Ecological assessment of the red deer population in the Lousã Mountain

Durante o último século, as populações de cervídeos têm aumentado substancialmente um pouco por toda a Europa. O veado Cervus elaphus não foi exceção, apresentando atualmente uma ampla distribuição geográfica. Após a quase extinção de todas as populações selvagens desta espécie em Portugal, o número de efetivos de veado e a área de distribuição da espécie têm aumentado significativamente nas últimas décadas. Esta proliferação deveu-se fundamentalmente aos processos de reintrodução implementados em algumas zonas do país, como foi o caso da Serra da Lousã. Dez anos após a reintrodução, a expansão geográfica e demográfica é já uma realidade e a espécie assume um papel relevante tanto do ponto de vista cinegético como turístico. Com o aumento das populações de ungulados, surge a necessidade de aumentar o conhecimento existente sobre estas espécies, particularmente ao nível das estimativas populacionais, do uso e seleção de habitat, do comportamento e da fisiologia das populações. Neste sentido, um dos objetivos foi comparar quatro métodos de contagem de excrementos em termos de estimativa populacional, aplicabilidade e eficiência. Face aos resultados obtidos, o método de transectos lineares com distance sampling revelou-se o mais eficiente, providenciando uma boa precisão num menor tempo. Relativamente ao uso e seleção do habitat, recorrendo a transectos de contagem de excrementos e a observações diretas, verificou-se que o veado seleciona positivamente habitats que lhe proporcionam simultaneamente alimento e refúgio, como é o caso das áreas de ecótono. A preferência por áreas de ecótono evidencia um comportamento adaptativo de maximização de energia, no qual os animais optam por procurar refúgio na proximidade das áreas de alimentação de forma a minimizarem os dispêndios energéticos. Em termos de dinâmica populacional, verificou-se uma relação entre a densidade de veado e o tamanho dos seus grupos, bem como o efeito nos mesmos do coberto vegetal. Contudo, dado o seu alto dimorfismo sexual em termos de tamanho corporal, as preferências de habitat podem também ser em parte responsáveis pela segregação sexual fora da época de reprodução. Face aos resultados obtidos através do método de observação direta de animais, a segregação sexual surge como consequência da interação entre fatores sociais e de habitat, que resultam de diferentes estratégias reprodutivas por parte de ambos os sexos. As diferentes estratégias reprodutivas são também notórias em termos de condição física e imunológica, com os machos a aumentarem a sua condição durante as épocas de primavera e verão de forma a melhorarem a sua performance durante o cio, e as fêmeas a viverem grande parte do ano no limiar da condição física devido ao seu investimento na sobrevivência da sua descendência. Globalmente, o veado apresenta uma boa adaptação à Serra da Lousã e representa um importante recurso natural para esta região. Contudo, para que a proliferação desta população selvagem continue, é necessária a implementação de medidas de gestão adequadas a este ecossistema mediterrâneo.

Conservation status of the endangered chimpanzee (Pan troglodytes verus) in Lagoas de Cufada Natural Park : (Republic of Guinea-Bissau)

Tese de doutoramento, Biologia (Ecologia), Universidade de Lisboa, Faculdade de Ciências, 2014

Adaptive modeling and high quality spectral estimation for speech enhancement

In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

Adaptive filtering for high quality HMM based speech synthesis

In this work an adaptive filtering scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for Hidden Markov Model (HMM) based speech synthesis quality enhancement. The objective is to improve signal smoothness across HMMs and their related states and to reduce artifacts due to acoustic model's limitations. Both speech and artifacts are modelled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. Themodel parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The quality enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. The system's performance has been evaluated using mean opinion score tests and the proposed technique has led to improved results.

Grain size analyses in tin-lead glazes based on 2d-sections

A problem in the archaeometric classification of Catalan Renaissance pottery is the fact, that the clay supply of the pottery workshops was centrally organized by guilds, and therefore usually all potters of a single production centre produced chemically similar ceramics. However, analysing the glazes of the ware usually a large number of inclusions in the glaze is found, which reveal technological differences between single workshops. These inclusions have been used by the potters in order to opacify the transparent glaze and to achieve a white background for further decoration. In order to distinguish different technological preparation procedures of the single workshops, at a Scanning Electron Microscope the chemical composition of those inclusions as well as their size in the two-dimensional cut is recorded. Based on the latter, a frequency distribution of the apparent diameters is estimated for each sample and type of inclusion. Following an approach by S.D. Wicksell (1925), it is principally possible to transform the distributions of the apparent 2D-diameters back to those of the true three-dimensional bodies. The applicability of this approach and its practical problems are examined using different ways of kernel density estimation and Monte-Carlo tests of the methodology. Finally, it is tested in how far the obtained frequency distributions can be used to classify the pottery

Active regions for colour texture segmentation integrating region and boundary information

In this paper a colour texture segmentation method, which unifies region and boundary information, is proposed. The algorithm uses a coarse detection of the perceptual (colour and texture) edges of the image to adequately place and initialise a set of active regions. Colour texture of regions is modelled by the conjunction of non-parametric techniques of kernel density estimation (which allow to estimate the colour behaviour) and classical co-occurrence matrix based texture features. Therefore, region information is defined and accurate boundary information can be extracted to guide the segmentation process. Regions concurrently compete for the image pixels in order to segment the whole image taking both information sources into account. Furthermore, experimental results are shown which prove the performance of the proposed method

An Estimate of Nest Loss in Canada Due to Industrial Forestry Operations

Annual loss of nests by industrial (nonwoodlot) forest harvesting in Canada was estimated using two avian point-count data sources: (1) the Boreal Avian Monitoring Project (BAM) dataset for provinces operating in this biome and (2) available data summarized for the major (nonboreal) forest regions of British Columbia. Accounting for uncertainty in the proportion of harvest occurring during the breeding season and in avian nesting densities, our estimate ranges from 616 thousand to 2.09 million nests. Estimates of the impact on numbers of individuals recruited into the adult breeding population were made based on the application of survivorship estimates at various stages of the life cycle. Future improvements to this estimate are expected as better and more extensive avian breeding pair density estimates become available and as provincial forestry statistics become more refined, spatially and temporally. The effect of incidental take due to forestry is not uniform and is disproportionately centered in the southern boreal. Those species whose ranges occur primarily in these regions are most at risk for industrial forestry in general and for incidental take in particular. Refinements to the nest loss estimate for industrial forestry in Canada will be achieved primarily through the provision of more accurate estimates of the area of forest harvested annually during the breeding season stratified by forest type and Bird Conservation Region (BCR). A better understanding of survivorship among life-history stages for forest birds would also allow for better modeling of the effect of nest loss on adult recruitment. Finally, models are needed to project legacy effects of forest harvesting on avian populations that take into account forest succession and accompanying cumulative effects of landscape change.

A process for analysis of microarray comparative genomics hybridisation studies for bacterial genomes

Background: Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results: The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion: After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.

A Gaussian-mixture ensemble transform filter

We generalize the popular ensemble Kalman filter to an ensemble transform filter, in which the prior distribution can take the form of a Gaussian mixture or a Gaussian kernel density estimator. The design of the filter is based on a continuous formulation of the Bayesian filter analysis step. We call the new filter algorithm the ensemble Gaussian-mixture filter (EGMF). The EGMF is implemented for three simple test problems (Brownian dynamics in one dimension, Langevin dynamics in two dimensions and the three-dimensional Lorenz-63 model). It is demonstrated that the EGMF is capable of tracking systems with non-Gaussian uni- and multimodal ensemble distributions. Copyright © 2011 Royal Meteorological Society

Análises espaciais na identificação das áreas de risco para a esquistossomose mansônica no município de Lauro de Freitas, Bahia, Brasil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Home ranges of Guiana dolphins (Sotalia guianensis) (Cetacea: Delphinidae) in the Cananeia estuary, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Distance software: design and analysis of distance sampling surveys for estimating population size

1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modeling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modeling analysis engine for spatial and habitat-modeling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of- the-art software that implements these methods is described that makes the methods accessible to practicing ecologists.

Monitoring Raccoon Rabies in Alabama: The Potential Effects of Habitat and Demographics

Density, morphometrics, and disease prevalence of raccoon populations were determined in 4 habitats (agriculture, riverine, managed, and forested) in central Alabama. In addition we monitored 71 collared raccoons to determine survival. Density estimates were similar in the agriculture (ag) and riverine habitats in central Alabama with 8 raccoons/km2, and lower in the forested habitat at 5 raccoons/ km2. Retention of juveniles did not appear to contribute to observed higher populations in the riverine and ag habitat. Although the riverine and ag, possibly due to supplemental resources, likely provide better habitat for raccoons, we found only body size in female raccoons to be different across habitats (P = 0.001). Human-caused mortality (either hunting or missing and presumed killed) was the main cause of mortality in several raccoon populations during fall; however, fall survival did not differ between the habitats (χ = 1.47, d.f. = 3, P = 0.69). Although rabies and distemper virus were prevalent in all habitats, they did not appear to contribute to mortality even with a high proportion of the population exhibiting positive CDV titers (ag – 44%, managed- 50%) and rabies titers (managed- 57% and riverine habitat-60%).

A snapshot of suspended sediment and fluid mud occurrence in a mixed-energy embayment, Tijucas Bay, Brazil

Along the southern Brazilian coast, Tijucas Bay is known for its unique muddy tidal flats associated with chenier plains. Previous field observations pointed to very high suspended sediment concentrations (SSCs) in the inner parts of the bay, and in the estuary of the Tijucas River, suggesting the presence of fluid mud. In this study, the occurrences of suspended sediments and fluid mud were examined during a larger-scale, high-resolution 2-day field campaign on 1-2 May 2007, encompassing survey lines spanning nearly 80 km, 75 water sampling stations for near-bottom density estimates, and ten sediment sampling stations. Wave refraction modeling provided qualitative wave energy estimates as a function of different incidence directions. The results show that SSC increases toward the inner bay near the water surface, but seaward near the bottom. This suggests that suspended sediment is supplied by the local rivers, in particular the Tijucas. Near-surface SSCs were of the order of 50 mg l(-1) close to the shore, but exceeded 100 mg l(-1) near the bottom in the deeper parts of the bay. Fluid mud thickness and location given by densimetry and echo-sounding agreed in some places, although being mostly discordant. The best agreement was observed where wave energy was high during the campaign. The discrepancy between the two methods may be an indication for the existence of fluid mud, which is recorded by one method but not the other. Agreement is considered to be an indication of fluidization, whereas disagreement indicates more consolidation. Wave modeling suggests that waves from the ENE and SE are the most effective in supplying energy to the inner bay, which may induce the liquefaction of mud deposits to form fluid mud. Nearshore mud resuspension and weak horizontal currents result in sediment-laden offshore flow, which explains the higher SSCs measured in the deeper parts of the bay, besides providing a mechanism for fine-sediment export to the inner shelf.

Morphological Homogeneity of Neurons: Searching for Outlier Neuronal Cells

We report a morphology-based approach for the automatic identification of outlier neurons, as well as its application to the NeuroMorpho.org database, with more than 5,000 neurons. Each neuron in a given analysis is represented by a feature vector composed of 20 measurements, which are then projected into a two-dimensional space by applying principal component analysis. Bivariate kernel density estimation is then used to obtain the probability distribution for the group of cells, so that the cells with highest probabilities are understood as archetypes while those with the smallest probabilities are classified as outliers. The potential of the methodology is illustrated in several cases involving uniform cell types as well as cell types for specific animal species. The results provide insights regarding the distribution of cells, yielding single and multi-variate clusters, and they suggest that outlier cells tend to be more planar and tortuous. The proposed methodology can be used in several situations involving one or more categories of cells, as well as for detection of new categories and possible artifacts.