The influence of oceanographic scenarios on the population dynamics of demersal resources in the western Mediterranean: Hypothesis for hake and red shrimp off Balearic Islands

The aim of the present paper is to study the relationships between some climatic indices and parental stock, recruitment and accessibility to trawl fishery of hake (Merluccius merluccius) and red shrimp (Aristeus antennatus) off Balearic Islands (western Mediterranean). Available annual catch per unit effort, recruitment and spawning stock biomass have been used as biological data. As environmental data, the meso-scale IDEA index and the large-scale North Atlantic Oscillation (NAO) and Mediterranean Oscillation (MO) indices have been used. To analyze possible links between these indices with the population dynamics of demersal resources, two non-linear approaches have been applied: (i) stock–recruitment relationships from Ricker and Beverton–Holt models, by sequentially incorporating environment factors; (ii) generalized additive modelling, both classical general and threshold non-additive models were considered. The latter simulate an abrupt change in explicative variables across different phases (time periods or climatic index values). The results have shown that two oceanographic scenarios around the Balearic Islands, associated with macro and meso-scale climate regimes, can influence the population dynamics of hake and red shrimp. This is especially true for recruitment, which seems to be enhanced during low NAO and IDEA indices periods. During these periods, colder-than-normal winters generate high amounts of cold Western Mediterranean Intermediate Waters (WIW) in the Gulf of Lions, which flow southwards and reach the Balearic Islands channels in spring, increasing the productivity in the area. This oceanographic scenario could also be favourable to the distribution of hake on the fishing grounds where the trawl fleet targets this species, increasing its accessibility to the fishery. Both spawning stock and abundance of red shrimp seems to be also enhanced by high MO index periods, which could reflect the increased presence of the saline and warm Levantine Intermediate Waters (LIW) in the study area, extending over the fishing grounds of this species. The proposed interactions can be useful to assess and manage these important demersal resources.     

Inferring origin–destination trip matrices from aggregate volumes on groups of links: a case study using volumes inferred from mobile phone data

The origin–destination matrix is an important source of information describing transport demand in a region. Most commonly used methods for matrix estimation use link volumes collected on a subset of links in order to update an existing matrix. Traditional volume data collection methods have significant shortcomings because of the high costs involved and the fact that detectors only provide status information at specified locations in the network. Better matrix estimates can be obtained when information is available about the overall distribution of traffic through time and space. Other existing technologies are not used in matrix estimation methods because they collect volume data aggregated on groups of links, rather than on single links. That is the case of mobile systems. Mobile phones sometimes cannot provide location accuracy for estimating flows on single links but do so on groups of links; in contrast, data can be acquired over a wider coverage without additional costs. This paper presents a methodology adapted to the concept of volume aggregated on groups of links in order to use any available volume data source in traditional matrix estimation methodologies. To calculate volume data, we have used a model that has had promising results in transforming phone call data into traffic movement data. The proposed methodology using vehicle volumes obtained by such a model is applied over a large real network as a case study. The experimental results reveal the efficiency and consistency of the solution proposed, making the alternative attractive for practical applications. Copyright © 2011 John Wiley & Sons, Ltd.     

Constrained nested logit model: formulation and estimation

A model of traveller behaviour should recognise the exogenous and endogenous factors that limit the choice set of users. These factors impose constraints on the decision maker, which constraints may be considered implicitly, as soft constraints imposing thresholds on the perception of changes in attribute values, or explicitly as hard constraints. The purpose of this paper is twofold: (1) To present a constrained nested logit-type choice model to cope with hard constraints. This model is derived from the entropy-maximizing framework. (2) To describe a general framework to deal with (dynamic) non-linear utilities. This approach is based on Reproducing Kernel Hilbert Spaces. The resulting model allows the dynamic aspect and the constraints on the choice process to be represented simultaneously. A novel estimation procedure is introduced in which the utilities are viewed as the parameters of the proposed model instead of attribute weights as in the classical linear models. A discussion on over-specification of the proposed model is presented. This model is applied to a synthetic test problem and to a railway service choice problem in which users choose a service depending on the timetable, ticket price, travel time and seat availability (which imposes capacity constraints). Results show (1) the relevance of incorporating constraints into the choice models, (2) that the constrained models appear to be a better fit than the counterpart unconstrained choice models; and (3) the viability of the approach, in a real case study of railway services on the Madrid–Seville corridor (Spain).     

An empirical analysis of freight transport traffic modes in Brazil, 1996–2012

This paper analyses the performance of freight transportation modes in Brazil – namely air, water, rail and road – from February 1996 to August 2012 by investigating their long memory properties using fractional integration and autoregressive models on monthly tonnage data. Two important features are analysed: the degree of dependence of transportation traffic across time and its seasonal structure over the period. Furthermore, the stability of parameters across the sample period is investigated, incorporating potential structural breaks in the data, which describe discontinuity in freight transportation traffic. Some policy implications are derived.     

Assessing the influence of indicators’ complexity on hybrid discrete choice model estimates

Transportation - Hybrid discrete choice (HDC) modeling requires indicators to allow for the identification of latent variables. An indicator usually expresses the level of agreement of a respondent...     

Transit Users’ Route‐Choice Modelling in Transit Assignment: A Review

Abstract

This paper reviews the main studies on transit users’ route choice in the context of transit assignment. The studies are categorized into three groups: static transit assignment, within‐day dynamic transit assignment, and emerging approaches. The motivations and behavioural assumptions of these approaches are re‐examined. The first group includes shortest‐path heuristics in all‐or‐nothing assignment, random utility maximization route‐choice models in stochastic assignment, and user equilibrium based assignment. The second group covers within‐day dynamics in transit users’ route choice, transit network formulations, and dynamic transit assignment. The third group introduces the emerging studies on behavioural complexities, day‐to‐day dynamics, and real‐time dynamics in transit users’ route choice. Future research directions are also discussed.     

Computational Bayesian Statistics in Transportation Modeling: From Road Safety Analysis to Discrete Choice

In this paper, we review both the fundamentals and the expansion of computational Bayesian econometrics and statistics applied to transportation modeling problems in road safety analysis and travel behavior. Whereas for analyzing accident risk in transportation networks there has been a significant increase in the application of hierarchical Bayes methods, in transportation choice modeling, the use of Bayes estimators is rather scarce. We thus provide a general discussion of the benefits of using Bayesian Markov chain Monte Carlo methods to simulate answers to the problems of point and interval estimation and forecasting, including the use of the simulated posterior for building predictive distributions and constructing credible intervals for measures such as the value of time. Although there is the general idea that going Bayesian is just another way of finding an equivalent to frequentist results, in practice Bayes estimators have the potential of outperforming frequentist estimators and, at the same time, may offer more information. Additionally, Bayesian inference is particularly interesting for small samples and weakly identified models.     

A risk-based first-principles approach to assessing green seas loading on the hatch covers of bulk carriers in extreme weather conditions

This paper aims to present and explain the work undertaken at the SSRC on the Safety of Bulk Carriers in extreme weather conditions over the past 3 years, to draw conclusions deriving there from, concerning key influencing design, operational and environmental parameters and to offer recommendations regarding the rule development process and on the way forward considering research, development and implementation to ship design and operation with the view to improving the safety of these ships cost-effectively. In severe storms, hatch covers of low freeboard vessels such as bulk carriers are the first-line of protection against flooding. Present methods of hatch covers design are still empirical because impact loads due to green seas and structural behaviour due to this type of loads have not been examined, hence not known accurately. The loading due to green seas is implicitly non-linear and, as model test results demonstrated, bulk carriers in extreme conditions are exposed to significant loads, which in some cases exceed current design standards. Since the consequences of hatch cover failure are potentially catastrophic, the risk of this happening should be quantified in probabilistic terms as required by modern safety standards. To this end, the paper aims to propose and implement a methodology for estimating probabilities of deck wetness and impact loads due to green seas as a function of key design and operational parameters.     

Ekman transport along the Galician Coast (NW, Spain) calculated from QuikSCAT winds

Ekman transport is studied close to the Galician coast by means of wind data provided by the QuikSCAT satellite from November 1999 to October 2005. Three different coastal zones are identified, western coast from Miño River to Cape Finisterre, middle coast from Cape Finisterre to Cape Ortegal and northern coast, from Cape Ortegal to Cape Peñas. In addition to existence of long-term variations, the periodicity of the transport signal is characterized by an annual component (365 days), a seasonal fluctuation (50–80 days) and a time scale related to passing storms (15–20 days). Although the periodicity of the signal is similar at the three zones due to external meteorological forcing, the Ekman transport is modulated by the presence of the coast, in such a way that seasonal patterns vary in intensity and direction along the coast. Thus, the spring–summer pattern is characterized by high transport at the western coast, pointing seaward perpendicular to the shore-line. The same orientation is observed at the middle coast although with a lower magnitude. Finally, Ekman transport at the northern coast points landward and oblique to the shore-line. The different transport orientations are shown to be responsible for the upwelling probability variation along the coast. On the other hand, the autumn–winter pattern does not show a clear trend with important inter-annual differences showing the high variability of Ekman transport for this period.     

Ridership estimation procedure for a transit corridor with new bus rapid transit service

Ridership estimation is a critical step in the planning of a new transit route or change in service. Very often, when a new transit route is introduced, the existing routes will be modified, vehicle capacities changed, or service headways adjusted. This has made ridership forecasts for the new, existing, and modified routes challenging. This paper proposes and demonstrates a procedure that forecasts the ridership of all transit routes along a corridor when a new bus rapid transit (BRT) service is introduced and existing regular bus services are adjusted. The procedure uses demographic data along the corridor, a recent origin–destination survey data, and new and existing transit service features as inputs. It consists of two stages of transit assignment. In the first stage, a transit assignment is performed with the existing transit demand on the proposed BRT and existing bus routes, so that adjustments to the existing bus services can be identified. This transit assignment is performed iteratively until there is no adjustment in transit services. In the second stage, the transit assignment is carried out with the new BRT and adjusted regular bus services, but incorporates a potential growth in ridership because of the new BRT service. The final outputs of the procedure are ridership for all routes and route segments, boarding and alighting volumes at all stops, and a stop‐by‐stop trip matrix. The proposed ridership estimation procedure is applicable to a new BRT route with and without competing regular bus routes and with BRT vehicles traveling in dedicated lanes or in mixed traffic. The application of the proposed procedure is demonstrated via a case study along the Alameda Corridor in El Paso, Texas. Copyright © 2015 John Wiley & Sons, Ltd.