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At least 1,243 records · Page 69Linked to original sources
USGS2010

Mapping products of Titan's surface

Remote sensing instruments aboard the Cassini spacecraft have been observed the surface of Titan globally in the infrared and radar wavelength ranges as well as locally by the Huygens instruments revealing a wealth of new morphological features indicating a geologically active surface. We present a summary of mapping products of Titan's surface derived from data of the remote sensing instruments onboard the Cassini spacecraft (ISS, VIMS, RADAR) as well as the Huygens probe (DISR) that were achieved during the nominal Cassini mission including an overview of Titan's recent nomenclature.

Book chapter↗
USGS2009

Mapping products of Titan's surface

Remote sensing instruments aboard the Cassini spacecraft have been observed the surface of Titan globally in the infrared and radar wavelength ranges as well as locally by the Huygens instruments revealing a wealth of new morphological features indicating a geologically active surface. We present a summary of mapping products of Titan's surface derived from data of the remote sensing instruments onboard the Cassini spacecraft (ISS, VIMS, RADAR) as well as the Huygens probe (DISR) that were achieved during the nominal Cassini mission including an overview of Titan's recent nomenclature.

Book chapter↗
USGS2008

Geology and Surface Processes on Titan

The surface of Titan has been revealed globally, if incompletely, by Cassini observations at infrared and radar wavelengths as well as locally by the instruments on the Huygens probe. Extended dune fields, lakes, mountainous terrain, dendritic erosion patterns and erosional remnants indicate dynamic surface processes. Valleys, small-scale gullies and rounded cobbles such as those observed at the Huygens landing site require erosion by energetic flow of a liquid. There is strong evidence that liquid hydrocarbons are ponded on the surface in high-latitude lakes, predominantly, but not exclusively, at high northern latitudes. A variety of features including extensive flows and caldera-like constructs are interpreted to be cryovolcanic in origin. Chains and isolated blocks of rugged terrain rising from smoother areas are best described as mountains and might be related to tectonic processes. Finally, impact craters are observed but their small numbers indicate that the crater retention age is very young overall. In general, Titan exhibits a geologically active surface indicating significant endogenic and exogenic processes, with diverse geophysical and atmospheric processes reminiscent of those on Earth.

Book chapter↗
USGS2010

Biodegration of chlorinated ethenes

Biodegradation of chlorinated ethenes by naturally occurring or artificially enhanced processes is an important component of current site remediation strategies. At this writing, several microbial mechanisms for chlorinated ethene transformation and degradation have been identified. The purpose of this chapter is to briefly summarize the current understanding of those processes that lead to the biodegradation of chlorinated ethenes.

Book chapter↗
USGS2010

The ASTER data system: An overview of the data products in Japan and in the United States

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data system is a cooperative system, which is operated jointly by Japan’s Ministry of Economy, Trade, and Industry (METI) through its Earth Remote Sensing Data Analysis Center (ERSDAC), and by the National Aeronautics and Space Administration (NASA) primarily through its Goddard Space Flight Center (GSFC) and Land Processes (LP) Distributed Active Archive Center (DAAC). ASTER is a moderate-resolution land remote sensing system onboard the Earth Observing System (EOS) Terra spacecraft. ASTER-acquired data are received at the White Sands, New Mexico, ground receiving station, and then transmitted via land network to the EOS Data and Operations System (EDOS) within the Goddard DAAC, located at the GSFC. EDOS pre-processes raw ASTER data to Level-0 (L0) data, and sends them via the high-speed Asia-Pacific Advanced Network (APAN) to the ASTER Ground Data System (GDS) in Japan. ASTER GDS processes the L0 data to level-1 (L1) datasets; they distribute these data to users, and also use them to generate higher-level products for their user community. ASTER GDS sends a copy of all L1A data they produce to NASA’s LP DAAC, located at the U.S. Geological Survey’s Center for Earth Resources Observation and Science (EROS) near Sioux Falls, South Dakota. All L1 data received from Japan are ingested, archived, and available for users at LP DAAC. The LP DAAC also generates and distributes higher-level products from L1 data based on requests from users. To meet time-critical needs related to sensor health and performance, natural disasters, national emergencies, and certain field campaigns, the ASTER Expedited Data System (EDS) was developed, and is operated jointly by U.S. and Japanese partners.

Book chapter↗
USGS2011

Topographic mapping data semantics through data conversion and enhancement

This paper presents research on the semantics of topographic data for triples and ontologies to blend the capabilities of the Semantic Web and The National Map of the U.S. Geological Survey. Automated conversion of relational topographic data of several geographic sample areas to the triple data model standard resulted in relatively poor semantic associations. Further research employed vocabularies of feature type and spatial relation terms. A user interface was designed to model the capture of non-standard terms relevant to public users and to map those terms to existing data models of The National Map through the use of ontology. Server access for the study area triple stores was made publicly available, illustrating how the development of linked data may transform institutional policies to open government data resources to the public. This paper presents these data conversion and research techniques that were tested as open linked data concepts leveraged through a user-centered interface and open USGS server access to the public.

Book chapter↗
USGS1996

Environmental hazards of aluminum to plants, invertebrates, fish, and wildlife

Aluminum (Al) is the third most common mineral and the most common metal in Earth’s crust, accounting for approximately 8.1% of the crust by weight. Thus, it cannot be considered a contaminant in the usual sense of the word. However, despite its near omnipresence throughout the world, Al has been of major concern as a primary limiting factor to cultivated plants for several decades. In much of the world, Al severely restricts the growth and presence of plant species. Since the late 1970s, concern about Al toxicity has spread to natural habitats, most notably forests and aquatic communities. The primary impetus for this concern has been the increased awareness of the effects of anthropogenic acidification through mine drainage, acid deposition, and other sources. The toxicity of Al is intimately associated with pH in that the metal is soluble and biologically available in acidic (pH <5.5) soils and waters but relatively innocuous in circumneutral (pH 5.5-7.5) conditions. Forest die-offs and reduced survivorship or impaired reproduction of aquatic invertebrates, fish, and amphibians have been directly connected to Al toxicity. Indirect effects on birds and mammals also have been identified. The purpose of this review is to summarize the toxic effects of Al to populations and to evaluate the potential hazards to the communities in which these populations are found.

Book chapter↗
USGS1994

National standards and guidelines for pesticides in water, sediment, and aquatic organisms

The effects of pesticides 1 on water quality commonly are assessed by comparing measured concentrations of individual pesticide compounds in the environment with concentrations that have been determined to have potential adverse effects on humans, aquatic organisms, or other beneficial uses of water. Direct evaluation of the adverse effects of every pesticide present in a given hydrologic system is beyond the scope and budget of most water-quality studies. Many studies rely on standards or guidelines set by federal or state agencies or other institutions to indicate what concentrations may have adverse effects on human health, aquatic organisms, or wildlife. Such standards and guidelines generally are based on laboratory or field studies that document the effects of individual pesticides on specific aspects of water quality. Single-species toxicity tests (using a single species of a test organism) under various laboratory conditions are the most common type of study, whereas artificial ecosystem studies (using multiple species of a test organism) and field studies are relatively uncommon. Such studies rarely consider the effects of exposure to more than one chemical at a time. Technical information from such studies has been used by the U.S. Environmental Protection Agency (USEPA) 2 in issuing national standards, such as drinking-water regulations (for example, see USEPA 1991a) and guidelines, such as ambient water-quality criteria for the protection of human health and aquatic organisms (for example, see USEPA 1980a) to meet its statutory requirements under the Safe Drinking Water Act (SDWA) and the Clean Water Act (CWA). The Food and Drug Administration (FDA) also has used its authority under the Federal Food, Drug, and Cosmetic Act (FFDCA) to set action levels (enforceable regulatory limits) for unavoidable residues of pesticides in foods (FDA 1990).

Book chapter↗
USGS1991

Freshwater molluscs as indicators of bioavailability and toxicity of metals in surface-water systems

During the past several decades, studies from a variety of locations have demonstrated widespread occurrence of metals in surface waters at concentrations significantly higher than background levels. Elevated concentrations are not limited to certain water types or polluted areas; they appear in all types of systems and in all geographic areas. It is clear that metals enter the aquatic systems from diverse sources, both point and nonpoint, and they can be readily transported from one system to another. Transport routes include atmospheric, terrestrial, subterranean, aquatic, and biological pathways (Elder 1988; Salomons and Forstner 1984).

Book chapter↗
USGS1990

Embryotoxicity and teratogenicity of environmental contaminants to bird eggs

In light of recent ecological disasters such as the Exxon Valdez oil spill of 1989, which has already claimed the lives of thousands of aquatic birds with the reproductive success of countless others at risk, there is a need to evaluate the embryotoxic potential of a continuously growing number of industrial and agricultural environmental contaminants that may come in direct contact with bird eggs. Since the Clean Air Act of 1970, the Environmental Protection Agency has issued regulations for only seven toxics, yet in 1987 alone industry released over two billion pounds of toxic substances into the air (Easterbrook 1989).

Book chapter↗
USGS1992

Impacts of variation in planktivorous fish on abundance of daphnids: A simulation model of the Lake Mendota food web: Chapter 20

Previous chapters in this volume have outlined the goals of the Lake Mendota food web manipulation study (Rudstam et al., Ch. 12) and have reported on variations in phytoplankton and zooplankton abundances during the past 15 years (Lathrop and Carpenter, Ch. 7 and 8). Because of the long time scales inherent in such a lake management manipulation, it became imperative to attempt to predict how the lake would respond to changes in planktivorous fish abundance over time scales of several decades. We know from the past 15 years of study (Lathrop and Carpenter, Ch. 7 and 8; Magnuson and Lathrop, Ch. 11) that substantial variation of planktivorous fish, zooplankton, and phytoplankton abundances can occur the lake. Given the current stocking of piscivores, we have the potential to substantially modify the abundance of planktivorous fish and possibly shift the assemblages of phytoplankton and zooplankton beyond the ranges of those which occurred previously. In this chapter we describe the construction and use of a simulation model designed to examine how variation in plantivore abundance might impact zooplankton biomass and species composition.

Wisconsin↗
USGS1989

On inter-tidal transport equation

The transports of solutes, sediments, nutrients, and other tracers are fundamental to the interactive physical, chemical, and biological processes in estuaries. The characteristic time scales for most estuarine biological and chemical processes are on the order of several tidal cycles or longer. To address the long-term transport mechanism meaningfully, the formulation of an inter-tidal conservation equation is the main subject of this paper. The commonly used inter-tidal conservation equation takes the form of a convection-dispersion equation in which the convection is represented by the Eulerian residual current, and the dispersion terms are due to the introduction of a Fickian hypothesis, unfortunately, the physical significance of this equation is not clear, and the introduction of a Fickian hypothesis is at best an ad hoc approximation. Some recent research results on the Lagrangian residual current suggest that the long-term transport problem is more closely related to the Lagrangian residual current than to the Eulerian residual current. With the aid of additional insight of residual current, the inter-tidal transport equation has been reformulated in this paper using a small perturbation method for a weakly nonlinear tidal system. When tidal flows can be represented by an M 2 system, the new intertidal transport equation also takes the form of a convective-dispersion equation without the introduction of a Fickian hypothesis. The convective velocity turns out to be the first order Lagrangian residual current (the sum of the Eulerian residual current and the Stokes&rsquo; drift), and the correlation terms take the form of convection with the Stokes&rsquo; drift as the convective velocity. The remaining dispersion terms are perturbations of lower order solution to higher order solutions due to shear effect and turbulent mixing.

Book chapter↗
USGS2001

Uncertainty and spatial linear models for ecological data

Models are not perfect; they do not fit the data exactly and they do not allow exact prediction. Given that models are imperfect, we need to assess the uncertainties in the fits of the models and their ability to predict new outcomes. The goals of building models for scientific problems include (1) understanding and developing appropriate relationships between variables, and (2) predicting variables in the future or at locations where data have not been collected. Ecological models range in complexity from those that are relatively simple (e.g., linear regression) to those that are very complex (e.g., ecosystem models, forest-growth models, and nitrogen-cycling models). In a mathematical model, parameters control the relationships between variables in the model. In this framework of parametric modeling, inference is the process whereby we take output (data) and estimate model parameters, whereas deduction is the process whereby we take a parameterized model and obtain output (data) or deduce properties. We often add random components in both inference and deduction to reflect a model’s lack-of-fit and our uncertainty about predicting outcomes. Complex models in ecology have largely been of the deductive type, where the scientist takes some values of parameters (usually obtained from an independent data source or chosen from a reasonable range of values) and then simulates results based on model relationships. These models may be quite realistic, but the manner in which their parameters are obtained for the simulations is questionable.

Book chapter↗
USGS2001

Coastal sage scrub case study

In ecological applications of large-scale spatial data to management decisions concerning land planning and conservation, errors and biases may creep into the analysis and decision making at several steps (see Chaps. 1, 2, and 3), including: • Uncertainty in positions of spatial locations of relevant ecological and physiographic features of the landscape. • Uncertainty of the type and attributes of land cover at a particular location. • Uncertainty in how different land covers at a position in space and the geometric arrangement of land covers nearby might influence an animal species occurrence or distribution, or the magnitude of some ecological process. • Uncertainty about the relative importance of each spatial location to the overall success or persistence of a population or ecological process. • Uncertainty about how to weight each species or ecological process in determining the overall biodiversity and functioning of ecosystems, local and national resource priorities, and consistency with legislative mandates. We would like to be able to quantify the errors at each step, identify biases, and pass these along to the next analysis step so that our degree of uncertainty regarding potential outcomes is evident at each level (e.g., Stoms et al. 1992).

Book chapter↗
USGS1996

Dimethylsulfoniopropionate as a potential methanogenic substrate in Mono Lake sediments

A high concentration of dimethylsulfoniopropionate (DMSP) was found in the water column (0.1–1.8 µM particulate plus dissolved) of Mono Lake, CA, an alkaline, hypersaline waterbody. The dense Artemia monica population contained high levels of DMSP (1.7–2.5 mmol.g -1 wet weight), presumably as an osmolyte. Death of these brine shrimp caused accumulation of DMSP along the shoreline of the lake, where concentrations peaked at 7–13 jumol.cm -3 sediment. DMSP was also associated with the phototrophic microbial population in microbial mats close to the shoreline. Chemical hydrolysis of DMSP caused by the high pH value of the water (9.7–10.0) competed with biological consumption. Flux chamber experiments suggested that part of the dimethylsulfide (DMS) generated by hydrolysis escaped to the atmosphere. Vertical profiles of DMSP and DMS in the sediment correlated well. Methane and DMS also had similar distributions. Additional inhibitor studies showed that a major biological sink for DMS(P) is methanogenesis, although monooxygenase-containing bacteria also contributed to its consumption.

Book chapter↗