SPATIAL VARIABILITY OF THE RAINFALL EROSIVE POTENTIAL IN THE STATE OF MATO GROSSO DO SUL, BRAZIL

Information about rainfall erosivity is important during soil and water conservation planning. Thus, the spatial variability of rainfall erosivity of the state Mato Grosso do Sul was analyzed using ordinary kriging interpolation. For this, three pluviograph stations were used to obtain the regression equations between the erosivity index and the rainfall coefficient EI30. The equations obtained were applied to 109 pluviometric stations, resulting in EI30 values. These values were analyzed from geostatistical technique, which can be divided into: descriptive statistics, adjust to semivariogram, cross-validation process and implementation of ordinary kriging to generate the erosivity map. Highest erosivity values were found in central and northeast regions of the State, while the lowest values were observed in the southern region. In addition, high annual precipitation values not necessarily produce higher erosivity values.

Spatio-temporal patterns of tuberculosis incidence in Ribeirao Preto, State of Sao Paulo, southeast Brazil, and their relationship with social vulnerability: a Bayesian analysis

Introduction: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirao Preto, State of Sao Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. Methods: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. Results: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirao Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. Conclusions: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.

Stand-level patterns of carbon fluxes and partitioning in a Eucalyptus grandis plantation across a gradient of productivity, in Sao Paulo State, Brazil

Wood production represents a large but variable fraction of gross primary production (GPP) in highly productive Eucalyptus plantations. Assessing patterns of carbon (C) partitioning (C flux as a fraction of GPP) between above- and belowground components is essential to understand mechanisms driving the C budget of these plantations. Better knowledge of fluxes and partitioning to woody and non-woody tissues in response to site characteristics and resource availability could provide opportunities to increase forest productivity. Our study aimed at investigating how C allocation varied within one apparently homogeneous 90 ha stand of Eucalyptus grandis (W. Hill ex Maiden) in Southeastern Brazil. We assessed annual above-ground net primary production (ANPP: stem, leaf, and branch production) and total belowground C flux (TBCF: the sum of root production and respiration and mycorrhizal production and respiration), GPP (computed as the sum of ANPP, TBCF and estimated aboveground respiration) on 12 plots representing the gradient of productivity found within the stand. The spatial heterogeneity of topography and associated soil attributes across the stand likely explained this fertility gradient. Component fluxes of GPP and C partitioning were found to vary among plots. Stem NPP ranged from 554 g C m(-2) year(-1) on the plot with lowest GPP to 923 g C m(-2) year(-1) on the plot with highest GPP. Total belowground carbon flux ranged from 497 to 1235 g C m(-2) year(-1) and showed no relationship with ANPP or GPP. Carbon partitioning to stem NPP increased from 0.19 to 0.23, showing a positive trend of increase with GPP (R-2 = 0.29, P = 0.07). Variations in stem wood production across the gradient of productivity observed at our experimental site were a result of the variability in C partitioning to different forest system components.

Decisions on Temporal Sampling Protocol Influence the Detection of Ecological Patterns

Within-site variability in species detectability is a problem common to many biodiversity assessments and can strongly bias the results. Such variability can be caused by many factors, including simple counting inaccuracies, which can be solved by increasing sample size, or by temporal changes in species behavior, meaning that the way the temporal sampling protocol is designed is also very important. Here we use the example of mist-netted tropical birds to determine how design decisions in the temporal sampling protocol can alter the data collected and how these changes might affect the detection of ecological patterns, such as the species-area relationship (SAR). Using data from almost 3400 birds captured from 21,000 net-hours at 31 sites in the Brazilian Atlantic Forest, we found that the magnitude of ecological trends remained fairly stable, but the probability of detecting statistically significant ecological patterns varied depending on sampling effort, time of day and season in which sampling was conducted. For example, more species were detected in the wet season, but the SAR was strongest in the dry season. We found that the temporal distribution of sampling effort was more important than its total amount, discovering that similar ecological results could have been obtained with one-third of the total effort, as long as each site had been equally sampled over 2 yr. We discuss that projects with the same sampling effort and spatial design, but with different temporal sampling protocol are likely to report different ecological patterns, which may ultimately lead to inappropriate conservation strategies.

Spatial clusters of suicide in the municipality of Sao Paulo 1996-2005: an ecological study

Background: In a classical study, Durkheim mapped suicide rates, wealth, and low family density and realized that they clustered in northern France. Assessing others variables, such as religious society, he constructed a framework for the analysis of the suicide, which still allows international comparisons using the same basic methodology. The present study aims to identify possible significantly clusters of suicide in the city of Sao Paulo, and then, verify their statistical associations with socio-economic and cultural characteristics. Methods: A spatial scan statistical test was performed to analyze the geographical pattern of suicide deaths of residents in the city of Sao Paulo by Administrative District, from 1996 to 2005. Relative risks and high and/or low clusters were calculated accounting for gender and age as co-variates, were analyzed using spatial scan statistics to identify geographical patterns. Logistic regression was used to estimate associations with socioeconomic variables, considering, the spatial cluster of high suicide rates as the response variable. Drawing from Durkheim's original work, current World Health Organization (WHO) reports and recent reviews, the following independent variables were considered: marital status, income, education, religion, and migration. Results: The mean suicide rate was 4.1/100,000 inhabitant-years. Against this baseline, two clusters were identified: the first, of increased risk (RR = 1.66), comprising 18 districts in the central region; the second, of decreased risk (RR = 0.78), including 14 districts in the southern region. The downtown area toward the southwestern region of the city displayed the highest risk for suicide, and though the overall risk may be considered low, the rate climbs up to an intermediate level in this region. One logistic regression analysis contrasted the risk cluster (18 districts) against the other remaining 78 districts, testing the effects of socioeconomic-cultural variables. The following categories of proportion of persons within the clusters were identified as risk factors: singles (OR = 2.36), migrants (OR = 1.50), Catholics (OR = 1.37) and higher income (OR = 1.06). In a second logistic model, likewise conceived, the following categories of proportion of persons were identified as protective factors: married (OR = 0.49) and Evangelical (OR = 0.60). Conclusions: This risk/ protection profile is in accordance with the interpretation that, as a social phenomenon, suicide is related to social isolation. Thus, the classical framework put forward by Durkheim seems to still hold, even though its categorical expression requires re-interpretation.

Phylogeography of the neotropical Anopheles triannulatus complex (Diptera: Culicidae) supports deep structure and complex patterns

Abstract Background The molecular phylogenetic relationships and population structure of the species of the Anopheles triannulatus complex: Anopheles triannulatus s.s., Anopheles halophylus and the putative species Anopheles triannulatus C were investigated. Methods The mitochondrial COI gene, the nuclear white gene and rDNA ITS2 of samples that include the known geographic distribution of these taxa were analyzed. Phylogenetic analyses were performed using Bayesian inference, Maximum parsimony and Maximum likelihood approaches. Results Each data set analyzed septely yielded a different topology but none provided evidence for the seption of An. halophylus and An. triannulatus C, consistent with the hypothesis that the two are undergoing incipient speciation. The phylogenetic analyses of the white gene found three main clades, whereas the statistical parsimony network detected only a single metapopulation of Anopheles triannulatus s.l. Seven COI lineages were detected by phylogenetic and network analysis. In contrast, the network, but not the phylogenetic analyses, strongly supported three ITS2 groups. Combined data analyses provided the best resolution of the trees, with two major clades, Amazonian (clade I) and trans-Andean + Amazon Delta (clade II). Clade I consists of multiple subclades: An. halophylus + An. triannulatus C; trans-Andean Venezuela; central Amazonia + central Bolivia; Atlantic coastal lowland; and Amazon delta. Clade II includes three subclades: Panama; cis-Andean Colombia; and cis-Venezuela. The Amazon delta specimens are in both clades, likely indicating local sympatry. Spatial and molecular variance analyses detected nine groups, corroborating some of subclades obtained in the combined data analysis. Conclusion Combination of the three molecular markers provided the best resolution for differentiation within An. triannulatus s.s. and An. halophylus and C. The latest two species seem to be very closely related and the analyses performed were not conclusive regarding species differentiation. Further studies including new molecular markers would be desirable to solve this species status question. Besides, results of the study indicate a trans-Andean origin for An. triannulatus s.l. The potential implications for malaria epidemiology remain to be investigated.

Spatio-temporal patterns of tuberculosis incidence in Ribeirão Preto, State of São Paulo, southeast Brazil, and their relationship with social vulnerability: a Bayesian analysis

INTRODUCTION: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirão Preto, State of São Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. METHODS: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. RESULTS: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirão Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. CONCLUSIONS: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.