Distribution of Sandflies (Diptera:Psychodidae) on Tree-trunks in a Non-flooded Area of the Ducke Forest Reserve, Manaus, AM, Brazil

Sandflies were collected in the base of tree-trunks in the seasons of high and least rainfall in the Ducke Forest Reserve, near Manaus in the State of Amazonas. Lutzomyia umbratilis was the most abundant sandfly species. Caryocar villosum, Chrysophyllum amazonicum, Dinizia excelsa, Eschweilera atropetiolata and Parkia multijuga were the tree species on which most sandflies were collected and relative abundance were related to trunk characteristics. Seasonal patterns of sandfly distribution in the forest were observed.

A Mitochondrial DNA Phylogeny Indicates Close Relationships between Populations of Lutzomyia whitmani (Diptera: Psychodidae, Phlebotominae) from the Rain-forest Regions of Amazônia and Northeast Brazil

Phylogenetic analysis of all 31 described mitochondrial (cytochrome b) haplotypes of Lutzomyia whitmani demonstrated that new material from the State of Rondônia, in southwest Amazônia, forms a clade within a lineage found only in the rain-forest regions of Brazil. This rain-forest lineage also contains two other clades of haplotypes, one from eastern Amazônia and one from the Atlantic forest zone of northeast Brazil (including the type locality of the species in Ilhéus, State of Bahia). These findings do not favour recognizing two allopatric cryptic species of L. whitmani, one associated with the silvatic transmission of Leishmania shawi in southeast Amazônia and the other with the peridomestic transmission of Le. braziliensis in northeast Brazil. Instead, they suggest that there is (or has been in the recent past) a continuum of inter-breeding populations of L. whitmani in the rain-forest regions of Brazil.

Borrelia-like spirochetes recovered from ticks and small mammals collected in the Atlantic Forest Reserve, Cotia county, State of São Paulo, Brazil

Forty-four marsupials, 77 rodents and 161 ticks were captured in an Atlantic Forest Reserve in Cotia county, State of São Paulo, where human cases of Lyme disease (LD) simile were reported. Twenty-one borrelia-like spirochete isolates were recovered from the mammals' blood and rodent livers or spleens, and triturated ticks inoculated into BSK II medium. Our results suggest that the reservoirs and ticks collected may harbor borrelia-like spirochetes, some of which have an antigenic similarity with the unknown causative agent of LD simile in Brazil, and/or with North American Borrelia burgdorferi s.s.

Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms

The paper presents an approach for mapping of precipitation data. The main goal is to perform spatial predictions and simulations of precipitation fields using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integrating geostatistics and machine learning algorithms. To demonstrate how such models work, two case studies have been considered: first, a 2-day accumulation of heavy precipitation and second, a 6-day accumulation of extreme orographic precipitation. The first example is used to compare the performance of two optimization algorithms (conjugate gradients and Levenberg-Marquardt) of a neural network for the reproduction of extreme values. Hybrid models, which combine geostatistical and machine learning algorithms, are also treated in this context. The second dataset is used to analyze the contribution of radar Doppler imagery when used as external drift or as input in the models (kriging with external drift and neural networks). Model assessment is carried out by comparing independent validation errors as well as analyzing data patterns.

The Phlebotominae sand fly (Diptera: Psychodidae) fauna of two Atlantic Rain Forest Reserves in the State of Rio de Janeiro, Brazil

During two consecutive years, studies on the sand fly fauna in Poço das Antas and Fazenda Bom Retiro, two Atlantic Rain Forest Reserves from the State of Rio de Janeiro, were performed using Shannon traps, CDC light traps and human bait collections. Eleven species were identified; Lutzomyia longipalpis, L. migonei, L. edwardsi, L. intermedia, L. whitmani, L. fischeri, L. shannoni, L. ayrozai, L. hirsuta, L. monticola and L. misionensis (first occurrence in the State of Rio de Janeiro). L. intermedia and L. whitmani were the predominant anthropophilic species around houses, while L. hirsuta predominated in the forest.

Characterization of Triatoma guasayana biotopes in a hardwood forest of Santiago del Estero, Argentina

Triatoma guasayana is a silvatic triatomine species distributed in Argentina, Bolivia and Paraguay. The study was performed in a secondary forest of Santiago del Estero, Argentina. The abundance of T. guasayana was evaluated by census in the following wild biotopes: quimiles (Opuntia quimilo), chaguares (dry bromeliads), logs and underground burrows. Ten biotopes of each type were dismantled in winter (August) and another 40 in summer (January); all fauna was recorded. The biotopes most infested by T. guasayana were quimiles (65%), followed by chaguares (55%), and logs (25%). Quimiles and chaguares were infested in both seasons, whereas logs were positive only in summer and burrows were never infested. Infestation and abundance were higher in summer than in winter. The biotope structure is a key factor for T. guasayana colonization. The larger number of refuges, the constant presence of blood sources and suitable inner microclimatic conditions offered by quimiles may favour the persistence of T. guasayana colonies. The richness of invertebrate fauna per type of biotope was ranked in the same order as that of T. guasayana, suggesting similar microhabitat requirements for all studied arthropods.

Cinéma, machine à mondes : essai sur les films à univers multiples

Dans cet ouvrage, l'auteur propose une conceptualisation théorique de la coprésence en un même film de mondes multiples en abordant différents paramètres (hétérogénéité de la facture de l'image, pratiques du montage alterné, typologie des enchâssements, expansion sérielle, etc.) sur la base d'un corpus de films de fiction récents qui appartiennent pour la plupart au genre de la science-fiction (Matrix, Dark City, Avalon, Resident Evil, Avatar,...). Issue de la filmologie, la notion de « diégèse » y est développée à la fois dans le potentiel d'autonomisation dont témoigne la conception mondaine qui semble dominer aujourd'hui à l'ère des jeux vidéo, dans ses liens avec le récit et dans une perspective intermédiale. Les films discutés ont la particularité de mettre en scène des machines permettant aux personnages de passer d'un monde à l'autre : les modes de figuration de ces technologies sont investigués en lien avec les imaginaires du dispositif cinématographique et les potentialité du montage. La comparaison entre les films (Tron et son récent sequel, Totall Recall et son remake) et entre des oeuvres filmiques et littéraires (en particulier les nouvelles de Philip K. Dick et Simlacron 3 de Galouye) constitue un outil d'analyse permettant de saisir la contemporanéité de cette problématique, envisagée sur le plan esthétique dans le contexte de l'imagerie numérique.

Search for Borrelia sp. in ticks collected from potential reservoirs in an urban forest reserve in the State of Mato Grosso do Sul, Brazil: a short report

A total of 128 ticks of the genus Amblyomma were recovered from 5 marsupials (Didelphis albiventris) - with 4 recaptures - and 17 rodents (16 Bolomys lasiurus and 1 Rattus norvegicus) captured in an urban forest reserve in Campo Grande, State of Mato Grosso do Sul, Brazil. Of the ticks collected, 95 (78.9%) were in larval form and 22 (21.1%) were nymphs; the only adult (0.8%) was identified as A. cajennense. Viewed under dark-field microscopy in the fourth month after seeding, 9 cultures prepared from spleens and livers of the rodents, blood of the marsupials, and macerates of Amblyomma sp. nymphs revealed spiral-shaped, spirochete-like structures resembling those of Borrelia sp. Some of them showed little motility, while others were non-motile. No such structures could be found either in positive Giemsa-stained culture smears or under electron microscopy. No PCR amplification of DNA from those cultures could be obtained by employing Leptospira sp., B. burgdorferi, and Borrelia sp. primers. These aspects suggest that the spirochete-like structures found in this study do not fit into the genera Borrelia or Leptospira, requiring instead to be isolated for proper identification.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Horizontal stratification of the sand fly fauna (Diptera: Psychodidae) in a transitional vegetation between caatinga and tropical rain forest, state of Bahia, Brazil

A study about the horizontal stratification of the sand fly fauna in two distinct ecosystems, caatinga area, endemic for visceral leishmaniasis, and the tropical rain forest area, endemic for cutaneous leishmaniasis, was performed in the state of Bahia, Brazil. Lutzomyia longipalpis was predominant in the caatinga, and following it came the species L. capixaba and L. oswaldoi. In the tropical rain forest other species were found, such as L. intermedia, L. migonei, L. whitmani, L. yuilli, L.fischeri, L. damascenoi, L. evandroi, L. monticola, and L. lenti. It was found that the geographical limits of the vector species of visceral and cutaneous leishmaniasis are clearly defined by the biological and phytogeographic characteristics.

Host-ectoparasite specificity in a small mammal community in an area of Atlantic Rain Forest (Ilha Grande, State of Rio de Janeiro), Southeastern Brazil

The analyses of the ectoparasite species associated with a small mammal community on Ilha Grande, a coastal island in southern of the state of Rio de Janeiro, Brazil, evaluated the level of host-ectoparasite specificity. Was used the Jaccard index for qualitative data to analyse the similarity. The lowest value of similarity occurred between Proechimys iheringi and Marmosops incanus and between Sciurus aestuans and Nectomys squamipes (Cj = 0.08) and the highest between P. iheringi and Oxymycterus sp. (Cj = 0.33). This index showed a low value of similarity across the ectoparasite community. The only exception from this pattern of high host specificity occurred with P. iheringi and Oxymycterus sp., which shared five species of ectoparasites. The similarity values, for most of the cases, is smaller than 0.2.

Siphonaptera parasites of wild rodents and marsupials trapped in three mountain ranges of the Atlantic Forest in Southeastern Brazil

A study of the associations between small mammals and fleas was undertaken in three areas of the Atlantic Forest in Souhtheastern Brazil: Serra da Fartura, SP, Serra da Bocaina, SP, and Itatiaia, RJ. Trapping of small rodents and marsupials was done every 3 months during 2 years, from June 1999 to May 2001. A total 502 rodents (13 species) and 50 marsupials (7 species) were collected, and 185 hosts out of 552 (33.5%) captured in the traps were parasitized by 327 fleas belonging to 11 different species. New host records were determined for several flea species, and 5 significant associations between fleas and hosts were also found.