Specie Complex

Species complexes, groups of morphologically similar species that are difficult to distinguish, pose significant challenges to biodiversity research and conservation. Current research focuses on developing automated methods, primarily leveraging deep learning models like convolutional neural networks (CNNs) and incorporating large language models (LLMs) to analyze image and textual data for species identification and distribution modeling. These advancements aim to improve the efficiency and accuracy of species classification, enabling more effective monitoring of biodiversity, particularly in the context of invasive species management and conservation prioritization. The resulting improved data and predictive models are crucial for understanding species occurrences and informing conservation strategies.