954 resultados para Xerophytic vegetation


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Tese de doutoramento, Ciências do Mar, da Terra e do Ambiente, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

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We have used the BIOME4 biogeography–biochemistry model and comparison with palaeovegetation data to evaluate the response of six ocean–atmosphere general circulation models to mid-Holocene changes in orbital forcing in the mid- to high-latitudes of the northern hemisphere. All the models produce: (a) a northward shift of the northern limit of boreal forest, in response to simulated summer warming in high-latitudes. The northward shift is markedly asymmetric, with larger shifts in Eurasia than in North America; (b) an expansion of xerophytic vegetation in mid-continental North America and Eurasia, in response to increased temperatures during the growing season; (c) a northward expansion of temperate forests in eastern North America, in response to simulated winter warming. The northward shift of the northern limit of boreal forest and the northward expansion of temperate forests in North America are supported by palaeovegetation data. The expansion of xerophytic vegetation in mid-continental North America is consistent with palaeodata, although the extent may be over-estimated. The simulated expansion of xerophytic vegetation in Eurasia is not supported by the data. Analysis of an asynchronous coupling of one model to an equilibrium-vegetation model suggests vegetation feedback exacerbates this mid-continental drying and produces conditions more unlike the observations. Not all features of the simulations are robust: some models produce winter warming over Europe while others produce winter cooling. As a result, some models show a northward shift of temperate forests (consistent with, though less marked than, the expansion shown by data) and others produce a reduction in temperate forests. Elucidation of the cause of such differences is a focus of the current phase of the Palaeoclimate Modelling Intercomparison Project.

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Aim  This paper documents reconstructions of the vegetation patterns in Australia, Southeast Asia and the Pacific (SEAPAC region) in the mid-Holocene and at the last glacial maximum (LGM). Methods  Vegetation patterns were reconstructed from pollen data using an objective biomization scheme based on plant functional types. The biomization scheme was first tested using 535 modern pollen samples from 377 sites, and then applied unchanged to fossil pollen samples dating to 6000 ± 500 or 18,000 ± 1000 14C yr bp. Results  1. Tests using surface pollen sample sites showed that the biomization scheme is capable of reproducing the modern broad-scale patterns of vegetation distribution. The north–south gradient in temperature, reflected in transitions from cool evergreen needleleaf forest in the extreme south through temperate rain forest or wet sclerophyll forest (WSFW) and into tropical forests, is well reconstructed. The transitions from xerophytic through sclerophyll woodlands and open forests to closed-canopy forests, which reflect the gradient in plant available moisture from the continental interior towards the coast, are reconstructed with less geographical precision but nevertheless the broad-scale pattern emerges. 2. Differences between the modern and mid-Holocene vegetation patterns in mainland Australia are comparatively small and reflect changes in moisture availability rather than temperature. In south-eastern Australia some sites show a shift towards more moisture-stressed vegetation in the mid-Holocene with xerophytic woods/scrub and temperate sclerophyll woodland and shrubland at sites characterized today by WSFW or warm-temperate rain forest (WTRF). However, sites in the Snowy Mountains, on the Southern Tablelands and east of the Great Dividing Range have more moisture-demanding vegetation in the mid-Holocene than today. South-western Australia was slightly drier than today. The single site in north-western Australia also shows conditions drier than today in the mid-Holocene. Changes in the tropics are also comparatively small, but the presence of WTRF and tropical deciduous broadleaf forest and woodland in the mid-Holocene, in sites occupied today by cool-temperate rain forest, indicate warmer conditions. 3. Expansion of xerophytic vegetation in the south and tropical deciduous broadleaf forest and woodland in the north indicate drier conditions across mainland Australia at the LGM. None of these changes are informative about the degree of cooling. However the evidence from the tropics, showing lowering of the treeline and forest belts, indicates that conditions were between 1 and 9 °C (depending on elevation) colder. The encroachment of tropical deciduous broadleaf forest and woodland into lowland evergreen broadleaf forest implies greater aridity. Main conclusions  This study provides the first continental-scale reconstruction of mid-Holocene and LGM vegetation patterns from Australia, Southeast Asia and the Pacific (SEAPAC region) using an objective biomization scheme. These data will provide a benchmark for evaluation of palaeoclimate simulations within the framework of the Palaeoclimate Modelling Intercomparison Project.

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New compilations of African pollen and lake data are compared with climate (CCM1, NCAR, Boulder) and vegetation (BIOME 1.2, GSG, Lund) simulations for the last glacial maximum (LGM) and early to mid-Holocene (EMH). The simulated LGM climate was ca 4°C colder and drier than present, with maximum reduction in precipitation in semi-arid regions. Biome simulations show lowering of montane vegetation belts and expansion of southern xerophytic associations, but no change in the distribution of deserts and tropical rain forests. The lakes show LGM conditions similar or drier than present throughout northern and tropical Africa. Pollen data indicate lowering of montane vegetation belts, the stability of the Sahara, and a reduction of rain forest. The paleoenvironmental data are consistent with the simulated changes in temperature and moisture budgets, although they suggest the climate model underestimates equatorial aridity. EMH simulations show temperatures slightly less than present and increased monsoonal precipitation in the eastern Sahara and East Africa. Biome simulations show an upward shift of montane vegetation belts, fragmentation of xerophytic vegetation in southern Africa, and a major northward shift of the southern margin of the eastern Sahara. The lakes indicate conditions wetter than present across northern Africa. Pollen data show an upward shift of the montane forests, the northward shift of the southern margin of the Sahara, and a major extension of tropical rain forest. The lake and pollen data confirm monsoon expansion in eastern Africa, but the climate model fails to simulate the wet conditions in western Africa.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The vegetation in north Minas Gerais State is poorly known, and for some authors it is the southern limit of natural occurrence for 'carrasco' and 'caatinga' species. Floristic sampling was made in different areas of Januária municipality, Minas Gerais, including physiognomies of 'carrasco' (tree-shrub 'caatinga'), deciduous forest, 'cerrado', floodable field and riparian vegetation ('vereda'), besides calcicolous vegetation. Six-hundred-eight species in 114 families were found, the five most diverse families were Fabaceae (87 species), Asteraceae (35 species), Euphorbiaceae (28 species), Bignoniaceae (25 species), and Malpighiaceae (21 species). The sampled vegetation included a diversity of vegetation forms. The most diverse areas were the 'carrasco' and the deciduous forest (274 species), secondary vegetation along roads and trails, and pastures (160 species), 'cerrado' (105 species), 'vereda' (98 species), and calcicolous vegetation and riparian vegetation (78 species each). Compared to other floristic surveys performed in northeastern Brazil, even considering only the woody component (tree and shrubs with 323 species), these results highlight the floristic and physiognomic diversity of the studied area. © 2005 Instituto de Ciências Biológicas - UFMG.

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Pollen stratigraphy of a core 270 cm long from Lake Dalgoto at 2310 m in the Northern Pirin Mountains, southern Bulgaria, was treated by optimal partitioning and compared to a broken-stick model to reveal statistically significant pollen zones. The vegetational reconstructions presented here are based on pollen percentages and pollen influx, on comparisons of modern and fossil pollen spectra, and on macrofossil dates from other sites in the mountains. During the Younger Dryas (11000–10200 14C yr BP), an open xerophytic herb vegetation with Artemisia and Chenopodiaceae was widely developed around the lake. Deciduous trees growing at lower elevations contributed to the pollen rain deposited at the higher-elevation sampling sites. Specifically, from 10200 to 8500 yr BP, Quercus, Ulmus, Tilia and Betula expanded rapidly at low and intermediate elevations, and between 8500 and 6500 yr BP they extended to higher elevations close to the upper forest limit, which was formed by Betula pendula at about 1900 m. Coniferous species were limited in the region at this time. After 6500 yr BP, the expansion of conifers (Pinus peuce, P. sylvestris, P. mugo, Abies alba) at high elevations forced the deciduous trees downward. Between 6500 and 3000 yr BP, the forest limit at 2200 m was formed by P. peuce, and A. alba had its maximum vertical range up to 1900 m. Later the abundance and vertical range of P. peuce and A. alba were reduced. After 3000 yr BP, Picea expanded.

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The following paper presents an evaluation of airborne sensors for use in vegetation management in powerline corridors. Three integral stages in the management process are addressed including, the detection of trees, relative positioning with respect to the nearest powerline and vegetation height estimation. Image data, including multi-spectral and high resolution, are analyzed along with LiDAR data captured from fixed wing aircraft. Ground truth data is then used to establish the accuracy and reliability of each sensor thus providing a quantitative comparison of sensor options. Tree detection was achieved through crown delineation using a Pulse-Coupled Neural Network (PCNN) and morphologic reconstruction applied to multi-spectral imagery. Through testing it was shown to achieve a detection rate of 96%, while the accuracy in segmenting groups of trees and single trees correctly was shown to be 75%. Relative positioning using LiDAR achieved a RMSE of 1.4m and 2.1m for cross track distance and along track position respectively, while Direct Georeferencing achieved RMSE of 3.1m in both instances. The estimation of pole and tree heights measured with LiDAR had a RMSE of 0.4m and 0.9m respectively, while Stereo Matching achieved 1.5m and 2.9m. Overall a small number of poles were missed with detection rates of 98% and 95% for LiDAR and Stereo Matching.

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The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.

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This paper reports on the empirical comparison of seven machine learning algorithms in texture classification with application to vegetation management in power line corridors. Aiming at classifying tree species in power line corridors, object-based method is employed. Individual tree crowns are segmented as the basic classification units and three classic texture features are extracted as the input to the classification algorithms. Several widely used performance metrics are used to evaluate the classification algorithms. The experimental results demonstrate that the classification performance depends on the performance matrix, the characteristics of datasets and the feature used.

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This paper presents a comprehensive discussion of vegetation management approaches in power line corridors based on aerial remote sensing techniques. We address three issues 1) strategies for risk management in power line corridors, 2) selection of suitable platforms and sensor suite for data collection and 3) the progress in automated data processing techniques for vegetation management. We present initial results from a series of experiments and, challenges and lessons learnt from our project.

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A good object representation or object descriptor is one of the key issues in object based image analysis. To effectively fuse color and texture as a unified descriptor at object level, this paper presents a novel method for feature fusion. Color histogram and the uniform local binary patterns are extracted from arbitrary-shaped image-objects, and kernel principal component analysis (kernel PCA) is employed to find nonlinear relationships of the extracted color and texture features. The maximum likelihood approach is used to estimate the intrinsic dimensionality, which is then used as a criterion for automatic selection of optimal feature set from the fused feature. The proposed method is evaluated using SVM as the benchmark classifier and is applied to object-based vegetation species classification using high spatial resolution aerial imagery. Experimental results demonstrate that great improvement can be achieved by using proposed feature fusion method.