Estimating causal networks in biosphere–atmosphere interaction with the PCMCI approach

Local meteorological conditions and biospheric activity are tightly coupled. Understanding these links is an essential prerequisite for predicting the Earth system under climate change conditions. However, many empirical studies on the interaction between the biosphere and the atmosphere are based on correlative approaches that are not able to deduce causal paths, and only very few studies apply causal discovery methods. Here, we use a recently proposed causal graph discovery algorithm, which aims to reconstruct the causal dependency structure underlying a set of time series. We explore the potential of this method to infer temporal dependencies in biosphere-atmosphere interactions. Specifically we address the following questions: How do periodicity and heteroscedasticity influence causal detection rates, i.e. the detection of existing and non-existing links? How consistent are results for noise-contaminated data? Do results exhibit an increased information content that justifies the use of this causal-inference method? We explore the first question using artificial time series with well known dependencies that mimic real-world biosphere-atmosphere interactions. The two remaining questions are addressed jointly in two case studies utilizing observational data. Firstly, we analyse three replicated eddy covariance datasets from a Mediterranean ecosystem at half hourly time resolution allowing us to understand the impact of measurement uncertainties. Secondly, we analyse global NDVI time series (GIMMS 3g) along with gridded climate data to study large-scale climatic drivers of vegetation greenness. Overall, the results confirm the capacity of the causal discovery method to extract time-lagged linear dependencies under realistic settings. The violation of the method's assumptions increases the likelihood to detect false links. Nevertheless, we consistently identify interaction patterns in observational data. Our findings suggest that estimating a directed biosphere-atmosphere network at the ecosystem level can offer novel possibilities to unravel complex multi-directional interactions. Other than classical correlative approaches, our findings are constrained to a few meaningful set of relations which can be powerful insights for the evaluation of terrestrial ecosystem models

A diffusion Monte Carlo algorithm with very small time‐step errors

We propose modifications to the simple diffusion Monte Carlo algorithm that greatly reduce the time‐step error. The improved algorithm has a time‐step error smaller by a factor of 70 to 300 in the energy of Be, Li2 and Ne. For other observables the improvement is yet larger. The effective time step possible with the improved algorithm is typically a factor of a few hundred larger than the time step used in domain Green function Monte Carlo. We also present an optimized 109 parameter trial wave function for Be which, used in combination with our algorithm, yields an exceedingly accurate ground state energy. A simple solution to the population control bias in diffusion Monte Carlo is also discussed

Dispersal Modeling of Fish Early Life Stages: Sensitivity with Application to Atlantic Cod in the Western Gulf of Maine

As an initial step in establishing mechanistic relationships between environmental variability and recruitment in Atlantic cod Gadhus morhua along the coast of the western Gulf of Maine, we assessed transport success of larvae from major spawning grounds to nursery areas with particle tracking using the unstructured grid model FVCOM (finite volume coastal ocean model). In coastal areas, dispersal of early planktonic life stages of fish and invertebrate species is highly dependent on the regional dynamics and its variability, which has to be captured by our models. With state-of-the-art forcing for the year 1995, we evaluate the sensitivity of particle dispersal to the timing and location of spawning, the spatial and temporal resolution of the model, and the vertical mixing scheme. A 3 d frequency for the release of particles is necessary to capture the effect of the circulation variability into an averaged dispersal pattern of the spawning season. The analysis of sensitivity to model setup showed that a higher resolution mesh, tidal forcing, and current variability do not change the general pattern of connectivity, but do tend to increase within-site retention. Our results indicate strong downstream connectivity among spawning grounds and higher chances for successful transport from spawning areas closer to the coast. The model run for January egg release indicates 1 to 19 % within-spawning ground retention of initial particles, which may be sufficient to sustain local populations. A systematic sensitivity analysis still needs to be conducted to determine the minimum mesh and forcing resolution that adequately resolves the complex dynamics of the western Gulf of Maine. Other sources of variability, i.e. large-scale upstream forcing and the biological environment, also need to be considered in future studies of the interannual variability in transport and survival of the early life stages of cod

Cleavage of E-Cadherin Contributes to Defective Barrier Function in Neosquamous Epithelium

After ablation of Barrett’s esophagus (BE), the esophagus heals with neosquamous epithelium (NSE). Despite normal endoscopic appearance, NSE exhibits defective barrier function with similarities to defects noted in the distal esophageal epithelium in patients with gas-troesophageal reflux disease (GERD)

Initial Hubble Diagram Results from the Nearby Supernova Factory

The use of Type Ia supernovae as distance indicators led to the discovery of the accelerating expansion of the universe a decade ago. Now that large second generation surveys have significantly increased the size and quality of the high-redshift sample, the cosmological constraints are limited by the currently available sample of ~50 cosmologically useful nearby supernovae. The Nearby Supernova Factory addresses this problem by discovering nearby supernovae and observing their spectrophotometric time development. Our data sample includes over 2400 spectra from spectral timeseries of 185 supernovae. This talk presents results from a portion of this sample including a Hubble diagram (relative distance vs. redshift) and a description of some analyses using this rich dataset.Comment: Short version of proceedings for ICHEP08, Philadelphia PA, July 2008; see v1 for full-length versio

Commensurate and Incommensurate Vortex States in Superconductors with Periodic Pinning Arrays

As a function of applied field, we find a rich variety of ordered and partially-ordered vortex lattice configurations in systems with square or triangular arrays of pinning sites. We present formulas that predict the matching fields at which commensurate vortex configurations occur and the vortex lattice orientation with respect to the pinning lattice. Our results are in excellent agreement with recent imaging experiments on square pinning arrays [K. Harada et al., Science 274, 1167 (1996)].Comment: 9 pages, 3 figures. Accepted to Physical Review

Standardizing Type Ia Supernova Absolute Magnitudes Using Gaussian Process Data Regression

We present a novel class of models for Type Ia supernova time-evolving spectral energy distributions (SED) and absolute magnitudes: they are each modeled as stochastic functions described by Gaussian processes. The values of the SED and absolute magnitudes are defined through well-defined regression prescriptions, so that data directly inform the models. As a proof of concept, we implement a model for synthetic photometry built from the spectrophotometric time series from the Nearby Supernova Factory. Absolute magnitudes at peak $B$ brightness are calibrated to 0.13 mag in the $g$-band and to as low as 0.09 mag in the $z=0.25$ blueshifted $i$-band, where the dispersion includes contributions from measurement uncertainties and peculiar velocities. The methodology can be applied to spectrophotometric time series of supernovae that span a range of redshifts to simultaneously standardize supernovae together with fitting cosmological parameters.Comment: 47 pages, 15 figures, accepted for publication by Astrophysical Journa