Modeling seabird group size: implications for ecological impact assessments

The purpose of this project is to model seabird flock size data to provide recommendations to the Bureau of Ocean and Energy Management for offshore wind turbine placement. Our hypothesis is that ecological characteristics influence which statistical distribution will provide the best fit to seabird flock size data. To test this, seabird species can be grouped based on shared ecological traits, such as foraging mechanism or diet.

Deriving acceptable biological catch from the overfishing limit: implications for assessment models

The recently revised Magnuson–Stevens Fishery Conservation and Management Act requires that U.S. fishery management councils avoid overfishing by setting annual catch limits (ACLs) not exceeding recommendations of the councils’ scientific advisers. To meet that requirement, the scientific advisers will need to know the overfishing limit (OFL) estimated in each stock assessment, with OFL being the catch available from applying the limit fishing mortality rate to current or projected stock biomass. The advisers then will derive ‘‘acceptable biological catch’’ (ABC) from OFL by reducing OFL to allow for scientific uncertainty, and ABC becomes their recommendation to the council. We suggest methodology based on simple probability theory by which scientific advisers can compute ABC from OFL and the statistical distribution of OFL as estimated by a stock assessment. Our method includes approximations to the distribution of OFL if it is not known from the assessment; however, we find it preferable to have the assessment model estimate the distribution of OFL directly. Probability-based methods such as this one provide well-defined approaches to setting ABC and may be helpful to scientific advisers as they translate the new legal requirement into concrete advice.

Three-dimensional direct numerical simulations of autoignition in turbulent non-premixed flows with simple and complex chemistry

3D Direct Numerical Simulations (DNS) of autoignition in turbulent non-premixed flows between fuel and hotter air have been carried out using both 1-step and complex chemistry consisting of a 22 species n-heptane mechanism to investigate spontaneous ignition timing and location. The simple chemistry results showed that the previous findings from 2D DNS that ignition occurred at the most reactive mixture fraction (ξMR) and at small values of the conditional scalar dissipation rate (N|ξMR) are valid also for 3D turbulent mixing fields. Performing the same simulation many times with different realizations of the initial velocity field resulted in a very narrow statistical distribution of ignition delay time, consistent with a previous conjecture that the first appearance of ignition is correlated with the low-N content of the conditional probability density function of N. The simulations with complex chemistry for conditions outside the Negative Temperature Coefficient (NTC) regime show behaviour similar to the single-step chemistry simulations. However, in the NTC regime, the most reactive mixture fraction is very rich and ignition seems to occur at high values of scalar dissipation. Copyright © 2006 by ASME.

The Modeling of Ion Implantation in a Three-Layer Structure Using the Method of Dose Matching

The method of modeling ion implantation in a multilayer target using moments of a statistical distribution and numerical integration for dose calculation in each target layer is applied to the modelling of As⁺ in poly-Si/SiO2/Si. Good agreement with experiment is obtained. Copyright © 1985 by The Institute of Electrical and Electronics Engineers, Inc.

Photoluminescence study on coarsening of self-assembled InAlAs quantum dots on GaAs (001)

Red-emission at similar to 640 nm from self-assembled In0.55Al0.45As/Al0.5Ga0.5As quantum dots grown on GaAs substrate by molecular beam epitaxy (MBE) has been demonstrated. We obtained a double-peak structure of photoluminescence (PL) spectra from quantum dots. An atomic force micrograph (AFM) image for uncapped sample also shows a bimodal distribution of dot sizes. From the temperature and excitation intensity dependence of PL spectra, we found that the double-peak structure of PL spectra from quantum dots was strongly correlated to the two predominant quantum dot families. Taking into account quantum-size effect on the peak energy, we propose that the high (low) energy peak results from a smaller (larger) dot family, and this result is identical with the statistical distribution of dot lateral size from the AFM image.

Photoluminescence study on coarsening of self-assembled InAlAs quantum dots on GaAs (001)

Red-emission at similar to 640 nm from self-assembled In0.55Al0.45As/Al0.5Ga0.5As quantum dots grown on GaAs substrate by molecular beam epitaxy (MBE) has been demonstrated. We obtained a double-peak structure of photoluminescence (PL) spectra from quantum dots. An atomic force micrograph (AFM) image for uncapped sample also shows a bimodal distribution of dot sizes. From the temperature and excitation intensity dependence of PL spectra, we found that the double-peak structure of PL spectra from quantum dots was strongly correlated to the two predominant quantum dot families. Taking into account quantum-size effect on the peak energy, we propose that the high (low) energy peak results from a smaller (larger) dot family, and this result is identical with the statistical distribution of dot lateral size from the AFM image.

Computer simulation of the damage evolution of fiber-reinforced polypropylene-matrix composites with matrix defects

The damage evolution of fiber-reinforced polypropylene-matrix composites with matrix defects was studied via a Monte Carlo technique combined with a finite element method. A finite element model was constructed to predict the effects of various matrix defect shapes on the stress distributions. The results indicated that a small matrix defect had almost no effect on fiber stress distributions other than interfacial shear stress distributions. Then, a finite element model with a statistical distribution of the fiber strength was constructed to investigate the influences of the spatial distribution and the volume fraction of matrix defects on composite failure. The results showed that it was accurate to use the shear-lag models and Green's function methods to predict the tensile strength of composites even though the axial stresses in the matrix were neglected.

Evaluation of a combined wavelet and a combined principal component analysis classification system for BCG diagnostic problem

Heart disease is one of the main factor causing death in the developed countries. Over several decades, variety of electronic and computer technology have been developed to assist clinical practices for cardiac performance monitoring and heart disease diagnosis. Among these methods, Ballistocardiography (BCG) has an interesting feature that no electrodes are needed to be attached to the body during the measurement. Thus, it is provides a potential application to asses the patients heart condition in the home. In this paper, a comparison is made for two neural networks based BCG signal classification models. One system uses a principal component analysis (PCA) method, and the other a discrete wavelet transform, to reduce the input dimensionality. It is indicated that the combined wavelet transform and neural network has a more reliable performance than the combined PCA and neural network system. Moreover, the wavelet transform requires no prior knowledge of the statistical distribution of data samples and the computation complexity and training time are reduced.

块体理论赤平投影解析法与关键块体滑落概率研究—以锦屏二级水电站皮带机隧道为例

Block theory is an effective method on stability analysis of fractured rigid rock mass. There are a lot of discontinuous planes developed in rock mass of Jinping II hydropower station conveyor tunnel, so the stability of conveyor tunnel is related with whether there are unstable blocks on excavation planes. This paper deals with the stability of conveyor tunnel with stereo-analytical method for block theory on the basis of detailed investigation of rock mass data, and makes judgements on the movable blocks sliding types which are induced by all rock discontinuous planes and every excavation plane of conveyor tunnel. A conclusion is obtained that the sliding type of blocks is mainly single sliding, and a relatively few sliding types of double-sided sliding and vertical block falling; Also, the obvious statistical distribution result on movable blocks in conveyor tunnel indicates that there are a bit more instability blocks in left wall, left and right arches than right wall. In this paper, the stochastic probability model is drawn into block theory to study the sliding probability of key block on the basis of detailed investigation of its rock mass data and the development of the discontinuous planes in rock mass of Jinping II hydropower station conveyor tunnel. And some following conclusions are obtained. The relationship between trace length and the probability of instability of key block is inverse ratio. The probability of 1-3m primary joints are relatively higher. Key block containing joints J2 is relatively stable and the reinforcement of the arch would be crucial in the conveyor tunnel. They are all useful to offer effective reinforcement design and have important engineering values.

Distribuições estatísticas, testes de ajuste e métodos para estimação de parâmetros na área da fiabilidade

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Storm tracks and climate change

Extratropical and tropical transient storm tracks are investigated from the perspective of feature tracking in the ECHAM5 coupled climate model for the current and a future climate scenario. The atmosphere-only part of the model, forced by observed boundary conditions, produces results that agree well with analyses from the 40-yr ECMWF Re-Analysis (ERA-40), including the distribution of storms as a function of maximum intensity. This provides the authors with confidence in the use of the model for the climate change experiments. The statistical distribution of storm intensities is virtually preserved under climate change using the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario until the end of this century. There are no indications in this study of more intense storms in the future climate, either in the Tropics or extratropics, but rather a minor reduction in the number of weaker storms. However, significant changes occur on a regional basis in the location and intensity of storm tracks. There is a clear poleward shift in the Southern Hemisphere with consequences of reduced precipitation for several areas, including southern Australia. Changes in the Northern Hemisphere are less distinct, but there are also indications of a poleward shift, a weakening of the Mediterranean storm track, and a strengthening of the storm track north of the British Isles. The tropical storm tracks undergo considerable changes including a weakening in the Atlantic sector and a strengthening and equatorward shift in the eastern Pacific. It is suggested that some of the changes, in particular the tropical ones, are due to an SST warming maximum in the eastern Pacific. The shift in the extratropical storm tracks is shown to be associated with changes in the zonal SST gradient in particular for the Southern Hemisphere.

Estimating uncertainty in terrestrial critical loads and their exceedances at four sites in the UK

Critical loads are the basis for policies controlling emissions of acidic substances in Europe and elsewhere. They are assessed by several elaborate and ingenious models, each of which requires many parameters, and have to be applied on a spatially-distributed basis. Often the values of the input parameters are poorly known, calling into question the validity of the calculated critical loads. This paper attempts to quantify the uncertainty in the critical loads due to this "parameter uncertainty", using examples from the UK. Models used for calculating critical loads for deposition of acidity and nitrogen in forest and heathland ecosystems were tested at four contrasting sites. Uncertainty was assessed by Monte Carlo methods. Each input parameter or variable was assigned a value, range and distribution in an objective a fashion as possible. Each model was run 5000 times at each site using parameters sampled from these input distributions. Output distributions of various critical load parameters were calculated. The results were surprising. Confidence limits of the calculated critical loads were typically considerably narrower than those of most of the input parameters. This may be due to a "compensation of errors" mechanism. The range of possible critical load values at a given site is however rather wide, and the tails of the distributions are typically long. The deposition reductions required for a high level of confidence that the critical load is not exceeded are thus likely to be large. The implication for pollutant regulation is that requiring a high probability of non-exceedance is likely to carry high costs. The relative contribution of the input variables to critical load uncertainty varied from site to site: any input variable could be important, and thus it was not possible to identify variables as likely targets for research into narrowing uncertainties. Sites where a number of good measurements of input parameters were available had lower uncertainties, so use of in situ measurement could be a valuable way of reducing critical load uncertainty at particularly valuable or disputed sites. From a restricted number of samples, uncertainties in heathland critical loads appear comparable to those of coniferous forest, and nutrient nitrogen critical loads to those of acidity. It was important to include correlations between input variables in the Monte Carlo analysis, but choice of statistical distribution type was of lesser importance. Overall, the analysis provided objective support for the continued use of critical loads in policy development. (c) 2007 Elsevier B.V. All rights reserved.

LiDAR mapping of tidal marshes for ecogeomorphological modelling in the TIDE project

The European research project TIDE (Tidal Inlets Dynamics and Environment) is developing and validating coupled models describing the morphological, biological and ecological evolution of tidal environments. The interactions between the physical and biological processes occurring in these regions requires that the system be studied as a whole rather than as separate parts. Extensive use of remote sensing including LiDAR is being made to provide validation data for the modelling. This paper describes the different uses of LiDAR within the project and their relevance to the TIDE science objectives. LiDAR data have been acquired from three different environments, the Venice Lagoon in Italy, Morecambe Bay in England, and the Eden estuary in Scotland. LiDAR accuracy at each site has been evaluated using ground reference data acquired with differential GPS. A semi-automatic technique has been developed to extract tidal channel networks from LiDAR data either used alone or fused with aerial photography. While the resulting networks may require some correction, the procedure does allow network extraction over large areas using objective criteria and reduces fieldwork requirements. The networks extracted may subsequently be used in geomorphological analyses, for example to describe the drainage patterns induced by networks and to examine the rate of change of networks. Estimation of the heights of the low and sparse vegetation on marshes is being investigated by analysis of the statistical distribution of the measured LiDAR heights. Species having different mean heights may be separated using the first-order moments of the height distribution.

Reduced space optimal interpolation of daily rain gauge precipitation in Switzerland

The coarse spacing of automatic rain gauges complicates near-real- time spatial analyses of precipitation. We test the possibility of improving such analyses by considering, in addition to the in situ measurements, the spatial covariance structure inferred from past observations with a denser network. To this end, a statistical reconstruction technique, reduced space optimal interpolation (RSOI), is applied over Switzerland, a region of complex topography. RSOI consists of two main parts. First, principal component analysis (PCA) is applied to obtain a reduced space representation of gridded high- resolution precipitation fields available for a multiyear calibration period in the past. Second, sparse real-time rain gauge observations are used to estimate the principal component scores and to reconstruct the precipitation field. In this way, climatological information at higher resolution than the near-real-time measurements is incorporated into the spatial analysis. PCA is found to efficiently reduce the dimensionality of the calibration fields, and RSOI is successful despite the difficulties associated with the statistical distribution of daily precipitation (skewness, dry days). Examples and a systematic evaluation show substantial added value over a simple interpolation technique that uses near-real-time observations only. The benefit is particularly strong for larger- scale precipitation and prominent topographic effects. Small-scale precipitation features are reconstructed at a skill comparable to that of the simple technique. Stratifying the reconstruction method by the types of weather type classifications yields little added skill. Apart from application in near real time, RSOI may also be valuable for enhancing instrumental precipitation analyses for the historic past when direct observations were sparse.

The role of increasing temperature variability in European summer heatwaves

Instrumental observations1, 2 and reconstructions3, 4 of global and hemispheric temperature evolution reveal a pronounced warming during the past 150 years. One expression of this warming is the observed increase in the occurrence of heatwaves5, 6. Conceptually this increase is understood as a shift of the statistical distribution towards warmer temperatures, while changes in the width of the distribution are often considered small7. Here we show that this framework fails to explain the record-breaking central European summer temperatures in 2003, although it is consistent with observations from previous years. We find that an event like that of summer 2003 is statistically extremely unlikely, even when the observed warming is taken into account. We propose that a regime with an increased variability of temperatures (in addition to increases in mean temperature) may be able to account for summer 2003. To test this proposal, we simulate possible future European climate with a regional climate model in a scenario with increased atmospheric greenhouse-gas concentrations, and find that temperature variability increases by up to 100%, with maximum changes in central and eastern Europe.