- Dahlias: good to look at, good to eat.
- Why agriculture bypassed herbaceous perennials, until now.
Monitoring plants of “Community interest” in Europe
There’s been an item in the news the last couple of days to the effect that “[a] report by the European Commission shows that habitat and wildlife protection targets across Europe will be missed…” Digging a bit deeper into that seemingly simple statement led me to a hitherto unknown (to me) world of EU rules and regulations and reporting requirements.
Let’s start at the beginning. There’s a thing called the Habitats Directive (1992). This requests all Member States “to monitor habitat types and species considered to be of Community interest.” It’s unclear to me how they were selected (perhaps someone out there can tell us), but these species are listed in various annexes to the Directive, though that sounds more simple than it is:
Where a species appears in this Annex but does not appear in either Annex IV or Annex V, the species name is followed by the symbol (o); where a species which appears in this Annex also appears in Annex V but does not appear in Annex IV, its name is followed by the symbol (V).
Anyway, Article 17 provides for regular reports on implementation of the Directive, and the report “for the period 2001-2006 for the first time includes assessments on the conservation status of the habitat types and species of Community interest.”
The website which houses the Article 17 reports is, well, complicated, but well worth exploring. The most interesting bit from an agrobiodiversity perspective is the page from which you can get species reports. These include all kinds of information about the status of those “species considered to be of Community interest,” country by country (there’s also an overall summary). Some of these species “of interest” are crop wild relatives such as Allium grosii, an endemic to the Balearic Islands (click the map to enlarge it).
There’s a few more CWRs in those annexes, though not all that many. A Hungarian Pyrus, for example. Any chance to get a few more on there? The bureaucratic infrastructure and mechanism for regular monitoring and early(ish) warning of any threats would seem to be well and truly in place, European Union-style.
Nibbles: India, City chicks, Rooftop gardens, Black cherry, Prairie grasses, Oryza SNP
- ICRISAT recommends diversity to cope with climate change in India.
- US urban farmers “mad as wet hens“. City chicks?
- US urban farmers with a view to die for.
- CWR becomes nuisance when free of soil pathogen.
- Convicts help with germplasm regeneration and multiplication.
- The “gold-standard set of curated polymorphisms” for rice.
Nibbles: New Agriculturist, Coffee
- New Agriculturist is out. Among many cool things, check out the piece on crossing rice with a wild relative to make it perennial.
- Nestle finds 33 elite coffee trees in Indonesia, evaluates 6, will use these to produce seedlings by somatic embryogenesis. What could possibly go wrong?
Making that haystack smaller
Germplasm collections can be very large, and that can put off potential users. What breeder really wants to screen thousands of accessions, when only a dozen might end up being useful? It’s not surprising, therefore, that people have looked for short-cuts. One approach is to make a “core collection.” You use the available data on the collection to select a sub-set which you hope will contain most of the original genetic diversity in a fraction (20%, say) of the total number of accessions. And then you evaluate that subset, rather than the whole collection, and use the results to delve back into the remaining 80% of the material, with hopefully a better chance of finding what you’re looking for.
That’s been done for lots of large collections now, with a certain amount of success in increasing their use — and usefulness. But breeders are not really satisfied. They want to shorten the odds even more. And the application of Geographic Information Systems (GIS) technology in something called the Focused Identification of Germplasm Strategy (FIGS) provides a potentially effective way of doing just that.
Jeremy described recently over at Bioversity how FIGS was used to increase the chances of finding a needle in a haystack by “start[ing] with a smaller haystack.” The haystack was 16,000 wheat accessions. The needle was resistance to powdery mildew.
It works like this: take 400 genebank samples known to have some resistance to powdery mildew and use the geographical location where they evolved and were collected to determine the environmental profile that can be associated with resistance. Then apply that profile to a further 16,089 samples with location data, using the profile as a template to identify those that were found in places that share the conditions associated with resistance. The result is a group of 1320 wheat varieties, mostly from Turkey, Iran and Afghanistan. This much more manageable subset was screened by growing them with diverse strains of powdery mildew. About 16% of the samples (211 of 1320) showed some resistance.
These varieties then moved to the next phase, molecular screening for the presence of different alleles of the Pm3 gene. More than half (111 of the 211) had Pm3 resistance, some in previously unknown forms. In the end the group isolated and identified 7 new functional alleles of the Pm3 gene. It took scientists 100 years to find the first 7 Pm3 alleles. FIGS doubled the number in a fraction of the time.
Very good. But is it always going to work? Another recent paper — in fact, a series of papers — counsels caution.