Research

I made incremental progress on various projects. Don’t want to plant too many flags here yet until these are a little more mature. However, a couple of exciting bits:

KBAs. I’m going to be working with BirdLife International on finding new candidates for Key Biodiversity Areas (KBAs). These are areas around the world flagged as key for conservation.

The criteria for identifying KBAs are a little complicated, and the existing method for longlisting KBAs involves many repeated iterations of manual validation (and is therefore quite expensive). We’re hoping to find a clever way, likely with TESSERA (see below), to automate a little bit of the longlisting.

This past week, BirdLife shared some of their data with me and I’ve started getting my teeth into it.

TESSERA v1.1. I wrote about TESSERA in last week’s notes. This past week, a new version (1.1) has been released. This addresses some issues with v1.0, such as tiling artefacts. It also goes a little farther out from the coast everywhere. I’ve spent a bit of time playing around with the new embeddings, which are very pretty!

Python package: datahues

Yesterday I tidied up and released a python package I made some months back. It’s called datahues, and has a very simple functionality: given two colours, generate a perceptually uniform colour ramp between them. I find myself needing to do this all the time and in the past have always just bodged around with some quite complicated colour-space libraries, so I thought I would write a simple utility for it. It’s now available on PyPI and conda-forge.

Here is the figure from the README, demonstrating the need for the utility:

In the left-hand panel, the green transitions very unevenly to red: there is some awful banding in the transition zone. Without perceptual uniformity (as in the right-hand panel), one might well see patterns in data that aren’t truly there.

Here is a map I made with datahues a few months ago, depicting the annual number of sunshine hours across GB:

It is very gloomy in the Highlands!

Garden

Our vegetable seedlings had a bit of an adventure in May. They travelled 800 miles and lived in four different houses. Now, they’re finally in the ground in our garden in Edinburgh.

These are sweetcorn and yellow courgettes. We’re growing them in the same bed (along with some upcoming borlotti beans), following the “three sisters” method of companion planting. The idea is that the corn provides a rigid structure for the beans to climb, while the beans fix nitrogen in the soil. The courgettes, meanwhile, provide ground cover to retain moisture and suppress weeds.

All of our seeds were F1 varieties, a decision I now regret a little. Having recently read Dan Saladino’s excellent book Eating to Extinction, I’m a zealous convert to the idea of preserving traditional, open-pollinated seed varieties. Doing so helps preserve food heritage, rare flavours, and genetic diversity. Next year!

Clerihews

I learned this week about a very silly poetic form: the clerihew. 4 lines, AABB, whimsical and funny, with the rhymes often extremely contrived and the metre absolutely all over the place. They were invented around the start of the twentieth century by Edmund Clerihew Bentley, and they are typically biographical, with the subject of the poem being the first line. For example, from Bentley’s 1905 Biography for Beginners:

Sir Humphry Davy
Abominated gravy.
He lived in the odium
Of having discovered sodium.

Another example, also from Bentley’s collection:

The people of Spain think Cervantes
Equal to half-a-dozen Dantes:
An opinion resented most bitterly
By the people of Italy.

They aren’t always biographical. My favourite is from the introduction of Bentley’s collection, and is about the very nature of biography:

The Art of Biography
Is different from Geography.
Geography is about Maps,
But Biography is about Chaps.

TESSERA

TESSERA is a geospatial foundation model developed here in Cambridge. It providing a vast, rich dataset of “embeddings”: summary vectors for every 10m pixel on the planet. My new job is to do a bunch of conservation science with these embeddings.

This past week, I had my first proper play with the embeddings. I used them to train a very basic ML model, making some toy habitat maps of the Centre for Landscape Regeneration project areas (the Cairngorms, the Fens, and Cumbria). These were just quick and dirty first passes to get a ‘feel’ for Tessera.

Research plan

I spent a lot of the week thinking about my longer term research goals, both for the coming years in Cambridge and the years thereafter. I’ve written up a first draft of a research plan, just 3 pages. I won’t go into too much detail about it here, but it has been fun reading around a lot of the literature (see below!). One detail I will add here is that I used the typeface Bembo, which I’ve gotten very into recently.

100 Maps

I used the Bank Holiday Monday to get a bit of work done on my side project (“100 Maps of Britain”, hoping to have a page about that on this site soon!). One of the maps is of linguistic roots of British place names. Here, I learned about the Landsker line, a surprisingly sharp linguistic boundary in south Pembrokeshire between regions of predominantly English names (south) and Welsh place names (north). The line is thought to have been formed in the 12th century, when the Normans established themselves in the area and encouraged English settlement.

Research Literature

I read a bunch of stuff around: agri-environment schemes, causal inference, and some of the older back-catalogue of papers around the “land sharing” versus “land sparing” debate.

The idea here is that there are two broad approaches one could take to grow a fixed amount of food across a landscape: modern, intensive agriculture at a few sites and pristine nature reserves elsewhere (land sparing), or low-intensity, nature-friendly agriculture everywhere (land sharing).

Of course, the reality is not so much a binary as a spectrum. Nonetheless, evidence is beginning to accumulate in favour of approaches towards the land-sparing end of the spectrum.

This is a nuanced question, and I won’t be able to do it justice yet. Planning to read more about it in coming weeks.

Elsewhere

Less work-related, I’ve been reading “What the Railways Did For Us” by Stuart Hylton. A very well-researched and funny book about the coming of the railways to Britain and their impact on society, such as the impact on the economy, on cities, and even on the class system.

The opening chapter, concerning everyone’s grumbles about the initial spread of railways, was particularly memorable. Here is Wilhelm I, Kaiser of Prussia, on the subject:

No one will pay good money to get from Berlin to Potsdam in one hour when he can ride his horse there in one day for free.

Parts of the discussion struck a painfully familiar note:

Partly as a result of all this process, Britain became the most expensive country in the world in which to get consent for a railway. Sometimes the parliamentary process alone could cost thousands of pounds a mile, added to which some landowners might extract quite exorbitant payments for their land as the price for removing their objections.