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Subsidence induced by underground extraction is a class of human-induced (anthropogenic) land subsidence that principally is caused by the withdrawal of subsurface fluids (groundwater, oil, and gas) or by the underground mining of coal and other minerals.
A complex system consists of many interacting parts, generates new collective behavior through self organization, and adaptively evolves through time. Many theories have been developed to study complex systems, including chaos, fractals, cellular automata, self organization, stochastic processes, turbulence, and genetic algorithms.
Magnetic indices are simple measures of magnetic activity that occurs, typically, over periods of time of less than a few hours and which is recorded by magnetometers at ground‐based observatories (Mayaud, 1980 ; Rangarajan, 1989 ; McPherron, 1995 ). The variations that indices measure have their origin in the Earth's ionosphere and magnetosphere. Some indices having been designed specifically to quantify idealized physical processes, while others function as more generic measures of magnetic activity. Indices are routinely used across the many subdisciplines in geomagnetism, including direct studies of the physics of the upper atmosphere and space, for induction studies of the Earth's crust and mantle, and for removal of disturbed‐time magnetic data in studies of the Earth's deep interior and core. Here we summarize the most commonly used magnetic indices, using data from a worldwide distribution of observatories, those shown in Figure M31 and whose sponsoring agencies are given in Table M1 .
The Geomagnetism Program of the US Geological Survey has, for over a century now, monitored the Earth's magnetic field through a network of magnetic observatories and conducted scientific analysis on the data collected. The program traces its origins to the Reorganization Act of 1843, in which Congress authorized the creation of a coastal survey agency, as part of the Treasury Department, that was responsible for, among other things, geomagnetic surveys. The 19th century saw the establishment of relatively short‐lived magnetic stations, as well as the production of declination maps for the United States and territories. With the purchase of Alaska, coastal surveys became an increasingly higher priority, and in 1889 the Coast and Geodetic Survey, with a Division of Terrestrial Magnetism, was established. The first essentially permanent geomagnetic observatories were established under the Division's leadership of Dr. Louis A. Bauer and Dr. John A. Fleming: Cheltenham Maryland Observatory was established in 1900, subsequently moved to the Fredericksburg site in 1956; Sitka Alaska Observatory was established in 1901 and that of Honolulu Hawaii in 1902. Soon after these observatories became operational, it was found that the Sitka and Honolulu magnetometers were also sensitive to local earthquakes, and so seismometers were installed at the sites. In part, because of this colocation of instruments, the magnetic and seismological programs in the Coast and Geodetic Survey were united in 1925 under the Division of Geomagnetism and Seismology. Over the years, the Geomagnetism Program has evolved in response to the needs of the United States and in response to changes in the nation's various federal agencies. In 1903 the Coast and Geodetic Survey was transferred to the newly organized Department of Commerce, and in 1970 the survey became part of the National Oceanic and Atmospheric Administration (NOAA). In 1973, the US Geological Survey of the Department of the Interior assumed responsibility for the nation's Geomagnetism and Seismology programs.
When studying the mean and variance of paleomagnetic data it is a common practice to employ principal component analysis (Jolliffe, 2002 ). The theory of this method is related to the mathematics quantifying the moment of inertia of a set of particles of mass about some reference point of interest. For the purposes of data analysis, principal component analysis was first promoted by Pearson ( 1901 ) and Hotelling ( 1933 ), and it also often associated with Karhunen ( 1947 ) and Loéve ( 1977 ). Principal component analysis is widely applied in crystallography (e.g., Schomaker et al ., 1959 ). In paleomagnetism (e.g., Mardia, 1972 ; Kirschvink, 1980 ), it finds application in studies of the average paleofield, paleosecular variation, demagnetization, and magnetic susceptibility. Here we discuss and demonstrate principal component analysis in application to full paleomagnetic vectorial data and, separately, to paleomagnetic directional data.
Our concern is with the statistical description of paleomagnetic vectors and the estimation of their mean and variance. These vectors may come from a number of different rock units or archeological samples, representing a range of acquisition times, and be useful for studies of the mean paleomagnetic field and paleosecular variation ; alternatively, the vectors may come from individual measurements taken from a given rock unit or archeological sample, representing the same moment of acquisition, and be useful for studying the acquisition process itself. Directional data of a particular polarity are usually analyzed with a Fisher distribution (1953), and data of mixed polarities are usually analyzed with a Bingham distribution (1964). Occasionally, other directional distributions are used. For example, Bingham ( 1983 ) considered the projection of a three‐dimensional (3D), scalar‐variance Gaussian distribution onto the unit sphere, something he called the “angular‐Gaussian” distribution. More recently, Khokhlov et al. ( 2001 ) considered a generalization of the angular‐Gaussian distribution, one with a covariance matrix, which they used to analyze directional data from a number of sites. With respect to intensity data, they have traditionally been treated separately from paleodirections, analyzed with normal, log‐normal, or gamma distributions. Here, for data of either a particular polarity or of mixed polarities, we summarize these works, and that of Love and Constable ( 2003 ), who developed a full‐vector, scalar‐variance, Gaussian‐statistical framework for treating directional and intensity data simultaneously and self‐consistently.
Soils and aquifers are major compartments of the subsurface environment, which together control the terrestrial hydrological cycle. This subsurface is important for water resources and also as repository for municipal, industrial, and government waste. Aquifers are typically recharged by natural rainfall entering the soil profile and leaching into deeper soil layers. Due to intensive agricultural or industrial activities the leachate leaving the soil profile and entering the aquifer may contain concentrations of toxic substances such as agrochemicals, heavy metals, and polycyclic aromatic hydrocarbons. At contaminated industrial sites light and dense non-aqueous phase liquids (LNAPLs, DNAPLs) may be transported as a separate phase to the underlying aquifer systems. Once any of these chemicals have entered the aquifer they can be transported over large horizontal distances thus contaminating large parts of the aquifer and threateningwater supplywells. Remediation of highly contaminated aquifer systems is commonly a long-term and expensive proposition. As safe and effective use of the subsurface environment is a major challenge facing our society, there is a great need to improve our understanding of the shallow subsurface and the groundwater systems. This particularly includes the understanding of transport processes, which are responsible for the fate of contaminants.
No abstract available.
Worldwide, the intrusion of salinity into irrigated and natural landscapes has major economic and cultural impacts and has resulted in large reductions in crop yields (Epstein et al. 1980; Flowers 2003). Losses have prompted wide-scale programs to improve the salt tolerance of many agronomic species or to identify crop species that can tolerate lands affected by low levels of salinity. Few historic research efforts have considered forest tree species in the United States, especially in nonurban areas. Newer programs have focused on identifying salt tolerance in forest tree species but have mainly limited these efforts to compiling lists of salt tolerant species to be used in afforestation projects (Gogate et al. 1984; Shrivastava et al. 1988; Beckmann 1991; Bell 1999). Gogate et al. (1984), for instance, listed 26 potential species from Australia with silvicultural application to salt affected lands in India. More comprehensive efforts have considered species lists along with specific site requirements (Bell 1999); species tolerant to saline irrigation waters on dry land, for example, will not often be tolerant of salinity increases in wetland settings. Similar ideas have spawned field trials of native and nonnative tree species in India, Pakistan, Thailand, Australia, and the United States (Thomson 1988; Beckmann 1991; Krauss et al. 2000; Conner and Ozalp 2002; Marcar and Crawford 2004; Conner and Inabinette 2005). Concerted attempts at salt tolerance improvement of forest tree species have been limited, owing in part to the diversity of regional issues that such programs must consider. Whereas food, fodder, and pulp yield may be the major improvement goal on salt affected lands in India (Mathur and Sharma 1984), identifying trees that can survive deicing salts (Townsend 1989), oil and gas brine discharges (Auchmoody and Walters 1988), or sea-level rise induced salinity changes (Pezeshki et al. 1987, 1990) are of greater interest to larger industrial nations. Nevertheless, salt tolerance research on a range of tree species has converged on one very important finding; among the mechanisms proposed for salt tolerance in nonhalophytes (Greenway and Munns 1980; Munns and Termaat 1986; Cheeseman 1988), ion exclusion from cellular processes, especially exclusion of Cl- , ranks high (Townsend 1989). Identifying the principal mechanism and location of ion exclusion and determining the range of additive genetic variation available among physiological, morphological, and growth attributes for individual species have been the major elements of salt tolerance improvement programs for trees (Allen et al. 1994a).
No abstract available
Studies of tidal freshwater forested wetlands are few in contrast to the diversity of conditions and information needs that exist for this ecosystem type. Basic information is lacking on the physiological ecology of major wetland tree species under natural settings, the structure and dynamics of pure and mixed species communities, soil-plant interactions, biogeochemistry, hydrology, soils, wildlife habitat, primary biotic and abiotic functions, and the response of these systems to natural and human-caused disruptions. Existing information is often not in a form that can be applied to ecosystem problems, especially those related to management, restoration, or creation of tidal swamps. Accordingly, there is a critical need for research on fundamental biotic and abiotic processes and functions in tidal forested wetland landscapes on a local and regional scale. In this chapter, we detail those research needs, and we highlight some restoration ideas for tidal freshwater forested wetlands with the hope that much additional research will follow.
No abstract available.
No abstract available.
Tidal freshwater swamps in the southeastern United States are subjected to tidal hydroperiods ranging in amplitude from microtidal (<0.1 m) to mesotidal (2-4 m), both having different susceptibilities to anthropogenic change. Small alterations in flood patterns, for example, can switch historically microtidal swamps to permanently flooded forests, scrub-shrub stands, marsh, or open water but are less likely to convert mesotidal swamps. Changes to hydrological patterns tend to be more noticeable in Louisiana than do those in South Carolina. The majority of Louisiana’s coastal wetland forests are found in the Mississippi River deltaic plain region. Coastal wetland forests in the deltaic plain have been shaped by the sediments, water, and energy of the Mississippi River and its major distributaries. Baldcypress ( Taxodium distichum [L.] L.C. Rich.) and water tupelo ( Nyssa aquatica L.) are the primary tree species in the coastal swamp forests of Louisiana. Sites where these species grow usually hold water for most of the year; however, some of the more seaward sites were historically microtidal, especially where baldcypress currently dominates. In many other locations, baldcypress and water tupelo typically grow in more or less pure stands or as mixtures of the two with common associates such as black willow ( Salix nigra Marsh.), red maple ( Acer rubrum L.), water locust ( Gleditsia aquatic Marsh.), overcup oak ( Quercus lyrata Walt.), water hickory ( Carya aquatica [Michx. f.] Nutt.), green ash ( Fraxinus pennsylvanica Marsh.), pumpkin ash (F. profunda Bush.), and redbay ( Persea borbonia [L.] Sprengel) (Brown and Montz 1986). The South Carolina coastal plain occupies about two-thirds of the state and rises gently to 150 m from the Atlantic Ocean up to the Piedmont plateau. Many rivers can be found in the Coastal Plain with swamps near the coast that extend inland along the rivers. Strongly tidal freshwater forests occur along the lower reaches of redwater rivers (Santee, Great Pee Dee, and Savannah) that arise in the mountains and along the numerous blackwater rivers (Ashepoo, Combahee, Cooper, and Waccamaw) that arise in the coastal regions. Most of the tidal freshwater forests were converted to tidal rice fields in the 1700s (Porcher 1995). Canopy members of the present day forests include baldcypress, water tupelo, swamp tupelo ( N. biflora Walt.), red maple, and Carolina ash ( Fraxinus caroliniana Miller). Subcanopy and shrub species include Virginia sweetspire ( Itea virginica L.), dwarf palmetto ( Sabal minor (Jacquin) Pers.), coastal plain willow ( Salix caroliniana Michx.), redbay, and water-elm ( Planera aquatica Gmel.).
No abstract available.