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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Seabird distribution is better predicted by abundance of prey than oceanography. A case study in the Gulf of Cadiz (SW, Iberian Peninsula)

Abstract Quantifying factors that influence marine predator distributions is essential to understanding the current and future change in marine biodiversity. Here, we test whether marine predator distribution relates to prey, or is better predicted by other specific habitat features. We examine the correlation between spatial distribution of three seabird species and their prey, as well as environmental proxies (oceanographic characteristics) in the Gulf of Cadiz, NE Atlantic. We modeled the at-sea distribution of Cory's shearwater, Balearic shearwater and Northern gannet, based on: (i) pelagic fish abundance according to acoustic surveys, and (ii) a forecast-model of remotely sensed environmental variables (productivity, sea surface temperature, and salinity). In general, seabird distributions were better predicted by abundance of fish than by environmental variables at the habitat scale. We obtained consistent correlations between seabird presence and the abundance of medium-sized (10–20 cm) sardines, anchovies and Mediterranean horse mackerel, providing information on their preferred prey. Additionally, oceanographic productivity variables moderately contributed to seabird distribution models, with better predictive value for the critically endangered Balearic shearwater and Northern gannet in the summer, whilst the model for Cory's shearwater's produced poorer predictions. Predator–prey combined studies may represent essential tools for an efficient ecosystem-based management of marine environments.

de la Cruz, Andrés (ORCID:0000000203632498)↗
DOE OSTI2023

Light-independent phytoplankton degradation and detoxification of methylmercury in water

Phytoplankton serves as a key entry point for the trophic transfer and bioaccumulation of the neurotoxin methylmercury (MeHg) in aquatic food webs. However, it is unclear whether and how phytoplankton itself may degrade and metabolize MeHg in the dark. Here, using several strains of the freshwater alga Chlorella vulgaris, the marine diatom Chaetoceros gracilis and two cyanobacteria (or blue-green algae), we report a light-independent pathway of MeHg degradation in water by phytoplankton, rather than its associated bacteria. About 36–85% of MeHg could be degraded intracellularly to inorganic Hg(II) and/or Hg(0) via dark reactions. Furthermore, endogenic reactive oxygen species, particularly singlet oxygen, were identified as the main driver of MeHg demethylation. Given the increasing incidence of algal blooms in lakes and marine systems globally, these findings underscore the potential roles of phytoplankton demethylation and detoxification of MeHg in aquatic ecosystems and call for improved modelling and assessment of MeHg bioaccumulation and environmental risks.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2009

Watershed and Hydrodynamic Modeling for Evaluating the Impact of Land Use Change on Submerged Aquatic Vegetation and Seagrasses in Mobile Bay

There is a continued need to understand how human activities along the northern Gulf of Mexico coast are impacting the natural ecosystems. The gulf coast is experiencing rapid population growth and associated land cover/land use change. Mobile Bay, AL is a designated pilot region of the Gulf of Mexico Alliance (GOMA) and is the focus area of many current NASA and NOAA studies, for example. This is a critical region, both ecologically and economically to the entire United States because it has the fourth largest freshwater inflow in the continental USA, is a vital nursery habitat for commercially and recreational important fisheries, and houses a working waterfront and port that is expanding. Watershed and hydrodynamic modeling has been performed for Mobile Bay to evaluate the impact of land use change in Mobile and Baldwin counties on the aquatic ecosystem. Watershed modeling using the Loading Simulation Package in C++ (LSPC) was performed for all watersheds contiguous to Mobile Bay for land use Scenarios in 1948, 1992, 2001, and 2030. The Prescott Spatial Growth Model was used to project the 2030 land use scenario based on observed trends. All land use scenarios were developed to a common land classification system developed by merging the 1992 and 2001 National Land Cover Data (NLCD). The LSPC model output provides changes in flow, temperature, sediments and general water quality for 22 discharge points into the Bay. These results were inputted in the Environmental Fluid Dynamics Computer Code (EFDC) hydrodynamic model to generate data on changes in temperature, salinity, and sediment concentrations on a grid with four vertical profiles throughout the Bay s aquatic ecosystems. The models were calibrated using in-situ data collected at sampling stations in and around Mobile bay. This phase of the project has focused on sediment modeling because of its significant influence on light attenuation which is a critical factor in the health of submerged aquatic vegetation. The impact of land use change on sediment concentrations was evaluated by analyzing the LSPC and EFDC sediment simulations for the four land use scenarios. Such analysis was also performed for storm and non-storm periods. In- situ data of total suspended sediments (TSS) and light attenuation were used to develop a regression model to estimate light attenuation from TSS. This regression model was used to derive marine light attenuation estimates throughout Mobile bay using the EFDC TSS outputs. The changes in sediment concentrations and associated impact on light attenuation in the aquatic ecosystem were used to perform an ecological analysis to evaluate the impact on seagreasses and Submerged Aquatic Vegetation (SAV) habitat. This is the key product benefiting the Mobile Bay coastal environmental managers that integrates the influences of sediments due to land use driven flow changes with the restoration potential of SAVs.

Estes, Maurice G.↗
NASA NTRS1988

Carbon recycling in materially closed ecological life support systems

Results of studies are presented of materially closed energetically open microbial ecosystems or 'closed ecosystems'. These are natural marine ecosystems that have been sealed in glass containers to prevent material exchange with the environment but allow energy to pass freely through them. They represent model life support systems for the future human habitation of space. The results are discussed analytically and indicate that these ecosystems, when subjected to a constant energy flux, seem to be reliable and self-sufficient systems for recycling of biologically produced carbon compounds.

Obenhuber, D. C.↗
NASA NTRS2001

Impacts of Interannual Climate Variability on Agricultural and Marine Ecosystems

The El Nino - Southern Oscillation (ENSO) is the dominant mode of global interannual climate variability, and seems to be the only mode for which current prediction methods are more skillful than climatology or persistence. The Zebiak and Cane intermediate coupled ocean-atmosphere model has been in use for ENSO prediction for more than a decade, with notable success. However, the sole dependence of its original initialization scheme and the improved initialization on wind fields derived from merchant ship observations proved to be a liability during 1997/1998 El Nino event: the deficiencies of wind observations prevented the oceanic component of the model from reaching the realistic state during the year prior to the event, and the forecast failed. Our work on the project was concentrated on the use of satellite data for improving various stages of ENSO prediction technology: model initialization, bias correction, and data assimilation. Close collaboration with other teams of the IDS project was maintained throughout.

Cane, M. A.↗
NASA NTRS1976

Assessment of the impact of increased solar ultraviolet radiation upon marine ecosystems

Data was provided to assess the potential impact upon marine ecosystems if space shuttle operations contribute to a reduction of the stratospheric ozone layer. The potential for irreversible damage to the productivity, structure and/or functioning of a model estuarine ecosystem by increased UV-B radiation was established. The sensitivity of key community components (the primary producers) to increased UV-B radiation was delineated.

Vandyke, H.↗
DOE OSTI2025

Phage resistance mutations in a marine bacterium impact biogeochemically relevant cellular processes

Phage–bacteria interactions shape ecology and biogeochemistry across biomes. Resistance, arising from their evolutionary arms race, is well documented for receptor mutations, but other resistance mechanisms and their ecological implications remain unexplored. Here we isolated, sequenced and characterized 13 phage-resistant mutants of marine Cellulophaga baltica (Flavobacteriia). Mechanistically, mutations in surface proteins provided broad and complete extracellular resistance against multiple phages through decreased adsorption. Intracellular mutations affecting serine, glycine and threonine metabolism produced narrower resistance against a single phage, permitting viral DNA replication, and, in one mutant, were shown to be lipid mediated. Putative ecosystem impacts inferred from in vitro experiments include: (1) altered carbon utilization for all mutants, but especially by surface ones, (2) increased metabolite secretion for one modelled intracellular mutant (including experimentally verified acetate) and (3) increased ‘stickiness’ for all mutants, with surface mutants also sedimenting faster. Our findings highlight new resistance mechanisms and suggest that the phage–host arms race could result in ecosystem-level biogeochemical impacts in marine microorganisms.

Urvoy, Marion [Ohio State University]↗
NASA NTRS2010

A Combined Observational and Modeling Approach to Study Modern Dust Transport from the Patagonia Desert to East Antarctica

The understanding of present atmospheric transport processes from Southern Hemisphere (SH) landmasses to Antarctica can improve the interpretation of stratigraphic data in Antarctic ice cores. In addition, long range transport can deliver key nutrients normally not available to marine ecosystems in the Southern Ocean and may trigger or enhance primary productivity. However, there is a dearth of observational based studies of dust transport in the SH. This work aims to improve current understanding of dust transport in the SH by showing a characterization of two dust events originating in the Patagonia desert (south end of South America). The approach is based on a combined and complementary use of satellite retrievals (detectors MISR, MODIS, GLAS ,POLDER, OMI,), transport model simulation (HYSPLIT) and surface observations near the sources and aerosol measurements in Antarctica (Neumayer and Concordia sites). Satellite imagery and visibility observations confirm dust emission in a stretch of dry lakes along the coast of the Tierra del Fuego (TdF) island (approx.54deg S) and from the shores of the Colihue Huapi lake in Central Patagonia (approx.46deg S) in February 2005. Model simulations initialized by these observations reproduce the timing of an observed increase in dust concentration at the Concordia Station and some of the observed increases in atmospheric aerosol absorption (here used as a dust proxy) in the Neumayer station. The TdF sources were the largest contributors of dust at both sites. The transit times from TdF to the Neumayer and Concordia sites are 6-7 and 9-10 days respectively. Lidar observations and model outputs coincide in placing most of the dust cloud in the boundary layer and suggest significant de- position over the ocean immediately downwind. Boundary layer dust was detected as far as 1800 km from the source and approx.800 km north of the South Georgia Island over the central sub-Antarctic Atlantic Ocean. Although the analysis suggests the presence of dust at approx.1500 km SW of South Africa five days after, the limited capabilities of existing satellite platforms to differentiate between aerosol types do not permit a definitive conclusion. In addition, the model simulations show dust lifting to the free troposphere as it travels south but it could not be confirmed by the satellite observations due to cloudiness. This work demonstrates that complementary information from existing transport models, satellite and surface data can yield a consistent picture of the dust transport from the Patagonia desert to Antarctica. It also illustrates the limitation of using any of these approaches individually to characterize the transport of dust in a heavily cloudy area.

Gasso, S.↗
DOE OSTI2023

Skillful Multi‐Month Predictions of Ecosystem Stressors in the Surface and Subsurface Ocean

Abstract Anthropogenic carbon emissions and associated climate change are driving rapid warming, acidification, and deoxygenation in the ocean, which increasingly stress marine ecosystems. On top of long‐term trends, short term variability of marine stressors can have major implications for marine ecosystems and their management. As such, there is a growing need for predictions of marine ecosystem stressors on monthly, seasonal, and multi‐month timescales. Previous studies have demonstrated the ability to make reliable predictions of the surface ocean physical and biogeochemical state months to years in advance, but few studies have investigated forecast skill of multiple stressors simultaneously or assessed the forecast skill below the surface. Here, we use the Community Earth System Model (CESM) Seasonal to Multiyear Large Ensemble (SMYLE) along with novel observation‐based biogeochemical and physical products to quantify the predictive skill of dissolved inorganic carbon (DIC), dissolved oxygen, and temperature in the surface and subsurface ocean. CESM SMYLE demonstrates high physical and biogeochemical predictive skill multiple months in advance in key oceanic regions and frequently outperforms persistence forecasts. We find up to 10 months of skillful forecasts, with particularly high skill in the Northeast Pacific (Gulf of Alaska and California Current Large Marine Ecosystems) for temperature, surface DIC, and subsurface oxygen. Our findings suggest that dynamical marine ecosystem prediction could support actionable advice for decision making.

Environmental Sciences & Ecology↗
NASA NTRS1988

Alpha, beta, or gamma: where does all the diversity go?

Global taxonomic richness is affected by variation in three components: within-community, or alpha, diversity, between-community, or beta, diversity; and between-region, or gamma, diversity. A data set consisting of 505 faunal lists distributed among 40 stratigraphic intervals and six environmental zones was used to investigate how variation of alpha and beta diversity influenced global diversity through the Paleozoic, and especially during the Ordovician radiations. As first shown by Bambach (1977), alpha diversity increased by 50 to 70 percent in offshore marine environments during the Ordovician and then remained essentially constant of the remainder of the Paleozoic. The increase is insufficient, however, to account for the 300 percent rise observed in global generic diversity. It is shown that beta diversity among level, soft-bottom communities also increased significantly during the early Paleozoic. This change is related to enhanced habitat selection, and presumably increased overall specialization, among diversifying taxa during the Ordovician radiations. Combined with alpha diversity, the measured change in beta diversity still accounts for only about half of the increase in global diversity. Other sources of increase are probably not related to variation in gamma diversity but rather to appearance and/or expansion of organic reefs, hardground communities, bryozoan thickets, and crinoid gardens during the Ordovician.

NASA Discipline Exobiology↗
DOE OSTI2024

Underestimation of multi-decadal global O 2 loss due to an optimal interpolation method

Abstract. The global ocean's oxygen content has declined significantly over the past several decades and is expected to continue decreasing under global warming, with far-reaching impacts on marine ecosystems and biogeochemical cycling. Determining the oxygen trend, its spatial pattern, and uncertainties from observations is fundamental to our understanding of the changing ocean environment. This study uses a suite of CMIP6 Earth system models to evaluate the biases and uncertainties in oxygen distribution and trends due to sampling sparseness. Model outputs are sub-sampled according to the spatial and temporal distribution of the historical shipboard measurements, and the data gaps are filled by a simple optimal interpolation method using Gaussian covariance with a constant e-folding length scale. Sub-sampled results are compared to full model output, revealing the biases in global and basin-wise oxygen content trends. The simple optimal interpolation underestimates the modeled global deoxygenation trends, capturing approximately two-thirds of the full model trends. The North Atlantic and subpolar North Pacific are relatively well sampled, and the simple optimal interpolation is capable of reconstructing more than 80 % of the oxygen trend in the non-eddying CMIP models. In contrast, pronounced biases are found in the equatorial oceans and the Southern Ocean, where the sampling density is relatively low. The application of the simple optimal interpolation method to the historical dataset estimated the global oxygen loss to be 1.5 % over the past 50 years. However, the ratio of the global oxygen trend between the sub-sampled and full model output has increased the estimated loss rate in the range of 1.7 % to 3.1 % over the past 50 years, which partially overlaps with previous studies. The approach taken in this study can provide a framework for the intercomparison of different statistical gap-filling methods to estimate oxygen content trends and their uncertainties due to sampling sparseness.

Ito, Takamitsu (ORCID:000000019873099X)↗
NASA NTRS2006

A comparison of global estimates of marine primary production from ocean color

The third primary production algorithm round robin (PPARR3) compares output from 24 models that estimate depth-integrated primary production from satellite measurements of ocean color, as well as seven general circulation models (GCMs) coupled with ecosystem or biogeochemical models. Here we compare the global primary production fields corresponding to eight months of 1998 and 1999 as estimated from common input fields of photosynthetically-available radiation (PAR), sea-surface temperature (SST), mixed-layer depth, and chlorophyll concentration. We also quantify the sensitivity of the ocean-color-based models to perturbations in their input variables. The pair-wise correlation between ocean-color models was used to cluster them into groups or related output, which reflect the regions and environmental conditions under which they respond differently. The groups do not follow model complexity with regards to wavelength or depth dependence, though they are related to the manner in which temperature is used to parameterize photosynthesis. Global average PP varies by a factor of two between models. The models diverged the most for the Southern Ocean, SST under 10 C, and chlorophyll concentration exceeding 1mg Chlm-3. Based on the conditions under which the model results diverge most, we conclude that current ocean-color-based models are challenged by high-nutrient low-chlorophyll conditions, and extreme temperatures or chlorophyll concentrations. The GCM-based models predict comparable primary production to those based on ocean color: they estimate higher values in the Southern Ocean, at low SST, and in the equatorial band, while they estimate lower values in eutrophic regions (probably because the area of high chlorophyll concentrations is smaller in the GCMs). Further progress in primary production modeling requires improved understanding of the effect of temperature on photosynthesis and better parameterization of the maximum photosynthetic rate.

Yamanaka, Yasuhiro↗
NASA NTRS2001

Models of Small-Scale Patchiness

Patchiness is perhaps the most salient characteristic of plankton populations in the ocean. The scale of this heterogeneity spans many orders of magnitude in its spatial extent, ranging from planetary down to microscale. It has been argued that patchiness plays a fundamental role in the functioning of marine ecosystems, insofar as the mean conditions may not reflect the environment to which organisms are adapted. Understanding the nature of this patchiness is thus one of the major challenges of oceanographic ecology. The patchiness problem is fundamentally one of physical-biological-chemical interactions. This interconnection arises from three basic sources: (1) ocean currents continually redistribute dissolved and suspended constituents by advection; (2) space-time fluctuations in the flows themselves impact biological and chemical processes, and (3) organisms are capable of directed motion through the water. This tripartite linkage poses a difficult challenge to understanding oceanic ecosystems: differentiation between the three sources of variability requires accurate assessment of property distributions in space and time, in addition to detailed knowledge of organismal repertoires and the processes by which ambient conditions control the rates of biological and chemical reactions. Various methods of observing the ocean tend to lie parallel to the axes of the space/time domain in which these physical-biological-chemical interactions take place. Given that a purely observational approach to the patchiness problem is not tractable with finite resources, the coupling of models with observations offers an alternative which provides a context for synthesis of sparse data with articulations of fundamental principles assumed to govern functionality of the system. In a sense, models can be used to fill the gaps in the space/time domain, yielding a framework for exploring the controls on spatially and temporally intermittent processes. The following discussion highlights only a few of the multitude of models which have yielded insight into the dynamics of plankton patchiness. In addition, this particular collection of examples is intended to furnish some exposure to the diversity of modeling approaches which can be brought to bear on the problem. These approaches range from abstract theoretical models intended to elucidate specific processes, to complex numerical formulations which can be used to actually simulate observed distributions in detail.

McGillicuddy, D. J.↗
NASA NTRS2013

Algorithm Development for Predicting Biodiversity Based on Phytoplankton Absorption

Ocean color remote sensing has provided the scientific community with unprecedented global coverage of chlorophyll a, an indicator of phytoplankton biomass. Together, satellite-derived chlorophyll a and knowledge of Phytoplankton Functional Types (PFTs) will improve our limited understanding of marine ecosystem responses to physiochemical climate drivers involved in carbon cycle dynamics and linkages. Using cruise data from the Gulf of Maine and the Middle Atlantic Bight (N 269 pairs of HPLC and phytoplankton absorption samples), two modeling approaches were utilized to predict phytoplankton absorption and pigments. Algorithm I predicts the chlorophyll-specific absorption coefficient (a*(sub ph) (m(exp 2) mg chl a(exp - 1)) using inputs of temperature, light, and chlorophyll a. Modeled r(exp 2) values (400700 nm) ranged from 0.79 to 0.99 when compared to in situ observations with approximately 25 percent lower r(exp 2) values in the UV region. Algorithm II-a utilizes matrix inversion analysis to predict a(sub ph)(m(exp -1), 400700 nm) and r(exp 2) values ranged from 0.89 to 0.99. The prediction of phytoplankton pigments with Algorithm II-b produced r(exp 2) values that ranged from 0.40 to 0.93. When used in combination, Algorithm I, and Algorithm II-a are able to use satellite products of SST, PAR, and chlorophyll a (Algorithm I) to predict pigment concentrations and ratios to describe the phytoplankton community. The results of this study demonstrate that the spatial variation in modeled pigment ratios differ significantly from the 10-year SeaWiFS average chlorophyll a data set. Contiguous observations of chlorophyll a and phytoplankton biodiversity will elucidate ecosystem responses with unprecedented complexity.

phytoplankton↗
DOE OSTI2023

Surface and subsurface oceanographic features drive forage fish distributions and aggregations: Implications for prey availability to top predators in the US Northeast Shelf ecosystem

Abstract Forage fishes are a critical food web link in marine ecosystems, aggregating in a hierarchical patch structure over multiple spatial and temporal scales. Surface‐level forage fish aggregations (FFAs) represent a concentrated source of prey available to surface‐ and shallow‐foraging marine predators. Existing survey and analysis methods are often imperfect for studying forage fishes at scales appropriate to foraging predators, making it difficult to quantify predator–prey interactions. In many cases, general distributions of forage fish species are known; however, these may not represent surface‐level prey availability to predators. Likewise, we lack an understanding of the oceanographic drivers of spatial patterns of prey aggregation and availability or forage fish community patterns. Specifically, we applied Bayesian joint species distribution models to bottom trawl survey data to assess species‐ and community‐level forage fish distribution patterns across the US Northeast Continental Shelf (NES) ecosystem. Aerial digital surveys gathered data on surface FFAs at two project sites within the NES, which we used in a spatially explicit hierarchical Bayesian model to estimate the abundance and size of surface FFAs. We used these models to examine the oceanographic drivers of forage fish distributions and aggregations. Our results suggest that, in the NES, regions of high community species richness are spatially consistent with regions of high surface FFA abundance. Bathymetric depth drove both patterns, while subsurface features, such as mixed layer depth, primarily influenced aggregation behavior and surface features, such as sea surface temperature, sub‐mesoscale eddies, and fronts influenced forage fish diversity. In combination, these models help quantify the availability of forage fishes to marine predators and represent a novel application of spatial models to aerial digital survey data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Estimating the Importance of Viral Contributions to Soil Carbon Dynamics

ABSTRACT Biogeochemical models for predicting carbon dynamics increasingly include microbial processes, reflecting the importance of microorganisms in regulating the movement of carbon between soils and the atmosphere. Soil viruses can redirect carbon among various chemical pools, indicating a need for quantification and development soil carbon models that explicitly represent viral dynamics. In this opinion, we derive a global estimate of carbon potentially released from microbial biomass by viral infections in soils and synthesize a quantitative soil carbon budget from existing literature that explicitly includes viral impacts. We then adapt known mechanisms by which viruses influence carbon cycles in marine ecosystems into a soil‐explicit framework. Finally, we explore the diversity of virus–host interactions during infection and conceptualize how infection mode may impact soil carbon fate. Our synthesis highlights key knowledge gaps hindering the incorporation of viruses into soil carbon cycling research and generates specific hypotheses to test in the pursuit of better quantifying microbial dynamics that explain ecosystem‐scale carbon fluxes. The importance of identifying critical drivers behind soil carbon dynamics, including these elusive but likely pervasive viral mechanisms of carbon redistribution, becomes more pressing with climate change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Human‐induced salinity changes impact marine organisms and ecosystems

Abstract Climate change is fundamentally altering marine and coastal ecosystems on a global scale. While the effects of ocean warming and acidification on ecology and ecosystem functions and services are being comprehensively researched, less attention is directed toward understanding the impacts of human‐driven ocean salinity changes. The global water cycle operates through water fluxes expressed as precipitation, evaporation, and freshwater runoff from land. Changes to these in turn modulate ocean salinity and shape the marine and coastal environment by affecting ocean currents, stratification, oxygen saturation, and sea level rise. Besides the direct impact on ocean physical processes, salinity changes impact ocean biological functions with the ecophysiological consequences are being poorly understood. This is surprising as salinity changes may impact diversity, ecosystem and habitat structure loss, and community shifts including trophic cascades. Climate model future projections (of end of the century salinity changes) indicate magnitudes that lead to modification of open ocean plankton community structure and habitat suitability of coral reef communities. Such salinity changes are also capable of affecting the diversity and metabolic capacity of coastal microorganisms and impairing the photosynthetic capacity of (coastal and open ocean) phytoplankton, macroalgae, and seagrass, with downstream ramifications on global biogeochemical cycling. The scarcity of comprehensive salinity data in dynamic coastal regions warrants additional attention. Such datasets are crucial to quantify salinity‐based ecosystem function relationships and project such changes that ultimately link into carbon sequestration and freshwater as well as food availability to human populations around the globe. It is critical to integrate vigorous high‐quality salinity data with interacting key environmental parameters (e.g., temperature, nutrients, oxygen) for a comprehensive understanding of anthropogenically induced marine changes and its impact on human health and the global economy.

54 ENVIRONMENTAL SCIENCES↗