Generative AI to Understand Complex Ecological Interactions

The recent use of Generative AI (GenAI) techniques in Ecology has provided insights into predicting species co-occurrence patterns, specifically in water-limited ecosystems where multispecific plant clumps grow sparsely. In particular, these patterns have been employed to elucidate the mechanisms governing the assembly of plant communities in the context of Southeastern Spain. We discuss how the important concepts of transfer learning, and data augmentation take on slightly different meanings in this context, as compared to their usual application in Computer Vision. In particular, using transfer learning, the same models have been successfully applied to other plant communities in another semi-arid region of Spain and of tropical Mexico, opening the door to a specific kind of data augmentation by combining data sets from disparate communities. Beyond that, we also discuss the use of GenAI for synthetic data, and for predictions that can be of practical use when replanting vegetation in degraded environments, with an eye to biodiversity.