2020-2024 Theses and dissertations

Abstract

Arctic sea ice is currently undergoing a period of rapid decline and concurrent high variability. Future projection uncertainty is dominated by internal variability in the short and medium term. In this thesis we use a large number of climate model simulations, which together can explain driversand characteristics of variability, whilst diagnosing model limitations when compared with observations. We find that large ensembles from the Coupled Model Intercomparison Project - Phase5 (CMIP5) generally simulate interannual variability within observational uncertainty. However, model realism is only achieved due to large observational uncertainties and spatially heterogeneousmodel biases. To reduce uncertainty of low-frequency variability, we find that climate modes ofvariability can be used skillfully to explain regional Arctic sea ice variability. The primary drivers of a decadal decline in Arctic sea ice are above trend global temperatures, a negative Interdecadal Pacific Oscillation (IPO) and a positive Atlantic Meridional Oscillation (AMO), which currently are aligned as such. The IPO across CMIP6 climate models is highly important for up to 15 years, but with large variations in magnitude and sign between models and realizations. With further investigation, we find the decadal predictive skill of the IPO is often dependent on the modulation by the slowly-changing Pacific-Arctic (PARC) atmospheric teleconnection. Considering the current negative phases of the IPO and PARC, an increased likelihood of an accelerated transition to an ice-free Arctic is expected by most climate models.

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Abstract

Water isotopes serve as a useful proxy for past climate conditions at ice core sites and their respective moisture sources. Here we present the application of a novel numerical model to reconstruct absolute surface temperature, condensation temperature, and source-region evaporation temperature for all publicly accessible Greenland ice core records that yield the necessary data. We apply this analysis to the last glacial period, which was punctuated by a series of rapid climate oscillations—records of which are particularly well-defined in Greenland ice cores. Reconstructed moisture source temperatures are deconvolved from paleo- sea surface temperature variability in the Northern Hemisphere Atlantic to derive changes in moisture source latitude during this time. We attribute shifts in moisture source latitude principally to atmospheric variability. We pair this analysis with investigation into other potential forcings on moisture source latitude and find that changes in atmospheric circulation persists as the dominant contributor of variability. Our reconstructions show dynamic shifts in moisture source latitude (up to 20 degrees within a given abrupt climate event), indicative of a significant atmospheric reorganization during the last glaciation. These results provide a framework from which to assess the role of atmospheric circulation during the abrupt climate shifts that marked the last ice age.

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Abstract

Over three chapters of my dissertation, I aimed to address drivers of riparian ecosystem change at different scales, ranging from leaf-level plant ecophysiology to long-term plant community dynamics. In my first chapter, I assessed willow water limitation in Rocky Mountain National Park in the context of degraded sites with high ungulate browsing that have also functionally lost beaver-mediated hydrology. I found that, in these degraded contexts, willows were not water-limited compared to more intact reference sites but rather showed responses in association with seasonal drydown. In my second chapter, I assessed decadal turnover trends in riparian wetlands, wet meadows, and fens in Rocky Mountain National Park. I found that riparian ecosystems experienced the greatest compositional change while wet meadows and fen functional group components were relatively stable through time. Further, water balance metrics were the most important determinants of plant community composition and there were only a couple of instances indicating where native functional groups might exclude corresponding nonnative functional groups through limiting similarity. In my third chapter, I tested the effectiveness of using a functional trait-based approach to see if functional diversity conferred stability in productivity and reduced invasion by increased niche occupation and complementarity in a riparian restoration project in the Front Range of Colorado. I found some support for a functional diversity oriented approach contributing to the stability of productivity, whereas invasion trends were largely driven by a soil moisture gradient and not biotic contexts. Together, this collection of work provides quantitative assessments for riparian restoration and conservation trajectories that can be used in adaptive management contexts for decisions about whether to design management strategies to manage drivers of change, enhance adaptive capacity, or enable novel ecosystem configurations.

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Abstract

Pyrite weathering, the biogeochemical process creating acid rock drainage (ARD) and acid mine drainage (AMD), is commonly associated with the mobilization of trace metals and eventual precipitation of hydrous metal oxides. Drier conditions attributed to a warming climate have accelerated this process. The chemical parameters for pyrite weathering generate concentrations that mobilize various metals, including rare earth elements (REEs). Recently, an increase in REE concentration was discovered in a tributary leading to the Dillon Reservoir, CO--the source of drinking water for Denver, Colorado. The humic fraction of dissolved organic matter (DOM) can form complexes with REEs and can also be sorbed by hydrous metal oxides. To study this relationship and the fate and transport of REEs I chose five locations in the Colorado Mineral Belt with distinct biogeochemical environments. These locations vary in dominant types of hydrous metal oxides, DOM sources, such as above tree lines, subalpine forests or wetlands, and known REE concentrations in country rock or water. To gain an understanding of the DOM-REE relationship I used synoptic sampling to (1) identify geochemical parameters, particularly REEs, sum and individual concentrations, within stream-water and flocculant found on the streambed (2) used these geochemical parameters to assess the connections between changes in REE-DOM complexes and their sorption onto hydrous metal oxides. DOM has some control on the REE sorption, but the dominant control is the precipitation and concentration of hydrous Al oxides. REEs are preferentially sorbed with Al precipitates over Fe precipitates. This research advances the understanding of how REEs behave in aqueous environments and will be useful in addressing issues related to increasing REEs concentrations in the Colorado Mineral Belt. This research is particularly relevant to adaptation to climate change driven changes in water quality because there are currently no drinking water standards regarding REEs.

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Abstract

Shifting precipitation and temperature regimes across the Western US is increasing uncertainty about moisture availability in upland forests. As these ecosystems are characterized by thin soils and deep rooting, deep vadose zone water is thought to be central in controlling late-season water availability and potentially water stress. Here, we quantify the spatiotemporal dynamics of rock moisture in a montane catchment of the Colorado Front Range. Direct measurements of rock moisture were accompanied by monitoring of precipitation, transpiration, soil moisture, tree stress, and groundwater levels. Our results show dynamic rock moisture use is widespread, mirrors aboveground vegetation density, likely mitigates drought stress, and is largely confined to the upper saprolite layers. Our findings provide some of the first direct measurements of rock moisture storage and use in the Rocky Mountains and support previous work indicating rock moisture use is not confined to periods of drought or to Mediterranean and semi-arid climates.

Abstract

Climate projections indicate snowfall-dominated areas across the western United States (U.S.) will decline substantially in the coming decades. Temperature increases are already causing snowmelt to occur earlier in the Rocky Mountain region than in the past, significantly impacting the whole functioning of semi-arid ecosystems. Streams within these regions are experiencing a shift from snowmelt to rainfall dominant inputs, with impacts to overall catchment storage and downstream water delivery. Semi-arid forests have also been experiencing widespread forest water stress and regional-scale mortality events in response to increased temperatures and reduced precipitation. To improve our understanding of the implications of these climatic shifts in montane ecosystems, this dissertation investigated hydrological and ecological processes within a semi-arid montane region in the Colorado Front Range. A combination of geochemical mixing models and hydrometric measurements of precipitation, soil moisture, groundwater levels and streamflow were used to quantify spatiotemporal shifts in hydrologic connectivity and stormflow within a semi-arid montane headwater catchment. Source areas to streamflow were found to shift with longitudinal distance downstream, and with time of year. Notably, contributions from upstream source areas became less important than lateral inputs from spring snowmelt into the fall return to baseflow. This was most pronounced within the upper catchment near the stream headwaters, where upstream contributions to streamflow decreased up to 33.3% between spring and fall. During summer storm pulses, pre-event water dominated storm runoff generation across the study catchment, indicating the dominance of groundwater inputs to sustaining streamflow. Although event water contributed minimally to storm runoff generation (< 15%) we observed distinct threshold behavior for event water deliver to the stream with increasing rainfall totals. In a warming climate, this increasing trend in event water delivery to streams will result in reductions of overall catchment storage, with the potential to increase stream intermittency and significantly reduce downstream water delivery. These results reflect dynamic shifts in hydrologic connectivity and stormflow in space and in time, which will become increasingly important to land and water resource management given rapid climate changes within the western United States. Given the prevalence of forest mortality as a result of a warming climate within semi-arid regions, effective and cost-efficient methods for monitoring drought stress over a large spatial scale are needed. We test a new method for monitoring drought stress in a stand of trees within a ponderosa pine forest. This method builds off of previous work that has found that changes in the natural sway period of trees (tree sway) is a strong indicator of drought stress. We pair direct measurements of sway period using accelerometers with video image processed measurements of sway period. While the video processed sway period overall underestimated and had greater variability in sway period relative to accelerometer measurements, this method was capable of detecting a distinct diurnal pattern in sway period consistent with diurnal patterns of tree water stress. We propose improvements to the method, including a different approach for selecting focus regions within the videos, different strategic mounting of the camera, and testing more sophisticated video processing algorithms.

Abstract

Changes in the global ocean system are exerting unprecedented environmental pressures on the microorganisms that drive ocean biogeochemistry. The need for robust molecular biomarkers to assess the contribution of microbial communities to productivity and organic matter pools are vital. Intact polar lipids (IPLs), the main constituents of cell membranes, show great utility in assessing microbial community compositions and contributions to organic matter pools. However, significant challenges in their application remain due to an increasingly diverse pool of discovered molecules with limited information of source organisms, in addition to an added complexity of IPL remodeling (structural modifications) in response to changing environmental conditions.

In this thesis, I present observations of the abundances and distributions of IPLs in microbial plankton from the oxygen minimum zone (OMZ) of the coastal Eastern Tropical South Pacific (ETSP) in both oceanographic transects and mesocosm experiments. I aim to improve the utility of IPLs in reconstructing microbial communities by employing geochemical conditions, size-fractionated analyses, metabolic rates, and other molecular biomarkers as statistical constraints to distinguish biological sources of IPLs. In addition, I investigate the potential extent and impacts of physiological adaptations of photosynthetic microorganisms (phytoplankton) in response to multi-environmental drivers based in remodeling of the intact lipidome.

The results from oceanographic transects indicate that statistical ordination of geochemical environments and size-fractionated analyses improve the specificity of IPL sources. We demonstrate that IPL distributions are strongly indicative of living microbial biomass and a major contribution of water column biomass is found in the anaerobic subsurface. Via mesocosm experiments, we find evidence of widespread intact lipid remodeling among phytoplankton in response to changing temperatures, carbon chemistry, oxygen concentrations, light availability, and nutrient stoichiometries. We also suggest a dependence of IPL distributions on metabolic rates that may distinguish specific source organisms of microbial IPLs. Finally, we establish IPL richness to increase as the system’s limiting nutrient (inorganic nitrogen) declines, in addition to enhanced community respiration and production rates. This investigation of marine IPLs aims to improve our understanding of microbial community structure, the major reservoirs of organic matter they represent, and assess physiological responses to changing ocean conditions.

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Abstract

Hydrologic exchange flows (HEFs), which are the movement of water between a river channel and the adjacent subsurface, are important for water quantity, quality, and ecosystem function. The spatial distributions of HEFs in streams are influenced by hydrologic conditions in the aquifer, hydraulic conditions in the channel, and the spatial distribution of permeability under and around the channel. Exchange with adjacent aquifers is less well understood in large rivers because tracer injections are much more difficult due to water depth and higher flows than in small streams where they have been used extensively. In this study we ask whether large-scale geologic units in the area drive HEF locations more than the finer-scale sediment types and the riverbed morphology along a 75 km reach of the Columbia River near the Hanford Site in eastern Washington. To determine the locations of HEFs we measured temperature, specific conductance, and dissolved Radon-222 along the riverbed during three sampling events in 2021/2022. We used a FloaTEM system to identify the locations of changes in the large-scale geology and compared these to the locations of HEFs. Though each method we used had some shortcomings, together they provided a more complete picture of what drives HEF locations. We observed water quality anomalies in similar locations to 3D numerical modeling experiments and past field research in the study area, but we did not find a single factor that completely explained the locations of HEFs. Though sensitive to surface water inflows, our method is useful for quickly surveying long reaches of river and determining locations for more in-depth investigations of HEF dynamics.

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Abstract

Marine phytoplankton (algae) play a key role in the Earth system by influencing ocean biogeochemical cycling, the flux of carbon dioxide from the atmosphere to the ocean, and the productivity of fisheries. The growth of these microscopic, unicellular primary producers is strongly affected by the oceanic physical and biogeochemical environment. As such, the variable and changing climate system has a large influence on phytoplankton abundance, its spatial distribution, and its temporal variability. Internal variability naturally arises from interactions between components of the coupled climate system, for example, between the ocean and the atmosphere. Whereas, anthropogenic changes to the climate system are considered to be externally forced, as they arise from greenhouse gas emissions. Phytoplankton experience both internal climate variability and externally forced anthropogenic changes, and it can be difficult to discern the influence of internal and external processes in the marine biosphere. Recent research suggests that it may be possible to separate internal and external influences on the coupled Earth system using large ensembles of Earth system models (ESMs). However, ESMs may not skillfully predict observed spatial patterns and temporal dynamics in real-world marine phytoplankton. In this dissertation, I use observational records and ESM ensembles to investigate the role of internal climate variability in marine phytoplankton in a warming climate. I first use a novel statistical emulation technique to place the remotely sensed record of surface ocean chlorophyll concentrations into the large ensemble framework. Much like a large initial condition ensemble generated with an ESM, the resulting observationally constrained synthetic ensemble represents multiple possible spatiotemporal evolutions of observed ocean chlorophyll, each with a different phasing of internal climate variability. I use the observationally constrained synthetic ensemble to contextualize the interpretation of long-term trends in the presence of internal variability and identify a wider range of possible trends in chlorophyll due to the sampling of internal variability in subpolar regions than in subtropical regions. Next, I evaluate the statistical methodology of the observationally constrained synthetic ensemble in the context of a large ensemble of an ESM. When applying the statistical approach to the Community Earth System Model Large Ensemble (CESM1-LE) over the historical period, simulated variability in surface ocean chlorophyll concentration is able to be reproduced using the statistical method. Finally, I quantify the influence of anthropogenic climate change on variability in phytoplankton biomass using the CESM1-LE. I find a significant decrease in the interannual variance of phytoplankton biomass under a business-as-usual (RCP8.5) emission scenario, with heterogeneous regional trends. Statistical analysis of regional trends reveal zooplankton grazing (top-down control) as an important contributor to changes in phytoplankton variance. The results of this dissertation highlight the influence of internal climate variability on marine phytoplankton in a warming climate.

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Abstract

Seasonal snowpack is an essential component in the Earth's hydrological cycle. About one-sixth of the global population relies on seasonal snowpack and glacier-derived runoff as a primary water resource. Snowmelt contributes to regional water supply, partially dictating the timing and volume of downstream water resources. Mountain snowpacks act as a natural "water tower," storing winter precipitation until spring and summer months when downstream water demand is greatest. The magnitude and duration of regional snow water storage at the Earth's surface is thus a function of precipitation phase (as rainfall or snowfall) and the subsequent timing of water release, is unevenly distributed across regions, and is highly sensitive to climate changes. In mountainous western North America, hydrologic partitioning of catchment water inputs is likely sensitive to snow water storage, greatly influencing the volume and timing of downstream water resources. While previous works have studied the distribution of snow water equivalent (SWE) and trends in SWE, previous works have not evaluated the magnitude and duration of snow water storage. As a result, our understanding of how future changes in snowpacks will impact land surface hydrology is poorly understood. Hence, by evaluating trends in the magnitude and duration of snow water storage, and its impact on land surface hydrology, this dissertation adds substantively to the current literature.

In this dissertation, I developed a snow water storage metric with a focus on surface water (i.e., above the soil layer), investigated historical and future changes in snow water storage, and related this metric to hydrologic partitioning, or the allocation of water inputs to streamflow (or evapotranspiration) across multiple spatial scales. The second chapter of this dissertation is an overview of a newly developed snow water storage metric, which quantifies the differences in volume and timing between precipitation and surface water inputs (SWI, the daily summation of rainfall and snowmelt). Using precipitation forcings and modeled SWE outputs from the Variable Infiltration Capacity (VIC) model, I produced a Snow Storage Index (SSI) to quantify snow water storage volume and duration across western North America. I found that the average annual SSI has decreased (p<0.01) from 1950-2013. By evaluating precipitation and SWI trends, I showed that the decrease in SSI was a result of significantly earlier SWI in spring months and comparable decreases in SWI later in the year. In mountainous regions where the SSI is declining, which includes > 25% of the western North America study domain, snowmelt and rainfall have begun occurring earlier in the year, reducing the duration and magnitude of snow water storage. This is particularly evident in the Cascades and Southern Rockies. Additional declines in winter precipitation have reduced snow water storage in the Canadian and Northern Rockies. The sensitivity of the SSI depends on annual and seasonal temperature and precipitation variability and varies across different regional mountain ranges. As opposed to trends in SWE or snow fraction, the SSI represents the degree to which snow is delaying the timing (and magnitude) of SWI relative to precipitation. This lag between precipitation inputs and water availability is a fundamental component of the hydrologic cycle in snow-affected regions, offering a more hydrologically relevant perspective (than SWE trends, for example) on changes in water delivery and related climatic sensitivities for hydrologic and ecologic cycles and water resource management.In Chapter Three of this work, I related the SSI to hydrologic partitioning across the United States mountainous west. I discovered that the relationship between SSI and partitioning of incoming precipitation to streamflow is strongly and positively correlated within many ecoregions in the study domain. The ecoregions showing the strongest, positive correlations included: Cascades (r2 = 0.62), North Cascades (r2 = 0.61), Blue Mountains (r2 = 0.56), Canadian Rockies (r2 = 0.55), Idaho Batholith (r2 = 0.48), and Columbia Mountains / Northern Rockies (r2 = 0.45). The ratio of weekly SWI to weekly precipitation (SWI:P) was an equally strong predictor for hydrologic partitioning, particularly in mid-spring (e.g., March / April) and early summer (e.g., June / July) in the same mountainous ecoregions. When less water enters the soil system in spring months, and more in summer months, indicating a longer duration of water storage in the snowpack, more annual water inputs are partitioned to streamflow (maximum r2 across the same ecoregions = 0.62-0.74).Secondarily, when clustering ecoregions by climate and energy- vs. water-limitations, there was a strong and positive correlation between the SSI and hydrologic partitioning to streamflow in regions with greater energy-limitations, in both maritime (r2 = 0.57) and inter-mountain / continental (r2 = 0.42) climates. Relatively water-limited ecoregions, such as the Sierra Nevada, Middle Rockies, Wasatch / Uinta Mountains, and Southern Rockies, showed less sensitivity of hydrologic partitioning to the SSI, potentially due to relatively high aridity. As snow water storage decreases with warming, the timing of water delivery will change to varying degrees across the western United States, with large implications for hydrological and ecological processes and for water resource management across Earth's snow-influenced regions.In Chapter Four of this work, I used similar methodology to represent historical (control) and future (warming) snow water storage and hydrologic partitioning behavior and relationships at a smaller, alpine watershed in the Front Range of Colorado. Using the Distributed Hydrology Soil Vegetation Model and Weather Research and Forecasting Model-based projections of future climatic conditions, I generated a control and end-of-century warming simulation to compare snow water storage in the past and the future. Similar to the larger scale analyses in Chapters Two and Three, I found that areas where SSI was high experienced a decrease in snow water storage magnitude and duration in the warming (future) simulation, compared to the control (historical) simulation, due to increased rainfall and earlier snowmelt. Within both simulations, areas annually storing water as snow in larger volumes and for longer durations (i.e., greater SSI) partitioned more water to streamflow compared to areas of lower snow water storage (i.e., lower SSI), particularly within bare ground (r2 = 0.82 (control), 0.76 (warming)), alpine meadow (r2 = 0.71, 0.79) and closed shrub (r2 = 0.80, 0.72) vegetation types.

On average across the catchment, the warming simulation showed decreased snow water storage (SSI: -0.11) from the control simulation (SSI: -0.07), resulting in a -57% change in SSI. Spatially, SSI percent change across the catchment ranged from -100% to +27%, with increases occurring in wind-scoured areas of the catchment where summer-dominant precipitation seasonality became more uniform. As such, using the Budyko framework, there was an average -10.2% change in the expected amount of precipitation that was partitioned to streamflow under warming conditions. Decreases in partitioning to streamflow with warming suggests that, particularly in cold, alpine regions, future streamflow losses may stress ecological, biological, and sociological dependents downstream, even at small, sub-catchment scales.

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Abstract

Harmful algal blooms (HABs) create a risk to water resources as these overgrown algae can (1) deplete oxygen in waterbodies affecting aquatic habitat and (2) potentially develop toxins when composed of toxic-producing algae (e.g., cyanobacteria) that are proven to adversely affect human health. This comparative limnology study integrates in situ methods to better understand biogeochemical processes simultaneously with remote sensing data. We studied four waterbodies under Boulder Open Space and Mountain Parks management from June to August in Summer 2021: Sawhill Ponds No. 1, Teller Lake No. 5, Sombrero Marsh, and Wonderland Lake. For much of the summer, Sombrero Marsh exhibited N-limited conditions with higher chlorophyll-a and percent cyanobacteria. Other waterbodies remained P-limited and generally increased biomass throughout the summer, with peaks at the end of July and August. Remote sensing results found algal blooms in all waterbodies, but only Sombrero Marsh with a cyanobacterial bloom, but maps indicated evidence of cyanobacteria in 3 of the four waterbodies sampled. When using chlorophyll-a as a proxy for HABs, remote sensing was unable to detect cyanobacterial blooms in waterbodies with chlorophyll-a concentrations <10 μg/L. These findings suggest that remote sensing is a viable tool to monitor algal blooms; but for these smaller waterbodies, there is uncertainty unless a high concentration of algae is present on the water surface to determine a cyanobacterial bloom.

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Abstract

I present quantitative Pliocene-Pleistocene terrestrial tropical temperature estimates along with the refinement of organic and stable isotope geochemical proxies in the northern tropical Andes of Colombia. The Pliocene epoch, 5 to ~2.6 million years ago (Ma), is often cited as the last time when Earth’s mean temperature was ~2.5-4°C warmer than today, and CO2 concentrations may have been higher than preindustrial levels. Although the tropics play an important role in regulating global climate, a recent summary of Pliocene temperature terrestrial records includes no site within 10º of the equator. The Sabana de Bogotá in the Eastern Cordillera of Colombia offers unique sedimentary archives from the tropics (~4ºN), including sediment from an extinct lake preserved in the Funza-II core that dates back to late Pliocene, which allows an opportunity to apply quantitative geochemical proxies for temperature reconstructions.

Branched glycerol dialkyl glycerol tetraethers (brGDGTs) are bacterial cell membrane lipids that, when preserved in sedimentary archives, can be used to infer continental paleotemperatures. I present an in situ regional calibration of soil brGDGTs along altitudinal transects on both flanks of the Eastern Cordillera of Colombia that spans ~3,200 m in elevation for soil and air temperatures. These calibrations yield RMSEs of 1.5°C and 1.9°C, respectively, and allow for more precise and reliable reconstructions of past temperatures in the tropics than global calibrations. Along with refining brGDGTs in the northern tropical Andes, I also evaluate the efficacy of stable isotopes of precipitation and plant waxes as proxies for paleoaltimetry studies in the region. I use monthly hydrogen (δ²H_p) and oxygen (δ¹⁸O_p) isotope values of precipitation for an annual cycle, as well as hydrogen isotope values of plant waxes (δ²H_wax) in top soils along the same elevation transects as for the brGDGTs calibrations. The δ²H_wax values along the eastern flank of the Eastern Cordillera follow a simple Rayleigh distillation, with the average δ²H_wax values of n-C29, n-C31, and n-C33 alkanes showing an R² = 0.65 when regressed against elevation. In contrast, because of the lack of correlation with elevation in modern precipitation on the western flank, neither δ²H_p nor δ¹⁸O_p, and therefore δ²H_wax, offer reliable estimates of past elevations.

Regressions of surface temperatures in the Eastern Cordillera of Colombia with sea-surface temperatures (SSTs) in the equatorial Pacific show that the Eastern Cordillera warms or cools by half of the amplitude of the variation of SSTs in the eastern Tropical Pacific. Because Pliocene SSTs in the eastern Tropical Pacific resemble those during major El Niño events, when SSTs warm by ~4°C, the Pliocene Eastern Cordillera warms by ~2ºC at both high and low elevations. To evaluate how temperature changed in the Sabana de Bogotá during the Pliocene-Pleistocene, I estimated brGDGTs-based temperatures in the Funza-II core. New geochronology based on zircon U-Pb dates from ash layers place the base of the core at around ~4 Ma. I show that Pliocene temperatures were ~2.2 ± 2.0°C warmer than mid-late Pleistocene temperatures. This ~2°C warm in temperature could be explained by a permanent El Niño-like teleconnection to the Eastern Cordillera of Colombia, rather than a pantropical change in temperature. These temperature estimates are the only terrestrial tropical record within 5° of the equator for Pliocene time.

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Abstract

Acid rock drainage (ARD) produces low pH, high metal concentration waters into receiving waters down-gradient from oxidizing sulfide minerals. ARD can degrade habitat, poison aquatic organisms, and lead to the transport of heavy metals long distances down streams. This dissertation investigates ARD responses to three different perturbations: decadal-scale response to targeted AMD remediation strategies including source material removal and bulkhead installation, decadal-scale response to climate change, and month-scale response to bulkhead implementation in draining mine adits. The goal of these investigations is to advance the understanding of ARD responses to anthropogenic and natural changes to help optimize remediation actions and future management of ARD affected waters. First, monitoring water quality data were paired with USGS flow gage data and an estimator was used to estimate higher temporal frequency records of in-stream water quality in three ARD affected alpine watersheds. These data were then analyzed for trends in water quality corresponding with timing of treatment implementation. Two streams record decreased zinc concentrations following treatment implementation; one stream records a substantial increase in zinc concentration following a shift from active treatment to passive, bulkhead-oriented treatment strategies. A second study investigated trends in background ARD in response to local climate change at 24 headwater stream sites across the Colorado Mineral Belt. Zinc concentration increased at 75% of sites over the period of record (10-40 years) by 2-6 fold and sulfate concentration increased at 96% of streams. The final study presented in this dissertation investigates the short-term impacts of a bullhead closure on water quality in receiving waters. Results indicate that sulfate and heavy metal concentrations decreased during the test closure buy 65-68%. However, the short duration of the test closure and the relatively small volume of water impounded during the test closure (<1% of the estimated storage volume) leave uncertainty over longer-term impacts of the bulkhead test. Collectively, the studies presented in this dissertation expand the knowledge of ARD responses to both remediation-based changes and natural climate driven changes on the catchment scale.

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Abstract

One of the most reliable features of natural systems is that they fluctuate through time. Both community ecology and evolutionary theory predict that these fluctuations will have important implications for the evolution of life history strategies to cope with temporal variation as well as community composition and coexistence. In this study we evaluated the role of two components of temporal environmental variation - variability and predictability - on community composition and individual species distribution patterns within a single water catchment at the Niwot Ridge Long-Term Ecological Research site located in the Front Range of Colorado (USA). We used high-temporal-resolution sensors located within the sensor network array (SNA) at Niwot Ridge to evaluate the variability (coefficient of variation or threshold crossing) and predictability (autocorrelation) over daily and seasonal time scales. We used community composition data from plots co-located with sensors to evaluate the relative contributions of the mean, variability, and predictability in soil moisture and temperature in predicting spatial variation among communities. We then tested how the mean, variability, and predictability in soil moisture and temperature influence patterns of occurrence and abundance for individual species. We found that variability in soil moisture and soil temperature were as important as mean conditions for explaining variation among communities. We also found no uniform effect on species occurrences or abundances for any variable we tested; instead, species showed a wide range of relationships with environmental variables. Our results suggest that alpine species specialize and differentiate on not only mean conditions in soil moisture and temperature, but also the variability and predictability components, and that including measures of temporal variability in environmental conditions can improve our ability to explain species distributions and patterns of community composition in heterogeneous landscapes.

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Abstract

Streams are biogeochemical connectors that transport and transform nutrients and carbon throughout their watershed. This ability can be altered temporarily or permanently by anthropogenic disturbances like climate warming. The ephemeral streams of the McMurdo Dry Valleys, Antarctica [MDV], are 'model systems', with relatively simple ecology and hydrology: they are fed only by glacial meltwater, and perennial microbial communities drive stream ecosystem function. As Antarctic climate warming continues, it is important to understand both current stream biogeochemical processes and how these may alter under a warmer climate regime.My research goals are to quantify two key MDV stream biogeochemical processes: carbon fluxes and nutrient (N, P) uptake; and to assess how these ecosystems respond to a warming-related thermokarst disturbance. First, I quantified concentration-discharge relationships for dissolved organic carbon [DOC], and found that, despite low organic carbon stocks and large diel changes in discharge, these streams exhibit DOC chemostasis. To explain this behavior, I developed a new conceptual model for DOC generation and storage. Next, I used pulse additions to determine nutrient uptake dynamics for NO3-N, NH4-N and PO4-P in six streams across the Taylor Valley, at nutrient concentrations from ambient to saturation. These streams demonstrated efficient uptake even at concentrations 2-3 orders of magnitude above typical background levels, indicating biotic ability to adjust to large and rapid changes in nutrient levels. Finally, I quantified stream biotic response to a 2012 thermokarst event, which loaded sediment and nutrients into an MDV stream, by using high-resolution satellite imagery to map stream microbial mat activity from 2010 to 2019. Surprisingly, biotic activity increased the year after the thermokarst event, indicating that MDV mat communities are resilient to this type of disturbance. We hypothesize that significantly-higher post-thermokarst N and P loads may have aided this rapid recovery.As a whole, my research advances understanding of essential stream biogeochemistry in this polar desert environment, including how these systems may respond to a warmer future. Findings from these model systems can also advance our understanding of more complex systems, e.g. temperate and tropical streams, where the microbially-driven processes I elucidate are often hidden by other, larger fluxes.

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Abstract

Uncertainty in climate predictions arises from three distinct sources: the internal variability of the climate system, which refers to natural fluctuations in climate that occur even in the absence of external forcing, model or structural uncertainty, as different models make different assumptions and hence simulate somewhat different changes in climate in response to the same forcing, and scenario uncertainty, which represents humankind’s free will concerning future climate change. In this thesis, we evaluate projections of Arctic sea ice in the context of these different sources of uncertainty. In particular, we show that internal variability, not scenario uncertainty, will ultimately determine the year of first summer ice-free conditions in the Arctic, in addition to the contribution from model uncertainty. Moreover, the increased inter-annual variability in late historical biomass burning forcing is found to cause a strong acceleration in sea ice decline in the early 21st century in several CMIP6 models, with model uncertainty affecting how different CMIP6 models respond to this forcing. Finally, we focus on the implications of scenario uncertainty on the changing sea ice cover through the lens of trans-border exchange of sea ice between the exclusive economic zones of the Arctic states. These different perspectives on climate model uncertainty allow for an improved understanding of the processes, variability and implications of a diminishing Arctic sea ice cover.

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Abstract

Plucking is a common erosional mechanism in steep bedrock rivers with well-jointed, layered bedrock. Where active, plucking is one of the most efficient erosional mechanisms. However, the influence of bedrock layering and jointing on the evolution of rivers carved into layered landscapes has yet to be properly addressed at the process level. Rivers carving into fractured and jointed rock commonly display sharp steps in the bed separated by flat reaches between the steps. At the edges of these steps, blocks are vulnerable to plucking by both sliding and toppling. In this work, I seek to constrain the roles of block geometry and flow physics on the susceptibility of such blocks to entrainment. I use numerical modeling to demonstrate how blocks play an important role in setting the pace of river evolution, and therefore should be accounted for in landscapes where plucking is active. I first employ a computational fluid dynamics model to constrain the pressure and shear forces on blocks under different flow conditions. I use the results of this model to inform calculations of the susceptibility of blocks to entrainment and find that accounting for the pressure differences around blocks in force calculations significantly reduces entrainment thresholds. I then use these numerical results to inform a process-based 1-D model of bedrock river evolution that accounts for the entrainment probability of individual blocks in a jointed bed. I find that in the absence of external forcing, jointed beds will self-organize into a series of steps that is set by the baselevel lowering rate and block heights. Adding layers consisting of larger blocks stalls erosion at the contact between the large blocks and smaller blocks. Further, the large blocks prevent any signal of changes in baselevel lowering from being transmitted upstream until the large blocks are able to be plucked. Finally, I test this model with a spillway erosion case study from Canyon Lake, Texas, where an 8 m deep canyon was carved during a three-day flood event. The work presented here demonstrates the importance of properly accounting for block physics in river evolution models.

Advisor

Robert S. Anderson

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Abstract

Quantifying snowmelt behavior is valuable for understanding snow’s implications for water availability, flood risk, and ecosystem health. Building off of ongoing analyses of observed lateral movement of liquid water through snow, this research used repeat ground penetrating radar (GPR) derived liquid water content (LWC) maps and terrestrial Light Detection and Ranging (LiDAR) derived snow depth maps to explore the effects of wind and topography on the distribution of liquid water within an alpine snowpack on Niwot Ridge, Colorado. Observations of wind speed and direction were combined with a simplified linear turbulence model to produce distributed estimates of wind speed for this alpine basin. In this paper, we assess how wind-driven snow accumulation and redistribution impact the subsequent patterns of liquid water in snow during the melt season. Using linear regression models relating topography and liquid water estimates, we explore the physical controls on snowmelt water availability. In areas of deep snow, wind flow patterns play a critical role in determining the storage and transmission of liquid water in the snowpack. The GPR and LiDAR data indicate that meltwater tends to collect at the interfaces of the snow layers, largely governed by wind dynamics, and this water moves rapidly along these interfaces to streams and rivers. We discuss how improved model representation of in-snow liquid water may be achieved through the aforementioned detailed measurements and analyses. 

Abstract

Mountain snowpack is one of the primary surface water sources for about one-sixth of the global population. Accurately monitoring the spatial and temporal distribution of mountain snowpack – often measured as snow water equivalent (SWE) – is crucial for effective water management. While existing SWE estimation approaches remain highly uncertain, particularly when applied over large mountainous regions, the remotely-sensed snow data provide new opportunities to better characterize the spatial distributions of mountain snowpacks. This dissertation investigates the approaches that optimally blend satellite, airborne, and ground snow observations to improve (near) real-time SWE estimation over mountainous terrain.

The second chapter of this dissertation evaluates the accuracy of existing SWE estimation models in Sierra Nevada California. Five large-scale SWE datasets at fine spatial resolutions (<= 1000 m) are comprehensively validated and compared with the Airborne Snow Observatory (ASO) SWE data and ground snow pillow and snow course SWE observations. These SWE datasets include REC-INT, REC-ParBal, a Sierra Nevada SWE reanalysis (REC-DA), and two operational SWE datasets from the Snow Data Assimilation System (SNODAS) and the National Water Model (NWM-SWE), respectively. The results show that the REC-DA overall provides the most accurate SWE estimates across the Sierra Nevada (R2 = 0.87, MAE = 66 mm, PBIAS = 8.3%), followed by the REC-ParBal (R2 = 0.73, MAE = 83 mm, PBIAS = -6.4%), which is the least biased SWE estimates. Generally, SNODAS (R2 = 0.66, MAE = 106 mm, PBIAS = 9.3%) and REC-INT (R2 = 0.61, MAE = 131 mm, PBIAS = -28.3%) exhibit comparable but lower accuracy than the earlier mentioned two datasets, while NWM-SWE (R2 = 0.49, MAE = 142 mm, PBIAS = -25.2%) shows the least accuracy among the five SWE datasets.

Given that REC-DA is not applicable in real-time, in the third chapter, a SWE data-fusion framework is developed, which integrates the historical SWE patterns derived from REC-DA into a statistically-based linear regression model (LRM) to estimate SWE in real-time. To investigate the influence of satellite-observed daily mean fractional snow-covered area (DMFSCA) on SWE estimation accuracy, two LRMs are compared: a baseline regression model (LRM-baseline) in which physiographic data and historical SWE patterns are used as independent variables, and an FSCA-informed regression model (LRM-FSCA) in which the DMFSCA from MODIS satellite imagery is included as an additional independent variable. By incorporating DMFSCA, LRM-FSCA outperforms LRM-baseline with improved R2 from 0.54 to 0.60, and reduced PBIAS from 2.6% to 2.2% in snow pillow cross-validation. The improvement in LRM-FSCA’s performance is more significant during snow accumulation periods than during the snowmelt seasons. Compared to the ASO SWE, the LRM-FSCA explains 85% of the variance on average, which is at least 21% higher than the operational SNODAS (R2 = 0.64) and NWM-SWE (R2 = 0.33) in comparison.

In chapter 4, a SWE bias correction framework (SWE-BCF) is developed that incorporates the ASO SWE and machine learning (ML) algorithms to further improve LRM SWE estimates in real-time. The performance of a wide range of commonly used machine learning algorithms is examined in the SWE-BCF including Gaussian Process Regression (GPR), Support Vector Machine (SVM), Bayesian Regularized Neural Networks (BRNN), Random Forest (RF), and Gradient Boosting Machine (GBM). The results indicate that all ML algorithms are capable of improving LRM-SWE accuracy substantially. While no single model performs significantly better than others, GPR, overall, shows the best performance with a 20% (0.14) increase in mean R2 value, a 31% (51 mm) reduction in mean RMSE, and a 61% (18.0%) reduction in absolute PBIAS compared with the original LRM using ASO SWE data for model validation. RF shows the most robust and stable performance in SWE bias correction with a 10% (0.08) increase in median R2 and a 41% (50 mm) reduction in median RMSE compared with the original LRM.

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Abstract

Stable isotopes of hydrogen and oxygen in polar ice cores provide information about local temperature and atmospheric circulation. We use a multi-taper method (MTM) of spectral analysis on a continuous high-resolution (i.e. mm-scale) Greenland water isotope record, recently recovered from the East Greenland Ice Core Project (EGRIP), to determine how interannual and decadal temperature variability changed throughout the past 50 thousand years. We are specifically interested in trends across the most recent glacial-interglacial transition and across millennial scale Dansgaard-Oeschger (i.e. stadial-interstadial) cycles to elucidate how large temperature changes affect variability around the mean in Greenland. To further understand global relationships in variability, we later make comparisons with mm-scale ice core records from the South Pole (SPC) and the West Antarctic Ice Sheet Divide (WDC). Our results reveal a strong coupling between mean temperature and high-frequency (i.e. 7-15 year) climate variability at EGRIP. On average, the Last Glacial Period (LGP; 11.7-50 ka bp) exhibits 2.5 times greater variability than the Holocene and within the context of the LGP, cold stadial periods are 1.5 times more variable than warm interstadial periods. We provide a plausible mechanism for the trend we observe across Dansgaard-Oeschger (DO) cycles in northeast Greenland: a larger sea ice area coupled with a more variable sea ice front may explain the increased isotopic variability during cold stadial periods. In contrast, neither Antarctic site (SPC or WDC) exhibit changes in high-frequency variability across millennial scale warm phases, known as Antarctic Isotope Maxima (AIM) events, that occur with each DO Event. While elucidating exact forcing mechanisms for observed trends in high-frequency variability is outside the scope of this study, we provide critical benchmarks and reasonable hypotheses to test in future climate modeling research.

Abstract

Polar ice cores contain multiple proxies which record vast amounts of climate information over hundreds of thousands of years. Water isotopes in ice cores can be used to infer past temperature and atmospheric circulation patterns, and with recent advances in technology can be measured at very high resolution. Here, I present analyses of continuous water isotope records from two new Greenland ice cores, and use snow surface experiments to work towards improving our interpretation of ice core records.

The Renland Ice Cap is located in East-Central Greenland, and an ice core drilled in 2015 contains a seasonally-resolved water isotope signal through 2.6 ka and sub-decadal signals through 8 ka. Using spectral analysis, I find that decadal (i.e. 15-20 year) isotope variability at Renland co-varies with North Atlantic sediment core indicators of ocean circulation patterns throughout the Holocene. Furthermore, analysis of the seasonal signal reveals that a decreasing trend in the winter isotope signal may correspond to an increase in Arctic sea ice cover and a decrease in total annual insolation over the last 2.6 ka. Together, these findings show that coastal Greenland climate may be closely tied to regional sea surface conditions.

The East Greenland Ice Core Project (EastGRIP) is an ongoing drilling campaign in Northeast Greenland, with a record currently extending to 50 ka. EastGRIP has sub-decadal isotope signals preserved through the Glacial period, and for the first time we have a continuous Glacial record for multiple isotope parameters (i.e. δ18O and deuterium excess). Through comparison to a North-Central Greenland ice core record, I demonstrate the importance of high-resolution sampling and expand on our understanding of spatial variability in Greenland climate. Additionally, an analysis of abrupt climate events throughout the Glacial period indicates that rapid warming is preceded by a shift in North Atlantic atmospheric circulation patterns; this has important implications for our understanding of mechanisms occurring during abrupt climate changes.

Many aspects of the isotope-climate relationships are well constrained through decades of research; however, there remain gaps in our understanding of processes taking place at the surface of the ice sheet between depositional precipitation events, and how they influence the recorded climate signal. To address this I use a series of laboratory experiments to show that in a controlled environment the snow isotopic composition changes rapidly due to sublimation, with this finding supported by model results. Complementary field experiments demonstrate that in a natural setting, the top 4 cm of the snow surface evolves on an hourly timescale due to sublimation and exchange with atmospheric vapor. These results suggest that water isotopes may effectively integrate across multiple parameters to record a more continuous climate signal, which may improve isotope-enabled climate models and inform our interpretation of ice core water isotope records.

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Abstract

Lagerman Reservoir is a saline, closed evaporite basin subject to changing hydrologic regime, algal blooms, and fish kills. This ecological survey was conducted to obtain scientific data for future management decisions and recreational safety. Weekly shore samples and monthly depth profile samples were taken, along with data synthesis of EPA's CyAN satellite monitoring system. Dissolved oxygen was low, indicating unfavorable conditions for fish and macroinvertebrates. Transparency and nutrient concentrations were also low, with nitrogen limiting the system. The algal biomass was dominated by Synechococcus, as well as Dolichospermum, Lyngbya, Oscillatoria, and Merismopedia. Chlorophyll-a analysis indicated similar trends to the CyAN satellite data, with a peak of algal growth around late June, followed by a die off of algal biomass. This reservoir ranged from eutrophic to hypereutrophic. Lagerman Reservoir is considered to be unsuitable for fish and vulnerable to toxic algal blooms that could be hazardous to human health.

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Abstract

As high latitude regions continue a decades-long trend of warming at roughly twice the rate of the global average, an understanding of their climatic histories becomes increasing important for predicting their future. Organic molecular proxies preserved in lake sediment archives offer one avenue for reconstructing key elements of such past climates, including their temperature, precipitation, and vegetation regimes. In particular, a class of bacterial membrane-spanning lipids called branched glycerol dialkyl glycerol tetraethers (brGDGTs) form the basis for a paleothermometer that can be applied to reconstruct temperatures as far back as the Cretaceous in sedimentary archives across the globe.

Despite these successes, challenges remain that complicate the development and application of brGDGT-based proxies. First, while they correlate best with temperature and pH, other environmental parameters can influence brGDGT distributions, including seasonality, conductivity, and oxygen availability. Second, it is unknown whether these empirical correlations are the result of a direct physiological response of brGDGT-producing organisms to their environment or an indirect effect resulting from variations in bacterial community composition. Finally, an incomplete understanding of where brGDGTs are produced on the landscape and how they contribute to the sedimentary record hinders our ability to interpret proxies in mixed-source archives.

Herein, I present research addressing each of these three challenges with an emphasis on the Eastern Canadian Arctic and Iceland. First, I develop a technique for grouping brGDGTs based on structural characteristics and show that it can be used to deconvolve the effects of temperature and pH/conductivity. I further find a warm-season bias in brGDGT-derived temperatures and develop calibration equations for temperature and conductivity. Next, I compile >2500 samples from a dozen sample types across the globe and find near-universal trends in the relationships between brGDGTs and temperature, pH, and one another. These commonalities support a physiological basis for observed environmental trends. Finally, by measuring brGDGTs in their intact, polar form, I find that lipid sources in lake catchments can be distinguished and suggest novel applications down core. By advancing our understanding of brGDGTs, my results further our ability to reconstruct key climatic variables from sedimentary archives, especially at high latitudes.

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Abstract

Wetlands serve as important locations of disproportionately high biogeochemical activity and plant productivity in many lowland regions. However, little is known about the function of alpine wetlands, or about how their biogeochemical cycling compares with the broader alpine landscape, which is usually composed of thin, rocky soils and tundra vegetation. In my thesis research, I compared the soil and water biogeochemistry among three types of alpine wetlands at Niwot Ridge, Colorado: alpine wet meadow, periglacial solifluction lobe, and subalpine wetland. Each wetland type exhibited unique biogeochemical characteristics and higher concentrations of carbon and sulfur than dry alpine meadow. These findings suggest that wetlands may have a disproportionate effect on biogeochemical and ecological processes at Niwot Ridge, and serve as important sites in predicting the effects of global change on alpine landscapes.

Abstract

The past several decades have witnessed a fascinating evolution in the sulfur (S) cycle, resulting in an unprecedented increase in agricultural S use. However, little research has explored how intensive agricultural S applications alter S biogeochemistry across a range of agricultural settings and scales— essential for constraining the cascade of environmental effects of using S in agriculture. In this dissertation, I identify and trace the biogeochemical “fingerprint” of agricultural S from field-to-watershed scales.

Asking first how patterns of S chemistry change across a watershed with intensive agricultural S inputs, I contrasted S stable isotope (δ34S) and sulfate (SO42-) concentration measurements collected within agricultural areas and surrounding forests and grasslands with background (atmospheric and geologic) S sources. Stable S isotope results showed that agricultural S has a robust and distinctive biogeochemical fingerprint that is traceable beyond fields. I then delved deeply into processes affecting organic S composition—the largest pool of S within soils. I developed a novel method to directly measure δ34S of dissolved organic matter (DOM) and combined this approach with techniques to measure organic S speciation and molecular composition. Agricultural S applications increased DOM S-content by two-fold compared to forests and grasslands, and I found that a suite of molecules unique to agricultural areas have the potential to be used as agricultural S tracers. Finally, I investigated how wildfire disturbance affects agricultural S and its interactions with other elemental cycles. Though not appearing to strongly affect the agricultural S fingerprint, wildfire did enhance organic carbon leaching, producing a potentially potent cocktail for stimulating toxin production in downstream aquatic ecosystems. These results reinforce the importance of considering integrative studies at watershed scales to evaluate the transport and fates of agricultural S and point to the increasing role of climate change as an additional control on agricultural S biogeochemistry.

Combined, this research (1) reveals agricultural changes to the modern S cycle at multiple scales, (2) establishes tools and techniques to trace agricultural S through watersheds, and (3) provides a critical first step towards fully constraining the environmental fates and unintended consequences of S inputs to agricultural systems.

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Abstract

As water flows downstream, it is transported to and from environments that surround the visible stream. Along with surface water, these laterally and vertically connected environments comprise the stream corridor. Stream corridor connectivity influences many ecosystem services, including retention of excess nutrients. The subsurface area where stream water and groundwater mixes—the hyporheic zone—represents one of the most biogeochemically active parts of stream corridors.

The goal of my research is to advance understanding of how connectivity between different parts of a stream corridor controls the availability and retention of nitrogen (N), a primary nutrient that can negatively impact water quality. First, I developed and applied a new machine learning method to objectively characterize the extent and variability of hyporheic exchange using geophysical data. In applying this method to a benchmark dataset, I found that hyporheic extent does not scale uniformly with streamflow and that changes in the heterogeneity of connectivity differ over small (<10 m) distances. Next, I leveraged the relative simplicity of ephemeral streams of the McMurdo Dry Valleys (MDVs), Antarctica, to isolate stream corridor processes that influence the fate of N. Through intensive field sampling campaigns, I found that the hyporheic zone can be a persistent source of N even in this low nutrient environment. Next, I combined historic sample data and remote sensing analysis to estimate how much N is stored in an MDV stream corridor. My results indicate that up to 104 times more N is stored in this system than is exported each year, with most of this storage in the shallow (< 10 cm) hyporheic zone. Lastly, I examined 25 years of data for 10 streams to assess how stream corridor processes control concentration-discharge relationships. I found that in the absence of hillslope connectivity, stream corridor processes alone can maintain chemostasis – relatively small concentrations changes with large fluctuations in streamflow – of both geogenic solutes and nutrients. My analysis also revealed that solutes subject to control by biological processes exhibit more variability within chemostatic relationships than weathering solutes.

Altogether, this research advances characterization of processes that are difficult to measure or are often overlooked in typical studies of temperate stream corridors. These studies provide insight into the surprising ways in which N is mobilized, transformed, and retained due to stream corridor connectivity in intermittent stream systems with few N inputs.

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Abstract

The Chukchi Sea is a key region for shipping and other growing economic activities in the Arctic. Seasonal sea ice conditions in the Chukchi Sea are strongly determined by the oceanic heat transport into the Chukchi Sea from the north Pacific Ocean via the Bering Strait (see Chapter 1). In Chapter 2, we statistically model Bering Strait heat transports and then use these models to forecast sea ice retreat and advance dates in the Chukchi Sea. In Chapter 3, we further investigate the interannual variability of spring Bering Strait water temperatures. We find that June Bering Strait water temperatures are set upstream the preceding autumn and winter by ocean temperatures in the southwestern Bering Sea shelf, and then advected by the Anadyr current towards the Bering Strait. In Chapter 4, this research is summarized and avenues for future work are discussed.

Abstract

The impacts of anthropogenic climate change, including sea-level rise, warming temperatures, and ocean deoxygenation, are expected to significantly alter marine and terrestrial ecosystems, though the exact nature of future changes are not well constrained. Intervals in Earth history that have experienced similar conditions, such as the Cretaceous Oceanic Anoxic Event 2 (OAE2; ~94 Ma), can serve as case studies for investigating the responses of global biogeochemistry to carbon cycle perturbations, sea-level rise, and expanded and intensified ocean anoxia.

A rock core from southern Utah (SH#1 core) presents an expanded sedimentary record of OAE2 from the western margin of the Western Interior Seaway that contains abundant organic matter derived from marine and terrestrial environments. In this dissertation, we developed and established several analytical organic chemical methods to characterize lipid biomarkers in the SH#1 core as a means of investigating biogeochemical responses to global climate change during OAE2. Results indicate that sea-level rise and CO2 input drove increased marine productivity, alterations in marine ecology, and expanded and intensified ocean deoxygenation. Ocean anoxia was persistent in bottom waters, and periods of severe anoxia, including euxinia in the upper water column, occurred throughout the event. Bacterial and algal populations were altered in response to sea-level changes, ocean deoxygenation, and increased productivity, with the frequent appearance of green sulfur bacteria, methanotrophic bacteria, and several periodic changes in dominant algal groups. Records of biomarkers produced by forest fires show an increase in the frequency of forest fires during OAE2, likely due to increased atmospheric oxygen from widespread marine organic carbon burial at the onset of the event. Biomarkers and carbon isotope mass balance equations indicate that forest fires may have been part of a global-scale positive feedback between terrestrial nutrient input to the oceans, marine productivity, ocean anoxia, and marine organic carbon burial. 

Results from carbon isotope analyses of individual marine and terrestrial biomarkers provide constraints on the carbon cycle during OAE2, including a high resolution atmospheric pCO2 record, and estimates of the isotopic composition of oceanic dissolved inorganic carbon and atmospheric CO2. Nitrogen isotopic analyses of bulk organic matter in the SH#1 core and another core from the southern Western Interior Seaway indicate that nitrogen cycling was sensitive to changes in water column deoxygenation and sea level, and varied across oceanographic settings. Results from ongoing porphyrin-specific nitrogen isotope analyses will inform isotope mixing models to decipher dominant sedimentary organic nitrogen sources and nitrogen transformation in anoxic oceans. This dissertation elucidates the nature of ecosystem responses to global environmental change, which can provide a historical context for understanding anthropogenic climate change, and inform projections for future changes in ocean circulation, chemistry, biology, and carbon burial.

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Abstract

Primary producing algae form the basis of carbon fixation, oxygen production, and food webs in aquatic ecosystems globally. However, human activities disrupt climate and freshwater physicochemistry. These impacts alter the health of algal communities and the ecosystem services algae provide. Meanwhile, spatial processes like dispersal and landscape characteristics like geology also influence algal structure and function. Diatoms are indicators of stream health and are model organisms for understanding the processes underlying microbial biogeography. Benthic cyanobacteria present risks to human health through the proliferation of toxin-producing blooms. With this dissertation, I investigate the ecosystem processes that influence diatom and cyanobacterial community composition and taxon distributions. My goal is to advance the understanding of ecosystem controls on algal biogeography and to characterize taxon-specific autecology for use in environmental management. First, I measured the extent of wind-mediated dispersal of benthic diatoms across aquatic habitats to better understand how community composition is structured by spatial processes across the McMurdo Dry Valleys polar desert in Antarctica. I found that inter-habitat dispersal is common but less influential on community composition than intra-habitat factors such as environmental conditions. I then used non-linear, multivariable modeling to assess the relative influences of climate, watershed characteristics, and in-stream stressors on the relative abundances of 268 diatom taxa across gradients of human impact in the northeast United States. My results indicate diatom taxa are affected by different suites of environmental conditions but that taxa belong to ecological guilds based on shared responsiveness to environmental factors. Finally, I applied multivariable modeling towards understanding the effects of aquatic stressors, including herbicides and persistent organic pollutants, on the distributions of benthic cyanobacteria across northeast U.S. streams. I found that watershed characteristics, streamflow, and herbicides were more influential than light availability, water temperature, and nutrients on the distributions of potentially toxigenic cyanobacterial genera. Collectively, this research expands the knowledge of how benthic algal communities and taxon distributions are structured at large spatial scales along gradients of unimpacted and human-altered environmental conditions. I provide a novel modeling framework and taxon-specific autecological information that can be applied to environmental assessments of stream health and future algal research.

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Abstract

A deep-water aerial sampling technique has been designed and implemented for sampling pit lakes, which are dangerous water bodies for boats to approach. The approach involves an unmanned aerial vehicle (UAV) hexacopter, DJI Matrice 600, that can attach a 1.2L Niskin sample bottle or conductivity, temperature, and depth profiler. The bottom attachment on the UAV consists of two servo motors that allow the detachment of a 1 kg messenger that triggers a 1.2L Niskin bottle shut and provides an emergency payload release. We first tested this technology on September 20, 2016 and obtained a conductivity, temperature and depth (CTD) profile of Dillon Reservoir and then collected a water sample from 25 m depth. The CTD profile showed a possible layer of water originating from an inflow stream, the Snake River, which has high particulate and dissolved metals from acid rock drainage. In addition, this UAV deep-water sampling approach has been tested at seven pit lakes from 2016 – 2017, the deepest sample retrieved was 80 meters, and is seen to be an effective method of water sampling at depth. It is important to gain an understanding of water-quality conditions to determine the extent to which pit lakes are effecting the environment. The water-quality characteristics of pit lakes also provide a better understanding of remediation requirements. This methodology of sampling with a heavy lifting drone is seen to be an effective approach to sampling dangerous water bodies and a municipality’s water supply. The benefits and field considerations of a UAV water sampler include improved safety, reduced sampling costs, and improved efficiency.

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Abstract

Nearly 80% of the United States’ freshwater originates in forested landscapes at risk of wildfires, which influence both the terrestrial landscape and hydrologic regime by introducing a heterogeneous spectrum of thermally altered carbon compounds, known as pyrogenic carbon (PyC). Given the projected increase in both wildfire frequency and intensity, understanding the coupling of hydrologic transport and chemical fractionation that wildfires impose on water sources is critical. New research has begun to show that PyC can be quite mobile and reactive with turnover time of decades or years in soils rather than previously assumed millennia timescales, emphasizing the importance of dissolved PyC (DPyC) translocation from soils to rivers. While riverine PyC transport has been identified as a key component of the global PyC cycle, the extent to which photodegradation contributes to both short-term and long-term DPyC chemical fraction has yet to be resolved. This research investigates the role of photodegradation as a major driver altering aquatic DPyC physical and chemical properties using fluorescence spectroscopy. Artificial PyC was created by burning organic matter at various temperatures to isolate distinct portions of the PyC spectrum. The organic matter, comprised of leaves and soils, was collected from Great Smoky Mountain National Park. Each temperature range of the PyC spectrum was separately leached, filtered, and the dissolved fraction was placed outside and exposed to natural sunlight for various exposure times ranging from zero to 28 days. This photodegradation experiment took place in Boulder, Colorado during the summer months to maximize daily sun exposure. Photochemistry was confirmed by monitoring the photochemical formation of hydrogen peroxide via constant wavelength fluorescence spectroscopy. The dissolved organic matter was characterized using ultraviolet-visible absorption and excitation- emission matrix fluorescence spectroscopy. By isolating distinct portions of the PyC spectrum, we will better be able to anticipate the fate of PyC in watersheds effected by wildfires.

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Abstract

Dissolved oxygen (DO) concentrations in rivers are critical for aquatic habitat and controlled by biological generation and uptake, and physical factors. One important physical factor is hydrology: not only streamflow dynamics (changing amounts of water), but also changes in surface-groundwater exchanges. Over a period of 15 months in East River, Colorado from August 2017 (a somewhat "average" flow year) to October 2018 (a low flow year), high frequency (5 minute) DO and temperature data were collected in the water column of the river and directly in the streambed at depths of 10 cm, 20 cm, and 35 cm. Using the VFLUX2 model, temperature data were used to estimate vertical upwelling and downwelling vertical fluxes of water. We find that there was downwelling throughout both years, and increased fluxes into the bed during peak flows. From relating vertical flux to steam discharge and groundwater tables we find that stream discharge is a control of streambed DO during low flow. We calculated DO removal from the channel to the bed, finding enhanced removal rates in 2018. We observed an extended hyporheic anoxic period throughout the summer and fall of 2018 due to increased DO removal rates. The three subsurface locations were found to not all be on the same flow path, which may account for some of the DO differences in 2017 while increased removal due to low flow conditions are the primary factor in 2018. This research has advanced our understanding of the dependence of DO in both the streambed and open channel on stream-groundwater exchanges by showing periods of stream discharge control on DO dynamics.

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Abstract

In the McMurdo Dry Valleys (MDVs), foehn winds are a principal vector of landscape connectivity that facilitate movement of materials between glaciers, streams, soils, lakes and other parts of the ecosystem. While previous publications show that turbulent, warm and dry foehn winds indirectly relate to an increase in lake level rise via an increase in degree days above freezing (DDAF), the direct quantified impact of foehn winds to streamflow and lake level rise remains unclear. The MDVs are the largest ice-free region of Antarctica, which experience minimal precipitation. Valley bottoms contain permanently ice-covered closed basin lakes filled with meltwater from outlet glaciers via stream channels. In Taylor Valley, several meteorological stations and lake monitoring stations record average measurements of weather conditions and lake conditions on 15 to 20-minute intervals. In this thesis, the meteorological definition of foehn winds is refined and hydrologic response to foehn winds is evaluated. During the austral summer streamflow season (November-February), foehn winds are predicted to increase meltwater generation and closed-basin lake level rise. Past publications have shown that foehn wind events contribute to lake ice sublimation year-round, whereas melt does not typically occur in nonsummer months. Analysis of non-summer lake ice ablation utilizing recent lake stage and ablation data is also explored herein. Although a significant correlation was not found, summer foehn winds appear to promote above average daily lake level rise given sufficient air temperatures. Daily average lake level rise is greater for longer periods (i.e., 4-day average daily rise > 3-day average daily rise, etc.) indicating that there is at least a 4-day post-foehn impact on lake level rise during the summer. Lake ice ablation in non-summer months is shown to have a significant relationship with increasing foehn wind occurrence and wind-run. Because foehn winds are expected to increase with global warming, these hydrologic relationships aid in predicting the future of the McMurdo Dry Valley ecosystem in a warming world.

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Abstract

This thesis aims to assess the validity of bacterial branched glycerol dialkyl glycerol tetraethers (brGDGTs) temperature reconstructions in Arctic lake settings from a Holocene (~11,700 BP) lacustrine sediment core from Baffin Island, Eastern Canadian Arctic. The distribution of brGDGTs in peats, soils, and lake sediments has been shown to correlate with mean annual air temperature (MAAT) and this proxy has been widely applied to sedimentary archives for paleotemperature reconstructions. However, the production and distribution of brGDGTs are impacted by confounding environmental variables that are currently not well understood. Here I study the distribution of brGDGTs preserved in a high-Arctic lake setting and apply the most up-to-date brGDGT-inferred temperature reconstruction calibrations. This thesis specifically investigates the role of changing oxygen levels on reconstructed brGDGT paleotemperatures. Comparisons with other soil and lacustrine samples from Baffin Island suggest that brGDGTs in Upper Gnarly are primarily sourced from within the lake over the Holocene, and estimated temperatures from surface sediments using recently published lake-specific calibrations compare favorably with measured summer air and water temperatures from the region. The downcore reconstruction from Upper Gnarly exhibits a trend opposite of what is expected with a cool Early Holocene followed by warming towards the present. Importantly, two intervals of cooler reconstructed temperatures are observed during intervals of supposed suboxia in the lake. Overall, my results present further evidence that suboxic conditions generate a cold-bias in brGDGT paleotemperature reconstructions, and ultimately need to be considered in future research in paleotemperature reconstruction in high-Arctic lake settings.

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Abstract

Seasonal sea ice transitions dates are under-utilized in evaluating climate model projections of Arctic sea ice loss despite long, pan-Arctic satellite-based observational records of seasonal transition dates. In this thesis, we show how the limitations that have prevented their widespread use can be overcome through the use of large ensembles and a novel sea ice satellite simulator, and how seasonal sea ice transitions dates can benefit model evaluations.

In particular, we quantify the uncertainty related to definition differences and internal variability, allowing us to use seasonal sea ice transitions as process-based metrics to understand model biases in sea ice simulations. In addition, we demonstrate that a sea ice satellite simulator can take model evaluation a step further, providing novel and direct comparisons between satellite observations and model simulations as well as insights into the physical processes captured by sea ice remote sensing algorithms. These direct comparisons enable more accurate climate model assessment and improve the evaluation of seasonal Arctic sea ice transitions in models.

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Abstract

El Nino Southern Oscillation (ENSO) is Earth's largest source of interannual climate variability; however, its future remains difficult to predict. Evaluation of past ENSO may help improve our basic understanding of the phenomenon and help resolve discrepancies among models tasked with simulating future climate. Individual foraminifera analysis (IFA), a tool that allows continuous down-core records of ENSO-related temperature variability through the construction and comparison of paleotemperature distributions, provides an opportunity to extend records of past ENSO beyond the most recent geologic past. However, accurately interpreting ENSO from IFA requires (1) an understanding of how partial dissolution affects temperature distributions derived from individual planktic foraminifera, (2) confirmation that a population of planktic foraminifera is capable of capturing site-specific temperature variability, and when employing down-core, (3) consideration of the complexity of ENSO diversity.

In Chapter 1 of this dissertation, I evaluate how partial dissolution affects the Mg/Ca-temperature proxy. I show that temperatures derived from individual measurements of Mg/Ca in two species of planktic foraminifera, Globigerinoides ruber and Neogloboquadrina dutertrei, support a percent Mg loss model which does not affect the shape or variability of a temperature distribution and is ideal for reconstructing past ENSO. In Chapter 2 of this dissertation, I investigate whether Mg/Ca-based IFA is capable of capturing site-specific temperature variability using nine core-tops across the equatorial Pacific. Using quantile-quantile analysis, I show that individual measurements of Mg/Ca in G. ruber and N. dutertrei reflect site-specific temperature distribution shape and variance when accounting for regional differences in depth habitat of both species of planktic foraminifera. In Chapter 3, this dissertation transitions to investigate ENSO during the Last Glacial Maximum (LGM). I use individual measurements of Mg/Ca in two species of planktic foraminifera, G. ruber and N. dutertrei, from two locations in the eastern equatorial Pacific to show that the center of ENSO activity was farther east during the LGM than during the late Holocene suggesting that ENSO diversity can affect interpretations of IFA records and emphasizing the necessity for multi-site reconstructions.

Abstract

Soils contain the largest pool of terrestrial organic carbon and the organic content of soil is strongly influenced by climate, vegetation, land use, time, and physicochemical properties of the soil. In order to better understand factors that control soil carbon, I seek to understand the mechanisms of stabilization of soil organic matter (SOM) across a diverse range of soil types. To integrate SOM stabilization and vulnerability across different spatial scales, it is important to understand the mechanisms of stabilization and how broad (climate) and fine scale (soil physicochemical properties) controls impact SOM dynamics under climate change conditions. The goals of my research are to (1) develop fluorescence spectroscopy models designed for SOM; (2) understand how the molecular composition of SOM varies as a function of fine and broad scale controls; (3) build a predictive model for SOM composition; and (4) relate metrics of composition between fluorescence spectroscopy and mass spectrometry. Using fluorescence spectroscopy and PARAllel Factor Analysis (PARAFAC), I created a universal 6 component soil model to compare and interpret fluorescence signals. Using sequential extraction methods, I can determine the composition of the SOM that is hydraulically active (non-stabilized) and which fraction loosely held in soils (labile). To understand how the molecular composition of SOM varies across a diverse range of soil types, I will be coupling fluorescence spectroscopy and Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) of soil extracts. Combining environmental factors, physicochemical properties of the soil, vegetation indices, and FT-ICR-MS data I determined that SOM composition in the hydraulically active and labile fraction (water extract) is related to by climate and physio-chemical properties of soil. In the methanol extractable fraction, the SOM composition is related to vegetation indices, and in the chloroform extract was related to soil texture, precipitation, and vegetation. I use this work to gain insight into the interplay between mineralogy, SOM composition, stabilization and vulnerability to changes in broad scale controls.

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Abstract

The intensity, duration, and spatial distribution of frozen soil influences hydrologic flow paths, soil biogeochemistry, and slope geomorphology. In mountain environments, steep topography produces strong gradients in solar insolation, vegetation, and snowpack dynamics that lead to large differences in soil temperature over short distances, suggesting a need for high-resolution, process-based models that quantify the influence of topography. Surface energy balance calculations and a physical snowpack model based on the Utah Energy Balance have been coupled with PFLOTRAN-ICE, a subsurface thermo-hydrologic model that simulates water and energy transport in the subsurface, including freeze-thaw processes. A thermo-hydrologic modeling study is presented against the backdrop of field observations from Gordon Gulch and Niwot Ridge, seasonally snow-covered catchments in the headwaters of the Boulder Creek watershed. Despite a persistent snowpack on the north-facing slope at Gordon Gulch, seasonally frozen ground is more prevalent and persistent there because of low solar insolation and a thin snowpack. The south-facing slope experiences significantly higher incoming solar radiation that prevents the persistence of frozen ground. Representation of the snowpack and surface energy balance significantly improves soil temperature estimates compared to model forcing based on air temperature alone. At Niwot Ridge, deep (>1m depth) frozen soil underlying bare ground impeded groundwater recharge, and shallow frozen ground (<1m depth) beneath seasonal snow limited infiltration. Modeled alpine and subalpine snowcover exerted a positive effect on soil temperatures but did not prevent or eliminate frozen ground completely. Shallow freezing beneath snow-covered ground exerted a much stronger effect on infiltration than shallow freezing beneath bare ground because the soil beneath the snow remained frozen while the snowpack was melting, whereas solar insolation thawed bare patches by the time they received excess snowmelt “run-on”. In projections of seasonally frozen ground, simulations forecast two additional months of unfrozen soils by the end of the 21st century compared to the 1952-1970 time period. A permafrost analysis provides support for the occurrence of permafrost above 3800m and suggests that the deep soil thaw that has taken place over the last several decades is small compared to deep soil thaw that should be expected throughout the current century.

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Abstract

Glaciers are an integral part of polar and alpine landscapes, providing water, inorganic, and organic material subsidies to downstream ecosystems. These subsides regulate downstream temperature, streamflow, and sediment supplies. Warming in high altitude and high latitude environments due to climate change is resulting in rapid and substantial mass loss of glaciers. In order to better predict impacts and future change to glaciers and downstream environments, we endeavor to better understand glacier physical and biogeochemical processes. Glaciers in the McMurdo Dry Valleys (MDVs) of Antarctica are very sensitive to slight changes in the energy balance. Small temperature or solar radiation increases can result in outsize increases in glacier melt, which is the main source of water for the MDV ecosystem. Sediment on the glacier surface is thought to be a key factor driving both melt and biogeochemical cycling on glaciers. This dissertation examines the distribution of sediment on the MDVs glacier surfaces, how it may have driven recent glacier morphological change, and identifies sediment-driven biogeochemical processes on the MDV glaciers. To do so, we carried out field data collection, field- and lab-based nutrient uptake experiments, geospatial analysis, and coupled sediment and energy balance modeling. We find that the glacier surfaces have changed in response to recent warm events by increasing roughness and the density of meltwater channels on the glacier surface. The increase in roughness occurred in already rough areas that serve as collection points for wind- and water-transported sediment. The rough surfaces and sediment have low albedo and can absorb a higher amount of energy, spurring additional melt. The distribution of sediment on the surface and in the top meter of ice is a reflection of patterns of wind deposition and seasonal melt on the glacier. The total amount of sediment in the top meter of ice agrees with previously measured rates of sediment deposition and follows a valley-wide pattern. The depth of the peak sediment concentration in the top meter of ice is a function of the thermal history of the glacier – both summer energy balance and winter sublimation rates. We also find that the biota living in the sediment is capable of removing nutrients from glacier melt water, modulating the amount and form of nutrients delivered to downstream ecosystems. This research clarifies the role of glaciers within the larger MDV ecosystem. It also advances our understanding of surficial glacier melt and biogeochemistry, which can improve predictions of how the functional role of glaciers within their larger ecosystems will evolve due to climate change.

Abstract

Each winter, snow whitens up to a third of the land on Earth, plus the ice-covered tenth of the ocean. In wind-swept areas, this snow collects in shifting bedforms such as ripples, dunes, and waves. These bedforms cover 10-20% of the surface of the Earth, and increase the surface roughness and energy fluxes, but their formation is little understood. Here, I present the first observations of snow bedform movement and growth, drawn from a three-year field study in the Colorado Front Range (Ch. 2). These observations show snow dunes accelerating minute-by-minute in response to gusts; migrating sastrugi stripping a layer of snow; and eroding surfaces organizing into upwind-facing steps. These changes are functions of wind, melt, and time since snowfall (Ch. 3). Flat snow exists but briefly in the Front Range, in gentle winds. After identifying the processes that drive bedform evolution, I developed the first numerical model of snow bedform growth (Ch. 4). The model uses a cellular automaton to simulate saltation, snowfall, and sintering, producing realistic dunes and waves. I discuss model non-dimensionalization, calibration, acceleration, and emulation.Finally, I simulated the growth of snow dunes in a range of wind and snowfall conditions (Ch. 5). The simulated dunes grew tall and widely-separated when winds were strong and snow fell slowly; these trends agreed with field observations. I then quantified the impact of the simulated bedforms on radiative and conductive heat transfer. Snow dune and wave growth likely increase heat fluxes through snow in most of the polar regions - sea ice, tundra, the Greenland and Antarctic ice sheets - by up to 94%

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Abstract

The humid tropics are undergoing land use and climate change at a rate which outpaces many other parts of the world. Despite this, the impacts of these environmental changes to many hydrological and biogeochemical processes remain poorly understood. To address outstanding knowledge gaps limiting our ability to anticipate how future changes will impact water resources in these regions, this dissertation investigated hydrological and biogeochemical processes across a gradient of tropical land covers in central Panama. By analyzing relationships between stream chemistry and physical hydrological processes in three catchments of varying land cover (mature forest, young secondary tropical forest, and cattle pasture), several outstanding questions in tropical hydrology and biogeochemistry were addressed.

A combination of geochemical mixing models was used to identify dominant hydrologic flowpaths in each catchment, and the hydrologic conditions under which they became active. Pasture land cover produced infiltration excess overland flow during large wet season storm events, resulting in massive exports of event water to streams and comparatively higher new- runoff efficiencies. Contrarily, lateral subsurface flow through macropores in the upper 30cm of the soil column was the dominant hydrologic flowpath in the forested catchments, producing lower new-water runoff efficiencies and allowing for greater vertical connectivity in the soil column. The activation of these flowpaths in each catchment were found to be driven by the exceedance of rainfall magnitude and intensity thresholds, which varied according to land cover. Differences in flowpaths between the catchments produced differences in seasonal runoff dynamics between them, with the forested catchments producing only a fraction of the total new-water driven runoff produced by pasture.

To study how hydrological and biological differences between the catchments impacts biogeochemical processes like weathering and nutrient cycling, concentrations-runoff relationships and exports of eight major solutes were quantified and compared between the catchments. Despite a large disparity in total runoff production between the different land covers, their export of bedrock and atmospherically derived solutes was largely the same. The catchments produced differing loads of biologically active solutes and nutrients, a function of both differences in their biota and in the hydrologic flowpaths connecting these solutes to the stream.