990 resultados para forest system
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In fragmented landscapes, agroforest woodlots can potentially act as stepping stones facilitating movement between forest fragments. We assessed the influence of agroforest woodlots on bird distribution and diversity in the Atlantic forest region (SE Brazil), and also tested which categories of species can use different types of connection elements, and whether this use is influenced by the distance to large forest patches. We studied two fragmented landscapes, with and without stepping stones linking large fragments, and one forested landscape. Using a point count, a bird survey was undertaken in the fragmented landscapes in five different elements: large remnants (> 400 ha), agroforest woodlots (0.4-1.1 ha), small patches (0.5-7 ha), riparian corridor, and pasture areas (the main matrix). Generalist and open-area species were commonly observed in the agroforest system or other connection elements, whereas only a few forest species were present in these connections. For the latter species, the distance of woodlots to large patches was essential to determine their richness and abundance. Based on our results and data from literature, we suggest that there is an optimal relationship between the permeability of the matrix and the efficiency of stepping stones, which occurs at intermediate degrees of matrix resistance, and is species-dependent. Because the presence of agroforest system favors a higher richness of generalist species, they appeared to be more advantageous for conservation than the monoculture system; for this reason, they should be considered as a management alternative, particularly when the matrix permeability requirement is met.
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This article discusses seasonal and interannual variations of the evapotranspiration (ET) rates in Bananal Island floodplain, Brazil. Measurements included ET and sensible heat flux using the eddy covariance method, atmospheric forcings (net radiation, Rn, vapor pressure deficit, VPD, wind speed and air temperature), soil moisture profiles, groundwater level and flood height, taken from November 2003 to December 2006. For the hydrological years (October-September) of 2003/2004, 2004/2005 and 2005/2006, the accumulated precipitation was 1692, 1471, 1914 mm and the accumulated ET was 1361, 1318 and 1317 mm, respectively. Seasonal analyses indicated that ET decreased in the dry season (average 3.7 mm day(-1)), despite the simultaneous increase in Rn, air temperature and VPD. The increase of ET in the wet season and particularly in the flood period (average 4.1 mm day(-1)) showed that the free water surface evaporation strongly influenced the energy exchange. Soil moisture, which was substantially depleted during the dry season, and adaptative vegetation mechanisms such as leaf senescence contributed to limit the dry season ET. Strong drainage within permeable sandy soils helped to explain the soil moisture depletion. These results suggest that the Bananal flooding area shows a different pattern in relation to the upland Amazon forests, being more similar to the savanna strictu senso areas in central Brazil. For example, seasonal ET variation was not in phase with Rn; the wet season ET was higher than the dry season ET; and the system stored only a tiny memory of the flooding period, being sensitive to extended drought periods.
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Pollinator visitation rates over the life of a flower are determined by pollinator abundance and floral longevity. If flowers are not visited frequently enough, pollen limitation may occur, favoring the evolution of self-compatibility (SC). In plant species with varying SC levels, central populations often are self-incompatible (SI) and peripheral populations are SC. Witheringia solanacea (Solanaceae) is a species that follows this trend with the exception of one population in the Monteverde Cloud Forest Reserve, which is peripheral yet SI. I investigated this population using multiple techniques including floral bagging, pollinator observations, microsatellite analysis, and floral longevity manipulations. My results confirmed the self-incompatibility of the Monteverde population and indicated low but perhaps adequate rates of pollinator visitation per flower per hour. I found reduced genetic diversity at Monteverde and gene flow occurring unidirectionally from San Luis (a central population) to Monteverde. In the greenhouse, there was more of an effect of male than female function on floral longevity, but the largest differences were environmental. Flowers stayed open substantially longer when cool, cloudy weather was simulated and shorter when conditions were hot and sunny. The results indicate that the Monteverde population of W. solanacea is SI because 1) it is unable to maximize its fitness due to gene flow from San Luis and its relatively recent colonization of the area and 2) pollen limitation may not be severe because of supplemental pollinator availability from other Witheringia species in the area and increased floral longevities due to cool and cloudy conditions.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Cutting analysis is a important and crucial task task to detect and prevent problems during the petroleum well drilling process. Several studies have been developed for drilling inspection, but none of them takes care about analysing the generated cutting at the vibrating shale shakers. Here we proposed a system to analyse the cutting's concentration at the vibrating shale shakers, which can indicate problems during the petroleum well drilling process, such that the collapse of the well borehole walls. Cutting's images are acquired and sent to the data analysis module, which has as the main goal to extract features and to classify frames according to one of three previously classes of cutting's volume. A collection of supervised classifiers were applied in order to allow comparisons about their accuracy and efficiency. We used the Optimum-Path Forest (OPF), Artificial Neural Network using Multi layer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC) for this task. The first one outperformed all the remaining classifiers. Recall that we are also the first to introduce the OPF classifier in this field of knowledge. Very good results show the robustness of the proposed system, which can be also integrated with other commonly system (Mud-Logging) in order to improve the last one's efficiency.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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About 45 palm species occur in the Atlantic forest of Brazil, and most of them are affected by loss of seed dispersers resulting from forest fragmentation and hunting. Here we report the effects of habitat loss and defaunation on the seed dispersal system of an endemic palm, Astrocaryum aculeatissimum. We evaluated seed removal, insect and rodent seed predation, and scatter-hoarding in nine sites, ranging from 19 ha to 79 000 ha. We report the seedling, juvenile and adult palm densities in this range of sites. Endocarps remaining beneath the parent palm had a higher probability of being preyed upon by insects in small, mostly fragmented and more defaunated sites. The frequency of successful seed removal, scatter-hoarding and consumption by rodents increased in the larger, less defaunated sites. Successful removal and dispersal collapsed in small (< 1000 ha), highly defaunated sites and frequently resulted in low densities of both seedlings and juveniles. Our results indicate that a large fraction of Atlantic forest palms that rely on scatter-hoarding rodents may become regionally extinct due to forest fragmentation and defaunation. Current management practices including palm extraction and hunting pressure have a lasting effect on Atlantic forest palm regeneration by severely limiting successful recruitment of prereproductive individuals.(c) 2006 the Linnean Society of London.
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The reproductive phenology of the entire climber community (96 species of lianas and 40 species of vines) in a semideciduous forest in Southeastern Brazil (22 degrees 49'45''S; 47 degrees 06'33''W and 670 m altitude) was observed from March 1988 to February 1991. Phenological observations were made weekly by walking along a 10.5 km trail in the interior and at the forest edges of the Santa Genebra Reserve (SGR). The most species-rich families of climbers were Bignoniaceae (22), Malpighiaceae (17), Sapindaceae (12) and Asteraceae (12). Flowering patterns for woody lianas and herbaceous vines differed. Lianas had two flowering peaks: a minor peak in March in the transition from wet to dry season, and a major peak in October during the transition from dry to wet season. The flowering peak for herbaceous vines was in April. Fruiting of lianas was highly seasonal, with one peak in the late dry season (July-August). Fruiting for vines was less seasonal with a slight peak in March. These differences were consistent with the predominance of wind-dispersed fruits among lianas (72% of species) versus vines (52%). Low rainfall, high leaf fall, and strong winds during the dry season favor wind dispersal. More species of vines (40%) have animal-dispersed seeds than lianas (19%), and most vines fruited during the wet season. Phenological patterns of climbers and trees and treelets at SGR differed. The life form of lianas and their system of reserve economy may allow them to reproduce during periods unfavorable to trees. Displacement of peak flowering periods of trees and climbers pollinated by bees and small generalist insects may decrease competition for pollen vectors among species of these two groups of plants. Whereas the fruiting patterns of wind-dispersed trees and climbers at SGR were similar (most species fruiting during the dry season), animal-dispersed trees and treelets fruited throughout the year while animal-dispersed climbers exhibited a pronounced peak in late wet season. The distinct phenological patterns of climbers, generally complementary to those presented by trees, resulted in constant availability of Bowers and fruits throughout the year and enhances the importance of this plant group in Neotropical forests.
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This paper addresses biometric identification using large databases, in particular, iris databases. In such applications, it is critical to have low response time, while maintaining an acceptable recognition rate. Thus, the trade-off between speed and accuracy must be evaluated for processing and recognition parts of an identification system. In this paper, a graph-based framework for pattern recognition, called Optimum-Path Forest (OPF), is utilized as a classifier in a pre-developed iris recognition system. The aim of this paper is to verify the effectiveness of OPF in the field of iris recognition, and its performance for various scale iris databases. The existing Gauss-Laguerre Wavelet based coding scheme is used for iris encoding. The performance of the OPF and two other - Hamming and Bayesian - classifiers, is compared using small, medium, and large-scale databases. Such a comparison shows that the OPF has faster response for large-scale databases, thus performing better than the more accurate, but slower, classifiers.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Climate change is expected to increase the intensity of extreme precipitation events in Amazonia that in turn might produce more forest blowdowns associated with convective storms. Yet quantitative tree mortality associated with convective storms has never been reported across Amazonia, representing an important additional source of carbon to the atmosphere. Here we demonstrate that a single squall line (aligned cluster of convective storm cells) propagating across Amazonia in January, 2005, caused widespread forest tree mortality and may have contributed to the elevated mortality observed that year. Forest plot data demonstrated that the same year represented the second highest mortality rate over a 15-year annual monitoring interval. Over the Manaus region, disturbed forest patches generated by the squall followed a power-law distribution (scaling exponent alpha = 1.48) and produced a mortality of 0.3-0.5 million trees, equivalent to 30% of the observed annual deforestation reported in 2005 over the same area. Basin-wide, potential tree mortality from this one event was estimated at 542 +/- 121 million trees, equivalent to 23% of the mean annual biomass accumulation estimated for these forests. Our results highlight the vulnerability of Amazon trees to wind-driven mortality associated with convective storms. Storm intensity is expected to increase with a warming climate, which would result in additional tree mortality and carbon release to the atmosphere, with the potential to further warm the climate system. Citation: Negron-Juarez, R. I., J. Q. Chambers, G. Guimaraes, H. Zeng, C. F. M. Raupp, D. M. Marra, G. H. P. M. Ribeiro, S. S. Saatchi, B. W. Nelson, and N. Higuchi (2010), Widespread Amazon forest tree mortality from a single cross-basin squall line event, Geophys. Res. Lett., 37, L16701, doi:10.1029/2010GL043733.
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The social wasp nests were quantified in three different plant physiognomies (forested Caatinga, shrubby Caatinga, and agricultural systems) to analyze the effect of environmental seasonality and plant physiognomy on the richness, nest abundance, and species composition of social wasps in the region of tropical dry forest of Brazil. The forested Caatinga physiognomy had the greatest richness of species (S = 16), followed by shrubby Caatinga (S 13) and by agricultural system (S = 12). The first axis of detrended correspondence analysis (DCA) explained 67.8% of the variability and shows a gradient of the fauna from agricultural system and shrubby Caatinga to forested Caatinga. In the first axis, wet season scores were much higher than those for the dry season in forested Caatinga. The second axis explained 18.7% of the variability and shows a separation of samples collected during the wet or the dry periods in shrubby Caatinga. This separation was less evident in the agricultural system. Variations in nest abundance were more intense in arbustive caatinga (45% decrease in number of active nests in the dry period), moderate in forested Caatinga (24% decrease in number of active nests in the dry period), and low in agricultural systems (8% decrease in the dry period).
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Majority of biometric researchers focus on the accuracy of matching using biometrics databases, including iris databases, while the scalability and speed issues have been neglected. In the applications such as identification in airports and borders, it is critical for the identification system to have low-time response. In this paper, a graph-based framework for pattern recognition, called Optimum-Path Forest (OPF), is utilized as a classifier in a pre-developed iris recognition system. The aim of this paper is to verify the effectiveness of OPF in the field of iris recognition, and its performance for various scale iris databases. This paper investigates several classifiers, which are widely used in iris recognition papers, and the response time along with accuracy. The existing Gauss-Laguerre Wavelet based iris coding scheme, which shows perfect discrimination with rotary Hamming distance classifier, is used for iris coding. The performance of classifiers is compared using small, medium, and large scale databases. Such comparison shows that OPF has faster response for large scale database, thus performing better than more accurate but slower Bayesian classifier.
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This study analyses the spatial distribution of characidiin fishes Characidium lauroi and Characidium alipioi (Crenuchidae) in a forest stream system located in southeastern Brazil. Fish were sampled from Jury 2001 to April 2002. Collections were made with an electro-fishing device in five stream reaches of the Ribeirão Grande system. Conductivity, pH, water temperature and dissolved oxygen were measured at each site. The species have different distributions in Ribeirão Grande system. Characidium lauroi is abundant in montane-piedmont zones and Characidium alipioi occurs mainly in piedmont-plain zones. Streams' different features contribute to these species' distribution in the system.
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Fraud detection in energy systems by illegal consumers is the most actively pursued study in non-technical losses by electric power companies. Commonly used supervised pattern recognition techniques, such as Artificial Neural Networks and Support Vector Machines have been applied for automatic commercial frauds identification, however they suffer from slow convergence and high computational burden. We introduced here the Optimum-Path Forest classifier for a fast non-technical losses recognition, which has been demonstrated to be superior than neural networks and similar to Support Vector Machines, but much faster. Comparisons among these classifiers are also presented. © 2009 IEEE.