Integration of georeferenced and genetic data for the management of biodiversity in sheep genetic resources in Brazil.

There are few animal germplasm/gene bank collections in Brazil, and basic studies are needed to attend the future internal and external demands from international partners. The aim of this work was to validate a "proof of concept" that integrates spatial (georeferenced data) and genetic data regarding the local of origin from 3518 DNA samples from 17 different genetic groups or breeds of sheep in the Brazilian Germplasm bank. Spatialisation shows that not all genetic groups have samples in the bank, and collection is concentrated in the conservation nuclei spread nationwide. Only 21% of states with a specific breed have samples in the gene bank. The mean number of animals sampled per collection was 32, while the mean distance travelled to collect samples was 262 km from the conservation nuclei. For example, the Brazilian Somali were only collected in the conservation nucleus in Ceará State. No samples were collected to date for the Cariri breed, which is recognised by the Brazilian Ministry of Agriculture. Only two farms and one breed in the bank are from the northern region. Of the 27 states, there are samples in the gene bank of sheep from 13, so several states have no samples, requiring collection from herds outside the official system of conservation to make sure that studies using this germplasm realised are not biased. Significant genetic differences are seen above 332 km, which should guide future sampling efforts. Suggestions are given for improving the quantity, quality and diversity of samples in the gene bank.

Spatial dynamics of the Girolando breed in Brazil: analysis of genetic integration and environmental factors.

Brazil is one of the world's largest milk producers. Several scientific studies have been developed related to landscape analyses that combine genetic with landscape structure data. In the present study, we aimed to analyze the relationship between genetic, environmental, and socioeconomic aspects of production in Girolando cattle in Brazil, as well as verify the spatial patterns of its genetic diversity. Genetic values and accuracy of 46,289 animals were used as well as information from DNA of 310 Girolando animals. Canonic, discriminant, and cluster analyses were conducted in SAS® and K-means method in ArcGIS 10.3 software. The relationship between genetic and geographic distance was analyzed using different methods in software Alleles in Space®. Clusters with animals with higher genetic values for milk production are located in municipalities with lower gross domestic product, fewer family-based establishments, and lower human development index. These clusters are associated with regions with higher area planted with crops, lower percentage of pastures that were less degraded, higher humidity, lower temperature range, and lower normalized difference vegetation index (NDVI) values. The greater the geographical distance between groups of animals, the greater the genetic distance between them with a significant distinction over 504 km. There is high genetic heterogeneity among animals. From these results, it will be possible to develop methodologies for better evaluation of the animals within the production systems.

Spatial dependence of malaria epidemics in municipalities of the Amazonian Ecosystem.

INTRODUCTION: In 2010, there were 305 (37.8%) municipalities with malaria epidemics in the Brazilian Amazon. The epidemics spread can be explained by the spatial distribution pattern. OBJECTIVE: To analyze the spatial dependence, autocorrelation, of the malaria epidemics in the municipalities of this region. METHODS: An automated algorithm was used for the detection of epidemic municipalities in 2003, 2007 and 2010. Spatial dependence was analyzed by applying the global and local Moran index on the epidemic months proportion variable. The epidemic municipalities clusters were identified using the TerraView software. RESULTS: The global Moran index values were 0.4 in 2003; 0.6 in 2007; and 0.5 in 2010 (p = 0.01), confirming the spatial dependence among the epidemic municipalities. Box Map and Moran Map identified inter-municipal, interstate and borders clusters with spatial autocorrelation (p < 0.05). There were 10 epidemic municipalities clusters in 2003; 9 in 2007 and 8 in 2010. DISCUSSION: The epidemic municipalities clusters may be linked to the health facilities difficulties on acting together. The structural limitations of the health services can be overcome by territorial integration to support planning and control activities, strengthening the interventions. CONCLUSION: The routine analysis of the epidemic municipalities clusters with spatial and temporal persistence may provide a new indicator of planning and integrated control prioritization, contributing to malaria epidemics reducing in inter-municipal, interstate and borders areas.

Spatial dependence of malaria epidemics in municipalities of the Brazilian Amazon / Dependência espacial das epidemias de malária em municípios da Amazônia Brasileira

Introduction: In 2010, there were 305 (37.8%) municipalities with malaria epidemics in the Brazilian Amazon. The epidemics spread can be explained by the spatial distribution pattern. Objective: To analyze the spatial dependence, autocorrelation, of the malaria epidemics in the municipalities of this region. Methods: An automated algorithm was used for the detection of epidemic municipalities in 2003, 2007 and 2010. Spatial dependence was analyzed by applying the global and local Moran index on the epidemic months proportion variable. The epidemic municipalities clusters were identified using the TerraView software. Results: The global Moran index values were 0.4 in 2003; 0.6 in 2007; and 0.5 in 2010 (p = 0.01), confirming the spatial dependence among the epidemic municipalities. Box Map and Moran Map identified inter-municipal, interstate and borders clusters with spatial autocorrelation (p < 0.05). There were 10 epidemic municipalities clusters in 2003; 9 in 2007 and 8 in 2010. Discussion: The epidemic municipalities clusters may be linked to the health facilities difficulties on acting together. The structural limitations of the health services can be overcome by territorial integration to support planning and control activities, strengthening the interventions. Conclusion: The routine analysis of the epidemic municipalities clusters with spatial and temporal persistence may provide a new indicator of planning and integrated control prioritization, contributing to malaria epidemics reducing in inter-municipal, interstate and borders areas. .

Introdução: Em 2010, foram observados 305 (37,8%) municípios com epidemias de malária na Amazônia brasileira. A propagação dos eventos epidêmicos pode ser explicada pelo padrão da distribuição espacial. Objetivo: Analisar a dependência espacial, autocorrelação, das epidemias de malária nos municípios dessa região. Métodos: Foi utilizado algoritmo automatizado para detecção dos municípios epidêmicos nos anos de 2003, 2007 e 2010. A dependência espacial foi analisada por meio da variável proporção de meses epidêmicos, aplicando-se os índices de Moran global e local. Foram identificados os agrupamentos de municípios epidêmicos com o programa TerraView. Resultados: Os valores do índice global de Moran foram 0,4 em 2003; 0,6 em 2007; e 0,5 em 2010 (p = 0,01), confirmando a existência de dependência espacial entre os municípios epidêmicos. O Box Map e o Moran Map identificaram agrupamentos intermunicipais, interestaduais e fronteiriços com autocorrelação espacial estaticamente significante, sendo 10 clusters em 2003; 9 em 2007; e 8 em 2010 (p < 0,05). Discussão: Agrupamentos de municípios epidêmicos podem estar vinculados às dificuldades dos serviços de saúde em atuar articuladamente. Limitações estruturais podem ser superadas buscando a integração territorial para sustentação do planejamento e ações de controle, potencializando as intervenções no contexto espacial abrangente. Conclusão: A análise rotineira da autocorrelação espacial entre municípios epidêmicos, identificando os agrupamentos com persistência espaço-temporal, poderá fornecer novo indicador de grande utilidade para o planejamento e priorização ...