Late cretaceous (Maestrichtian) calcareous nannoplankton biogeography with emphasis on events immediately preceding the cretaceous/paleocene boundary

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 1993.Vita.Includes bibliographical references (leaves 205-218).by Thomas Wolfgang Ehrendorfer.Ph.D

Nuclear and plastid haplotypes suggest rapid diploid and polyploid speciation in the N Hemisphere Achillea millefolium complex (Asteraceae)

<p>Abstract</p> <p>Background</p> <p>Species complexes or aggregates consist of a set of closely related species often of different ploidy levels, whose relationships are difficult to reconstruct. The N Hemisphere <it>Achillea millefolium </it>aggregate exhibits complex morphological and genetic variation and a broad ecological amplitude. To understand its evolutionary history, we study sequence variation at two nuclear genes and three plastid loci across the natural distribution of this species complex and compare the patterns of such variations to the species tree inferred earlier from AFLP data.</p> <p>Results</p> <p>Among the diploid species of <it>A. millefolium </it>agg., gene trees of the two nuclear loci, ncp<it>GS </it>and <it>SBP</it>, and the combined plastid fragments are incongruent with each other and with the AFLP tree likely due to incomplete lineage sorting or secondary introgression. In spite of the large distributional range, no isolation by distance is found. Furthermore, there is evidence for intragenic recombination in the ncp<it>GS </it>gene. An analysis using a probabilistic model for population demographic history indicates large ancestral effective population sizes and short intervals between speciation events. Such a scenario explains the incongruence of the gene trees and species tree we observe. The relationships are particularly complex in the polyploid members of <it>A. millefolium </it>agg.</p> <p>Conclusions</p> <p>The present study indicates that the diploid members of <it>A. millefolium </it>agg. share a large part of their molecular genetic variation. The findings of little lineage sorting and lack of isolation by distance is likely due to short intervals between speciation events and close proximity of ancestral populations. While previous AFLP data provide species trees congruent with earlier morphological classification and phylogeographic considerations, the present sequence data are not suited to recover the relationships of diploid species in <it>A. millefolium </it>agg. For the polyploid taxa many hybrid links and introgression from the diploids are suggested.</p

Allopolyploid speciation and ongoing backcrossing between diploid progenitor and tetraploid progeny lineages in the Achillea millefolium species complex: analyses of single-copy nuclear genes and genomic AFLP

<p>Abstract</p> <p>Background</p> <p>In the flowering plants, many polyploid species complexes display evolutionary radiation. This could be facilitated by gene flow between otherwise separate evolutionary lineages in contact zones. <it>Achillea collina </it>is a widespread tetraploid species within the <it>Achillea millefolium </it>polyploid complex (Asteraceae-Anthemideae). It is morphologically intermediate between the relic diploids, <it>A. setacea</it>-2x in xeric and <it>A. asplenifolia</it>-2x in humid habitats, and often grows in close contact with either of them. By analyzing DNA sequences of two single-copy nuclear genes and the genomic AFLP data, we assess the allopolyploid origin of <it>A. collina</it>-4x from ancestors corresponding to <it>A. setacea</it>-2x and <it>A. asplenifolia</it>-2x, and the ongoing backcross introgression between these diploid progenitor and tetraploid progeny lineages.</p> <p>Results</p> <p>In both the ncp<it>GS </it>and the <it>PgiC </it>gene tree, haplotype sequences of the diploid <it>A. setacea</it>-2x and <it>A. asplenifolia</it>-2x group into two clades corresponding to the two species, though lineage sorting seems incomplete for the <it>PgiC </it>gene. In contrast, <it>A. collina</it>-4x and its suspected backcross plants show homeologous gene copies: sequences from the same tetraploid individual plant are placed in both diploid clades. Semi-congruent splits of an AFLP Neighbor Net link not only <it>A. collina</it>-4x to both diploid species, but some 4x individuals in a polymorphic population with mixed ploidy levels to <it>A. setacea</it>-2x on one hand and to <it>A. collina</it>-4x on the other, indicating allopolyploid speciation as well as hybridization across ploidal levels.</p> <p>Conclusions</p> <p>The findings of this study clearly demonstrate the hybrid origin of <it>Achillea collina</it>-4x, the ongoing backcrossing between the diploid progenitor and their tetraploid progeny lineages. Such repeated hybridizations are likely the cause of the great genetic and phenotypic variation and ecological differentiation of the polyploid taxa in <it>Achillea millefolium </it>agg.</p

Ensemble-based data assimilation and the localisation problem

The “butterfly effect” is a popularly known paradigm; commonly it is said that when a butterfly flaps its wings in Brazil, it may cause a tornado in Texas. This essentially describes how weather forecasts can be extremely senstive to small changes in the given atmospheric data, or initial conditions, used in computer model simulations. In 1961 Edward Lorenz found, when running a weather model, that small changes in the initial conditions given to the model can, over time, lead to entriely different forecasts (Lorenz, 1963). This discovery highlights one of the major challenges in modern weather forecasting; that is to provide the computer model with the most accurately specified initial conditions possible. A process known as data assimilation seeks to minimize the errors in the given initial conditions and was, in 1911, described by Bjerkness as “the ultimate problem in meteorology” (Bjerkness, 1911)

Flow-directed PCA for monitoring networks

Measurements recorded over monitoring networks often possess spatial and temporal correlation inducing redundancies in the information provided. For river water quality monitoring in particular, flow-connected sites may likely provide similar information. This paper proposes a novel approach to principal components analysis to investigate reducing dimensionality for spatiotemporal flow-connected network data in order to identify common spatiotemporal patterns. The method is illustrated using monthly observations of total oxidized nitrogen for the Trent catchment area in England. Common patterns are revealed that are hidden when the river network structure and temporal correlation are not accounted for. Such patterns provide valuable information for the design of future sampling strategies

Data assimilation in a multi-scale model

Data assimilation for multi-scale models is an important contemporary research topic. Especially the role of unresolved scales and model error in data assimilation needs to be systematically addressed. Here we examine these issues using the Ensemble Kalman filter (EnKF) with the two-level Lorenz-96 model as a conceptual prototype model of the multi-scale climate system. We use stochastic parameterization schemes to mitigate the model errors from the unresolved scales. Our results indicate that a third-order autoregressive process performs better than a first-order autoregressive process in the stochastic parameterization schemes, especially for the system with a large time-scale separation.Model errors can also arise from imprecise model parameters. We find that the accuracy of the analysis (an optimal estimate of a model state) is linearly correlated to the forcing error in the Lorenz-96 model. Furthermore, we propose novel observation strategies to deal with the fact that the dimension of the observations is much smaller than the model states. We also propose a new analog method to increase the size of the ensemble when its size is too small

Ensemble prediction for nowcasting with a convection-permitting model - II: forecast error statistics

A 24-member ensemble of 1-h high-resolution forecasts over the Southern United Kingdom is used to study short-range forecast error statistics. The initial conditions are found from perturbations from an ensemble transform Kalman filter. Forecasts from this system are assumed to lie within the bounds of forecast error of an operational forecast system. Although noisy, this system is capable of producing physically reasonable statistics which are analysed and compared to statistics implied from a variational assimilation system. The variances for temperature errors for instance show structures that reflect convective activity. Some variables, notably potential temperature and specific humidity perturbations, have autocorrelation functions that deviate from 3-D isotropy at the convective-scale (horizontal scales less than 10 km). Other variables, notably the velocity potential for horizontal divergence perturbations, maintain 3-D isotropy at all scales. Geostrophic and hydrostatic balances are studied by examining correlations between terms in the divergence and vertical momentum equations respectively. Both balances are found to decay as the horizontal scale decreases. It is estimated that geostrophic balance becomes less important at scales smaller than 75 km, and hydrostatic balance becomes less important at scales smaller than 35 km, although more work is required to validate these findings. The implications of these results for high-resolution data assimilation are discussed

FT Raman and DFT Study on a Series of All- anti Oligothienoacenes End-Capped with Triisopropylsilyl Groups

Herein, we study the Π-conjugational properties of a homologous series of all -anti oligothienoacenes containing four to eight fused thiophene rings by means of FT Raman spectroscopy and DFT calculations. The theoretical analysis of the spectroscopic data provides evidence that selective enhancement of a very limited number of Raman scatterings is related to the occurrence in these oligothienoacenes of strong vibronic coupling between collective Ν(C[bouble bond]C) stretching modes in the 1600–1300 cm −1 region and the HOMO/LUMO frontier orbitals (HOMO=highest occupied molecular orbital; LUMO=lowest unoccupied molecular orbital). The correlation of the Raman spectroscopic data and theoretical results for these all -anti oligothienoacenes with those previously collected for a number of all -syn oligothienohelicenes gives further support to the expectation that cross-conjugation is dominant in heterohelicenes. Fully planar all -anti oligothienoacenes display linear Π conjugation which seemingly does not reach saturation with increasing number of annulated thiophene rings in the oligomeric chain at least up to the octamer.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/64547/1/3069_ftp.pd

Data assimilation in slow-fast systems using homogenized climate models

A deterministic multiscale toy model is studied in which a chaotic fast subsystem triggers rare transitions between slow regimes, akin to weather or climate regimes. Using homogenization techniques, a reduced stochastic parametrization model is derived for the slow dynamics. The reliability of this reduced climate model in reproducing the statistics of the slow dynamics of the full deterministic model for finite values of the time scale separation is numerically established. The statistics however is sensitive to uncertainties in the parameters of the stochastic model. It is investigated whether the stochastic climate model can be beneficial as a forecast model in an ensemble data assimilation setting, in particular in the realistic setting when observations are only available for the slow variables. The main result is that reduced stochastic models can indeed improve the analysis skill, when used as forecast models instead of the perfect full deterministic model. The stochastic climate model is far superior at detecting transitions between regimes. The observation intervals for which skill improvement can be obtained are related to the characteristic time scales involved. The reason why stochastic climate models are capable of producing superior skill in an ensemble setting is due to the finite ensemble size; ensembles obtained from the perfect deterministic forecast model lacks sufficient spread even for moderate ensemble sizes. Stochastic climate models provide a natural way to provide sufficient ensemble spread to detect transitions between regimes. This is corroborated with numerical simulations. The conclusion is that stochastic parametrizations are attractive for data assimilation despite their sensitivity to uncertainties in the parameters.Comment: Accepted for publication in Journal of the Atmospheric Science