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1. Sea-level trends across The Bahamas constrain peak last interglacial ice melt

   https://doi.org/10.1073/pnas.2026839118  

   Dyer, Blake ; Austermann, Jacqueline ; D’Andrea, William J. ; Creel, Roger C. ; Sandstrom, Michael R. ; Cashman, Miranda ; Rovere, Alessio ; Raymo, Maureen E. ( August 2021 , Proceedings of the National Academy of Sciences)

   During the last interglacial (LIG) period, global mean sea level (GMSL) was higher than at present, likely driven by greater high-latitude insolation. Past sea-level estimates require elevation measurements and age determination of marine sediments that formed at or near sea level, and those elevations must be corrected for glacial isostatic adjustment (GIA). However, this GIA correction is subject to uncertainties in the GIA model inputs, namely, Earth’s rheology and past ice history, which reduces precision and accuracy in estimates of past GMSL. To better constrain the GIA process, we compare our data and existing LIG sea-level data across the Bahamian archipelago with a suite of 576 GIA model predictions. We calculated weights for each GIA model based on how well the model fits spatial trends in the regional sea-level data and then used the weighted GIA corrections to revise estimates of GMSL during the LIG. During the LIG, we find a 95% probability that global sea level peaked at least 1.2 m higher than today, and it is very unlikely (5% probability) to have exceeded 5.3 m. Estimates increase by up to 30% (decrease by up to 20%) for portions of melt that originate from the Greenland ice sheet (Westmore »Antarctic ice sheet). Altogether, this work suggests that LIG GMSL may be lower than previously assumed.

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2. Florida mangrove saltmarsh reference surface soils

   https://doi.org/10.6073/pasta/0e08cbe07c84488cb7b9dd16669946d0  

   Lewis, David Bruce ( January 2021 )

   Abstract

   Site description. This data package consists of data obtained from sampling surface soil (the 0-7.6 cm depth profile) in black mangrove (Avicennia germinans) dominated forest and black needlerush (Juncus roemerianus) saltmarsh along the Gulf of Mexico coastline in peninsular west-central Florida, USA. This location has a subtropical climate with mean daily temperatures ranging from 15.4 °C in January to 27.8 °C in August, and annual precipitation of 1336 mm. Precipitation falls as rain primarily between June and September. Tides are semi-diurnal, with 0.57 m median amplitudes during the year preceding sampling (U.S. NOAA National Ocean Service, Clearwater Beach, Florida, station 8726724). Sea-level rise is 4.0 ± 0.6 mm per year (1973-2020 trend, mean ± 95 % confidence interval, NOAA NOS Clearwater Beach station). The A. germinans mangrove zone is either adjacent to water or fringed on the seaward side by a narrow band of red mangrove (Rhizophora mangle). A near-monoculture of J. roemerianus is often adjacent to and immediately landward of the A. germinans zone. The transition from the mangrove to the J. roemerianus zone is variable in our study area. An abrupt edge between closed-canopy mangrove and J. roemerianus monoculture may extend for up to several hundred meters in some locations, while other stretches of ecotone present a gradual transition where smaller, widely spaced trees are interspersed into the herbaceous marsh. Juncus roemerianus then extends landward to a high marsh patchwork of succulent halophytes (including Salicornia bigellovi, Sesuvium sp., and Batis maritima), scattered dwarf mangrove, and salt pans, followed in turn by upland vegetation that includes Pinus sp. and Serenoa repens. Field design and sample collection. We established three study sites spaced at approximately 5 km intervals along the western coastline of the central Florida peninsula. The sites consisted of the Salt Springs (28.3298°, -82.7274°), Energy Marine Center (28.2903°, -82.7278°), and Green Key (28.2530°, -82.7496°) sites on the Gulf of Mexico coastline in Pasco County, Florida, USA. At each site, we established three plot pairs, each consisting of one saltmarsh plot and one mangrove plot. Plots were 50 m^2 in size. Plots pairs within a site were separated by 230-1070 m, and the mangrove and saltmarsh plots composing a pair were 70-170 m apart. All plot pairs consisted of directly adjacent patches of mangrove forest and J. roemerianus saltmarsh, with the mangrove forests exhibiting a closed canopy and a tree architecture (height 4-6 m, crown width 1.5-3 m). Mangrove plots were located at approximately the midpoint between the seaward edge (water-mangrove interface) and landward edge (mangrove-marsh interface) of the mangrove zone. Saltmarsh plots were located 20-25 m away from any mangrove trees and into the J. roemerianus zone (i.e., landward from the mangrove-marsh interface). Plot pairs were coarsely similar in geomorphic setting, as all were located on the Gulf of Mexico coastline, rather than within major sheltering formations like Tampa Bay, and all plot pairs fit the tide-dominated domain of the Woodroffe classification (Woodroffe, 2002, "Coasts: Form, Process and Evolution", Cambridge University Press), given their conspicuous semi-diurnal tides. There was nevertheless some geomorphic variation, as some plot pairs were directly open to the Gulf of Mexico while others sat behind keys and spits or along small tidal creeks. Our use of a plot-pair approach is intended to control for this geomorphic variation. Plot center elevations (cm above mean sea level, NAVD 88) were estimated by overlaying the plot locations determined with a global positioning system (Garmin GPS 60, Olathe, KS, USA) on a LiDAR-derived bare-earth digital elevation model (Dewberry, Inc., 2019). The digital elevation model had a vertical accuracy of ± 10 cm (95 % CI) and a horizontal accuracy of ± 116 cm (95 % CI). Soil samples were collected via coring at low tide in June 2011. From each plot, we collected a composite soil sample consisting of three discrete 5.1 cm diameter soil cores taken at equidistant points to 7.6 cm depth. Cores were taken by tapping a sleeve into the soil until its top was flush with the soil surface, sliding a hand under the core, and lifting it up. Cores were then capped and transferred on ice to our laboratory at the University of South Florida (Tampa, Florida, USA), where they were combined in plastic zipper bags, and homogenized by hand into plot-level composite samples on the day they were collected. A damp soil subsample was immediately taken from each composite sample to initiate 1 y incubations for determination of active C and N (see below). The remainder of each composite sample was then placed in a drying oven (60 °C) for 1 week with frequent mixing of the soil to prevent aggregation and liberate water. Organic wetland soils are sometimes dried at 70 °C, however high drying temperatures can volatilize non-water liquids and oxidize and decompose organic matter, so 50 °C is also a common drying temperature for organic soils (Gardner 1986, "Methods of Soil Analysis: Part 1", Soil Science Society of America); we accordingly chose 60 °C as a compromise between sufficient water removal and avoidance of non-water mass loss. Bulk density was determined as soil dry mass per core volume (adding back the dry mass equivalent of the damp subsample removed prior to drying). Dried subsamples were obtained for determination of soil organic matter (SOM), mineral texture composition, and extractable and total carbon (C) and nitrogen (N) within the following week. Sample analyses. A dried subsample was apportioned from each composite sample to determine SOM as mass loss on ignition at 550 °C for 4 h. After organic matter was removed from soil via ignition, mineral particle size composition was determined using a combination of wet sieving and density separation in 49 mM (3 %) sodium hexametaphosphate ((NaPO_3)_6) following procedures in Kettler et al. (2001, Soil Science Society of America Journal 65, 849-852). The percentage of dry soil mass composed of silt and clay particles (hereafter, fines) was calculated as the mass lost from dispersed mineral soil after sieving (0.053 mm mesh sieve). Fines could have been slightly underestimated if any clay particles were burned off during the preceding ignition of soil. An additional subsample was taken from each composite sample to determine extractable N and organic C concentrations via 0.5 M potassium sulfate (K_2SO_4) extractions. We combined soil and extractant (ratio of 1 g dry soil:5 mL extractant) in plastic bottles, reciprocally shook the slurry for 1 h at 120 rpm, and then gravity filtered it through Fisher G6 (1.6 μm pore size) glass fiber filters, followed by colorimetric detection of nitrite (NO_2^-) + nitrate (NO_3^-) and ammonium (NH_4^+) in the filtrate (Hood Nowotny et al., 2010,Soil Science Society of America Journal 74, 1018-1027) using a microplate spectrophotometer (Biotek Epoch, Winooski, VT, USA). Filtrate was also analyzed for dissolved organic C (referred to hereafter as extractable organic C) and total dissolved N via combustion and oxidation followed by detection of the evolved CO_2 and N oxide gases on a Formacs HT TOC/TN analyzer (Skalar, Breda, The Netherlands). Extractable organic N was then computed as total dissolved N in filtrate minus extractable mineral N (itself the sum of extractable NH_4-N and NO_2-N + NO_3-N). We determined soil total C and N from dried, milled subsamples subjected to elemental analysis (ECS 4010, Costech, Inc., Valencia, CA, USA) at the University of South Florida Stable Isotope Laboratory. Median concentration of inorganic C in unvegetated surface soil at our sites is 0.5 % of soil mass (Anderson, 2019, Univ. of South Florida M.S. thesis via methods in Wang et al., 2011, Environmental Monitoring and Assessment 174, 241-257). Inorganic C concentrations are likely even lower in our samples from under vegetation, where organic matter would dilute the contribution of inorganic C to soil mass. Nevertheless, the presence of a small inorganic C pool in our soils may be counted in the total C values we report. Extractable organic C is necessarily of organic C origin given the method (sparging with HCl) used in detection. Active C and N represent the fractions of organic C and N that are mineralizable by soil microorganisms under aerobic conditions in long-term soil incubations. To quantify active C and N, 60 g of field-moist soil were apportioned from each composite sample, placed in a filtration apparatus, and incubated in the dark at 25 °C and field capacity moisture for 365 d (as in Lewis et al., 2014, Ecosphere 5, art59). Moisture levels were maintained by frequently weighing incubated soil and wetting them up to target mass. Daily CO_2 flux was quantified on 29 occasions at 0.5-3 week intervals during the incubation period (with shorter intervals earlier in the incubation), and these per day flux rates were integrated over the 365 d period to compute an estimate of active C. Observations of per day flux were made by sealing samples overnight in airtight chambers fitted with septa and quantifying headspace CO_2 accumulation by injecting headspace samples (obtained through the septa via needle and syringe) into an infrared gas analyzer (PP Systems EGM 4, Amesbury, MA, USA). To estimate active N, each incubated sample was leached with a C and N free, 35 psu solution containing micronutrients (Nadelhoffer, 1990, Soil Science Society of America Journal 54, 411-415) on 19 occasions at increasing 1-6 week intervals during the 365 d incubation, and then extracted in 0.5 M K_2SO_4 at the end of the incubation in order to remove any residual mineral N. Active N was then quantified as the total mass of mineral N leached and extracted. Mineral N in leached and extracted solutions was detected as NH_4-N and NO_2-N + NO_3-N via colorimetry as above. This incubation technique precludes new C and N inputs and persistently leaches mineral N, forcing microorganisms to meet demand by mineralizing existing pools, and thereby directly assays the potential activity of soil organic C and N pools present at the time of soil sampling. Because this analysis commences with disrupting soil physical structure, it is biased toward higher estimates of active fractions. Calculations. Non-mobile C and N fractions were computed as total C and N concentrations minus the extractable and active fractions of each element. This data package reports surface-soil constituents (moisture, fines, SOM, and C and N pools and fractions) in both gravimetric units (mass constituent / mass soil) and areal units (mass constituent / soil surface area integrated through 7.6 cm soil depth, the depth of sampling). Areal concentrations were computed as X × D × 7.6, where X is the gravimetric concentration of a soil constituent, D is soil bulk density (g dry soil / cm^3), and 7.6 is the sampling depth in cm.
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3. The robustness of geodetically derived 1-D Antarctic viscosity models in the presence of complex 3-D viscoelastic Earth structure

   https://doi.org/10.1093/gji/ggac129  

   Powell, E. ; Latychev, K. ; Gomez, N. ; Mitrovica, J. X. ( March 2022 , Geophysical Journal International)

   Earth structure beneath the Antarctic exerts an important control on the evolution of the ice sheet. A range of geological and geophysical data sets indicate that this structure is complex, with the western sector characterized by a lithosphere of thickness ∼50–100 km and viscosities within the upper mantle that vary by 2–3 orders of magnitude. Recent analyses of uplift rates estimated using Global Navigation Satellite System (GNSS) observations have inferred 1-D viscosity profiles below West Antarctica discretized into a small set of layers within the upper mantle using forward modelling of glacial isostatic adjustment (GIA). It remains unclear, however, what these 1-D viscosity models represent in an area with complex 3-D mantle structure, and over what geographic length-scale they are applicable. Here, we explore this issue by repeating the same modelling procedure but applied to synthetic uplift rates computed using a realistic model of 3-D viscoelastic Earth structure inferred from seismic tomographic imaging of the region, a finite volume treatment of GIA that captures this complexity, and a loading history of Antarctic ice mass changes inferred over the period 1992–2017. We find differences of up to an order of magnitude between the best-fitting 1-D inferences and regionally averaged depth profilesmore »through the 3-D viscosity field used to generate the synthetics. Additional calculations suggest that this level of disagreement is not systematically improved if one increases the number of observation sites adopted in the analysis. Moreover, the 1-D models inferred from such a procedure are non-unique, that is a broad range of viscosity profiles fit the synthetic uplift rates equally well as a consequence, in part, of correlations between the viscosity values within each layer. While the uplift rate at each GNSS site is sensitive to a unique subspace of the complex, 3-D viscosity field, additional analyses based on rates from subsets of proximal sites showed no consistent improvement in the level of bias in the 1-D inference. We also conclude that the broad, regional-scale uplift field generated with the 3-D model is poorly represented by a prediction based on the best-fitting 1-D Earth model. Future work analysing GNSS data should be extended to include horizontal rates and move towards inversions for 3-D structure that reflect the intrinsic 3-D resolving power of the data.

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4. Resolving glacial isostatic adjustment (GIA) in response to modern and future ice loss at marine grounding lines in West Antarctica

   https://doi.org/10.5194/tc-16-2203-2022  

   Wan, Jeannette Xiu ; Gomez, Natalya ; Latychev, Konstantin ; Han, Holly Kyeore ( January 2022 , The Cryosphere)

   Abstract. Accurate glacial isostatic adjustment (GIA) modelling in the cryosphere is required for interpreting satellite, geophysical and geological recordsand for assessing the feedbacks of Earth deformation and sea-level change on marine ice-sheet grounding lines. GIA modelling in areas of active ice lossin West Antarctica is particularly challenging because the ice is underlain by laterally varying mantle viscosities that are up to several orders ofmagnitude lower than the global average, leading to a faster and more localised response of the solid Earth to ongoing and future ice-sheet retreatand necessitating GIA models that incorporate 3-D viscoelastic Earth structure. Improvements to GIA models allow for computation of the viscoelasticresponse of the Earth to surface ice loading at sub-kilometre resolution, and ice-sheet models and observational products now provide the inputs toGIA models at comparably unprecedented detail. However, the resolution required to accurately capture GIA in models remains poorly understood, andhigh-resolution calculations come at heavy computational expense. We adopt a 3-D GIA model with a range of Earth structure models based on recentseismic tomography and geodetic data to perform a comprehensive analysis of the influence of grid resolution on predictions of GIA in the AmundsenSea Embayment (ASE) in West Antarctica. Through idealised sensitivity testing downmore »to sub-kilometre resolution with spatially isolated ice loadingchanges, we find that a grid resolution of ∼ 13 of the radius of the load or higher is required to accurately capture the elasticresponse of the Earth. However, when we consider more realistic, spatially coherent ice loss scenarios based on modern observational records andfuture ice-sheet model projections and adopt a viscoelastic Earth, we find that predicted deformation and sea-level change along the grounding lineconverge to within 5 % with grid resolutions of 7.5 km or higher, and to within 2 % for grid resolutions of 3.75 km andhigher, even when the input ice model is on a 1 km grid. Furthermore, we show that low mantle viscosities beneath the ASE lead to viscousdeformation that contributes to the instrumental record on decadal timescales and equals or dominates over elastic effects by the end of the 21stcentury. Our findings suggest that for the range of resolutions of 1.9–15 km that we considered, the error due to adopting a coarser gridin this region is negligible compared to the effect of neglecting viscous effects and the uncertainty in the adopted mantle viscosity structure.« less
5. The influence of glacial isostatic adjustment on continental shelf stratigraphic correlation

   https://doi.org/10.1130/G49841.1  

   King, Meghan E. ; Creveling, Jessica R. ( May 2022 , Geology)

   Glacial isostatic adjustment (GIA) imparts geographic variability in the amplitude and timing of local sea-level (LSL) change arising from glacial-interglacial oscillations relative to a global mean signal (eustasy). We modeled how GIA manifests in the stratigraphic record across four shelf-perpendicular transects moving progressively more distal to the Quaternary North American ice complex, subject to varying amounts of GIA during glacial-interglacial cycles. Along each transect, we obtained LSL histories for nine sites between 1 m and 250 m water depth from the output of a gravitationally self-consistent GIA model run from marine oxygen isotope stage (MIS) 11 to the present. We paired each site’s unique LSL history with 50 identical annual sedimentation models to create a library of 400-k.y.-duration synthetic stratigraphic columns (each assuming no tectonics). Comparison of the suite of synthetic stratigraphic columns between transects for a given bathymetric depth reveals latitudinal differences in the stratigraphically determined number, magnitude, and age of glacial-interglacial cycles, as inferred from stratigraphic sequence count, apparent water-depth change, and age of preserved deglacial transgression. We conclude that, for many field locales, extraction of primary information about the number, scale, and duration of pre-Cenozoic glacial-interglacial cycles from continental shelf stratigraphic records near ice sheets demands amore »deconvolution of the GIA signal.« less