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The usage of spatial tools might be helpful in the optimization of decision-making regarding soil management, with technologies that assist in the interpretation of information related to soil fertility. Therefore, the present study evaluated the spatial variability of chemical attributes of the soil under an agroforestry system compared to a native forest in the municipality of Tomé-açu, Eastern Amazon, Brazil. Soil samples were performed at 36 points arranged in a 55 x 55 m grid. The soils were prepared and submitted to analysis in order to determine pH in H2O, exchangeable calcium, magnesium, potassium and aluminium, available phosphorus, potential acidity, organic matter, bases saturation and aluminium saturation. For each soil attribute, the spherical, gaussian and exponential models were adjusted. After the semivariograms fitting, data interpolation for assessment of spatial variability of the variables was performed through ordinary kriging. The spherical and gaussian models were the most efficient models in estimation of soil attributes spatial variability, in most cases. Most of variables presented a regular spatial variability in their respective kriging maps, with some exceptions. In general, the kriging maps can be used, and we can take them as logistical maps for management and intervention practices in order to improve the soil fertility in the study areas. The results principal components indicate the need for integrated management of soil chemical attributes, with localized application of acidity correctors, fertilizers and other types of incomes, using the spatial variability of these fertility variables.

Abstract: At a moment when the importance of planted forests in the Amazon region is increasing, hypsometric models become highly relevant tools as they allow monitoring of and planning for tree plantations in a way that is practical and economic for the producer. Thus, the objective of the current study was to select and adjust a model of hypsometric relationships for a clonal plantation of Tectona grandis Linn F., submitted to selective thinning, located in Capitão Poço municipality, Pará state, Brazil. Data were collected from permanent plots in five-year-old stands using the fixed area method and systematic process. The best adjusted model was selected with an adjusted determination coefficient (R²aj.%), residual standard deviation of the percentage estimate (Syx%), recalculated residual standard error (Syxr%), diagnosis of distribution of residuals as a percentage and the Percent Average Deviation (PAD%). Hyperbolic models 2 and 3 had the highest determination coefficients (83.42 and 83.40%) and lowest PAD (-0.006 and -0.154%). The polynomial (1) and hyperbolic models (2 and 3) showed the smallest errors in related to the estimates. Model 2 (hyperbolic) was found to generate the best estimate of total T. grandis clonal plantation height. Use of this hypsometric model will allow a significant reduction of costs and time in forest inventory studies. = Resumo: No cenário em que a importância das florestas plantadas na região Amazônica tem sido crescente, os modelos hipsométricos são ferramentas relevantes por permitirem o monitoramento e o planejamento de plantios florestais de forma prática e econômica para o produtor. Assim, objetivou-se com este estudo ajustar e selecionar um modelo de relação hipsométrica para um plantio clonal de Tectona grandis Linn F., submetido a desbaste seletivo, localizado no município de Capitão Poço, Pará. Os dados foram coletados em parcelas permanentes em povoamento com cinco anos de idade pelo método de área fixa e processo sistemático. A seleção do melhor modelo ajustado foi determinada pelo coeficiente de determinação ajustado (R²aj.%), erro padrão residual da estimativa em percentagem (Syx%), erro padrão residual recalculado (Syxr%), diagnóstico da distribuição dos resíduos em percentagem e do desvio médio percentual (DMP%). Os modelos hiperbólicos (2 e 3) apresentaram maiores coeficientes de determinação (83,42 e 83,40%) e menores DMP (-0,006 e -0,154%). Os modelos polinomiais (1) e hiperbólicos (2 e 3) apresentaram os menores erros relacionados às estimativas. Verificou-se que a melhor estimativa da altura total do plantio clonal de T. grandis foi gerada pela modelo 2 (hiperbólico). A utilização deste modelo hipsométrico possibilitará a redução significativa de custos e tempo no inventário florestal.

At a moment when the importance of planted forests in the Amazon region is increasing, hypsometric models become highly relevant tools as they allow monitoring of and planning for tree plantations in a way that is practical and economic for the producer. Thus, the objective of the current study was to select and adjust a model of hypsometric relationships for a clonal plantation of Tectona grandis Linn F., submitted to selective thinning, located in Capitão Poço municipality, Pará state, Brazil. Data were collected from permanent plots in five-year-old stands using the fixed area method and systematic process. The best adjusted model was selected with an adjusted determination coefficient (R²aj.%), residual standard deviation of the percentage estimate (Syx%), recalculated residual standard error (Syxr%), diagnosis of distribution of residuals as a percentage and the Percent Average Deviation (PAD%). Hyperbolic models 2 and 3 had the highest determination coefficients (83.42 and 83.40%) and lowest PAD (-0.006 and -0.154%). The polynomial (1) and hyperbolic models (2 and 3) showed the smallest errors in related to the estimates. Model 2 (hyperbolic) was found to generate the best estimate of total T. grandis clonal plantation height. Use of this hypsometric model will allow a significant reduction of costs and time in forest inventory studies.

The seed bank is essential for the initiation of natural forest regeneration, especially in ecosystems in the early stages of development, where there have been anthropogenic or natural disturbances. The objective of the current study was to evaluate seed bank dynamics in three forest ecosystems, two in Utinga State Park (PEUt) and one on the Federal Rural University of Amazonia (UFRA) campus, both in Belém, Pará, Amazonian Brazil. The ecosystems were: primary forest (PF), early successional forest (ESF), and late successional forest (LSF). For seed bank evaluation, five plots were installed in each forest ecosystem, and in each plot 5 soil samples were removed at a depth of 0-0.05 m. In the three ecosystems, the most abundant species in the seed bank were Cecropia obtusa, Phyllanthus tenellus and Vismia guianensis. Zoochoria was the dominant dispersion syndrome with 1,041 (67.8%) individuals. In the PF and LST ecosystems the predominant life form was tree, followed by shrub, whereas in the ESF the shrub life form predominated, followed by tree. Thirtyone species were recorded in PF, 26 in ISF, and 32 in LSF. In general, pioneers were most frequent ecological group, with 289 individuals (93.2%) in PF, 288 individuals (88.7%) in LSF, and 188 (75.06%) in ESF. Thus, all ecosystems possessed a high potential for resilience in case of possible forest disturbances, and the PF seed bank was considered the most diverse in terms of arboreal species.