211 resultados para Savanna
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The reproductive biology of shrubs and trees of a preserved savanna (''cerrado'') area in the municipality of Corumbatai São Paulo State, Brazil was studied. The floral sexuality of 135 species were characterized, with 85.2 % hermaphroditic, 9.4 % dioecious, 4.5 % monoecious, and one determine the breeding systems. Nine apomictic species were found, all belonging Melastomataceae. Among the twelve sexual reproducing species, seven (58.3 %) proved to be self-compatible, and five (41.7 %) self-incompatible. Anemophily was found in five species, although pollinations systems were not investigated in other species.
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The quantity and distribution of vegetal biomass are important aspects to consider in ecosystem studies. However, little information is available about Brazil's Pantanal woodland savannas. This work involved the development of regression equations of the aerial biomass and wood volume of native tree species in a region of woodland savanna on Rio Negro farm in the Pantanal of Nhecolandia, Brazil. Samples were taken from 10 trees of each of five species: Protium heptaphyllum (Aub1.) Marchand, Magonia pubescens A. St.-Hil., Diptychandra aurantiaca Tul., Terminalia argentea Mart. and Zucc. and Licania minutiflora (Sagot) Fritsch and from a miscellaneous group of I I different species. Linear and nonlinear regression analyses were developed relating the diameter at breast height to the dry weight of wood, branches and leaves, wood volume and total aerial biomass. All the regressions showed a significance of P < 0.05 and an R-2 close to or above 0.8. The biomass curve predicted by linear regression analysis of the studied species was similar to the nonlinear regression, with the exception of L. minutiflora and the miscellaneous group. The breast height diameter proved a good choice for estimating biomass and wood volume. The estimated wood volume and biomass of the Pantanal woodland savanna is crucial information for understanding the carbon cycle and for ensuring the region's conservation and sustainable use. (c) 2006 Elsevier B.V. All rights reserved.
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Plant phenology has gained importance in the context of global change research, stimulating the development of new technologies for phenological observation. Digital cameras have been successfully used as multi-channel imaging sensors, providing measures of leaf color change information (RGB channels), or leafing phenological changes in plants. We monitored leaf-changing patterns of a cerrado-savanna vegetation by taken daily digital images. We extract RGB channels from digital images and correlated with phenological changes. Our first goals were: (1) to test if the color change information is able to characterize the phenological pattern of a group of species; and (2) to test if individuals from the same functional group may be automatically identified using digital images. In this paper, we present a machine learning approach to detect phenological patterns in the digital images. Our preliminary results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; and (2) different plant species present a different behavior with respect to the color change information. Based on those results, we suggest that individuals from the same functional group might be identified using digital images, and introduce a new tool to help phenology experts in the species identification and location on-the-ground. ©2012 IEEE.
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Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V. All rights reserved.
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The ecology of forest and savanna trees species will largely determine the structure and dynamics of the forest-savanna boundaries, but little is known about the constraints to leaf trait variation imposed by selective forces and evolutionary history during the process of savanna invasion by forest species. We compared seasonal patterns in leaf traits related to leaf structure, carbon assimilation, water, and nutrient relations in 10 congeneric species pairs, each containing one savanna species and one forest species. All individuals were growing in dystrophic oxisols in a fire-protected savanna of Central Brazil. We tested the hypothesis that forest species would be more constrained by seasonal drought and nutrient-poor soils than their savanna congeners. We also hypothesized that habitat, rather than phylogeny, would explain more of the interspecific variance in leaf traits of the studied species. We found that throughout the year forest trees had higher specific leaf area (SLA) but lower integrated water use efficiency than savanna trees. Forest and savanna species maintained similar values of predawn and midday leaf water potential along the year. Lower values were measured in the dry season. However, this was achieved by a stronger regulation of stomatal conductance and of CO2 assimilation on an area basis (A area) in forest trees, particularly toward the end of the dry season. Relative to savanna trees, forest trees maintained similar (P, K, Ca, and Mg) or slightly higher (N) leaf nutrient concentrations. For the majority of traits, more variance was explained by phylogeny, than by habitat of origin, with the exception of SLA, leaf N concentration, and A area, which were apparently subjected to different selective pressures in the savanna and forest environments. In conclusion, water shortage during extended droughts would be more limiting for forest trees than nutrient-poor soils. © 2013 Springer-Verlag Berlin Heidelberg.
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Communication contributes to mediate the interactions between plants and the animals that disperse their genes. As yet, seasonal patterns in plant-animal communication are unknown, even though many habitats display pronounced seasonality e.g. when leaves senescence. We thus hypothesized that the contrast between fruit displays and their background vary throughout the year in a seasonal habitat. If this variation is adaptive, we predicted higher contrasts between fruits and foliage during the fruiting season in a cerrado-savanna vegetation, southeastern Brazil. Based on a six-year data base of fruit ripening and a one-year data set of fruit biomass, we used reflectance measurements and contrast analysis to show that fruits with distinct colors differed in the beginning of ripening and the peak of fruit biomass. Black, and particularly red fruits, that have a high contrast against the leaf background, were highly seasonal, peaking in the wet season. Multicolored and yellow fruits were less seasonal, not limited to one season, with a bimodal pattern for yellow ones, represented by two peaks, one in each season. We further supported the hypothesis that seasonal changes in fruit contrasts can be adaptive because fruits contrasted more strongly against their own foliage in the wet season, when most fruits are ripe. Hence, the seasonal variation in fruit colors observed in the cerrado-savanna may be, at least partly, explicable as an adaptation to ensure high conspicuousness to seed dispersers. © 2013 The Authors.
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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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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Savannas are characterized by sparsely distributed woody species within a continuous herbaceous cover, composed mainly by grasses and small eudicot herbs. This vegetation structure is variable across the landscape, with shifts from open grassland to savanna woodland determined by factors that control tree density. These shifts often appear coupled with environmental variations, such as topographic gradients. Here we investigated whether herbaceous and woody savanna species differ in their use of soil water along a topographic gradient of about 110 m, spanning several vegetation physiognomies generally associated with Neotropical savannas. We measured the delta H-2 and delta O-18 signatures of plants, soils, groundwater and rainfall, determining the depth of plant water uptake and examining variations in water uptake patterns along the gradient. We found that woody species use water from deeper soil layers compared to herbaceous species, regardless of their position in the topographic gradient. However, the presence of a shallow water table restricted plant water uptake to the superficial soil layers at lower portions of the gradient. We confirmed that woody and herbaceous species are plastic with respect to their water use strategy, which determines niche partitioning across topographic gradients. Abiotic factors such as groundwater level, affect water uptake patterns independently of plant growth form, reinforcing vegetation gradients by exerting divergent selective pressures across topographic gradients. (C) 2013 SAAB. Published by Elsevier B.V. All rights reserved.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação do Amparo à Pesquisa do Estado de São Paulo (FAPESP)