A ubiquitous ∼62-Myr periodic fluctuation superimposed on general trends in fossil biodiversity. II. Evolutionary dynamics associated with periodic fluctuation in marine diversity

Inertial mass is detected on Earth only when matter is accelerated or decelerated. Recently evidence has been reported for a low-level velocity oscillation with a period of 39 ± 1 Mpc (127 ± 3 Myr) superimposed on the Hubble flow. Like the Hubble flow, this oscillation is assumed to be an expansion and contraction of space itself. If space is oscillating as it expands and the Hubble flow contains a superimposed velocity ripple, matter on Earth will experience alternating accelerations and decelerations relative to the rest of the matter in the Universe. The acceleration curve can be obtained from the velocity oscillation curve simply by taking the magnitude of the derivative of the velocity curve and the acceleration curve is found here to have a period of 63.5 ± 1.5 Myr. Evidence has also been claimed recently for a ubiquitous ~62 ± 3 Myr periodic fluctuation superimposed on general trends in the fossil biodiversity on Earth. The periods of the acceleration curve oscillation and fossil biodiversity fluctuations are thus identical within the errors. A second, weaker fluctuation is also detected in both the Hubble flow and fossil biodiversity trends. They too have identical periods of ~140 Myr. From this excellent agreement, it is argued here that it is the oscillation in the Hubble flow, through an inertia-like phenomenon involving all the matter in the universe that has produced the fluctuations in the fossil biodiversity on Earth. This may represent the first instance where observational evidence supporting Mach’s Principle of Inertia has been found.

We use Fourier analysis and related techniques to investigate the question of periodicities in fossil biodiversity. These techniques are able to identify cycles superimposed on the long-term trends of the Phanerozoic. We review prior results and analyze data previously reduced and published. Joint time-series analysis of various reductions of the Sepkoski Data, Paleobiology Database, and Fossil Record 2 indicate the same periodicity in biodiversity of marine animals at 62 Myr. We have not found this periodicity in the terrestrial fossil record. We have found that the signal strength decreases with time because of the accumulation of apparently “resistant” long-lived genera. The existence of a 62-Myr periodicity despite very different treatment of systematic error, particularly sampling-strength biases, in all three major databases strongly argues for its reality in the fossil record.

A comprehensive study on spectral analysis and anomaly detection of river water quality dynamics with high time resolution measurements

Quasispecies theory provides the conceptual and theoretical bases for describing the dynamics of biological information of replicators subject to large mutation rates. This theory, initially conceived within the framework of prebiotic evolution, is also being used to investigate the evolutionary dynamics of RNA viruses and heterogeneous cancer cells populations. In this sense, efforts to extend the initial quasispecies theory to more realistic scenarios have been made in recent decades. Despite this, how time lags in RNA synthesis and periodic fluctuations impact quasispecies dynamics remains poorly studied. In this article, we combine the theory of delayed ordinary differential equations and topological Leray-Schauder degree to investigate the classical quasispecies model in the single-peak fitness landscape considering time lags and periodic fluctuations in replication. First, we prove that the dynamics with time lags under the constant population constraint remains in the simplex in both forward and backward times. With backward mutation and periodic fluctuations, we prove the existence of periodic orbits regardless of time lags. Nevertheless, without backward mutation, neither periodic fluctuations nor the introduction of time lags leads to periodic orbits. However, in the case of periodic fluctuations, solutions converge exponentially to a periodic oscillation around the equilibria associated with a constant replication rate. We check the validity of the error catastrophe hypothesis assuming no backward mutation; we determine that the error threshold remains sound for the case of time of periodic fitness and time lags with constant fitness. Finally, our results show that the error threshold is not found with backward mutations.

Energetics in the global marinefauna: A connection between terrestrial diversification and change in the marine biosphere

Droplet generation in a T-shape microchannel, with a main channel width of 50 $$\upmu \hbox {m}$$ , side channel width of 25 $$\upmu \hbox {m}$$ , and height of 50 $$\upmu \hbox {m}$$ , is simulated to study the effects of the forced fluctuation of the bottom wall. The periodic fluctuations of the bottom wall are applied on the near junction part of the main channel in the T-shape microchannel. Effects of bottom wall’s shape, fluctuation periods, and amplitudes on the droplet generation are covered in the research of this protocol. In the simulation, the average size is affected a little by the fluctuations, but significantly by the fixed shape of the deformed bottom wall, while the droplet size range is expanded by the fluctuations under most of the conditions. Droplet sizes are distributed in a periodic pattern with small amplitude along the relative time when the fluctuation is forced on the bottom wall near the T-junction, while the droplet emerging frequency is not varied by the fluctuation. The droplet velocity is varied by the bottom wall motion, especially under the shorter period and the larger amplitude. When the fluctuation period is similar to the droplet emerging period, the droplet size is as stable as the non-fluctuation case after a development stage at the beginning of flow, while the droplet velocity is varied by the moving wall with the scope up to 80% of the average velocity under the conditions of this investigation.

Long-term time-series of bluefin tuna catches from ancestral Mediterranean and Atlantic trap fisheries are presented and analysed. The trap is a passive gear, little modified for centuries, that catches bluefin tuna Thunnus thynnus during their annual spawning migration. These features, together with preliminary analyses, lead us to suggest that long-term fluctuations in trap catches could reflect those in true abundance if they vary in the same manner all around the western Mediterranean and adjacent Atlantic. To test this hypothesis, we investigated 54 time-series more than 20 years long (the longest ones spanning four centuries) of trap catches along the western Mediterranean coasts of Italy, Sicily, Sardinia, Tunisia, Spain, and Morocco, and the adjacent Atlantic coasts of Spain, Portugal, and Morocco. Trends and cycles were identified using Eigen Vector Filtering and spectral analysis, and the synchrony between short- and long-term fluctuations in trap catches was studied with the modified correlogram of Koenig and Knops. The magnitude of fluctuations in trap catches is large, periods of great abundance being up to seven times bigger than those when abundance was low. More interesting was the occurrence of 100-year-long periodic fluctuations as well as 20-year cycles. These medium- to long-term fluctuations, representing more than 50% of the total variability in the time-series, were synchronous all around the western Mediterranean and adjacent North Atlantic. In contrast, short-term variability was synchronous at a local scale only. It is argued that long-term fluctuations in trap catches could be considered as a proxy for those of true abundance, and a synthetic time-series has been computed to depict them. Biological and ecological processes that could cause such long-term fluctuations are also discussed.

Autocorrelation in recruitment success of fish is frequently reported, but the underlying mechanisms are generally only vaguely alluded to. We analysed recruitment success of 21 cod (Gadus morhua) stocks in the North Atlantic to investigate possible common causes of autocorrelation in recruitment. We found autocorrelation and periodic fluctuations in recruitment success and adult growth in just above half of the stocks considered and investigated six possible underlying mechanisms. With three exceptions, the variations in recruitment success were not significantly related to temperature or growth anomalies, indicating that the variation was not caused by temperature-dependent survival or growth-dependent spawning products. Further, a link between recruitment and subsequent spawning biomass could not explain the observed recruitment patterns. Slow-growing cod stocks tended to exhibit longer cycles and positive autocorrelations consistent with dilution of predation mortality by adjacent large year classes or age reading errors, whereas fast-growing cod stocks showed shorter cycles and no significant autocorrelation at lag 1. Both types exhibited significant negative autocorrelations consistent with cannibalism at one or more lags greater than lag 1.

Flow pattern identification for internally threaded tubes based on pressure drop fluctuations

From an analysis of more than three years of calibration data we derived a new calibration data for the ``small` calorimeter. Using this calibration we should be able to measure the thermal output power of unknown radiological sample to better than 0.3% of the true value (based on one standard deviation) when the unknown lies in the power range 0.25 - 4.0 watt. We learned that the calibration data taken before August 1987 showed considerably more variability than data collected subsequently. We also detected a long-term periodic fluctuation in the data on the scale of about one year. The cause of this fluctuation is unknown. This fluctuation does significantly reduce the accuracy of our measurements. The accuracy of the calorimeter is degraded by the random error of the entire measurment system, the periodic fluctuation, and the statistical error in estimating the calibration coefficients. We recommend that the cause of the periodic fluctuation be determined by monitoring the environmental conditions of the calorimeter laboratory, and a continuous program of recalibration to assure continued accuracy of these measurements.

A simple nonlinear structural model of endogenous belief heterogeneity is proposed. News about fundamentals is an IID random process, but nevertheless volatility clustering occurs as an endogenous phenomenon caused by the interaction between different types of traders, fundamentalists and technical analysts. The belief types are driven by adaptive, evolutionary dynamics according to the success of the prediction strategies as measured by accumulated realized profits, conditioned upon price deviations from the rational expectations fundamental price. Asset prices switch irregularly between two different regimes — periods of small price fluctuations and periods of large price changes triggered by random news and reinforced by technical trading — thus, creating time varying volatility similar to that observed in real financial data.

A simple nonlinear structural model of endogenous belief heterogeneity is proposed. News about fundamentals is an IID random process, but nevertheless volatility clustering occurs as an endogenous phenomenon caused by the interaction between different types of traders, fundamentalists and technical analysts. The belief types are driven by adaptive, evolutionary dynamics according to the success of the prediction strategies as measured by accumulated realized profits, conditioned upon price deviations from the rational expectations fundamental price. Asset prices switch irregularly between two different regimes — periods of small price fluctuations and periods of large price changes triggered by random news and reinforced by technical trading — thus, creating time varying volatility similar to that observed in real financial data.

A simple nonlinear structural model of endogenous belief heterogeneity is proposed. News about fundamentals is an IID random process, but nevertheless volatility clustering occurs as an endogenous phenomenon caused by the interaction between different types of traders, fundamentalists and technical analysts. The belief types are driven by adaptive, evolutionary dynamics according to the success of the prediction strategies as measured by accumulated realized profits, conditioned upon price deviations from the rational expectations fundamental price. Asset prices switch irregularly between two different regimes --periods of small price fluctuations and periods of large price changes triggered by random news and reinforced by technical trading -- thus, creating time varying volatility similar to that observed in real financial data.

A pulsar timing system has been operating in the 18-cm band at the Urumqi Astronomical Observatory 25-m telescope since mid-1999. Frequency resolution allowing de-dispersion of the pulsar signals is provided by a filterbank/digitizer system. Observations of 74 pulsars over more than 12 months have resulted in updated pulsar periods and period derivatives, as well as improved positions. Comparison with previous measurements showed that the changes in period and period derivative tend to have the same sign and to be correlated in amplitude. A model based on unseen glitches gives a good explanation of the observed changes, suggesting that long-term fluctuations in period and period derivatives are dominated by glitches. In 2000 July, we detected a glitch of relative amplitude in the Crab pulsar. The post-glitch decay appears similar to other large Crab glitches.

SummaryIt is widely accepted that the fossil record suffers from various sampling biases – diversity signals through time may partly or largely reflect the rock record – and many methods have been devised to deal with this problem. One widely used method, the ‘residual diversity’ method, uses residuals from a modelled relationship between palaeodiversity and sampling (sampling‐driven diversity model) as ‘corrected’ diversity estimates, but the unorthodox way in which these residuals are generated presents serious statistical problems; the response and predictor variables are decoupled through independent sorting, rendering the new bivariate relationship meaningless.Here, we use simple simulations to demonstrate the detrimental consequences of independent sorting, through assessing error rates and biases in regression model coefficients.Regression models based on independently sorted data result in unacceptably high rates of incorrect and systematically, directionally biased estimates, when the true parameter values are known. The large number of recent papers that used the method are likely to have produced misleading results and their implications should be reassessed.We note that the ‘residuals’ approach based on the sampling‐driven diversity model cannot be used to ‘correct’ for sampling bias, and instead advocate the use of phylogenetic multiple regression models that can include various confounding factors, including sampling bias, while simultaneously accounting for statistical non‐independence owing to shared ancestry. Evolutionary dynamics such as speciation are inherently a phylogenetic process, and only an explicitly phylogenetic approach will correctly model this process.