Bayesian estimation of ancestral character states on phylogenies

Biologists frequently attempt to infer the character states at ancestral nodes of a phylogeny from the distribution of traits observed in contemporary organisms. Because phylogenies are normally inferences from data, it is desirable to account for the uncertainty in estimates of the tree and its branch lengths when making inferences about ancestral states or other comparative parameters. Here we present a general Bayesian approach for testing comparative hypotheses across statistically justified samples of phylogenies, focusing on the specific issue of reconstructing ancestral states. The method uses Markov chain Monte Carlo techniques for sampling phylogenetic trees and for investigating the parameters of a statistical model of trait evolution. We describe how to combine information about the uncertainty of the phylogeny with uncertainty in the estimate of the ancestral state. Our approach does not constrain the sample of trees only to those that contain the ancestral node or nodes of interest, and we show how to reconstruct ancestral states of uncertain nodes using a most-recent-common-ancestor approach. We illustrate the methods with data on ribonuclease evolution in the Artiodactyla. Software implementing the methods ( BayesMultiState) is available from the authors.

Shear wave velocity estimation in the metropolitan area of Málaga (S Spain)

We carry out a seismic noise study based on array measurements at three sites in the Málaga basin, South Spain, for the further estimation of shear wave velocity profiles. For this purpose, we use both the H/V method and the f–k technique in order to characterize the different materials present in the zone, i.e., Quaternary sediments and Pliocene sedimentary rocks above the bedrock. The H/V analysis shows frequency peaks going from 1 Hz, in areas close to the border of the basin, to 0.3 Hz in places located toward the center of the formation. The f–k analysis allows obtaining the dispersion curves associated with each site and subsequently, estimating the Vs profiles by inversion of the respective group velocities. In this way, the basin basement can be characterized by S-wave velocities greater than 2000 m/s. Regarding the basin fill, it is divided into three layers defined by different wave velocity intervals. The shallowest one is featured by velocities ranging from 150 to 400 m/s and comprises the Quaternary sediments, while velocities going from 550–700 to1200–1600 m/s characterize the two underlying layers composed by Pliocene sediments. Finally, the information provided by the three Vs profiles is integrated in a 2D cross-section of the basin to have a spatial view of its sedimentary structure. The results obtained here, in addition to providing useful information about the infill of the basin near the metropolitan area of Málaga, will be very helpful for future seismic zonation studies in the region.

Simulation of runoff and recharge and estimation of constituent loads in runoff, Edwards aquifer recharge zone (outcrop) and catchment area, Bexar County, Texas, 1997-2000 /

Includes bibliographical references (p. 31).

Allometric models for estimating the phytomass of a secondary Atlantic Forest area of southeastern Brazil

The purpose of this study was to develop and validate equations to estimate the aboveground phytomass of a 30 years old plot of Atlantic Forest. In two plots of 100 m², a total of 82 trees were cut down at ground level. For each tree, height and diameter were measured. Leaves and woody material were separated in order to determine their fresh weights in field conditions. Samples of each fraction were oven dried at 80 °C to constant weight to determine their dry weight. Tree data were divided into two random samples. One sample was used for the development of the regression equations, and the other for validation. The models were developed using single linear regression analysis, where the dependent variable was the dry mass, and the independent variables were height (h), diameter (d) and d²h. The validation was carried out using Pearson correlation coefficient, paired t-Student test and standard error of estimation. The best equations to estimate aboveground phytomass were: lnDW = -3.068+2.522lnd (r² = 0.91; s y/x = 0.67) and lnDW = -3.676+0.951ln d²h (r² = 0.94; s y/x = 0.56).

Modelos preditores da fitomassa aérea da Floresta Baixa de Restinga

Este estudo teve como objetivo desenvolver modelos preditores de fitomassa epigéa da vegetação arbórea da Floresta Baixa de Restinga. Foram selecionadas 102 árvores de 29 espécies ocorrentes na área de estudo e 102 indivíduos de jerivá (Syagrus romanzoffiana (Cham.) Glassman), distribuídos proporcionalmente entre as classes de diâmetro da vegetação arbórea. As árvores foram cortadas, ao nível do solo e foram medidos a altura total e o diâmetro à altura do peito (DAP) de cada árvore. As folhas foram separadas do lenho e a massa fresca da porção lenhosa e foliar medidas separadamente. Amostras de cada fração foram secas a 70 °C, até peso constante, para determinação da massa seca das árvores. Os modelos foram desenvolvidos através de análise de regressão linear, sendo a variável dependente a massa seca (MS) das árvores e as variáveis independentes a altura (h), o diâmetro a altura do peito (d) e as relações d² h e d² h multiplicada pela densidade da madeira (ρ d² h). Os modelos desenvolvidos indicam que o diâmetro explica grande parte da variabilidade da fitomassa das árvores da restinga e a altura é a variável explanatória da equação específica para o jerivá. Os modelos selecionados foram: ln MS (kg) = -1,352 + 2,009 ln d (R² = 0,96; s yx = 0,34) para a comunidade vegetal sem jerivá, ln MS (kg) = -2,052 + 0,801 ln d² h (R² = 0,94; s yx = 0,38) para a comunidade incluindo o jerivá, e ln MS (kg) = -0,884 + 2,40 ln h (R² = 0,92; s yx = 0,49) para o jerivá.

Circulation of antibodies against yellow fever virus in a simian population in the area of Porto Primavera Hydroelectric Plant, São Paulo, Brazil

Yellow fever (YF) is an acute viral infectious disease transmitted by mosquitoes which occurs in two distinct epidemiological cycles: sylvatic and urban. In the sylvatic cycle, the virus is maintained by monkey's infection and transovarian transmission in vectors. Surveillance of non-human primates is required for the detection of viral circulation during epizootics, and for the identification of unaffected or transition areas. An ELISA (enzyme-linked immunosorbent assay) was standardized for estimation of the prevalence of IgG antibodies against yellow fever virus in monkey sera (Alouatta caraya) from the reservoir area of Porto Primavera Hydroelectric Plant, in the state of São Paulo, Brazil. A total of 570 monkey sera samples were tested and none was reactive to antibodies against yellow fever virus. The results corroborate the epidemiology of yellow fever in the area. Even though it is considered a transition area, there were no reports to date of epizootics or yellow fever outbreaks in humans. Also, entomological investigations did not detect the presence of vectors of this arbovirus infection. ELISA proved to be fast, sensitive, an adequate assay, and an instrument for active search in the epidemiological surveillance of yellow fever allowing the implementation of prevention actions, even before the occurrence of epizootics.

Circulation of antibodies against yellow fever virus in a simian population in the area of Porto Primavera hydroeletric plant, São Paulo, Brazil

A febre amarela (FA) é doença infecciosa aguda de origem viral transmitida por mosquitos. No ciclo silvestre, o vírus é mantido por meio da infecção de macacos e da transmissão transovariana nos vetores. A vigilância sobre populações de primatas não humanos torna-se necessária para detectar a circulação viral, quando ainda está restrito a epizootias, e para determinar sua presença em regiões indenes ou de transição para a doença. Padronizou-se a técnica ELISA (Enzyme Linked Immunosorbent Assay) para determinar a prevalência de anticorpos da classe IgG contra o vírus da FA em soros de bugios (Alouatta caraya) da região do reservatório da Usina Hidrelétrica de Porto Primavera, SP. Foram testados soros de 570 macacos sendo que nenhuma amostra mostrou-se reativa para a presença de anticorpos contra o vírus da FA. Os resultados são coerentes com a epidemiologia da FA na região. Mesmo sendo área de transição, não se conhece, até o momento, ocorrência de epizootia ou surto de FA em humanos e investigações entomológicas não apontaram a presença de vetores para esta arbovirose. A técnica mostrou-se sensível, rápida e útil à vigilância epidemiológica como instrumento de busca ativa permitindo desencadear ações preventivas, como vacinação, antes mesmo do surgimento de epizootias

Continental passive microwave-based rainfall estimation algorithm: Application to the Amazon Basin

This paper presents a new statistical algorithm to estimate rainfall over the Amazon Basin region using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The algorithm relies on empirical relationships derived for different raining-type systems between coincident measurements of surface rainfall rate and 85-GHz polarization-corrected brightness temperature as observed by the precipitation radar (PR) and TMI on board the TRMM satellite. The scheme includes rain/no-rain area delineation (screening) and system-type classification routines for rain retrieval. The algorithm is validated against independent measurements of the TRMM-PR and S-band dual-polarization Doppler radar (S-Pol) surface rainfall data for two different periods. Moreover, the performance of this rainfall estimation technique is evaluated against well-known methods, namely, the TRMM-2A12 [ the Goddard profiling algorithm (GPROF)], the Goddard scattering algorithm (GSCAT), and the National Environmental Satellite, Data, and Information Service (NESDIS) algorithms. The proposed algorithm shows a normalized bias of approximately 23% for both PR and S-Pol ground truth datasets and a mean error of 0.244 mm h(-1) ( PR) and -0.157 mm h(-1)(S-Pol). For rain volume estimates using PR as reference, a correlation coefficient of 0.939 and a normalized bias of 0.039 were found. With respect to rainfall distributions and rain area comparisons, the results showed that the formulation proposed is efficient and compatible with the physics and dynamics of the observed systems over the area of interest. The performance of the other algorithms showed that GSCAT presented low normalized bias for rain areas and rain volume [0.346 ( PR) and 0.361 (S-Pol)], and GPROF showed rainfall distribution similar to that of the PR and S-Pol but with a bimodal distribution. Last, the five algorithms were evaluated during the TRMM-Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) 1999 field campaign to verify the precipitation characteristics observed during the easterly and westerly Amazon wind flow regimes. The proposed algorithm presented a cumulative rainfall distribution similar to the observations during the easterly regime, but it underestimated for the westerly period for rainfall rates above 5 mm h(-1). NESDIS(1) overestimated for both wind regimes but presented the best westerly representation. NESDIS(2), GSCAT, and GPROF underestimated in both regimes, but GPROF was closer to the observations during the easterly flow.

The risk of chikungunya fever in a dengue-endemic area

Background. Chikungunya, an alphavirus of the Togaviridae family, causes a febrile disease transmitted to humans by the bite of infected Aedes mosquitoes. This infection is reaching endemic levels in many Southeast Asian countries. Symptoms include sudden onset of fever, chills, headache, nausea, vomiting, joint pain with or without swelling, low back pain, and rash. According to the World Health Organization, there are 2 billion people living in Aedes-infested areas. In addition, traveling to these areas is popular, making the potential risk of infections transmitted by the bite of infected Aedes mosquitoes very high. Methods. We proposed a mathematical model to estimate the risk of acquiring chikungunya fever in an Aedes-infested area by taking the prevalence of dengue fever into account. The basic reproduction number for chikungunya fever R-0chik can be written as a function of the basic reproduction number of dengue R-0dengue by calculating the ratio R-0chik/R-0dengue. From R-0chik, we estimated the force of infection and the risk of acquiring the disease both for local residents of a dengue-endemic area and for travelers to this area. Results. We calculated that R-0chik is 64.4% that of R-0dengue. The model was applied to a hypothetical situation, namely, estimating the individual risk of acquiring chikungunya fever in a dengue-endemic area, both for local inhabitants (22% in steady state) and for visiting travelers (from 0.31% to 1.23% depending on the time spent in the area). Conclusions. The method proposed based on the output of a dynamical model is innovative and provided an estimation of the risk of infection, both for local inhabitants and for visiting travelers.

Radio link quality estimation in wireless sensor networks: a survey

Radio link quality estimation in Wireless Sensor Networks (WSNs) has a fundamental impact on the network performance and also affects the design of higher-layer protocols. Therefore, for about a decade, it has been attracting a vast array of research works. Reported works on link quality estimation are typically based on different assumptions, consider different scenarios, and provide radically different (and sometimes contradictory) results. This article provides a comprehensive survey on related literature, covering the characteristics of low-power links, the fundamental concepts of link quality estimation in WSNs, a taxonomy of existing link quality estimators, and their performance analysis. To the best of our knowledge, this is the first survey tackling in detail link quality estimation in WSNs. We believe our efforts will serve as a reference to orient researchers and system designers in this area.

Estimation of vegetation carbon stock in Portugal using land use/ land cover data

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies