Extreme weather events recorded by daily to hourly resolution biogeochemical proxies of marine giant clam shells

Yan, Hong; Liu, Chengcheng; An, Zhisheng; Yang, Wei; Yang, Yibo; Huang, Ping; Qiu, Shican; Zhou, Pengchao; Zhao, Nan; Fei, Haobai; Ma, Xiaolin; Shi, Ge; Dodson, John; Hao, Jialong; Yu, Kefu; Wei, Gangjian; Yang, Ya‐Nan; Jin, Zhangdong; Zhou, Wei

doi:10.1073/pnas.1916784117

Cited by 54 publications

(29 citation statements)

References 33 publications

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“…While the discussion above focuses on optimizing approaches for combining samples for clumped isotope analyses in paleoseasonality reconstructions, the problem of combining samples to reduce uncertainty and isolate variation in datasets is very common (e.g., Zhang et al, 2004;Merz and Thieken, 2005;Tsukakoshi, 2011). Therefore, the approaches outlined and tested in this study have applications beyond paleoseasonality reconstructions.…”

Section: Implications For Other Sample Size Problemsmentioning

confidence: 99%

Optimizing sampling strategies in high-resolution paleoclimate records

2021

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Abstract. The aim of paleoclimate studies resolving climate variability from noisy proxy records can in essence be reduced to a statistical problem. The challenge is to extract meaningful information about climate variability from these records by reducing measurement uncertainty through combining measurements for proxies while retaining the temporal resolution needed to assess the timing and duration of variations in climate parameters. In this study, we explore the limits of this compromise by testing different methods for combining proxy data (smoothing, binning, and sample size optimization) on a particularly challenging paleoclimate problem: resolving seasonal variability in stable isotope records. We test and evaluate the effects of changes in the seasonal temperature and the hydrological cycle as well as changes in the accretion rate of the archive and parameters such as sampling resolution and age model uncertainty in the reliability of seasonality reconstructions based on clumped and oxygen isotope analyses in 33 real and virtual datasets. Our results show that strategic combinations of clumped isotope analyses can significantly improve the accuracy of seasonality reconstructions compared to conventional stable oxygen isotope analyses, especially in settings in which the isotopic composition of the water is poorly constrained. Smoothing data using a moving average often leads to an apparent dampening of the seasonal cycle, significantly reducing the accuracy of reconstructions. A statistical sample size optimization protocol yields more precise results than smoothing. However, the most accurate results are obtained through monthly binning of proxy data, especially in cases in which growth rate or water composition cycles obscure the seasonal temperature cycle. Our analysis of a wide range of natural situations reveals that the effect of temperature seasonality on oxygen isotope records almost invariably exceeds that of changes in water composition. Thus, in most cases, oxygen isotope records allow reliable identification of growth seasonality as a basis for age modeling in the absence of independent chronological markers in the record. These specific findings allow us to formulate general recommendations for sampling and combining data in paleoclimate research and have implications beyond the reconstruction of seasonality. We briefly discuss the implications of our results for solving common problems in paleoclimatology and stratigraphy.

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Section: Implications For Other Sample Size Problemsmentioning

confidence: 99%

Optimizing sampling strategies in high-resolution paleoclimate records

2021

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“…Sano et al, 2012;Warter andMüller, 2017, de Winter et al, 2020a). The emergence of such records allows new information to be obtained about the daily cycle (Warter et al, 2018;de Winter et al, 2020a) and extreme weather events (Yan et al, 2020) in the past, potentially bridging the gap between weather and climate reconstructions. The sampling resolution required to resolve variability at such a fine temporal scale warrants an even more careful consideration of the tradeoff between sample size, sampling resolution and analytical uncertainty than the paleoseasonality examples considered here.…”

Section: Sub-seasonal Variabilitymentioning

confidence: 99%

“…The sampling resolution required to resolve variability at such a fine temporal scale warrants an even more careful consideration of the tradeoff between sample size, sampling resolution and analytical uncertainty than the paleoseasonality examples considered here. If quantitative estimates of insolation, temperature and the frequency of extreme weather events are to be reconstructed from these novel records, a compromise will need to be found between analytical uncertainty and the temporal resolution of measurements (Sano et al, 2012;de Winter et al, 2020a;Yan et al, 2020). Applying the temporal (e.g.…”

Section: Sub-seasonal Variabilitymentioning

confidence: 99%

Optimizing sampling strategies in high-resolution paleoclimate records

Winter¹,

Agterhuis²,

Ziegler³

2020

Preprint

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Abstract. The aim of paleoclimate studies to resolve climate variability from noisy proxy records can in essence be reduced to a statistical problem. The challenge is to isolate meaningful information on climate events from these records by reducing measurement uncertainty through a combination of proxy data while retaining the temporal resolution needed to assess the timing and duration of the event. In this study, we explore the limits of this compromise by testing different methods for combining proxy data (smoothing, binning and sample size optimization) on a particularly challenging paleoclimate problem: resolving seasonal variability in stable isotope records. We test and evaluate the effects of changes in the seasonal temperature and hydrology cycle as well as changes in accretion rate of the archive and parameters such as sampling resolution and age model uncertainty on the reliability of seasonality reconstructions based on clumped and oxygen isotope analyses in 33 real and virtual datasets. Our results show that strategic combinations of clumped isotope analyses can significantly improve the accuracy of seasonality reconstructions if compared with conventional stable oxygen isotope analyses, especially in settings where the isotopic composition of the water is poorly constrained. Smoothing data using a moving average often leads to a dampening of the seasonal cycle, significantly reducing the accuracy of reconstructions. A statistical sample size optimization protocol yields more precise results than smoothing. However, the most accurate results are obtained through monthly binning of proxy data, especially in cases where growth rate or water composition cycles dampen the seasonal temperature cycle. Our analysis of a wide range of natural situations reveals that the effect of temperature seasonality on isotope records almost invariably exceeds that of changes in water composition. Thus, in most cases, isotope records allow reliable identification of growth seasonality as a basis for age modelling and seasonality reconstructions in absence of independent chronological markers in the record. These specific findings allow us to formulate general recommendations for sampling and combining data in paleoclimate research and have implications beyond the reconstruction of seasonality. We discuss the implications of our results for solving common problems in paleoclimatology and stratigraphy, including cyclostratigraphy, strontium isotope dating and event stratigraphy.

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“…All Tridacna species produce thick, dense and rigid shells mostly of crossed lamellar microstructure ( Taylor, 1973 ; Dauphin and Denis, 2000 ; Agbaje et al, 2017 ; Gannon et al, 2017 ). As the giant clams continue to grow their shells throughout the life, shells are precise recorders of environmental conditions such as seawater temperature ( Arias-Ruiz et al, 2017 ; Yan et al, 2020 ). The longevity of giant clams allows the shells to archive long-term environmental conditions, with a resolution ranging from century to month, or even higher ( Yan et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

“…As the giant clams continue to grow their shells throughout the life, shells are precise recorders of environmental conditions such as seawater temperature ( Arias-Ruiz et al, 2017 ; Yan et al, 2020 ). The longevity of giant clams allows the shells to archive long-term environmental conditions, with a resolution ranging from century to month, or even higher ( Yan et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

The ‘Shellome’ of the Crocus Clam Tridacna crocea Emphasizes Essential Components of Mollusk Shell Biomineralization

et al. 2021

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Molluscan shells are among the most fascinating research objects because of their diverse morphologies and textures. The formation of these delicate biomineralized structures is a matrix-mediated process. A question that arises is what are the essential components required to build these exoskeletons. In order to understand the molecular mechanisms of molluscan shell formation, it is crucial to identify organic macromolecules in different shells from diverse taxa. In the case of bivalves, however, taxon sampling in previous shell proteomics studies are focused predominantly on representatives of the class Pteriomorphia such as pearl oysters, edible oysters and mussels. In this study, we have characterized the shell organic matrix from the crocus clam, Tridacna crocea, (Heterodonta) using various biochemical techniques, including SDS-PAGE, FT-IR, monosaccharide analysis, and enzyme-linked lectin assay (ELLA). Furthermore, we have identified a number of shell matrix proteins (SMPs) using a comprehensive proteomics approach combined to RNA-seq. The biochemical studies confirmed the presence of proteins, polysaccharides, and sulfates in the T. crocea shell organic matrix. Proteomics analysis revealed that the majority of the T. crocea SMPs are novel and dissimilar to known SMPs identified from the other bivalve species. Meanwhile, the SMP repertoire of the crocus clam also includes proteins with conserved functional domains such as chitin-binding domain, VWA domain, and protease inhibitor domain. We also identified BMSP (Blue Mussel Shell Protein, originally reported from Mytilus), which is widely distributed among molluscan shell matrix proteins. Tridacna SMPs also include low-complexity regions (LCRs) that are absent in the other molluscan genomes, indicating that these genes may have evolved in specific lineage. These results highlight the diversity of the organic molecules – in particular proteins – that are essential for molluscan shell formation.

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Extreme weather events recorded by daily to hourly resolution biogeochemical proxies of marine giant clam shells

Abstract: This article contains supporting information online at https://www.pnas.org/lookup/suppl/

Cited by 54 publications

References 33 publications

Optimizing sampling strategies in high-resolution paleoclimate records

Optimizing sampling strategies in high-resolution paleoclimate records

Optimizing sampling strategies in high-resolution paleoclimate records

The ‘Shellome’ of the Crocus Clam Tridacna crocea Emphasizes Essential Components of Mollusk Shell Biomineralization

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