{"title":"IPC中多毛类的综合数据集：物种分布、DNA条形码和功能性状。","authors":"Jieyang Weng, Xuwen Wu, Chenrui Li, Yongnan Li, Qian Li, Fangkun Dou, Tiantian Wang, Jie Li, Yue Wang, Linlin Zhang","doi":"10.1038/s41597-025-05298-w","DOIUrl":null,"url":null,"abstract":"<p><p>The Indo Pacific Convergence Zone (IPC) is recognized as an area of highest taxonomic and functional diversity. The polychaetes have garnered attention as their enormous functional trait diversity and their significant role in biomonitoring ecosystems. Here, we developed a comprehensive dataset for polychaetes in the IPC, encompassing information on species distribution, DNA barcodes, and functional traits. The species distribution data were collected from 39,310 occurrence records, with over 13% newly contributed from museum collections and 350 scientific papers. This dataset also provides 29% known species coverage in the IPC, 154 mitochondrial genomes (35.1% are new contributions), and 7,052 COI/18S/16S sequences (4.6% are new contributions). Our functional traits subdatabase comprises approximately 12,000 records and 2,831 species, belonging to 696 genera and 75 families, with 90% of which are new additions. The functional trait data were categorized into 13 traits spanning morphology, life history, physiology, and behavior. The datasetbase provide an unprecedented and original contribution for conservation and for studying the biogeography, evolution processes, and ecology of tropic organisms.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"12 1","pages":"956"},"PeriodicalIF":6.9000,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12145429/pdf/","citationCount":"0","resultStr":"{\"title\":\"Comprehensive Dataset for Polychaetes in the IPC: Species Distribution, DNA Barcodes, and Functional Traits.\",\"authors\":\"Jieyang Weng, Xuwen Wu, Chenrui Li, Yongnan Li, Qian Li, Fangkun Dou, Tiantian Wang, Jie Li, Yue Wang, Linlin Zhang\",\"doi\":\"10.1038/s41597-025-05298-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The Indo Pacific Convergence Zone (IPC) is recognized as an area of highest taxonomic and functional diversity. The polychaetes have garnered attention as their enormous functional trait diversity and their significant role in biomonitoring ecosystems. Here, we developed a comprehensive dataset for polychaetes in the IPC, encompassing information on species distribution, DNA barcodes, and functional traits. The species distribution data were collected from 39,310 occurrence records, with over 13% newly contributed from museum collections and 350 scientific papers. This dataset also provides 29% known species coverage in the IPC, 154 mitochondrial genomes (35.1% are new contributions), and 7,052 COI/18S/16S sequences (4.6% are new contributions). Our functional traits subdatabase comprises approximately 12,000 records and 2,831 species, belonging to 696 genera and 75 families, with 90% of which are new additions. The functional trait data were categorized into 13 traits spanning morphology, life history, physiology, and behavior. The datasetbase provide an unprecedented and original contribution for conservation and for studying the biogeography, evolution processes, and ecology of tropic organisms.</p>\",\"PeriodicalId\":21597,\"journal\":{\"name\":\"Scientific Data\",\"volume\":\"12 1\",\"pages\":\"956\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2025-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12145429/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Data\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41597-025-05298-w\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-025-05298-w","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Comprehensive Dataset for Polychaetes in the IPC: Species Distribution, DNA Barcodes, and Functional Traits.
The Indo Pacific Convergence Zone (IPC) is recognized as an area of highest taxonomic and functional diversity. The polychaetes have garnered attention as their enormous functional trait diversity and their significant role in biomonitoring ecosystems. Here, we developed a comprehensive dataset for polychaetes in the IPC, encompassing information on species distribution, DNA barcodes, and functional traits. The species distribution data were collected from 39,310 occurrence records, with over 13% newly contributed from museum collections and 350 scientific papers. This dataset also provides 29% known species coverage in the IPC, 154 mitochondrial genomes (35.1% are new contributions), and 7,052 COI/18S/16S sequences (4.6% are new contributions). Our functional traits subdatabase comprises approximately 12,000 records and 2,831 species, belonging to 696 genera and 75 families, with 90% of which are new additions. The functional trait data were categorized into 13 traits spanning morphology, life history, physiology, and behavior. The datasetbase provide an unprecedented and original contribution for conservation and for studying the biogeography, evolution processes, and ecology of tropic organisms.
期刊介绍：
Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data.
The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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