Regional methods for evaluating the effects of flow alteration on stream ecosystems

2012 Summer.Includes bibliographical references.Three stand-alone chapters explore the development and implementation of regional flow-ecology methods. Ecohydrology is an interdisciplinary field that brings together specialized research in hydrology, hydraulics, geomorphology and ecology. My dissertation reflects the need for interdisciplinary knowledge, tackling issues as diverse as low flows for trout (Chapter 2) to peak flows for cottonwood (Chapter 3). A regional-scale view unifies these investigations, with Chapter 1 establishing the scientific foundation and management objectives for regional flow-ecology methods. Summary Chapter 1 - To balance the benefits of dams and water diversions against society's expectations for the natural environment, flow managers require scientific advice on the ecosystem response to flow alteration. The methods selected to investigate the ecosystem effects of flow alteration (e.g., PHABSIM - Physical Habitat Simulation) should reflect the scale of flow management and the information requirements of flow managers. In addition, a hierarchical habitat framework provides an ecological foundation for the development and implementation of flow-ecology methods, because ecosystem response to flow is constrained by large-scale processes. This can be put into practice using hydrogeomorphic classification to define the higher-level physical processes (e.g., sediment transport, disturbance) that dictate the mechanisms of biotic response to flow. Regional flow-ecology methods provide a vehicle for incorporating prior knowledge and hydrogeomorphic processes into flow management at both regional and local scales. Chapter 2 - Changes in hydraulic habitat (depth and velocity) with flow can be predicted using intensive reach-specific methods, such as PHABSIM. I used existing PHABSIM data to develop GHMs (Generalized Habitat Models) that predict trout habitat-flow curves for unsurveyed streams of the southern Rocky Mountains. Predicted habitat was significantly correlated with the abundance of large brown trout (P40% flow reduction). Historic photographs revealed that narrowleaf in the Middle Park area (Colorado) have increased in abundance since dam closure, colonizing previously bare gravel bars. That narrowleaf appear less sensitive to flow alteration than plains cottonwood could reflect different species traits (e.g., alternative sources of disturbance for root suckering by narrowleaf), together with the many physical transitions from plains to mountains that are associated with the species transition

Harmonic analysis of music using combinatory categorial grammar

FP7 grant 249520 (GRAMPLUS)Various patterns of the organization of Western tonal music exhibit hierarchical structure, among them the harmonic progressions underlying melodies and the metre underlying rhythmic patterns. Recognizing these structures is an important part of unconscious human cognitive processing of music. Since the prosody and syntax of natural languages are commonly analysed with similar hierarchical structures, it is reasonable to expect that the techniques used to identify these structures automatically in natural language might also be applied to the automatic interpretation of music. In natural language processing (NLP), analysing the syntactic structure of a sentence is prerequisite to semantic interpretation. The analysis is made difficult by the high degree of ambiguity in even moderately long sentences. In music, a similar sort of structural analysis, with a similar degree of ambiguity, is fundamental to tasks such as key identification and score transcription. These and other tasks depend on harmonic and rhythmic analyses. There is a long history of applying linguistic analysis techniques to musical analysis. In recent years, statistical modelling, in particular in the form of probabilistic models, has become ubiquitous in NLP for large-scale practical analysis of language. The focus of the present work is the application of statistical parsing to automatic harmonic analysis of music. This thesis demonstrates that statistical parsing techniques, adapted from NLP with little modification, can be successfully applied to recovering the harmonic structure underlying music. It shows first how a type of formal grammar based on one used for linguistic syntactic processing, Combinatory Categorial Grammar (CCG), can be used to analyse the hierarchical structure of chord sequences. I introduce a formal language similar to first-order predicate logical to express the hierarchical tonal harmonic relationships between chords. The syntactic grammar formalism then serves as a mechanism to map an unstructured chord sequence onto its structured analysis. In NLP, the high degree of ambiguity of the analysis means that a parser must consider a huge number of possible structures. Chart parsing provides an efficient mechanism to explore them. Statistical models allow the parser to use information about structures seen before in a training corpus to eliminate improbable interpretations early on in the process and to rank the final analyses by plausibility. To apply the same techniques to harmonic analysis of chord sequences, a corpus of tonal jazz chord sequences annotated by hand with harmonic analyses is constructed. Two statistical parsing techniques are adapted to the present task and evaluated on their success at recovering the annotated structures. The experiments show that parsing using a statistical model of syntactic derivations is more successful than a Markovian baseline model at recovering harmonic structure. In addition, the practical technique of statistical supertagging serves to speed up parsing without any loss in accuracy. This approach to recovering harmonic structure can be extended to the analysis of performance data symbolically represented as notes. Experiments using some simple proof-of-concept extensions of the above parsing models demonstrate one probabilistic approach to this. The results reported provide a baseline for future work on the task of harmonic analysis of performances

ISIS2: Pixel Sensor with Local Charge Storage for ILC Vertex Detector

ISIS (In-situ Storage Imaging Sensor) is a novel CMOS sensor with multiple charge storage capability developed for the ILC vertex detector by the Linear Collider Flavour Identification (LCFI) collaboration. This paper reports test results for ISIS2, the second generation of ISIS sensors implemented in a 0.18 micron CMOS process. The local charge storage and charge transfer were unambiguously demonstrated.Comment: 11 pages, 16 figures, to be included in the Proceedings of International Linear Collider Workshop 201

Large Intelligent Surface Measurements for Joint Communication and Sensing

Multiple concepts for future generations of wireless communication standards utilize coherent processing of signals from many distributed antennas. Names for these concepts include distributed MIMO, cell-free massive MIMO, XL-MIMO, and large intelligent surfaces. They aim to improve communica- tion reliability, capacity, as well as energy efficiency and provide possibilities for new applications through joint communication and sensing. One such recently proposed solution is the concept of RadioWeaves. It proposes a new radio infrastructure for distributed MIMO with distributed internal processing, storage and compute resources integrated into the infrastructure. The large bandwidths available in the higher bands have inspired much work regarding sensing in the mmWave- and sub-THz- bands, however, sub-6 GHz cellular bands will still be the main provider of broad cellular coverage due to the more favorable propagation conditions. In this paper, we present results from a sub-6 GHz measurement campaign targeting the non-stationary spatial channel statistics for a large RadioWeave and the temporal non-stationarity in a dynamic scenario with RadioWeaves. From the results, we also predict the possibility of multi-static sensing and positioning of users in the environment

Cd/Pt Precursor Solution for Solar H-2 Production and in situ Photochemical Synthesis of Pt Single-atom Decorated CdS Nanoparticles

Despite extensive efforts to develop high-performance H2 evolution catalysts, this remains a major challenge. Here, we demonstrate the use of Cd/Pt precursor solutions for significant photocatalytic H2 production (154.7 mmol g−1 h−1), removing the need for a pre-synthesized photocatalyst. In addition, we also report simultaneous in situ synthesis of Pt single-atoms anchored CdS nanoparticles (PtSA-CdSIS) during photoirradiation. The highly dispersed in situ incorporation of extensive Pt single atoms on CdSIS enables the enhancement of active sites and suppresses charge recombination, which results in exceptionally high solar-to-hydrogen conversion efficiency of ≈1 % and an apparent quantum yield of over 91 % (365 nm) for H2 production. Our work not only provides a promising strategy for maximising H2 production efficiency but also provides a green process for H2 production and the synthesis of highly photoactive PtSA-CdSIS nanoparticles

Global Trends of Benthic Bacterial Diversity and Community Composition Along Organic Enrichment Gradients of Salmon Farms

The analysis of benthic bacterial community structure has emerged as a powerful alternative to traditional microscopy-based taxonomic approaches to monitor aquaculture disturbance in coastal environments. However, local bacterial diversity and community composition vary with season, biogeographic region, hydrology, sediment texture, and aquafarm-specific parameters. Therefore, without an understanding of the inherent variation contained within community complexes, bacterial diversity surveys conducted at individual farms, countries, or specific seasons may not be able to infer global universal pictures of bacterial community diversity and composition at different degrees of aquaculture disturbance. We have analyzed environmental DNA (eDNA) metabarcodes (V3–V4 region of the hypervariable SSU rRNA gene) of 138 samples of different farms located in different major salmon-producing countries. For these samples, we identified universal bacterial core taxa that indicate high, moderate, and low aquaculture impact, regardless of sampling season, sampled country, seafloor substrate type, or local farming and environmental conditions. We also discuss bacterial taxon groups that are specific for individual local conditions. We then link the metabolic properties of the identified bacterial taxon groups to benthic processes, which provides a better understanding of universal benthic ecosystem function(ing) of coastal aquaculture sites. Our results may further guide the continuing development of a practical and generic bacterial eDNA-based environmental monitoring approach.publishedVersio

The local ordering of polar solvents around crystalline carbon nitride nanosheets in solution

The crystalline graphitic carbon nitride, poly-triazine imide (PTI) is highly unusual among layered materials since it is spontaneously soluble in aprotic, polar solvents including dimethylformamide (DMF). The PTI material consists of layers of carbon nitride intercalated with LiBr. When dissolved, the resulting solutions consist of dissolved, luminescent single to multilayer nanosheets of around 60–125 nm in diameter and Li+ and Br− ions originating from the intercalating salt. To understand this unique solubility, the structure of these solutions has been investigated by high-energy X-ray and neutron diffraction. Although the diffraction patterns are dominated by inter-solvent correlations there are clear differences between the X-ray diffraction data of the PTI solution and the solvent in the 4–6 Å −1 range, with real space differences persisting to at least 10 Å. Structural modelling using both neutron and X-ray datasets as a constraint reveal the formation of distinct, dense solvation shells surrounding the nanoparticles with a layer of Br − close to the PTI-solvent interface. This solvent ordering provides a configuration that is energetically favourable underpinning thermodynamically driven PTI dissolution. This article is part of the theme issue 'Exploring the length scales, timescales and chemistry of challenging materials (Part 2)'

Turning off the DRIP (‘Data-rich, information-poor’) – rationalising monitoring with a focus on marine renewable energy developments and the benthos

Marine renewable energy developments (MREDs) are rapidly expanding in size and number as society strives to maintain electricity generation whilst simultaneously reducing climate-change linked CO2 emissions. MREDs are part of an ongoing large-scale modification of coastal waters that also includes activities such as commercial fishing, shipping, aggregate extraction, aquaculture, dredging, spoil-dumping and oil and gas exploitation. It is increasingly accepted that developments, of any kind, should only proceed if they are ecologically sustainable and will not reduce current or future delivery of ecosystem services. The benthos underpins crucial marine ecosystem services yet, in relation to MREDs, is currently poorly monitored: current monitoring programmes are extensive and costly yet provide little useful data in relation to ecosystem-scale-related changes, a situation called ‘data-rich, information-poor’ (DRIP). MRED –benthic interactions may cause changes that are of a sufficient scale to change ecosystem services provision, particularly in terms of fisheries and biodiversity and, via trophic linkages, change the distribution of fish, birds and mammals. The production of DRIPy data should be eliminated and the resources used instead to address relevant questions that are logically bounded in time and space. Efforts should target identifying metrics of change that can be linked to ecosystem function or service provision, particularly where those metrics show strongly non-linear effects in relation to the stressor. Future monitoring should also be designed to contribute towards predictive ecosystem models and be sufficiently robust and understandable to facilitate transparent, auditable and timely decision-making

Reverse engineering: transaminase biocatalystdevelopment using ancestral sequencereconstruction

The development of new biocatalysts using ancestral sequence reconstruction is reported. When applied to an ω-transaminase, the ancestral proteins demonstrated novel and superior activities with eighty percent of the forty compounds tested compared to the modern day protein, and improvements in activity of up to twenty fold. These included a range of compounds pertinent as feedstocks in polyamide manufacture.MW and SK were supported by CSIRO Research Office Postdoctoral Fellowships