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Introduction to Special Issue on Biodiversity in China

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Introduction to Special Issue on Biodiversity in China Introduction to Special Issue on Biodiversity in China China Scientific Data Ji Liqiang1* Vol.3, No.1, 2018 1. Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, P. R. China PUBLISHED: * Email: [email protected] March 31, 2018 China is one of the countries with the richest biodiversity in the world. It is home to over 35,000 higher plant species (ranked 3rd in the world), about 7,000 vertebrate species, and a large number of fungi resources. For its vast territory, China has all types of ecosystems in the northern hemisphere ranging from frigid to tropical. With abundant genetic resources, China is one of the world’s origin places of crops. Over the years, Chinese and foreign researchers conducted extensive and in- depth research on the origin, evolution, current pattern and potential trend of biodiversity in China, which achieved rich outcomes in species diversity, genetic diversity and ecosystem diversity. Large amounts of data were accumulated in fields like biodiversity survey, monitoring and analysis, as well as ex-situ and in-situ conservation, which have great value for biodiversity research and conservation in China. This special issue comes out in a way to promote the sharing of biodiversity data, foster data findability and reusability, and protect the intellectual property rights of data owners. It consists of 12 data papers on biodiversity in China, published in two issues of China Scientific Data (Issue 4, 2017; Issue 1, 2018). The datasets cover the following fields. Biological species inventory. Wang Hanqiang et al.1 collected and processed the taxonomic data of Ensifera (Insecta: Orthoptera) from authoritative taxonomic works and the latest research findings, through which to build a dataset of Ensifera (Insecta: Orthoptera) in China. This dataset contains not only the taxonomic information of Ensifera, but also its morphological description, type, distribution, diagnostic images, coupled with literature referred. It not only provides comprehensive information for taxonomic research, but also lays a scientific basis for ornamental insect utilization. By referring to the taxonomic system of amphibians and reptiles and the latest achievements in systematics, Cai Bo et al.2 sorted and processed specimen data and field survey data to form the distributional list of amphibians and reptiles in Sichuan Province. This dataset provides the latest scientific basis for endemic species protection and alien species administration. Likely, based on the latest advances in taxonomy and systematics, Chen Jiahui et al.3 integrated specimen information, survey data and historical records to build the catalogue of seed plants in Yunnan Province. The catalogue provides credible scientific data for botanical research and science popularization. He Yanbiao et al.4 extracted and processed data from authoritative botanical resources, such as GBIF, BHL, Flora of China, based on which they developed the data set of plant diversity in Myanmar. As a response to the Belt & Road Initiative, this data set integrates heterogeneous data from diverse international organizations and time periods but still bases itself on China’s core data. It provides statistical support for biodiversity inventory in Southeast Asia and relevant international cooperation projects. - 1 - Genetic diversity resources. Based on the registration information of plant seeds, plant genomic DNAs, and plant in vitro materials from China’s big science project – Germplasm Bank of Wild Species, Li Tuojing et al.5 built the germplasm bank of wild species in southwest China. This database has great significance for the conservation and utilization of wild plant genetic resources. Wang Lin et al.6 sorted the morphological, biochemical and molecular biological data of venomous animals and compiled the dataset of venomous animals in China. Besides the taxonomic information of the animals, this dataset also contains data on active toxic ingredients, as well as intoxication prevention and treatment, which is of practical value for both scientific research and science popularization. Wild animal survey data. Based on the investigations of marine macrobenthic mollusks conducted by Beidou research vessel during its three cruises, Xu Yong et al.7 developed and published the dataset of macrobenthic mollusks of southern Yellow Sea in summer 2011 – 2013. This dataset contains fundamental data of the species, including sampling location, sampling date, number of samples, density, among others, which has great significance for marine biodiversity research and marine bioresource utilization. Animal image feature data. Wang Jiangning et al.8 extracted Pieridae feature data from standardized specimen images, including color, shape and texture, based on which they built a complete dataset of image feature for Chinese Pieridae specimen. When used in combination with another published dataset of the authors, “A dataset of image feature for Chinese Papilionidae specimen”,9 this dataset can provide extensive material for intelligent species identification and relevant research. Animal 3D image data. Compared with 2D images, 3D images provide rich and abundant information on morphological structure for species identification, phylogeny, individual development, morphological function and bionic mechanism. Ren Jing et al.10 performed micro-computed tomography on the heads of Chrysomela populi adults, which is an important pest of forestry. The tomography image sequence they published provides high-precision data for insect morphology and anatomy. Yi Hongyu et al.11 published the 3D CT morphological data of the skull of Liaodactylus primus, discovered from the Late Jurassic Tiaojishan Formation in Jianchang County, Liaoning Province. This dataset contains 3D modelling videos and morphological character matrices. Pan Zhaohui et al.12 published the 3D morphological data of the fossil of an important placoderm, Pauropetalichthys magnoculus, from the Early Devonian of Qujing, Yunnan Province, which helps understand the evolution of early vertebrate neurocranium. Jia Jia et al.13 collected and published the high-precision 3D data of the fossil specimens of Qinglongtriton gangouensis from the Upper Jurassic of Hebei Province. This dataset consists of CT scan data and 3D reconstruction video material, providing important information for understanding the morphological characters of the salamandroid Qinglongtriton gangouensis from the Upper Jurassic. The publishing of the above data sets has great scientific implications for research on biodiversity evolution, as well as animals’ structure and function. The data papers included in this special issue provide not only detailed dataset description, but also data collection and processing methods, quality evaluation and validation methods, as well as other information that can facilitate users’ understanding and reuse of the data described. - 2 - We hope, through publishing the inventory, distributional, character, resource, survey, experimental, analytical and comprehensive data of the biological species, this special issue can advance biodiversity data sharing in China and promote biodiversity research at large. In doing so, we aim to support the conservation and sustainable use of biological resources in China. References 1. Wang H, Dai L, Zhu W et al. A dataset of Ensifera (Insecta: Orthoptera) in China. China Scientific Data 3 (2018). DOI: 10.11922/csdata.2017.25.zh 2. Cai B, Lyu K, Chen Y et al. The distributional list of amphibians and reptiles in Sichuan Province, China. China Scientific Data 3 (2018). DOI: 10.11922/csdata.2017.20.zh 3. Chen J, Deng T, Zhang D et al. The catalogue of seed plants in Yunnan Province. China Scientific Data 3 (2018). DOI: 10.11922/csdata.2017.20.zh 4. He Y, Zhuang H & Wang Y. A data set of plant biodiversity in Myanmar. China Scientific Data 3 (2018). DOI: 10.11922/csdata.2017.23.zh 5. Li T, Li H & Li D. Germplasm bank of wild species in southwest China. China Scientific Data 3 (2018). DOI: 10.11922/csdata.2017.19.zh 6. Wang L, Li W & Zhu J. A dataset of venomous animals in China. China Scientific Data 2 (2017). DOI: 10.11922/csdata.2017.13.zh 7. Xu Y, Li X, Wang H et al. A dataset of macrobenthic mollusks of southern Yellow Sea in summer 2011 – 2013. China Scientific Data 2 (2017). DOI: 10.11922/csdata.2017.12.zh 8. Wang J, Han Y & Ji L. A dataset of image feature for Chinese Pieridae specimen. China Scientific Data 3 (2018). DOI: 10.11922/csdata.2017.15.zh 9. Wang J, Han Y & Ji L. A dataset of image feature for Chinese Papilionidae specimen. China Scientific Data 1 (2016). DOI: 10.11922/csdata.180.2015.0008 10. Ren J & Ge S. Micro-CT images of the head of Chrysomela populi adults. China Scientific Data 2 (2017). DOI: 10.11922/csdata.2017.17.zh 11. Yi H, Zhou C & Gao K. A 3D CT dataset of the skull of Liaodactylus primus (Reptilia: Pterosauria) from the Jurassic of China. China Scientific Data 2 (2017). DOI: 10.11922/csdata.2017.22.zh 12. Pan Z & Zhu M. 3D morphological data of Pauropetalichthys magnoculus from the Early Devonian of Qujing, Yunnan, China. China Scientific Data 2 (2017). DOI: 10.11922/csdata.2017.16.zh 13. Jia J & Gao K. Dataset of 3D high-resolution μCT scan of fossil specimens of Qinglongtriton gangouensis, a basal salamandroid (Amphibia, Urodela) from the Upper Jurassic of Hebei Province, China. China Scientific Data 2 (2017). DOI: 10.11922/csdata.2017.0004.zh ------------------------------------------------------------------------------------------------- How to cite this article: Ji L. Introduction to Special Issue on Biodiversity in China. China Scientific Data 3 (2018). DOI: 10.11922/csdata.2018.0007.zh - 3 - .
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