are in fact better understood as ever-changing hybrid swarms, rather than distinct evolutionary lineages. Most importantly, the authors find that introgressed genetic variants have repeatedly contributed to adaptation in different species. The paper therefore portrays Vitis diversity as a reticulate network — or tangle — of species, populations and gene flow, rather than a set of discrete species.
This has important implications for conservation: hybrid zones and admixed populations may be really significant reservoirs of adaptive diversity. The framework of the first paper might potentially underestimate the conservation importance of regions where these occur, if they contain substantial genetic variation but aren’t well represented by the taxonomic units used in the gap analysis. For example, it might happen that two neighbouring species are reasonably well represented ex situ, but not from the specific regions where they hybridize and introgression occurs.
This suggests a useful next, synthetic step: take the geographic gaps from the first paper and overlay them with the evidence for introgression and gene flow networks from the second. The resulting map could identify not just under-collected species, but under-collected (or under-conserved in situ) evolutionary processes and genetic mixtures. That could be valuable for designing the next Vitis collecting mission.
The accessions in Spain fall mainly everywhere
My ex-colleagues at the Crop Trust have a very nice animation on the Genesys blog-type thing showing the progress of landrace collecting around the world over the past 125 years.
Do please read the post for the details of how it was done, and some observations on the results.
Here I just wanted to highlight something that has always intrigued me: how did Spain get so heavily collected? It’s really striking how in any global map of collecting localities, Spain looks like a solid carpet, with genebank accessions from practically every nook and cranny. More so than most neighbouring countries, I would say.
Well, it’s a little difficult to be sure because there’s no slider on the animation to take it backwards and forwards at will, but it looks like a burst of collecting first in the 40s, and then some filling in of gaps in the 80s, are responsible for the blanket coverage.
Maybe someone more familiar with the history of germplasm collecting in Spain can explain more.
Brainfood: Mapping edition
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We’re moving house so this might be the last post for a while. See you on the other side. In the meantime, enjoy this bunch of papers on different applications of spatial analysis to agricultural biodiversity and associated topics.
- Addressing global hotspots of drought-related crop production losses. A crop-specific drought sensitivity metric for 17 major crops finds rainfed production losses of 10% globally under historically observed extremes, enough to feed 2 billion people, with hotspots in the US Midwest, eastern Brazil, the Mediterranean and South Asia. Sustainable irrigation expansion and crop switching could avoid 60% of those losses. No word on varietal change, but I’m sure it would help.
- GEM-Forest: A Global satellite EMbedding–based map of forests and tree crops for 2020. Using Google DeepMind’s Alpha Earth Foundation embeddings, this 10 m global dataset classifies forest, non-forest and tree crop areas with 90% accuracy, showing that lightweight classifiers on satellite embeddings 1 can rival more complex forest-monitoring pipelines built to support things like the EU Deforestation Regulation.
- Global distribution of cattle, horses, goats, sheep and buffaloes at 1 km resolution for 2000–2022 based on subnational census data and spatiotemporal machine learning. Harmonizing 55,336 census polygons across 147 countries produces annual 1 km livestock headcount and density layers for five species, letting users track shifting grazing pressure over more than two decades rather than relying on single-year snapshots. 2
- A Spatial-Econometric Analysis of Fruit Tree Diversity in Lebanon: A contextual framework for supporting smallholder farmers. How geography, socio-economic conditions and local context shape fruit tree diversity in Lebanon, helping identify where interventions could best support smallholder resilience.
- High-resolution mapping of rice cropping pattern, intensity, calendar, and ecosystem type across Southeast Asia. Joins the growing pile of fine-resolution rice products for the region, this one distinguishing not just how many harvests a field gets but which rice ecosystem (irrigated, rainfed, upland) it belongs to. Is which variety is being grown next on the agenda?
- Entrenchment of cropping patterns reinforces climate exposure for certain crops in US. County-level analysis of US cropping decisions finds that climate risk has actually risen for some crops (like rainfed soybeans) even as it fell for others, suggesting economic and policy incentives are keeping farmers planted in increasingly climate-mismatched patterns rather than nudging them toward the drought-sensitivity-driven switching the first paper above models.
Mind the conservation gap
In the interest of completeness, I feel it incumbent upon me to complement the post on gap analysis for crop diversity conservation that I put up a few days ago with a couple of additional links.
The Crop Trust and FAO elearning Academy have collaborated on a course on the Global Crop Conservation Strategies that includes a lesson on “Crop coverage assessments and gap analysis.”
And the Crop Trust has also made available a “Curriculum of an online lesson for gap analysis.”
So there’s really no excuse for not doing your own gap analysis, is there? And add to the storied history of the field.