Accounting for the effects of biological variability and temporal autocorrelation in assessing the preservation of species abundance

Paleobiology ◽  
2011 ◽  
Vol 37 (2) ◽  
pp. 332-354 ◽  
Author(s):  
Adam Tomaŝových ◽  
Susan M. Kidwell
Keyword(s):  
Species Abundance ◽  
Large Degree ◽  
Interspecific Variation ◽  
Compositional Variation ◽  
Time Averaging ◽  
Data Sets ◽  
Biological Variability ◽  
Temporal Autocorrelation ◽  
Population Turnover ◽  
Short Period

Quantifying the effects of taphonomic processes on species abundances in time-averaged death assemblages (DAs) is pivotal for paleoecological inference. However, fidelity estimates based on conventional “live-dead” comparisons are fundamentally ambiguous: (1) data on living assemblages (LAs) are based on a very short period of sampling and thus do not account for biological variability in the LA, (2) LAs are sampled at the same time as the DA and thus do not necessarily reflect past LAs that contributed to the DA, (3) compositions of LAs and DAs can be autocorrelated owing to shared cohorts, and (4) fidelity estimates are cross-scale estimates because DAs are time-averaged and LAs are not. Some portion of raw (total) live-dead (LD) variation in species composition thus arises from incomplete sampling of LAs and from biological temporal variation among LAs (together = premortem component of LD variation), as contrasted withnewvariation created by interspecific variation in population turnover and preservation rates and by the time-averaging of skeletal input (together = postmortem component of LD variation). To tackle these problems, we introduce a modified test for homogeneity of multivariate dispersions (HMD) in order to (1) account for temporal autocorrelation in composition between LAs and DAs and (2) decompose total LD compositional variation into premortem and postmortem components, and we use simulations to evaluate the contribution of within-habitat time-averaging on the postmortem component. Applying this approach to 31 marine molluscan data sets, each consisting of spatial replicates of LAs and DAs in a single habitat, we find that total LD variation is driven largely by variation among LAs. However, genuinely postmortem processes have significant effects on composition in 25–65% of data sets (depending on the metric) when the effects of temporal autocorrelation are taken into account using HMD. Had we ignored the effects of autocorrelation, the effects of postmortem processes would have been negligible, inflating the similarity between LAs and DAs. Simulations show that within-habitat time-averaging does not increase total LD variation to a large degree—it increases total LD variation mainly via increasing species richness, and decreases total LD variation by reducing dispersion among DAs. The postmortem component of LD variation thus arises from differential turnover and preservation and multi-habitat time-averaging. Moreover, postmortem processes have less effect on the compositions of DAs in habitats characterized by high variability among LAs than they have on DAs in temporally stable habitats, a previously unrecognized first-order factor in estimating postmortem sources of compositional variation in DAs.

Preservation of spatial and environmental gradients by death assemblages

Paleobiology ◽  
2009 ◽  
Vol 35 (1) ◽  
pp. 119-145 ◽  
Author(s):  
Adam Tomašových ◽  
Susan M. Kidwell
Keyword(s):  
Community Structure ◽  
Community Composition ◽  
Environmental Gradients ◽  
Compositional Variation ◽  
Time Averaging ◽  
Data Sets ◽  
Square Root ◽  
Spatial Gradients ◽  
Death Assemblages ◽  
The Impact

Although only a few studies have explicitly evaluated live-dead agreement of species and community responses to environmental and spatial gradients, paleoecological analyses implicitly assume that death assemblages capture these gradients accurately. We use nine data sets from modern, relatively undisturbed coastal study areas to evaluate how the response of living molluscan assemblages to environmental gradients (water depth and seafloor type; “environmental component” of a gradient) and geographic separation (“spatial component”) is captured by their death assemblages. We find that:1. Living assemblages vary in composition either in response to environmental gradients alone (consistent with a species-sorting model) or in response to a combination of environmental and spatial gradients (mass-effect model). None of the living assemblages support the neutral model (or the patch-dynamic model), in which variation in species abundance is related to the spatial configuration of stations alone. These findings also support assumptions that mollusk species consistently differ in responses to environmental gradients, and suggest that in the absence of postmortem bias, environmental gradients might be accurately captured by variation in species composition among death assemblages. Death assemblages do in fact respond uniquely to environmental gradients, and show a stronger response when abundances are square-root transformed to downplay the impact of numerically abundant species and increase the effect of rare species.2. Species' niche positions (position of maximum abundance) along bathymetric and sedimentary gradients in death assemblages show significantly positive rank correlations to species positions in living assemblages in seven of nine data sets (both square-root-transformed and presence-absence data).3. The proportion of compositional variation explained by environmental gradients in death assemblages is similar to that of counterpart living assemblages. Death assemblages thus show the same ability to capture environmental gradients as do living assemblages. In some instances compositional dissimilarities in death assemblages show higher rank correlation with spatial distances than with environmental gradients, but spatial structure in community composition is mainly driven by spatially structured environmental gradients.4. Death assemblages correctly identify the dominance of niche metacommunity models in mollusk communities, as revealed by counterpart living assemblages. This analysis of the environmental resolution of death assemblages thus supports fine-scale niche and paleoenvironmental analyses using molluscan fossil records. In spite of taphonomic processes and time-averaging effects that modify community composition, death assemblages largely capture the response of living communities to environmental gradients, partly because of redundancy in community structure that is inherently associated with multispecies assemblages. The molluscan data sets show some degree of redundancy as evidenced by the presence of at least two mutually exclusive subsets of species that replicate the community structure, and simple simulations show that between-sample relationships can be preserved and remain significant even when a large proportion of species is randomly removed from data sets.

scholarly journals Activity of Specialized Biomolecules against Gram-Positive and Gram-Negative Bacteria

Antibiotics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 314 ◽  
Author(s):  
Tânia D. Tavares ◽  
Joana C. Antunes ◽  
Jorge Padrão ◽  
Ana I. Ribeiro ◽  
Andrea Zille ◽  
...  
Keyword(s):  
Cell Morphology ◽  
Time Averaging ◽  
Gram Negative Bacteria ◽  
Gram Positive ◽  
Intracellular Space ◽  
Gram Negative ◽  
Tea Tree ◽  
Minimal Inhibitory Concentrations ◽  
Agar Diffusion Test ◽  
Short Period

The increased resistance of bacteria against conventional pharmaceutical solutions, the antibiotics, has raised serious health concerns. This has stimulated interest in the development of bio-based therapeutics with limited resistance, namely, essential oils (EOs) or antimicrobial peptides (AMPs). This study envisaged the evaluation of the antimicrobial efficacy of selected biomolecules, namely LL37, pexiganan, tea tree oil (TTO), cinnamon leaf oil (CLO) and niaouli oil (NO), against four bacteria commonly associated to nosocomial infections: Staphylococcus aureus, Staphylococcus epidermidis, Escherichia coli and Pseudomonas aeruginosa. The antibiotic vancomycin and silver nanoparticles (AgNPs) were used as control compounds for comparison purposes. The biomolecules were initially screened for their antibacterial efficacy using the agar-diffusion test, followed by the determination of minimal inhibitory concentrations (MICs), kill-time kinetics and the evaluation of the cell morphology upon 24 h exposure. All agents were effective against the selected bacteria. Interestingly, the AgNPs required a higher concentration (4000–1250 μg/mL) to induce the same effects as the AMPs (500–7.8 μg/mL) or EOs (365.2–19.7 μg/mL). Pexiganan and CLO were the most effective biomolecules, requiring lower concentrations to kill both Gram-positive and Gram-negative bacteria (62.5–7.8 μg/mL and 39.3–19.7 μg/mL, respectively), within a short period of time (averaging 2 h 15 min for all bacteria). Most biomolecules apparently disrupted the bacteria membrane stability due to the observed cell morphology deformation and by effecting on the intracellular space. AMPs were observed to induce morphological deformations and cellular content release, while EOs were seen to split and completely envelope bacteria. Data unraveled more of the potential of these new biomolecules as replacements for the conventional antibiotics and allowed us to take a step forward in the understanding of their mechanisms of action against infection-related bacteria.

scholarly journals Short-Period Oscillations of Earth Rotation

2000 ◽  
Vol 178 ◽  
pp. 533-544 ◽  
Author(s):  
B. Kołaczek ◽  
W. Kosek ◽  
H. Schuh
Keyword(s):  
Seasonal Variations ◽  
Earth Rotation ◽  
Polar Motion ◽  
Correlation Coefficients ◽  
Data Sets ◽  
Annual Variations ◽  
Geodetic Vlbi ◽  
Atmospheric Excitation ◽  
Short Period ◽  
Seasonal Oscillations

AbstractSub-seasonal variations and especially sub-seasonal oscillations with periods of about 120, 60, 50, 40 days in polar motion and of about 120, 60–90, and 50 days in LOD are presented. Variations of amplitudes of these sub-seasonal oscillations of polar motion are shown. Maxima of these amplitudes are of the order of 2–4 mas. These oscillations are elliptical ones. The correlation coefficients between geodetic and atmospheric excitation functions in this range of the spectrum are variable and have annual variations. Maxima of correlation coefficients are of the order of 0.6–0.8.Modern geodetic VLBI experiments provide very accurate results in polar motion and UT1–UTC with a temporal resolution of 3–7 minutes. Several irregular, quasi-periodic variations were found. In many UT1–UTC data sets, oscillations with periods around 8 hours and between 5 and 7 hours can be seen.

Normalization for Affymetrix GeneChips

2005 ◽  
Vol 44 (03) ◽  
pp. 414-417 ◽  
Author(s):  
M. Neuhäuser ◽  
T. Boes
Keyword(s):  
Biomedical Research ◽  
Computing Time ◽  
Normalization Method ◽  
Point Of View ◽  
Data Sets ◽  
Quantile Normalization ◽  
Biological Variability ◽  
Biological Origin ◽  
Affymetrix Genechips ◽  
Normalization Methods

Summary Objectives: The high density oligonucleotide micro-arrays from Affymetrix (Affymetrix GeneChips) are very popular in biomedical research. They enable to study the expression of thousands of genes simultaneously. In experiments with multiple arrays, normalization techniques are used to reduce the so-called obscuring variation, i.e. the technical variation that is of non-biological origin. Several different normalization methods have been proposed during the last years. Methods: We review published results about the comparison of normalization methods proposed for Affymetrix GeneChips. Results: The quantile normalization seems to perform favorably regarding precision (low variance), accuracy (low bias), and practicability (low computing time). However, according to very recent results [1], this normalization method can have an impact on the biological variability and, therefore, appears to be less than optimal from this point of view. Conclusion: Although the quantile normalization may be recommendable, more investigations based on more data sets are needed so that the different normalization methods can be evaluated on widely differing data.

scholarly journals Validation of a new signal processing scheme for the MST radar at Aberystwyth

2008 ◽  
Vol 26 (11) ◽  
pp. 3253-3268 ◽  
Author(s):  
D. A. Hooper ◽  
J. Nash ◽  
T. Oakley ◽  
M. Turp
Keyword(s):  
Signal Processing ◽  
Measurement Error ◽  
Gravity Wave ◽  
Wave Activity ◽  
Horizontal Wind ◽  
Time Averaging ◽  
Random Measurement Error ◽  
Processing Scheme ◽  
Random Measurement ◽  
Short Period

Abstract. This paper describes a new signal processing scheme for the 46.5 MHz Doppler Beam Swinging wind-profiling radar at Aberystwyth, in the UK. Although the techniques used are similar to those already described in literature – i.e. the identification of multiple signal components within each spectrum and the use of radial- and time-continuity algorithms for quality-control purposes – it is shown that they must be adapted for the specific meteorological environment above Aberystwyth. In particular they need to take into account the three primary causes of unwanted signals: ground clutter, interference, and Rayleigh scatter from hydrometeors under stratiform precipitation conditions. Attention is also paid to the fact that short-period gravity-wave activity can lead to an invalidation of the fundamental assumption of the wind field remaining stationary over the temporal and spatial scales encompassed by a cycle of observation. Methods of identifying and accounting for such conditions are described. The random measurement error associated with horizontal wind components is estimated to be 3.0–4.0 m s−1 for single cycle data. This reduces to 2.0–3.0 m s−1 for data averaged over 30 min. The random measurement error associated with vertical wind components is estimated to be 0.2–0.3 m s−1. This cannot be reduced by time-averaging as significant natural variability is expected over intervals of just a few minutes under conditions of short-period gravity-wave activity.

The living, the dead, and the expected dead: variation in life span yields little bias of proportional abundances in bivalve death assemblages

Paleobiology ◽  
2010 ◽  
Vol 36 (4) ◽  
pp. 615-640 ◽  
Author(s):  
Susan M. Kidwell ◽  
Thomas A. Rothfus
Keyword(s):  
Mortality Rate ◽  
Life Span ◽  
Data Sets ◽  
Population Turnover ◽  
Marine Bivalves ◽  
Death Assemblages ◽  
Living Species ◽  
Biological Relationship ◽  
The Difference ◽  
Positive Correlations

All else being equal, species with short life spans are expected to be overrepresented in time-averaged death assemblages relative to their standing abundance in the living community, but the magnitude of the distortion of proportional abundance and assemblage evenness has received little attention. Here, information from 30 data sets on the living and dead abundances of marine bivalves in local habitats is combined with a global compilation of bivalve life spans to determine whether bias from mortality rate can explain observed differences in species proportional abundances. Although bivalve maximum life spans range from one to 75 years in these data sets, indicating annual mortality rates of 0.97 to 0.09, the “life span bias” (LB) of a species–the difference between its proportional abundance expected dead and that observed alive–is consistently small in magnitude (average change <2%, maximum about 20%) and random in sign relative to observed discordance (OD = difference between that species' proportional abundance observed dead and that observed alive). The aggregate result for 413 living species occurrences is a significantly positive but weak correlation of OD to LB, with only 10% of variation in OD explained. The model performs better among longer-lived species than among shorter-lived species, probably because longer-lived species conform better to the model assumption that species maintain a constant proportional abundance in the living assemblage over time. Among individual data sets, only seven exhibit significant positive correlations between OD and LB. The model also under-predicts the cases where a death assemblage is dominated by a species that is shorter lived than the dominant species in the living assemblage, indicating that some factor(s) other than or in addition to mortality rate is responsible for OD. We can find no evidence of preservational bias linked to life span, for example through body size. This negative outcome reflects a weak biological relationship between life span and living abundance among bivalves in local habitats, contrary to the terrestrial paradigm, and points toward a simpler model of time-averaged death assemblage formation where higher abundances reflect (under-sampled) past populations. Contrary to long-held expectations, variation in population turnover among species is not a major source of taphonomic bias in time-averaged death assemblages among bivalves and perhaps among other marine groups: bias must arise largely from other factors.

Classification of Main Shocks and Aftershocks in the NGA-West2 Database

2014 ◽  
Vol 30 (3) ◽  
pp. 1257-1267 ◽  
Author(s):  
Kathryn E. Wooddell ◽  
Norman A. Abrahamson
Keyword(s):  
Time Window ◽  
Strong Motion ◽  
Data Sets ◽  
Horizontal Distance ◽  
Strong Motion Data ◽  
Motion Data ◽  
Rupture Plane ◽  
Main Shocks ◽  
Short Period ◽  
Surface Projection

Previous studies have found a systematic difference between short-period ground motions from aftershocks and main shocks, but have not used a consistent methodology for classifying earthquakes in strong motion data sets. A method for unambiguously classifying earthquakes in strong motion data sets is developed. The classification is based on the Gardner and Knopoff time window, but with a distance window based on a new distance metric, CRJB, defined as the shortest horizontal distance between the centroid of the surface projection of the potential aftershock rupture plane and the surface projection of the main shock rupture plane. Class 2 earthquakes are earthquakes that have a CRJB distance less than a selected limit and within a time window appropriate for aftershocks. All other earthquakes are classified as Class 1. For maximum CRJB of 0 km and 40 km, 11% and 36% of the earthquakes in the NGA-West2 database are Class 2 events, respectively.

Early patterns of revegetation of artificial earthen mounds in a northern mixed prairie

1992 ◽  
Vol 70 (1) ◽  
pp. 145-150 ◽  
Author(s):  
Charles E. Umbanhowar Jr.
Keyword(s):  
Species Composition ◽  
Key Words ◽  
Species Abundance ◽  
Bare Soil ◽  
Compositional Variation ◽  
Stem Density ◽  
Mixed Prairie ◽  
Outer Perimeter ◽  
Species Abundance Data ◽  
Key Words Colonization

Patches of bare soil are thought to be important to the diversity and structure of North American grasslands. In 1987, 45 7.5-dm diameter artificial earthen mounds were built in low-, mid-, and high-prairie types to experimentally study the effects of mound location on patterns of mound revegetation. Stem densities and species abundance data were recorded every other week during the summers of 1987 and 1988. Few stems were recorded in 1987, and stem density more than quadrupled in 1988, but less than 1 % of all stems were seedlings. Grass stem densities were significantly higher on low-prairie mounds than mid- or high-prairie mounds and were concentrated in the outer perimeter of mounds. Forb stem densities did not vary significantly between prairie types or on-mound position. Mound species composition closely resembled surrounding vegetation, reflecting between and within prairie-type compositional variation. Key words: colonization, disturbance, earthen mounds, northern mixed prairie, patch, revegetation.

Kinematic linkage between minibasin welds and extreme overpressure in the deepwater Gulf of Mexico

2014 ◽  
Vol 2 (1) ◽  
pp. SB69-SB77 ◽  
Author(s):  
Niven Shumaker ◽  
Daniel Haymond ◽  
Joe Martin
Keyword(s):  
Gulf Of Mexico ◽  
Seismic Velocity ◽  
Large Degree ◽  
Data Sets ◽  
Seismic Velocities ◽  
Burial History ◽  
Well Control ◽  
Deep Blue ◽  
Exploration Well ◽  
Primary Section

A geopressure interpretation technique known as the seismic velocity method is a common workflow in which shale compaction functions are characterized at offset control wells, matched to interval seismic velocities, and then used to predictively calculate geopressure away from well control. The seismic velocity method is used to interpret the expected geopressure profile at the Deep Blue subsalt exploration well in Green Canyon 723 in the deep water Gulf of Mexico. The Deep Blue prospect is distinct from other prospects in the play fairway in that the prospective section is overlain by a salt withdrawal minibasin, whereas the offsetting fields are positioned either along the flanks of minibasins or under a thick allochthonous salt canopy. Predrill geopressure interpretations using numerous tomographic imaging velocity data sets shows a large degree of consistency with the magnitude of geopressure encountered in offsetting supra salt and subsalt fields. Results from the Deep Blue 1 exploration well indicate the predrill geopressure interpretation from interval seismic velocities failed to anticipate the extreme degree overpressure encountered in the subsalt section of the well due to poor deep velocity resolution and an “unloaded” compaction signature. The magnitude of overpressure in the primary section is attributed to the emplacement of an unconformable halokinetic sequence over the primary subsalt basin. An interpretive paradigm is described in which the Deep Blue pressure cell is created through two halokinetic episodes: (1) rapid progradation of a salt canopy followed by (2) subsequent salt withdrawal and emplacement of an overlying minibasin. The linkage between halokinetic sequences, burial history, and the development of overpressure can be used to predictively characterize subsalt geopressure environments.

scholarly journals Data reduction for serial crystallography using a robust peak finder

2021 ◽  
Vol 54 (5) ◽  
Author(s):  
Marjan Hadian-Jazi ◽  
Alireza Sadri ◽  
Anton Barty ◽  
Oleksandr Yefanov ◽  
Marina Galchenkova ◽  
...  
Keyword(s):  
Robust Statistics ◽  
Probability Distributions ◽  
Data Sets ◽  
Time Data ◽  
Peak Finding ◽  
Short Period ◽  
Serial Crystallography ◽  
Diffraction Patterns ◽  
Analyse Data ◽  
Real Time Data Processing

A peak-finding algorithm for serial crystallography (SX) data analysis based on the principle of `robust statistics' has been developed. Methods which are statistically robust are generally more insensitive to any departures from model assumptions and are particularly effective when analysing mixtures of probability distributions. For example, these methods enable the discretization of data into a group comprising inliers (i.e. the background noise) and another group comprising outliers (i.e. Bragg peaks). Our robust statistics algorithm has two key advantages, which are demonstrated through testing using multiple SX data sets. First, it is relatively insensitive to the exact value of the input parameters and hence requires minimal optimization. This is critical for the algorithm to be able to run unsupervised, allowing for automated selection or `vetoing' of SX diffraction data. Secondly, the processing of individual diffraction patterns can be easily parallelized. This means that it can analyse data from multiple detector modules simultaneously, making it ideally suited to real-time data processing. These characteristics mean that the robust peak finder (RPF) algorithm will be particularly beneficial for the new class of MHz X-ray free-electron laser sources, which generate large amounts of data in a short period of time.

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