Abstract The region that comprises the Atlantic Forest is one of the most degraded areas of the planet, being especially vulnerable in climate change scenarios, which project a mean temperature increase between 2ºC and 3ºC by 2070 for the Brazilian Northeast region. This article aims to analyze the main drivers of socio-environmental vulnerability in the Atlantic Forest region that comprises the southernmost identity territory of Bahia (Brazil) and their potential consequences for coping with climate change. To this end, historical data on land use and occupation was spatialized and evaluated, along with socioeconomic indicators and legal environmental adequacy in the municipalities that make up this territory. The results indicate four structural drivers that generate regional vulnerabilities: the persistence of deforestation; the continuous expansion of monoculture areas; the maintenance of low levels of well-being of the population; as well as a picture of legal environmental liabilities. Based on the analysis of these data, strategies are proposed to increase the adaptive capacity to climate change in this region, especially considering the role of municipalities as a central actor in the implementation of adaptation actions by incorporating into their existing planning instruments indicators and strategies that address the multiple current challenges, especially when the federal government seems to be neglecting climate change.

RESUMO As chuvas constituem-se na principal fonte de água para bacias hidrográficas. Por isso, a quantificação e o conhecimento de sua distribuição temporal e espacial são indispensáveis para o dimensionamento de projetos hidráulicos. Objetivou-se avaliar a aderência de séries de dados pluviométricos a diferentes modelos probabilísticos e estimar parâmetros da equação de intensidade-duração-frequência (IDF) para estações pluviométricas do Estado da Paraíba. Os dados pluviométricos de cada estação foram obtidos a partir do banco de dados da Agência Nacional de Águas. Para estimar as precipitações máximas diárias de cada estação e o período de retorno (5, 10, 15, 25, 50 e 100 anos), foram utilizadas as seguintes distribuições de probabilidade: Gumbel, Log-Normal II, Log-Normal III, Pearson III e Log-Pearson III. A estimativa das chuvas nas durações de 5-1.440 min foi realizada pela desagregação das precipitações pluviométricas diárias. O ajuste da equação IDF foi realizado por meio de regressão múltipla não linear, com uso do método de interação de gradação reduzida generalizada não linear. As equações de chuvas intensas para a maioria das estações, quando comparadas aos dados observados, apresentaram ajustes com coeficientes de determinação acima de 0,99, o que referenda a metodologia empregada neste trabalho.

ABSTRACT Rainfall is the primary water source for hydrographic basins. Hence, the quantification and knowledge of its temporal and spatial distribution are indispensable in dimensioning hydraulic projects. This study aimed at assessing the fit of a series of rainfall data to different probability models, as well as estimating parameters of the intensity-duration-frequency (IDF) equation for rain stations of the Paraíba State, Brazil. The rainfall data of each station were obtained from the Brazilian Water Agency databanks. To estimate the maximum daily rainfall of each station and return period (5, 10, 15, 25, 50 and 100 years), the following probability distributions were used: Gumbel, Log-Normal II, Log-Normal III, Pearson III and Log-Pearson III. The estimation of rainfall in durations of 5-1,440 min was carried out by daily rainfall disaggregation. The adjustment of the IDF equation was performed via nonlinear multiple regression, using the nonlinear generalized reduced gradient interaction method. When compared to the data observed, the intense rainfall equations for most stations showed goodness of fit with coefficients of determination above 0.99, which supports the methodology applied in this study.

RESUMO O objetivo com a realização deste trabalho foi determinar áreas com risco de contaminação por agrotóxicos utilizados na produção de monoculturas anuais na bacia do Riacho da Estiva, afluente do Rio Uruçuí-Preto, Piauí, por meio de álgebra de mapas, fazendo-se uso de planos de informação ambiental para determinar a tendência do comportamento da água, infiltração e escoamento, juntamente com o transporte de agrotóxicos. O cruzamento dessas informações foi utilizado para gerar um mapa com as áreas de risco de contaminação por agroquímicos utilizados. A bacia hidrográfica apresentou elevada antropização, com aumento de aproximadamente 55% do uso e ocupação do solo por culturas agrícolas em um período de 27 anos (1984 a 2011). Área de 269 Km2, que corresponde a 11% da área da bacia, apresenta alto potencial de risco de contaminação por agroquímicos, 45% apresentam médio risco de contaminação e 44% apresentam baixo risco de contaminação.

ABSTRACT The aims of this work was to determine risk areas with pesticide contamination on the Estiva stream watershed, a tributary of Uruçuí-Preto river, Brazil. Environmental data was used to determine layers of water way, infiltration and runoff with the transport of pesticide. The overlay of this information has generated a map with the risk areas with pesticide contamination. The basin had high human disturbance, with an increase of about 55% of land use and occupation by agricultural crops, in a period of approximately 27 years (1984-2011). An area of 269 Km2, correspondent to 11% of the basin area, has a high potential pesticide contamination risk, 45% medium contamination risk and 44% have little contamination risk.

The aim of this study was to compare the genetic diversity of 12 populations of goats in Brazil and Morocco (n = 796) through the use of physical measurements and different multivariate techniques. Traits measured included wither height (WH), distance from the brisket to the ground (BH) and ear length (EL). The standardized Euclidean distance (D) was adopted. The D values were submitted to clustering analysis using hierarchical methods (from nearest neighbor and UPGMA - Unweighted Pair Group Method with Arithmetic Mean) and the numbers of clusters were analyzed using the Tocher optimization method. The population clustering was different depending on the method of analysis used. Among the hierarchical methods, UPGMA showed the best fit (CCC = 0.82). The Tocher method enabled the formation of four different clusters. Although the hierarchical and Tocher methods resulted in different cluster formations, both contributed to the interpretation of the genetic cluster divergence. The results obtained through UPGMA and Tocher optimization enable their use for future studies that may include a larger number of biometric variables on greater numbers of individuals and additional populations.

The aim was to analyze variation in 12 Brazilian and Moroccan goat populations, and, through principal component analysis (PCA), check the importance of body measures and their indices as a means of distinguishing among individuals and populations. The biometric measurements were wither height (WH), brisket height (BH) and ear length (EL). Thorax depth (WH-BH) and the three indices, TD/WH, EL/TD and EL/WH, were also calculated. Of the seven components extracted, the first three principal components were sufficient to explain 99.5% of the total variance of the data. Graphical dispersion by genetic groups revealed that European dairy breeds clustered together. The Moroccan breeds were separated into two groups, one comprising the Drâa and the other the Zagora and Rhâali breeds. Whereas, on the one side, the Anglo-Nubian and undefined breeds were the closest to one another the goats of the Azul were observed to have the highest variation of all the breeds. The Anglo-Nubian and Boer breeds were similar to each other. The Nambi-type goats remained distinct from all the other populations. In general, the use of graphical representation of PCA values allowed to distinguish genetic groups.