Evaluation of Inference Adequacy in Cumulative Logistic Regression Models: An Empirical Validation of ISWRidge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p 〈0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to cheek the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height （X1 ） and potential energy （X2 ） significantly impact （p 〈 0. 0001 ） the amplitude-based refleeted rate; the P-values for the deviance and Pearson are all 〉 0.05 （0.2839, 0.3438, respectively）. That is, the goodness-of-fit between ridge height （ X1 ） and potential energy （X2） can further predict parameters under the scenario of the best parsimonious model. Investigation of 6 predictive powers （ R2, Max-rescaled R^2, Sorners＇ D, Gamma, Tau-a, and c, respectively） indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

Oceanic exchange variability across the continental slope west coast,South Island,New Zealand

Current observations taken at depths between 630 and 830 m from the west coast South Island continental slope exhibit one‐ to four‐weekly periodicities superimposed on the semi‐diurnal tide. These variable flows at 630 m and otter large, longer‐timescale events have a significart onshore/offshore component of flow which leads to a similar transport of alongshore momentum and heat.     

Optical water type discrimination and tuning remote sensing band-ratio algorithms: Application to retrieval of chlorophyll and Kd(490) in the Irish and Celtic Seas

This paper assesses the feasibility of applying remote sensing algorithms based on blue/green reflectance ratios to Case 2 waters. Two algorithms from the SeaDAS (NASA) image processing package, OC4v4 for surface chlorophyll concentration, Chl, and K(490) for the attenuation coefficient for downward irradiance at 490 nm, K_d(490), were investigated using an extensive set of observations from the Irish and Celtic Seas. In situ data from a profiling radiometer were used as inputs for the algorithms to avoid uncertainties in atmospheric correction procedures, and direct measurements of Chl and K_d490 and were used for validation purposes. The standard versions of the algorithms performed poorly: OC4v4 generally overestimated Chl (with a very low coefficient of determination), and K(490) progressively underestimated K_d490 for values greater than 0.3 m⁻¹. A two-step procedure for level 2 product generation was therefore devised in which the numerical coefficients of OC4v4 and K(490) were tuned for the two optical water types known to occur most frequently in this region (McKee, D., Cunningham, A., 2006. Identification and characterisation of two optical water types in the Irish Sea from in situ inherent optical properties and seawater constituents. Estuarine, Coastal and Shelf Science 68, 305–316) by statistical regression on a data set of 102 stations from the Irish and Celtic Seas. The water types were distinguished by the magnitude of their normalised water leaving radiance signals at 665 nm, nL_w(665), and appropriate versions of the tuned algorithms applied to each water type. When this procedure was tested on an independent data set of 19 stations from the Bristol Channel, Chl values were recovered with an RMS error of 0.36 mg m⁻³ and K_d(490) values with an RMS error of 0.095 m⁻¹. The identification of water types from water-leaving radiance signals, and the application of band-ratio algorithms tuned for specific water types, may therefore provide a simple means of improving the quality of remote sensing products in optically complex shelf seas.     

Multi-factor impact analysis of agricultural production in Bangladesh with climate change

Diverse vulnerabilities of Bangladesh's agricultural sector in 16 sub-regions are assessed using experiments designed to investigate climate impact factors in isolation and in combination. Climate information from a suite of global climate models (GCMs) is used to drive models assessing the agricultural impact of changes in temperature, precipitation, carbon dioxide concentrations, river floods, and sea level rise for the 2040–2069 period in comparison to a historical baseline. Using the multi-factor impacts analysis framework developed in Yu et al. (2010), this study provides new sub-regional vulnerability analyses and quantifies key uncertainties in climate and production. Rice (aman, boro, and aus seasons) and wheat production are simulated in each sub-region using the biophysical Crop Environment REsource Synthesis (CERES) models. These simulations are then combined with the MIKE BASIN hydrologic model for river floods in the Ganges-Brahmaputra-Meghna (GBM) Basins, and the MIKE21 Two-Dimensional Estuary Model to determine coastal inundation under conditions of higher mean sea level. The impacts of each factor depend on GCM configurations, emissions pathways, sub-regions, and particular seasons and crops. Temperature increases generally reduce production across all scenarios. Precipitation changes can have either a positive or a negative impact, with a high degree of uncertainty across GCMs. Carbon dioxide impacts on crop production are positive and depend on the emissions pathway. Increasing river flood areas reduce production in affected sub-regions. Precipitation uncertainties from different GCMs and emissions scenarios are reduced when integrated across the large GBM Basins’ hydrology. Agriculture in Southern Bangladesh is severely affected by sea level rise even when cyclonic surges are not fully considered, with impacts increasing under the higher emissions scenario.     

Erratum to: Assessment of coastal communities’ vulnerability to floods using indicator-based approach: a case study of Greater Accra Metropolitan Area,Ghana

In this paper, the extent to which the potentially transit-dependent portion of the population is vulnerable to the effects of a hurricane is estimated. The vulnerability of an area is defined as a composite measure of the proportion of disadvantaged persons, distance to transit, and flooding potential of people within an area. Unlike past studies which have focused on the vulnerability of the population in relatively large geographic areas, this study estimates the vulnerability of the population in 30 m × 30 m areas as defined in the National Land Cover Database. Population estimates from the national census at block level are disaggregated to the 30 m × 30 m units using a modified dasymetric mapping method in ArcGIS. The modified mapping method assigns population to each small areal unit using weights estimated by regressing the area of each land use in a census block against the population in that block. The coefficients in the regression analysis are “weights” associating population with each land use, and are used to distribute the population in each census block to the small geographic units based on their land use. In a case study of New Orleans, the results show that some areas are not well served by the existing transit pickup locations, as evidenced by their high vulnerability scores. Reassignment of pickup point locations to cover higher vulnerability score areas was investigated using integer linear programming. The results show that the optimally located pickup points serve areas with a larger average vulnerability score than the current pickup points in the study area. The method appears to be helpful in identifying vulnerable areas that, subsequently, could receive improved hurricane evacuation service in the future.     

Hyper Redundancy for Accuracy Enhancement in Automated Close Range Photogrammetry

A generic network design in close range photogrammetry is one where optimal multi-ray intersection geometry is obtained with as few camera stations as practicable. Hyper redundancy is a concept whereby, once the generic network is in place, many additional images are recorded, with the beneficial impact upon object point precision being equivalent to the presence of multiple exposures at each camera position within the generic network. The effective number of images per station within a hyper redundant network might well be in the range of 10 to 20 or more. As is apparent when it is considered that a hyper redundant network may comprise hundreds of images, the concept is only applicable in practice to fully automatic vision metrology systems, where it proves to be a very effective means of enhancing measurement accuracy at the cost of minimal additional work in the image recording phase. This paper briefly reviews the network design and accuracy aspects of hyper redundancy and illustrates the technique by way of the photogrammetric measurement of surface deformation of a radio telescope of 26 m diameter. This project required an object point measurement accuracy of σ  = 0·065 mm, or 1/400 000 of the diameter of the reflector.     

Stromatoporoid growth forms and Devonian reef fabrics in the Upper Devonian Alexandra Reef System,Canada – Insight on the challenges of applying Devonian reef facies models

Existing facies models for Devonian reef systems can be divided into high‐energy and low‐energy types. A number of assumptions have been made in the development of these models and, in some cases, criteria that distinguish important aspects of the models are poorly defined. The Upper Devonian Alexandra Reef System contains a variety of reef fabrics from different depositional environments and is ideal for studying the range of environments in which stromatoporoids thrived and the facies from these different environments. A wide variety of stromatoporoid growth forms including laminar, tabular, anastamosing laminar and tabular, domal, bulbous, dendroid, expanding conical, concave‐up whorled‐laminar, concave‐up massive tabular and platy‐multicolumnar are present in the Alexandra Reef System. The whorled‐laminar and massive tabular concave‐up growth forms are virtually undocumented from other Devonian reefs but were common in the reef front of the Alexandra, where they thrived in a low‐energy environment around and below fair‐weather wave base. In contrast, high‐energy parts of the reef margin were dominated by bioclastic rubble deposits with narrow ribbon‐like discontinuous bodies of laminar stromatoporoid framestone. In the lagoon, laminar stromatoporoids formed steep‐sided sediment‐dominated bioherms in response to sea‐level rise and flooding. Relying mostly on the different reef facies in the Alexandra system, a new classification scheme for Devonian reef fabrics has been developed. Devonian reef fabrics can be classified as being: (i) sediment‐laden metazoan dominated; (ii) metazoan–microbial dominated (boundstone); (iii) metazoan dominated (framestone); or (iv) metazoan–marine cement dominated. Distinction of these fabrics carries important sedimentary and palaeoecological implications for reconstructing the depositional environment. With examples from the Alexandra Formation, it is demonstrated that reef facies accumulated in a range of depositional environments and that the simple observation of massive stromatoporoids with or without microbial deposits does not automatically imply a high‐energy reef margin, as otherwise portrayed in a number of the existing facies models for these systems.     

Genetic structure of the tall sea pen Funiculina quadrangularis in NW Scottish sea lochs

The tall sea pen Funiculina quadrangularis has a patchy distribution around the UK, being found in sheltered waters below 20 m depth on the northwest coast of Scotland and Ireland. The limited distribution and sensitivity to bottom fishing activities make F. quadrangularis vulnerable to reduction in population numbers that may lead to genetic isolation and reduced diversity. Because of this vulnerability and low resilience to physical disturbance, the tall sea pen is recognised as a Species of Principle Importance under the Natural Environment and Rural Communities Act, 2006, UK. ( http://www.legislation.gov.uk/ukpga/2006/16/contents ) and is also on the Biodiversity Action Plan list of Priority Species for the UK. In the Mediterranean it is recognised as a sensitive and essential fish habitat because it forms habitat for several commercially important crustaceans. The aim of this study was to understand the current state of the genetic structure and gene flow of F. quadrangularis in areas of NW Scotland. We developed 10 microsatellite markers and used them to genotype 176 samples from four populations. Overall, our results suggest that there is high genetic diversity and high gene flow between colonies of F. quadrangularis in and among locations in Loch Linnhe and Loch Duich. As a result of the high rates of gene flow, genetic differentiation between sites was low. This may provide resilience to human impacts if distant populations have a high connectivity. However, care must be taken, as small but significant isolation by distance was found between the most geographically distant sites and only a small part of the species range was examined in this study. The genetic tools developed here will provide a foundation for wider studies of this vulnerable species.     

Experimental validation of the wavefield transform of electromagnetic fields

The wavefield transform is a mathematical technique for transforming low-frequency electromagnetic (EM) signals to a non-diffusive wave domain. The ray approximation is valid in the transform space and this makes traveltime tomography for 3D mapping of the electrical conductivity distribution in the subsurface possible. The transform, however, imposes stringent frequency bandwidth and signal-to-noise ratio requirements on the data. Here we discuss a laboratory scale experiment designed to collect transform quality EM data, and to demonstrate the practical feasibility of transforming these data to the wavefield domain.
We have used the scalable nature of EM fields to design a time-domain experiment using graphite blocks to simulate realistic field conditions while leaving the time scale undisturbed. The spatial dimensions have been scaled down by a factor of a thousand by scaling conductivity up by a factor of a million. The graphite blocks have two holes drilled into them to carry out cross-well and borehole-to-surface experiments. Steel sheets have been inserted between the blocks to simulate a conductive layer.
Our experiments show that accurate EM data can be recorded on a laboratory scale model even when the scaling of some features, such as drill-hole diameters, is not maintained. More importantly, the time-domain EM data recorded in cross-well and surface-to-borehole modes can be usefully and accurately transformed to the wavefield domain. The observed wavefield propagation delay is proportional to the direct distance between the transmitter and receiver in a homogeneous medium. In a layered medium, data accuracy is reduced and, hence, our results are not so conclusive. On the basis of the experimental results we conclude that the wavefield transform could constitute a valid approach to the interpretation of accurate, undistorted time-domain data if further improvement in the transform can be realized.