Large pre-trained models (LPMs) have the capabilities to understand natural language, code, and diverse data including images; e.g., large language models (LLMs), code-generative models, and large vision models (LVMs) as well as combined as multi-modal models. We outlines the main applications of LPMs and multi-modal LPMs for ecology and biodiversity conservation. These applications include generating ecological data, generating code, providing insights into public opinion and sentiment. We highlighted the significant potential of LPMs and the potential use of Ecology-specialized LPMs for ecology and biodiversity conservation. They offer unprecedented opportunities for analyzing diverse data, extracting meaningful insights, and informing conservation decisions.

Large Language Models (LLMs) have revolutionized the field of natural language processing. These models can analyze vast amounts of data, extract meaningful insights, and provide a basis for informed conservation decisions. This paper identifies the main applications of LLMs for ecology and biodiversity conservation: generation of ecological data, prediction using coding by LLMs, providing insights into public opinion and sentiment, and the potential application of Ecology-specialized LLMs.We discuss the potential challenges and limitations associated with the use of LLMs, such as biases in LLM-generated code and data, and the need for careful evaluation and interpretation of LLM-generated results.