What have I worked on the past two weeks?

Working with Michael to improve the habitat maps underlying LIFE and STAR seems a great place to start my PhD. It’s very valuable work – these metrics are likely to be increasingly relied upon by governments, NGOs and businesses who will look to IUCN’s authority about what nature metrics to include towards nature-positive decision making (for example, see IUCN’s STAR press release from last week). So improving the accuracy of these metrics could be very impactful (for example, see this IUCN report about STAR being applied in Kenya and Cameroon). We’re uniquely placed here at the CCI to collaborate with the IUCN on this. I also think I have a lot to offer here with my stats and ML background.

Initially the first step is to look at answering the key question Michael has been facing: how do we know if a habitat map is good enough? This will involve building some validation infrastructure for this, improving upon Dahal et al’s validation standard. We can then use this validation structure to see if we can use ML and TESSERA embeddings to produce significantly better quality habitat maps.

Other advantages of this work include getting me up to speed with working with citizen science data (GBIF) and remote sensing data (via TESSERA embeddings) – data sources it’s important I get hands-on experience with, as I’ll certainly be using these a lot over the next few years. It also will get me up to speed with running large-scale geospatial processing pipelines on our computing cluster.

Particular thanks go out to Michael Dales who has patiently given me a lot of his time to contextualise and walk me through the LIFE and STAR pipelines and future directions. I’m excited to continue to learn from and work with him here!

I’d also be very excited to work with James Ball and David Coomes in their projects on vegetation mapping using TESSERA (starting with the Cairngorms, and building towards the entire UK), so I’m hoping this will all tie together – especially given including plant data in LIFE and STAR is probably the biggest opportunity for improving them.

Finally, taking a step back with a bigger-picture lens for my PhD, I’ve sketched out three broad problem domains I’m interested in working on, as illustrated in the diagram below:

Screenshot 2025-10-19 at 7.37.31 pm.png

This simplifies to:

  1. Better habitat maps for STAR and LIFE (including better validation techniques)
  2. Addressing data-deficiency in plant, fungi and marine data (multi-modal approaches combining literature, remote sensing, and citizen science data; and active learning approaches to guide the search for rare plant data)
  3. Simulating entire ecosystems (revisiting Madingley for 2025 in the age of AI+data+compute).

Each of these problems tie together and could all be interesting domains to explore during the course of my PhD. But we’ll see how things play out over the coming weeks – I’m aware that research tends to be an iterative journey that can take unexpected turns.

That’s all from me this week. Excited to be moving forward. Onwards and upwards!