The Linnaean system and its 250-year persistence

The Linnaean system of nomenclature has been used and adapted by biologists over a period of almost 250 years. Under the current system of codes, it is now applied to more than 2 million species of organisms. Inherent in the Linnaean system is the indication of hierarchical relationships. The Linnaean system has been justified primarily on the basis of stability. Stability can be assessed on at least two grounds: the absolute stability of names, irrespective of taxonomic concept; and the stability of names under changing concepts. Recent arguments have invoked conformity to phylogenetic methods as the primary basis for choice of nomenclatural systems, but even here stability of names as they relate to monophyletic groups is stated as the ultimate objective. The idea of absolute stability as the primary justification for nomenclatural methods was wrong from the start. The reasons are several. First, taxa are concepts, no matter the frequency of assertions to the contrary; as such, they are subject to change at all levels and always will be, with the consequence that to some degree the names we use to refer to them will also be subject to change. Second, even if the true nature of all taxa could be agreed upon, the goal would require that we discover them all and correctly recognize them for what they are. Much of biology is far from that goal at the species level and even further for supraspecific taxa. Nomenclature serves as a tool for biology. Absolute stability of taxonomic concepts—and nomenclature—would hinder scientific progress rather than promote it. It can been demonstrated that the scientific goals of systematists are far from achieved. Thus, the goal of absolute nomenclatural stability is illusory and misguided. The primary strength of the Linnaean system is its ability to portray hierarchical relationships; stability is secondary. No single system of nomenclature can ever possess all desirable attributes: i.e., convey information on hierarchical relationships, provide absolute stability in the names portraying those relationships, and provide simplicity and continuity in communicating the identities of the taxa and their relationships. Aside from myriad practical problems involved in its implementation, it must be concluded that “phylogenetic nomenclature” would not provide a more stable and effective system for communicating information on biological classifications than does the Linnaean system.     

Multi-stream LSTM-HMM decoding and histogram equalization for noise robust keyword spotting

Highly spontaneous, conversational, and potentially emotional and noisy speech is known to be a challenge for today’s automatic speech recognition (ASR) systems, which highlights the need for advanced algorithms that improve speech features and models. Histogram Equalization is an efficient method to reduce the mismatch between clean and noisy conditions by normalizing all moments of the probability distribution of the feature vector components. In this article, we propose to combine histogram equalization and multi-condition training for robust keyword detection in noisy speech. To better cope with conversational speaking styles, we show how contextual information can be effectively exploited in a multi-stream ASR framework that dynamically models context-sensitive phoneme estimates generated by a long short-term memory neural network. The proposed techniques are evaluated on the SEMAINE database—a corpus containing emotionally colored conversations with a cognitive system for “Sensitive Artificial Listening”.     

Can abstractions be causes?

The Empiricist or Lockean view says natural kinds do not exist objectively in nature but are practical categories reflecting use of words. The Modern, Ostensive view says they do exist, and one can refer to such a kind by ostention and recursion, assuming his designation of it is related causally to the kind itself. However, this leads to a problem: Kinds are abstract repeatables, and it seems impossible that abstractions could have causal force. In defence of the Modern view, I suggest we can think of kinds as — or as like — ecological niches existing in nature, which are causally effective by virtue of the fact that they predictively determine (some) properties of the things that happen to occupy them.     

Behaviour of simple population models under ecological processes

The two most popular and extensively-used discrete models of population growth display the generic bifurcation structure of a hierarchy of period-doubling sequence to chaos with increasing growth rates. In this paper we show that these two models, though they belong to a general class of one-dimensional maps, show very different dynamics when important ecological processes such as immigration and emigration/depletion, are considered. It is important that ecologists recognize the differences between these models before using them to describe their data—or develop optimization strategies—based on these models.     

The category of roots and the roots of categories: what we learn from selection in derivation

Selection—the tendency of derivational affixes to choose the category of their base—has most often been couched in terms of syntactic categories such as Noun, Verb, and Adjective. In recent years several theories have claimed, however, that roots are categoryless, and receive category only by virtue of being merged with functional projections of various sorts. This article examines three such theories—Distributed Morphology, Borer’s Exo-Skeletal model, and DiSciullo’s Asymmetrical Morphology, and determines that none of them can handle the phenomenon of affixal selection. We may, however, maintain the claim that roots lack syntactic category if we make use of a system of lexical semantic categorization that allows us to state selection in terms of semantic categories. It is shown that the framework of Lieber (2004) allows for such categorization, and moreover that semantic categorization permits us to make generalizations that are not available in a theory in which selection is purely on the basis of syntactic category. I am grateful to the faculty and students of the University of Patras, Greece for discussion and comments on an earlier version of this work. Thanks also to Sergio Scalise, Antonietta Bisetto, Chiara Melloni, and three anonymous reviewers for useful comments.     

Alternative spatial sampling in studies of plant demography: consequences for estimates of population growth rate

Ecologists commonly use matrix models to study the population dynamics of plants. Most studies of plant demography use plot-based methods to collect data, in part, because mapped individuals are easier to relocate in subsequent surveys and survey methods can be standardized among sites. However, there is tremendous variation among studies, both in terms of plot arrangement and the total area sampled. In addition, there has been little discussion of how alternative sampling arrangements influence estimates of population growth rates (λ) calculated with matrix models. We surveyed the literature to determine what sampling designs are most used in studies of plant demography using matrix models. We then used simulations of three common sampling techniques—using a single randomly placed plot, multiple randomly placed plots, and systematically distributed plots—to evaluate how these alternative strategies influenced the precision of estimates of λ. These simulations were based on long-term demographic data collected on 13 populations of the Amazonian understory herb Heliconia acuminate (Heliconiaceae). We found that the method used to collect data did not affect the bias or precision of estimates in our system—a surprising result, since the advantage in efficiency that is gained from systematic sampling is a well-known result from sampling theory. Because the statistical advantage of systematic sampling is most evident when there is spatial structure in demographic vital rates, we attribute this result to the lack of spatially structured vital rates in our focal populations. Given the likelihood of spatial autocorrelation in most ecological systems, we advocate sampling with a systematic grid of plots in each study site, as well as that researchers ensure that enough area is sampled—both within and across sites—to encompass the range of spatial variation in plant survival, growth, and reproduction.     

The System of Interpretance, Naturalizing Meaning as Finality

A materialist construction of semiosis requires system embodiment at particular locales, in order to function as systems of interpretance. I propose that we can use a systemic model of scientific measurement to construct a systems view of semiosis. I further suggest that the categories required to understand that process can be used as templates when generalizing to biosemiosis and beyond. The viewpoint I advance here is that of natural philosophy—which, once granted, incurs no principled block to further generalization all the way to pansemiotics—nearer to Peirce’s own very general perspective. This project requires a hylozooic framework, which I present in the form of a specification hierarchy, whereby physical dynamics subsume all other transactions at more highly developed integrative levels. The upshot of the paper is a proposal that meanings can be assimilated most generally to final causes.     

Postspawning survival in lacustrine sock-eyed salmon Oncorhynchus nerka Walb

The state of gonads, age, structure of scales, and size of specimens of the resident lacustrine form of sock-eyed salmon—kokanee Onchorhynchus nerka—are analyzed. In stocked, previously fishless, lakes, there are specimens that have survived spawning and have remained active for a year or several years. No evidence was found of the possibility of repeated spawning. Thus, such fish do not belong to the spawning stock of the population, and their ecological function is not clear.     

A conceptual framework for impact assessment within SLCA

Purpose  

This paper aims at spelling out the area of protection (AoP), namely the general concept of human well-being and the impact categories in social life cycle assessment (SLCA). The applicability of the so-called capabilities approach—a concept frequently used for evaluating human lives—is explored. It is shown how the principles of the capabilities approach can be transferred to the impact assessment within SLCA.     

Integrate-and-fire vs Poisson models of LGN input to V1 cortex: noisier inputs reduce orientation selectivity

One of the reasons the visual cortex has attracted the interest of computational neuroscience is that it has well-defined inputs. The lateral geniculate nucleus (LGN) of the thalamus is the source of visual signals to the primary visual cortex (V1). Most large-scale cortical network models approximate the spike trains of LGN neurons as simple Poisson point processes. However, many studies have shown that neurons in the early visual pathway are capable of spiking with high temporal precision and their discharges are not Poisson-like. To gain an understanding of how response variability in the LGN influences the behavior of V1, we study response properties of model V1 neurons that receive purely feedforward inputs from LGN cells modeled either as noisy leaky integrate-and-fire (NLIF) neurons or as inhomogeneous Poisson processes. We first demonstrate that the NLIF model is capable of reproducing many experimentally observed statistical properties of LGN neurons. Then we show that a V1 model in which the LGN input to a V1 neuron is modeled as a group of NLIF neurons produces higher orientation selectivity than the one with Poisson LGN input. The second result implies that statistical characteristics of LGN spike trains are important for V1’s function. We conclude that physiologically motivated models of V1 need to include more realistic LGN spike trains that are less noisy than inhomogeneous Poisson processes.     

The response of cortical neurons to in vivo-like input current: theory and experiment

The study of several aspects of the collective dynamics of interacting neurons can be highly simplified if one assumes that the statistics of the synaptic input is the same for a large population of similarly behaving neurons (mean field approach). In particular, under such an assumption, it is possible to determine and study all the equilibrium points of the network dynamics when the neuronal response to noisy, in vivo-like, synaptic currents is known. The response function can be computed analytically for simple integrate-and-fire neuron models and it can be measured directly in experiments in vitro. Here we review theoretical and experimental results about the neural response to noisy inputs with stationary statistics. These response functions are important to characterize the collective neural dynamics that are proposed to be the neural substrate of working memory, decision making and other cognitive functions. Applications to the case of time-varying inputs are reviewed in a companion paper (Giugliano et al. in Biol Cybern, 2008). We conclude that modified integrate-and-fire neuron models are good enough to reproduce faithfully many of the relevant dynamical aspects of the neuronal response measured in experiments on real neurons in vitro.     

The statistical analysis of multivariate serological frequency data

Data occurring in the form of frequencies are common in genetics—for example, in serology. Examples are provided by the AB0 group, the Rhesus group, and also DNA data. The statistical analysis of tables of frequencies is carried out using the available methods of multivariate analysis with usually three principal aims. One of these is to seek meaningful relationships between the components of a data set, the second is to examine relationships between populations from which the data have been obtained, the third is to bring about a reduction in dimensionality. This latter aim is usually realized by means of bivariate scatter diagrams using scores computed from a multivariate analysis. The multivariate statistical analysis of tables of frequencies cannot safely be carried out by standard multivariate procedures because they represent compositions and are therefore embedded in simplex space, a subspace of full space. Appropriate procedures for simplex space are compared and contrasted with simple standard methods of multivariate analysis (“raw” principal component analysis). The study shows that the differences between a log-ratio model and a simple logarithmic transformation of proportions may not be very great, particularly as regards graphical ordinations, but important discrepancies do occur. The divergencies between logarithmically based analyses and raw data are, however, great. Published data on Rhesus alleles observed for Italian populations are used to exemplify the subject.     

Estimating the directed information to infer causal relationships in ensemble neural spike train recordings

Advances in recording technologies have given neuroscience researchers access to large amounts of data, in particular, simultaneous, individual recordings of large groups of neurons in different parts of the brain. A variety of quantitative techniques have been utilized to analyze the spiking activities of the neurons to elucidate the functional connectivity of the recorded neurons. In the past, researchers have used correlative measures. More recently, to better capture the dynamic, complex relationships present in the data, neuroscientists have employed causal measures—most of which are variants of Granger causality—with limited success. This paper motivates the directed information, an information and control theoretic concept, as a modality-independent embodiment of Granger’s original notion of causality. Key properties include: (a) it is nonzero if and only if one process causally influences another, and (b) its specific value can be interpreted as the strength of a causal relationship. We next describe how the causally conditioned directed information between two processes given knowledge of others provides a network version of causality: it is nonzero if and only if, in the presence of the present and past of other processes, one process causally influences another. This notion is shown to be able to differentiate between true direct causal influences, common inputs, and cascade effects in more two processes. We next describe a procedure to estimate the directed information on neural spike trains using point process generalized linear models, maximum likelihood estimation and information-theoretic model order selection. We demonstrate that on a simulated network of neurons, it (a) correctly identifies all pairwise causal relationships and (b) correctly identifies network causal relationships. This procedure is then used to analyze ensemble spike train recordings in primary motor cortex of an awake monkey while performing target reaching tasks, uncovering causal relationships whose directionality are consistent with predictions made from the wave propagation of simultaneously recorded local field potentials.     

Yeast prions as a model of neurodegenerative infectious amyloidoses in humans

Several neurodegenerative diseases (so-called age-related diseases) in humans are associated with development of protein aggregates—amyloids. Prion diseases—kuru, Kreutzfeldt—Jakob and Gerstmann—Straussler—Sheinker diseases, fatal familial insomnia, etc.—are examples of infectious amyloidoses. A model system for investigation of mechanisms of amyloidogenesis and of its infectious nature had been developed as a result of yeast prion discovery. The existence of a prion network as an interaction of different prions identified in yeast is being confirmed recently as an interaction of different anyloids in humans. The potential danger of amyloidoses is conditioned by the very structure of almost all proteins containing fragments capable to be organized as β-sheets, which lead to their aggregation being exposed. Meanwhile, there are several well-defined examples of the adaptive value of amyloid aggregates: cytoplasmic incompatibility factor in Podospora anserina, spider silk, cytoplasmic stress granules in mammals, prion form of CPEB protein responsible for the neuron activity in Aplisia, etc. These facts should be taken into consideration when seeking antiamyloid drugs. Discovery of protein inheritance in lower eukaryotes modifies our knowledge of the template principle significance in biology and adds a concept of conformational templates (II order templates) involved in reproduction of the three-dimensional structure of the supramolecular complexes in the cell.     

Radical responses to neoliberalism: immigrant rights in the global era

Contemporary debate about immigrants provides an opportunity to expand the conversation about race and class. Immigrants in the US complicate racial categories and class formation, putting them in flux, while simultaneously opening possibilities to address historical and contemporary racial and social inequalities. Migrants affect class relations within and across borders, contributing to the conversation and activity around global justice. The convergence of the immigrant rights struggle with the global justice movement has furthered strategies that do both—confront racism and class oppression.     

Top-Down Modulation on Perceptual Decision with Balanced Inhibition through Feedforward and Feedback Inhibitory Neurons

Recent physiological studies have shown that neurons in various regions of the central nervous systems continuously receive noisy excitatory and inhibitory synaptic inputs in a balanced and covaried fashion. While this balanced synaptic input (BSI) is typically described in terms of maintaining the stability of neural circuits, a number of experimental and theoretical studies have suggested that BSI plays a proactive role in brain functions such as top-down modulation for executive control. Two issues have remained unclear in this picture. First, given the noisy nature of neuronal activities in neural circuits, how do the modulatory effects change if the top-down control implements BSI with different ratios between inhibition and excitation? Second, how is a top-down BSI realized via only excitatory long-range projections in the neocortex? To address the first issue, we systematically tested how the inhibition/excitation ratio affects the accuracy and reaction times of a spiking neural circuit model of perceptual decision. We defined an energy function to characterize the network dynamics, and found that different ratios modulate the energy function of the circuit differently and form two distinct functional modes. To address the second issue, we tested BSI with long-distance projection to inhibitory neurons that are either feedforward or feedback, depending on whether these inhibitory neurons do or do not receive inputs from local excitatory cells, respectively. We found that BSI occurs in both cases. Furthermore, when relying on feedback inhibitory neurons, through the recurrent interactions inside the circuit, BSI dynamically and automatically speeds up the decision by gradually reducing its inhibitory component in the course of a trial when a decision process takes too long.     

Partitioning of yeast RNA in aqueous two-phase system

Summary The partition behaviour of RNA extracted from yeast was examined using three types of aqueous two-phase systems: potassium phosphate—polyethyleneglycol (PEG) system, ammonium sulphate—PEG system and dextran sulphate—PEG—NaCl system. The molecular weight of PEG showed rather remarkable effects of RNA partition than did the electrolyte. High molecular weight RNA was concentrated at the interface in these systems. This suggests the possibility of its simple concentration or extraction.     

Species monophyly

In biological systematics, as well as in the philosophy of biology, species and higher taxa are individuated through their unique evolutionary origin. This is taken by some authors to mean that monophyly is a (relational) property not only of higher taxa, but also of species. A species is said to originate through speciation, and to go extinct when it splits into two daughter species (or through terminal extinction). Its unique evolutionary origin is said to bestow identity on a species through time and change, and to render species names rigid designators. Species names are thus believed to function just like names of supraspecific taxa. However, large parts of the Web of Life are composed of species that do not have a unique evolutionary origin from a single population, lineage or stem-species. Further, monophyly is an ambiguous concept if it is defined simply in terms of 'unique evolutionary origin'. Disambiguating the concept by defining a monophyletic taxon as 'a taxon that includes the ancestor and all, and only, its descendant' renders monophyly inapplicable to species. At the heart of the problem lies a fundamental distinction between species and monophyletic taxa, where species form mutually exclusive reticulated systems, while higher taxa form inclusive hierarchical systems. Examples are given both at the species level and below to illustrate the problems that result from the application of the monophyly criterion to species. The conclusion is that the concepts of exclusivity and monophyly should be treated as non-overlapping: exclusivity marks out a species synchronistically, i.e. in the present time. Monophyly marks out clades (groups of species) diachronistically, i.e. within an historical dimension.     

CuA centers and their biosynthetic models in azurin

Cu_A is a binuclear copper center that functions as an electron transfer agent, cycling between a reduced Cu(I)Cu(I) state and an oxidized mixed-valence Cu(+1.5)···Cu(+1.5) state. The copper ions are bridged by two cysteine thiolate ligands and form a copper–copper bond, the first reported of its kind in Nature. Such a “diamond-core” Cu₂S(Cys)₂ structure allows an unpaired electron to be completely delocalized over the two copper ions and contributes to its highly efficient electron transfer properties. This review provides accounts of how the Cu_A center was structurally characterized and highlights its salient spectroscopic properties. In the process, it introduces the Cu_A center in four different systems—native protein systems, soluble protein truncates of native proteins, synthetic models using organic molecules, and biosynthetic models using proteins as ligands—with a greater emphasis on biosynthetic models of Cu_A, especially on new, deeper insights gained from their studies.     

Theory predicts a rapid transition from niche-structured to neutral biodiversity patterns across a speciation-rate gradient

A central challenge in community ecology is to predict patterns of biodiversity with mechanistic models. The neutral model of biodiversity is a simple model that appears to provide parsimonious and accurate predictions of biodiversity patterns in some ecosystems, even though it ignores processes such as species interactions and niche structure. In a recent paper, we used analytical techniques to reveal why the mean predictions of the neutral model are robust to niche structure in high diversity but not low-diversity ecosystems. In the present paper, we explore this phenomenon further by generating stochastic simulated data from a spatially implicit hybrid niche-neutral model across different speciation rates. We compare the resulting patterns of species richness and abundance with the patterns expected from a pure neutral and a pure niche model. As the speciation rate in the hybrid model increases, we observe a surprisingly rapid transition from an ecosystem in which diversity is almost entirely governed by niche structure to one in which diversity is statistically indistinguishable from that of the neutral model. Because the transition is rapid, one prediction of our abstract model is that high-diversity ecosystems such as tropical forests can be approximated by one simple model—the neutral model—whereas low-diversity ecosystems such as temperate forests can be approximated by another simple model—the niche model. Ecosystems that require the hybrid model are predicted to be rare, occurring only over a narrow range of speciation rates.