Dispersal Modeling of Fish Early Life Stages: Sensitivity with Application to Atlantic Cod in the Western Gulf of Maine

As an initial step in establishing mechanistic relationships between environmental variability and recruitment in Atlantic cod Gadhus morhua along the coast of the western Gulf of Maine, we assessed transport success of larvae from major spawning grounds to nursery areas with particle tracking using the unstructured grid model FVCOM (finite volume coastal ocean model). In coastal areas, dispersal of early planktonic life stages of fish and invertebrate species is highly dependent on the regional dynamics and its variability, which has to be captured by our models. With state-of-the-art forcing for the year 1995, we evaluate the sensitivity of particle dispersal to the timing and location of spawning, the spatial and temporal resolution of the model, and the vertical mixing scheme. A 3 d frequency for the release of particles is necessary to capture the effect of the circulation variability into an averaged dispersal pattern of the spawning season. The analysis of sensitivity to model setup showed that a higher resolution mesh, tidal forcing, and current variability do not change the general pattern of connectivity, but do tend to increase within-site retention. Our results indicate strong downstream connectivity among spawning grounds and higher chances for successful transport from spawning areas closer to the coast. The model run for January egg release indicates 1 to 19 % within-spawning ground retention of initial particles, which may be sufficient to sustain local populations. A systematic sensitivity analysis still needs to be conducted to determine the minimum mesh and forcing resolution that adequately resolves the complex dynamics of the western Gulf of Maine. Other sources of variability, i.e. large-scale upstream forcing and the biological environment, also need to be considered in future studies of the interannual variability in transport and survival of the early life stages of cod

FVCOM validation experiments : comparisons with ROMS for three idealized barotropic test problems

Author Posting. © American Geophysical Union, 2008. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 113 (2008): C07042, doi:10.1029/2007JC004557.The unstructured-grid Finite-Volume Coastal Ocean Model (FVCOM) is evaluated using three idealized benchmark test problems: the Rossby equatorial soliton, the hydraulic jump, and the three-dimensional barotropic wind-driven basin. These test cases examine the properties of numerical dispersion and damping, the performance of the nonlinear advection scheme for supercritical flow conditions, and the accuracy of the implicit vertical viscosity scheme in barotropic settings, respectively. It is demonstrated that FVCOM provides overall a second-order spatial accuracy for the vertically averaged equations (i.e., external mode), and with increasing grid resolution the model-computed solutions show a fast convergence toward the analytic solutions regardless of the particular triangulation method. Examples are provided to illustrate the ability of FVCOM to facilitate local grid refinement and speed up computation. Comparisons are also made between FVCOM and the structured-grid Regional Ocean Modeling System (ROMS) for these test cases. For the linear problem in a simple rectangular domain, i.e., the wind-driven basin case, the performance of the two models is quite similar. For the nonlinear case, such as the Rossby equatorial soliton, the second-order advection scheme used in FVCOM is almost as accurate as the fourth-order advection scheme implemented in ROMS if the horizontal resolution is relatively high. FVCOM has taken advantage of the new development in computational fluid dynamics in resolving flow problems containing discontinuities. One salient feature illustrated by the three-dimensional barotropic wind-driven basin case is that FVCOM and ROMS simulations show different responses to the refinement of grid size in the horizontal and in the vertical.For this work, H. Huang and G. Cowles were supported by the Massachusetts Marine Fisheries Institute (MFI) through NOAA grants DOC/NOAA/NA04NMF4720332 and DOC/ NOAA/NA05NMF472113; C. Chen was supported by NSF grants (OCE0234545, OCE0606928, OCE0712903, OCE0732084, and OCE0726851), NOAA grants (NA160P2323, NA06RG0029, and NA960P0113), MIT Sea grant (2006-RC-103), and Georgia Sea grant (NA26RG0373 and NA66RG0282); C. Winant was supported through NSF grant OCE-0726673; R. Beardsley was supported through NSF OCE—0227679 and the WHOI Smith Chair; K. Hedstrom was supported through NASA grant NAG13– 03021 and the Arctic Region Supercomputing Center; and D. Haidvogel was supported through grants ONR N00014- 03-1-0683 and NSF OCE 043557

Traps of multi-level governance. Lessons from the implementation of the Water Framework Directive in Italy

During recent decades, different patterns of multi-level governance (MLG) have spread across Europe as a consequence of Europeanisation of public policies, which have increasingly adopted decentralized and participatory procedures conceived as a tool of more effective and accountable policy-making. It appears, however, that the implementation of operational designs based on MLG may be rather problematic and it does not necessarily bring to the expected performance improvements. Referring to the case of the EU Water Framework Directive (2000/60/EC), which conceives the creation of new multi-level institutional settings as a key tool for enacting a new holistic approach to water management and protection, this article explores the difficulties that the implementation of such settings has brought in Italy, despite some favorable pre-conditions existing in the country. Evidence is provided that along with institutional and agency variables, the implementation effectiveness of MLG arrangements promoted by the EU can be challenged by their inherent characteristics

Using Markov chain Monte Carlo methods for estimating parameters with gravitational radiation data

We present a Bayesian approach to the problem of determining parameters for coalescing binary systems observed with laser interferometric detectors. By applying a Markov Chain Monte Carlo (MCMC) algorithm, specifically the Gibbs sampler, we demonstrate the potential that MCMC techniques may hold for the computation of posterior distributions of parameters of the binary system that created the gravity radiation signal. We describe the use of the Gibbs sampler method, and present examples whereby signals are detected and analyzed from within noisy data.Comment: 21 pages, 10 figure

Enhancement and suppression effects resulting from information structuring in sentences

Information structuring through the use of cleft sentences increases the processing efficiency of references to elements within the scope of focus. Furthermore, there is evidence that putting certain types of emphasis on individual words not only enhances their subsequent processing, but also protects these words from becoming suppressed in the wake of subsequent information, suggesting mechanisms of enhancement and suppression. In Experiment 1, we showed that clefted constructions facilitate the integration of subsequent sentences that make reference to elements within the scope of focus, and that they decrease the efficiency with reference to elements outside of the scope of focus. In Experiment 2, using an auditory text-change-detection paradigm, we showed that focus has similar effects on the strength of memory representations. These results add to the evidence for enhancement and suppression as mechanisms of sentence processing and clarify that the effects occur within sentences having a marked focus structure

Comparison of observed and model-computed low frequency circulation and hydrography on the New England Shelf

Author Posting. © American Geophysical Union, 2008. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 113 (2008): C09015, doi:10.1029/2007JC004394.The finite volume coastal ocean model (FVCOM) is configured to study the interannual variability of circulation in the Gulf of Maine (GoM) and Georges Bank. The FVCOM-GoM system incorporates realistic time-dependent surface forcing derived from a high-resolution mesoscale meteorological model (MM5) and assimilation of observed quantities including sea surface temperature and salinity and temperature fields on the open boundary. An evaluation of FVCOM-GoM model skill on the New England shelf is made by comparison of computed fields and data collected during the Coastal Mixing and Optics (CMO) Program (August 1996–June 1997). Model mean currents for the full CMO period compare well in both magnitude and direction in fall and winter but overpredict the westward flow in spring. The direction and ellipticity of the subtidal variability correspond but computed magnitudes are around 20% below observed, partially due to underprediction of the variability by MM5. Response of subtidal currents to wind-forcing shows the model captures the directional dependence, as well as seasonal variability of the lag. Hydrographic results show that FVCOM-GoM resolves the spatial and temporal evolution of the temperature and salinity fields. The model-computed surface salinity field compares well, except in May when there is no indication of the fresh surface layer from the Connecticut River discharge noted in the observations. Analysis of model-computed results indicates that the plume was unable to extend to the mooring location due to the presence of a westward mean model-computed flow during that time that was stronger than observed. Overall FVCOM-GoM captures well the dynamics of the mean and subtidal flow on the New England shelf.G. Cowles was supported by the Massachusetts Marine Fisheries Institute (MFI) through NOAA grants DOC/NOAA/ NA04NMF4720332 and DOC/NOAA/NA05NMF4721131, S. Lentz by the NSF Ocean Sciences Division through grants OCE-841292 and OCE- 848961, C. Chen and Q. Xu through the NSF/NOAA GLOBEC/Northwest Atlantic/Georges Bank Program under NSF grants OCE-0234545 and OCE-0227679 and NOAA grants NA-16OP2323, and R. Beardsley through NOAA grant NA-17RJ1223

Understanding Face and Shame: A Servant-Leadership and Face Management Model

Clergy can have a negative impact on churches and other individuals when they knowingly or unknowingly attempt to save face, that is, try to protect their standing or reputation. The desire to gain face and the fear of losing face and feeling ashamed will likely permeate clergy’s decision-making processes without even being noticed. This study explores the essence of face and face management and the relationship between face management and two characteristics of servant-leadership—awareness and healing—in both Chinese and American churches through the methodology of hermeneutic phenomenology. Prior to this study, to my knowledge, no hermeneutic phenomenological research of face management has been conducted in a church setting. Through a review of the literature, four areas are explored: face and shame, face management, servant-leadership, and face, shame, and face management within the church. This study obtained approval from the Institutional Review Board and informed consent from the participants. Three Chinese and three American Christian ministers were chosen to complete a question sheet and participate in two semi-structured interview sessions. A first cycle of open coding and second cycle of pattern coding were used during data analysis. Face experiences are discussed in light of eight major themes: body, triggers, becoming, face concepts, strategies, emotions, servant-leadership, and the church. Findings from the study help build a servant-leadership and face management model, which can offer an anchored approach for clergy and pastoral counselors to address face and shame and to develop therapeutic interventions

A new ghost cell/level set method for moving boundary problems:application to tumor growth

In this paper, we present a ghost cell/level set method for the evolution of interfaces whose normal velocity depend upon the solutions of linear and nonlinear quasi-steady reaction-diffusion equations with curvature-dependent boundary conditions. Our technique includes a ghost cell method that accurately discretizes normal derivative jump boundary conditions without smearing jumps in the tangential derivative; a new iterative method for solving linear and nonlinear quasi-steady reaction-diffusion equations; an adaptive discretization to compute the curvature and normal vectors; and a new discrete approximation to the Heaviside function. We present numerical examples that demonstrate better than 1.5-order convergence for problems where traditional ghost cell methods either fail to converge or attain at best sub-linear accuracy. We apply our techniques to a model of tumor growth in complex, heterogeneous tissues that consists of a nonlinear nutrient equation and a pressure equation with geometry-dependent jump boundary conditions. We simulate the growth of glioblastoma (an aggressive brain tumor) into a large, 1 cm square of brain tissue that includes heterogeneous nutrient delivery and varied biomechanical characteristics (white matter, gray matter, cerebrospinal fluid, and bone), and we observe growth morphologies that are highly dependent upon the variations of the tissue characteristics—an effect observed in real tumor growth

Inferring signalling networks from longitudinal data using sampling based approaches in the R-package 'ddepn'

<p>Abstract</p> <p>Background</p> <p>Network inference from high-throughput data has become an important means of current analysis of biological systems. For instance, in cancer research, the functional relationships of cancer related proteins, summarised into signalling networks are of central interest for the identification of pathways that influence tumour development. Cancer cell lines can be used as model systems to study the cellular response to drug treatments in a time-resolved way. Based on these kind of data, modelling approaches for the signalling relationships are needed, that allow to generate hypotheses on potential interference points in the networks.</p> <p>Results</p> <p>We present the R-package 'ddepn' that implements our recent approach on network reconstruction from longitudinal data generated after external perturbation of network components. We extend our approach by two novel methods: a Markov Chain Monte Carlo method for sampling network structures with two edge types (activation and inhibition) and an extension of a prior model that penalises deviances from a given reference network while incorporating these two types of edges. Further, as alternative prior we include a model that learns signalling networks with the scale-free property.</p> <p>Conclusions</p> <p>The package 'ddepn' is freely available on R-Forge and CRAN <url>http://ddepn.r-forge.r-project.org</url>, <url>http://cran.r-project.org</url>. It allows to conveniently perform network inference from longitudinal high-throughput data using two different sampling based network structure search algorithms.</p