Assessment of C, N, and Si Isotopes as Tracers of Past Ocean Nutrient and Carbon Cycling

28 pages, 6 figures, 1 box, 1 appendix.-- Data Availability Statement: Data sets presented in this research are available via the following repositories and study (listed by Figure): Figures 3 and 4: (1)δ13CDIC:(a) CLIVAR P16S (Feely et al., 2008) from GLODAPv2.2020 database (Olsen et al., 2020): https://www.glodap.info/index.php/merged-and-adjusted-data-product/. (b) GEOTRACES GA03 (Quay & Wu, 2015) and GP16 (P. Quay, unpublished data) from GEOTRACES IDP2017 (Schlitzer et al., 2018): https://www.bodc.ac.uk/geotraces/data/idp2017/. (2) δ15Nnitrate:(a) CLIVAR P16S (Rafter et al., 2013) from BCO-DMO: https://www.bco-dmo.org/dataset/651722. (b) GEOTRACES GA03 (Marconi et al., 2015) and GP16 (Peters et al., 2018) from GEOTRACES IDP2017 (Schlitzer et al., 2018): https://www.bodc.ac.uk/geotraces/data/idp2017/. (3) δ30Si: GEOTRACES GA03 (Brzezinski & Jones, 2015) and GIPY04 (Fripiat et al., 2012) from GEOTRACES IDP2017 (Schlitzer et al., 2018): https://www.bodc.ac.uk/geotraces/data/idp2017/. (4) Figure 4a POC Flux (DeVries & Weber, 2017): SIMPLE-TRIM Output from https://tdevries.eri.ucsb.edu/models-and-data-products/. Figure 5: (a) Antarctic CO2 composite: https://www.ncdc.noaa.gov/paleo-search/study/17975. (b) ∆δ13Cthermocline-deep from Ziegler et al. (2013) supporting information: https://www.nature.com/articles/ngeo1782; ∆δ13Cepifaunal-infaunal (Hoogakker et al., 2018): https://doi.pangaea.de/10.1594/PANGAEA.891185. (c) SAZ FB-δ15N (Martínez-García et al., 2014): https://www.ncdc.noaa.gov/paleo/study/18318; AZ DB-δ15N (Studer et al., 2015): https://doi.pangaea.de/10.1594/PANGAEA.848271. (d) SAZ Fe flux (Martínez-García et al., 2014): https://www.ncdc.noaa.gov/paleo/study/18318. (e) AZ diatom δ30Si (Robinson et al., 2014): https:// www.ncdc.noaa.gov/paleo/study/17917. Figure 6: (a) and (b) Benthic foraminifera δ18O and δ13C (Zachos et al., 2001): https:// www.ncdc.noaa.gov/paleo/study/8674. (c) FB-δ15N from Kast et al. (2019) supporting information data: https://science.sciencemag.org/content/suppl/2019/04/24/364.6438.386.DC1. (d) and (e) Diatom, sponge, and radiolarian δ30Si in Egan et al. (2013) supporting information: https://www.sciencedirect.com/science/article/pii/S0012821X13002185, Fontorbe et al. (2016) supporting information: https://www.sciencedirect.com/science/article/pii/S0012821X16304265, and Fontorbe et al. (2017) supporting information: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2017PA003090Biological productivity in the ocean directly influences the partitioning of carbon between the atmosphere and ocean interior. Through this carbon cycle feedback, changing ocean productivity has long been hypothesized as a key pathway for modulating past atmospheric carbon dioxide levels and hence global climate. Because phytoplankton preferentially assimilate the light isotopes of carbon and the major nutrients nitrate and silicic acid, stable isotopes of carbon (C), nitrogen (N), and silicon (Si) in seawater and marine sediments can inform on ocean carbon and nutrient cycling, and by extension the relationship with biological productivity and global climate. Here, we compile water column C, N, and Si stable isotopes from GEOTRACES-era data in four key ocean regions to review geochemical proxies of oceanic carbon and nutrient cycling based on the C, N, and Si isotopic composition of marine sediments. External sources and sinks as well as internal cycling (including assimilation, particulate matter export, and regeneration) are discussed as likely drivers of observed C, N, and Si isotope distributions in the ocean. The potential for C, N, and Si isotope measurements in sedimentary archives to record aspects of past ocean C and nutrient cycling is evaluated, along with key uncertainties and limitations associated with each proxy. Constraints on ocean C and nutrient cycling during late Quaternary glacial-interglacial cycles and over the Cenozoic are examined. This review highlights opportunities for future research using multielement stable isotope proxy applications and emphasizes the importance of such applications to reconstructing past changes in the oceans and climate systemThis workshop was funded by the United States National Science Foundation (NSF) through the GEOTRACES program, the international Past Global Changes (PAGES) project, which in turn received support from the Swiss Academy of Sciences and NSF, and the French national program LEFE (Les Enveloppes Fluides et l'Environnement). [...] This study was supported by PAGES, LEFE, and GEOTRACES through NSF. J. R. Farmer acknowledges support from the Max Planck Society, the Tuttle Fund of the Department of Geosciences of Princeton University, the Grand Challenges Program of the Princeton Environmental Institute, and through Exxon Mobil via the Andlinger Center for Energy and the Environment of Princeton University. Open access funding enabled and organized by Projekt DEAL. [...] With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S

Bioactive Trace Metals and Their Isotopes as Paleoproductivity Proxies: An Assessment Using GEOTRACES-Era Data

86 pages, 33 figures, 2 tables, 1 appendix.-- Data Availability Statement: The majority of the dissolved data were sourced from the GEOTRACES Intermediate Data Products in 2014 (Mawji et al., 2015) and 2017 (Schlitzer et al., 2018), and citations to the primary data sources are given in the caption for each figure. Data sources for Figure 1 are given below. Figure 1: Iron: Conway & John, 2014a (Atlantic); Conway & John, 2015a (Pacific); Abadie et al., 2017 (Southern). Zinc: Conway & John, 2014b (Atlantic); Conway & John, 2015a (Pacific); R. M. Wang et al., 2019 (Southern). Copper: Little et al., 2018 (Atlantic); Takano et al., 2017 (Pacific); Boye et al., 2012 (Southern). Cadmium: Conway and John, 2015b (Atlantic); Conway & John, 2015a (Pacific); Abouchami et al., 2014 (Southern). Molybdenum: Nakagawa et al., 2012 (all basins). Barium: Bates et al., 2017 (Atlantic); Geyman et al., 2019 (Pacific); Hsieh & Henderson, 2017 (Southern). Nickel: Archer et al., 2020 (Atlantic); Takano et al., 2017 (Pacific); R. M. Wang et al., 2019 (Southern). Chromium: Goring-Harford et al., 2018 (Atlantic); Moos & Boyle, 2019 (Pacific); Rickli et al., 2019 (Southern). Silver: Fischer et al., 2018 (Pacific); Boye et al., 2012 (Southern)Phytoplankton productivity and export sequester climatically significant quantities of atmospheric carbon dioxide as particulate organic carbon through a suite of processes termed the biological pump. Constraining how the biological pump operated in the past is important for understanding past atmospheric carbon dioxide concentrations and Earth's climate history. However, reconstructing the history of the biological pump requires proxies. Due to their intimate association with biological processes, several bioactive trace metals and their isotopes are potential proxies for past phytoplankton productivity, including iron, zinc, copper, cadmium, molybdenum, barium, nickel, chromium, and silver. Here, we review the oceanic distributions, driving processes, and depositional archives for these nine metals and their isotopes based on GEOTRACES-era datasets. We offer an assessment of the overall maturity of each isotope system to serve as a proxy for diagnosing aspects of past ocean productivity and identify priorities for future research. This assessment reveals that cadmium, barium, nickel, and chromium isotopes offer the most promise as tracers of paleoproductivity, whereas iron, zinc, copper, and molybdenum do not. Too little is known about silver to make a confident determination. Intriguingly, the trace metals that are least sensitive to productivity may be used to track other aspects of ocean chemistry, such as nutrient sources, particle scavenging, organic complexation, and ocean redox state. These complementary sensitivities suggest new opportunities for combining perspectives from multiple proxies that will ultimately enable painting a more complete picture of marine paleoproductivity, biogeochemical cycles, and Earth's climate historyThis contribution grew (and grew) out of a joint workshop between GEOTRACES and Past Global Changes (PAGES) held in Aix-en-Provence in December 2018. The workshop was funded by the U.S. National Science Foundation (NSF) through the GEOTRACES program, the international PAGES project, which received support from the Swiss Academy of Sciences and NSF, and the French program Les Envelopes Fluides et l'Environnement. [...] T. J. Horner acknowledges support from NSF; S. H. Little from the UK Natural Environment Research Council (NE/P018181/1); T. M. Conway from the University of South Florida; and, J. R. Farmer from the Max Planck Society, the Tuttle Fund of the Department of Geosciences of Princeton University, the Grand Challenges Program of the Princeton Environmental Institute, and the Andlinger Center for Energy and the Environment of Princeton University. [...] With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S

Discerning Changes in High-Frequency Climate Variability Using Geochemical Populations of Individual Foraminifera

Individual foraminiferal analysis (IFA) has proven to be a useful tool in reconstructing the amplitude of high-frequency climate signals such as the annual cycle and the El Niño-Southern Oscillation (ENSO). However, using IFA to evaluate past changes in climate variability is complicated by many factors including geographic location, foraminiferal ecology, methods of sample processing, and the influence of multiple, superimposed high-frequency climate signals. Robust statistical tools and rigorous uncertainty analysis are therefore required to ensure the reliability of IFA-based interpretations of paleoclimatic change. Here, we present a new proxy system model—called the Quantile Analysis of Temperature using Individual Foraminiferal Analyses (QUANTIFA)—that combines methods for assessing IFA detection sensitivity with analytical tools for processing and interpreting IFA data to standardize and streamline reconstructions employing IFA-Mg/Ca measurements. Model exercises with simulated and real IFA data demonstrate that the dominant signal retained by IFA populations is largely determined by the annual-to-interannual ratio of climate variability at a given location and depth and can be impacted by seasonal biases in foraminiferal productivity. In addition, our exercises reveal that extreme quantiles can be reliable indicators of past changes in climate variability, are often more sensitive to climate change than quantiles within the distributional interior, and can be used to distinguish changes in interannual phenomena like ENSO from seasonality. Altogether, QUANTIFA provides a useful tool for modeling IFA uncertainties and processing IFA data that can be leveraged to establish a history of past climate variability. © 2021. American Geophysical Union. All Rights Reserved.6 month embargo; first published: 01 February 2021This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Bioactive trace metals and their isotopes as paleoproductivity proxies: An assessment using GEOTRACES‐era data

Phytoplankton productivity and export sequester climatically significant quantities of atmospheric carbon dioxide as particulate organic carbon through a suite of processes termed the biological pump. How the biological pump operated in the past is therefore important for understanding past atmospheric carbon dioxide concentrations and Earth’s climate history. However, reconstructing the history of the biological pump requires proxies. Due to their intimate association with biological processes, several bioactive trace metals and their isotopes are potential proxies for past phytoplankton productivity, including: iron, zinc, copper, cadmium, molybdenum, barium, nickel, chromium, and silver. Here we review the oceanic distributions, driving processes, and depositional archives for these nine metals and their isotopes based on GEOTRACES-era datasets. We offer an assessment of the overall maturity of each isotope system to serve as a proxy for diagnosing aspects of past ocean productivity and identify priorities for future research. This assessment reveals that cadmium, barium, nickel, and chromium isotopes offer the most promise as tracers of paleoproductivity, whereas iron, zinc, copper, and molybdenum do not. Too little is known about silver to make a confident determination. Intriguingly, the elements that are least sensitive to productivity may be used to trace other aspects of ocean chemistry, such as nutrient sources, particle scavenging, organic complexation, and ocean redox state. These complementary sensitivities suggest new opportunities for combining perspectives from multiple proxies that will ultimately enable painting a more complete picture of marine paleoproductivity, biogeochemical cycles, and Earth’s climate history

Black hole formation from axion stars

The classical equations of motion for an axion with potential V(phgr)=ma2fa2 [1−cos (phgr/fa)] possess quasi-stable, localized, oscillating solutions, which we refer to as ``axion stars''. We study, for the first time, collapse of axion stars numerically using the full non-linear Einstein equations of general relativity and the full non-perturbative cosine potential. We map regions on an ``axion star stability diagram", parameterized by the initial ADM mass, MADM, and axion decay constant, fa. We identify three regions of the parameter space: i) long-lived oscillating axion star solutions, with a base frequency, ma, modulated by self-interactions, ii) collapse to a BH and iii) complete dispersal due to gravitational cooling and interactions. We locate the boundaries of these three regions and an approximate ``triple point" (MTP,fTP) ~ (2.4 Mpl2/ma,0.3 Mpl). For fa below the triple point BH formation proceeds during winding (in the complex U(1) picture) of the axion field near the dispersal phase. This could prevent astrophysical BH formation from axion stars with fa Lt Mpl. For larger fa gsim fTP, BH formation occurs through the stable branch and we estimate the mass ratio of the BH to the stable state at the phase boundary to be Script O(1) within numerical uncertainty. We discuss the observational relevance of our findings for axion stars as BH seeds, which are supermassive in the case of ultralight axions. For the QCD axion, the typical BH mass formed from axion star collapse is MBH ~ 3.4 (fa/0.6 Mpl)1.2 M⊙