- Agricultural diversification promotes multiple ecosystem services without compromising yield. Meta-meta-analysis shows diversification is good for biodiversity, pollination, pest control, nutrient cycling, soil fertility, and water regulation and not bad for crop yields either.
- Holocene land and sea‐trade routes explain complex patterns of pre‐Columbian crop dispersion. Cherimoya reached the Andes by boat.
- Safeguarding and using global banana diversity: a holistic approach. 1617 banana accessions from 38 countries maintained in an in vitro collection, backed-up in cryo; over 18,000 samples distributed to researchers and farmers in 113 countries in 35 years. And that’s just the basics.
- Designing sustainable pathways for the livestock sector: the example of Atsbi, Ethiopia and Bama, Burkina Faso. It’s not just a straight choice between intensive or extensive production, stop with the dichotomies.
- Moving health to the heart of agri-food policies; mitigating risk from our food systems. It’s difficult to separate food from health; and yet…
- Genes derived from ancient polyploidy have higher genetic diversity and are associated with domestication in Brassica rapa. Agriculture depends on polyploidy.
- Genetic diversity is indispensable for plant breeding to improve crops. Plant breeding from an industry perspective, using the Brassicaceae as a case study.
- Yield, yield stability and farmers’ preferences of evolutionary populations of bread wheat: A dynamic solution to climate change. A totally different perspective to the above, using a totally different crop. Compare and contrast.
- Enhancing seed conservation in rural communities of Guatemala by implementing the dry chain concept. Cool way for farmers to save their seeds so they can do the above.
- Landrace hotspots identification in Europe. Where to implement the above.
- Innovation and the commons: lessons from the governance of genetic resources in potato breeding. This is a tricky one. Near as I can figure it, the authors are trying to say that it’s difficult to govern genetic resources apart from the tools needed to develop and use them. But hey, you have a go.
- Conservation of Native Wild Ivory-White Olives from the MEDES Islands Natural Reserve to Maintain Virgin Olive Oil Diversity. I did not have an endemic insular wild albino olive on my bingo card.
- Agri-nutrition research: Revisiting the contribution of maize and wheat to human nutrition and health. Staple cereals are more nutritious than often thought.
- On the origin and dispersal of cultivated spinach (Spinacia oleracea L.). Spinach originated more eastward than often thought.
- What plant is that? Tests of automated image recognition apps for plant identification on plants from the British flora. Botanists shouldn’t give up their day jobs.
Mapping gaps in genebank collections, or trying to
So the original idea of this post was to document how I fed accession locality data into two new online mapping tools I had recently run across, and then maybe even mashed up the results. It didn’t quite work out that way, but I did spend quite a bit of time on trying to make it happen, so I want to get some kind of blog post out of it anyway. So here goes.
The two new tools are:
- The Global Accessibility Mapping Interactive Accessibility Tool. This enables the user to create a map showing travel time to a set of points of their choice.
- Crop-Climate Suitability Mapping. “A continuously updatable crop suitability geovisualization application for locating the fundamental climate niche of select crops across geographies and temporal scales.”
My thought was to get a bunch of localities for landraces of a crop from Genesys, plug them into the accessibility tool, and then compare the output of that with the overall suitability map for the crop in the region in question. Result: areas suitable for the crop but far from locations of current genebank accessions. That is, priorities for further collecting. Or at least one possible approach to prioritizing collecting. ((Here’s an infinitely more sophisticated approach.))
The first bit was easy enough. I got locality data on barley accessions from Yemen out of Genesys, fiddled with the CSV file a bit, uploaded it into the accessibility tool, ran it, and eventually downloaded a GeoTIFF, which you can upload into Google Earth.
The next step was not so straightforward. I was just not able to get a sensible map for barley in Yemen out of the Crop-Climate Suitability Mapping tool. And I did try. A lot. All I got was the whole of Yemen being classified as “pessimal” for barley, which can’t be right. “Max agriculture extent” was not bad, but no amount of fiddling with the parameters allowed me to produce a mad showing where barley might be expected to grow within that area. But even if I had succeeded, it was not clear to me how I could have used the results outside the confines of the tool itself. There’s no way to download the map, that I could find, apart from a screenshot like this one, which just shows that wherever there is agriculture in Yemen is abysmally bad for barley (red means “pessimal”, orange merely unsuitable).
But having invested quite a bit of time already, I decided to fall back on SPAM. The Spatial Production Allocation Model is still the go-to tool for crop suitability mapping, it seems. And the maps you can make online, such as this one for barley, are nice.
There’s not much more you can do with this, though. You can map accessions from Genesys from the same menu, though not, alas, on the same map as the suitability results. However, SPAM does also provide downloadable data for barley, which comes as part of a huge bunch of global GeoTIFFs. I uploaded that into Google Earth along with the accessibility map.
Here’s what I got.
Ok, not great, I admit. The colour from both the accessibility and SPAM results disappeared when imported in Google Earth, so now suitability is the lighter colour and accessibility the dark streaks. I’ve overlapped the layers so that if you see any light colour, that shows places which are suitable for barley but relatively inaccessible from the locations of other barley accessions (the yellow circles). Those could be your priority collecting localities, in other words.
So not great, but not bad either. At least as a conversation starter. So don’t let me down, start a conversation below…
Brainfood: Now what edition
- Image-Based Goat Breed Identification and Localization Using Deep Learning. Fancy maths can identify goat breeds from photos. Ok, cool, now what?
- AI Naturalists Might Hold the Key to Unlocking Biodiversity Data in Social Media Imagery. Fancy math can often identify common flowers on Flickr. Ok, cool, now what?
- FoodMine: Exploring Food Contents in Scientific Literature. Fancy maths can trawl the literature to pick out the chemical components of different foods. Ok, cool, I guess, now what?
- Cultural and linguistic diversities are underappreciated pillars of biodiversity. Well, yeah. But now what?
- Global priority areas for ecosystem restoration. Fancy maths says restoring 15% of converted lands in identified priority areas could avoid 60% of expected extinctions while sequestering 30% of the total CO2 increase in the atmosphere since the Industrial Revolution. Cool, now what?
- An unexpectedly large count of trees in the West African Sahara and Sahel. Wait, does that mean some of the above won’t be necessary?
- Cost and affordability of nutritious diets at retail prices: Evidence from 177 countries. Fancy maths shows that nutritious diets are almost 3 times as expensive as diets supplying basic energy needs, and costs increase with remoteness. Ok, cool, now what?
- Phylogenetic inference enables reconstruction of a long-overlooked outbreak of almond leaf scorch disease (Xylella fastidiosa) in Europe. The olive plague started on almonds. Ok, now what though?
- Genome-wide association study in accessions of the mini-core collection of mungbean (Vigna radiata) from the World Vegetable Gene Bank (Taiwan). Genotyping, phenotyping and fancy maths find that mungbean could grow in temperate conditions. Ok, cool, now what?
- Enhancing the searchability, breeding utility, and efficient management of germplasm accessions in the USDA−ARS rice collection. Genotyping and fancy maths can improve genebank management. Well, yeah, but now what? No, wait, we know exactly now what: digital genebanks!
- Ok, that was a bit of fun, but the important point is that research, no matter how cool, is only the beginning.
Brainfood: CGIAR genebanks, Sweet potato heat, Rice breeding, CWR gap trifecta, PES, Wild potatoes, Wild olives, Rare olives, Cryo veggies, Broccoli diversity, Crop switching, Cattle diversity, IK
- Germplasm Acquisition and Distribution by CGIAR Genebanks. A lot of stuff going in, a lot of stuff coming out, to everyone’s benefit. 35 years of data, with special focus on the last 10.
- Intraspecific diversity as a reservoir for heat-stress tolerance in sweet potato. 132 out of 1973 accessions tolerant of heat, though in different ways. A prime example of the above benefits.
- Identification and characterization of high‐yielding, short‐duration rice genotypes for tropical Asia. Short-duration varieties will need to be a bit taller and leafier to yield more. Another example of the above benefits.
- Modelled distributions and conservation priorities of wild sorghums (Sorghum Moench). More stuff needs to go into the above genebanks, though, for example from N. Australia.
- Ex situ and in situ conservation gap analysis of crop wild relative diversity in the Fertile Crescent of the Middle East. Same from the Fertile Crescent.
- In situ and ex situ conservation gap analyses of crop wild relatives from Malawi. And not just the above genebanks either.
- The Potential of Payment for Ecosystem Services for Crop Wild Relative Conservation. Ok, we have the gaps (see above), and now here we have the method. What’s stopping us?
- Assessing under-Estimation of Genetic Diversity within Wild Potato (Solanum) Species Populations. Wild diploid species more diverse than previously thought. So providing more ecosystem services?
- Genetic diversity and differentiation of Olea europaea subsp. cuspidata (Wall. & G.Don) Cif. in the Hajar Mountains of Oman. No word on the ecosystem services being provided.
- The investigation of minor and rare Tunisian olive cultivars to enrich and diversify the olive genetic resources of the country. Rare + minor doesn’t mean bad. But maybe an influx of Omani genes would help?
- Biobanking of vegetable genetic resources by in vitro conservation and cryopreservation. Yes, even for vegetables.
- From landrace to modern hybrid broccoli: the genomic and morphological domestication syndrome within a diverse B. oleracea collection. Four subpopulations: Calabrese broccoli landraces, hybrids, sprouting broccoli, and violet cauliflower. Diversity in modern varieties decreasing with time.
- Crop switching reduces agricultural losses from climate change in the United States by half under RCP 8.5. But it will have to be a lot of switching. Hopefully out of broccoli.
- The mosaic genome of indigenous African cattle as a unique genetic resource for African pastoralism. An influx of zebu genes about a thousand years ago is responsible for the success of African pastoralism.
- Protection of traditional agricultural knowledge and rethinking agricultural research from farmers’ perspective: A case from Turkey. Against power imbalances the gods themselves contend in vain.
Nibbles: Crop loss, Soil data, CONABIO stuff, Digging dope, Ceres2030
- There’s a series of interactive workshops to gather feedback on how to measure the Global Burden of Crop Loss. I want an initiative on the Global Burden of Crop Diversity Loss though.
- Soil data makes its way to Google Maps.
- CONABIO has some really excellent agrobiodiversity posters and other resources. Calabazas and amaranth are just the start, so dig away on these orphan crops and others.
- Speaking of digging, ancient people got high. Well there’s a shocker.
- Speaking of shockers: huge literature review says researchers should get to grips with smallholders.