Procedimento para estudo da escolha modal em viagens realizadas por estudantes de instituições de ensino médio, mediado pela psicologia social

Tese (doutorado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, 2016.

Modeling and Mapping Agroforestry Aboveground Biomass in the Brazilian Amazon Using Airborne Lidar Data.

Agroforestry has large potential for carbon (C) sequestration while providing many economical, social, and ecological benefits via its diversified products. Airborne lidar is considered as the most accurate technology for mapping aboveground biomass (AGB) over landscape levels. However, little research in the past has been done to study AGB of agroforestry systems using airborne lidar data. Focusing on an agroforestry system in the Brazilian Amazon, this study first predicted plot-level AGB using fixed-effects regression models that assumed the regression coefficients to be constants. The model prediction errors were then analyzed from the perspectives of tree DBH (diameter at breast height)?height relationships and plot-level wood density, which suggested the need for stratifying agroforestry fields to improve plot-level AGB modeling. We separated teak plantations from other agroforestry types and predicted AGB using mixed-effects models that can incorporate the variation of AGB-height relationship across agroforestry types. We found that, at the plot scale, mixed-effects models led to better model prediction performance (based on leave-one-out cross-validation) than the fixed-effects models, with the coefficient of determination (R2) increasing from 0.38 to 0.64. At the landscape level, the difference between AGB densities from the two types of models was ~10% on average and up to ~30% at the pixel level. This study suggested the importance of stratification based on tree AGB allometry and the utility of mixed-effects models in modeling and mapping AGB of agroforestry systems.

Modelação de taxas de resgate em seguros de vida

Mestrado em Ciências Actuariais

Analysis of the claims data of a life insurance portfolio

Mestrado em Ciências Actuariais

Influência da gestão do habitat na distribuição e abundância do coelho-bravo no Sítio Natura 2000 Monchique

O coelho-bravo, devido à sua importância ecológica e económica, tem sido alvo de diversos planos de gestão e vários esforços têm sido empreendidos no sentido de contrariar o decréscimo das suas populações. Este estudo foi realizado em três zonas de caça do Sítio Monchique e o principal objectivo é determinar se as medidas de gestão implementadas influenciam a distribuição e abundância da espécie na área de estudo. A abundância relativa foi interpolada com o método "Inverso do Peso da Distância" {IDW), e as relações entre presença de coelho e os descritores ambientais foram analisadas através de Modelos Lineares Generalizados (GLM). Os resultados da modelação estatística mostraram que as medidas de melhoria de habitat parecem ter sido determinantes para um aumento da área de distribuição do coelho-bravo nos locais intervencionados. São propostas novas medidas de gestão, cujo objectivo será promover a continuação do aumento da ocorrência e abundância da espécie neste local. /ABSTRACT: The wild rabbit, due to its ecological and economical role, has been the target of several management plans and considerable efforts have been made to enhance its populations. This study was held in three game estates located inside Monchique Natura 2000. Site and aims to determine if the habitat management actions implemented in the study area influence rabbit distribution and abundance. The relative abundance was interpolated to all study area with lnverse Distance Weight method {IDW} and the relationships between rabbit presence and the environmental descriptors were evaluated with Generalized Linear Models (GLM). The results of the statistical modelling showed that the management actions seem to have contributed significantly to an enhancement on the rabbit occurrence in the studied game estates. Several new management actions are proposed with the aim to continue to increase rabbit occurrence and abundance in this site.

Prevalence of chronic diseases in private healthcare sector of South Africa: A threat to public health

Purpose: To evaluate the prevalence of patients suffering from registered chronic disease list (CDL) conditions in a section of the South African private health sector from 2008 - 2012. Methods: This study was a retrospective analysis of the medicine claims database of a nationally (South African) representative Pharmacy Benefit Management (PBM) company data between 2008 and 2012. Statistical analysis was used to analyse the data. Descriptive analysis was performed to calculate the prevalence of CDL conditions for the entire population, and stratified by age and gender. However, MIXED linear modelling was used to determine changes in the average number of CDL conditions per patient, adjusted for age and gender from 2008 - 2012. Results: An increase of 0.20 in chronic diseases was observed from 2008 - 2012 in patients having any CDL condition, with an average of 1.57 (1.57 - 1.58, 95 % CI) co-morbid CDL conditions in 2008 and 1.77 (1.77 - 1.78, 95 % CI) in 2012. This increase in average number of CDL conditions per patient between 2008 and 2012 was statistically significant (p < 0.05), but with no large practical significance (d < 0.8). Conclusion: Prevalence of patients with CDL conditions along with risk of co-morbidity has been increasing with time in the private health sector of South Africa. Risk of increased co-morbidity with age and among different genders was prevalent.

Sex-biased differences in the effects of host individual, host population and environmental traits driving tick parasitism in red deer

The interactions between host individual, host population, and environmental factors modulate parasite abundance in a given host population. Since adult exophilic ticks are highly aggregated in red deer (Cervus elaphus) and this ungulate exhibits significant sexual size dimorphism, life history traits and segregation, we hypothesized that tick parasitism on males and hinds would be differentially influenced by each of these factors. To test the hypothesis, ticks from 306 red deer-182 males and 124 females-were collected during 7 years in a red deer population in south-central Spain. By using generalized linear models, with a negative binomial error distribution and a logarithmic link function, we modeled tick abundance on deer with 20 potential predictors. Three models were developed: one for red deer males, another for hinds, and one combining data for males and females and including "sex" as factor. Our rationale was that if tick burdens on males and hinds relate to the explanatory factors in a differential way, it is not possible to precisely and accurately predict the tick burden on one sex using the model fitted on the other sex, or with the model that combines data from both sexes. Our results showed that deer males were the primary target for ticks, the weight of each factor differed between sexes, and each sex specific model was not able to accurately predict burdens on the animals of the other sex. That is, results support for sex-biased differences. The higher weight of host individual and population factors in the model for males show that intrinsic deer factors more strongly explain tick burden than environmental host-seeking tick abundance. In contrast, environmental variables predominated in the models explaining tick burdens in hinds.

Effect of cattle on Salmonella carriage, diversity and antimicrobial resistance in free-ranging wild boar (Sus scrofa) in northeastern Spain

Salmonella is distributed worldwide and is a pathogen of economic and public health importance. As a multi-host pathogen with a long environmental persistence, it is a suitable model for the study of wildlife-livestock interactions. In this work, we aim to explore the spill-over of Salmonella between free-ranging wild boar and livestock in a protected natural area in NE Spain and the presence of antimicrobial resistance. Salmonella prevalence, serotypes and diversity were compared between wild boars, sympatric cattle and wild boars from cattle-free areas. The effect of age, sex, cattle presence and cattle herd size on Salmonella probability of infection in wild boars was explored by means of Generalized Linear Models and a model selection based on the Akaike's Information Criterion. Prevalence was higher in wild boars co-habiting with cattle (35.67%, CI 95% 28.19-43.70) than in wild boar from cattle-free areas (17.54%, CI 95% 8.74-29.91). Probability of a wild boar being a Salmonella carrier increased with cattle herd size but decreased with the host age. Serotypes Meleagridis, Anatum and Othmarschen were isolated concurrently from cattle and sympatric wild boars. Apart from serotypes shared with cattle, wild boars appear to have their own serotypes, which are also found in wild boars from cattle-free areas (Enteritidis, Mikawasima, 4:b:- and 35:r:z35). Serotype richness (diversity) was higher in wild boars co-habiting with cattle, but evenness was not altered by the introduction of serotypes from cattle. The finding of a S. Mbandaka strain resistant to sulfamethoxazole, streptomycin and chloramphenicol and a S. Enteritidis strain resistant to ciprofloxacin and nalidixic acid in wild boars is cause for public health concern.

Landscape Patterns of Permafrost Disturbance and Degradation in the Canadian High Arctic

Intensification of permafrost disturbances such as active layer detachments (ALDs) and retrogressive thaw slumps (RTS) have been observed across the circumpolar Arctic. These features are indicators of unstable conditions stemming from recent climate warming and permafrost degradation. In order to understand the processes interacting to give rise to these features, a multidisciplinary approach is required; i.e., interactions between geomorphology, hydrology, vegetation and ground thermal conditions. The goal of this research is to detect and map permafrost disturbance, predict landscape controls over disturbance and determine approaches for monitoring disturbance, all with the goal of contributing to the mitigation of permafrost hazards. Permafrost disturbance inventories were created by applying semi-automatic change detection techniques to IKONOS satellite imagery collected at the Cape Bounty Arctic Watershed Observatory (CBAWO). These methods provide a means to estimate the spatial distribution of permafrost disturbances for a given area for use as an input in susceptibility modelling. Permafrost disturbance susceptibility models were then developed using generalized additive and generalized linear models (GAM, GLM) fitted to disturbed and undisturbed locations and relevant GIS-derived predictor variables (slope, potential solar radiation, elevation). These models successfully delineated areas across the landscape that were susceptible to disturbances locally and regionally when transferred to an independent validation location. Permafrost disturbance susceptibility models are a first-order assessment of landscape susceptibility and are promising for designing land management strategies for remote permafrost regions. Additionally, geomorphic patterns associated with higher susceptibility provide important knowledge about processes associated with the initiation of disturbances. Permafrost degradation was analyzed at the CBAWO using differential interferometric synthetic aperture radar (DInSAR). Active-layer dynamics were interpreted using inter-seasonal and intra-seasonal displacement measurements and highlight the importance of hydroclimatic factors on active layer change. Collectively, these research approaches contribute to permafrost monitoring and the assessment of landscape-scale vulnerability in order to develop permafrost disturbance mitigation strategies.

What Are Effective Program Characteristics of Self-Management Interventions in Patients With Heart Failure? : An Individual Patient Data Meta-analysis

Background To identify those characteristics of self-management interventions in patients with heart failure (HF) that are effective in influencing health-related quality of life, mortality, and hospitalizations. Methods and Results Randomized trials on self-management interventions conducted between January 1985 and June 2013 were identified and individual patient data were requested for meta-analysis. Generalized mixed effects models and Cox proportional hazard models including frailty terms were used to assess the relation between characteristics of interventions and health-related outcomes. Twenty randomized trials (5624 patients) were included. Longer intervention duration reduced mortality risk (hazard ratio 0.99, 95% confidence interval [CI] 0.97–0.999 per month increase in duration), risk of HF-related hospitalization (hazard ratio 0.98, 95% CI 0.96–0.99), and HF-related hospitalization at 6 months (risk ratio 0.96, 95% CI 0.92–0.995). Although results were not consistent across outcomes, interventions comprising standardized training of interventionists, peer contact, log keeping, or goal-setting skills appeared less effective than interventions without these characteristics. Conclusion No specific program characteristics were consistently associated with better effects of self-management interventions, but longer duration seemed to improve the effect of self-management interventions on several outcomes. Future research using factorial trial designs and process evaluations is needed to understand the working mechanism of specific program characteristics of self-management interventions in HF patients.

The Effect of Climate Variability on Main Components of Cow Milk in Iran

The main purpose of this study is to assess the relationship between six bioclimatic indices for cattle (temperature humidity (THI), environmental stress (ESI), equivalent temperature (ESI), heat load (HLI), modified heat load (HLInew) and respiratory rate predictor(RRP)) and fundamental milk components (fat, protein, and milk yield) considering uncertainty. The climate parameters used to calculate the climate indices were taken from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis from 2002 to 2010. Cow milk data were considered for the same period from April to September when cows use natural pasture, with possibility for cows to choose to stay in the barn or to graze on the pasture in the pasturing system. The study is based on a linear regression analysis using correlations as a summarizing diagnostic. Bootstrapping is used to represent uncertainty estimation through resampling in the confidence intervals. To find the relationships between climate indices (THI, ETI, HLI, HLInew, ESI and RRP) and main components of cow milk (fat, protein and yield), multiple liner regression is applied. The least absolute shrinkage selection operator (LASSO) and the Akaike information criterion (AIC) techniques are applied to select the best model for milk predictands with the smallest number of climate predictors. Cross validation is used to avoid over-fitting. Based on results of investigation the effect of heat stress indices on milk compounds separately, we suggest the use of ESI and RRP in the summer and ESI in the spring. THI and HLInew are suggested for fat content and HLInew also is suggested for protein content in the spring season. The best linear models are found in spring between milk yield as predictands and THI, ESI,HLI, ETI and RRP as predictors with p-value < 0.001 and R2 0.50, 0.49. In summer, milk yield with independent variables of THI, ETI and ESI show the highest relation (p-value < 0.001) with R2 (0.69). For fat and protein the results are only marginal. It is strongly suggested that new and significant indices are needed to control critical heat stress conditions that consider more predictors of the effect of climate variability on animal products, such as sunshine duration, quality of pasture, the number of days of stress (NDS), the color of skin with attention to large black spots, and categorical predictors such as breed, welfare facility, and management system. This methodology is suggested for studies investigating the impacts of climate variability/change on food quality/security, animal science and agriculture using short term data considering uncertainty or data collection is expensive, difficult, or data with gaps.

Environmental influence on commercial fishery landings of small pelagic fish in Portugal

Small pelagic fishes are particularly abundant in areas with high environmental variability (zones of coastal upwelling and areas of tidal mixing and river discharge), and because of this, their abundance suffers large inter-annual and inter-decadal fluctuations. In Portugal, the most important species in terms of landings are European sardine, Atlantic horse mackerel and Atlantic chub mackerel. Small pelagic fish landings account for 62.8 % of the total fish biomass and represent 32.7 % of the economical value of all catches. We have investigated trends in landings of these small pelagic fishes and detected the effects of environmental factors in this fishery. In order to explain the variability of landings of small pelagic fishes, we have used official landings (1965-2012) for trawling and purse seine fisheries and applied generalized linear models, using the North Atlantic Oscillation index (NAO) (annual and winter NAO index), sea surface temperature (SST), wind data (strength and North-South and East-West wind components) and rainfall, as explanatory variables. Regression analysis was used to describe the relationship between landings and SST. The models explained between 50.16 and 51.07 % of the variability of the LPUE, with the most important factors being winter NAO index, SST and wind strength. The LPUE of European sardine and Atlantic horse mackerel was negatively correlated with SST, and LPUE of Atlantic chub mackerel was positively correlated with SST. The use of landings of three important species of small pelagic fishes allowed the detection of variations in landings associated with changes in sea water temperature and NAO index.

Geographical and environmental correlates of big and small game in Andalusia (southern Spain)

In Andalusia, southern Spain, each game estate applies its own rules and presents its results in annual hunting reports, which have been mandatory for Spanish game estates since 1989. We used the information about hunting yields, included in 32134 annual hunting reports produced during the period 1993/94 to 2001/02 by 6049 game estates, to determine the current distribution of hunting yields of big and small game species in Andalusia. Using generalised linear models and a geographic information system, we determined the most favourable municipalities to big and small game, respectively, and delimited potential areas to attain good hunting yields for big and small game at a 1-km2 resolution. Municipalities and areas favourable to big game are mainly located in the Sierra Morena and the westernmost fringe of the Betic Range, while those favourable to small game occupy the upper Guadalquivir River valley. There is a clear segregation between big and small game species according to the physiography and land uses of the territory. Big game species are typical of Mediterranean woodland areas, while the most emblematic small game species prefer agricultural areas. Our results provide a territorial ordination of hunting yields in southern Spain and have several potential applications in strategic planning for hunting activities and biodiversity conservation in Andalusia that can be extrapolated to other regions.

ABOVE-GROUND BIOMASS ESTIMATION OF OPUNTIA FICUS-INDICA (L.) MILL. FOR FORAGE CROP IN A MEDITERRANEAN ENVIRONMENT BY USING NON-DESTRUCTIVE METHODS

In marginal lands Opuntia ficus-indica (OFI) could be used as an alternative fruit and forage crop. The plant vigour and the biomass production were evaluated in Portuguese germplasm (15 individuals from 16 ecotypes) by non-destructive methods, 2 years following planting in a marginal soil and dryland conditions. Two Italian cultivars (Gialla and Bianca) were included in the study for comparison purposes. The biomass production and the plant vigour were estimated by measuring the cladodes number and area, and the fresh (FW) and dry weight (DW) per plant. We selected linear models by using the biometric data from 60 cladodes to predict the cladode area, the FW and the DW per plant. Among ecotypes, significant differences were found in the studied biomass-related parameters and several homogeneous groups were established. Four Portuguese ecotypes had higher biomass production than the others, 3.20 Mg ha−1 on average, a value not significantly different to the improved ‘Gialla’ cultivar, which averaged 3.87 Mg ha−1. Those ecotypes could be used to start a breeding program and to deploy material for animal feeding and fruit production.

Portuguese ecotypes of Opuntia ficus-indica differ in biomass production

The Opuntia ficus-indica (L.) Miller is a species from the Cactaceae family with the center of origin and domestication in central Mexico. This species introduction in the Iberia Peninsula occurred, probably, by the end of the 15th century, after the discovery of America, spreading later throughout the Mediterranean basin. In Portugal, O. ficus-indica is located, usually, with a typical ruderal behavior, at the edge of roads and paths. In Portugal, as in other Mediterranean regions, inlands areas are under severe draught during extensive summers, in particular, and global warming is expected to affect them deeply in the near future. O. ficus-indica, by its morpho-physiological characteristics and multiple economic uses, represent an alternative crop for those regions. Sixteen Portuguese O. ficus indica ecotypes and two ‘Italian’ cultivars ("Gialla" and "Bianca") were evaluated for plant vigor and biomass production, by nondestructive methods, in the two years following planting. Biomass production and plant vigor were measured by estimating cladode number, cladode area and fresh weight per plant. Linear models to predict the area of cladodes and fresh weight per plant were previously established using a biometric analysis of 180 cladodes. It was not possible to establish an accurate linear model for dry matter using non-destructive estimation. Significant differences were found among populations in the studied biomass-related parameters, and different groups were unfolded. A group of four Portuguese ecotypes outperformed in terms of biomass production, comparable with the “Gialla” cultivar. This group could be used to start a breeding program with the objective of deploy material for animal feeding, biomass and fruit production. Nevertheless, the ‘Gialla’ cultivar showed the best performance, achieving the highest biomass related parameters, not surprisingly for it is an improved plant material.