PAST: paleontological statistics software package for education and data analysis version 2.09
01 Jan 2001-
TL;DR: PAST integrates spreadsheet-type data entry with univariate and multivariate statistics, curve fitting, timeseries analysis, data plotting, and simple phylogenetic analysis, making it a complete educational package for courses in quantitative methods.
Abstract: A comprehensive, but simple-to-use software package for executing a range of standard numerical analysis and operations used in quantitative paleontology has been developed. The program, called PAST (PAleontological STatistics), runs on standard Windows computers and is available free of charge. PAST integrates spreadsheet-type data entry with univariate and multivariate statistics, curve fitting, timeseries analysis, data plotting, and simple phylogenetic analysis. Many of the functions are specific to paleontology and ecology, and these functions are not found in standard, more extensive, statistical packages. PAST also includes fourteen case studies (data files and exercises) illustrating use of the program for paleontological problems, making it a complete educational package for courses in quantitative methods.
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1,571 citations
Stockholm University1, Alfred Wegener Institute for Polar and Marine Research2, University of Hamburg3, United States Geological Survey4, University of Florida5, Northern Arizona University6, University of Alaska Fairbanks7, Lawrence Berkeley National Laboratory8, National Park Service9, University of Copenhagen10, Argonne National Laboratory11, Bowdoin College12, Lehigh University13
TL;DR: In this article, the authors presented revised estimates of permafrost organic carbon stocks, including quantitative uncertainty estimates, in the 0-3 m depth range in soils as well as for sediments deeper than 3 m in deltaic deposits of major rivers and in the Yedoma region of Siberia and Alaska.
Abstract: Soils and other unconsolidated deposits in the northern circumpolar permafrost region store large amounts of soil organic carbon (SOC). This SOC is potentially vulnerable to remobilization following soil warming and permafrost thaw, but SOC stock estimates were poorly constrained and quantitative error estimates were lacking. This study presents revised estimates of permafrost SOC stocks, including quantitative uncertainty estimates, in the 0–3 m depth range in soils as well as for sediments deeper than 3 m in deltaic deposits of major rivers and in the Yedoma region of Siberia and Alaska. Revised estimates are based on significantly larger databases compared to previous studies. Despite this there is evidence of significant remaining regional data gaps. Estimates remain particularly poorly constrained for soils in the High Arctic region and physiographic regions with thin sedimentary overburden (mountains, highlands and plateaus) as well as for deposits below 3 m depth in deltas and the Yedoma region. While some components of the revised SOC stocks are similar in magnitude to those previously reported for this region, there are substantial differences in other components, including the fraction of perennially frozen SOC. Upscaled based on regional soil maps, estimated permafrost region SOC stocks are 217 ± 12 and 472 ± 27 Pg for the 0–0.3 and 0–1 m soil depths, respectively (±95% confidence intervals). Storage of SOC in 0–3 m of soils is estimated to 1035 ± 150 Pg. Of this, 34 ± 16 Pg C is stored in poorly developed soils of the High Arctic. Based on generalized calculations, storage of SOC below 3 m of surface soils in deltaic alluvium of major Arctic rivers is estimated as 91 ± 52 Pg. In the Yedoma region, estimated SOC stocks below 3 m depth are 181 ± 54 Pg, of which 74 ± 20 Pg is stored in intact Yedoma (late Pleistocene ice- and organic-rich silty sediments) with the remainder in refrozen thermokarst deposits. Total estimated SOC storage for the permafrost region is ∼1300 Pg with an uncertainty range of ∼1100 to 1500 Pg. Of this, ∼500 Pg is in non-permafrost soils, seasonally thawed in the active layer or in deeper taliks, while ∼800 Pg is perennially frozen. This represents a substantial ∼300 Pg lowering of the estimated perennially frozen SOC stock compared to previous estimates.
1,168 citations
TL;DR: It is shown that a major proportion of bacterial sequences of unrelated healthy individuals is identical, supporting the concept of a core microbiome at health.
Abstract: Background: Most studies examining the commensal human oral microbiome are focused on disease or are limited in methodology. In order to diagnose and treat diseases at an early and reversible stage an indepth definition of health is indispensible. The aim of this study therefore was to define the healthy oral microbiome using recent advances in sequencing technology (454 pyrosequencing). Results: We sampled and sequenced microbiomes from several intraoral niches (dental surfaces, cheek, hard palate, tongue and saliva) in three healthy individuals. Within an individual oral cavity, we found over 3600 unique sequences, over 500 different OTUs or "species-level" phylotypes (sequences that clustered at 3% genetic difference) and 88 - 104 higher taxa (genus or more inclusive taxon). The predominant taxa belonged to Firmicutes (genus Streptococcus, family Veillonellaceae, genus Granulicatella), Proteobacteria (genus Neisseria, Haemophilus), Actinobacteria (genus Corynebacterium, Rothia, Actinomyces), Bacteroidetes (genus Prevotella, Capnocytophaga, Porphyromonas) and Fusobacteria (genus Fusobacterium). Each individual sample harboured on average 266 "species-level" phylotypes (SD 67; range 123 - 326) with cheek samples being the least diverse and the dental samples from approximal surfaces showing the highest diversity. Principal component analysis discriminated the profiles of the samples originating from shedding surfaces (mucosa of tongue, cheek and palate) from the samples that were obtained from solid surfaces (teeth). There was a large overlap in the higher taxa, "species-level" phylotypes and unique sequences among the three microbiomes: 84% of the higher taxa, 75% of the OTUs and 65% of the unique sequences were present in at least two of the three microbiomes. The three individuals shared 1660 of 6315 unique sequences. These 1660 sequences (the "core microbiome") contributed 66% of the reads. The overlapping OTUs contributed to 94% of the reads, while nearly all reads (99.8%) belonged to the shared higher taxa. Conclusions: We obtained the first insight into the diversity and uniqueness of individual oral microbiomes at a resolution of next-generation sequencing. We showed that a major proportion of bacterial sequences of unrelated healthy individuals is identical, supporting the concept of a core microbiome at health.
1,006 citations
TL;DR: The results identify ACE2 as a key regulator of dietary amino acid homeostasis, innate immunity, gut microbial ecology, and transmissible susceptibility to colitis, providing a molecular explanation for how amino acid malnutrition can cause intestinal inflammation and diarrhoea.
Abstract: Malnutrition affects up to one billion people in the world and is a major cause of mortality. In many cases, malnutrition is associated with diarrhoea and intestinal inflammation, further contributing to morbidity and death. The mechanisms by which unbalanced dietary nutrients affect intestinal homeostasis are largely unknown. Here we report that deficiency in murine angiotensin I converting enzyme (peptidyl-dipeptidase A) 2 (Ace2), which encodes a key regulatory enzyme of the renin-angiotensin system (RAS), results in highly increased susceptibility to intestinal inflammation induced by epithelial damage. The RAS is known to be involved in acute lung failure, cardiovascular functions and SARS infections. Mechanistically, ACE2 has a RAS-independent function, regulating intestinal amino acid homeostasis, expression of antimicrobial peptides, and the ecology of the gut microbiome. Transplantation of the altered microbiota from Ace2 mutant mice into germ-free wild-type hosts was able to transmit the increased propensity to develop severe colitis. ACE2-dependent changes in epithelial immunity and the gut microbiota can be directly regulated by the dietary amino acid tryptophan. Our results identify ACE2 as a key regulator of dietary amino acid homeostasis, innate immunity, gut microbial ecology, and transmissible susceptibility to colitis. These results provide a molecular explanation for how amino acid malnutrition can cause intestinal inflammation and diarrhoea.
974 citations
TL;DR: A comprehensive but simple‐to‐use software package called DPS (Data Processing System) has been developed to execute a range of standard numerical analyses and operations used in experimental design, statistics and data mining in entomology.
Abstract: A comprehensive but simple-to-use software package called DPS (Data Processing System) has been developed to execute a range of standard numerical analyses and operations used in experimental design, statistics and data mining. This program runs on standard Windows computers. Many of the functions are specific to entomological and other biological research and are not found in standard statistical software. This paper presents applications of DPS to experimental design, statistical analysis and data mining in entomology.
892 citations
Cites methods from "PAST: paleontological statistics so..."
...One reason for this has been the difficulty in acquiring and using appropriate data analysis software (Hammer et al., 2001)....
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References
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01 Jan 1994
TL;DR: The Diskette v 2.06, 3.5''[1.44M] for IBM PC, PS/2 and compatibles [DOS] Reference Record created on 2004-09-07, modified on 2016-08-08.
Abstract: Note: Includes bibliographical references, 3 appendixes and 2 indexes.- Diskette v 2.06, 3.5''[1.44M] for IBM PC, PS/2 and compatibles [DOS] Reference Record created on 2004-09-07, modified on 2016-08-08
19,881 citations
"PAST: paleontological statistics so..." refers methods in this paper
...The algorithm is based on a leastsquares criterion and singular value decomposition (Press et al. 1992)....
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...Spectral (harmonic) analysis of time series can be performed using the Lomb periodogram algorithm, which is more appropriate than the standard Fast Fourier Transform for paleontological data (which are often unevenly sampled; Press et al. 1992)....
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...Spectral (harmonic) analysis of time series can be performed using the Lomb periodogram algorithm, which is more appropriate than the standard Fast Fourier Transform for paleontological data (which are often unevenly sampled; Press et al. 1992)....
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...the logistic equation y=a/(1+be-cx), using Levenberg-Marquardt nonlinear optimization (Press et al. 1992)....
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...Further, PAST allows fitting of data to the logistic equation y=a/(1+be-cx), using Levenberg-Marquardt nonlinear optimization (Press et al. 1992)....
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Book•
01 Jan 1973
TL;DR: In this article, a thoroughly revised edition presents important methods in the quantitative analysis of geologic data, such as probability, nonparametric statistics, and Fourier analysis, as well as data analysis methods such as the semivariogram and the process of kriging.
Abstract: From the Publisher:
This thoroughly revised edition presents important methods in the quantitative analysis of geologic data. Retains the basic arrangement of the previous edition but expands sections on probability, nonparametric statistics, and Fourier analysis. Contains revised coverage of eigenvalues and eigenvectors, and new coverage of data analysis methods, such as the semivariogram and the process of kriging.
5,956 citations
TL;DR: DCA consistently gives the most interpretable ordination results, but as always the interpretation of results remains a matter of ecological insight and is improved by field experience and by integration of supplementary environmental data for the vegetation sample sites.
Abstract: Studies by ourselves and others (Swan 1970, Austin & Noy-Meir 1972, Beals 1973, Hill 1973, 1974, Austin 1976a, b, Fasham 1977, Gauch Whittaker & Wentwarth 1977, Noy-Meir & Whittaker 1977, Orloci 1978, Gauch, Whittaker & Singer 1979) have found faults with all ordination techniques currently in use, at least when applied to ecological data specifying the occurrences of species in community samples. These faults certainly do not make existing techniques useless; but they mean that results must be interpreted with caution. Even with the best techniques, the underlying structure of the data is often poorly expressed.
3,628 citations
"PAST: paleontological statistics so..." refers methods in this paper
...Finally, the program can also compute correlation matrices and perform contingency-table analysis....
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TL;DR: The temporal distribution of the major extinctions over the past 250 million years has been investigated statistically using various forms of time series analysis and contains 12 extinction events that show a statistically significant periodicity.
Abstract: The temporal distribution of the major extinctions over the past 250 million years has been investigated statistically using various forms of time series analysis. The analyzed record is based on variation in extinction intensity for fossil families of marine vertebrates, invertebrates, and protozoans and contains 12 extinction events. The 12 events show a statistically significant periodicity (P less than 0.01) with a mean interval between events of 26 million years. Two of the events coincide with extinctions that have been previously linked to meteorite impacts (terminal Cretaceous and Late Eocene). Although the causes of the periodicity are unknown, it is possible that they are related to extraterrestrial forces (solar, solar system, or galactic).
800 citations
"PAST: paleontological statistics so..." refers background in this paper
...Applications include detection of Milankovitch cycles in isotopic data (Muller and MacDonald 2000) and searching for periodicities in diversity curves (Raup and Sepkoski 1984)....
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TL;DR: The good fit of this model to data on Phanerozoic familial diversity suggests that many of the large-scale patterns of diversification seen in the marine fossil record of animal families are simple consequences of nonlinear interrelationships among a small number of parameters that are intrinsic to the evolutionary faunas and are largely (but not completely) invariant through time.
Abstract: A three-phase kinetic model with time-specific perturbations is used to describe large-scale patterns in the diversification of Phanerozoic marine families. The basic model assumes that the Cambrian, Paleozoic, and Modern evolutionary faunas each diversified logistically as a consequence of early exponential growth and of later slowing of growth as the ecosystems became filled; it also assumes interaction among the evolutionary faunas such that expansion of the combined diversities of all three faunas above any single fauna's equilibrium caused that fauna's diversity to begin to decline. This basic model adequately describes the diversification of the evolutionary faunas through the Paleozoic Era as well as the asymmetrical rise and fall of background extinction rates through the entire Phanerozoic. Declines in diversity and changes in faunal dominance associated with mass extinctions can be accommodated in the model with short-term accelerations in extinction rates or declines in equilibria. Such accelerations, or perturbations, cause diversity to decline exponentially and then to rebound sigmoidally following release. The amount of decline is dependent on the magnitude and duration of the perturbation, the timing of the perturbation with respect to the diversification of the system, and the system's initial per-taxon rates of diversification and turnover. When applied to the three-phase model, such perturbations describe the changes in diversity and faunal dominance during and after major mass extinctions, the long-term rise in total diversity following the Late Permian and Norian mass extinctions, and the peculiar diversification and then decline of the remnants of the Paleozoic fauna during the Mesozoic and Cenozoic Eras. The good fit of this model to data on Phanerozoic familial diversity suggests that many of the large-scale patterns of diversification seen in the marine fossil record of animal families are simple consequences of nonlinear interrelationships among a small number of parameters that are intrinsic to the evolutionary faunas and are largely (but not completely) invariant through time.
687 citations
"PAST: paleontological statistics so..." refers background or methods in this paper
...The logistic equation can model growth with saturation, and it was used by Sepkoski (1984) to describe the proposed stabilization of marine diversity in the late Palaeozoic....
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...Applications include detection of Milankovitch cycles in isotopic data (Muller and MacDonald 2000) and searching for periodicities in diversity curves (Raup and Sepkoski 1984)....
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