Are plant species encoded in the model currently?

Great work overall to the whole team behind this.

On the research collaboration side of things, next week I'm leading a NSF program on [DeepEarth](https://github.com/legel/deepearth) in Boulder, Colorado for [AI-supported species-specific landscape-scale fire resilience prediction](https://i-guide.io/summer-school/summer-school-2025/projects/#:~:text=DeepEarth), and we've been wanting to build on top of LFMC 2.0.

It seems this encoding of LFMC 2.0 does not (yet) incorporate the _plant species_? I'm curious if the Galileo model has any means to potentially integrate that as another modality, and if this has been explored at all? As a hint, you might consider taking an LLM and extracting embeddings from a pre-trained model, and then combining that encoding during the multimodal sensor fusion.

Happy to discuss further, feel free to ping me at lance@ecodash.ai for collaboration on this. Our work is integrated with the needs of landscape designers and a key requirement is that they be able to evaluate fire risk of individual and new plant species across landscapes. This is something that in some form I expect to move forward with next week, so please reach out if this sounds interesting to help bring everything together with the outstanding work your team has already done here.