There’s a nice paper in Nature on how sensitive vegetation around the world is expected to be to climate change. Here’s the money map.
Cries to be mashed up with crop wild relative distributions and gap analysis.
Nibbles: Cover crops, Viet coconut, Water maps, Mao’s mango, Tudor bread, Belgian gardening, IRRI fingerprints, Stay green barley, Miniature donkey
- Uncovering cover crops, the NY Times way.
- Uncovering coconut cultivation in Vietnam, the Roland Bourdeix way.
- Where to expect water shortages, and irrigation. Crying for a mashup.
- When a mango is not just a mango.
- Bread, and much else, according to the Tudors.
- A Belgian plantsman is revolutionizing gardening. No, really.
- How genomics will revolutionize rice breeding. No, really.
- How to get deeper barley roots for drought tolerance? Look to sorghum.
- And today’s miniature livestock is…a donkey.
On mammal diversity and vegetation biomass
Two global maps coincidentally turned up almost side-by-side on Twitter this weekend. Interesting in their own right individually, they threw up a question for me when I was forced to look at them together in my feed. A paper in Diversity and Distributions mapped what the diversity of large mammals would look like if not for what humans have wrought. Here it is.
And a paper in Global Change Biology mapped above-ground vegetation biomass across the tropics.
So my question is this: why does high-biomass vegetation support a relatively large diversity of mammals in SE Asia, but not in tropical Africa or South America?
Well, since we’re calling for paradigm shifts…
There’s a lot that’s both nice and deliciously ironic about IFPRI’s recent blog post “Granular socioeconomic data are increasingly becoming available in agricultural research.” This summarizes a letter to Nature Climate Change from HarvestChoice scientists which adds some nuance to a previous commentary in that journal calling on socioeconomists to up their data game. The point is a good one, and it’s stated right up front in the post, quoting the letter:
Spatially explicit, harmonized socio-economic data products are increasingly available to the public, such as population and poverty grids, microdata derived from national household surveys, and rasterized sociodemographic indicators. While these products are often overlooked in the economic literature, they are well suited to the study of climate’s impact on human geography across scales.
But, then comes the irony.
First, both the letter and the original article, helpfully linked to in the blog post, are of course behind paywalls. Second, the map included in the post is provided with an incorrect caption. There’s a screen grab here on the left. As you can see, the caption suggests that the map illustrates that childhood wasting is more prevalent in the drier areas of sub-Saharan Africa. But the map shows no such thing, as a glance at the legend, or indeed the map in the original letter, will prove. What the map caption should actually be is “Subnational Demographic and Health Surveys (DHS) data showing centroids of DHS clusters overlaid on Agro-ecological Zones.” Not quite so catchy. The map showing the relationship between wasting and agroecological zones is this one, and it’s in the Supplementary Materials to the letter. ((Which, bizarrely, seem to be freely available.)) I hope I don’t get into trouble for reproducing it here, but it is pretty cool.
And thirdly, and most importantly, frankly neither the socioeconomic datasets nor the agroecological map which the HarvestChoice researchers cleverly mashed up to make their point about data availability are exactly easy for the average non-GIS geek to use, let alone to combine. Try it and see.
The original paper calls for a “new paradigm in data gathering.” The blog post echoes the follow-up letter in saying “the paradigm shift is alive and kicking already.” Oh good. But I’d like to be able to look at the distribution of stunting and other nutritional indicators together with the distribution of different crops and varieties without having to beg a GIS person to do it for me, or spending half a day putzing around trying to understand what this means
Data layers are available in comma-separated values format (.csv) suitable for MSExcel, in ESRI ASCII Raster (.asc) and GeoTIFF formats (.tif) suitable for any desktop GIS tool. To view ASCII or GeoTIFF rasters in ArcMap or QuantumGIS simply drag and drop the downloaded files onto the layer pane.
Sure, have your paradigm shift in data gathering. But can I also have one in usability, please?
Nibbles: Cashmere goat introduction, ICARDA kudos, Biodiverse software, Green Revolution wheat, Chickpea genomes (plural)
- Coals to Newcastle: Afghan goat edition.
- Middle East head of Gates Foundation praises ICARDA and its genebank.
- New software for mapping biodiversity.
- Wheat is special.
- I see your 3000 rice genomes and I raise you 3000 chickpea genomes.