Abstract The 13C/12C value of dissolved inorganic carbon (DIC) in the ocean has varied through time and can be determined from the marine carbonate record as changes in δ13Ccarb. These variations provide insight into global carbon cycle dynamics, as well as relative age information (chronostratigraphy) that can be used to correlate sedimentary successions globally. The global carbon cycle includes both short- and long-term components, and their interactions dominate the isotopic record presented in this chapter. The partitioning and sequestration of carbon between organic and carbonate rock reservoirs, and their fluxes to and from the ocean–atmosphere–biosphere system, drive secular changes in the δ13C of DIC in the oceans that are ultimately recovered from the stratigraphic record. The pre-Cenozoic data presented here utilize bulk carbonate data for compilation, but a wide range of materials has been analyzed in the literature to produce previous composites. Care must be taken to consider what materials have been analyzed in comparing global carbon isotope records from the literature.
Group-occurring loess falls are common catastrophic geological hazards on the Loess Plateau, typically triggered by heavy rainfall, excessive irrigation, or earthquakes. However, group-occurring loess falls induced by sustained sewage discharge are exceedingly rare. To better understand the failure mechanism of group-occurring loess falls caused by persistent domestic sewage scouring in Liudian Village, Qingyang City, Gansu Province, multi-temporal remote-sensing images and UAV-derived DEMs, together with field investigations, were used to track slope evolution. ERT and drilling were used to characterize subsurface moisture and stratigraphy. A flume test was set up using analogous materials, and water infiltrated from the constant-level tank at the slope toe. Displacement and inclination were monitored. The results show that basal loess saturation increased progressively and caused collapsible settlement. Once the basal layer became fully saturated, the slope toe gradually softened, and capillary action promoted the upward migration of moisture, saturating the upper slope. This hydrological process induced plastic deformation and slow creep, eventually resulting in an overall slope fall and sliding. The entire failure process can be divided into three stages: steady-state deformation, accelerated deformation, and final failure, each displaying distinct characteristics. These observations indicate an erosion-controlled, time-dependent cumulative failure pattern with recurrent collapses under sustained toe water supply. In the future, mitigation can focus on sewage diversion and toe flow interception, together with localized toe protection, to reduce long-term scouring and infiltration.
Abstract Stratal stacking patterns provide the basis for the definition of all units and surfaces of sequence stratigraphy. The same types of stacking patterns may be observed at different scales, in relation to stratigraphic cycles of different magnitudes. At each scale of observation, stacking patterns define systems tracts, and changes in stacking pattern mark the position of sequence stratigraphic surfaces. The construction of a framework of systems tracts and bounding surfaces fulfills the practical purpose of sequence stratigraphy. Beyond this framework, model-dependent choices with respect to the selection of the ‘sequence boundary’ may be made as a function of the mappability of the various types of sequence stratigraphic surface within the studied section. Sequence stratigraphic frameworks are basin-specific in terms of timing and scales of the component units and bounding surfaces, reflecting the interplay of global and local controls on accommodation and sedimentation. A stratigraphic sequence corresponds to a cycle of change in stratal stacking patterns, defined by the recurrence of the same type of sequence stratigraphic surface in the rock record. Sequences, as well as component systems tracts and depositional systems, can be observed at all stratigraphic scales. Sequences of any scale may include unconformities of equal and/or lower hierarchical ranks, whose identification depends on the resolution of the data available. The relative ranking of sequences of different scales is defined by their stratigraphic relationships, as lower rank sequences are nested within higher rank systems tracts. Despite this nested architecture, the stratigraphic framework is not truly fractal because sequences of different scales may differ in terms of underlying controls and internal composition of systems tracts. A scale-independent approach to methodology and nomenclature is key to the standard application of sequence stratigraphy across the entire range of geological settings, stratigraphic scales, and types of data available.
The IceCube Neutrino Observatory is a cubic-kilometer Cherenkov array deployed in the deep, glacial ice at the geographic South Pole. An important feature of the instrumented ice are undulations of layers of constant optical properties over the footprint of the detector. During detector construction, these layers were mapped using stratigraphy measurements obtained from a stand-alone laser dust logger. While this system is very precise, its cost does not scale to the instrumented volume envisioned for the proposed IceCube-Gen2 Observatory. Here, we explore the possibility of obtaining equivalent stratigraphy data from camera footage recorded during the deployment of IceCube more than a decade ago. If successful, this could be an alternative technique to be considered for IceCube-Gen2.
A precise understanding of the optical properties of the instrumented Antarctic ice sheet is crucial to the performance of optical Cherenkov telescopes such as the IceCube Neutrino Observatory and its planned successor, IceCube-Gen2. One complication arising from the large envisioned footprint of IceCube-Gen2 is the larger impact of the so-called ice tilt. It describes the undulation of ice layers of constant optical properties within the detector. In this contribution, we will describe the project to build a co-deployed laser dust logger. This is a device to measure the stratigraphy of impurities in the ice to derive the ice tilt. It consists of a light source that will be co-deployed with the photosensor modules, meaning it is part of the deployment string and operated during the deployment of the detector. The newly developed device will be tested during the deployment of the IceCube Upgrade in the 2025/26 austral summer to pave the way for IceCube-Gen2.
<p>The conventional zircon (U–Th) <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M3" display="inline" overflow="scroll" dspmath="mathml"><mo>/</mo></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="8pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="e653eaf840568ee76bb20ba3bf368ae0"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gchron-6-199-2024-ie00004.svg" width="8pt" height="14pt" src="gchron-6-199-2024-ie00004.png"/></svg:svg></span></span> He (ZHe) method typically uses microscopy measurements of the dated grain together with the assumption that the zircon can be appropriately modeled as a geometrically perfect tetragonal or ellipsoidal prism in the calculation of volume (<span class="inline-formula"><i>V</i></span>), alpha-ejection correction (<span class="inline-formula"><i>F</i><sub>T</sub></span>), equivalent spherical radius (<span class="inline-formula"><i>R</i><sub>FT</sub></span>), effective uranium concentration (eU), and corrected (U–Th) <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M7" display="inline" overflow="scroll" dspmath="mathml"><mo>/</mo></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="8pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="36bd7baae116a5efc17e692d563c2b51"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gchron-6-199-2024-ie00005.svg" width="8pt" height="14pt" src="gchron-6-199-2024-ie00005.png"/></svg:svg></span></span> He date. Here, we develop a set of corrections for systematic error and determine uncertainties to be used in the calculation of the above parameters for zircon, using the same methodology as Zeigler et al. (2023) for apatite. Our approach involved acquiring both “2D” microscopy measurements and high-resolution “3D” nano-computed tomography (CT) data for a suite of 223 zircon grains from nine samples showcasing a wide range of morphology, size, age, and lithological source, calculating the <span class="inline-formula"><i>V</i></span>, <span class="inline-formula"><i>F</i><sub>T</sub></span>, and <span class="inline-formula"><i>R</i><sub>FT</sub></span> values for the 2D and 3D measurements and comparing the 2D vs. 3D results. We find that the values derived from the 2D microscopy data overestimate the true 3D <span class="inline-formula"><i>V</i></span>, <span class="inline-formula"><i>F</i><sub>T</sub></span>, and <span class="inline-formula"><i>R</i><sub>FT</sub></span> values for zircon, with one exception (<span class="inline-formula"><i>V</i></span> of ellipsoidal grains). Correction factors for this misestimation determined by regressing the 3D vs. 2D data range from 0.81–1.04 for <span class="inline-formula"><i>V</i></span>, 0.97–1.0 for <span class="inline-formula"><i>F</i><sub>T</sub></span>, and 0.92–0.98 for <span class="inline-formula"><i>R</i><sub>FT</sub></span>, depending on zircon geometry. Uncertainties (1<span class="inline-formula"><i>σ</i></span>) derived from the scatter of data around the regression line are 13 %–21 % for <span class="inline-formula"><i>V</i></span>, 5 %–1 % for <span class="inline-formula"><i>F</i><sub>T</sub></span>, and 8 % for <span class="inline-formula"><i>R</i><sub>FT</sub></span>, again depending on zircon morphologies. Like for apatite, the main control on the magnitude of the corrections and uncertainties is grain geometry, with grain size being a secondary control on <span class="inline-formula"><i>F</i><sub>T</sub></span> uncertainty. Propagating these uncertainties into a real dataset (<span class="inline-formula"><i>N</i>=28</span> ZHe analyses) generates 1<span class="inline-formula"><i>σ</i></span> uncertainties of 12 %–21 % in eU and 3 %–7 % in the corrected ZHe date when both analytical and geometric uncertainties are included. Accounting for the geometric corrections and uncertainties is important for appropriately reporting, plotting, and interpreting ZHe data. For both zircon and apatite, the Geometric Correction Method is a practical and straightforward approach for calculating more accurate (U–Th) <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M25" display="inline" overflow="scroll" dspmath="mathml"><mo>/</mo></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="8pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="64e3733ac81609367f37ca130d7132b9"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gchron-6-199-2024-ie00006.svg" width="8pt" height="14pt" src="gchron-6-199-2024-ie00006.png"/></svg:svg></span></span> He data and for including geometric uncertainty in eU and date uncertainties.</p>