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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Modeling the mechanisms of conifer mortality under seawater exposure

Summary Relative sea level rise (SLR) increasingly impacts coastal ecosystems through the formation of ghost forests. To predict the future of coastal ecosystems under SLR and changing climate, it is important to understand the physiological mechanisms underlying coastal tree mortality and to integrate this knowledge into dynamic vegetation models. We incorporate the physiological effect of salinity and hypoxia in a dynamic vegetation model in the Earth system land model, and used the model to investigate the mechanisms of mortality of conifer forests on the west and east coast sites of USA, where trees experience different form of sea water exposure. Simulations suggest similar physiological mechanisms can result in different mortality patterns. At the east coast site that experienced severe increases in seawater exposure, trees loose photosynthetic capacity and roots rapidly, and both storage carbon and hydraulic conductance decrease significantly within a year. Over time, further consumption of storage carbon that leads to carbon starvation dominates mortality. At the west coast site that gradually exposed to seawater through SLR, hydraulic failure dominates mortality because root loss impacts on conductance are greater than the degree of storage carbon depletion. Measurements and modeling focused on understanding the physiological mechanisms of mortality is critical to reducing predictive uncertainty.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Engineered Production of Hydroxycinnamoyl Tyramine Conjugates Limits the Growth of the Pathogen Pseudomonas syringae in Arabidopsis

Hydroxycinnamoyl tyramine conjugates are phenolamides produced by plants in response to pathogen attack and biotic stresses. Their proposed mechanisms of action include cytotoxicity towards pathogens, cell wall reinforcement to restrict pathogen proliferation, and signaling activity to trigger general stress responses. Here, we engineered the production of the tyramine conjugates p-coumaroyltyramine (CT) and feruloyltyramine (FT) in Arabidopsis to gain insight into their mode of action. Co-expression of feedback-insensitive 3-deoxy-D-arabino-heptulosonate 7-phosphate synthase and tyrosine decarboxylase increased tyramine content. Additional expression of tyramine hydroxycinnamoyltransferase led to de-novo production of CT and FT, which were found as soluble and cell-wall-bound forms. FT was associated with lignin in stems. The growth of pathogenic Pseudomonas syringae was reduced in rosettes of the Arabidopsis CT- and FT-producing lines compared to wild type. These lines also exhibited increased transpirational water loss in excised rosettes. Transcriptomic analysis of transgenic lines grown under normal conditions revealed alterations in the expression of genes associated with the biological circadian clock. These changes led to a reduction in flavonoids and an early flowering phenotype. Important changes in the expression of genes related to abiotic stress such as drought, cold, heat, and hypoxia potentially contribute to reduced growth of P. syringae in engineered Arabidopsis.

Phenolamides↗
DOE OSTI2025

The mevalonate pathway of isoprenoid biosynthesis supports metabolic flexibility in Mycobacterium marinum

ABSTRACT Isoprenoids are a diverse class of natural products that are essential in all domains of life. Most bacteria synthesize isoprenoids through either the methylerythritol phosphate (MEP) pathway or the mevalonate (MEV) pathway, while a small subset encodes both pathways, including the pathogen Mycobacterium marinum (Mm). It is unclear whether the MEV pathway is functional in Mm, or why Mm encodes seemingly redundant metabolic pathways. Here, we show that the MEP pathway is essential in Mm, while the MEV pathway is dispensable in culture, with the ΔMEV mutant having no growth defect in axenic culture but a competitive growth defect compared to WT Mm. We found that the MEV pathway does not play a role in ex vivo or in vivo acute infection but does play a role in survival of peroxide stress. Metabolite profiling revealed that modulation of the MEV pathway causes compensatory changes in the concentration of MEP intermediates DOXP and CDP-ME, suggesting that the MEV pathway is functional and that the pathways interact at the metabolic level. Finally, the MEV pathway is upregulated early in the shift down to hypoxia, suggesting that it may provide metabolic flexibility to this bacterium. Interestingly, we found that our complemented strains, which vary in copy number of the polyprenyl synthetase idsB2 , responded differently to peroxide and UV stresses, suggesting a role for this gene as a determinant of downstream prenyl phosphate metabolism. Together, these findings suggest that MEV may serve as an anaplerotic pathway to make isoprenoids under stress conditions. IMPORTANCE Organisms from all domains of life utilize isoprenoids to carry out thousands of critical and auxiliary cellular processes, including signaling, maintaining membrane integrity, stress response, and host-pathogen interactions. The common precursor of all isoprenoids is synthesized via one of two biosynthetic pathways. Importantly, some bacteria encode both pathways, including M. marinum . We found that only one pathway is essential in M. marinum , while the nonessential pathway may confer metabolic flexibility to help the bacterium better adapt to various environmental conditions. We also found that the polyprenyl synthetase IdsB2 plays an important role in driving such phenotypes. Further, we demonstrate metabolic interplay between both functional pathways. These insights represent the first characterization of isoprenoid biosynthesis in dual pathway-encoding mycobacteria.

Qabar, Christine M. [Department of Plant and Micro↗
DOE OSTI2024

Feedbacks Regulating the Salinization of Coastal Landscapes

The impact of saltwater intrusion on coastal forests and farmland is typically understood as sea-level-driven inundation of a static terrestrial landscape, where ecosystems neither adapt to nor influence saltwater intrusion. Yet recent observations of tree mortality and reduced crop yields have inspired new process-based research into the hydrologic, geomorphic, biotic, and anthropogenic mechanisms involved. We review several negative feedbacks that help stabilize ecosystems in the early stages of salinity stress (e.g., reduced water use and resource competition in surviving trees, soil accretion, and farmland management). However, processes that reduce salinity are often accompanied by increases in hypoxia and other changes that may amplify saltwater intrusion and vegetation shifts after a threshold is exceeded (e.g., subsidence following tree root mortality). This conceptual framework helps explain observed rates of vegetation change that are less than predicted for a static landscape while recognizing the inevitability of large-scale change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Exosomes From Induced Pluripotent Stem Cell–Derived Cardiomyocytes Promote Autophagy for Myocardial Repair

Background. Induced pluripotent stem cells and their differentiated cardiomyocytes (iCMs) have tremendous potential as patient-specific therapy for ischemic cardiomyopathy following myocardial infarctions, but difficulties in viable transplantation limit clinical translation. Exosomes secreted from iCMs (iCM-Ex) can be robustly collected in vitro and injected in lieu of live iCMs as a cell-free therapy for myocardial infarction. Methods and Results. iCM-Ex were precipitated from iCM supernatant and characterized by protein marker expression, nanoparticle tracking analysis, and functionalized nanogold transmission electron microscopy. iCM-Ex were then used in in vitro and in vivo models of ischemic injuries. Cardiac function in vivo was evaluated by left ventricular ejection fraction and myocardial viability measurements by magnetic resonance imaging. Cardioprotective mechanisms were studied by JC-1 (tetraethylbenzimidazolylcarbocyanine iodide) assay, immunohistochemistry, quantitative real-time polymerase chain reaction, transmission electron microscopy, and immunoblotting. iCM-Ex measured ≈140 nm and expressed CD63 and CD9. iCM and iCM-Ex microRNA profiles had significant overlap, indicating that exosomal content was reflective of the parent cell. Mice treated with iCM-Ex demonstrated significant cardiac improvement post–myocardial infarction, with significantly reduced apoptosis and fibrosis. In vitro iCM apoptosis was significantly reduced by hypoxia and exosome biogenesis inhibition and restored by treatment with iCM-Ex or rapamycin. Autophagosome production and autophagy flux was upregulated in iCM-Ex groups in vivo and in vitro. Conclusions. iCM-Ex improve post–myocardial infarction cardiac function by regulating autophagy in hypoxic cardiomyoytes, enabling a cell-free, patient-specific therapy for ischemic cardiomyopathy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Mixing Driven by Critical Reflection of Near-Inertial Waves over the Texas–Louisiana Shelf

Studies of internal wave-driven mixing in the coastal ocean have been focused on internal tides, while wind-driven near-inertial waves (NIWs) have received less attention in this regard. Here, this study demonstrates a scenario of NIW-driven mixing over the Texas–Louisiana shelf. Supported by a high-resolution simulation over the shelf, the NIWs driven by land–sea breeze radiate downward at a sharp front and enhance the mixing in the bottom boundary layer where the NIWs are focused because of slantwise critical reflection. The criterion for slantwise critical reflection of NIWs is ω=$\sqrt{f{^2}+s^{2}_{bot}N{^2}(1-s_{ρ}/s_{bot})}$ (where ω is the wave frequency, s bot is the bottom slope, and s ρ is the isopycnal slope), under the assumption that the mean flow is in a thermal wind balance and only varies in the slope-normal direction. The mechanism driving the enhanced mixing is explored in an idealized simulation. During slantwise critical reflection, NIWs are amplified with enhanced shear and periodically destratify a bottom boundary layer via differential buoyancy advection, leading to periodically enhanced mixing. Turbulent transport of tracers is also enhanced during slantwise critical reflection of NIWs, which has implications for bottom hypoxia over the Texas–Louisiana shelf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Sulfur Species in Zinc-Rich Condylar Zones of a Rat Temporomandibular Joint

We performed synchrotron-based micro-X-ray absorption near-edge spectroscopy (µ-XANES) coupled with micro-X-ray fluorescence (µ-XRF) for the identification of elements that included biometal zinc (Zn) and nonmetal sulfur (S) (and its species) in the condylar zones of a rat temporomandibular joint (TMJ). Zone-specific spatial localization of biometal Zn and nonmetal S from a materials viewpoint when correlated with hypoxia inducible factor-1α (HIF-1α) (a surrogate for tissue oxygenation) can provide insights into Zn-specific redox pathways at the vulnerable subchondral interface. Histologic localization of Zn, HIF-1α, and sulfur-rich proteoglycans (PGs) were mapped using an optical microscope. The µ-XRF maps coupled with site-specific micro-X-ray diffraction (µ-XRD) patterns were used to underline Zn-incorporated biological apatite in the subchondral bone and the bone of a rat TMJ condyle. Results demonstrated an association between Zn, PG, and HIF-1α histologic maps with µ-XRF, µ-XANES, and µ-XRD data and provided insights into plausible biological S species in Zn-enriched zones of a rat TMJ condyle. Spatially localized Zn and S underscore their roles in cell and tissue functions in a zone-specific manner. Elemental Zn with organic and inorganic S species at the cartilage-bone interface and the biomineral phase of Zn-enriched biological apatite from subchondral bone to condylar bone were ascertained using µ-XRF-XANES and µ-XRF-XRD. The coupled µ-XRF-XANES in situ complemented with µ-XRF-XRD in situ and immunohistochemistry provided valuable biological insights into zone-specific biological pathways in rat TMJ condyles. Based on these data, we present a workflow to reliably map and correlate S species within Zn-enriched regions of cartilage, bone, and their interface. We suggest the use of this correlative and complementary microspectroscopic spatial information for zone-specific localization of biometal Zn and nonmetal S to gain insights into plausible microanatomy-specific oxidative stress in the TMJ.

apatites↗
DOE OSTI2022

Label-free affinity screening, design and synthesis of inhibitors targeting the Mycobacterium tuberculosis L-alanine dehydrogenase

The ability of Mycobacterium tuberculosis (Mtb) to persist in its host may enable an evolutionary advantage for drug resistant variants to emerge. A potential strategy to prevent persistence and gain drug efficacy is to directly target the activity of enzymes that are crucial for persistence. We present a method for expedited discovery and structure-based design of lead compounds by targeting the hypoxia-associated enzyme L-alanine dehydrogenase (AlaDH). Biochemical and structural analyses of AlaDH confirmed binding of nucleoside derivatives and showed a site adjacent to the nucleoside binding pocket that can confer specificity to putative inhibitors. Using a combination of dye-ligand affinity chromatography, enzyme kinetics and protein crystallographic studies, we show the development and validation of drug prototypes. Crystal structures of AlaDH-inhibitor complexes with variations at the N6 position of the adenyl-moiety of the inhibitor provide insight into the molecular basis for the specificity of these compounds. We describe a drug-designing pipeline that aims to block Mtb to proliferate upon re-oxygenation by specifically blocking NAD accessibility to AlaDH. The collective approach to drug discovery was further evaluated through in silico analyses providing additional insight into an efficient drug development strategy that can be further assessed with the incorporation of in vivo studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Saturated Bioenergy Buffers: Site Suitability Classification and Estimated Areas of Candidate Sites in the U.S. Midwest Under Three Scenarios

The loss of nutrients applied to tile-drained row-crop fields is a critically important component of agriculture’s impact on surface water quality, because drain tiles provide a short circuit to ditches and creeks, resulting in rapid nutrient loss. This nutrient loss ultimately advances eutrophication and hypoxia, i.e., the creation of dead zones in bodies of water, both locally and regionally (for example, in western Lake Erie and the Gulf of Mexico). Saturated buffers help address the tile-drainage water quality problem, and incorporating bioenergy crops into saturated bioenergy buffers could provide both environmental protection and an additional source of income for farmers.

09 BIOMASS FUELS↗
DOE OSTI2020

Integrated Hydro-Terrestrial Modeling: Development of a National Capability

Water is one of our most important natural resources and is essential to our national economy and security. Multiple federal government agencies have mission elements that address national needs related to water. Each water-related agency champions a unique science and/or operational mission focused on advancing a portion of the nation’s ability to meet our water-related challenges. These diverse mission needs have engendered a rich and extensive base of water-related data and modeling capabilities. While useful for their intended purposes, these capabilities are not well integrated to address complex regional problems and overarching national problems. These major investments by a number of federal agencies, however, lay the foundation for an integrated hydro-terrestrial modeling and data infrastructure that will enhance knowledge, understanding, prediction, and management of the nation’s diverse water challenges. Creating a more seamless national hydro-terrestrial modeling and data capacity presents an enormous opportunity to advance operational as well as research capabilities leading to more effective water management. Advances are necessary not only in operational tools for forecasting but also in research to identify and resolve knowledge and data gaps that lead to unacceptable uncertainties in forecast outcomes. As such, close coordination across scientific, operational, and resource management communities is required. To this end, an interagency workshop on “Integrated Hydro-Terrestrial Modeling: Development of a National Capacity” was held at the National Science Foundation (NSF) headquarters in Alexandria, Virginia in September 2019, led jointly by the NSF, the U.S. Department of Energy (DOE) and the U.S. Geological Survey (USGS) and with broader interagency support provided through an interagency steering committee. This workshop provided a venue to bring together representatives of water-related agencies and their scientific partners (including university researchers) to initiate and refine a vision for a national Integrated Hydro-Terrestrial Modeling (IHTM) and data infrastructure and advance ideas towards its development. The workshop was designed to address three critical foci to advance the development of a national IHTM capacity: “Priority Water Challenges” around which to motivate and initiate development; Technical and methodological obstacles related to data and modeling; Organizational, structural, and cultural barriers that heretofore have impeded integration of capabilities across the federal and research landscapes. The following “Priority Water Challenge” domain areas represent targets for initiating development of the IHTM and were identified and selected in alignment with priorities of the administration’s Water Sub-Cabinet: (1) Nutrient loading, hypoxia, and harmful algal blooms; (2) Water availability in the western United States; and (3) Extreme weather-related water hazards. These water challenges span agency mission boundaries and encompass a broad range of geographies, complex system dynamics and feedbacks, and critical processes spanning hydrological, climatic, and biophysical systems as well as land-use/land-cover, agricultural, built infrastructure, societal, economic, and decisional environments. These three Priority Water Challenges cannot be fully addressed without leveraging complementary and synergistic capabilities across multiple agencies.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Scaling Global Warming Impacts on Ocean Ecosystems: Lessons From a Suite of Earth System Models

An important technique used by climate modelers to isolate the impacts of increasing greenhouse gasses on Earth System processes is to simulate the impact of an abrupt increase in carbon dioxide. The spatial pattern of change provides a “fingerprint” that is generally much larger than natural variability. Insofar as the response to radiative forcing is linear (the impact of quadrupling CO 2 is twice the impact of doubling CO 2 ) this fingerprint can then be used to estimate the impact of historical greenhouse gas forcing. However, the degree to which biogeochemical cycles respond linearly to radiative forcing has rarely been tested. In this paper, we evaluate which ocean biogeochemical fields are likely to respond linearly to changing radiative forcing, which ones do not, and where linearity breaks down. We also demonstrate that the representation of lateral mixing by mesoscale eddies, which varies significantly across climate models, plays an important role in modulating the breakdown of linearity. Globally integrated surface rates of biogeochemical cycling (primary productivity, particulate export) respond in a relatively linear fashion and are only moderately sensitive to mixing. By contrast, the habitability of the interior ocean (as determined by hypoxia and calcite supersaturation) behaves non-linearly and is very sensitive to mixing. This is because the deep ocean, as well as certain regions in the surface ocean, are very sensitive to the magnitude of deep wintertime convection. The cessation of convection under global warming is strongly modulated by the representation of eddy mixing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Long-term warming modulates diversity, vertical structuring of microbial communities, and sulfate reduction in coastal Baltic Sea sediments

Coastal waters such as those found in the Baltic Sea already suffer from anthropogenic related problems including increased algal blooming and hypoxia while ongoing and future climate change will likely worsen these effects. Microbial communities in sediments play a crucial role in the marine energy- and nutrient cycling, and how they are affected by climate change and shape the environment in the future is of great interest. The aims of this study were to investigate potential effects of prolonged warming on microbial community composition and nutrient cycling including sulfate reduction in surface (∼0.5 cm) to deeper sediments (∼ 24 cm). To investigate this, 16S rRNA gene amplicon sequencing was performed, and sulfate concentrations were measured and compared between sediments in a heated bay (which has been used as a cooling water outlet from a nearby nuclear power plant for approximately 50 years) and a nearby but unaffected control bay. The results showed variation in overall microbial diversity according to sediment depth and higher sulfate flux in the heated bay compared to the control bay. A difference in vertical community structure reflected increased relative abundances of sulfur oxidizing- and sulfate reducing bacteria along with a higher proportion of archaea, such as Bathyarchaeota, in the heated compared to the control bay. This was particularly evident closer to the sediment surface, indicating a compression of geochemical zones in the heated bay. These results corroborate findings in previous studies and additionally point to an amplified effect of prolonged warming deeper in the sediment, which could result in elevated concentrations of toxic compounds and greenhouse gases closer to the sediment surface.

16S rRNA gene amplicon↗
DOE OSTI2022

Pathophysiological Integration of Metabolic Reprogramming in Breast Cancer

Metabolic changes that facilitate tumor growth are one of the hallmarks of cancer. The triggers of these metabolic changes are located in the tumor parenchymal cells, where oncogenic mutations induce an imperative need to proliferate and cause tumor initiation and progression. Cancer cells undergo significant metabolic reorganization during disease progression that is tailored to their energy demands and fluctuating environmental conditions. Oxidative stress plays an essential role as a trigger under such conditions. These metabolic changes are the consequence of the interaction between tumor cells and stromal myofibroblasts. The metabolic changes in tumor cells include protein anabolism and the synthesis of cell membranes and nucleic acids, which all facilitate cell proliferation. They are linked to catabolism and autophagy in stromal myofibroblasts, causing the release of nutrients for the cells of the tumor parenchyma. Metabolic changes lead to an interstitium deficient in nutrients, such as glucose and amino acids, and acidification by lactic acid. Together with hypoxia, they produce functional changes in other cells of the tumor stroma, such as many immune subpopulations and endothelial cells, which lead to tumor growth. Thus, immune cells favor tissue growth through changes in immunosuppression. This review considers some of the metabolic changes described in breast cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Structuring Nutrient Yields throughout Mississippi/Atchafalaya River Basin Using Machine Learning Approaches

To minimize the eutrophication pressure along the Gulf of Mexico or reduce the size of the hypoxic zone in the Gulf of Mexico, it is important to understand the underlying temporal and spatial variations and correlations in excess nutrient loads, which are strongly associated with the formation of hypoxia. This study’s objective was to reveal and visualize structures in high-dimensional datasets of nutrient yield distributions throughout the Mississippi/Atchafalaya River Basin (MARB). For this purpose, the annual mean nutrient concentrations were collected from thirty-three US Geological Survey (USGS) water stations scattered in the upper and lower MARB from 1996 to 2020. Eight surface water quality indicators were selected to make comparisons among water stations along the MARB over the past two decades. Principal component analysis (PCA) was used to comprehensively evaluate the nutrient yields across thirty-three USGS monitoring stations and identify the major contributing nutrient loads. The results showed that all samples could be analyzed using two main components, which accounted for 81.6% of the total variance. The PCA results showed that yields of orthophosphate (OP), silica (SI), nitrate–nitrites (NO 3 -NO 2 ), and total suspended sediment (TSS) are major contributors to nutrient yields. It also showed that land-planted crops, density of population, domestic and industrial discharges, and precipitation are fundamental causes of excess nutrient loads in MARB. These factors are of great significance for the excess nutrient load management and pollution control of the Mississippi River. It was found that the average nutrient yields were stable within the sub-MARB area, but the large nitrogen yields in the upper MARB and the large phosphorus yields in the lower MARB were of great concern. t-distributed stochastic neighbor embedding (t-SNE) revealed interesting nonlinear and local structures in nutrient yield distributions. Clustering analysis (CA) showed the detailed development of similarities in the nutrient yield distribution. Moreover, PCA, t-SNE, and CA showed consistent clustering results. This study demonstrated that the integration of dimension reduction techniques, PCA, and t-SNE with CA techniques in machine learning are effective tools for the visualization of the structures of the correlations in high-dimensional datasets of nutrient yields and provide a comprehensive understanding of the correlations in the distributions of nutrient loads across the MARB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Comparison of Machine Learning-Based Predictive Models of the Nutrient Loads Delivered from the Mississippi/Atchafalaya River Basin to the Gulf of Mexico

Predicting nutrient loads is essential to understanding and managing one of the environmental issues faced by the northern Gulf of Mexico hypoxic zone, which poses a severe threat to the Gulf’s healthy ecosystem and economy. The development of hypoxia in the Gulf of Mexico is strongly associated with the eutrophication process initiated by excessive nutrient loads. Due to the complexities in the excessive nutrient loads to the Gulf of Mexico, it is challenging to understand and predict the underlying temporal variation of nutrient loads. The study was aimed at identifying an optimal predictive machine learning model to capture and predict nonlinear behavior of the nutrient loads delivered from the Mississippi/Atchafalaya River Basin (MARB) to the Gulf of Mexico. For this purpose, monthly nutrient loads (N and P) in tons were collected from US Geological Survey (USGS) monitoring station 07373420 from 1980 to 2020. Machine learning models—including autoregressive integrated moving average (ARIMA), gaussian process regression (GPR), single-layer multilayer perceptron (MLP), and a long short-term memory (LSTM) with the single hidden layer—were developed to predict the monthly nutrient loads, and model performances were evaluated by standard assessment metrics—Root Mean Square Error (RMSE) and Correlation Coefficient (R). The residuals of predictive models were examined by the Durbin–Watson statistic. The results showed that MLP and LSTM persistently achieved better accuracy in predicting monthly TN and TP loads compared to GPR and ARIMA. In addition, GPR models achieved slightly better test RMSE score than ARIMA models while their correlation coefficients are much lower than ARIMA models. Moreover, MLP performed slightly better than LSTM in predicting monthly TP loads while LSTM slightly outperformed for TN loads. Furthermore, it was found that the optimizer and number of inputs didn’t show effects on the LSTM performance while they exhibited impacts on MLP outcomes. This study explores the capability of machine learning models to accurately predict nonlinearly fluctuating nutrient loads delivered to the Gulf of Mexico. Further efforts focus on improving the accuracy of forecasting using hybrid models which combine several machine learning models with superior predictive performance for nutrient fluxes throughout the MARB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Uncertainty characterization in a coupled human-natural system: Modeling agricultural adaptation in the Great Lakes Region

The Great Lakes Region's water quality and ecological health are threatened by the export of nutrients from agricultural lands, which causes eutrophication, hypoxia, and destructive algal blooms. The intensification of hydrologic cycles brought about by climate change is expected to exacerbate nutrient loading in the region, and, at the same time, agricultural adaptation to changing conditions is also expected to affect loading through shifting amounts and timing of fertilization. Quantifying these future effects and their interactions necessitates modeling both the human and natural processes as a coupled system, by pairing land use and agricultural management with hydrologic modeling. At the same time, compounding uncertainties arising from the complex interactions in both systems significantly limit our predictive understanding of the region's impacts. This study utilizes the Soil and Water Assessment Tool (SWAT), developed for simulating the impact of various farmer decisions on watershed functions in Western Lake Erie watersheds, and an under-development agent-based model (ABM) for agricultural management decisions. The aim of this study is to use global sensitivity analysis on the coupled ABM and SWAT models to quantify how uncertainty in both models interactively affects nutrient loading. To do so, we will conduct Sobol sensitivity analysis experiments at different levels of coupling assumptions to quantify how various uncertain factors (e.g., soil moisture and crop choice) and their interactions affect our estimates of nutrient loading. The results of this analysis will allow us to quantify how complex interactions and dependencies between both systems amplify the effect of uncertainties. Insights gained from this study will have broader implications for modeling the adaptive co-evolution of human and natural systems under climate change and can inform effective management of nutrient loading in the Great Lakes Region.

Climate Change↗
DOE OSTI2024

Evaluating SWAT + model uncertainties for human and natural outcomes: Application in a Great Lakes agricultural watershed

Nutrient exports from agricultural lands in the Great Lakes Region pose significant threats to water quality and ecological health through eutrophication, hypoxia, and harmful algal blooms. Climate change and agricultural adaptation practices complicate future nutrient loading due to intensified hydrologic cycles and land use decisions. Our research focuses on evaluating the Soil and Water Assessment Tool (SWAT) plus model parametric uncertainties for human and natural outcomes across different scales. These factors are integral to ensuring a balance between productive agricultural practices and maintaining the health of watershed hydrology. However, uncertainties in modeling such complex interactions pose significant challenges, limiting our ability to precisely determine critical factors that influence crop yield and soil moisture. Our analysis employs Sobol global sensitivity analysis to evaluate first-order, second order, and total-order indices for SWAT crop growth parameter, ensuring comprehensive assessment of individual and interactive effects on model outputs. The objective is to identify the parameters that significantly affect model outputs for crop yield and soil moisture and improve our understanding of their interactions at the basin and hydrological response unit (HRU) scale. Our case study, the Portage River Watershed, which drains into Lake Erie, is chosen to better capture finer scale interactions crucial for predicting nutrient loading under future climate scenarios. This foundational work is aimed at setting the stage for the future development of an agent-based model (ABM). The ABM model would incorporate SWAT outputs to dynamically simulate decision-making processes.

Bunyon, Enock↗
DOE OSTI2021

Climate-driven deoxygenation elevates fishing vulnerability for the ocean's widest ranging shark

Climate-driven expansions of ocean hypoxic zones are predicted to concentrate pelagic fish in oxygenated surface layers, but how expanding hypoxia and fisheries will interact to affect threatened pelagic sharks remains unknown. Here, analysis of satellite-tracked blue sharks and environmental modelling in the eastern tropical Atlantic oxygen minimum zone (OMZ) shows shark maximum dive depths decreased due to combined effects of decreasing dissolved oxygen (DO) at depth, high sea surface temperatures, and increased surface-layer net primary production. Multiple factors associated with climate-driven deoxygenation contributed to blue shark vertical habitat compression, potentially increasing their vulnerability to surface fisheries. Greater intensity of longline fishing effort occurred above the OMZ compared to adjacent waters. Higher shark catches were associated with strong DO gradients, suggesting potential aggregation along suitable DO gradients contributed to habitat compression and higher fishing-induced mortality. Fisheries controls to counteract deoxygenation effects on shark catches will be needed as oceans continue warming.

Vedor, Marisa↗