Publication Details |
| Category | Text Publication |
| Reference Category | Journals |
| DOI | 10.1016/j.ecoinf.2026.103725 |
Licence  |
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| Title (Primary) | From LSA to LLM: Evolution and limitations of topic modelling methods for biodiversity conservation |
| Author | Takola, E.
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| Source Titel | Ecological Informatics |
| Year | 2026 |
| Department | CLE |
| Volume | 95 |
| Page From | art. 103725 |
| Language | englisch |
| Topic | T5 Future Landscapes |
| Keywords | Probabilistic modelling; Text mining; Machine learning; Artificial intelligence; Clustering; Latent Dirichlet Allocation |
| Abstract | Biodiversity conservation faces mounting challenges due to accelerating species loss driven by habitat degradation, agricultural expansion, and climate change. Scientific literature grows rapidly, making automated text analysis tools increasingly essential for synthesizing knowledge and informing policy. This study reviews the evolution of topic modelling techniques—from Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) to embedding-based models like BERTopic and Top2Vec, and most recently, Large Language Models (LLMs) such as GPT. While traditional probabilistic models remain valuable for identifying thematic structures in ecological texts, LLMs offer enhanced flexibility, particularly for grey literature and prompt-based analysis. Applications of topic modelling in biodiversity conservation include identifying knowledge gaps, monitoring public perceptions, analysing policy texts, and summarising scientific literature. Despite recent advances, key challenges persist, including lack of domain-specific models, limited access to ecological corpora, and reproducibility concerns with AI models. Furthermore, the environmental cost of large-scale computation must be weighed against ecological goals. This review highlights that while AI-based topic models present valuable tools for ecological research and evidence synthesis, their role should remain complementary to human expertise and field-based knowledge. |
| Takola, E. (2026): From LSA to LLM: Evolution and limitations of topic modelling methods for biodiversity conservation Ecol. Inform. 95 , art. 103725 10.1016/j.ecoinf.2026.103725 |
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