A perspective on reconstructing the spatial and temporal patterns of Earth's biodiversity in deep time
Reconstructing the extensive history of biodiversity in deep time is crucial to understanding the evolutionary patterns on Earth.As the sands of geological time flow,we can uncover glimpses into the origin,evolution and extinction of life in an effort to unravel its mysteries.Yet,over 99％of the organisms which once called this planet home have been washed away by time,with only a fraction of them leaving behind any clues of their existence in the form of fossils,much fewer of which have been discovered by mankind.Therefore,the process of reconstructing Earth's evolution history of biodiversity using only a small portion of fossil occurrences has proven to be a complex and strenuous task.The solution is to employ a multidisciplinary approach.Firstly,it is essential to establish a comprehensive global database that contains detailed spatial and temporal data of all fossil records.This database will serve as the basis for studying biodiversity patterns throughout earth history and identifying major biological events.Previous studies have mainly focused on marine invertebrate fossil records and the global terrestrial biodiversity curve remains to be established.Secondly,the incompleteness of fossil records and the uneven geographical sampling need to be addressed.Over the past decade,while substantial data have been accumulated and some analytical methods to solve uneven sampling in big data analysis have been explored,researchers have yet to provide an elegant solution to the problem.Thirdly,as the quantity of data increases and the quality of data has improved,new findings derived from big data have sparked numerous insights into the spatial and temporal patterns of biodiversity change on Earth through deep time.For example,with the publication of more data around the big five mass extinctions the extinction magnitudes and rates of extinction have declined accordingly,thereby requiring more accurate re-estimation using global big data.Among these extinctions,the end-Permian biological extinction undoubtedly remains the largest,while it is highly likely that the late Devonian F/F and the end-Triassic extinction events may have lost their Big Five places.Similarly,the duration and extinction magnitude of the end-Cretaceous biological extinction should be carefully re-evaluated under the lens of big data in a high-resolution timeline.In addition,the three major biodiversifications respectively during the Cambrian-Ordovician,Carboniferous-Permian,and Cenozoic also require verification using global high-resolution fossil data.The future research direction to achieve comparisons between deep time and the present time probably lies with ecosystem modeling supported by big data,artificial intelligence,supercomputing algorithms,and other techniques.These studies will enable us to realize a more comprehensive understanding of Earth's biodiversity pattern which will serve as a unique reference for solving the problems of global ecosystems faced human today.In summary,reconstructing the history of Earth's biodiversity is of great importance for understanding the evolution of life and predicting the future development of the Earth's ecosystem.Although many important advances have been made in the reconstruction of the Earth's biodiversity history over the past half a century,the problems of uncertainty,incompleteness and inconsistency of geological historical data,as well as the low spatial and temporal resolution of the Earth's biodiversity,are still to be solved by further efforts of scientists.Chinese scientists are leading the international charge in the field of stratigraphic palaeontology,and have achieved important results in the construction of geoscience databases and the application of big data.We need to make more efforts in the field of deep-time global biodiversity research,open up new disciplinary directions,and endeavour to contribute to the deep-time experience for the major scientific goal of a livable Earth.
deep timebig databiodiversitymass extinctionecological modelling
万方数据
维普
