124 resultados para Cloud Forest


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Leaf-cutting ants consume up to 10% of canopy leaves in the foraging area of their colony and therefore represent a key perturbation in the nutrient cycle of tropical forests. We used a chronosequence of nest sites on Barro, Colorado Island, Panama, to assess the influence of leaf-cutting ants (Atta colombica) on nutrient availability in a neotropical rainforest. Twelve nest sites were sampled, including active nests, recently abandoned nests (<1 year) and long-abandoned nests (>1 year). Waste material discarded by the ants down-slope from the nests contained large concentrations of nitrogen and phosphorus in both total and soluble forms, but decomposed within one year after the nests were abandoned. Despite this, soil under the waste material contained high concentrations of nitrate and ammonium that persisted after the disappearance of the waste, although soluble phosphate returned to background concentrations within one year of nest abandonment. Fine roots were more abundant in soil under waste than control soils up to one year after nest abandonment, but were not significantly different for older sites. In contrast to the waste dumps, soil above the underground nest chambers consistently contained lower nutrient concentrations than control soils, although this was not statistically significant. We conclude that the 'islands of fertility' created by leaf-cutting ants provide a nutritional benefit to nearby plants for less than one year after nest abandonment in the moist tropical environment of Barro Colorado Island. Published by Elsevier Ltd.

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Long-term monitoring of forest soils as part of a pan-European network to detect environmental change depends on an accurate determination of the mean of the soil properties at each monitoring event. Forest soil is known to be very variable spatially, however. A study was undertaken to explore and quantify this variability at three forest monitoring plots in Britain. Detailed soil sampling was carried out, and the data from the chemical analyses were analysed by classical statistics and geostatistics. An analysis of variance showed that there were no consistent effects from the sample sites in relation to the position of the trees. The variogram analysis showed that there was spatial dependence at each site for several variables and some varied in an apparently periodic way. An optimal sampling analysis based on the multivariate variogram for each site suggested that a bulked sample from 36 cores would reduce error to an acceptable level. Future sampling should be designed so that it neither targets nor avoids trees and disturbed ground. This can be achieved best by using a stratified random sampling design.

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In a recent investigation, Landsat TM and ETM+ data were used to simulate different resolutions of remotely-sensed images (from 30 to 1100 m) and to analyze the effect of resolution on a range of landscape metrics associated with spatial patterns of forest fragmentation in Chapare, Bolivia since the mid-1980s. Whereas most metrics were found to be highly dependent on pixel size, several fractal metrics (DLFD, MPFD, and AWMPFD) were apparently independent of image resolution, in contradiction with a sizeable body of literature indicating that fractal dimensions of natural objects depend strongly on image characteristics. The present re-analysis of the Chapare images, using two alternative algorithms routinely used for the evaluation of fractal dimensions, shows that the values of the box-counting and information fractal dimensions are systematically larger, sometimes by as much as 85%, than the "fractal" indices DLFD, MPFD, and AWMFD for the same images. In addition, the geometrical fractal features of the forest and non-forest patches in the Chapare region strongly depend on the resolution of images used in the analysis. The largest dependency on resolution occurs for the box-counting fractal dimension in the case of the non-forest patches in 1993, where the difference between the 30 and I 100 m-resolution images corresponds to 24% of the full theoretical range (1.0 to 2.0) of the mass fractal dimension. The observation that the indices DLFD, MPFD, and AWMPFD, unlike the classical fractal dimensions, appear relatively unaffected by resolution in the case of the Chapare images seems due essentially to the fact that these indices are based on a heuristic, "non-geometric" approach to fractals. Because of their lack of a foundation in fractal geometry, nothing guarantees that these indices will be resolution-independent in general. (C) 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

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Inductively coupled plasma mass spectrometry (ICP-MS) was used to investigate changes in trace element concentration in two high resolution sequences of tree rings from central Sweden. Individual annual growth increments from 18002002 to 1930-2002 were sampled from two Scots pine (Pinus sylvestris) trees from the Siljansfors Experimental Forest. The aims of the study were: to test the viability of conventional solution induction ICP-MS as a technique for investigating the multi-elemental chemistry of long tree ring sequences at annual resolution, and, to test this specifically with a view to detecting changes in elemental concentrations of Swedish tree rings contemporary with the major (and relatively proximal) Icelandic eruption of Askja (1875). It was found that despite a time consuming sample preparation process, it was possible to use conventional ICP-MS for multi-elemental analysis of a long sequence of tree rings at annual resolution. Although promising data were produced, no truly conclusive concentration anomaly could be detected in the sequence to indicate the impact of the Askja eruption on environmental chemistry. Overall findings underlined the complexity of the tree/environment interaction and the cautious approach to data interpretation essential for any dendrochemical study. (c) 2006 Elsevier Ltd. All rights reserved.

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Stream-water flows and in-stream nitrate and ammonium concentrations in a small (36.7 ha) Atlantic Forest catchment were simulated using the Integrated Nitrogen in CAtchments (INCA) model version 1.9.4. The catchment, at Cunha, is in the Serra do Mar State Park, SE Brazil and is nearly pristine because the nearest major conurbations, Sao Paulo and Rio, are some 450 km distant. However, intensive farming may increase nitrogen (N) deposition and there are growing pressures for urbanisation. The mean-monthly discharges and NO3-N concentration dynamics were simulated adequately for the calibration and validation periods with (simulated) loss rates of 6.55 kg.ha(-1) yr(-1) for NO3-N and 3.85 kg.ha(-1) yr(-1) for NH4-N. To investigate the effects of elevated levels of N deposition in the future, various scenarios for atmospheric deposition were simulated; the highest value corresponded to that in a highly polluted area of Atlantic Forest in Sao Paulo City. It was found that doubling the atmospheric deposition generated a 25% increase in the N leaching rate, while at levels approaching the highly polluted Sao Paulo deposition rate, five times higher than the current rate, leaching increased by 240%, which would create highly eutrophic conditions, detrimental to downstream water quality. The results indicate that the INCA model can be useful for estimating N concentration and fluxes for different atmospheric deposition rates and hydrological conditions.

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We performed an ensemble of twelve five-year experiments using a coupled climate-carbon-cycle model with scenarios of prescribed atmospheric carbon dioxide concentration; CO2 was instantaneously doubled or quadrupled at the start of the experiments. Within these five years, climate feedback is not significantly influenced by the effects of climate change on the carbon system. However, rapid changes take place, within much less than a year, due to the physiological effect of CO2 on plant stomatal conductance, leading to adjustment in the shortwave cloud radiative effect over land, due to a reduction in low cloud cover. This causes a 10% enhancement to the radiative forcing due to CO2, which leads to an increase in the equilibrium warming of 0.4 and 0.7 K for doubling and quadrupling. The implications for calibration of energy-balance models are discussed.

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[1] Cloud cover is conventionally estimated from satellite images as the observed fraction of cloudy pixels. Active instruments such as radar and Lidar observe in narrow transects that sample only a small percentage of the area over which the cloud fraction is estimated. As a consequence, the fraction estimate has an associated sampling uncertainty, which usually remains unspecified. This paper extends a Bayesian method of cloud fraction estimation, which also provides an analytical estimate of the sampling error. This method is applied to test the sensitivity of this error to sampling characteristics, such as the number of observed transects and the variability of the underlying cloud field. The dependence of the uncertainty on these characteristics is investigated using synthetic data simulated to have properties closely resembling observations of the spaceborne Lidar NASA-LITE mission. Results suggest that the variance of the cloud fraction is greatest for medium cloud cover and least when conditions are mostly cloudy or clear. However, there is a bias in the estimation, which is greatest around 25% and 75% cloud cover. The sampling uncertainty is also affected by the mean lengths of clouds and of clear intervals; shorter lengths decrease uncertainty, primarily because there are more cloud observations in a transect of a given length. Uncertainty also falls with increasing number of transects. Therefore a sampling strategy aimed at minimizing the uncertainty in transect derived cloud fraction will have to take into account both the cloud and clear sky length distributions as well as the cloud fraction of the observed field. These conclusions have implications for the design of future satellite missions. This paper describes the first integrated methodology for the analytical assessment of sampling uncertainty in cloud fraction observations from forthcoming spaceborne radar and Lidar missions such as NASA's Calipso and CloudSat.

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Eight years of cloud properties retrieved from Television Infrared Observation Satellite-N (TIROS-N) Observational Vertical Sounder (TOVS) observations aboard the NOAA polar orbiting satellites are presented. The relatively high spectral resolution of these instruments in the infrared allows especially reliable cirrus identification day and night. This dataset therefore provides complementary information to the International Satellite Cloud Climatology Project (ISCCP). According to this dataset, cirrus clouds cover about 27% of the earth and 45% of the Tropics, whereas ISCCP reports 19% and 25%, respectively. Both global datasets agree within 5% on the amount of single-layer low clouds, at 30%. From 1987 to 1995, global cloud amounts remained stable to within 2%. The seasonal cycle of cloud amount is in general stronger than its diurnal cycle and it is stronger than the one of effective cloud amount, the latter the relevant variable for radiative transfer. Maximum effective low cloud amount over ocean occurs in winter in SH subtropics in the early morning hours and in NH midlatitudes without diurnal cycle. Over land in winter the maximum is in the early afternoon, accompanied in the midlatitudes by thin cirrus. Over tropical land and in the other regions in summer, the maximum of mesoscale high opaque clouds occurs in the evening. Cirrus also increases during the afternoon and persists during night and early morning. The maximum of thin cirrus is in the early afternoon, then decreases slowly while cirrus and high opaque clouds increase. TOVS extends information of ISCCP during night, indicating that high cloudiness, increasing during the afternoon, persists longer during night in the Tropics and subtropics than in midlatitudes. A comparison of seasonal and diurnal cycle of high cloud amount between South America, Africa, and Indonesia during boreal winter has shown strong similarities between the two land regions, whereas the Indonesian islands show a seasonal and diurnal behavior strongly influenced by the surrounding ocean. Deeper precipitation systems over Africa than over South America do not seem to be directly reflected in the horizontal coverage and mesoscale effective emissivity of high clouds.