Thesis. 1977. M.S.--Massachusetts Institute of Technology. Dept. of Earth and Planetary Sciences. / Microfiche copy available in Archives and Science. / Bibliography : leaves 52-54. / M.S.

A wealth of empirical and theoretical studies has investigated the consequences of biodiversity loss on ecosystem properties. Whilst the importance of biodiversity in mediating ecosystem properties has been established, the magnitude and direction of effects vary between studies and are dependent on the biotic and abiotic conditions of the experimental system. Consequently there are still significant gaps in our understanding of how species loss may affect ecosystem properties, what the underlying mechanisms are, and how the effects of species loss are modified by environmental context.

A benthic environments classification system is devised from digital interpretations of multi-spectral IKONOS satellite imagery for 1,360 km2 of the carbonate platform and presented in a comprehensive digitized map. The classification scheme is designed as a 7th order hierarchical structure that integrates 5 Physiographic Realms, 24 Morphodynamic Zones, 11 Geoforms, 39 Landforms, 6 dominant surface sediment types, 9 dominant biological covers and 3 densities of biological covers for the description of benthic environments. Digital analysis of the high-resolution (4 m) IKONOS imagery employed ESRI's ArcMap to manually digitize 412 mapping units at a scale of 1:6,000 differentiated by spectral reflectance, color tones, and textures of seafloor topologies. The context of each morphodynamic zone is characterized by the content and areal distribution (in km2) of geomorphic forms and biological covers. Over 58% of the mapping area is occupied by sediment flats, and seagrasses are colonized in almost 80% of the topologies. / by Jacob Thomas Steinle. / Thesis (M.S.)--Florida Atlantic University, 2011. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2011. Mode of access: World Wide Web.

Seabed gouging by ice, also known as ice scouring, is a common feature of the Arctic and sub Arctic regions of the planet as well as in Antarctica. It is a phenomenon which occurs when ice moves while in contact with the seabed. Ice gouging is of economical significance due to the probability of disruption of seabed structures such as subsea pipelines. Small scale laboratory tests were conducted at 1g to investigate the scour force produced when a scaled iceberg model scours a test bed in dry and saturated conditions. The tests were conducted for a range of scour depths, scour widths, frontal rake angles and soil conditions to study the performance of a rigid indenter (iceberg keel) scouring a test bed. Furthermore, the tests were also conducted at various speeds to study the rate effect in sand. The effect of the drifting speed on the drag force was found to be important: a sandy seabed scoured by an iceberg with a mean drifting speed of 0.1 m/s can generate scour loads twice as large as the static loads. The methods used currently to predict ice scour loads consider only the static loads under drained conditions and these should be revised. The PIV (Particle Image Velocimetry) technique was utilized to study the sub-gouge deformation and the soil failure mechanism associated with ice gouging. The soil resistance and the sub gouge deformation results obtained in the laboratory were compared with centrifuge investigations (the PRISE and PIRAM programs) in order to examine the viability of extrapolating the results from the model scale to a prototype scale.

[Truncated abstract] Spatially explicit marine habitat data is required for effective resource planning and management across large areas, although mapped boundaries typically lack rigour in explaining what factors influence habitat distributions. Accurate, quantitative methods are needed. In this thesis I aimed to assess the utility of ecological models to determine what factors limit the spatial extent of marine habitats. I assessed what types of modeling methods were able to produce the most accurate predictions and what influenced model results. To achieve this, initially a broad scale marine habitat survey was undertaken in the Recherche Archipelago, on the south coast of Western Australia using video and sidescan sonar. Broad and more detailed functional habitats types were mapped for 1054km2 of the Archipelago. Broad habitats included high and low profile reefs, sand, seagrass and extensive rhodolith beds, although considerable variation could be identified from video within these broad types. Different densities of seagrass were identified and reefs were dominated by macroalgae, filter feeder communities, or a combination of both. Geophysical characteristics (depth, substrate, relief) and dominant benthic biota were recorded and then modelled using decision trees and a combination of generalised additive models (GAMs) and generalised linear models (GLMs) to determine the factors influencing broad and functional habitat variation. Models were developed for the entire Archipelago (n=2769) and a subset of data in Esperance Bay (n=797), which included exposure to wave conditions (mean maximum wave height and mean maximum shear stress) calculated from oceanographic models. Additional distance variables from the mainland and islands were also derived and used as model inputs for both datasets. Model performance varied across habitats, with no one method better than the other in terms of overall model accuracy for each habitat type, although prevalent classes (>20%) such as high profile reefs with macroalgae and dense seagrass were the most reliable (Area Under the Curve >0.7). ... This highlighted not only issues of data prevalence, but also how ecological models can be used to test the reliability of classification schemes. Care should be taken when mapping predicted habitat occurrence with broad habitat models. It should not be assumed that all habitats within the type will be defined spatially, as this may result in the distribution of distinctive and unique habitats such as filterfeeders being underestimated or not identified at all. More data is needed to improve prediction of these habitats. Despite the limitations identified, the results provide direction for future field sampling to ensure appropriate variables are sampled and classification schemes are carefully designed to improve descriptions of habitat distributions. Reliable habitat models that make ecological sense will assist future assessments of biodiversity within habitats as well as provide improved data on the probability of habitat occurrence. This data and the methods developed will be a valuable resource for reserve selection models that prioritise sites for management and planning of marine protected areas.

Wave-formed rippled sediment beds are extremely important to the processes that act on or across the sediment-water interface. Ripples increase the exchange of materials between the sediment and the water column, enhance sediment transport rates, and act to increase the dissipation of waves by increasing the hydraulic roughness of the seafloor. Previous research has, however, failed to take into account the substantial spatial and temporal variation rippled beds display when formed under real sea conditions. Based on a set of laboratory experiments a spectral method to predict and model rippled beds has been developed. Through the use of the rippled surface's spectral density function the spatial and temporal variability of the rippled surface can be taken into account with greater efficiency. A prediction method for the equilibrium ripple spectrum was developed based on a nondimensional spectral form, which utilised the peak orbital excursion diameter and the 50th percentile grain size diameter of the sediment bed. The method provided an effective technique to predict ripple parameters with the same degree of accuracy achievable at small scale as more accepted ripple prediction methods. A new method was derived to model the changes a rippled bed undergoes as it actively evolves between two given equilibrium states due to a change in surface wave conditions. The evolution of a rippled bed can be described mathematically in exactly the same way as a rippled bed growing from a flat bed condition. The method allows any bed to be modelled through time if the flow conditions and sediment properties are known. There is little advantage in using the spectral method to predict rippled beds when they are in equilibrium with the flow conditions. The main benefit of the spectral method comes when attempting to model rippled beds evolving under changed flow conditions. In the same way as the parameterisation of surface waves in terms of their spectral density function has increased the ability to model wind generated wave fields, studies of rippled beds would benefit from the increased detail and ease the spectral method brings. / Thesis (Ph.D.)--School of Civil and Environmental Engineering, 2005.

Thesis (Ph. D.)--Joint Program in Applied Ocean Sciences (Massachusetts Institute of Technology, Dept. of Ocean Engineering; and the Woods Hole Oceanographic Institution), 2002. / Includes bibliographical references (leaves 161-170).

Thesis (M.S. in Applied Science (Signal Processing))--Naval Postgraduate School, June 2004. / Thesis advisor(s): Lawrence J. Ziomek. Includes bibliographical references (p. 47). Also available online.

Previous studies have suggested that ocean bottom pressure (OBP) can be used to measure the transport variability of the Antarctic Circumpolar Current (ACC). The OBP observations from the Gravity Recovery and Climate Experiment (GRACE) are used to calculate transport along the choke point between Antarctica and Australia. Statistical analysis will be conducted to determine the uncertainty of the GRACE observations using a simulated data set. There has been some evidence to suggest that Southern Hemisphere winds and the Southern Annular Mode (SAM) or the Antarctic Oscillation (AAO) play a significant role in accelerating/decelerating ACC transport, along with some contribution from buoyancy forcing. We will examine whether average zonal wind stress, wind stress curl, local zonal winds, or the SAM are representative of the low frequency zonal mass transport variability. Preliminary studies suggest that seasonal variation in transport across the Australia-Antarctica choke point is driven by winds along and north of the northern front of the ACC, the Sub Tropical front (STF). It also appears that interannual variations in transport are related to wind variations centered south of the Sub Antarctic Front (SAF). We have observed a strong negative correlation/positive correlation across the STF of the ACC in the Indian Ocean, which suggests wind stress curl may also be responsible for transport variations.

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