几丁虫是古生代海洋中一类重要的微体生物化石, 迄今已有近百年的研究历史。作为一类有效的生物地层工具, 几丁虫在奥陶纪和志留纪生物地层研究中发挥着重要作用, 为早古生代油气-矿产资源勘探提供可靠的地层对比资料, 还为一些重大地质-环境-生物事件的全球对比提供可靠依据, 特别是那些缺乏笔石和牙形类的地层。然而, 随着现代古生物学的快速发展以及几丁虫资料的不断积累, 几丁虫研究目前正遭遇着瓶颈期, 主要体现在: (1)受制于有限的技术手段及尚未形成规范的研究标准, 不少早期建立的几丁虫分类单元存在着明显的问题, 如描述简单、展示标本过少、光学显微成像无法很好地揭示壳表的形态特征等, 使得后期相关属种的鉴定存在争议; (2)在全球古生物数据不断被数字化和可视化的进程中, 几丁虫相关工作进展迟缓。目前尚未能对全球的几丁虫数据进行有效汇总, 影响了几丁虫宏演化及生物地层学研究, 同时也使得几丁虫古生物地理学与古生态学这类薄弱研究环节一直未能形成突破; (3)几丁虫的生物学属性近来虽有进展, 但仍有争论, 亟待寻求新的证据及思路以解决这一问题。为了能有效地解决这些问题, 促进几丁虫学科的持续发展, 建立一个涵盖系统分类、鉴定特征、标本影像、定量数据、产地、层位、剖面及文献出处等多维度信息的几丁虫开源数据库正逢其时。相关从业人员均可对数据进行检索、录入、厘定、导出及分析研究, 切实增进几丁虫数据的可用性和便捷性。在进行数据库建设的同时, 运用一系列高新技术手段, 逐步对早前建立的信息不完备的、或有争议的几丁虫进行再研究, 完善其形态学特征, 对争议属种进行厘定。该研究不仅有利于推动基于大数据的几丁虫古生物学研究, 为数据驱动的基础研究新范式提供典型案例, 还将有效促进以几丁虫为代表的微体化石的学科发展, 最终提升我国在这一领域的国际学术影响力。

Chitinozoans are one of the vital groups of microfossils in the Palaeozoic ocean. Because of their rapid evolution at species level and high abundance in different types of sediments, chitinozoans have been used as one of the most essential and valuable tools in Ordovician and Silurian biostratigraphy. Related research results have provided crucial insights into major geological, environmental, and biological events. However, with the development in modern palaeontology and the accumulation of data during the last decades, chitinozoan study has been experiencing a period of stagnation. First, due to limited techniques applied and lacking standard research criteria in early chitinozoan study, poorly presented images and simple descriptions have resulted in confusion on the taxonomy of some early established chitinozoan taxa, which in turn has a negative influence on the chitinozoan systematics, as well as further study that relies on taxonomy, preventing a better survey of major biological events such as the Great Ordovician Biodiversification Event. Second, digitalisation and visualisation of palaeontological data have become two of the most important and hottest subjects in palaeontology. However, chitinozoan research in this aspect is proceeding quite slowly. Until now, the lack of an efficient database collecting and analysing global chitinozoan data has seriously weakened the usage of the chitinozoan data and has failed to provide data support on the study of chitinozoan macroevolution, biostratigraphy, palaeobiogeography, and palaeoecology. Third, recent studies have provided new insights into the biological affinity of chitinozoans, albeit with some controversies. New evidence is required to further discuss this issue. ＜br＞To effectively facilitate chitinozoan studies, we suggest designing and constructing an open-access chitinozoan database for all the 1311 documented chitinozoan species on the Geobiodiversity Database platform. This database will present combined information such as taxonomy, morphological features, high-resolution images, locality data, formations, ages, section information, and related references. Registered users can search, input, revise, import and analyse the data. In the meantime, revisions on poorly documented chitinozoan records from China and the Baltic will be carried out as a first step to make the data more reliable. Advanced imaging techniques, such as Near-Infrared Microscopy, focused ion beam scanning electron microscopy, field emission scanning electron microscope, and X-ray computed micro-tomography will be applied to update the morphological information of all poorly imaged types, including their interior structures and ultrastructures. Revisions on controversial chitinozoan records from the Ordovician as well as those from the Silurian and the Devonian in other areas will be carried out in the future.
Creating a global chitinozoan database and revising poorly presented chitinozoan records based on extensive data analysis and high-resolution imaging techniques will be a significant advance for the field. This will substantially facilitate the study of the morphology, microevolution, biostratigraphy, palaeogeography and palaeoecology of chitinozoans. This project will bring chitinozoan research into a new era and will be an essential case study to show how far basic research can go with the support of big data and advanced techniques.

国家自然科学基金(41972015)；中国科学院青年促进会会员(2021306)；中国科学院战略性先导科技专项(B类) (XDB26000000)联合资助