Geology topics

Jennifer Druhan

Publications and source records attributed to Jennifer Druhan.

7 recordsLinked to original sources

USGS2021

Development of soil radiocarbon profiles in a reactive transport framework

Today, there is a greater appreciation for the importance of the physical protection of carbon (C) through interactions with mineral surfaces, isolation from microbes, and the important role of transport in shaping soil properties and controlling moisture limitations on decomposition. As our paradigm for soil organic carbon (SOC) preservation changes, so too should our representation of the underlying processes in soil models. Reactive transport models (RTMs) provide a framework capable of assessing the interactive influence of soil chemistry and transport processes on the accumulation and turnover of SOC. In this study, we present new developments in the isotopically enabled RTM “CrunchTope,” which is capable of explicitly tracking the three isotopes of carbon ( 12 C, 13 C, and 14 C) and their fractionation between multiple coexisting and interacting solid, liquid and gas phases. This modeling framework opens the door to new applications of depth-resolved RTMs models in application to SOC and deeper subsurface carbon reservoirs. Here, we demonstrate SOC accumulation and radiocarbon aging for long-timescale models of soil development in CrunchTope. Our goal is to assess advantages and limitations of such an approach and to identify the type and complexity of reaction networks that are required to adequately apply this model to SOC dynamics. We assess the behavior of this model relative to a high-resolution dataset of SOC content, stable isotope composition, and radiocarbon ages as well as physical and hydrologic data measured from a chronosequence of soils located near Santa Cruz, California. Starting from a previously published model using a simplified reaction network with a single class of carbon, we sequentially incorporate multiple C reservoirs subject to both reactivity and transport pathways. Our results indicate that multiple SOC pools with different mean ages of C do not inherently emerge as a result of including reactions which are conventionally expected to provide a diversity of transit times, i.e., sorption and complexation of SOC on mineral surfaces. Instead, transit times emerge as a result of the timescales of the reactions represented in the reaction network. For mineral associated C, the RTM framework imposes dynamic equilibrium with the fluid phase dissolved organic C, such that no distinction in radiocarbon ages is achieved between these pools. Aged C can be produced by including a solid-phase C reservoir, with a rate-limited solubilization coefficient. Aging of SOC in this way is more akin to selective preservation than to mineral protection and, while such a mechanism may be at play in many soils, mineral protection is thought to be at least as important. As such, our results indicate that additional parameterization is required to reproduce the heterogeneity of carbon transit times that result from organo-mineral interactions. These efforts show the promise of a modeling approach where the varied transit time of soil C emerges from the dynamic physical and hydrologic properties of the model rather than from the a priori assignment of operationally defined pools.

Geochimica et Cosmochimica Acta↗

USGS2021

A reactive transport approach to modeling cave seepage water chemistry II: Elemental signatures

Karst systems are useful for examining spatial and temporal variability in Critical Zone processes because they provide a window into the subsurface where waters have interacted with vegetation, soils, regolith, and bedrock across a range of length and timescales. These hydrologic pathways frequently include the precipitation of speleothems, which provide long-term archives of climate and environmental change. Trace element ratios in speleothems (Mg/Ca, Sr/Ca, Ba/Ca) have the potential to provide information about past changes in rainfall and infiltration, but controls on them can be complex and their interpretation must be based on an understanding of the modern cave system. Here we integrate observations of surface conditions, bedrock, soil, and drip water chemistry of Blue Spring Cave in Tennessee, USA with the reactive transport model CrunchTope, which we have calibrated for karst systems to investigate the primary controls on trace element variations in cave seepage waters. We find that measured drip water Mg/Ca and Sr/Ca are captured within the model through variable amounts of limestone dissolution followed by precipitation of secondary calcite that happens within the cave rather than the host limestone. However, strong spatial controls on drip water Mg/Ca and Sr/Ca likely reflect seepage water interactions with variable amounts of diagenetic phases in the host rock. In contrast, Ba/Ca values are consistent across the cave and vary with effective rainfall, suggesting that this parameter may be the most consistent metric for limestone dissolution and prior calcite precipitation and can act as a proxy for rainfall and infiltration in this cave system. Our findings emphasize the importance of evaluating spatial heterogeneity in cave drip waters and outline a novel modeling approach for determining the dominant controls on drip water chemistry in support of the interpretations of paleoclimate records.

Geochimica et Cosmochimica Acta↗

USGS2021

A reactive transport approach to modeling cave seepage water chemistry I: Carbon isotope transformations

The majority of Critical Zone research has emphasized silicate lithologies, which are typified by relatively slow rates of reactivity and incongruent weathering. However, the relatively simpler weathering of carbonate-dominated lithology can result in secondary mineral deposits, such as speleothems, which provide a long-term archive for Critical Zone processes. In particular, carbon isotopic variability in speleothems has the potential to provide records of changes in vegetation, soil respiration, carbon stabilization in deep soils, and/or chemical weathering in the host rock. Despite this opportunity to reconstruct many Critical Zone processes, multiple influences can also make interpretion of these speleothem carbon isotope records challenging. The integration of observational data and simulations specific to karst systems offers an interpretive framework for these unique time-averaged records accumulated through the evolution of carbonate landscapes. Here, we present a forward and process-based reactive transport simulation based on a multi-year monitoring study of Blue Spring Cave in central Tennessee, USA. The simulations describe the fluid-driven weathering of limestone including explicit tracking of dissolved calcium, stable carbon, and radiocarbon isotope ratios based on reaction rates calibrated through laboratory batch reaction data. We find that calcium concentrations and radiocarbon isotope ratios are strongly influenced by the combination of fluid flow rate and soil CO 2 content, and require rapid gas phase communication between the overlying soil boundary condition and interior karst to sustain both elevated limestone weathering rates and relatively modern radiocarbon signatures. Stable carbon isotopes are largely dictated by temperature-dependent equilibrium fractionation among contemporaneous species. These simulations are extended to a wide range of parameter space to demonstrate the environmental factors that these isotope proxies record.

Geochimica et Cosmochimica Acta↗

USGS2020

Soil respiration response to rainfall modulated by plant phenology in a montane meadow, East River, Colorado, USA

Soil respiration is a primary component of the terrestrial carbon cycle. However, predicting the response of soil respiration to climate change remains a challenge due to the complex interactions between environmental drivers, especially plant phenology, temperature, and soil moisture. In this study, we use a 1‐D diffusion‐reaction model to calculate depth‐resolved CO 2 production rates from soil CO 2 concentrations and surface efflux observations in a subalpine meadow in the East River watershed, CO. Modeled rates are compared to in situ soil temperature and moisture conditions and MODIS satellite enhanced vegetation index (EVI) representing plant phenology across three hydrologically distinct growing seasons from 2016–2018. While soil respiration correlated with temperature on diel timescales ( p < 0.05), seasonal variability was dominated by soil moisture and plant phenology ( p < 0.05). We observed significant respiration increases in response to precipitation events; however, magnitude and duration were significantly higher in 2017 than 2016 despite similar wetting characteristics. Based on MODIS EVI, we suggest that the respiration response to rainfall is controlled by plant phenology, which in turn reflects the capacity of plants to respond to precipitation via increased photosynthesis and autotrophic respiration, behavior that is not captured in typical soil respiration pulse models. Projected changes in montane climate such as earlier snowmelt and prolonged fore‐summer drought may decrease soil respiration fluxes by decreasing the overlap between peak productivity and the summer monsoon. Finally, we observed significant late season CO 2 fluxes from the deep subsoil (>165 cm) that support growing evidence for the importance of subsoil processes in driving integrated respiration fluxes.

Colorado↗

USGS2019

Modeling transient soil moisture limitations on microbial carbon respiration: A cost-performance comparison

Soil microorganisms are known to survive periods of aridity and to recover rapidly after wetting events, with the ability to transition between a dormant state in dry conditions and an active state in wet conditions. Though this dynamic behavior has been previously incorporated into soil carbon respiration modeling frameworks, a direct comparison between this active-dormant transition mechanism and a more simplified first-order model has yet to be made. Here, we demonstrate the necessary extent of model complexity needed to reproduce transient carbon respiration rates obtained from a set of soil incubation experiments implemented over a range of soil depths and time intervals. Two approaches are tested, one uses simplified first-order kinetics whereas the other employs a transition between active and dormant biomass. The performance of each model is evaluated using an Akaike Information Criterion (AIC) based on the accuracy with which they reproduce an experimental dataset consisting of two sets of time series soil incubations collected across a range of time and depth resolutions. Based on the AIC evaluation and model-data comparison, we conclude that a dormancy-enabled model featuring two distinct microbial strategists performs best for the majority of the soil profile (above 108 cm) for both high- and low- depth resolution and sampling frequency, despite the added parameters required. In contrast, the first-order model achieves better AIC scores when simulating our deepest soils (112-165 cm), where moisture fluctuations are expected to be less prevalent. These results guide how and where we choose to apply more cost intensive models.

Biogeosciences↗

USGS2018

Beyond clay: Towards an improved set of variables for predicting soil organic matter content

Improved quantification of the factors controlling soil organic matter (SOM) stabilization at continental to global scales is needed to inform projections of the largest actively cycling terrestrial carbon pool on Earth, and its response to environmental change. Biogeochemical models rely almost exclusively on clay content to modify rates of SOM turnover and fluxes of climate-active CO 2 to the atmosphere. Emerging conceptual understanding, however, suggests other soil physicochemical properties may predict SOM stabilization better than clay content. We addressed this discrepancy by synthesizing data from over 5,500 soil profiles spanning continental scale environmental gradients. Here, we demonstrate that other physicochemical parameters are much stronger predictors of SOM content, with clay content having relatively little explanatory power. We show that exchangeable calcium strongly predicted SOM content in water-limited, alkaline soils, whereas with increasing moisture availability and acidity, iron- and aluminum-oxyhydroxides emerged as better predictors, demonstrating that the relative importance of SOM stabilization mechanisms scales with climate and acidity. These results highlight the urgent need to modify biogeochemical models to better reflect the role of soil physicochemical properties in SOM cycling.

Biogeochemistry↗

USGS2017

Expanding the role of reactive transport models in critical zone processes

Models test our understanding of processes and can reach beyond the spatial and temporal scales of measurements. Multi-component Reactive Transport Models (RTMs), initially developed more than three decades ago, have been used extensively to explore the interactions of geothermal, hydrologic, geochemical, and geobiological processes in subsurface systems. Driven by extensive data sets now available from intensive measurement efforts, there is a pressing need to couple RTMs with other community models to explore non-linear interactions among the atmosphere, hydrosphere, biosphere, and geosphere. Here we briefly review the history of RTM development, summarize the current state of RTM approaches, and identify new research directions, opportunities, and infrastructure needs to broaden the use of RTMs. In particular, we envision the expanded use of RTMs in advancing process understanding in the Critical Zone, the veneer of the Earth that extends from the top of vegetation to the bottom of groundwater. We argue that, although parsimonious models are essential at larger scales, process-based models offer tools to explore the highly nonlinear coupling that characterizes natural systems. We present seven testable hypotheses that emphasize the unique capabilities of process-based RTMs for (1) elucidating chemical weathering and its physical and biogeochemical drivers; (2) understanding the interactions among roots, micro-organisms, carbon, water, and minerals in the rhizosphere; (3) assessing the effects of heterogeneity across spatial and temporal scales; and (4) integrating the vast quantity of novel data, including “omics” data (genomics, transcriptomics, proteomics, metabolomics), elemental concentration and speciation data, and isotope data into our understanding of complex earth surface systems. With strong support from data-driven sciences, we are now in an exciting era where integration of RTM framework into other community models will facilitate process understanding across disciplines and across scales.

Earth-Science Reviews↗