985 resultados para Parzen density estimates
Resumo:
Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.
Resumo:
Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.
Resumo:
Densities of layer 2 basalt recovered during the Deep Sea Drilling Project have been found to decrease steadily with age, a finding ascribed to progressive submarine weathering in the context of sea-floor spreading. The least-squares solution for 52 density measurements gives a rate of decrease in density of (Delta p)/(Delta t) = -0.0046 g per ccm m.y. = -16 percent per 100 m.y., which is in excellent agreement with earlier estimates based on observed chemical depletion rates of dredged oceanic basalt. Weathering of sea-floor basalt, should it penetrate to any considerable depth in layer 2, will decrease layer 2 seismic refraction velocities, act as a source of geothermal heat, and substantially influence the chemistry of sea water and the overlying column of sediment.
Resumo:
The South Georgia region supports a large biomass of krill that is subject to high interannual variability. The apparent lack of a locally self-maintaining krill population at South Georgia means that understanding the mechanism underlying these observed population characteristics is essential to successful ecosystem-based management of krill fishery in the region. Krill acoustic-density data from surveys conducted in the early, middle and late period of the summers of 2001 to 2005, together with krill population size structure over the same period from predator diet data, were used with a krill population dynamics model to evaluate potential mechanisms behind the observed changes in krill biomass. Krill abundance was highest during the middle of the summer in 3 years and in the late period in 2 years; in the latter there was evidence that krill recruitment was delayed by several months. A model scenario that included empirically derived estimates of both the magnitude and timing of recruitment in each year showed the greatest correlation with the acoustic series. The results are consistent with a krill population with allochthonous recruitment entering a retained adult population; i.e. oceanic transport of adult krill does not appear to be the major factor determining the dynamics of the adult population. The results highlight the importance of the timing of recruitment, especially where this could introduce a mismatch between the peak of krill abundance and the peak demand from predators, which may exacerbate the effects of changes in krill populations arising from commercial harvesting and/or climate change.
Resumo:
Paleotemperature estimates based on coral Sr/Ca have not been widely accepted because the reconstructed glacial-Holocene shift in tropical sea-surface temperature (~4-6°C) is larger than that indicated by foraminiferal Mg/Ca (~2-4°C). We show that corals over-estimate changes in sea-surface temperature (SST) because their records are attenuated during skeletogenesis within the living tissue layer. To quantify this process, we microprofiled skeletal mass accumulation within the tissue layer of Porites from Australasian coral reefs and laboratory culturing experiments. The results show that the sensitivity of the Sr/Ca and d18O thermometers in Porites will be suppressed, variable, and dependent on the relationship between skeletal growth rate and mass accumulation within the tissue layer. Our findings help explain why d18O-SST sensitivities for Porites range from -0.08 per mil/°C to -0.22 per mil/°C and are always less than the value of -0.23 per mil/°C established for biogenic aragonite. Based on this observation, we recalibrated the coral Sr/Ca thermometer to determine a revised sensitivity of -0.084 mmol/mol/°C. After rescaling, most of the published Sr/Ca-SST estimates for the Indo-Pacific region for the last ~14,000 years (-7°C to +2°C relative to modern) fall within the 95% confidence envelope of the foraminiferal Mg/Ca-SST records. We conclude that two types of calibration scales are required for coral paleothermometry; an attenuated Porites-specific thermometer sensitivity for studies of seasonal to interannual change in SST and, importantly, the rescaled -0.084 mmol/mol/°C Sr/Ca sensitivity for studies of 20th-century trends and millennial-scale changes in mean SST. The calibration-scaling concept will apply to the development of transfer functions for all geochemical tracers in corals.
Resumo:
Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.
Resumo:
Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.
Resumo:
Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.
Resumo:
Permanent displacements of a gas turbine founded on a fine, poorly graded, and medium density sand are studied. The amplitudes and modes of vibration are computed using Barkan´s formulation, and the “High-Cycle Accumulation” (HCA) model is employed to account for accumulated deformations due to the high number of cycles. The methodology is simple: it can be easily incorporated into standard mathematical software, and HCA model parameters can be estimated based on granulometry and index properties. Special attention is devoted to ‘transient’ situations at equipment´s start-up, during which a range of frequencies – including frequencies that could be similar to the natural frequencies of the ground – is traversed. Results show that such transient situations could be more restrictive than stationary situations corresponding to normal operation. Therefore, checking the stationary situation only might not be enough, and studying the influence of transient situations on computed permanent displacements is needed to produce a proper foundation design
Resumo:
Although tree ferns are an important component of temperate and tropical forests, very little is known about their ecology. Their peculiar biology (e.g., dispersal by spores and two-phase life cycle) makes it difficult to extrapolate current knowledge on the ecology of other tree species to tree ferns. In this paper, we studied the effects of negative density dependence (NDD) and environmental heterogeneity on populations of two abundant tree fern species, Cyathea caracasana and Alsophila engelii, and how these effects change across a successional gradient. Species patterns harbor information on processes such as competition that can be easily revealed using point pattern analysis techniques. However, its detection may be difficult due to the confounded effects of habitat heterogeneity. Here, we mapped three forest plots along a successional gradient in the montane forests of Southern Ecuador. We employed homogeneous and inhomogeneous K and pair correlation functions to quantify the change in the spatial pattern of different size classes and a case-control design to study associations between juvenile and adult tree ferns. Using spatial estimates of the biomass of four functional tree types (short- and long-lived pioneer, shade- and partial shade-tolerant) as covariates, we fitted heterogeneous Poisson models to the point pattern of juvenile and adult tree ferns and explored the existence of habitat dependencies on these patterns. Our study revealed NDD effects for C. caracasana and strong environmental filtering underlying the pattern of A. engelii. We found that adult and juvenile populations of both species responded differently to habitat heterogeneity and in most cases this heterogeneity was associated with the spatial distribution of biomass of the four functional tree types. These findings show the effectiveness of factoring out environmental heterogeneity to avoid confounding factors when studying NDD and demonstrate the usefulness of covariate maps derived from mapped communities.
Resumo:
Mapping aboveground carbon density in tropical forests can support CO2 emissionmonitoring and provide benefits for national resource management. Although LiDAR technology has been shown to be useful for assessing carbon density patterns, the accuracy and generality of calibrations of LiDAR-based aboveground carbon density (ACD) predictions with those obtained from field inventory techniques should be intensified in order to advance tropical forest carbon mapping. Here we present results from the application of a general ACD estimation model applied with small-footprint LiDAR data and field-based estimates of a 50-ha forest plot in Ecuador?s Yasuní National Park. Subplots used for calibration and validation of the general LiDAR equation were selected based on analysis of topographic position and spatial distribution of aboveground carbon stocks. The results showed that stratification of plot locations based on topography can improve the calibration and application of ACD estimation using airborne LiDAR (R2 = 0.94, RMSE = 5.81 Mg?C? ha?1, BIAS = 0.59). These results strongly suggest that a general LiDAR-based approach can be used for mapping aboveground carbon stocks in western lowland Amazonian forests.
Resumo:
The primary electron donor in bacterial reaction centers is a dimer of bacteriochlorophyll a molecules, labeled L or M based on their proximity to the symmetry-related protein subunits. The electronic structure of the bacteriochlorophyll dimer was probed by introducing small systematic variations in the bacteriochlorophyll–protein interactions by a series of site-directed mutations that replaced residue Leu M160 with histidine, tyrosine, glutamic acid, glutamine, aspartic acid, asparagine, lysine, and serine. The midpoint potentials for oxidation of the dimer in the mutants showed an almost continuous increase up to ≈60 mV compared with wild type. The spin density distribution of the unpaired electron in the cation radical state of the dimer was determined by electron–nuclear–nuclear triple resonance spectroscopy in solution. The ratio of the spin density on the L side of the dimer to the M side varied from ≈2:1 to ≈5:1 in the mutants compared with ≈2:1 for wild type. The correlation between the midpoint potential and spin density distribution was described using a simple molecular orbital model, in which the major effect of the mutations is assumed to be a change in the energy of the M half of the dimer, providing estimates for the coupling and energy levels of the orbitals in the dimer. These results demonstrate that the midpoint potential can be fine-tuned by electrostatic interactions with amino acids near the dimer and show that the properties of the electronic structure of a donor or acceptor in a protein complex can be directly related to functional properties such as the oxidation–reduction midpoint potential.