DOI: 10.1016/j.epsl.2021.116790
论文题名: How is sea level change encoded in carbonate stratigraphy?
作者: Geyman E.C. ; Maloof A.C. ; Dyer B.
刊名: Earth and Planetary Science Letters
ISSN: 0012821X
出版年: 2021
卷: 560 语种: 英语
中文关键词: Bahamas
; carbonates
; cycles
; sedimentary facies
; stratigraphy
英文关键词: Biology
; Carbonates
; Carbonation
; Convolutional neural networks
; Hidden Markov models
; Satellite imagery
; Sedimentary rocks
; Sedimentology
; Signal processing
; Statistical mechanics
; Stratigraphy
; Carbonate stratigraphies
; Field observations
; Random variability
; Relative sea level
; Sea level condition
; Seawater chemistry
; Stacking patterns
; Statistical tools
; Sea level
; artificial neural network
; bathymetry
; carbonate
; facies
; forward modeling
; Markov chain
; satellite imagery
; sea level change
; stratigraphy
; water depth
; Andros [Bahamas]
; Bahamas
英文摘要: The history of organismal evolution, seawater chemistry, and paleoclimate is recorded in layers of carbonate sedimentary rock. Meter-scale cyclic stacking patterns in these carbonates often are interpreted as representing sea level change. A reliable sedimentary proxy for eustasy would be profoundly useful for reconstructing paleoclimate, since sea level responds to changes in temperature and ice volume. However, the translation from water depth to carbonate layering has proven difficult, with recent surveys of modern shallow water platforms revealing little correlation between carbonate facies (i.e., grain size, sedimentary bed forms, ecology) and water depth. We train a convolutional neural network with satellite imagery and new field observations from a 3,000 km2 region northwest of Andros Island (Bahamas) to generate a facies map with 5 m resolution. Leveraging a newly-published bathymetry for the same region, we test the hypothesis that one can extract a signal of water depth change, not simply from individual facies, but from sequences of facies transitions analogous to vertically stacked carbonate strata. Our Hidden Markov Model (HMM) can distinguish relative sea level fall from random variability with ∼90% accuracy. Finally, since shallowing-upward patterns can result from local (autogenic) processes in addition to forced mechanisms such as eustasy, we search for statistical tools to diagnose the presence or absence of external forcings on relative sea level. With a new data-driven forward model that simulates how modern facies mosaics evolve to stack strata, we show how different sea level forcings generate characteristic patterns of cycle thicknesses in shallow carbonates, providing a new tool for quantitative reconstruction of ancient sea level conditions from the geologic record. © 2021 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/165478
Appears in Collections: 气候变化与战略
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作者单位: Department of Geosciences, Princeton University, Princeton, NJ, United States; Department of Earth and Ocean Sciences, University of Victoria, Victoria, BC, Canada
Recommended Citation:
Geyman E.C.,Maloof A.C.,Dyer B.. How is sea level change encoded in carbonate stratigraphy?[J]. Earth and Planetary Science Letters,2021-01-01,560