The strategic importance of forest resources, both at the national and global level, as well as the scarcity of reliable qualitative and quantitative information about Brazilian forests are among the motivations that led to the implementation of a new national forest inventory in Brazil (IFN-BR). Beyond traditional field survey through clustered sampling, the IFN-BR incorporates Landscape Sample Units (LSU) as a geospatial component of the inventory. Landscape indicators and indices are generated through the analysis of land use/land cover in the LSUs, which provide information about composition, morphology, mosaic patterns, adjacent habitat similarity, connectivity, fragmentation, and state of riparian zones. In the current study, we describe the indicators selected to assess landscape using pilot LSUs established in Paraná State, as well as the calculation and composition of indices and scores.
Resumo -O objetivo deste trabalho foi propor estratégias de modelagem aplicadas aos dados de incidência de leprose-dos-citros, por meio do uso de um modelo autologístico espaço-temporal. A adequação do modelo autologístico foi avaliada quanto à: análise de dados provenientes de avaliações feitas em diferentes momentos; detecção de padrões espaciais da doença, pela avaliação de diferentes estruturas de vizinhança; consideração do efeito defasado no tempo de covariáveis de vizinhança; e ao efeito do ácaro transmissor na probabilidade de nova infecção. O modelo autologístico espaço-temporal adotado estendeu o modelo logístico usual, em que a estrutura de vizinhança é descrita por meio da construção de covariáveis, a partir da resposta observada em plantas vizinhas à planta avaliada, na mesma avaliação, ou em avaliações anteriores. Os dados de incidência de leprose nas plantas de citros foram coletados em pontos referenciados no espaço, durante aproximadamente dois anos. Os modelos detectam o efeito da presença do vetor e os padrões espaciais na ocorrência de novas infecções, tanto para covariáveis de vizinhança da mesma avaliação, quanto para covariáveis de vizinhança da avaliação anterior. Além disso, os modelos considerados permitem quantificar as variações na probabilidade de ocorrência da doença de acordo com o estado da doença e com a incidência do ácaro transmissor.
Termos para indexação: Brevipalpus phoenicis, Citrus leprosis virus, Citrus sinensis, estatística espacial, estruturas de vizinhança, pseudo-verossimilhança.
Spatial temporal autologistic model with an application to the analysis of spatial patterns of citrus leprosisAbstract -The goal of this study was to propose modeling strategies applied to the analysis of citrus leprosis incidence, through the use of a spatial temporal autologistic model. We evaluated the adequacy of autologistic model to consider data collected at different times; to detect spatial-temporal patterns through different neighboring structures; to consider the effect of covariates from previous times; and assessing the effect of the presence of the disease vector in the probability of new infections occurrence. The spatial temporal autologistic model adopted has extended the usual logistic model, in which the neighboring structures is described by means of covariates built from the status of plants nearby, at the same or at previous times. Data regarding the presence of the leprosis on plants were collected at field points referenced in space, over a period of approximately two years. Models detect the presence of spatial patterns on new infections for the studied neighboring structures, at the same or previous time. Additionally, probability estimates of a plant become infected can be obtained from the fitted models, given the occurrence of the disease and vector.
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