Scale-dependent response diversity of seabirds to prey in the North Sea

Functional response diversity is defined as the diversity of responses to environmental change among species that contribute to the same ecosystem function. Because different ecological processes dominate on different spatial and temporal scales, response diversity is likely to be scale dependent. Using three extensive data sets on seabirds, pelagic fish, and zooplankton, we investigate the strength and diversity in the response of seabirds to prey in the North Sea over three scales of ecological organization. Two-stage analyses were used to partition the variance in the abundance of predators and prey among the different scales of investigation: variation from year to year, variation among habitats, and variation on the local patch scale. On the year-to-year scale, we found a strong and synchronous response of seabirds to the abundance of prey, resulting in low response diversity. Conversely, as different seabird species were found in habitats dominated by different prey species, we found a high diversity in the response of seabirds to prey on the habitat scale. Finally, on the local patch scale, seabirds were organized in multispecies patches. These patches were weakly associated with patches of prey, resulting in a weak response strength and a low response diversity. We suggest that ecological similarities among seabird species resulted in low response diversity on the year-to-year scale. On the habitat scale, we suggest that high response diversity was due to interspecific competition and niche segregation among seabird species. On the local patch scale, we suggest that facilitation with respect to the detection and accessibility of prey patches resulted in overlapping distribution of seabirds but weak associations with prey. The observed scale dependencies in response strength and diversity have implications for how the seabird community will respond to different environmental disturbances.

Theoretical analysis of ocean color radiances anomalies and implications for phytoplankton groups detection in case 1 waters

Past years have seen the development of different approaches to detect phytoplankton groups from space. One of these methods, the PHYSAT one, is empirically based on reflectance anomalies. Despite observations in good agreement with in situ measurements, the underlying theoretical explanation of the method is still missing and needed by the ocean color community as it prevents improvements of the methods and characterization of uncertainties on the inversed products. In this study, radiative transfer simulations are used in addition to in situ measurements to understand the organization of the signals used in PHYSAT. Sensitivity analyses are performed to assess the impact of the variability of the following three parameters on the reflectance anomalies: specific phytoplankton absorption, colored dissolved organic matter absorption, and particles backscattering. While the later parameter explains the largest part of the anomalies variability, results show that each group is generally associated with a specific bio-optical environment which should be considered to improve methods of phytoplankton groups detection.

High-resolution view of the spring bloom initiation and net community production in the Subantarctic Southern Ocean using glider data

In the Southern Ocean, there is increasing evidence that seasonal to subseasonal temporal scales, and meso- to submesoscales play an important role in understanding the sensitivity of ocean primary productivity to climate change. This drives the need for a high-resolution approach to re- solving biogeochemical processes. In this study, 5.5 months of continuous, high-resolution (3 h, 2 km horizontal resolution) glider data from spring to summer in the Atlantic Subantarctic Zone is used to investigate: (i) the mechanisms that drive bloom initiation and high growth rates in the region and (ii) the seasonal evolution of water column production and respiration. Bloom initiation dates were analysed in the context of upper ocean boundary layer physics highlighting sensitivities of different bloom detection methods to different environmental processes. Model results show that in early spring (September to mid-November) increased rates of net community production (NCP) are strongly affected by meso- to submesoscale features. In late spring/early summer (late-November to mid-December) seasonal shoaling of the mixed layer drives a more spatially homogenous bloom with maximum rates of NCP and chlorophyll biomass. A comparison of biomass accumulation rates with a study in the North Atlantic highlights the sensitivity of phytoplankton growth to fine-scale dynamics and emphasizes the need to sample the ocean at high resolution to accurately resolve phytoplankton phenology and improve our ability to estimate the sensitivity of the biological carbon pump to climate change.

Use of culture and molecular analysis to determine the effect of antibiotic treatment on microbial community diversity and abundance during exacerbation in patients with cystic fibrosis

Background: Anaerobic bacteria are increasingly regarded as important in cystic fibrosis (CF) pulmonary infection. The aim of this study was to determine the effect of antibiotic treatment on aerobic and anaerobic microbial community diversity and abundance during exacerbations in patients with CF.

Methods: Sputum was collected at the start and completion of antibiotic treatment of exacerbations and when clinically stable. Bacteria were quantified and identified following culture, and community composition was also examined using culture-independent methods.

Results: Pseudomonas aeruginosa or Burkholderia cepacia complex were detected by culture in 24/26 samples at the start of treatment, 22/26 samples at completion of treatment and 11/13 stable samples. Anaerobic bacteria were detected in all start of treatment and stable samples and in 23/26 completion of treatment samples. Molecular analysis showed greater bacterial diversity within sputum samples than was detected by culture; there was reasonably good agreement between the methods for the presence or absence of aerobic bacteria such as P aeruginosa (kappa=0.74) and B cepacia complex (kappa=0.92), but agreement was poorer for anaerobes. Both methods showed that the composition of the bacterial community varied between patients but remained relatively stable in most individuals despite treatment. Bacterial abundance decreased transiently following treatment, with this effect more evident for aerobes (median decrease in total viable count 2.3 x 10(7) cfu/g, p=0.005) than for anaerobes (median decrease in total viable count 3 x 10(6) cfu/g, p=0.046).

Conclusion: Antibiotic treatment targeted against aerobes had a minimal effect on abundance of anaerobes and community composition, with both culture and molecular detection methods required for comprehensive characterisation of the microbial community in the CF lung. Further studies are required to determine the clinical significance of and optimal treatment for these newly identified bacteria.

Accuracy of LightCycler® SeptiFast for the detection and identification of pathogens in the blood of patients with suspected sepsis: a systematic review protocol

Background: There is growing interest in the potential utility of molecular diagnostics in improving the detection of life-threatening infection (sepsis). LightCycler® SeptiFast is a multipathogen probebased real-time PCR system targeting DNA sequences of bacteria and fungi present in blood samples within a few hours. We report here the protocol of the first systematic review of published clinical diagnostic accuracy studies of this technology when compared with blood culture in the setting of suspected sepsis. Methods/design: Data sources: the Cochrane Database of Systematic Reviews, the Database of Abstracts of Reviews of Effects (DARE), the Health Technology Assessment Database (HTA), the NHS Economic Evaluation Database (NHSEED), The Cochrane Library, MEDLINE, EMBASE, ISI Web of Science, BIOSIS Previews, MEDION and the Aggressive Research Intelligence Facility Database (ARIF). Study selection: diagnostic accuracy studies that compare the real-time PCR technology with standard culture results performed on a patient's blood sample during the management of sepsis. Data extraction: three reviewers, working independently, will determine the level of evidence, methodological quality and a standard data set relating to demographics and diagnostic accuracy metrics for each study. Statistical analysis/data synthesis: heterogeneity of studies will be investigated using a coupled forest plot of sensitivity and specificity and a scatter plot in Receiver Operator Characteristic (ROC) space. Bivariate model method will be used to estimate summary sensitivity and specificity. The authors will investigate reporting biases using funnel plots based on effective sample size and regression tests of asymmetry. Subgroup analyses are planned for adults, children and infection setting (hospital vs community) if sufficient data are uncovered. Dissemination: Recommendations will be made to the Department of Health (as part of an open-access HTA report) as to whether the real-time PCR technology has sufficient clinical diagnostic accuracy potential to move forward to efficacy testing during the provision of routine clinical care.

Community Engagement in Ireland's Developmental Welfare State: a study of the life cycle approach

The idea that people matter in modern democracies, often referred to as 'civic engagement' is recognised at the highest international level (United Nations 2008: 9). Civic or community engagement is essential to how budgets are decided, policy is developed and public services delivered. Significantly, community engagement is crucial in developing policy for sustained economic and social development. In Ireland the idea of the Developmental Welfare State (DWS) is based on the premise that the social policy system should support citizens so as to reach their full potential. Such a system comprises three overlapping elements: tax and welfare transfer, the provision of services and activist initiatives (National Economic and Social Council, 2005: ix-xviii). Civil Society Organisations have been challenged to 'operationalise the DWS' using a 'life cycle framework' as part of Ireland's corporatist partnership model (Department of Taoiseach, 2006: 40).

MICROBIAL COMMUNITY COMPOSITION IN THE LUNGS OF PATIENTS WITH CYSTIC FIBROSIS AND NON-CF BRONCHIECTASIS

Introduction and Aims: Persistent bacterial infection is a major cause of morbidity and mortality in patients with both Cystic Fibrosis (CF) and non-CF Bronchiectasis (non-CFBX). Numerous studies have shown that CF and non-CFBX airways are colonised by a complex microbiota. However, many bacteria are difficult, if not impossible, to culture by conventional laboratory techniques. Therefore, molecular detection techniques offer a more comprehensive view of bacterial diversity within clinical specimens. The objective of this study was to characterise and compare bacterial diversity and relative abundance in patients with CF and non-CFBX during exacerbation and when clinically stable.

Methods: Sputum samples were collected from CF (n=50 samples) and non-CFBX (n=52 samples) patients at the start and end of treatment for an infective exacerbation and when clinically stable. Pyrosequencing was used to assess the microbial diversity and relative genera (or the closest possibly taxonomic order) abundance within the samples. Each sequence read was defined based on 3% difference.

Results: High-throughput pyrosequencing allowed a sensitive and detailed examination of microbial community composition. Rich microbial communities were apparent within both CF (171 species-level phylotypes per genus) and non-CFBX airways (144 species-level phylotypes per genus). Relative species distribution within those two environments was considerably different; however, relatively few genera formed a core of microorganisms, representing approximately 90% of all sequences, which dominated both environments. Relative abundance based on observed operational taxonomic units demonstrated that the most abundant bacteria in CF were Pseudomonas (28%), Burkholderia (22%), Streptococcus (13%), family Pseudomonadaceae (8%) and Prevotella (6%). In contrast, the most commonly detected operational taxonomic units in non-CFBX were Haemophilus (22%), Streptococcus (14%), other (unassigned taxa) (11%), Pseudomonas (10%), Veillonella (7%) and Prevotella (6%).

Conclusions: These results suggest that distinctive microbial communities are associated with infection and/or colonisation in patients with both CF and non-CFBX. Although relatively high species richness was observed within the two environments, each was dominated by different core taxa. This suggests that differences in the lung environment of these two diseases may affect adaptability of the relevant bacterial taxa.

Sarcasm Detection on Czech and English Twitter

This paper presents a machine learning approach to sarcasm detection on Twitter in two languages – English and Czech. Although there has been some research in sarcasm detection in languages other than English (e.g., Dutch, Italian, and Brazilian Portuguese), our work is the first attempt at sarcasm detection in the Czech language. We created a large Czech Twitter corpus consisting of 7,000 manually-labeled tweets and provide it to the community. We evaluate two classifiers with various combinations of features on both the Czech and English datasets. Furthermore, we tackle the issues of rich Czech morphology by examining different preprocessing techniques. Experiments show that our language-independent approach significantly outperforms adapted state-of-the-art methods in English (F-measure 0.947) and also represents a strong baseline for further research in Czech (F-measure 0.582).

Anomaly Detection for Data with Spatial Attributes

The problem of detecting spatially-coherent groups of data that exhibit anomalous behavior has started to attract attention due to applications across areas such as epidemic analysis and weather forecasting. Earlier efforts from the data mining community have largely focused on finding outliers, individual data objects that display deviant behavior. Such point-based methods are not easy to extend to find groups of data that exhibit anomalous behavior. Scan Statistics are methods from the statistics community that have considered the problem of identifying regions where data objects exhibit a behavior that is atypical of the general dataset. The spatial scan statistic and methods that build upon it mostly adopt the framework of defining a character for regions (e.g., circular or elliptical) of objects and repeatedly sampling regions of such character followed by applying a statistical test for anomaly detection. In the past decade, there have been efforts from the statistics community to enhance efficiency of scan statstics as well as to enable discovery of arbitrarily shaped anomalous regions. On the other hand, the data mining community has started to look at determining anomalous regions that have behavior divergent from their neighborhood.In this chapter,we survey the space of techniques for detecting anomalous regions on spatial data from across the data mining and statistics communities while outlining connections to well-studied problems in clustering and image segmentation. We analyze the techniques systematically by categorizing them appropriately to provide a structured birds eye view of the work on anomalous region detection;we hope that this would encourage better cross-pollination of ideas across communities to help advance the frontier in anomaly detection.

Habitat-species interactions in a carnivore community

Na maioria das area protegidas nacionais existe uma considerável falta de informação científica relativa aos mamíferos carnívoros. A Reserva Natural da Serra da Malcata, localizada no centro-este de Portugal, tem vindo a desenvolver, desde os últimos 20 anos, estudos de ecologia e esta tese pretende dar seguimento a esse esforço de monitorização, através do desenvolvimento de métodos simples e eficientes, de monitorização de carnívoros, que possam servir como percursores de trabalhos a longo-prazo em áreas relevantes para a conservação. Através do uso de armadilhagem fotográfica, foram estudadas relações espécies-habitats para 5 espécies: gato-bravo (Felis silvestris), fuinha (Martes foina), raposa (Vulpes vulpes), gineta (Genetta genetta), e sacarrabos (Herpestes ichneumon). Foram desenvolvidos métodos para se determinar a densidade absoluta de raposa e gineta e a população de gato-bravo foi estudada em detalhe. As principais conclusões do estudo foram: 1) a ocupação de raposas é uniforme e parece ser independente de variáveis ambientais; 2) a ocupação de fuinha encontra-se relacionada com variáveis de habitat, estrutura paisagística e presas; 3) a ocupação de gineta está relacionada com a cobertura de folhosas e distribuição de presas; 4) para o sacarrabos verificase que a ocupação é influenciada pelas extensões de habitat arbustivos, 5) a população de gato-bravo sofreu um forte declínio durante o trabalho e requer urgentes medidas de conservação. Metodologicamente foi demonstrada a importância da modelação das probabilidades de detecção para espécies para as quais este parâmetros apresenta valores baixos ou é muito variável. Esta tese também demonstrou a grande importância da Serra da Malcata para a conservação de carnívoros e a necessidade do desenvolvimento de técnicas de monitorização padronizadas para uma correcta gestão adaptativa das áreas protegidas.

Managing Risk in a Culture of Rights: Providing Support and Treatment in Community-Based Settings for Persons with Intellectual Disabilities who Sexually Offend

People with intellectual disability who sexually offend commonly live in community-based settings since the closing of all institutions across the province of Ontario. Nine (n=9) front line staff who provide support to these individuals in three different settings (treatment setting, transitional setting, residential setting) were interviewed. Participants responded to 47 questions to explore how sex offenders with intellectual disability can be supported in the community to prevent re-offenses. Questions encompassed variables that included staff attitudes, various factors impacting support, structural components of the setting, quality of life and the good life, staff training, staff perspectives on treatment, and understanding of risk management. Three overlapping models that have been supported in the literature were used collectively for the basis of this research: The Good Lives Model (Ward & Gannon, 2006; Ward et al., 2007), the quality of life model (Felce & Perry, 1995), and variables associated with risk management. Results of this research showed how this population is being supported in the community with an emphasis on the following elements: positive and objective staff attitude, teamwork, clear rules and protocols, ongoing supervision, consistency, highly trained staff, and environments that promote quality of life. New concepts arose which suggested that all settings display an unequal balance of upholding human rights and managing risks when supporting this high-risk population. This highlights the need for comprehensive assessments in order to match the offender to the proper setting and supports, using an integration of a Risk, Need, Responsivity model and the Good Lives model for offender rehabilitation and to reduce the likelihood of re-offenses.

Advances in therapeutic risk management through signal detection and risk minimisation tool analyses

Les quatre principales activités de la gestion de risque thérapeutique comportent l’identification, l’évaluation, la minimisation, et la communication du risque. Ce mémoire aborde les problématiques liées à l’identification et à la minimisation du risque par la réalisation de deux études dont les objectifs sont de: 1) Développer et valider un outil de « data mining » pour la détection des signaux à partir des banques de données de soins de santé du Québec; 2) Effectuer une revue systématique afin de caractériser les interventions de minimisation de risque (IMR) ayant été implantées. L’outil de détection de signaux repose sur la méthode analytique du quotient séquentiel de probabilité (MaxSPRT) en utilisant des données de médicaments délivrés et de soins médicaux recueillis dans une cohorte rétrospective de 87 389 personnes âgées vivant à domicile et membres du régime d’assurance maladie du Québec entre les années 2000 et 2009. Quatre associations « médicament-événement indésirable (EI) » connues et deux contrôles « négatifs » ont été utilisés. La revue systématique a été faite à partir d’une revue de la littérature ainsi que des sites web de six principales agences réglementaires. La nature des RMIs ont été décrites et des lacunes de leur implémentation ont été soulevées. La méthode analytique a mené à la détection de signaux dans l'une des quatre combinaisons médicament-EI. Les principales contributions sont: a) Le premier outil de détection de signaux à partir des banques de données administratives canadiennes; b) Contributions méthodologiques par la prise en compte de l'effet de déplétion des sujets à risque et le contrôle pour l'état de santé du patient. La revue a identifié 119 IMRs dans la littérature et 1,112 IMRs dans les sites web des agences réglementaires. La revue a démontré qu’il existe une augmentation des IMRs depuis l’introduction des guides réglementaires en 2005 mais leur efficacité demeure peu démontrée.

Detecting local adaptation in widespread grassland species - the importance of scale and local plant community

1 Adaptation of plant populations to local environments has been shown in many species but local adaptation is not always apparent and spatial scales of differentiation are not well known. In a reciprocal transplant experiment we tested whether: (i) three widespread grassland species are locally adapted at a European scale; (ii) detection of local adaptation depends on competition with the local plant community; and (iii) local differentiation between neighbouring populations from contrasting habitats can be stronger than differentiation at a European scale. 2 Seeds of Holcus lanatus, Lotus corniculatus and Plantago lanceolata from a Swiss, Czech and UK population were sown in a reciprocal transplant experiment at fields that exhibit environmental conditions similar to the source sites. Seedling emergence, survival, growth and reproduction were recorded for two consecutive years. 3 The effect of competition was tested by comparing individuals in weeded monocultures with plants sown together with species from the local grassland community. To compare large-scale vs. small-scale differentiation, a neighbouring population from a contrasting habitat (wet-dry contrast) was compared with the 'home' and 'foreign' populations. 4 In P. lanceolata and H. lanatus, a significant home-site advantage was detected in fitness-related traits, thus indicating local adaptation. In L. corniculatus, an overall superiority of one provenance was found. 5 The detection of local adaptation depended on competition with the local plant community. In the absence of competition the home-site advantage was underestimated in P. lanceolata and overestimated in H. lanatus. 6 A significant population differentiation between contrasting local habitats was found. In some traits, this small-scale was greater than large-scale differentiation between countries. 7 Our results indicate that local adaptation in real plant communities cannot necessarily be predicted from plants grown in weeded monocultures and that tests on the relationship between fitness and geographical distance have to account for habitat-dependent small-scale differentiation. Considering the strong small-scale differentiation, a local provenance from a different habitat may not be the best choice in ecological restoration if distant populations from a more similar habitat are available.

Benchmark datasets for detection and tracking

There is a rising demand for the quantitative performance evaluation of automated video surveillance. To advance research in this area, it is essential that comparisons in detection and tracking approaches may be drawn and improvements in existing methods can be measured. There are a number of challenges related to the proper evaluation of motion segmentation, tracking, event recognition, and other components of a video surveillance system that are unique to the video surveillance community. These include the volume of data that must be evaluated, the difficulty in obtaining ground truth data, the definition of appropriate metrics, and achieving meaningful comparison of diverse systems. This chapter provides descriptions of useful benchmark datasets and their availability to the computer vision community. It outlines some ground truth and evaluation techniques, and provides links to useful resources. It concludes by discussing the future direction for benchmark datasets and their associated processes.