Stocks assesment, biomass and fish production in two mediterranean basins (NE Spain)

In order to evaluate the success of the reintroduction of the Eurasian otter (Lutra lutra) in the Empordh wetlands (Parc Natural dels Aiguamolls de I'Empordhà), and the Muga and Fluvih basins, density of fish, biomass and production in the Muga and Fluvia Rivers have been estimated, since fishes represent the principal prey in the otter diet. 12 study sites were selected in order to survey the main flows in both basins. Electrofishing surveys were conducted by blocking off the station with barrier nets, which was performed upon 3 successive catches. The density estimated presents a range of 1,136-1 25 ind .ha' in the Muga basin, 4,49-163 ind.ha' in the Fluvih basin and 3,76-52,2 ind.ha' in the Empordh wetlands. Estimated biomass ranges are 0,616-277,6 g.m2, 8,79-351,2 g.m2, and 5,7-108 g.m-2 respectively. These density anfi biomass ranges are similar to other results obtained from rivers inhabited by the Eurasian otter in NE Spain

Urban population density functions : the case of the Barcelona region

L'anàlisi de la densitat urbana és utilitzada per examinar la distribució espacial de la població dins de les àrees urbanes, i és força útil per planificar els serveis públics. En aquest article, s'estudien setze formes funcionals clàssiques de la relació existent entre la densitat i la distancia en la regió metropolitana de Barcelona i els seus onze subcentres.

Cubic spline population density functions and subcentre delimitation. The case of Barcelona

The presence of subcentres cannot be captured by an exponential function. Cubic spline functions seem more appropriate to depict the polycentricity pattern of modern urban systems. Using data from Barcelona Metropolitan Region, two possible population subcentre delimitation procedures are discussed. One, taking an estimated derivative equal to zero, the other, a density gradient equal to zero. It is argued that, in using a cubic spline function, a delimitation strategy based on derivatives is more appropriate than one based on gradients because the estimated density can be negative in sections with very low densities and few observations, leading to sudden changes in estimated gradients. It is also argued that using as a criteria for subcentre delimitation a second derivative with value zero allow us to capture a more restricted subcentre area than using as a criteria a first derivative zero. This methodology can also be used for intermediate ring delimitation.

The density of injective endomorphisms of a free group

"Vegeu el resum a l'inici del document del fitxer adjunt."

Effects of atmospheric carbon dioxide fertilization on biomass and secondary metabolites of some plant species with pharmacological interes under greenhouse conditions

RESUMEN El aumento del CO2 atmosférico debido al cambio global y/o a las prácticas hortícolas promueve efectos directos sobre crecimiento vegetal y el desarrollo. Estas respuestas pueden ocurrir en ecosistemas naturales, pero también se pueden utilizar para aumentar la producción de algunas plantas y de algunos compuestos secundarios. El actual trabajo intenta estudiar los efectos del enriquecimiento atmosférico del CO2 bajo condiciones de invernadero en el crecimiento y la concentración y la composición de metabolitos secundarios de Taxus bacatta, Hypericum perforatum y Echinacea purpurea en condiciones ambientales mediterráneas. La fertilización del CO2 muestra perspectivas interesantes para la mejorara y aplicabilidad de técnicas hortícolas para aumentar productividad de plantas medicinales, a pesar de diferencias claras entre la especie. En general esta técnica promueve aumentos importantes y significativos en producción primaria y, en algunos casos, también en compuestos secundarios. Esto tiene una gran importancia hortícola porque la productividad a nivel de cosecha total aumenta, directamente porque se aumenta la concentración e indirectamente porque se aumenta la biomasa. SUMMARY The increase of atmospheric CO2 due to global change and/or horticultural practices promotes direct effects on plant growth and development. These responses may occur in natural ecosystems, but also can be used to increase the production of some plants and some secondary compounds. Present work tries to study the effects of atmospheric CO2 enrichment under greenhouse conditions on growth and in the concentration and composition of secondary metabolites of Taxus bacatta, Hypericum perforatum and Echinacea purpurea under Mediterranean environmental conditions. CO2 fertilization shows interesting perspectives to increase and improve horticultural techniques in order to increase plant medicinal productivity, in spite of clear differences among the species. In general this technique promotes important and significant increases in primary productivity and, in some cases, also in secondary compounds. This has a great horticultural relevance because the total productivity of this kind of products increase at crop level, directly because concentration is increased and /or indirectly because biomass is increased. RESUM L'augment del CO2 atmosfèric a causa del canvi global i/o a les pràctiques hortícoles promou efectes directes sobre creixement vegetal i el desenvolupament. Aquestes respostes poden ocórrer en ecosistemes naturals, però també es poden utilitzar per a augmentar la producció d'algunes plantes i d'alguns compostos secundaris. L'actual treball intenta estudiar els efectes de l'enriquiment atmosfèric del CO2 sota condicions d'hivernacle en el creixement i la concentració i la composició de metabòlits secundaris de Taxus bacatta, Hypericum perforatum i Echinacea purpurea en condicions ambientals mediterrànies. La fertilització del CO2 mostra perspectives interessants per a la millora i aplicabilitat de tècniques hortícoles per a augmentar productivitat de plantes medicinals, a pesar de diferències clares entre l'espècie. En general aquesta tècnica promou augments importants i significatius en producció primària i, en alguns casos, també en compostos secundaris. Això té una gran importància hortícola perquè la productivitat a nivell de collita total augmenta, directament perquè s'augmenta la concentració i indirectament perquè s'augmenta la biomassa.

Condicions socioecològiques de la riera d'Arbúcies pel retorn de la llúdriga (Lutra lutra)

La llúdriga (Lutra lutra) va desaparèixer de la conca de la Tordera a causa de la pressió humana sobre ella i el seu hàbitat. Recentment les seves poblacions s’estan recuperant a las conques nord de Catalunya. En aquest context es presenta els resultats dels anàlisis dels requeriments socioecològics de la llúdriga en l’afluent del riu Tordera de la riera d’Arbúcies: qualitat del bosc de ribera, valoració de la contaminació de l’aigua i l’anàlisi de les poblacions d’ictiofauna, a més de l’estimació de l’espècie més abundant. L’evolució de l’ús i cobertes del sòl del sòl mostren que existeix una tendència augment en las masses forestals, zones urbanitzades i infraestructures; també una disminució del camps de cultiu, fruiters i vinyes. La qualitat del bosc de ribera es va valorar a partir del l’índex QBR, obtenint que la màxima qualitat es localitza en el tram alt, disminuint a mesura que s’apropa a la desembocadura al Tordera. La contaminació de l’aigua a estat valorada, per una banda analitzant la qualitat biològica a partir dels índexs IPS i BMWPC, obtenint que la qualitat de l’aigua disminueix a mesura que transcorre riu avall, segons l’IPS. Amb el BMWPC es troba que existeix una recuperació de la qualitat de l’aigua en l’últim tram. Per altra banda s’han analitzat el compostos químics que afecten a la llúdriga, obtenint que les concentracions d’aquest no són rellevants a l’aigua. S’ha analitzat l’estructura de la població d’ictiofauna present, trobant que el Barbus meridionalis és l’espècie més abundant en tots el trams, a més d’augmentar en captures a mesura que l’aigua s’apropa al aiguabarreig amb la Tordera. S’ha estimat la biomassa present d’aquesta espècie, concloent que es suficient per mantenir una població no gaire densa de llúdrigues, inferior a 0,15 individus per kilòmetre de riu.

On the density distribution across space: a probabilistic approach

This paper aims at providing a Bayesian parametric framework to tackle the accessibility problem across space in urban theory. Adopting continuous variables in a probabilistic setting we are able to associate with the distribution density to the Kendall's tau index and replicate the general issues related to the role of proximity in a more general context. In addition, by referring to the Beta and Gamma distribution, we are able to introduce a differentiation feature in each spatial unit without incurring in any a-priori definition of territorial units. We are also providing an empirical application of our theoretical setting to study the density distribution of the population across Massachusetts.

Sobolev mappings: Lipschitz density is not an isometric invariant of the target

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Gaussian estimates for the density of the non-linear stochastic heat equation in any space dimension

In this paper, we establish lower and upper Gaussian bounds for the probability density of the mild solution to the stochastic heat equation with multiplicative noise and in any space dimension. The driving perturbation is a Gaussian noise which is white in time with some spatially homogeneous covariance. These estimates are obtained using tools of the Malliavin calculus. The most challenging part is the lower bound, which is obtained by adapting a general method developed by Kohatsu-Higa to the underlying spatially homogeneous Gaussian setting. Both lower and upper estimates have the same form: a Gaussian density with a variance which is equal to that of the mild solution of the corresponding linear equation with additive noise.

Comparing methods for dimensionality reduction when data are density functions

Functional Data Analysis (FDA) deals with samples where a whole function is observedfor each individual. A particular case of FDA is when the observed functions are densityfunctions, that are also an example of infinite dimensional compositional data. In thiswork we compare several methods for dimensionality reduction for this particular typeof data: functional principal components analysis (PCA) with or without a previousdata transformation and multidimensional scaling (MDS) for diferent inter-densitiesdistances, one of them taking into account the compositional nature of density functions. The difeerent methods are applied to both artificial and real data (householdsincome distributions)

Hilbert space on probability density functions with Aitchison geometry

Compositional data analysis motivated the introduction of a complete Euclidean structure in the simplex of D parts. This was based on the early work of J. Aitchison (1986) and completed recently when Aitchinson distance in the simplex was associated with an inner product and orthonormal bases were identified (Aitchison and others, 2002; Egozcue and others, 2003). A partition of the support of a random variable generates a composition by assigning the probability of each interval to a part of the composition. One can imagine that the partition can be refined and the probability density would represent a kind of continuous composition of probabilities in a simplex of infinitely many parts. This intuitive idea would lead to a Hilbert-space of probability densitiesby generalizing the Aitchison geometry for compositions in the simplex into the set probability densities

Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

A comparison of the alr and ilr transformations for kernel density estimation of compositional data

In a seminal paper, Aitchison and Lauder (1985) introduced classical kernel densityestimation techniques in the context of compositional data analysis. Indeed, they gavetwo options for the choice of the kernel to be used in the kernel estimator. One ofthese kernels is based on the use the alr transformation on the simplex SD jointly withthe normal distribution on RD-1. However, these authors themselves recognized thatthis method has some deficiencies. A method for overcoming these dificulties based onrecent developments for compositional data analysis and multivariate kernel estimationtheory, combining the ilr transformation with the use of the normal density with a fullbandwidth matrix, was recently proposed in Martín-Fernández, Chacón and Mateu-Figueras (2006). Here we present an extensive simulation study that compares bothmethods in practice, thus exploring the finite-sample behaviour of both estimators

Chaos and order in the contemporary city. The impact of urban spatial structure on population density and commuting distance in Barcelona, 1986-2001.

One of the criticisms leveled at the model of dispersed city found all over the world is its unarticulated, random, and undifferentiated nature. To check this idea in the Barcelona Metropolitan Region, we estimated the impact of the urban spatial structure (CBD, subcenters and transportation infrastructures) over the population density and commuting distance. The results are unfavorable to the hypothesis of the increasing destructuring of cities given that the explanatory capacity of both functions improves over time, both when other control variables are not included and when they are included.

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment