Polytypy and Systematics: Diversification of Papilio Swallowtail Butterflies in the Biogeographically Complex Indo-Australian Region
National Centre for Biological Sciences
Abstract
A long-standing problem in evolutionary biology and systematics is defining patterns of diversification and speciation, which is compounded by allopatric distributions of polytypic taxa in biogeographically fragmented landscapes. In this paper we revisit this enduring systematic challenge using Mormon swallowtail butterflies ( Papilio subgenus Menelaides )—an evolutionary and genetic model system. Menelaides is speciose and intensively sampled, with nearly 260 years of systematic study complicated by polytypy resulting from discontinuous morphological variation. This variation is structured by the mainland-island matrix of the geologically complex Indo-Australian Region, where drawing species boundaries has been difficult. We sampled variation across the biogeographic range of Menelaides , covering 97% of currently recognized species and nearly half of all subspecies. We generated a well-supported mito-nuclear phylogeny, on which we delineated species based on two species delimitation methods (GMYC and mPTP) and strongly supported reciprocal monophyly. These analyses showed that the true species diversity in this group may be up to 25% greater than traditional taxonomy suggests, and prompts extensive taxonomic restructuring. Biogeographic analyses showed that Menelaides have diversified largely in allopatry in Indo-Australian subregions by repeated dispersals across key biogeographic barriers. These results provide critical insights into the diversification process in this morphologically diverse and taxonomically complicated model group. These results will also be informative in future studies on systematics, biogeography, speciation and morphological diversification in the Indo-Australian Region—arguably the most complex geological land/seascape in the world. ### Competing Interest Statement The authors have declared no competing interest.
MoreTranslated text
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
Reproductive Barriers and Genomic Hotspots of Adaptation During Allopatric Species Divergence
Molecular ecology 2025
被引用2
MOLECULAR PHYLOGENETICS AND EVOLUTION 2023
被引用12
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined