Shallow water marine sediment bacterial community shifts along a natural CO2 gradient in the Mediterranean Sea Off vulcano, Italy

The effects of increasing atmospheric CO(2) on ocean ecosystems are a major environmental concern, as rapid shoaling of the carbonate saturation horizon is exposing vast areas of marine sediments to corrosive waters worldwide. Natural CO(2) gradients off Vulcano, Italy, have revealed profound ecosystem changes along rocky shore habitats as carbonate saturation levels decrease, but no investigations have yet been made of the sedimentary habitat. Here, we sampled the upper 2 cm of volcanic sand in three zones, ambient (median pCO(2) 419 µatm, minimum Omega (arag) 3.77), moderately CO(2)-enriched (median pCO(2) 592 µatm, minimum Omega (arag) 2.96), and highly CO(2)-enriched (median pCO(2) 1611 µatm, minimum Omega (arag) 0.35). We tested the hypothesis that increasing levels of seawater pCO(2) would cause significant shifts in sediment bacterial community composition, as shown recently in epilithic biofilms at the study site. In this study, 454 pyrosequencing of the V1 to V3 region of the 16S rRNA gene revealed a shift in community composition with increasing pCO(2). The relative abundances of most of the dominant genera were unaffected by the pCO(2) gradient, although there were significant differences for some 5 % of the genera present (viz. Georgenia, Lutibacter, Photobacterium, Acinetobacter, and Paenibacillus), and Shannon Diversity was greatest in sediments subject to long-term acidification (>100 years). Overall, this supports the view that globally increased ocean pCO(2) will be associated with changes in sediment bacterial community composition but that most of these organisms are resilient. However, further work is required to assess whether these results apply to other types of coastal sediments and whether the changes in relative abundance of bacterial taxa that we observed can significantly alter the biogeochemical functions of marine sediments.

Computation of nonlinear streaky structures in boundary layer flow

En esta tesis se integran numéricamente las ecuaciones reducidas de Navier Stokes (RNS), que describen el flujo en una capa límite tridimensional que presenta también una escala característica espacial corta en el sentido transversal. La formulación RNS se usa para el cálculo de “streaks” no lineales de amplitud finita, y los resultados conseguidos coinciden con los existentes en la literatura, obtenidos típicamente utilizando simulación numérica directa (DNS) o nonlinear parabolized stability equations (PSE). El cálculo de los “streaks” integrando las RNS es mucho menos costoso que usando DNS, y no presenta los problemas de estabilidad que aparecen en la formulación PSE cuando la amplitud del “streak” deja de ser pequeña. El código de integración RNS se utiliza también para el cálculo de los “streaks” que aparecen de manera natural en el borde de ataque de una placa plana en ausencia de perturbaciones en la corriente uniforme exterior. Los resultados existentes hasta ahora calculaban estos “streaks” únicamente en el límite lineal (amplitud pequeña), y en esta tesis se lleva a cabo el cálculo de los mismos en el régimen completamente no lineal (amplitud finita). En la segunda parte de la tesis se generaliza el código RNS para incluir la posibilidad de tener una placa no plana, con curvatura en el sentido transversal que varía lentamente en el sentido de la corriente. Esto se consigue aplicando un cambio de coordenadas, que transforma el dominio físico en uno rectangular. La formulación RNS se integra también expresada en las correspondientes coordenadas curvilíneas. Este código generalizado RNS se utiliza finalmente para estudiar el flujo de capa límite sobre una placa con surcos que varían lentamente en el sentido de la corriente, y es usado para simular el flujo sobre surcos que crecen en tal sentido. Abstract In this thesis, the reduced Navier Stokes (RNS) equations are numerically integrated. This formulation describes the flow in a three-dimensional boundary layer that also presents a short characteristic space scale in the spanwise direction. RNS equations are used to calculate nonlinear finite amplitude “streaks”, and the results agree with those reported in the literature, typically obtained using direct numerical simulation (DNS) or nonlinear parabolized stability equations (PSE). “Streaks” simulations through the RNS integration are much cheaper than using DNS, and avoid stability problems that appear in the PSE when the amplitude of the “streak” is not small. The RNS integration code is also used to calculate the “streaks” that naturally emerge at the leading edge of a flat plate boundary layer in the absence of any free stream perturbations. Up to now, the existing results for these “streaks” have been only calculated in the linear limit (small amplitude), and in this thesis their calculation is carried out in the fully nonlinear regime (finite amplitude). In the second part of the thesis, the RNS code is generalized to include the possibility of having a non-flat plate, curved in the spanwise direction and slowly varying in the streamwise direction. This is achieved by applying a change of coordinates, which transforms the physical domain into a rectangular one. The RNS formulation expressed in the corresponding curvilinear coordinates is also numerically integrated. This generalized RNS code is finally used to study the boundary layer flow over a plate with grooves which vary slowly in the streamwise direction; and this code is used to simulate the flow over grooves that grow in the streamwise direction.

Utilising Provenance to Enhance Social Computation

Postprint

SC-PROV: A Provenance Vocabulary for Social Computation

The research described here is supported by the award made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub; award reference: EP/G066051/1.

The evolution of emergent computation.

A simple evolutionary process can discover sophisticated methods for emergent information processing in decentralized spatially extended systems. The mechanisms underlying the resulting emergent computation are explicated by a technique for analyzing particle-based logic embedded in pattern-forming systems. Understanding how globally coordinated computation can emerge in evolution is relevant both for the scientific understanding of natural information processing and for engineering new forms of parallel computing systems.

Table of natural logarithms ... /

"One in a series of mathematical tables prepared by the Project for the Computation of Mathematical Tables."--Volume I., Pref.

Experimental Support of Argument-based Syntactic Computation

Linguistic theory, cognitive, information, and mathematical modeling are all useful while we attempt to achieve a better understanding of the Language Faculty (LF). This cross-disciplinary approach will eventually lead to the identification of the key principles applicable in the systems of Natural Language Processing. The present work concentrates on the syntax-semantics interface. We start from recursive definitions and application of optimization principles, and gradually develop a formal model of syntactic operations. The result – a Fibonacci- like syntactic tree – is in fact an argument-based variant of the natural language syntax. This representation (argument-centered model, ACM) is derived by a recursive calculus that generates a mode which connects arguments and expresses relations between them. The reiterative operation assigns primary role to entities as the key components of syntactic structure. We provide experimental evidence in support of the argument-based model. We also show that mental computation of syntax is influenced by the inter-conceptual relations between the images of entities in a semantic space.

Effects of ocean acidification on embryonic respiration and development of a temperate wrasse living along a natural CO2 gradient

Volcanic CO2 seeps provide opportunities to investigate the effects of ocean acidification on organisms in the wild. To understand the influence of increasing CO2 concentrations on the metabolic rate (oxygen consumption) and the development of ocellated wrasse early life stages, we ran two field experiments, collecting embryos from nesting sites with different partial pressures of CO2 [pCO2; ambient (400 µatm) and high (800-1000 µatm)] and reciprocally transplanting embryos from ambient- to high-CO2 sites for 30 h. Ocellated wrasse offspring brooded in different CO2 conditions had similar responses, but after transplanting portions of nests to the high-CO2 site, embryos from parents that spawned in ambient conditions had higher metabolic rates. Although metabolic phenotypic plasticity may show a positive response to high CO2, it often comes at a cost, in this case as a smaller size at hatching. This can have adverse effects because smaller larvae often exhibit a lower survival in the wild. However, the adverse effects of increased CO2 on metabolism and development did not occur when embryos from the high-CO2 nesting site were exposed to ambient conditions, suggesting that offspring from the high-CO2 nesting site could be resilient to a wider range of pCO2 values than those belonging to the site with present-day pCO2 levels. Our study identifies a crucial need to increase the number of studies dealing with these processes under global change trajectories and to expand these to naturally high-CO2 environments, in order to assess further the adaptive plasticity mechanism that encompasses non-genetic inheritance (epigenetics) through parental exposure and other downstream consequences, such as survival of larvae.

A Role for Provenance in Social Computation

Postprint

Advances in Dynamic Modeling and Computation for Count Data

A class of multi-process models is developed for collections of time indexed count data. Autocorrelation in counts is achieved with dynamic models for the natural parameter of the binomial distribution. In addition to modeling binomial time series, the framework includes dynamic models for multinomial and Poisson time series. Markov chain Monte Carlo (MCMC) and Po ́lya-Gamma data augmentation (Polson et al., 2013) are critical for fitting multi-process models of counts. To facilitate computation when the counts are high, a Gaussian approximation to the P ́olya- Gamma random variable is developed.

Three applied analyses are presented to explore the utility and versatility of the framework. The first analysis develops a model for complex dynamic behavior of themes in collections of text documents. Documents are modeled as a “bag of words”, and the multinomial distribution is used to characterize uncertainty in the vocabulary terms appearing in each document. State-space models for the natural parameters of the multinomial distribution induce autocorrelation in themes and their proportional representation in the corpus over time.

The second analysis develops a dynamic mixed membership model for Poisson counts. The model is applied to a collection of time series which record neuron level firing patterns in rhesus monkeys. The monkey is exposed to two sounds simultaneously, and Gaussian processes are used to smoothly model the time-varying rate at which the neuron’s firing pattern fluctuates between features associated with each sound in isolation.

The third analysis presents a switching dynamic generalized linear model for the time-varying home run totals of professional baseball players. The model endows each player with an age specific latent natural ability class and a performance enhancing drug (PED) use indicator. As players age, they randomly transition through a sequence of ability classes in a manner consistent with traditional aging patterns. When the performance of the player significantly deviates from the expected aging pattern, he is identified as a player whose performance is consistent with PED use.

All three models provide a mechanism for sharing information across related series locally in time. The models are fit with variations on the P ́olya-Gamma Gibbs sampler, MCMC convergence diagnostics are developed, and reproducible inference is emphasized throughout the dissertation.

Natural high pCO2 increases autotrophy in Anemonia viridis (Anthozoa) as revealed from stable isotope (C, N) analysis

Contemporary cnidarian-algae symbioses are challenged by increasing CO2 concentrations (ocean warming and acidification) affecting organisms' biological performance. We examined the natural variability of carbon and nitrogen isotopes in the symbiotic sea anemone Anemonia viridis to investigate dietary shifts (autotrophy/heterotrophy) along a natural pCO2 gradient at the island of Vulcano, Italy. delta 13C values for both algal symbionts (Symbiodinium) and host tissue of A. viridis became significantly lighter with increasing seawater pCO2. Together with a decrease in the difference between delta 13C values of both fractions at the higher pCO2 sites, these results indicate there is a greater net autotrophic input to the A. viridis carbon budget under high pCO2 conditions. delta 15N values and C/N ratios did not change in Symbiodinium and host tissue along the pCO2 gradient. Additional physiological parameters revealed anemone protein and Symbiodinium chlorophyll a remained unaltered among sites. Symbiodinium density was similar among sites yet their mitotic index increased in anemones under elevated pCO2. Overall, our findings show that A. viridis is characterized by a higher autotrophic/heterotrophic ratio as pCO2 increases. The unique trophic flexibility of this species may give it a competitive advantage and enable its potential acclimation and ecological success in the future under increased ocean acidification.