Existing Modeling Approaches Research Articles

Eco‐genetic modeling of contemporary life‐history evolution

We present eco-genetic modeling as a flexible tool for exploring the course and rates of multi-trait life-history evolution in natural populations. We build on existing modeling approaches by combining features that facilitate studying the ecological and evolutionary dynamics of realistically structured populations. In particular, the joint consideration of age and size structure enables the analysis of phenotypically plastic populations with more than a single growth trajectory, and ecological feedback is readily included in the form of density dependence and frequency dependence. Stochasticity and life-history trade-offs can also be implemented. Critically, eco-genetic models permit the incorporation of salient genetic detail such as a population's genetic variances and covariances and the corresponding heritabilities, as well as the probabilistic inheritance and phenotypic expression of quantitative traits. These inclusions are crucial for predicting rates of evolutionary change on both contemporary and longer timescales. An eco-genetic model can be tightly coupled with empirical data and therefore may have considerable practical relevance, in terms of generating testable predictions and evaluating alternative management measures. To illustrate the utility of these models, we present as an example an eco-genetic model used to study harvest-induced evolution of multiple traits in Atlantic cod. The predictions of our model (most notably that harvesting induces a genetic reduction in age and size at maturation, an increase or decrease in growth capacity depending on the minimum-length limit, and an increase in reproductive investment) are corroborated by patterns observed in wild populations. The predicted genetic changes occur together with plastic changes that could phenotypically mask the former. Importantly, our analysis predicts that evolutionary changes show little signs of reversal following a harvest moratorium. This illustrates how predictions offered by eco-genetic models can enable and guide evolutionarily sustainable resource management.

The consideration of long-term emissions from landfills within life-cycle assessment

Within a product system of a life-cycle assessment (LCA), solid waste landfills should be treated as processes, because they are considered to be a part of the technical system. Hence, their inputs and outputs should be included in the life-cycle inventory analysis and evaluated within the life-cycle impact assessment. The aim of this paper is to discuss the consideration of emissions from solid waste landfills within the LCA framework and to investigate the uncertainties in existing modelling approaches. Based on this analysis the main limitations are discussed and recommendations for incorporating long-term emissions from landfills in LCA are made. It is emphasized that the lack of consideration of spatial and temporal characteristics of long-term emissions turns out to be an important source of uncertainty when modelling the environmental impact of landfills. For toxicity categories in particular, the life-cycle impact assessment might be the dominant source of uncertainty. However, in order to understand the reliability of LCA results with respect to landfill emissions, quantitative uncertainty should be routinely included in LCA studies and sources of uncertainty need to be thoroughly discussed.

Diesel Particulate Matter Number Emissions: Evaluation of Existing Modal Emission Modeling Approaches

Recent health and exposure studies have indicated that emissions and air quality standards of particulate matters (PM) numbers could be beneficial since they account for the more harmful ultrafine particles that have negligible mass. This study examines existing modal emission modeling approaches [e.g., polynomial regressions, fuel rate-based approach, and vehicle specific power (VSP)-based approach] in order to evaluate their ability of predicting diesel particle number concentration emitted from a transit diesel bus. This is a necessary and useful first step to quantifying vehicular emissions in terms of PM number. The existing modeling approaches were applied to and then the technique of bootstrapping was used on the onboard measurement data of PM number concentrations emitted from a diesel transit bus. The predictive ability of the models with respect to particle number concentration is assessed by examining the statistical significance of the key regressors used in those approaches and the adjusted R-squared values of the models. Results indicate less than satisfying predictive capability of the examined approaches for PM number emission that behaves in a different manner from gaseous emissions. The study, however, demonstrates that vehicle operating factors such as VSP, speed, and acceleration are significant in explaining the variability of transient PM number concentration measurements from the bus.

Estimating population size, structure, and residency time for whale sharks Rhincodon typus through collaborative photo-identification

ESR Endangered Species Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials ESR 7:39-53 (2009) - DOI: https://doi.org/10.3354/esr00186 Estimating population size, structure, and residency time for whale sharks Rhincodon typus through collaborative photo-identification Jason Holmberg1,2,*, Bradley Norman3, Zaven Arzoumanian2,4 1ECOCEAN USA, 4836 NE 31st Avenue, Portland, Oregon 92711, USA 2Centre for Fish and Fisheries Research, Murdoch University, South Street, Murdoch, Western Australia 6150, Australia 3ECOCEAN, c/o Centre for Fish and Fisheries Research, Murdoch University, South Street, Murdoch, Western Australia 6150, Australia 4Present address: Universities Space Research Association, 10211 Wincopin Circle, Columbia, Maryland 21044, USA *Email: jason@whaleshark.org ABSTRACT: Capture-mark-recapture (CMR) data from Ningaloo Marine Park (NMP) in Western Australia have recently been used to study the population dynamics of the local whale shark aggregation. Because nascent research efforts at other aggregation points look to NMP as a model, further analysis of existing modeling approaches is important. We have expanded upon previous studies of NMP whale sharks by estimating CMR survival and recruitment rates as functions of average total length (TL). Our analysis suggests a decline in reported values of TL coincident with marginally increasing abundance among sharks sighted in more than one year (‘returning’) from 1995 to 2008. We found a positive, average returning recruitment rate (λ) of 1.07 yr–1 (0.99 to 1.15, 95% CI); smaller individuals contributed in larger numbers to recruitment, allowing for population growth accompanied by a decline in median size. We subsequently explored intraseasonal population dynamics with the Open Robust Design (ORD) model structure. Our best-fit model estimated modestly increasing annual abundances between 107 (95% CI = 90 to 124) and 159 (95% CI = 127 to 190) for 2004 to 2007, suggesting a short-term increase in total annual abundance. The ORD also estimated an average residency time of 33 d (95% CI = 31 to 39) and biweekly entry profiles into the study area. Overall, our techniques demonstrate how large aggregations of the species can be modeled to better understand short- and long-term population trends. These results also show the direct scientific benefit from the development of an online, collaborative data management system to increase collection of sighting data for a rare species in conjunction with ecotourism activity. KEY WORDS: Mark-recapture · Open Robust Design · Population biology · Rhincodon typus · Survivorship · Transience · Whale shark Full text in pdf format PreviousNextCite this article as: Holmberg J, Norman B, Arzoumanian Z (2009) Estimating population size, structure, and residency time for whale sharks Rhincodon typus through collaborative photo-identification. Endang Species Res 7:39-53. https://doi.org/10.3354/esr00186 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in ESR Vol. 7, No. 1. Online publication date: April 08, 2009 Print ISSN: 1863-5407; Online ISSN: 1613-4796 Copyright © 2009 Inter-Research.

Maximising coverage of spatial demand for service

AbstractHow to represent geographic space has long been an issue in location modelling. Facilities, demand and/or the region of interest are often abstracted using aggregated points. However, substantial errors can be introduced, and obtained solutions could be dependent on the degree of aggregation. To address this, geographic representation of space is undergoing renewed research interest in spatial analysis and modelling. In this article the maximal coverage problem is studied, with a particular focus on demand coverage representation. Due to the limitations of existing modelling approaches for examining the coverage of space, there exist significant discrepancies between what is modelled and actual geographic coverage. In order to accurately reflect the mechanism of maximal coverage for spatial objects (points, lines or polygons), we introduce a new model explicitly accounting for joint service provided by multiple facilities. The new model can be viewed as an extension of existing approaches, but also a generalisation. An application to warning siren siting is carried out to demonstrate the merits of this new approach.

A fibre flexure–shear model for seismic analysis of RC‐framed structures

AbstractWhile currently existing modelling approaches of reinforced concrete (RC) behaviour allow a reasonably accurate prediction of flexural response, the determination of its shear counterpart needs further developments. There are various modelling strategies in the literature able to predict the shear response and the shear–flexure coupling under monotonic loading conditions. However, very few are the reported models that have demonstrated successful results under cyclic loading, as in the seismic load case. These considerations lead to this research work focused on the development of a flexure–shear model for RC beam–column elements. A reliable constitutive model for cracked RC subjected to cyclic loading was implemented as bi‐axial fibre constitutive model into a two‐dimensional Timoshenko beam–column element. Aim of this research work is to arrive at the definition of a numerical model sufficiently accurate and, at the same time, computationally efficient, which will enable implementation within a finite element package for nonlinear dynamic analysis of existing non‐seismically designed RC structures that are prone to shear‐induced damage and collapse. Copyright © 2009 John Wiley & Sons, Ltd.

Methods to describe and predict soil erosion in mountain regions

Suitable methods to describe and predict soil degradation in mountain areas with low accessibility, steep topography and extreme climate are urgently needed for suitable planning processes in Alpine regions under global change regime. Aerial photograph mapping has been proven to be a valuable tool in surveying landslide development over time. However, landslides < 10 m 2 as well as sheet erosion have been difficult to detect. Thus, the beginning of potentially heavy soil degradation cannot be tracked with aerial photographs. As an early warning system for soil degradation, we analyzed gradients of stable isotopes of carbon and nitrogen from upland (erosion source) to wetland soils (erosion sink). Oxic upland soils and anoxic wetlands differ in their isotopic signature, due to differing isotopic fingerprints of aerobic and anaerobic metabolism in soils. Gradients of δ 15N and δ 13C in soils reflected erosion of material. However, if soils were fertilized with manure, the δ 15N profiles were obscured. To quantify soil erosion, we noted that existing soil erosion models are generally unsuitable for mountain regions. As a first step, we developed a new modelling concept with a special algorithm for spatial discretization with irregular grids. The latter ensures three-dimensional water flow routing that is controlled by topography and not by the underlying algorithm. Regarding quantification of soil erosion an improvement and validation of existing modelling approaches or development of new models is urgently needed.

Modelling of essential fish habitat based on remote sensing, spatial analysis and GIS

We review the variety of existing modelling approaches applied to species habitat mapping and we discuss issues arising from the availability and nature of sampled biological data and corresponding ecological and environmental habitat descriptors, as well as the different spatial analysis approaches that are selected according to specific hypotheses. We focus on marine species habitat mapping, presenting an overview of work on modelling fish habitat carried out through a European Communities Policy-Support Action, EnviEFH ‘Environmental Approach to Essential Fish Habitat (EFH) Designation’ (2005–2008). The selection of the appropriate habitat model is dataset-specific and the resulting EFH maps are often similar in spite of using different models. Derived EFH maps are based on either environmental ranges (used as minimum and maximum environmental habitat descriptors) or probability of occurrence values. We apply model outputs to regions larger than sampled areas making use of the capacity of satellite data to cover wide areas.

Strain rate effects on the mechanical response of polypropylene-based composites deformed at small strains

The mechanical properties and response of two polypropylene (PP)-based composites have been determined for small strains and for a range of strain rates in the quasi-static domain. These two materials are talc-filled and unfilled high-impact PP. Uniaxial tensile tests were performed at different strain rates in order to characterize the mechanical response and the strain rate effect. The experimental results showed that both unfilled and talc-filled high-impact PP were sensitive to strain rate and exhibited nonlinear behavior even at relatively low strains. SEM analysis was conducted to obtain a better comprehension of deformation mechanisms involved during loading by observations of the microstructure evolution. For each of these two materials, two existing modeling approaches are proposed. The first one is a three-parameter nonlinear constitutive model based on the experimental results. The second is a micromechanically based approach for the elastic-viscoplastic behavior of the composite materials. The stress-strain curves predicted by these models are in fairly good agreement with our experimental results.

EFFECTIVENESS OF SUPPORT VECTOR MACHINE FOR CRIME HOT-SPOTS PREDICTION

Crime hot-spot location prediction is important for public safety. The output from the prediction can provide useful information to improve the activities aimed at detecting and preventing safety and security problems. Location prediction is a special case of spatial data mining classification. For instance, in the public safety domain, it may be interesting to predict location(s) of crime hot spots. In this study, we present a support vector machine (SVM)-based approach to predict the location as an alternative to existing modeling approaches. Support vector machine forms the new generation of machine-learning techniques used to find optimal separability between classes within datasets. We compare the performance of two types of SVMs techniques: two-class SVMs and one-class SVMs. We also compared SVM with a neural network-based approach and spatial auto-regression-based approach. Experiments on two different spatial datasets demonstrate that the former approach performs slightly better and the latter one gives reasonable results. Furthermore, in this study, we provide a general framework to customize the spatial data classification task for other spatial domains that have datasets similar to the analyzed crime datasets.

Classification of Runoff in Headwater Catchments: A Physical Problem?

AbstractLife on earth depends on water and where running water occurs on earth, there is life. Nevertheless, existing modelling approaches in hydrology almost completely neglect the biological aspects of water flow. We claim that ignoring biological behaviour and interaction in catchment runoff modelling is too restrictive, and that computational theories can be used to formalise behaviour and interaction and model the biological impact on runoff. To demonstrate this, starting with a general classification of catchment behaviour, as documented in runoff data, we will use symbolic dynamics to quantify randomness and complexity in the time series. This approach shows that runoff records from very different catchments show common behaviour. This behaviour can be fitted to a one‐parametric curve, stratified into three regions. In this manner, it becomes possible to represent and classify types of interactive behaviour that cannot be generated algorithmically. This suggests that physically based catchment models do not properly represent all types of interactive behaviour, and that signatures of biological interaction are present in runoff data.

Fuzzy Modelling for Early Architectural Design

Fuzzy modelling is simultaneously an extension of existing modelling approaches and a negation of one of their main aspects, the crispness of their definition. As a digital equivalent of analogue sketching it allows designers to register and manipulate imprecise and uncertain information. In the framework of design representations fuzzy modelling supports the development of conceptual design models characterized by flexible definition and interaction. The main advantages of such models are fluency, abstraction and continuity, at a level similar to that of analogue techniques. In addition to that they offer the possibility of local autonomy, i.e. segmentation of a representation into self-regulating and cooperating components. Three alternative forms of fuzzy modelling are proposed: (1) Canonical objects with tolerances, (2) objects described by minimal and maximal values, and (3) point sets comprising discrete, autonomous particles that describe the object by their spatial or structural relationships.

Modeling of Advanced Semiconductor Devices

Aggressive downscaling of modern semiconductor devices forces development engineers to question the validity of existing modeling approaches. Models for carrier transport have to be considered which are applicable on the transition into the quantum regime. An overview of semiclassical current transport models and their enhancements used for the simulation of nanoelectronic devices is given. Emphasis is put on arising modeling challenges in the existing and future technology nodes. Electron mobility analysis of ultra-scaled, strained field-effect transistors is presented in detail.

Predicting global change impacts on plant species’ distributions: Future challenges

Given the rate of projected environmental change for the 21st century, urgent adaptation and mitigation measures are required to slow down the on-going erosion of biodiversity. Even though increasing evidence shows that recent human-induced environmental changes have already triggered species’ range shifts, changes in phenology and species’ extinctions, accurate projections of species’ responses to future environmental changes are more difficult to ascertain. This is problematic, since there is a growing awareness of the need to adopt proactive conservation planning measures using forecasts of species’ responses to future environmental changes. There is a substantial body of literature describing and assessing the impacts of various scenarios of climate and land-use change on species’ distributions. Model predictions include a wide range of assumptions and limitations that are widely acknowledged but compromise their use for developing reliable adaptation and mitigation strategies for biodiversity. Indeed, amongst the most used models, few, if any, explicitly deal with migration processes, the dynamics of population at the “trailing edge” of shifting populations, species’ interactions and the interaction between the effects of climate and land-use. In this review, we propose two main avenues to progress the understanding and prediction of the different processes occurring on the leading and trailing edge of the species’ distribution in response to any global change phenomena. Deliberately focusing on plant species, we first explore the different ways to incorporate species’ migration in the existing modelling approaches, given data and knowledge limitations and the dual effects of climate and land-use factors. Secondly, we explore the mechanisms and processes happening at the trailing edge of a shifting species’ distribution and how to implement them into a modelling approach. We finally conclude this review with clear guidelines on how such modelling improvements will benefit conservation strategies in a changing world.

Modeling oyster growth rate by coupling oyster population and hydrodynamic models for Apalachicola Bay, Florida, USA

The eastern oyster ( Crassostrea virginica) plays an important role both ecologically and economically in Apalachicola Bay, Florida. Oyster population features such as population size, age structure, spawning, growth, and reproduction are closely related to bay salinity, which is often affected by freshwater flows from the Apalachicola River. Existing modeling approaches have used statistical models to examine the effects of changing freshwater inflow/salinity regime on oyster growth rates in Apalachicola Bay. However, little has been done using population process-based models. In this study, we adapted an oyster population model that simulates a diversity of population processes (including ingestion, assimilation, respiration, reproduction, spawning, recruitment, and mortality) and coupled it with a hydrodynamic model to examine the effects of changes in freshwater flow/salinity on oyster growth rates. We simulated oyster populations at two sites, Cat Point, a less-freshwater-influenced oyster reef, and Dry Bar, a more-freshwater-influenced oyster reef. The model simulations agree reasonably well with field measurements ( r 2 = 0.84). Statistical analyses suggested that oyster growth rates are significantly related to salinity. Lowest oyster growth rates tend to occur in mid-spring due to lowest salinity caused by highest Apalachicola River freshwater inflows whereas the growth peaks tend to occur in mid-summer because of the warm temperature and high food supply. Meanwhile, changes in freshwater inflows affect oyster growth rates through influencing salinities as well as other environmental factors such as food availability; and the magnitudes of the change in oyster growth rates depend on the difference between salinity and salinity range for optimal growth. The salinity range for optimal growth (≥2.0 mg AFDW oyster −1 day −1) is between 20 and 25 ppt at Cat Point and 17–26 ppt at Dry Bar. Only at the optimal salinity level can oysters achieve the maximum growth rates. Our simulations indicate that coupling oyster population process-based models with hydrodynamic models has significant advantage over statistical models in examining the multivariable system and understanding nonlinear relationships between oyster dynamics and environmental factors.

Flexure-Shear Fiber Beam-Column Elements for Modeling Frame Structures Under Seismic Loading — State of the Art

Whilst currently existing modeling approaches of reinforced concrete (RC) behavior allow a reasonably accurate prediction of flexural response, the determination of its shear counterpart needs further developments. In the last 20 years, models that predict shear response with acceptable accuracy for conditions of monotonic loading have been introduced, whilst, on the other hand, models capable of predicting the shear response under cyclic loading are less common. Among the approaches used for performing nonlinear analyses of frame structures, fiber beam-column elements have shown high capability in reproducing axial and flexural response, whereas the coupling between normal and shear stresses has been accounted for in very few models only. In this research work, the existing fiber beam-column elements with shear have been reviewed, underlying their most prominent characteristics and shortcomings, where relevant, with the objective of providing those interested in the topic with a relatively comprehensive overview of the subject. From this review, it can be concluded that thanks to the models proposed in the literature (and in particular, the ones herein presented) important and significant steps have been done towards the development of an analytical tool capable of modeling RC frame structures under cyclic and seismic loadings. However, further developments and improvements are still required in this research area.

Conducted-EMI Prediction for AC Converter Systems Using an Equivalent Modular–Terminal–Behavioral (MTB) Source Model

This paper presents a new frequency-domain method for predicting conducted electromagnetic-interference (EMI) noise in AC switching power converters whose switching conditions vary during an operating period. Based on an equivalent modular-terminal-behavioral (MTB) frequency-domain EMI source model developed for one switching period at a given operating point, the proposed approach superposes MTB models for different operating zones in the frequency domain to predict EMI noise for the entire operating period. Compared with the various existing modeling approaches, including physics-based or behavioral time-domain and frequency-domain methods, the proposed method is efficient, accurate, and more suitable for the system-level EMI study. The use of the methodology for both differential-mode and common-mode EMI-noise prediction is investigated. Verification was carried out through simulations and experiments using a half-bridge AC converter. This modular modeling approach can be applied to many other types of converters, including three-phase pulse-width-modulation inverters, as well as converters with different switching control schemes.

A framework for event based modeling and analysis

In this paper we will present a framework for modeling and management of complex systems. There are various approaches for modeling of these systems. One of the approaches is events driven modeling and management of complex system. Such approach is needed in information systems that provide information in real-time. Most of the existing modeling approaches use only information about type of event and the time when an event occurs. However, in the databases we can store and then we can use much richer information about events. This information might be structured as well as unstructured. There are new challenges in algorithms development in case of description of event by various attributes.

IFORS' Operational Research Hall of Fame Jay Wright Forrester

IFORS' Operational Research Hall of Fame Jay Wright Forrester

Modeling of pore blocking and cake layer formation in membrane filtration for wastewater treatment

Membrane filtration in municipal and industrial wastewater treatment is a technology being increasingly employed to enhance the quality of purified water, increase the productivity of existing plants, and build smaller, yet more effective purification processes. Barrier to a breakthrough of the technology is the increased operational cost due to fouling and membrane replacement. Simulation studies with rigorous process models are a powerful tool to increase the understanding of the process and its decisive characteristics in order to design optimal processes and efficient operational strategies. In this paper, two enhancements of existing modeling approaches are proposed. One is taking into account the adhesive forces between the particles and the membrane surface, which indeed strongly effect cake layer formation and back flushing efficiency. The other is assessing the decisive influence of particle and membrane pore size distributions on both cake layer formation and pore blocking and their mutual dependencies. Both phenomena are essential characteristics which need to be considered for a reliable prediction of process behavior. The model is successfully tested in simulation studies and compared to experimental data from a pilot wastewater treatment plant with submerged hollow fiber membranes.