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Abstract Terminal saline lakes are environmentally sensitive systems that are sentinels for anthropogenic change. Understanding recent changes in these systems is complicated, however, by a lack of data documenting their natural variability and past response to human disturbance. Isotopic data from shallow sediments of Great Salt Lake (GSL), UT, demonstrate a two‐phase shift in lake water and carbon budgets during the past 200 years. I suggest that these changes are associated with regional colonial settlement, which altered carbon budgets beginning in the mid‐19th century, and the hydrographic effects of a railroad causeway built in 1959. The post‐colonial isotope changes are unprecedented in the preceding ∼2,000 years and unusual in the context of an 8,000‐year record of natural variability. This work illustrates the utility of proxy data in identifying past human impacts on saline lake systems and documenting background states that can serve as targets for management. 

Billions of people rely upon groundwater for drinking water and agriculture, yet predicting how climate change may affect aquifer storage remains challenging. To gain insight beyond the short historical record, we reconstruct changes in groundwater levels in western North America during the last glacial termination (LGT, ~20 to 11 thousand years ago) using noble gas isotopes. Our reconstructions indicate remarkable stability of water table depth in a Pacific Northwest aquifer throughout the LGT despite increasing precipitation, closely matching independent Earth system model (ESM) simulations. In the American Southwest, ESM simulations and noble gas isotopes both suggest a pronounced LGT decline in water table depth in in response to decreasing precipitation, indicating distinct regional groundwater responses to climate. Despite the hydrologic simplicity of ESMs, their agreement with proxy reconstructions of past water table depth suggests that these models hold value in understanding groundwater dynamics and projecting large-scale aquifer responses to climate forcing. 

The late Paleocene and early Eocene (LPEE) are characterized by long-term (million years, Myr) global warming and by transient, abrupt (kiloyears, kyr) warming events, termed hyperthermals. Although both have been attributed to greenhouse (CO₂) forcing, the longer-term trend in climate was likely influenced by additional forcing factors (i.e., tectonics) and the extent to which warming was driven by atmospheric CO₂remains unclear. Here, we use a suite of new and existing observations from planktic foraminifera collected at Pacific Ocean Drilling Program Sites 1209 and 1210 and inversion of a multiproxy Bayesian hierarchical model to quantify sea surface temperature (SST) and atmospheric CO₂over a 6-Myr interval. Our reconstructions span the initiation of long-term LPEE warming (~58 Ma), and the two largest Paleogene hyperthermals, the Paleocene–Eocene Thermal Maximum (PETM, ~56 Ma) and Eocene Thermal Maximum 2 (ETM-2, ~54 Ma). Our results show strong coupling between CO₂and temperature over the long- (LPEE) and short-term (PETM and ETM-2) but differing Pacific climate sensitivities over the two timescales. Combined CO₂and carbon isotope trends imply the carbon source driving CO₂increase was likely methanogenic, organic, or mixed for the PETM and organic for ETM-2, whereas a source with higher δ¹³C values (e.g., volcanic degassing) is associated with the long-term LPEE. Reconstructed emissions for the PETM (5,800 Gt C) and ETM-2 (3,800 Gt C) are comparable in mass to future emission scenarios, reinforcing the value of these events as analogs of anthropogenic change. 

Abstract Stable isotope ratios of H (δ²H), O (δ¹⁸O), and C (δ¹³C) are linked to key biogeochemical processes of the water and carbon cycles; however, the degree to which isotope-associated processes are reflected in macroscale ecosystem flux observations remains unquantified. Here through formal information assessment, new measurements ofδ¹³C of net ecosystem exchange (NEE) as well asδ²H andδ¹⁸O of latent heat (LH) fluxes across the United States National Ecological Observation Network (NEON) are used to determine conditions under which isotope measurements are informative of environmental exchanges. We find all three isotopic datasets individually contain comparable amounts of information aboutNEEandLHfluxes as wind speed observations. Such information from isotope measurements, however, is largely unique. Generally,δ¹³C provides more information aboutLHas aridity increases or mean annual precipitation decreases.δ²H provides more information aboutLHas temperatures or mean annual precipitation decreases, and also provides more information aboutNEEas temperatures decrease. Overall, we show that the stable isotope datasets collected by NEON contribute non-trivial amounts of new information about bulk environmental fluxes useful for interpreting biogeochemical and ecohydrological processes at landscape scales. However, the utility of this new information varies with environmental conditions at continental scales. This study provides an approach for quantifying the value adding non-traditional sensing approaches to environmental monitoring sites and the patterns identified here are expected to aid in modeling and data interpretation efforts focused on constraining carbon and water cycles’ mechanisms. 

Unidentified human remains have historically been investigated nationally by law enforcement authorities. However, this approach is outdated in a globalized world with rapid transportation means, where humans easily move long distances across borders. Cross-border cooperation in solving cold-cases is rare due to political, administrative or technical challenges. It is fundamental to develop new tools to provide rapid and cost-effective leads for international cooperation. In this work, we demonstrate that isotopic measurements are effective screening tools to help identify cold-cases with potential international ramifications. We first complete existing databases of hydrogen and sulfur isotopes in human hair from residents across North America by compiling or analyzing hair from Canada, the United States (US) and Mexico. Using these databases, we develop maps predicting isotope variations in human hair across North America. We demonstrate that both δ 2 H and δ 34 S values of human hair are highly predictable and display strong spatial patterns. Multi-isotope analysis combined with dual δ 2 H and δ 34 S geographic probability maps provide evidence for international travel in two case studies. In the first, we demonstrate that multi-isotope analysis in bulk hair of deceased border crossers found in the US, close to the Mexico-US border, help trace their last place of residence or travel back to specific regions of Mexico. These findings were validated by the subsequent identification of these individuals through the Pima County Office of the Medical Examiner in Tucson, Arizona. In the second case study, we demonstrate that sequential multi-isotope analysis along the hair strands of an unidentified individual found in Canada provides detailed insights into the international mobility of this individual during the last year of life. In both cases, isotope data provide strong leads towards international travel. 

Abstract. Plant wax n-alkane chain length distribution and isotopeshave been studied in modern ecosystems as proxies to reconstruct vegetationand climate of the past. However, most paleo-proxies focus on eitherconcentrations or isotopes, whereas both carry complementary information onthe mixing sources. We propose a multi-source mixing model in a Bayesianframework that evaluates both chain length distributions and isotopessimultaneously. The model consists of priors that include user-definedsource groups and their associated parametric distributions of n-alkaneconcentration and δ13C. The mixing process involves newlydefined mixing fractions such as fractional leaf mass contribution (FLMC)that can be used in vegetation reconstruction. Markov Chain Monte Carlo isused to generate samples from the posterior distribution of these parametersconditioned on both data types. We present three case studies from distinctsettings. The first involves n-C27, n-C29, and n-C31 alkanes in lake surface sediments of Lake Qinghai, China. The model provides more specific interpretations on the n-alkane input from aquatic sources than the conventional Paq proxy. The second involves n-C29, n-C31, and n-C33 alkanes in lake surface sediments in Cameroon, western Africa. Themodel produces mixing fractions of forest C3, savanna C3, andC4 plants, offering additional information on the dominant biomescompared to the traditional two-end-member mixing regime. The third couplesthe vegetation source model to a hydrogen isotope model component, usingbiome-specific apparent fractionation factors (εa) toestimate the δ2H of mean annual precipitation. By leveraging chain length distribution, δ13C, and δ2H data offour n-alkane chains, the model produces estimated precipitation δ2H with relatively small uncertainty limits. The new framework shows promise for interpretation of paleo-data but could be further improved by including processes associated with n-alkane turnover in plants, transport,and integration into sedimentary archives. Future studies on modern plantsand catchment systems will be critical to develop calibration datasets thatadvance the strength and utility of the framework. 

Paleo-CO2 reconstructions are integral to understanding the evolution of Earth system processes and their interactions given that atmospheric-CO2 concentrations are intrinsically linked to planetary function. In this talk, we use several case studies, spanning the 3 Phanerozoic Eras, to illustrate the potential of paleo-CO2 records to constrain the magnitude and state-dependency of equilibrium climate sensitivity, to advance our understanding of global biogeochemical cycles, to test the sensitivity of Earth System modeled atmospheric and oceanic circulation to PCO2 over a range of climate states, and to interrogate ecosystem—CO2—climate linkages and physiological responses to CO2. Further advances in these areas, however, are dependent on how well we ‘know’ paleo-CO2 estimates. CO2 estimates exist for much of the past half-billion years, but the degree to which the accuracy and precision of these estimates are constrained is quite variable, leading to substantial uncertainty and inconsistency in paleo-CO2 estimates. Potential sources of this uncertainty and inconsistency include an incomplete understanding of how environmental and ecophysiological conditions and processes imprint the CO2 proxy signals we measure, of the sensitivity of the CO2 estimates to this uncertainty, and differences in approaches to assigning uncertainties to CO2 estimates, among other factors. Application of newly established screening criteria, defined as part of an effort to improve our understanding of how atmospheric CO2 has varied through the Cenozoic, illustrates how the majority of pre-Cenozoic estimates are unreliable in their current form. To address these issues and to advance paleo-CO2 reconstruction, we introduce CO2PIP, a new community-scale project that takes a two-step approach to building the next generation Phanerozoic-CO2 record. Collective efforts are modernizing existing terrestrial-based CO2 estimates through additional analyses, measurements and proxy system modeling to constrain critical parameters used to estimate paleo-CO2. A set of forward proxy system models being developed in collaboration with the CO2 community, will provide a quantified representation of proxy sensitivities to environmental and ecophysiological conditions and processes that govern the CO2 signals. Ultimately, statistical inversion analysis of the simulated and modernized proxy datasets will be used to revise individual CO2 records and to build a new integrated model-data-constrained CO2 record for the Phanerozoic. 

Abstract Sampling intervals of precipitation geochemistry measurements are often coarser than those required by fine-scale hydrometeorological models. This study presents a statistical method to temporally downscale geochemical tracer signals in precipitation so that they can be used in high-resolution, tracer-enabled applications. In this method, we separated the deterministic component of the time series and the remaining daily stochastic component, which was approximated by a conditional multivariate Gaussian distribution. Specifically, statistics of the stochastic component could be explained from coarser data using a newly identified power-law decay function, which relates data aggregation intervals to changes in tracer concentration variance and correlations with precipitation amounts. These statistics were used within a copula framework to generate synthetic tracer values from the deterministic and stochastic time series components based on daily precipitation amounts. The method was evaluated at 27 sites located worldwide using daily precipitation isotope ratios, which were aggregated in time to provide low resolution testing datasets with known daily values. At each site, the downscaling method was applied on weekly, biweekly and monthly aggregated series to yield an ensemble of daily tracer realizations. Daily tracer concentrations downscaled from a biweekly series had average (+/- standard deviation) absolute errors of 1.69‰ (1.61‰) for δ 2 H and 0.23‰ (0.24‰) for δ 18 O relative to observations. The results suggest coarsely sampled precipitation tracers can be accurately downscaled to daily values. This method may be extended to other geochemical tracers in order to generate downscaled datasets needed to drive complex, fine-scale models of hydrometeorological processes. 

Abstract The National Ecological Observatory Network (NEON) provides open-access measurements of stable isotope ratios in atmospheric water vapor (δ²H, δ¹⁸O) and carbon dioxide (δ¹³C) at different tower heights, as well as aggregated biweekly precipitation samples (δ²H, δ¹⁸O) across the United States. These measurements were used to create the NEON Daily Isotopic Composition of Environmental Exchanges (NEON-DICEE) dataset estimating precipitation (P; δ²H, δ¹⁸O), evapotranspiration (ET; δ²H, δ¹⁸O), and net ecosystem exchange (NEE; δ¹³C) isotope ratios. Statistically downscaled precipitation datasets were generated to be consistent with the estimated covariance between isotope ratios and precipitation amounts at daily time scales. Isotope ratios in ET and NEE fluxes were estimated using a mixing-model approach with calibrated NEON tower measurements. NEON-DICEE is publicly available on HydroShare and can be reproduced or modified to fit user specific applications or include additional NEON data records as they become available. The NEON-DICEE dataset can facilitate understanding of terrestrial ecosystem processes through their incorporation into environmental investigations that require daily δ²H, δ¹⁸O, and δ¹³C flux data.