Surface-dependent strategies and energy flux in benthic marine communities or, why corals do not exist in the Mediterranean

Most structure-building organisms in rocky benthic communities are surface-dependent because their energy inputs depend mainly on the surface they expose to water. Two photosynthetic strategies, divided into calcareous and non calcareous algae, strict suspension-feeders and photosynthetic suspension feeders (e.g. hermatypic corals) are the four main strategies evolutively acquired by benthic organisms. Competition between those strategies occur in relation to productivity of the different species, in such a way that, for given environmental conditions, species with a higher growth (P/B ratio) would dominate. At a worldwide scale, littoral marine benthos can he considered to fit into the four fields defined by two main axes: the first, relates to productivity and relies atrophic and oligotrophic waters and the second is defined by the degree of environmental variability or seasonality (from high to low). Coral reefs (marine ecosystems dominated by photosynthetic suspension feeders) develop in the space of oligotrophic areas with low variability, while kelp beds (marine ecosystem dominated by large, non calcareous algae) are to be found only in eutrophic places with a high variability. The space of eutrophic waters with a low variability do not has specially adapted, high structured, benthic marine ecosystems, and in these conditions opportunistic algae and animals predominate. Finally, photophilic mediterranean benthos -devoid of kelps and without hermatypic corals- typifies the field of oligotrophic areas with high variability; in its more genuine aspect, Mediterranean benthos is represented by small algae with a high percentage of calcareous thallii. In all cases strict suspension-feeders compete successfully with photosynthetic organisms only in situations of low irradiances or very high inputs of POM. In its turn, Mediterranean rocky benthos, in spite of its relative uniformity, is geographically organized along the same axes. The Gulf of Lions and the insular bottoms (Balearic Islands, for example) would correspond to the extremes of eutrophic-high variability areas and oligotrophic-low variability areas, respectively. Irradiance, nutrient and POM concentration, and hydrodynamism are the three variables which mainly affect the distribution of the different surface-dependent strategies, and thus, these parameters are of paramount interest for understanding the trophic structure of Mediterranean benthic communities. In environments non limited by light, nutrient availability, defined as the product between nutrient -POM concentration and hydrodynamism, states the dominance of calcareous versus non calcareous algae. Calcareous algae dominate in oligotrophic waters while non-calcareous algae dominate in moderately eutrophic waters. In light-limited environments, passive suspension feeders (octocorallaria, gorgonians) become dominant species if POM availability is enhanced by a high hydrodynamism (strong currents); in waters with a low charge of POM organisms of other groups, mainly active suspension feeders, predominate (sponges, bryozoans, scleractiniarians). In any case, there always exists a very variable bathymetric zone, depending on light attenuation and nutrient-POM availability, where encrusting calcareous algae strongly compete with suspension feeders (coralligenous).

A priori ratemaking using bivariate poisson regression models

In automobile insurance, it is useful to achieve a priori ratemaking by resorting to gene- ralized linear models, and here the Poisson regression model constitutes the most widely accepted basis. However, insurance companies distinguish between claims with or without bodily injuries, or claims with full or partial liability of the insured driver. This paper exa- mines an a priori ratemaking procedure when including two di®erent types of claim. When assuming independence between claim types, the premium can be obtained by summing the premiums for each type of guarantee and is dependent on the rating factors chosen. If the independence assumption is relaxed, then it is unclear as to how the tari® system might be a®ected. In order to answer this question, bivariate Poisson regression models, suitable for paired count data exhibiting correlation, are introduced. It is shown that the usual independence assumption is unrealistic here. These models are applied to an automobile insurance claims database containing 80,994 contracts belonging to a Spanish insurance company. Finally, the consequences for pure and loaded premiums when the independence assumption is relaxed by using a bivariate Poisson regression model are analysed.

Factors explaining local privatization: A meta-regression analysis

Privatization of local public services has been implemented worldwide in the last decades. Why local governments privatize has been the subject of much discussion, and many empirical works have been devoted to analyzing the factors that explain local privatization. Such works have found a great diversity of motivations, and the variation among reported empirical results is large. To investigate this diversity we undertake a meta-regression analysis of the factors explaining the decision to privatize local services. Overall, our results indicate that significant relationships are very dependent upon the characteristics of the studies. Indeed, fiscal stress and political considerations have been found to contribute to local privatization specially in the studies of US cases published in the eighties that consider a broad range of services. Studies that focus on one service capture more accurately the influence of scale economies on privatization. Finally, governments of small towns are more affected by fiscal stress, political considerations and economic efficiency, while ideology seems to play a major role for large cities.

Estimation of lean meat content in pig carcasses using X-ray Computed Tomography and PLS regression

Lean meat percentage (LMP) is an important carcass quality parameter. The aim of this work is to obtain a calibration equation for the Computed Tomography (CT) scans with the Partial Least Square Regression (PLS) technique in order to predict the LMP of the carcass and the different cuts and to study and compare two different methodologies of the selection of the variables (Variable Importance for Projection — VIP- and Stepwise) to be included in the prediction equation. The error of prediction with cross-validation (RMSEPCV) of the LMP obtained with PLS and selection based on VIP value was 0.82% and for stepwise selection it was 0.83%. The prediction of the LMP scanning only the ham had a RMSEPCV of 0.97% and if the ham and the loin were scanned the RMSEPCV was 0.90%. Results indicate that for CT data both VIP and stepwise selection are good methods. Moreover the scanning of only the ham allowed us to obtain a good prediction of the LMP of the whole carcass.

State-dependent threshold STAR models

In this paper we consider extensions of smooth transition autoregressive (STAR) models to situations where the threshold is a time-varying function of variables that affect the separation of regimes of the time series under consideration. Our specification is motivated by the observation that unusually high/low values for an economic variable may sometimes be best thought of in relative terms. State-dependent logistic STAR and contemporaneous-threshold STAR models are introduced and discussed. These models are also used to investigate the dynamics of U.S. short-term interest rates, where the threshold is allowed to be a function of past output growth and inflation.

Mixture of bivariate Poisson regression models with an application to insurance

In a recent paper Bermúdez [2009] used bivariate Poisson regression models for ratemaking in car insurance, and included zero-inflated models to account for the excess of zeros and the overdispersion in the data set. In the present paper, we revisit this model in order to consider alternatives. We propose a 2-finite mixture of bivariate Poisson regression models to demonstrate that the overdispersion in the data requires more structure if it is to be taken into account, and that a simple zero-inflated bivariate Poisson model does not suffice. At the same time, we show that a finite mixture of bivariate Poisson regression models embraces zero-inflated bivariate Poisson regression models as a special case. Additionally, we describe a model in which the mixing proportions are dependent on covariates when modelling the way in which each individual belongs to a separate cluster. Finally, an EM algorithm is provided in order to ensure the models’ ease-of-fit. These models are applied to the same automobile insurance claims data set as used in Bermúdez [2009] and it is shown that the modelling of the data set can be improved considerably.

Existence and uniqueness of viscosity solution for Hamilton-Jacobi equation with discontinuous coefficients dependent on time

The main result is a proof of the existence of a unique viscosity solution for Hamilton-Jacobi equation, where the hamiltonian is discontinuous with respect to variable, usually interpreted as the spatial one. Obtained generalized solution is continuous, but not necessarily differentiable.

Comrades or Culprits? Donor Engagement and Budget Transparency in Aid Dependent Countries

Budget transparency has come to be considered a key aspect of governance. Over the past decade, donors have invested increasing resources in strengthening processes through which budget transparency in developing countries can be enhanced. According to the 2008 Open Budget Index (OBI) Report, however, aid dependency and budget transparency appear to be inversely correlated. This article looks at the role of donor agencies in promoting or preventing budget transparency in aid dependent countries. It analyzes data for a sample of 16 aid-dependent countries included in the OBI, to test some preliminary hypotheses and select six countries for which more detailed findings are then presented. All of these countries have implemented reforms aimed at enhancing budget transparency, with substantial donor support. These, however, often had only limited success, partly because they were not well adapted to the local context, and partly because donors put limited emphasis on improving public access to budget information. Donor efforts were also often offset by other characteristics of donor interventions, namely their fragmentation, lack of transparency, and limited use of program aid modalities such as budget support and pooled sector funding.

An alternative method for dating unknown tephras based on a segmented regression model

In CoDaWork’05, we presented an application of discriminant function analysis (DFA) to 4 differentcompositional datasets and modelled the first canonical variable using a segmented regression modelsolely based on an observation about the scatter plots. In this paper, multiple linear regressions areapplied to different datasets to confirm the validity of our proposed model. In addition to dating theunknown tephras by calibration as discussed previously, another method of mapping the unknown tephrasinto samples of the reference set or missing samples in between consecutive reference samples isproposed. The application of these methodologies is demonstrated with both simulated and real datasets.This new proposed methodology provides an alternative, more acceptable approach for geologists as theirfocus is on mapping the unknown tephra with relevant eruptive events rather than estimating the age ofunknown tephra.Kew words: Tephrochronology; Segmented regression

Life-Cycle Effects on Household Expenditures: A Latent-Variable Approach

Using data from the Spanish household budget survey, we investigate life- cycle effects on several product expenditures. A latent-variable model approach is adopted to evaluate the impact of income on expenditures, controlling for the number of members in the family. Two latent factors underlying repeated measures of monetary and non-monetary income are used as explanatory variables in the expenditure regression equations, thus avoiding possible bias associated to the measurement error in income. The proposed methodology also takes care of the case in which product expenditures exhibit a pattern of infrequent purchases. Multiple-group analysis is used to assess the variation of key parameters of the model across various household life-cycle typologies. The analysis discloses significant life-cycle effects on the mean levels of expenditures; it also detects significant life-cycle effects on the way expenditures are affected by income and family size. Asymptotic robust methods are used to account for possible non-normality of the data.

Lyfe-cycle effects on household expenditures: A latent-variable approach

Using data from the Spanish household budget survey, we investigate life-cycle effects on several product expenditures. A latent-variable model approach is adopted to evaluate the impact of income on expenditures, controlling for the number of members in the family. Two latent factors underlying repeated measures of monetary and non-monetary income are used as explanatory variables in the expenditure regression equations, thus avoiding possible bias associated to the measurement error in income. The proposed methodology also takes care of the case in which product expenditures exhibit a pattern of infrequent purchases. Multiple-group analysis is used to assess the variation of key parameters of the model across various household life-cycle typologies. The analysis discloses significant life-cycle effects on the mean levels of expenditures; it also detects significant life-cycle effects on the way expenditures are affected by income and family size. Asymptotic robust methods are used to account for possible non-normality of the data.

Do Spanish informal caregivers come to the rescue of dependent people with formal care unmet needs?

This paper analyses the effect of unmet formal care needs on informal caregiving hours in Spain using the two wavesof the Informal Support Survey (1994, 2004). Testing for double sample selection from formal care receipt and theemergence of unmet needs provides evidence that the omission of either variable would causes underestimation of thenumber of informal caregiving hours. After controlling for these two factors the number of hours of care increaseswith both the degree of dependency and unmet needs. More importantly, in the presence of unmet needs, the numberof informal caregiving hours increases when some formal care is received. This result refutes the substitution modeland supports complementarity or task specificity between both types of care. For a given combination of formal careand unmet needs, informal caregiving hours increased between 1994 and 2004. Finally, in the model for 2004, theselection term associated with the unmet needs equation is larger than that of the formal care equation, suggestingthat using the number of formal care recipients as a quality indicator may be confounding, if we do not complete thisinformation with other quality indicators.

A data-dependent skeleton estimate and a scale-sensitive dimension for classification

The classical binary classification problem is investigatedwhen it is known in advance that the posterior probability function(or regression function) belongs to some class of functions. We introduceand analyze a method which effectively exploits this knowledge. The methodis based on minimizing the empirical risk over a carefully selected``skeleton'' of the class of regression functions. The skeleton is acovering of the class based on a data--dependent metric, especiallyfitted for classification. A new scale--sensitive dimension isintroduced which is more useful for the studied classification problemthan other, previously defined, dimension measures. This fact isdemonstrated by performance bounds for the skeleton estimate in termsof the new dimension.

High capacity robust audio watermarking scheme based on FFT and linear regression

Peer-reviewed

Genetic variation for carbon isotope composition in Juglans regia L.: relationships with growth, phenology and climate of origin

Among the traits of breeding interest for the common walnut tree Juglans regia L., characteristics such as timing of budbreak and leaf fall, water-use efficiency and growth performance are regarded as being of utmost relevance in Mediterranean conditions. The authors evaluated intraspecific variation in $\delta$13C (carbon isotope composition, surrogate of intrinsic water-use efficiency, WUE$_{\rm i}$) for 22 J. regia families grown in a progeny test under supplementary irrigation, and investigated whether such variation correlated with climatic indicators of native habitats. The genetic relationships between $\delta$13C, growth and phenology were also assessed during two consecutive years. Overall, the most water-use-efficient families (i.e. with higher $\delta$13C), which originated mainly from drought-prone provenance regions which have a high vapour pressure deficit and low rainfall, exhibited less height growth and smaller DBH. Using a stepwise regression procedure, $\delta$13C was included as the main explanatory variable of genotypic variation in growth traits, together with growing season duration (for DBH in both years) and flushing (for height in 2007). It was concluded that WUE$_{\rm i}$ is largely unconnected to phenology effects in the explanation of growth performance for J. regia, therefore suggesting the opportunity of simultaneously selecting for low WUE$_{\rm i}$ and extended growing period to maximise productivity in non-water-limited environments.