Agrobiodiversity is crops, livestock, foodways, microbes, pollinators, wild relatives …
Luigi mentioned the UK Science’s Museum’s interactive map on climate change and crops. Elsewhere, 1 he draws attention to maps of diabetes around the world. Now I find a map of “small farms” in the US.
What I want, obviously, is a graphic that will show me any relationships between the prevalence of small farms and diabetes, over time, corrected for access to the internet, obviously, and for the whole world. Not a lot to ask, is it? Oh, and I can’t find diabetes at Gapminder World.
There’s an interesting discussion going on over at PBForum, an e-mail based forum for plant breeding and related fields managed by GIPB. It started out with a question from a Philippines breeder about how to get climate-ready rice varieties. I was particularly struck by the latest contribution, which basically said that, rather, we should be trying to…
…create climate-change-ready breeding programmes. That is, build in the flexibility to shift relatively quickly to a new climate related breeding objective, once it becomes established in what direction the climate will change and how it will affect crop yield.
What I would add is that such “climate-change-ready breeding programmes” would necessarily include ready access to as wide a range of raw materials as possible, including, crucially, properly evaluated collections of landraces and crop wild relatives conserved in, and readily accessible from, genebanks.
Dag agrees with Fayaz on the uncritical use of niche modeling:
True! This is an important warning for uncritical use of niche models. The niche model predictions of a species distribution does not intend to imply that the species would necessarily be expected to be found there. The niche model only calculates a signature of the ecological climate for the specific occurrence data used to calibrate and train the model.
There’s a lot more.
The Science Museum in London has launched an interactive map. The data are from the Met Office’s Hadley Centre, as analyzed by the Walker Institute. I like the Hadley Centre’s one-page summary.
We have blogged a few times about niche modeling and how to improve it. Below Mohamed Fawzy Farag Nawar briefly highlights what will become a useful resource in this field, Lifemapper (the data for the modeling comes from GBIF), but points out some limitations.
Lifemapper.org is an initiative to implement online some sort of generic model to predict where a species might exists based on where it was collected, or where it was otherwise documented that it lived. Fine. But here is the results of the model on the species Clivipollia pulcher. This is a marine mollusk that was found along the coasts of eastern Australian, Papua New Guinea and the Philippines. You will see on the map of predicted distribution that the model suggests it might be found in various places inland in central Africa and Latin America. That is what you get when essential prior knowledge is not introduced to the model. Something like telling the developer of the model that marine species should be modeled to a different set of environmental data than Worldclim, which should only be used for terrestrial fauna and flora. Agricultural species are included in Lifemapper, though again the predicted distributions will have to be looked at fairly carefully before use.