Modelling the effects of climate change on the distribution and production of marine fishes: accounting for trophic interactions in a dynamic bioclimate envelope model

Climate change has already altered the distribution of marine fishes. Future predictions of fish distributions and catches based on bioclimate envelope models are available, but to date they have not considered interspecific interactions. We address this by combining the species-based Dynamic Bioclimate Envelope Model (DBEM) with a size-based trophic model. The new approach provides spatially and temporally resolved predictions of changes in species' size, abundance and catch potential that account for the effects of ecological interactions. Predicted latitudinal shifts are, on average, reduced by 20% when species interactions are incorporated, compared to DBEM predictions, with pelagic species showing the greatest reductions. Goodness-of-fit of biomass data from fish stock assessments in the North Atlantic between 1991 and 2003 is improved slightly by including species interactions. The differences between predictions from the two models may be relatively modest because, at the North Atlantic basin scale, (i) predators and competitors may respond to climate change together; (ii) existing parameterization of the DBEM might implicitly incorporate trophic interactions; and/or (iii) trophic interactions might not be the main driver of responses to climate. Future analyses using ecologically explicit models and data will improve understanding of the effects of inter-specific interactions on responses to climate change, and better inform managers about plausible ecological and fishery consequences of a changing environment.

Co-evaluation as a strategy to improve working group dynamics: an experience in Sport Sciences

The aim of this study was to analyze if the perceptions of students before and after carrying out the work, that is, their perception of different aspects of the functioning of the group, the working skills acquired as well as those they think that need to be improved, varied depending on whether the contribution of the different members of the group was being co-evaluated or not. 144 students of Physical Activity and Sport Sciences participated in this study. In order to analyze the students' perception of group work the adapted questionnaire by Bourne et al. (2001) was used. Results showed that groups which implemented co-evaluation assessed more negatively the experience in general than those which did not. However, co-evaluation groups perceived their competence to work as a team had improved to a greater extent than the groups without co-evaluation, evaluating more positively both the performance and the result of work and increasing their knowledge of the other team members. Using a co-evaluation system seems to generate both a better assessment of the running of the team and the result of its work.

Studying administrative reforms through textual analysis: the case of Italian central government accounting

This paper contributes to the literature on public-sector reforms by proposing textual analysis as a useful research strategy to explore how reform archetypes and related ideas are deployed in the parliamentary debate and regulations advancing reforms. Public Administration (PA) (Wilson 1887; Weber 1922), New Public Management (NPM) (Hood 1991, 1995; Dunleavy and Hood 1994; Ferlie et al. 1996) and Public Governance (GOV) (Osborne 2010; Rhodes 1997) can be depicted as three different archetypes providing characteristic administrative ideas and concepts (i.e. interpretive schemes) and related tools and practices (i.e. structures and systems) which lead reforms. We use textual analysis to look into more than twenty years of Italian central government accounting reforms and investigate how the three administrative archetypes have evolved, intertwined and replaced each other. Textual analysis proves a useful tool to investigate reform processes and allows highlighting that in neo-Weberian countries, such as Italy, NPM and GOV, far from being revolutionary paradigms, may represent fashionable trends that did not leave significant traces in the practice and rhetoric of reforms. These results also suggest interesting implications for practitioners and policy makers.

Sustainable urban metabolism as a link between bio-physical sciences and urban planning: the BRIDGE project

Urban metabolism considers a city as a system with flows of energy and material between it and the environment. Recent advances in bio-physical sciences provide methods and models to estimate local scale energy, water, carbon and pollutant fluxes. However, good communication is required to provide this new knowledge and its implications to endusers (such as urban planners, architects and engineers). The FP7 project BRIDGE (sustainaBle uRban plannIng Decision support accountinG for urban mEtabolism) aimed to address this gap by illustrating the advantages of considering these issues in urban planning. The BRIDGE Decision Support System (DSS) aids the evaluation of the sustainability of urban planning interventions. The Multi Criteria Analysis approach adopted provides a method to cope with the complexity of urban metabolism. In consultation with targeted end-users, objectives were defined in relation to the interactions between the environmental elements (fluxes of energy, water, carbon and pollutants) and socioeconomic components (investment costs, housing, employment, etc.) of urban sustainability. The tool was tested in five case study cities: Helsinki, Athens, London, Florence and Gliwice; and sub-models were evaluated using flux data selected. This overview of the BRIDGE project covers the methods and tools used to measure and model the physical flows, the selected set of sustainability indicators, the methodological framework for evaluating urban planning alternatives and the resulting DSS prototype.

Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling

Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple sources of uncertainty. Given the complexities of ecological studies, the hierarchical statistical model is an invaluable tool. This approach is not new in ecology, and there are many examples (both Bayesian and non-Bayesian) in the literature illustrating the benefits of this approach. In this article, we provide a baseline for concepts, notation, and methods, from which discussion on hierarchical statistical modeling in ecology can proceed. We have also planted some seeds for discussion and tried to show where the practical difficulties lie. Our thesis is that hierarchical statistical modeling is a powerful way of approaching ecological analysis in the presence of inevitable but quantifiable uncertainties, even if practical issues sometimes require pragmatic compromises.

A bivariate return period based on copulas for hydrologic dam design: accounting for reservoir routing in risk estimation

A multivariate analysis on flood variables is needed to design some hydraulic structures like dams, as the complexity of the routing process in a reservoir requires a representation of the full hydrograph. In this work, a bivariate copula model was used to obtain the bivariate joint distribution of flood peak and volume, in order to know the probability of occurrence of a given inflow hydrograph. However, the risk of dam overtopping is given by the maximum water elevation reached during the routing process, which depends on the hydrograph variables, the reservoir volume and the spillway crest length. Consequently, an additional bivariate return period, the so-called routed return period, was defined in terms of risk of dam overtopping based on this maximum water elevation obtained after routing the inflow hydrographs. The theoretical return periods, which give the probability of occurrence of a hydrograph prior to accounting for the reservoir routing, were compared with the routed return period, as in both cases hydrographs with the same probability will draw a curve in the peak-volume space. The procedure was applied to the case study of the Santillana reservoir in Spain. Different reservoir volumes and spillway lengths were considered to investigate the influence of the dam and reservoir characteristics on the results. The methodology improves the estimation of the Design Flood Hydrograph and can be applied to assess the risk of dam overtopping

Accounting for residential and non-residential environments to measure contextual effects on health behavior : the case of recreational walking behavior

Thèse réalisée en cotutelle entre l'Université de Montréal et l'Université Pierre et Marie Curie, Paris 06, Sorbonne Universités.

A stochastic metapopulation model accounting for habitat dynamics

A stochastic metapopulation model accounting for habitat dynamics is presented. This is the stochastic SIS logistic model with the novel aspect that it incorporates varying carrying capacity. We present results of Kurtz and Barbour, that provide deterministic and diffusion approximations for a wide class of stochastic models, in a form that most easily allows their direct application to population models. These results are used to show that a suitably scaled version of the metapopulation model converges, uniformly in probability over finite time intervals, to a deterministic model previously studied in the ecological literature. Additionally, they allow us to establish a bivariate normal approximation to the quasi-stationary distribution of the process. This allows us to consider the effects of habitat dynamics on metapopulation modelling through a comparison with the stochastic SIS logistic model and provides an effective means for modelling metapopulations inhabiting dynamic landscapes.

Accounting for management costs in sensitivity analyses of matrix population models

Traditional sensitivity and elasticity analyses of matrix population models have been used to p inform management decisions, but they ignore the economic costs of manipulating vital rates. For exam le, the growth rate of a population is often most sensitive to changes in adult survival rate, but this does not mean that increasing that rate is the best option for managing the population because it may be much more expensive than other options. To explore how managers should optimize their manipulation of vital rates, we incorporated the cost of changing those rates into matrix population models. We derived analytic expressions for locations in parameter space where managers should shift between management of fecundity and survival, for the balance between fecundity and survival management at those boundaries, and for the allocation of management resources to sustain that optimal balance. For simple matrices, the optimal budget allocation can often be expressed as simple functions of vital rates and the relative costs of changing them. We applied our method to management of the Helmeted Honeyeater (Lichenostomus melanops cassidix; an endangered Australian bird) and the koala (Phascolarctos cinereus) as examples. Our method showed that cost-efficient management of the Helmeted Honeyeater should focus on increasing fecundity via nest protection, whereas optimal koala management should focus on manipulating both fecundity and survival simultaneously, These findings are contrary to the cost-negligent recommendations of elasticity analysis, which would suggest focusing on managing survival in both cases. A further investigation of Helmeted Honeyeater management options, based on an individual-based model incorporating density dependence, spatial structure, and environmental stochasticity, confirmed that fecundity management was the most cost-effective strategy. Our results demonstrate that decisions that ignore economic factors will reduce management efficiency.

A reduced load approximation accounting for link interactions in a loss network

This paper is concerned with evaluating the performance of loss networks. Accurate determination of loss network performance can assist in the design and dimensioning of telecommunications networks. However, exact determination can be difficult and generally cannot be done in reasonable time. For these reasons there is much interest in developing fast and accurate approximations. We develop a reduced load approximation which improves on the famous Erlang fixed point approximation (EFPA) in a variety of circumstances. We illustrate our results with reference to a range of networks for which the EFPA may be expected to perform badly.

Accounting for residential and non-residential environments to measure contextual effects on health behavior : the case of recreational walking behavior

Thèse réalisée en cotutelle entre l'Université de Montréal et l'Université Pierre et Marie Curie, Paris 06, Sorbonne Universités.

Evaluating consumer price perception: a mental accounting and frame dependent perspective

In this thesis, we evaluate consumer purchase behaviour from the perspective of heuristic decision making. Heuristic decision processes are quick and easy mental shortcuts, adopted by individuals to reduce the amount of time spent in decision making. In particular, we examine those heuristics which are caused by framing – prospect theory and mental accounting, and examine these within price related decision scenarios. The impact of price framing on consumer behaviour has been studied under the broad umbrella of reference price, which suggests that decision makers use reference points as standards of comparison when making a purchase decision. We investigate four reference points - a retailer's past prices, a competitor's current prices, a competitor's past prices, and consumers' expectation of immediate future price changes, to further our understanding of the impact of price framing on mental accounting, and in turn, contribute to the growing body of reference price literature in Marketing research. We carry out experiments in which levels of price frame and monetary outcomes are manipulated in repeated measures analysis of variance (ANOVA). Our results show that where these reference points are clearly specified in decision problems, price framing significantly affects consumers' perceptions of monetary gains derived through discounts, and leads to reversals in consumer preferences. We also found that monetary losses were not sensitive to price frame manipulations.