Decomposition in soil and chemical characteristics of pollen

The input to soils made by pollen and its subsequent mineralization has rarely been investigated from a soil microbiological point of view even though the small but significant quantities of C and N in pollen may make an important contribution to nutrient cycling. The relative resistance to decomposition of pollen exines (outer layers) has led to much of the focus of pollen in soil being on its preservation for archaeological and palaeo-ecological purposes. We have examined aspects of the chemical composition and decomposition of pollen from birch (Betula alba) and maize (Zea mays) in soil. The relatively large N contents, small C-to-N ratios and large water-soluble contents of pollen from both species indicated that they would be readily mineralized in soil. When added to soil and incubated at 16 degrees C an amount of C equivalent to 22-26% of the added pollen C was lost as CO2 within 22 days, with the Z. mays pollen decomposing faster. For B. alba pollen, the water-soluble fraction decomposed faster than the whole pollen and the insoluble fraction decomposed more slowly over 22 days. By contrast, there were no significant differences in the decomposition rates of the different fractions from Z. mays pollen. Solid-state C-13 nuclear magnetic resonance (NMR) revealed no gross chemical differences between the pollen of these two species, with strong resonances in the alkyl- and methyl-C region (0-45 p.p.m.) indicative of aliphatic compounds, the O-alkyl-C (60-90 p.p.m.) and the acetal- and ketal-C region (90-110 p.p.m.) indicative of polysaccharides, and the carbonyl-C region indicative of peptides and carboxylic acids. In addition, both pollens gave a small but distinct resonance at 55 p.p.m. attributed to N-alkyl-C. The resonances attributed to polysaccharides were lost completely or substantially reduced after decomposition.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

Wavelets and the generalization of the variogram

The experimental variogram computed in the usual way by the method of moments and the Haar wavelet transform are similar in that they filter data and yield informative summaries that may be interpreted. The variogram filters out constant values; wavelets can filter variation at several spatial scales and thereby provide a richer repertoire for analysis and demand no assumptions other than that of finite variance. This paper compares the two functions, identifying that part of the Haar wavelet transform that gives it its advantages. It goes on to show that the generalized variogram of order k=1, 2, and 3 filters linear, quadratic, and cubic polynomials from the data, respectively, which correspond with more complex wavelets in Daubechies's family. The additional filter coefficients of the latter can reveal features of the data that are not evident in its usual form. Three examples in which data recorded at regular intervals on transects are analyzed illustrate the extended form of the variogram. The apparent periodicity of gilgais in Australia seems to be accentuated as filter coefficients are added, but otherwise the analysis provides no new insight. Analysis of hyerpsectral data with a strong linear trend showed that the wavelet-based variograms filtered it out. Adding filter coefficients in the analysis of the topsoil across the Jurassic scarplands of England changed the upper bound of the variogram; it then resembled the within-class variogram computed by the method of moments. To elucidate these results, we simulated several series of data to represent a random process with values fluctuating about a mean, data with long-range linear trend, data with local trend, and data with stepped transitions. The results suggest that the wavelet variogram can filter out the effects of long-range trend, but not local trend, and of transitions from one class to another, as across boundaries.

Decomposition in soil and chemical characteristics of pollen

The input to soils made by pollen and its subsequent mineralization has rarely been investigated from a soil microbiological point of view even though the small but significant quantities of C and N in pollen may make an important contribution to nutrient cycling. The relative resistance to decomposition of pollen exines (outer layers) has led to much of the focus of pollen in soil being on its preservation for archaeological and palaeo-ecological purposes. We have examined aspects of the chemical composition and decomposition of pollen from birch (Betula alba) and maize (Zea mays) in soil. The relatively large N contents, small C-to-N ratios and large water-soluble contents of pollen from both species indicated that they would be readily mineralized in soil. When added to soil and incubated at 16 degrees C an amount of C equivalent to 22-26% of the added pollen C was lost as CO2 within 22 days, with the Z. mays pollen decomposing faster. For B. alba pollen, the water-soluble fraction decomposed faster than the whole pollen and the insoluble fraction decomposed more slowly over 22 days. By contrast, there were no significant differences in the decomposition rates of the different fractions from Z. mays pollen. Solid-state C-13 nuclear magnetic resonance (NMR) revealed no gross chemical differences between the pollen of these two species, with strong resonances in the alkyl- and methyl-C region (0-45 p.p.m.) indicative of aliphatic compounds, the O-alkyl-C (60-90 p.p.m.) and the acetal- and ketal-C region (90-110 p.p.m.) indicative of polysaccharides, and the carbonyl-C region indicative of peptides and carboxylic acids. In addition, both pollens gave a small but distinct resonance at 55 p.p.m. attributed to N-alkyl-C. The resonances attributed to polysaccharides were lost completely or substantially reduced after decomposition.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

Low molecular weight heparin significantly reduces embolisation after carotid endarterectomy - a randomised controller trial

Objectives The administration of unfractionated heparin (UFH) prior to carotid clamping during carotid endarterectomy (CEA) transiently increases the platelet aggregation response to arachidonic acid (AA) despite the use of aspirin. We hypothesized that this phenomenon might be reduced by using low molecular weight heparin (LMWH) resulting in fewer emboli in the early post-operative period. Methods 183 aspirinated patients undergoing CEA were randomised to 5000 IU UFH (n = 91) or 2500 IU LMWH (dalteparin, n = 92) prior to carotid clamping. End-points were: transcranial Doppler (TCD) measurement of embolisation, effect on bleeding and platelet aggregation to AA and adenosine 5′-diphosphate (ADP). Results Patients randomised to UFH had twice the odds of experiencing a higher number of emboli in the first 3 h after CEA, than those randomised to LMWH (p = 0.04). This was not associated with increased bleeding (mean time from flow restoration to operation end: 23 min (UFH) vs. 24 min (LMWH), p = 0.18). Platelet aggregation to AA increased significantly following heparinisation, but was unaffected by heparin type (p = 0.90). The platelets of patients randomised to LMWH exhibited significantly lower aggregation to ADP compared to UFH (p < 0.0001). Conclusions Intravenous LMWH is associated with a significant reduction in post-operative embolisation without increased bleeding. The higher rate of embolisation seen with UFH may be mediated by increased platelet aggregation to ADP, rather than to AA.

Detecting the node-density artifact in phylogeny reconstruction

The node-density effect is an artifact of phylogeny reconstruction that can cause branch lengths to be underestimated in areas of the tree with fewer taxa. Webster, Payne, and Pagel (2003, Science 301:478) introduced a statistical procedure (the "delta" test) to detect this artifact, and here we report the results of computer simulations that examine the test's performance. In a sample of 50,000 random data sets, we find that the delta test detects the artifact in 94.4% of cases in which it is present. When the artifact is not present (n = 10,000 simulated data sets) the test showed a type I error rate of approximately 1.69%, incorrectly reporting the artifact in 169 data sets. Three measures of tree shape or "balance" failed to predict the size of the node-density effect. This may reflect the relative homogeneity of our randomly generated topologies, but emphasizes that nearly any topology can suffer from the artifact, the effect not being confined only to highly unevenly sampled or otherwise imbalanced trees. The ability to screen phylogenies for the node-density artifact is important for phylogenetic inference and for researchers using phylogenetic trees to infer evolutionary processes, including their use in molecular clock dating. [Delta test; molecular clock; molecular evolution; node-density effect; phylogenetic reconstruction; speciation; simulation.]

The life history legacy of evolutionary body size change in carnivores

We estimate the body sizes of direct ancestors of extant carnivores, and examine selected aspects of life history as a function not only of species' current size, but also of recent changes in size. Carnivore species that have undergone marked recent evolutionary size change show life history characteristics typically associated with species closer to the ancestral body size. Thus, phyletic giants tend to mature earlier and have larger litters of smaller offspring at shorter intervals than do species of the same body size that are not phyletic giants. Phyletic dwarfs, by contrast, have slower life histories than nondwarf species of the same body size. We discuss two possible mechanisms for the legacy of recent size change: lag (in which life history variables cannot evolve as quickly as body size, leading to species having the 'wrong' life history for their body size) and body size optimization (in which life history and hence body size evolve in response to changes in energy availability); at present, we cannot distinguish between these alternatives. Our finding that recent body size changes help explain residual variation around life history allometries shows that a more dynamic view of character change enables comparative studies to make more precise predictions about species traits in the context of their evolutionary background.