The composite-tendency Robert-Asselin-Williams (RAW) filter in semi-implicit integrations

Timediscretization in weatherandclimate modelsintroduces truncation errors that limit the accuracy of the simulations. Recent work has yielded a method for reducing the amplitude errors in leap-frog integrations from first-order to fifth-order.This improvement is achieved by replacing the Robert–Asselin filter with the Robert–Asselin–Williams (RAW) filter and using a linear combination of unfiltered and filtered states to compute the tendency term. The purpose of the present article is to apply the composite-tendency RAW-filtered leapfrog scheme to semi-implicit integrations. A theoretical analysis shows that the stability and accuracy are unaffected by the introduction of the implicitly treated mode. The scheme is tested in semi-implicit numerical integrations in both a simple nonlinear stiff system and a medium-complexity atmospheric general circulation model and yields substantial improvements in both cases. We conclude that the composite-tendency RAW-filtered leap-frog scheme is suitable for use in semi-implicit integrations.

Rooting theories of plant community ecology in microbial interactions

Predominant frameworks for understanding plant ecology have an aboveground bias that neglects soil micro-organisms. This is inconsistent with recent work illustrating the importance of soil microbes in terrestrial ecology. Microbial effects have been incorporated into plant community dynamics using ideas of niche modification and plant–soil community feedbacks. Here, we expand and integrate qualitative conceptual models of plant niche and feedback to explore implications of microbial interactions for understanding plant community ecology. At the same time we review the empirical evidence for these processes. We also consider common mycorrhizal networks, and propose that these are best interpreted within the feedback framework. Finally, we apply our integrated model of niche and feedback to understanding plant coexistence, monodominance and invasion ecology.

Bound Variable, Split Antecedent and Ellipsis Interpretations in L2 Portuguese: Implications for L2 Acquisition Theories.

Recently, in light of minimalist assumptions, some partial UG accessibility accounts to adult second language acquisition have made a distinction between the post-critical period ability to acquire new features based on their LF-interpretability (i.e. interpretable vs. uninterpretable features) (HAWKINS, 2005; HAWKINS; HATTORI, 2006; TSIMPLI; MASTROPAVLOU, 2007; TSIMPLI; DIMITRAKOPOULOU, 2007). The Interpretability Hypothesis (TSIMPLI; MASTROPAVLOU, 2007; TSIMPLI; DIMITRAKOPOULOU, 2007) claims that only uninterpretable features suffer a post-critical period failure and, therefore, cannot be acquired. Conversely, Full Access approaches claim that L2 learners have full access to UG’s entire inventory of features, and that L1/L2 differences obtain outside the narrow syntax. The phenomenon studied herein, adult acquisition of the Overt Pronoun Constraint (OPC) (MONTALBETTI, 1984) and inflected infinitives in nonnative Portuguese, challenges the Interpretability hypothesis insofar as it makes the wrong predictions for what is observed. The present data demonstrate that advanced learners of L2 Portuguese acquire the OPC and the syntax and semantics of inflected infinitives with native-like accuracy. Since inflected infinitives require the acquisition of new uninterpretable φ-features, the present data provide evidence in contra Tsimpli and colleagues’ Interpretability Hypothesis.

What does current generative theory have to say about the explicit-implicit debate?

Taking a generative perspective, we divide aspects of language into three broad categories: those that cannot be learned (are inherent in Universal Grammar), those that are derived from Universal Grammar, and those that must be learned from the input. Using this framework of language to clarify the “what” of learning, we take the acquisition of null (and overt) subjects in languages like Spanish as an example of how to apply the framework. We demonstrate what properties of a null-subject grammar cannot be learned explicitly, which properties can, but also argue that it is an open empirical question as to whether these latter properties are learned using explicit processes, showing how linguistic and psychological approaches may intersect to better understand acquisition.

Evidence from neurolinguistic methodologies: can it actually inform linguistic/ language acquisition theories and translate to evidence-based applications?

This special issue is a testament to the recent burgeoning interest by theoretical linguists, language acquisitionists and teaching practitioners in the neuroscience of language. It offers a highly valuable, state-of-the-art overview of the neurophysiological methods that are currently being applied to questions in the field of second language (L2) acquisition, teaching and processing. Research in the area of neurolinguistics has developed dramatically in the past twenty years, providing a wealth of exciting findings, many of which are discussed in the papers in this volume. The goal of this commentary is twofold. The first is to critically assess the current state of neurolinguistic data from the point of view of language acquisition and processing—informed by the papers that comprise this special issue and the literature as a whole—pondering how the neuroscience of language/processing might inform us with respect to linguistic and language acquisition theories. The second goal is to offer some links from implications of exploring the first goal towards informing language teachers and the creation of linguistically and neurolinguistically-informed evidence-based pedagogies for non-native language teaching.

Implicit equal-weights particle filter

Filter degeneracy is the main obstacle for the implementation of particle filter in non-linear high-dimensional models. A new scheme, the implicit equal-weights particle filter (IEWPF), is introduced. In this scheme samples are drawn implicitly from proposal densities with a different covariance for each particle, such that all particle weights are equal by construction. We test and explore the properties of the new scheme using a 1,000-dimensional simple linear model, and the 1,000-dimensional non-linear Lorenz96 model, and compare the performance of the scheme to a Local Ensemble Kalman Filter. The experiments show that the new scheme can easily be implemented in high-dimensional systems and is never degenerate, with good convergence properties in both systems.