986 resultados para Forest Science


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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In general, pattern recognition techniques require a high computational burden for learning the discriminating functions that are responsible to separate samples from distinct classes. As such, there are several studies that make effort to employ machine learning algorithms in the context of big data classification problems. The research on this area ranges from Graphics Processing Units-based implementations to mathematical optimizations, being the main drawback of the former approaches to be dependent on the graphic video card. Here, we propose an architecture-independent optimization approach for the optimum-path forest (OPF) classifier, that is designed using a theoretical formulation that relates the minimum spanning tree with the minimum spanning forest generated by the OPF over the training dataset. The experiments have shown that the approach proposed can be faster than the traditional one in five public datasets, being also as accurate as the original OPF. (C) 2014 Elsevier B. V. All rights reserved.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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There are strong uncertainties regarding LAI dynamics in forest ecosystems in response to climate change. While empirical growth & yield models (G&YMs) provide good estimations of tree growth at the stand level on a yearly to decennial scale, process-based models (PBMs) use LAI dynamics as a key variable for enabling the accurate prediction of tree growth over short time scales. Bridging the gap between PBMs and G&YMs could improve the prediction of forest growth and, therefore, carbon, water and nutrient fluxes by combining modeling approaches at the stand level.Our study aimed to estimate monthly changes of leaf area in response to climate variations from sparse measurements of foliage area and biomass. A leaf population probabilistic model (SLCD) was designed to simulate foliage renewal. The leaf population was distributed in monthly cohorts, and the total population size was limited depending on forest age and productivity. Foliage dynamics were driven by a foliation function and the probabilities ruling leaf aging or fall. Their formulation depends on the forest environment.The model was applied to three tree species growing under contrasting climates and soil types. In tropical Brazilian evergreen broadleaf eucalypt plantations, the phenology was described using 8 parameters. A multi-objective evolutionary algorithm method (MOEA) was used to fit the model parameters on litterfall and LAI data over an entire stand rotation. Field measurements from a second eucalypt stand were used to validate the model. Seasonal LAI changes were accurately rendered for both sites (R-2 = 0.898 adjustment, R-2 = 0.698 validation). Litterfall production was correctly simulated (R-2 = 0.562, R-2 = 0.4018 validation) and may be improved by using additional validation data in future work. In two French temperate deciduous forests (beech and oak), we adapted phenological sub-modules of the CASTANEA model to simulate canopy dynamics, and SLCD was validated using LAI measurements. The phenological patterns were simulated with good accuracy in the two cases studied. However, IA/max was not accurately simulated in the beech forest, and further improvement is required.Our probabilistic approach is expected to contribute to improving predictions of LAI dynamics. The model formalism is general and suitable to broadleaf forests for a large range of ecological conditions. (C) 2014 Elsevier B.V. All rights reserved.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Wild primates occupy large home ranges and travel long distances to reach goals. However, how primates are able to remember goal locations and travel efficiently is unclear. Few studies present consistent results regarding what reference system primates use to navigate, and what kind of spatial information they recognize. We analysed the pattern of navigation of one wild group of black capuchin monkeys, Cebus nigritus, at Atlantic Forest for 100 days in Carlos Botelho State Park (PECB), Brazil. We tested predictions based on the alternative hypotheses that black capuchin monkeys navigate using a sequence of landmarks as an egocentric reference system or an allocentric reference system, or both, depending on availability of food resources. The group location was recorded using a GPS device collecting coordinates at 5 min intervals, and route maps were generated using ArcView v9.3.1. The study group travelled through habitual routes during less than 30% of our study sample, and revisited resources from different starting points, using different paths and routes, even when prominent landmarks near feeding locations were not visible. The study group used habitual routes more frequently when high-quality foods were scarce, and navigated using different paths when revisiting food sources. Results support the hypothesis that black capuchin monkeys at PECB navigate using both egocentric and allocentric systems of reference, depending on the quality and distribution of the food resource they find. (C) 2010 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

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Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions: 1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? 2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? 3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- and Weibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (< 40 cm D) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8 Mg ha(-1) (range 6.6 to 112.4) to 8.0 Mg ha(-1) (-2.5 to 23.0).

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The design of a network is a solution to several engineering and science problems. Several network design problems are known to be NP-hard, and population-based metaheuristics like evolutionary algorithms (EAs) have been largely investigated for such problems. Such optimization methods simultaneously generate a large number of potential solutions to investigate the search space in breadth and, consequently, to avoid local optima. Obtaining a potential solution usually involves the construction and maintenance of several spanning trees, or more generally, spanning forests. To efficiently explore the search space, special data structures have been developed to provide operations that manipulate a set of spanning trees (population). For a tree with n nodes, the most efficient data structures available in the literature require time O(n) to generate a new spanning tree that modifies an existing one and to store the new solution. We propose a new data structure, called node-depth-degree representation (NDDR), and we demonstrate that using this encoding, generating a new spanning forest requires average time O(root n). Experiments with an EA based on NDDR applied to large-scale instances of the degree-constrained minimum spanning tree problem have shown that the implementation adds small constants and lower order terms to the theoretical bound.

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Dendrophryniscus is an early diverging clade of bufonids represented by few small-bodied species distributed in Amazonia and the Atlantic Forest. We used mitochondrial (414 bp of 12S, 575 bp of 16S genes) and nuclear DNA (785 bp of RAG-1) to investigate phylogenetic relationships and the timing of diversification within the genus. These molecular data were gathered from 23 specimens from 19 populations, including eight out of the 10 nominal species of the genus as well as Rhinella boulengeri. Analyses also included sequences of representatives of 18 other bufonid genera that were publically available. We also examined morphological characters to analyze differences within Dendrophryniscus. We found deep genetic divergence between an Amazonian and an Atlantic Forest clade, dating back to Eocene. Morphological data corroborate this distinction. We thus propose to assign the Amazonian species to a new genus, Amazonella. The species currently named R. boulengeri, which has been previously assigned to the genus Rhamphophryne, is shown to be closely related to Dendrophryniscus species. Our findings illustrate cryptic trends in bufonid morphological evolution, and point to a deep history of persistence and diversification within the Amazonian and Atlantic rainforests. We discuss our results in light of available paleoecological data and the biogeographic patterns observed in other similarly distributed groups. (C) 2011 Elsevier Inc. All rights reserved.

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This study evaluated whether processing non-timber forest products (NTFPs) and establishing trade partnerships between forest communities and companies enhance the outcomes of NTFP commercialization. In particular, we evaluated whether product processing, partnerships, or their combination was associated with a number of outcomes related to the well-being of forest inhabitants and forest conservation. We based our analyses on ethnographic and quantitative data (i.e., survey and systematic observations) gathered at seven communities from five societies of the Brazilian and Bolivian Amazon. Our results indicated that product processing and partnerships do not represent a silver bullet able to improve the results of NTFP commercialization in terms of well-being and conservation indicators. Compared with cases without interventions, households adopting partnerships but not product processing were most often associated with improved economic proxies of well-being (total income, NTFP income, food consumption and gender equality in income). In comparison, the combination of product processing and partnerships was associated with similar outcomes. Unexpectedly, product processing alone was associated with negative outcomes in the economic indicators of well-being. All of the investigated strategies were associated with less time spent in social and cultural activities. With respect to forest conservation, the strategies that included a partnership with or without processing produced similar results: while household deforestation tended to decrease, the hunting impact increased. Processing alone was also associated with higher levels of hunting, though it did not reduce deforestation. Our results indicate that establishing partnerships may enhance the outcomes of NTFP trade in terms of the financial outcomes of local communities, but practitioners need to use caution when adopting the processing strategy and they need to evaluate potential negative results for indicators of social and cultural activities. With respect to conservation, the three strategies are promising for reducing deforestation, but more pervasive impacts, such as hunting, might increase.

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Araucaria angustifolia, commonly named Araucaria, is a Brazilian native species that is intensively exploited due to its timber quality. Therefore, Araucaria is on the list of species threatened by extinction. Despite the importance of soil for forest production, little is known about the soil properties of the highly fragmented Araucaria forests. This study was designed to investigate the use of chemical and biological properties as indicators of conservation and anthropogenic disturbance of Araucaria forests in different sampling periods. The research was carried out in two State parks of Sao Paulo: Parque Estadual Turistico do Alto do Ribeira and Parque Estadual de Campos de Jordao. The biochemical properties carbon and nitrogen in microbial biomass (MB-C and MB-N), basal respiration (BR), the metabolic quotient (qCO(2)) and the following enzyme activities: beta-glucosidase, urease, and fluorescein diacetate hydrolysis (FDA) were evaluated. The sampling period (dry or rainy season) influenced the results of mainly MB-C, MB-N, BR, and qCO(2). The chemical and biochemical properties, except K content, were sensitive indicators of differences in the conservation and anthropogenic disturbance stages of Araucaria forests. Although these forests differ in biochemical and chemical properties, they are efficient in energy use and conservation, which is shown by their low qCO(2), suggesting an advanced stage of succession.

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The availability of chemical elements for plants is mainly dependent on the nature of the soil and characteristics of each species. The transfer factors of lanthanides from the soil to the tree leaves of the Atlantic Forest, Brazil, were calculated for one fern species (Alsophila sternbergii-Pteridophyta division) and four magnoliophytes species (Bathysa australis, Euterpe edulis, Garcinia gardneriana and Guapira opposita-Magnoliophyta division) obtained in two areas of Serra do Mar State Park and collected in two different seasons. Samples were analyzed by instrumental neutron activation analysis (INAA). The soil-to-plant transfer factor (TF = C(plant):C(soil)) in magnoliophytes species was correlated to the mass fraction of lanthanides in the soil, described by a exponential model (TF = a.C (soil) (-b) ). Despite the tree fern Alsophila sternbergii presented a hyperaccumulation of lanthanides, this species did not have a significant relationship between TF and mass fraction in soil. Results indicated that plants of Magnoliophyta division selected the input of lanthanides from the soil, while the same was not observed in Alsophila sternbergii.