Mapping reef fish and the seascape: using acoustics and spatial modeling to guide coastal management

Reef fish distributions are patchy in time and space with some coral reef habitats supporting higher densities (i.e., aggregations) of fish than others. Identifying and quantifying fish aggregations (particularly during spawning events) are often top priorities for coastal managers. However, the rapid mapping of these aggregations using conventional survey methods (e.g., non-technical SCUBA diving and remotely operated cameras) are limited by depth, visibility and time. Acoustic sensors (i.e., splitbeam and multibeam echosounders) are not constrained by these same limitations, and were used to concurrently map and quantify the location, density and size of reef fish along with seafloor structure in two, separate locations in the U.S. Virgin Islands. Reef fish aggregations were documented along the shelf edge, an ecologically important ecotone in the region. Fish were grouped into three classes according to body size, and relationships with the benthic seascape were modeled in one area using Boosted Regression Trees. These models were validated in a second area to test their predictive performance in locations where fish have not been mapped. Models predicting the density of large fish (≥29 cm) performed well (i.e., AUC = 0.77). Water depth and standard deviation of depth were the most influential predictors at two spatial scales (100 and 300 m). Models of small (≤11 cm) and medium (12–28 cm) fish performed poorly (i.e., AUC = 0.49 to 0.68) due to the high prevalence (45–79%) of smaller fish in both locations, and the unequal prevalence of smaller fish in the training and validation areas. Integrating acoustic sensors with spatial modeling offers a new and reliable approach to rapidly identify fish aggregations and to predict the density large fish in un-surveyed locations. This integrative approach will help coastal managers to prioritize sites, and focus their limited resources on areas that may be of higher conservation value.

National Status and Trends Bioeffects Program: field methods

Environmental quality indicators provide resource managers with information useful to assess coastal condition and scientifically defensible decisions. Since 1984, the National Oceanic and Atmospheric Administration (NOAA), through its National Status and Trends (NS&T) Program, has provided environmental monitoring data on chemical, physical, and biological indicators of coastal environments. The program has two major monitoring components to meet its goals. The Bioeffects Assessments Program evaluates the health of bays, estuaries, and the coastal zone around the nation using the Sediment Quality Triad technique that includes measuring sediment contaminant concentrations, sediment toxicity and benthic community structure. The Mussel Watch Program is responsible for temporal coastal monitoring of contaminant concentrations by quantifying chemicals in bivalve mollusks. The NS&T Program is committed to providing the highest quality data to meet its statutory and scientific responsibilities. Data, metadata and information products are managed within the guidance protocols and standards set forth by NOAA’s Integrated Ocean Observing System (IOOS) and the National Monitoring Network, as recommended by the 2004 Ocean Action Plan. Thus, to meet these data requirements, quality assurance protocols have been an integral part of the NS&T Program since its inception. Documentation of sampling and analytical methods is an essential part of quality assurance practices. A step-by–step summary of the Bioeffects Program’s field standard operation procedures (SOP) are presented in this manual.

A baseline assessment of the ecological resources of Jobos Bay, Puerto Rico

This baseline assessment of Jobos Bay and surrounding marine ecosystems consists of a two part series. The first report (Zitello et al., 2008) described the characteristics of the Bay and its watershed, including modeling work related to nutrients and sediment fluxes, based on existing data. The second portion of this assessment, presented in this document, presents the results of new field studies conducted to fill data gaps identified in previous studies, to provide a more complete characterization of Jobos Bay and the surrounding coral reef ecosystems. Specifically, the objective was to establish baseline values for the distribution of habitats, nutrients, contaminants, fi sh, and benthic communities. This baseline assessment is the first step in evaluating the effectiveness in changes in best management practices in the watershed. This baseline assessment is part of the Conservation Effects Assessment Project (CEAP), which is a multi-agency effort to quantify the environmental benefits of conservation practices used by agricultural producers participating in selected U.S. Department of Agriculture (USDA) conservation programs. Partners in the CEAP Jobos Bay Special Emphasis Watershed (SEW) included USDA’s Agricultural Research Service (ARS) and the Natural Resources Conservation Service (NRCS), National Oceanic and Atmospheric Administration (NOAA) and the Government of Puerto Rico. The project originated from an on-going collaboration between USDA and NOAA on the U.S. Coral Reef Task Force. The Jobos Bay watershed was chosen because the predominant land use is agriculture, including agricultural lands adjacent to the Jobos Bay National Estuarine Research Reserve (JBNERR or Reserve), one of NOAA’s 26 National Estuarine Research Reserves (NERR). This report is organized into six chapters that represent a suite of interrelated studies. Chapter 1 provides a short introduction to Jobos Bay, including the land use and hydrology of the watershed. Chapter 2 is focused on benthic mapping and provides the methods and results of newly created benthic maps for Jobos Bay and the surrounding coral reef ecosystem. Chapter 3 presents the results of new surveys of fish, marine debris, and reef communities of the system. Chapter 4 is focused on the distribution of chemical contaminants in sediments within the Bay and corals outside of the Bay. Chapter 5 focuses on quantifying nutrient and pesticide concentrations in the surface waters at the Reserve’s System-Wide Monitoring Program (SWMP) sites. Chapter 6 is a brief summary discussion that highlights key findings of the entire suite of studies.

Molecular methods for the genetic identification of salmonid prey from Pacific harbor seal (Phoca vitulina richardsi) scat

Twenty-six stocks of Pacific salmon and trout (Oncorhynchus spp.), representing evolutionary significant units (ESU), are listed as threatened or endangered under the Endangered Species Act (ESA) and six more stocks are currently being evaluated for listing. The ecological and economic consequences of these listings are large; therefore considerable effort has been made to understand and respond to these declining populations. Until recently, Pacific harbor seals (Phoca vitulina richardsi) on the west coast increased an average of 5% to 7% per year as a result of the Marine Mammal Protection Act of 1972 (Brown and Kohlman2). Pacific salmon are seasonally important prey for harbor seals (Roffe and Mate, 1984; Olesiuk, 1993); therefore quantifying and understanding the interaction between these two protected species is important for Morphobiologically sound management strategies. Because some Pacific salmonid species in a given area may be threatened or endangered, while others are relatively abundant, it is important to distinguish the species of salmonid upon which the harbor seals are preying. This study takes the first step in understanding these interactions by using molecular genetic tools for species-level identification of salmonid skeletal remains recovered from Pacific harbor seal scats.

Defects Detection and Assessment in Concrete Surfaces

Aside from cracks, the impact of other surface defects, such as air pockets and discoloration, can be detrimental to the quality of concrete in terms of strength, appearance and durability. For this reason, local and national codes provide standards for quantifying the quality impact of these concrete surface defects and owners plan for regular visual inspections to monitor surface conditions. However, manual visual inspection of concrete surfaces is a qualitative (and subjective) process with often unreliable results due to its reliance on inspectors’ own criteria and experience. Also, it is labor intensive and time-consuming. This paper presents a novel, automated concrete surface defects detection and assessment approach that addresses these issues by automatically quantifying the extent of surface deterioration. According to this approach, images of the surface shot from a certain angle/distance can be used to automatically detect the number and size of surface air pockets, and the degree of surface discoloration. The proposed method uses histogram equalization and filtering to extract such defects and identify their properties (e.g. size, shape, location). These properties are used to quantify the degree of impact on the concrete surface quality and provide a numerical tool to help inspectors accurately evaluate concrete surfaces. The method has been implemented in C++ and results that validate its performance are presented.

Shape vs. volume: Invariant shape descriptors for 3D region of interest characterization in MRI

We propose a new approach for quantifying regions of interest (ROIs) in medical image data. Rotationally invariant shape descriptors (ISDs) were applied to 3D brain regions extracted from MRI scans of 5 Parkinson's patients and 10 control subjects. We concentrated on the thalamus and the caudate nucleus since prior studies have suggested they are affected in Parkinson's disease (PD). In the caudate, both the ISD and volumetric analyses found significant differences between control and PD subjects. The ISD analysis however revealed additional differences between the left and right caudate nuclei in both control and PD subjects. In the thalamus, the volumetric analysis showed significant differences between PD and control subjects, while ISD analysis found significant differences between the left and right thalami in control subjects but not in PD patients, implying disease-induced shape changes. These results suggest that employing ISDs for ROI characterization both complements and extends traditional volumetric analyses. © 2006 IEEE.

Shock Propagation and MPT Noise From a Transonic Rotor in Nonuniform Flow

One of the major challenges in high-speed fan stages used in compact, embedded propulsion systems is inlet distortion noise. A body-force-based approach for the prediction of multiple-pure-tone (MPT) noise was previously introduced and validated. In this paper, it is employed with the objective of quantifying the effects of nonuniform flow on the generation and propagation of MPT noise. First-of-their-kind back-to-back coupled aero-acoustic computations were carried out using the new approach for conventional and serpentine inlets. Both inlets delivered flow to the same NASA/GE R4 fan rotor at equal corrected mass flow rates. Although the source strength at the fan is increased by 38 dB in sound power level due to the nonuniform inflow, far-field noise for the serpentine inlet duct is increased on average by only 3.1 dBA overall sound pressure level in the forward arc. This is due to the redistribution of acoustic energy to frequencies below 11 times the shaft frequency and the apparent cut-off of tones at higher frequencies including blade-passing tones. The circumferential extent of the inlet swirl distortion at the fan was found to be two blade pitches, or 1/11th of the circumference, suggesting a relationship between the circumferential extent of the inlet distortion and the apparent cut-off frequency perceived in the far field. A first-principles-based model of the generation of shock waves from a transonic rotor in nonuniform flow showed that the effects of nonuniform flow on acoustic wave propagation, which cannot be captured by the simplified model, are more dominant than those of inlet flow distortion on source noise. It demonstrated that nonlinear, coupled aerodynamic and aero-acoustic computations, such as those presented in this paper, are necessary to assess the propagation through nonuniform mean flow. A parametric study of serpentine inlet designs is underway to quantify these propagation effects. © 2013 American Society of Mechanical Engineers.

Shock propagation and MPT noise from a transonic rotor in non-uniform flow

One of the major challenges in hig4h-speed fan stages used in compact, embedded propulsion systems is inlet distortion noise. A body-force-based approach for the prediction of multiple-pure-tone (MPT) noise was previously introduced and validated. In this paper, it is employed with the objective of quantifying the effects of non-uniform flow on the generation and propagation of MPT noise. First-of-their-kind back-to-back coupled aero-acoustic computations were carried out using the new approach for conventional and serpentine inlets. Both inlets delivered flow to the same NASA/GE R4 fan rotor at equal corrected mass flow rates. Although the source strength at the fan is increased by 45 dB in sound power level due to the non-uniform inflow, farfield noise for the serpentine inlet duct is increased on average by only 3.1 dBA overall sound pressure level in the forward arc. This is due to the redistribution of acoustic energy to frequencies below 11 times the shaft frequency and the apparent cut-off of tones at higher frequencies including blade-passing tones. The circumferential extent of the inlet swirl distortion at the fan was found to be 2 blade pitches, or 1/11th of the circumference, suggesting a relationship between the circumferential extent of the inlet distortion and the apparent cut-off frequency perceived in the far field. A first-principles-based model of the generation of shock waves from a transonic rotor in non-uniform flow showed that the effects of non-uniform flow on acoustic wave propagation, which cannot be captured by the simplified model, are more dominant than those of inlet flow distortion on source noise. It demonstrated that non-linear, coupled aerodynamic and aeroacoustic computations, such as those presented in this paper, are necessary to assess the propagation through non-uniform mean flow. A parametric study of serpentine inlet designs is underway to quantify these propagation effects. Copyright © 2011 by ASME.

Liquid fuel visualization using laser-induced fluoresence during cold start

The presence of liquid fuel inside the engine cylinder is believed to be a strong contributor to the high levels of hydrocarbon emissions from spark ignition (SI) engines during the warm-up period. Quantifying and determining the fate of the liquid fuel that enters the cylinder is the first step in understanding the process of emissions formation. This work uses planar laser induced fluorescence (PLIF) to visualize the liquid fuel present in the cylinder. The fluorescing compounds in indolene, and mixtures of iso-octane with dopants of different boiling points (acetone and 3-pentanone) were used to trace the behavior of different volatility components. Images were taken of three different planes through the engine intersecting the intake valve region. A closed valve fuel injection strategy was used, as this is the strategy most commonly used in practice. Background subtraction and masking were both performed to reduce the effect of any spurious fluorescence. The images were analyzed on both a time and crank angle (CA) basis, showing the time of maximum liquid fuel present in the cylinder and the effect of engine events on the inflow of liquid fuel. The results show details of the liquid fuel distribution as it enters the engine as a function of crankangle degree, volatility and location in the cylinder. A. semi-quantitative analysis based on the integration of the image intensities provides additional information on the temporal distribution of the liquid fuel flow. © 1998 Society of Automotive Engineers, Inc.

Analysis of high pressure premixed flames using Equivalent Reactor Networks for predicting NOx emissions

This paper describes a computational study of lean premixed high pressure methane-air flames, using Computational Fluid Dynamics (CFD) together with a reactor network approach. A detailed chemical reaction mechanism is employed to predict pollutant concentrations, placing emphasis on nitrogen oxide emissions. The reacting flow field is divided into separate zones in which homogeneity of the physical and chemical conditions prevails. The defined zones are interconnected forming an Equivalent Reactor Network (ERN). Three flames are examined for which experimental data is available. Flame A is characterised by an equivalence ratio of 0.43 while Flames B and C are richer with equivalence ratios of 0.5 and 0.56 respectively. Computations are performed for a range of operating conditions, quantifying the effect in the emitted NOx levels. Model predictions are compared against the available experimental data. Sensitivity analysis is performed to investigate the effect of the network size, in order to define the optimum number of reactors for accurate predictions of the species mass fractions. © 2012 Elsevier Ltd. All rights reserved.

Rapid quantification of total microcystins in cyanobacterial samples by periodate-permanganate oxidation and reversed-phase liquid chromatography

Microcystins (MCs) comprise a family of more than 80 related cyclic hepatotoxic heptapeptides. Oxidation of MCs causes cleavage of the chemically unique C-20 beta-amino acid (2S, 3S, 8S, 9S)-3-amino-9-methoxy-2,6,8-trimethyl-10-phenyldeca-4,6-dienoic acid (Adda) amino to form 2-methyl-3-methoxy-4-phenylbutanoic acid (MMPB), which has been exploited to enable analysis of the entire family. In the present study, the reaction conditions (e.g. concentration of the reactants. temperature and pH) used in the production of MMPB by oxidation of cyanobacterial samples with permanganate-periodate were optimized through a series of well-controlled batch experiments. The oxidation product (MMPB) was then directly analyzed by high-performance liquid chromatography with diode array detection. The results of this study provided insight into the influence of reaction conditions on the yield of MMPB. Specifically, the optimal conditions, including a high dose of permanganate (>= 50 mM) in saturated periodate solution at ambient temperature under alkaline conditions (pH similar to 9) over 1-4 h were proposed, as indicated by a MMPB yield of greater than 85%. The technique developed here was applied to determine the total concentration of MCs in cyanobacterial bloom samples, and indicated that the MMPB technique was a highly sensitive and accurate method of quantifying total MCs. Additionally, these results will aid in development of a highly effective analytical method for detection of MMPB as an oxidation product for evaluation of total MCs in a wide range of environmental sample matrices, including natural waters, soils (sediments) and animal tissues. (C) 2009 Elsevier B.V. All rights reserved.

Nonautonomous contact guidance signaling during collective cell migration.

Directed migration of groups of cells is a critical aspect of tissue morphogenesis that ensures proper tissue organization and, consequently, function. Cells moving in groups, unlike single cells, must coordinate their migratory behavior to maintain tissue integrity. During directed migration, cells are guided by a combination of mechanical and chemical cues presented by neighboring cells and the surrounding extracellular matrix. One important class of signals that guide cell migration includes topographic cues. Although the contact guidance response of individual cells to topographic cues has been extensively characterized, little is known about the response of groups of cells to topographic cues, the impact of such cues on cell-cell coordination within groups, and the transmission of nonautonomous contact guidance information between neighboring cells. Here, we explore these phenomena by quantifying the migratory response of confluent monolayers of epithelial and fibroblast cells to contact guidance cues provided by grooved topography. We show that, in both sparse clusters and confluent sheets, individual cells are contact-guided by grooves and show more coordinated behavior on grooved versus flat substrates. Furthermore, we demonstrate both in vitro and in silico that the guidance signal provided by a groove can propagate between neighboring cells in a confluent monolayer, and that the distance over which signal propagation occurs is not significantly influenced by the strength of cell-cell junctions but is an emergent property, similar to cellular streaming, triggered by mechanical exclusion interactions within the collective system.

Bayesian parameter identification for vibro-acoustic models with nonparametric uncertainty

Vibration and acoustic analysis at higher frequencies faces two challenges: computing the response without using an excessive number of degrees of freedom, and quantifying its uncertainty due to small spatial variations in geometry, material properties and boundary conditions. Efficient models make use of the observation that when the response of a decoupled vibro-acoustic subsystem is sufficiently sensitive to uncertainty in such spatial variations, the local statistics of its natural frequencies and mode shapes saturate to universal probability distributions. This holds irrespective of the causes that underly these spatial variations and thus leads to a nonparametric description of uncertainty. This work deals with the identification of uncertain parameters in such models by using experimental data. One of the difficulties is that both experimental errors and modeling errors, due to the nonparametric uncertainty that is inherent to the model type, are present. This is tackled by employing a Bayesian inference strategy. The prior probability distribution of the uncertain parameters is constructed using the maximum entropy principle. The likelihood function that is subsequently computed takes the experimental information, the experimental errors and the modeling errors into account. The posterior probability distribution, which is computed with the Markov Chain Monte Carlo method, provides a full uncertainty quantification of the identified parameters, and indicates how well their uncertainty is reduced, with respect to the prior information, by the experimental data. © 2013 Taylor & Francis Group, London.

Exploring the use of sensors to measure behavioral interactions: an experimental evaluation of using hand trajectories.

Humans appear to be sensitive to relative small changes in their surroundings. These changes are often initially perceived as irrelevant, but they can cause significant changes in behavior. However, how exactly people's behavior changes is often hard to quantify. A reliable and valid tool is needed in order to address such a question, ideally measuring an important point of interaction, such as the hand. Wearable-body-sensor systems can be used to obtain valuable, behavioral information. These systems are particularly useful for assessing functional interactions that occur between the endpoints of the upper limbs and our surroundings. A new method is explored that consists of computing hand position using a wearable sensor system and validating it against a gold standard reference measurement (optical tracking device). Initial outcomes related well to the gold standard measurements (r = 0.81) showing an acceptable average root mean square error of 0.09 meters. Subsequently, the use of this approach was further investigated by measuring differences in motor behavior, in response to a changing environment. Three subjects were asked to perform a water pouring task with three slightly different containers. Wavelet analysis was introduced to assess how motor consistency was affected by these small environmental changes. Results showed that the behavioral motor adjustments to a variable environment could be assessed by applying wavelet coherence techniques. Applying these procedures in everyday life, combined with correct research methodologies, can assist in quantifying how environmental changes can cause alterations in our motor behavior.

An enzyme-linked immunosorbent assay for rare minnow (Gobiocypris rarus) vitellogenin and comparison of vitellogenin responses in rare minnow and zebrafish (Danio rerio)

A competitive enzyme-linked immunosorbent assay (ELISA) was developed to determine vitellogenin (Vtg) in rare minnow (Gobiocypris rarus) based on the separation and purification of rare minnow Vtg (r-Vtg) as well as the production of polyclonal antibody against r-Vtg in rabbits. Three different ELISAs for measuring r-Vtg were then compared: (1) indirect ELISA with the antibody against carp (Cyprinus carpio) Vtg (c-Vtg) (IC-ELISA); (2) competitive ELISA with the antibody against c-Vtg, and using r-Vtg for coating the plates and preparing standard curve (CC-ELISA); (3) competitive ELISA with the antibody against r-Vtg, and using r-Vtg for coating the plates and preparing standard curve (CR-ELISA). The result showed that the homologous CR-ELISA was the most sensitive among the three assays for quantifying r-Vtg. The sensitivities to 17 alpha-ethinylestradiol (EE2) Of rare minnow and zebrafish (Danio rerio) were compared upon the establishment of homologous competitive ELISA. The lowest observed effect concentrations (LOECs) to induce Vtg were found to be 0.8 ng EE2 l(-1) for rare minnow and 4 ng EE2 l(-1) for zebrafish respectively. Afterwards, CR-ELISA was applied to measure Vtg concentration in whole body homogenate (WBH) of juvenile rare minnow fed by three diets (tubifex from wastewater treatment plant, Artemia nauplii and commercial pellet food), and the agreements between bioassay and GC-MS analysis demonstrated that rare minnow was a sensitive fish model for assessing estrogenic effects of endocrine disrupting compounds in aquatic environment. (c) 2006 Elsevier B.V. All rights reserved.