964 resultados para SOUTH AMERICA
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The vast diversity of present vegetation and environments that occur throughout South America (12°N to 56°S) is the result of diverse processes that have been operating and interacting at different spatial and temporal scales. Global factors, such as the concentration of CO2 in the atmosphere, may have been significant for high altitude vegetation during times of lower abundance, while lower sea levels of glacial stages potentially opened areas of continental shelf for colonisation during a substantial portion of the Quaternary. Latitudinal variation in orbital forcing has operated on a regional scale. The pace of climate change in the tropics is dominated by precessional oscillations of c. 20 kyr, while the high latitudes of the south are dominated by obliquity oscillations of c. 40 kyr. In particular, seasonal insolation changes forced by precessional oscillations must have had important consequences for the distribution limits of species, with potentially different effects depending on the latitude. The availability of taxa, altitude and human impact, among other events, have locally influenced the environments. Disentangling the different forcing factors of environmental change that operate on different timescales, and understanding the underlying mechanisms leads to considerable challenges for palaeoecologists. The papers in this Special Issue present a selection of palaeoecological studies throughout South America on vegetation changes and other aspects of the environment, providing a window on the possible complexity of the nature of transitions and timings that are potentially available.
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Dissertação de mest., Linguística, Faculdade de Ciências Humanas e Sociais, Universidade do Algarve, 2007
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UANL
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This study proposes an objective integrated seasonal forecasting system for producing well-calibrated probabilistic rainfall forecasts for South America. The proposed system has two components: ( i) an empirical model that uses Pacific and Atlantic sea surface temperature anomalies as predictors for rainfall and ( ii) a multimodel system composed of three European coupled ocean - atmosphere models. Three-month lead austral summer rainfall predictions produced by the components of the system are integrated ( i. e., combined and calibrated) using a Bayesian forecast assimilation procedure. The skill of empirical, coupled multimodel, and integrated forecasts obtained with forecast assimilation is assessed and compared. The simple coupled multimodel ensemble has a comparable level of skill to that obtained using a simplified empirical approach. As for most regions of the globe, seasonal forecast skill for South America is low. However, when empirical and coupled multimodel predictions are combined and calibrated using forecast assimilation, more skillful integrated forecasts are obtained than with either empirical or coupled multimodel predictions alone. Both the reliability and resolution of the forecasts have been improved by forecast assimilation in several regions of South America. The Tropics and the area of southern Brazil, Uruguay, Paraguay, and northern Argentina have been found to be the two most predictable regions of South America during the austral summer. Skillful rainfall forecasts are generally only possible during El Nino or La Nina years rather than in neutral years.
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This study addresses three issues: spatial downscaling, calibration, and combination of seasonal predictions produced by different coupled ocean-atmosphere climate models. It examines the feasibility Of using a Bayesian procedure for producing combined, well-calibrated downscaled seasonal rainfall forecasts for two regions in South America and river flow forecasts for the Parana river in the south of Brazil and the Tocantins river in the north of Brazil. These forecasts are important for national electricity generation management and planning. A Bayesian procedure, referred to here as forecast assimilation, is used to combine and calibrate the rainfall predictions produced by three climate models. Forecast assimilation is able to improve the skill of 3-month lead November-December-January multi-model rainfall predictions over the two South American regions. Improvements are noted in forecast seasonal mean values and uncertainty estimates. River flow forecasts are less skilful than rainfall forecasts. This is partially because natural river flow is a derived quantity that is sensitive to hydrological as well as meteorological processes, and to human intervention in the form of reservoir management.
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We explored the potential for using Pediastrum (Meyen), a genus of green alga commonly found in palaeoecological studies, as a proxy for lake-level change in tropical South America. The study site, Laguna La Gaiba (LLG) (17°45′S, 57°40′W), is a broad, shallow lake located along the course of the Paraguay River in the Pantanal, a 135,000-km2 tropical wetland located mostly in western Brazil, but extending into eastern Bolivia. Fourteen surface sediment samples were taken from LLG across a range of lake depths (2-5.2 m) and analyzed for Pediastrum. We found seven species, of which P. musteri (Tell et Mataloni), P. argentiniense (Bourr. et Tell), and P. cf. angulosum (Ehrenb.) ex Menegh. were identified as potential indicators of lake level. Results of the modern dataset were applied to 31 fossil Pediastrum assemblages spanning the early Holocene (12.0 kyr BP) to present to infer past lake level changes qualitatively. Early Holocene (12.0-9.8 kyr BP) assemblages do not show a clear signal, though abundance of P. simplex (Meyen) suggests relatively high lake levels. Absence of P. musteri, characteristic of deep, open water, and abundance of macrophyte-associated taxa indicate lake levels were lowest from 9.8 to 3.0 kyr BP. A shift to wetter conditions began at 4.4 kyr BP, indicated by the appearance of P. musteri, though inferred lake levels did not reach modern values until 1.4 kyr BP. The Pediastrum-inferred mid-Holocene lowstand is consistent with lower precipitation, previously inferred using pollen from this site, and is also in agreement with evidence for widespread drought in the South American tropics during the middle Holocene. An inference for steadily increasing lake level from 4.4 kyr BP to present is consistent with diatom-inferred water level rise at Lake Titicaca, and demonstrates coherence with the broad pattern of increasing monsoon strength from the late Holocene until present in tropical South America.
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We present a well-dated, high-resolution, ~ 45 kyr lake sediment record reflecting regional temperature and precipitation change in the continental interior of the Southern Hemisphere (SH) tropics of South America. The study site is Laguna La Gaiba (LLG), a large lake (95 km2) hydrologically-linked to the Pantanal, an immense, seasonally-flooded basin and the world's largest tropical wetland (135,000 km2). Lake-level changes at LLG are therefore reflective of regional precipitation. We infer past fluctuations in precipitation at this site through changes in: i) pollen-inferred extent of flood-tolerant forest; ii) relative abundance of terra firme humid tropical forest versus seasonally-dry tropical forest pollen types; and iii) proportions of deep- versus shallow-water diatoms. A probabilistic model, based on plant family and genus climatic optima, was used to generate quantitative estimates of past temperature from the fossil pollen data. Our temperature reconstruction demonstrates rising temperature (by 4 °C) at 19.5 kyr BP, synchronous with the onset of deglacial warming in the central Andes, strengthening the evidence that climatic warming in the SH tropics preceded deglacial warming in the Northern Hemisphere (NH) by at least 5 kyr. We provide unequivocal evidence that the climate at LLG was markedly drier during the last glacial period (45.0–12.2 kyr BP) than during the Holocene, contrasting with SH tropical Andean and Atlantic records that demonstrate a strengthening of the South American summer monsoon during the global Last Glacial Maximum (~ 21 kyr BP), in tune with the ~ 20 kyr precession orbital cycle. Holocene climate conditions occurred as early as 12.8–12.2 kyr BP, when increased precipitation in the Pantanal catchment caused heightened flooding and rising lake levels in LLG. In contrast to this strong geographic variation in LGM precipitation across the continent, expansion of tropical dry forest between 10 and 3 kyr BP at LLG strengthens the body of evidence for widespread early–mid Holocene drought across tropical South America.
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An ongoing controversy in Amazonian palaeoecology is the manner in which Amazonian rainforest communities have responded to environmental change over the last glacial–interglacial cycle. Much of this controversy results from an inability to identify the floristic heterogeneity exhibited by rainforest communities within fossil pollen records. We apply multivariate (Principal Components Analysis) and classification (Unweighted Pair Group with Arithmetic Mean Agglomerative Classification) techniques to floral-biometric, modern pollen trap and lake sediment pollen data situated within different rainforest communities in the tropical lowlands of Amazonian Bolivia. Modern pollen rain analyses from artificial pollen traps show that evergreen terra firme (well-drained), evergreen terra firme liana, evergreen seasonally inundated, and evergreen riparian rainforests may be readily differentiated, floristically and palynologically. Analogue matching techniques, based on Euclidean distance measures, are employed to compare these pollen signatures with surface sediment pollen assemblages from five lakes: Laguna Bella Vista, Laguna Chaplin, and Laguna Huachi situated within the Madeira-Tapajós moist forest ecoregion, and Laguna Isirere and Laguna Loma Suarez, which are situated within forest patches in the Beni savanna ecoregion. The same numerical techniques are used to compare rainforest pollen trap signatures with the fossil pollen record of Laguna Chaplin.
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The process of global deforestation calls for urgent attention, particularly in South America where deforestation rates have failed to decline over the past 20 years. The main direct cause of deforestation is land conversion to agriculture. We combine data from the FAO and the World Bank for six tropical Southern American countries over the period 1970–2006, estimate a panel data model accounting for various determinants of agricultural land expansion and derive elasticities to quantify the effect of the different independent variables. We investigate whether agricultural intensification, in conjunction with governance factors, has been promoting agricultural expansion, leading to a ‘‘Jevons paradox’’. The paradox occurs if an increase in the productivity of one factor (here agricultural land) leads to its increased, rather than decreased, utilization. We find that for high values of our governance indicators a Jevons paradox exists even for moderate levels of agricultural productivity, leading to an overall expansion of agricultural area. Agricultural expansion is also positively related to the level of service on external debt and population growth, while its association with agricultural exports is only moderate. Finally, we find no evidence of an environmental Kuznets curve, as agricultural area is ultimately positively correlated to per-capita income levels.
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The results of coupled high resolution global models (CGCMs) over South America are discussed. HiGEM1.2 and HadGEM1.2 simulations, with horizontal resolution of ~90 and 135 km, respectively, are compared. Precipitation estimations from CMAP (Climate Prediction Center—Merged Analysis of Precipitation), CPC (Climate Prediction Center) and GPCP (Global Precipitation Climatology Project) are used for validation. HiGEM1.2 and HadGEM1.2 simulated seasonal mean precipitation spatial patterns similar to the CMAP. The positioning and migration of the Intertropical Convergence Zone and of the Pacific and Atlantic subtropical highs are correctly simulated by the models. In HiGEM1.2 and HadGEM1.2, the intensity and locations of the South Atlantic Convergence Zone are in agreement with the observed dataset. The simulated annual cycles are in phase with estimations of rainfall for most of the six regions considered. An important result is that HiGEM1.2 and HadGEM1.2 eliminate a common problem of coarse resolution CGCMs, which is the simulation of a semiannual cycle of precipitation due to the semiannual solar forcing. Comparatively, the use of high resolution in HiGEM1.2 reduces the dry biases in the central part of Brazil during austral winter and spring and in most part of the year over an oceanic box in eastern Uruguay.
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In this paper we address two topical questions: How do the quality of governance and agricultural intensification impact on spatial expansion of agriculture? Which aspects of governance are more likely to ensure that agricultural intensification allows sparing land for nature? Using data from the Food and Agriculture Organization, the World Bank, the World Database on Protected Areas, and the Yale Center for Environmental Law and Policy, we estimate a panel data model for six South American countries and quantify the effects of major determinants of agricultural land expansion, including various dimensions of governance, over the period 1970–2006. The results indicate that the effect of agricultural intensification on agricultural expansion is conditional on the quality and type of governance. When considering conventional aspects of governance, agricultural intensification leads to an expansion of agricultural area when governance scores are high. When looking specifically at environmental aspects of governance, intensification leads to a spatial contraction of agriculture when governance scores are high, signaling a sustainable intensification process.