Abundance-diversity relationship as a unique signature of temporal scaling in the fossil record.

Species diversity increases with the temporal grain of samples according to the species-time relationship (STR), impacting palaeoecological analyses because the temporal grain (time averaging) of fossil assemblages varies by several orders of magnitude. We predict a positive relation between total abundance and sample size-independent diversity (ADR) in fossil assemblages because an increase in time averaging, determined by a decreasing sediment accumulation, should increase abundance and depress species dominance. We demonstrate that, in contrast to negative ADR of non-averaged living assemblages, the ADR of Holocene fossil assemblages is positive, unconditionally or when conditioned on the energy availability gradient. However, the positive fossil ADR disappears when conditioned on sediment accumulation, demonstrating that ADR is a signature of diversity scaling induced by variable time averaging. Conditioning ADR on sediment accumulation can identify and remove the scaling effect caused by time averaging, providing an avenue for unbiased biodiversity comparisons across space and time.

Ecological regime shift preserved in the Anthropocene stratigraphic record.

Palaeoecological data are unique historical archives that extend back far beyond the last several decades of ecological observations. However, the fossil record of continental shelves has been perceived as too coarse (with centennial-millennial resolution) and incomplete to detect processes occurring at yearly or decadal scales relevant to ecology and conservation. Here, we show that the youngest (Anthropocene) fossil record on the northern Adriatic continental shelf provides decadal-scale resolution that accurately documents an abrupt ecological change affecting benthic communities during the twentieth century. The magnitude and the duration of the twentieth century shift in body size of the bivalve Corbula gibba is unprecedented given that regional populations of this species were dominated by small-size classes throughout the Holocene. The shift coincided with compositional changes in benthic assemblages, driven by an increase from approximately 25% to approximately 70% in median per-assemblage abundance of C. gibba. This regime shift increase occurred preferentially at sites that experienced at least one hypoxic event per decade in the twentieth century. Larger size and higher abundance of C. gibba probably reflect ecological release as it coincides with an increase in the frequency of seasonal hypoxia that triggered mass mortality of competitors and predators. Higher frequency of hypoxic events is coupled with a decline in the depth of intense sediment mixing by burrowing benthic organisms from several decimetres to less than 20 cm, significantly improving the stratigraphic resolution of the Anthropocene fossil record and making it possible to detect sub-centennial ecological changes on continental shelves.

A decline in molluscan carbonate production driven by the loss of vegetated habitats encoded in the Holocene sedimentary record of the Gulf of Trieste.

Carbonate sediments in non-vegetated habitats on the north-east Adriatic shelf are dominated by shells of molluscs. However, the rate of carbonate molluscan production prior to the 20th century eutrophication and overfishing on this and other shelves remains unknown because: (i) monitoring of ecosystems prior to the 20th century was scarce; and (ii) ecosystem history inferred from cores is masked by condensation and mixing. Here, based on geochronological dating of four bivalve species, carbonate production during the Holocene is assessed in the Gulf of Trieste, where algal and seagrass habitats underwent a major decline during the 20th century. Assemblages of sand-dwelling Gouldia minima and opportunistic Corbula gibba are time-averaged to >1000 years and Corbula gibba shells are older by >2000 years than shells of co-occurring Gouldia minima. This age difference is driven by temporally disjunct production of two species coupled with decimetre-scale mixing. Stratigraphic unmixing shows that Corbula gibba declined in abundance during the highstand phase and increased again during the 20th century. In contrast, one of the major contributors to carbonate sands - Gouldia minima - increased in abundance during the highstand phase, but declined to almost zero abundance over the past two centuries. Gouldia minima and herbivorous gastropods associated with macroalgae or seagrasses are abundant in the top-core increments but are rarely alive. Although Gouldia minima is not limited to vegetated habitats, it is abundant in such habitats elsewhere in the Mediterranean Sea. This live-dead mismatch reflects the difference between highstand baseline communities (with soft-bottom vegetated zones and hard-bottom Arca beds) and present-day oligophotic communities with organic-loving species. Therefore, the decline in light penetration and the loss of vegetated habitats with high molluscan production traces back to the 19th century. More than 50% of the shells on the sea floor in the Gulf of Trieste reflect inactive production that was sourced by heterozoan carbonate factory in algal or seagrass habitats.

Multiple helical conformations of the helix-turn-helix region revealed by NOE-restrained MD simulations of tryptophan aporepressor, TrpR.

The nature of flexibility in the helix-turn-helix region of E. coli trp aporepressor has been unexplained for many years. The original ensemble of nuclear magnetic resonance (NMR structures showed apparent disorder, but chemical shift and relaxation measurements indicated a helical region. Nuclear Overhauser effect (NOE) data for a temperature-sensitive mutant showed more helical character in its helix-turn-helix region, but nevertheless also led to an apparently disordered ensemble. However, conventional NMR structure determination methods require all structures in the ensemble to be consistent with every NOE simultaneously. This work uses an alternative approach in which some structures of the ensemble are allowed to violate some NOEs to permit modeling of multiple conformational states that are in dynamic equilibrium. Newly measured NOE data for wild-type aporepressor are used as time-averaged distance restraints in molecular dynamics simulations to generate an ensemble of helical conformations that is more consistent with the observed NMR data than the apparent disorder in the previously reported NMR structures. The results indicate the presence of alternating helical conformations that provide a better explanation for the flexibility of the helix-turn-helix region of trp aporepressor. Structures representing these conformations have been deposited with PDB ID: 5TM0. Proteins 2017; 85:731-740. © 2016 Wiley Periodicals, Inc.

Edited 1 H magnetic resonance spectroscopy in vivo: Methods and metabolites.

The Proton magnetic resonance (1 H-MRS) spectrum contains information about the concentration of tissue metabolites within a predefined region of interest (a voxel). The conventional spectrum in some cases obscures information about less abundant metabolites due to limited separation and complex splitting of the metabolite peaks. One method to detect these metabolites is to reduce the complexity of the spectrum using editing. This review provides an overview of the one-dimensional editing methods available to interrogate these obscured metabolite peaks. These methods include sequence optimizations, echo-time averaging, J-difference editing methods (single BASING, dual BASING, and MEGA-PRESS), constant-time PRESS, and multiple quantum filtering. It then provides an overview of the brain metabolites whose detection can benefit from one or more of these editing approaches, including ascorbic acid, γ-aminobutyric acid, lactate, aspartate, N-acetyl aspartyl glutamate, 2-hydroxyglutarate, glutathione, glutamate, glycine, and serine. Magn Reson Med 77:1377-1389, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

In vivo T(2) relaxation time measurement with echo-time averaging.

The accuracy of metabolite concentrations measured using in vivo proton ((1) H) MRS is enhanced following correction for spin-spin (T2 ) relaxation effects. In addition, metabolite proton T2 relaxation times provide unique information regarding cellular environment and molecular mobility. Echo-time (TE) averaging (1) H MRS involves the collection and averaging of multiple TE steps, which greatly simplifies resulting spectra due to the attenuation of spin-coupled and macromolecule resonances. Given the simplified spectral appearance and inherent metabolite T2 relaxation information, the aim of the present proof-of-concept study was to develop a novel data processing scheme to estimate metabolite T2 relaxation times from TE-averaged (1) H MRS data. Spectral simulations are used to validate the proposed TE-averaging methods for estimating methyl proton T2 relaxation times for N-acetyl aspartate, total creatine, and choline-containing compounds. The utility of the technique and its reproducibility are demonstrated using data obtained in vivo from the posterior-occipital cortex of 10 healthy control subjects. Compared with standard methods, distinct advantages of this approach include built-in macromolecule resonance attenuation, in vivo T2 estimates closer to reported values when maximum TE ≈ T2 , and the potential for T2 calculation of metabolite resonances otherwise inseparable in standard (1) H MRS spectra recorded in vivo.

Measuring glucose concentrations in the rat brain using echo-time-averaged point resolved spectroscopy at 7 tesla.

Glucose has multiple functions in the brain, and there is interest in estimating in vivo concentrations rather than merely the uptake determined by nuclear medicine. Glucose can be estimated using magnetic resonance spectroscopy, but measurement is difficult due to its multiple J-coupled proton signals overlapping with other metabolite signals. To minimize the effect of interfering signals, echo time (TE) values between 60 and 95 ms were averaged, and the loss in signal due to the T2 effect was corrected in both the estimation of glucose concentration and in creation of the basis files for fitting. The effectiveness of the TE-averaging method was evaluated by measuring the glucose concentration in fasted rats before and after feeding. The brain glucose in all rats increased after feeding with fasted and fed glucose-to-creatine ratios of 0.15 ± 0.03 and 0.24 ± 0.04, respectively. Data at a short TE of 13 ms measured ratios of 0.30 ± 0.16 and 0.36 ± 0.24 for the fasted and fed rats, respectively, demonstrating the difficulty in obtaining reliable glucose measurements at short TE. Overall, TE averaging minimizes the influence of macromolecular signals and nearby peaks to give precise, consistent estimates of glucose.

Statistical signals of copying are robust to time- and space-averaging.

Cattle brands (ownership marks left on animals) are subject to forces influencing other graphic codes: the copying of constituent parts, pressure for distinctiveness and pressure for complexity. The historical record of cattle brands in some US states is complete owing to legal registration, providing a unique opportunity to assess how sampling processes leading to time- and space-averaging influence our ability to make inferences from limited datasets in fields like archaeology. In this preregistered study, we used a dataset of ~81,000 Kansas cattle brands (1990-2016) to explore two aspects: (1) the relative influence of copying, pressure for distinctiveness and pressure for complexity on the creation and diffusion of brand components; and (2) the effects of time- and space-averaging on statistical signals. By conducting generative inference with an agent-based model, we found that the patterns in our data are consistent with copying and pressure for intermediate complexity. In addition, by comparing mixed and structured datasets, we found that these statistical signals of copying are robust to, and possibly boosted by, time- and space-averaging.

Low-Frequency NARS (LF NARS) by the use of a superheterodyne EPR spectrometer.

In this article, the possibilities of recording EPR spectra by the non-adiabatic rapid sweep (NARS) method on a superheterodyne spectrometer are investigated. This method allows recording the pure EPR absorption spectrum of the object under investigation without the need for lineshape-lineheight compromise, while increasing sensitivity by suppressing low-frequency noise. In the NARS method, a low-amplitude sinusoidal modulation of a magnetic field is not used, and an oscillating triangular-shaped bipolar magnetic field is superimposed on the main permanent magnetic field. The triangular field repetition rate should be higher than that of the undesirable noise, and the amplitude is such that the rate of field change satisfies the Bloch non-adiabaticity criterion. The EPR absorption signal is digitized by a fast ADC and accumulated over a large number (n) of triangular field periods. In this case, for low-frequency noise, the spectrum of which is located below the repetition frequency of the triangular field, an accumulation process occurs with an increase in the signal-to-noise ratio (SNR) in proportion to n. A remarkable property of a superheterodyne spectrometer is that the frequency below which low-frequency noise prevails over white noise is significantly lower for it than for a homodyne spectrometer. This allows the use of a low repetition rate (LF NARS), which makes it much easier to obtain a highly linear triangular field of significant amplitude even in microwave resonators with a massive metal case since the harmful effects of eddy currents are reduced. The conditions of non-adiabaticity become easily feasible. At the same time, the noise suppression effect during accumulation turns out to be so significant that the SNR of the LFNARS spectrum exceeds that of the traditional spectrum with magnetic field modulation, with the same recording time, by more than 10 times.

Boosting Throughput and Efficiency of Hardware Spiking Neural Accelerators Using Time Compression Supporting Multiple Spike Codes.

Spiking neural networks (SNNs) are the third generation of neural networks and can explore both rate and temporal coding for energy-efficient event-driven computation. However, the decision accuracy of existing SNN designs is contingent upon processing a large number of spikes over a long period. Nevertheless, the switching power of SNN hardware accelerators is proportional to the number of spikes processed while the length of spike trains limits throughput and static power efficiency. This paper presents the first study on developing temporal compression to significantly boost throughput and reduce energy dissipation of digital hardware SNN accelerators while being applicable to multiple spike codes. The proposed compression architectures consist of low-cost input spike compression units, novel input-and-output-weighted spiking neurons, and reconfigurable time constant scaling to support large and flexible time compression ratios. Our compression architectures can be transparently applied to any given pre-designed SNNs employing either rate or temporal codes while incurring minimal modification of the neural models, learning algorithms, and hardware design. Using spiking speech and image recognition datasets, we demonstrate the feasibility of supporting large time compression ratios of up to 16×, delivering up to 15.93×, 13.88×, and 86.21× improvements in throughput, energy dissipation, the tradeoffs between hardware area, runtime, energy, and classification accuracy, respectively based on different spike codes on a Xilinx Zynq-7000 FPGA. These results are achieved while incurring little extra hardware overhead.

Current and potential roles of archaeology in the development of cultural evolutionary theory.

Archaeology has much to contribute to the study of cultural evolution. Empirical data at archaeological timescales are uniquely well suited to tracking rates of cultural change, detecting phylogenetic signals among groups of artefacts, and recognizing long-run effects of distinct cultural transmission mechanisms. Nonetheless, these are still relatively infrequent subjects of archaeological analysis and archaeology's potential to help advance our understanding of cultural evolution has thus far been largely unrealized. Cultural evolutionary models developed in other fields have been used to interpret patterns identified in archaeological records, which in turn provides independent tests of these models' predictions, as demonstrated here through a study of late Prehistoric stone projectile points from the US Southwest. These tests may not be straightforward, though, because archaeological data are complex, often representing events aggregated over many years (or centuries or millennia), while processes thought to drive cultural evolution (e.g. biased learning) operate on much shorter timescales. To fulfil archaeology's potential, we should continue to develop models specifically tailored to archaeological circumstances, and explore ways to incorporate the rich contextual data produced by archaeological research.This article is part of the theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'.

The temporal scale of diet and dietary proxies.

Diets estimated from different proxies such as stable isotopes, stomach contents, and dental microwear often disagree, leading to nominally well-supported but greatly differing estimates of diet for both extinct and extant species that complicate our understanding of ecology. We show that these perceived incongruences can be caused by proxies recording diet over vastly different timescales. Field observations reveal a diet averaged over minutes or hours, whereas dental morphology may reflect the diet of a lineage over millions of years of evolution. Failing to explicitly consider the scale of proxies and the potentially large temporal variability in diet can cause erroneous predictions in any downstream analyses such as conservation planning or paleohabitat reconstructions. We propose a cross-scale framework for conceptualizing diet suitable for both modern ecologists and paleontologists and provide recommendations for any studies involving dietary data. Treating diet in this temporally explicit framework and matching the scale of our questions with the scale of our data will lead to a much richer and clearer understanding of ecological and evolutionary processes.