scholarly journals Changes in Ocean Ventilation Rates Over the Last 7000 Years Based on 14C Variations in the Atmosphere and Oceans

Radiocarbon ◽  
1989 ◽  
Vol 31 (03) ◽  
pp. 481-492 ◽  
Author(s):  
T-H Peng
Keyword(s):  
Age Differences ◽  
Benthic Foraminifera ◽  
Deep Sea ◽  
Ventilation Rate ◽  
Global Ocean ◽  
Production Rates ◽  
The Past ◽  
Ocean Ventilation ◽  
Deep Sea Sediments ◽  
Ventilation Rates

Changes in the ocean ventilation rate may be one of the causes for a net decrease of 100‰ Δ 14C in atmospheric CO2 over the last 8000 years. Ocean ventilation rates of the past can be derived from the 14C record preserved in planktonic and benthic foraminifera in deep-sea sediments. Results of 14C dating using accelerator mass spectrometry on deep sea sediments from the South China Sea show that the age differences between planktonic (G sacculifer) and benthic foraminifera increase from 1350 yr ca 7000 yr ago to 1590 yr at present. An 11-box geochemical model of global ocean circulation was used for this study. Both tree-ring-determined atmospheric 14C values and foraminifera 14C age differences are used as constraints to place limits on patterns of changes in ocean ventilation rates and in atmospheric 14C production rates. Results indicate: 1) 14C production rates in the atmosphere may have decreased by as much as 30% between 7000 and 3000 yr ago, and may have increased again by ca 15% in the past 2000 yr, and 2) the global ocean ventilation rate may not have been at steady state over the last 7000 yr, but may have slowed by as much as 35%.

Can Radiocarbon Records lead to Quantitative Estimates of Deep-Ocean Ventilation Rates with Error Estimates in the Geologic Past?

2020 ◽  
Author(s):  
Olivier Marchal ◽  
Ning Zhao ◽  
Faith Duffy
Keyword(s):  
Least Squares ◽  
Error Estimates ◽  
Deep Water ◽  
Benthic Foraminifera ◽  
Deep Ocean ◽  
The Past ◽  
Ocean Ventilation ◽  
Quantitative Estimates ◽  
History Of ◽  
Ventilation Rates

<p>Over the past two decades, an impressive amount of radiocarbon age measurements on samples of fossil benthic foraminifera and deep-sea corals have been published in the literature. These measurements are commonly used to draw inferences about changes in the ventilation of deep oceanic basins during the last deglacial period. Lacking in most previous studies, however, are quantitative estimates of deep-ocean paleo-ventilation rates and quantitative estimates of their errors, leading to potential over-interpretation and sterile debate. Moreover, most previous studies were concerned with the interpretation of individual records with low or no regard for other records available for the same time interval.</p><p>Here we present an effort to go beyond the qualitative interpretation of single radiocarbon records by analyzing an updated compilation of <sup>14</sup>C age data using recursive least-squares (RLS) methods (a Kalman filter and a related smoother). In stark contrast with other methods of data analysis, RLS methods can provide an estimate of the history of the state of the physical system of interest and an estimate of the error in this history, which are consistent (in the least-squares sense) with times series of data and with a dynamical model, given estimates of the statistics of the errors in the data and in the model. Our current compilation includes 1,698 deep water <sup>14</sup>C age data for the past 40 kyr based on fossil samples of benthic foraminifera, deep‐sea corals, deep‐dwelling planktonic foraminifera, bivalves, and spiral shells. The geographic distribution of the samples is very irregular, with most of them originating from near the margins and with large regions devoid of any data. The depths of the samples vary from about 250 m to about 5,000 m. In our study, the potential of RLS methods to estimate the history of deep-ocean ventilation rates and their errors from deep water <sup>14</sup>C age data is explored for a number of abyssal layers in the Atlantic Ocean during the deglacial interval from 20 to 10 kyr BP. The approach used to apply the powerful but computationally expensive RLS methods to the analysis of geologic time series is described, the least-squares estimates of ventilation rate history in different layers are reported, and their significance in the light of their error estimates is discussed.</p>

scholarly journals AMS Radiocarbon Dates on Foraminifera from Deep Sea Sediments

Radiocarbon ◽  
1986 ◽  
Vol 28 (2A) ◽  
pp. 424-428 ◽  
Author(s):  
Michael Andree ◽  
Hans Oeschger ◽  
W S Broecker ◽  
Nancy Beavan ◽  
Alan Mix ◽  
...  
Keyword(s):  
Deep Sea ◽  
East Pacific Rise ◽  
Ventilation Rate ◽  
Age Difference ◽  
Radiocarbon Dates ◽  
The Past ◽  
East Pacific ◽  
Multiple Analysis ◽  
Planktonic Species ◽  
The Tropical Pacific

14C ages were determined on samples of foraminifera separated from cores from three areas of the tropical Pacific (East Pacific Rise, Oontong Java Plateau, and South China Sea). Analyses were made on four planktonic species and on mixed benthics. The purpose of the multiple analysis on planktonic species is to assess the importance of artifacts resulting from the bioturbation-abundance change couple, from the bioturbation-partial dissolution couple and from redeposition by bottom currents. The goal is to use the benthic-planktonic age difference as a means of establishing changes in deep sea ventilation rate over the past 25,000 years. Results of a part of this work are presented in this paper.

scholarly journals Varying responses to I ndian monsoons during the past 220 kyr recorded in deep‐sea sediments in inner and outer regions of the G ulf of A den

2015 ◽  
Vol 120 (11) ◽  
pp. 7253-7270 ◽  
Author(s):  
Yuta Isaji ◽  
Hodaka Kawahata ◽  
Naohiko Ohkouchi ◽  
Nanako O. Ogawa ◽  
Masafumi Murayama ◽  
...  
Keyword(s):  
Deep Sea ◽  
The Past ◽  
Deep Sea Sediments

Microhabitats of benthic foraminifera within deep-sea sediments

Nature ◽  
1985 ◽  
Vol 314 (6010) ◽  
pp. 435-438 ◽  
Author(s):  
Bruce H. Corliss
Keyword(s):  
Benthic Foraminifera ◽  
Deep Sea ◽  
Deep Sea Sediments

scholarly journals Viral decay and viral production rates in continental-shelf and deep-sea sediments of the Mediterranean Sea

2010 ◽  
Vol 72 (2) ◽  
pp. 208-218 ◽  
Author(s):  
Cinzia Corinaldesi ◽  
Antonio Dell'Anno ◽  
Mirko Magagnini ◽  
Roberto Danovaro
Keyword(s):  
Continental Shelf ◽  
Mediterranean Sea ◽  
Deep Sea ◽  
Viral Production ◽  
Production Rates ◽  
Deep Sea Sediments ◽  
The Mediterranean

scholarly journals Deep-sea sediments of the global ocean

2020 ◽  
Author(s):  
Markus Diesing
Keyword(s):  
Machine Learning ◽  
Spatial Distribution ◽  
Deep Sea ◽  
Learning Algorithm ◽  
Marine Species ◽  
Global Ocean ◽  
Teaching Management ◽  
Sediment Distribution ◽  
Deep Sea Sediments ◽  
Seafloor Sediment

Abstract. Although the deep-sea floor accounts for more than 70 % of the Earth's surface, there has been little progress in relation to deriving maps of seafloor sediment distribution based on transparent, repeatable and automated methods such as machine learning. A new digital map of the spatial distribution of seafloor lithologies in the deep sea below 500 m water depth is presented to address this shortcoming. The lithology map is accompanied by estimates of the probability of the most probable class, which may be interpreted as a spatially-explicit measure of confidence in the predictions, and probabilities for the occurrence of seven lithology classes (Calcareous sediment, Clay, Diatom ooze, Lithogenous sediment, Mixed calcareous-siliceous ooze, Radiolarian ooze and Siliceous mud). These map products were derived by the application of the Random Forest machine learning algorithm to a homogenised dataset of seafloor lithology samples and global environmental predictor variables that were selected based on the current understanding of the controls on the spatial distribution of deep-sea sediments. The overall accuracy of the lithology map is 69.5 %, with 95 % confidence limits of 67.9 % and 71.1 %. It is expected that the map products are useful for various purposes including, but not limited to, teaching, management, spatial planning, design of marine protected areas and as input for global spatial predictions of marine species distributions and seafloor sediment properties. The map products are available at https://doi.org/10.1594/PANGAEA.911692 (Diesing, 2020).

Application of machine learning to map the global distribution of deep-sea sediments

2020 ◽  
Author(s):  
Markus Diesing
Keyword(s):  
Machine Learning ◽  
Deep Sea ◽  
Learning Algorithm ◽  
Predictor Variable ◽  
Global Ocean ◽  
Predictor Variables ◽  
Maximum Temperature ◽  
Sea Floor ◽  
Deep Sea Sediments ◽  
Calcareous Sediment

<p>The deep-sea floor accounts for >90% of seafloor area and >70% of the Earth’s surface. It acts as a receptor of the particle flux from the surface layers of the global ocean, is a place of biogeochemical cycling, records environmental and climate conditions through time and provides habitat for benthic organisms. Maps of the spatial patterns of deep-sea sediments are therefore a major prerequisite for many studies addressing aspects of deep-sea sedimentation, biogeochemistry, ecology and related fields.</p><p>A new digital map of deep-sea sediments of the global ocean is presented. The map was derived by applying the Random Forest machine-learning algorithm to published sample data of seafloor lithologies and environmental predictor variables. The selection of environmental predictors was initially based on the current understanding of the controls on the distribution of deep-sea sediments and the availability of data. A predictor variable selection process ensured that only important and uncorrelated variables were employed in the model. The three most important predictor variables were sea-surface maximum salinity, sea-floor maximum temperature and bathymetry. The occurrence probabilities of seven seafloor lithologies (Calcareous sediment, Clay, Diatom ooze, Lithogenous sediment, Mixed calcareous-siliceous ooze, Radiolarian ooze and Siliceous mud) were spatially predicted. The final map shows the most probable seafloor lithology and an associated probability value, which may be viewed as a spatially explicit measure of map confidence. An assessment of the accuracy of the map was based on a test set of observations not used for model training. Overall map accuracy was 69.5% (95% confidence interval: 67.9% - 71.1%). The sea-floor lithology map bears some resemblance with previously published hand-drawn maps in that the distribution of Calcareous sediment, Clay and Diatom ooze are very similar. Clear differences were however also noted: Most strikingly, the map presented here does not display a band of Radiolarian ooze in the equatorial Pacific.</p><p>The probability surfaces of individual seafloor lithologies, the categorical map of the seven mapped lithologies and the associated map confidence will be made freely available. It is hoped that they form a useful basis for research pertaining to deep-sea sediments.</p>

Pleistocene Climates in Central Europe: At least 17 Interglacials after the Olduvai Event

1977 ◽  
Vol 7 (3) ◽  
pp. 363-371 ◽  
Author(s):  
Julius Fink ◽  
George J. Kukla
Keyword(s):  
Environmental Change ◽  
Central Europe ◽  
Forest Soils ◽  
Deep Sea ◽  
Temperate Forests ◽  
Hardwood Forests ◽  
The Past ◽  
Deep Sea Sediments ◽  
Depositional Cycles ◽  
Definition Of

At least 17 times during the past 1.7 million years, the deposition of loess containing characteristic cold-resistant gastropods was interrupted by the development of temperate interglacial forests. This conclusion was reached in a study of paleomagnetically dated fossiliferous loess sequences in Krems, Austria and Brno, Czechoslovakia. Sequences of windblown loess interlayered with hillwash loams and steppe and forest soils exposed in brickyards around Brno and Praha, Czechoslovakia, revealed eight major depositional cycles within the Brunhes paleomagnetic epoch. We now report nine additional cycles of late and middle Matuyama age bringing the total number of glacial-interglacial cycles to 17, which occurred after the end of the Olduvai. The cycles are separated by marklines, levels of abrupt environmental change correlative with the terminations in deep-sea sediments. They are the boundaries between the windblown loess containing cold-resistant snail assemblages and between the clayey originally decalcified soils, accompanied by warmth loving Helix and Banatica snail faunas of hardwood forests. Because the presence of temperate forests in northwestern and central Europe is instrumental in the definition of an interglacial, each markline represents a glacial-interglacial boundary and each cycle is a glacial-interglacial cycle.

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