Part-whole relations between food webs and the validity of local food-web descriptions

This work analyzes the relationship between large food webs describing potential feeding relations between species and smaller sub-webs thereof describing relations actually realized in local communities of various sizes. Special attention is given to the relationships between patterns of phylogenetic correlations encountered in large webs and sub-webs. Based on the current theory of food-web topology as implemented in the matching model, it is shown that food webs are scale invariant in the following sense: given a large web described by the model, a smaller, randomly sampled sub-web thereof is described by the model as well. A stochastic analysis of model steady states reveals that such a change in scale goes along with a re-normalization of model parameters. Explicit formulae for the renormalized parameters are derived. Thus, the topology of food webs at all scales follows the same patterns, and these can be revealed by data and models referring to the local scale alone. As a by-product of the theory, a fast algorithm is derived which yields sample food webs from the exact steady state of the matching model for a high-dimensional trophic niche space in finite time. (C) 2008 Elsevier B.V. All rights reserved.

Some properties of the speciation model for food-web structure - Mechanisms for degree distributions and intervality

We present a mathematical analysis of the speciation model for food-web structure, which had in previous work been shown to yield a good description of empirical data of food-web topology. The degree distributions of the network are derived. Properties of the speciation model are compared to those of other models that successfully describe empirical data. It is argued that the speciation model unities the underlying ideas of previous theories. In particular, it offers a mechanistic explanation for the success of the niche model of Williams and Martinez and the frequent observation of intervality in empirical food webs. (c) 2005 Elsevier Ltd. All rights reserved.

Response characteristics of optical sensors for oxygen: models based on a distribution in tau(o) or kappa(q)

The features of two popular models used to describe the observed response characteristics of typical oxygen optical sensors based on luminescence quenching are examined critically. The models are the 'two-site' and 'Gaussian distribution in natural lifetime, tau(o),' models. These models are used to characterise the response features of typical optical oxygen sensors; features which include: downward curving Stern-Volmer plots and increasingly non-first order luminescence decay kinetics with increasing partial pressures of oxygen, pO(2). Neither model appears able to unite these latter features, let alone the observed disparate array of response features exhibited by the myriad optical oxygen sensors reported in the literature, and still maintain any level of physical plausibility. A model based on a Gaussian distribution in quenching rate constant, k(q), is developed and, although flawed by a limited breadth in distribution, rho, does produce Stern-Volmer plots which would cover the range in curvature seen with real optical oxygen sensors. A new 'log-Gaussian distribution in tau(o) or k(q)' model is introduced which has the advantage over a Gaussian distribution model of placing no limitation on the value of rho. Work on a 'log-Gaussian distribution in tau(o)' model reveals that the Stern-Volmer quenching plots would show little degree in curvature, even at large rho values and the luminescence decays would become increasingly first order with increasing pO(2). In fact, with real optical oxygen sensors, the opposite is observed and thus the model appears of little value. In contrast, a 'log-Gaussian distribution in k(o)' model does produce the trends observed with real optical oxygen sensors; although it is technically restricted in use to those in which the kinetics of luminescence decay are good first order in the absence of oxygen. The latter model gives a good fit to the major response features of sensors which show the latter feature, most notably the [Ru(dpp)(3)(2+)(Ph4B-)(2)] in cellulose optical oxygen sensors. The scope of a log-Gaussian model for further expansion and, therefore, application to optical oxygen sensors, by combining both a log-Gaussian distribution in k(o) with one in tau(o) is briefly discussed.

The Library of Essays on Law and Privacy

Privacy has now become a major topic not only in law but in computing, psychology, economics and social studies, and the explosion in scholarship has made it difficult for the student to traverse the field and identify the significant issues across the many disciplines. This series brings together a collection of significant papers with a multi-disciplinary approach which enable the reader to navigate through the complexities of the issues and make sense of the prolific scholarship published in this field.

The three volumes in this series address different themes: an anthropological approach to what privacy means in a cultural context; the issue of state surveillance where the state must both protect the individual and protect others from that individual and also protect itself; and, finally, what privacy might mean in a world where government and commerce collect data incessantly. The regulation of privacy is continually being called for and these papers help enable understanding of the ethical rationales behind the choices made in the sphere of regulation of privacy.

The articles presented in each of these collections have been chosen for the quality of their scholarship and their utility to the researcher, and feature a variety of approaches. The articles which debate the technical context of privacy are accessible to those from the arts and humanities; overall, the breadth of approach taken in the choice of articles has created a series which is an invaluable and important resource for lecturers, researchers and student.

Detecting the effects of diversity on measures of ecosystem function: experimental design, null models and empirical observations

Here we present a novel experimental approach to examine the relationship between diversity and ecosystem Function. We develop four null predictive models, with which to differentiate between the 'sampling effect' - the chance inclusion of a highly productive species, and 'species complementarity' - the complementary use of resources by species that differ in their niche or resource use. We investigate the effects of manipulating species and functional richness on ecosystem function in marine benthic system and using empirical data from our own experiments we illustrate the application of these models.

A Decade of Burkholderia cenocepacia Virulence Determinant Research

The Burkholderia cepacia complex (Bcc) is a group of genetically related environmental bacteria that can cause chronic opportunistic infections in patients with cystic fibrosis (CF) and other underlying diseases. These infections are difficult to treat due to the inherent resistance of the bacteria to antibiotics. Bacteria can spread between CF patients through social contact and sometimes cause cepacia syndrome, a fatal pneumonia accompanied by septicemia. Burkholderia cenocepacia has been the focus of attention because initially it was the most common Bcc species isolated from patients with CF in North America and Europe. Today, B. cenocepacia, along with Burkholderia multivorans, is the most prevalent Bcc species in patients with CF. Given the progress that has been made in our understanding of B. cenocepacia over the past decade, we thought that it was an appropriate time to review our knowledge of the pathogenesis of B. cenocepacia, paying particular attention to the characterization of virulence determinants and the new tools that have been developed to study them. A common theme emerging from these studies is that B. cenocepacia establishes chronic infections in immuno-compromised patients, which depend more on determinants mediating host niche adaptation than those involved directly in host cells and tissue damage.

Optimal diet choice for large herbivores: an extended contingency model

1. A more general contingency model of optimal diet choice is developed, allowing for simultaneous searching and handling, which extends the theory to include grazing and browsing by large herbivores.</p><p>2. Foraging resolves into three modes: purely encounter-limited, purely handling-limited and mixed-process, in which either a handling-limited prey type is added to an encounter-limited diet, or the diet becomes handling-limited as it expands.</p><p>3. The purely encounter-limited diet is, in general, broader than that predicted by the conventional contingency model,</p><p>4. As the degree of simultaneity of searching and handling increases, the optimal diet expands to the point where it is handling-limited, at which point all inferior prey types are rejected,</p><p>5. Inclusion of a less profitable prey species is not necessarily independent of its encounter rate and the zero-one rule does not necessarily hold: some of the less profitable prey may be included in the optimal diet. This gives an optimal foraging explanation for herbivores' mixed diets.</p><p>6. Rules are shown for calculating the boundary between encounter-limited and handling-limited diets and for predicting the proportion of inferior prey to be included in a two-species diet,</p><p>7. The digestive rate model is modified to include simultaneous searching and handling, showing that the more they overlap, the more the predicted diet-breadth is likely to be reduced.</p>

Species introduction promotes hybridization and introgression in Coregonus: is there sign of selection against hybrids?

Species introductions are considered one of the major drivers of biodiversity loss via ecological interactions and genetic admixture with local fauna. We examined two well-recognized fish species, native whitefish (Coregonus lavaretus) and introduced vendace (Coregonus albula), as well as their morphological hybrids in a single lake to test for selection against hybrids and backcrosses in the wild. A representative random subsample of 693 individuals (27.8%) was taken from the total catch of coregonids. This subsample was examined with the aim to select c. 50 individuals of pure whitefish (n = 52), pure vendace (n = 55) and putative hybrid (n = 19) for genetic analyses. The subsequent microsatellites and mitochondrial (mt) DNA analyses provided compelling evidence of hybridization and introgression. Of the 126 fish examined, four were found to be F-1, 14 backcrosses to whitefish and seven backcrosses to vendace. The estimates of historical gene flow suggested higher rates from introduced vendace into native whitefish than vice versa, whereas estimates of contemporary gene flow were equal. Mitochondrial introgression was skewed, with 18 backcrosses having vendace mtDNA and only three with whitefish mtDNA. Hybrids and backcrosses had intermediate morphology and niche utilization compared with parental species. No evidence of selection against hybrids or backcrosses was apparent, as both hybrid and backcross growth rates and fecundities were high. Hybrids (F-1) were only detected in 2 year-classes, suggesting temporal variability in mating between vendace and whitefish. However, our data show that hybrids reached sexual maturity and reproduced actively, with backcrosses recorded from six consecutive year-classes, whereas no F-2 individuals were found. The results indicate widespread introgression, as 10.8% of coregonids were estimated to be backcrosses.

A silicone elastomer vaginal ring for HIV prevention containing two microbicides with different mechanisms of action

Vaginal rings are currently being developed for the long-term (at least 30 days) continuous delivery of microbicides against human immunodeficiency virus (HIV). Research to date has mostly focused on devices containing a single antiretroviral compound, exemplified by the 25 mg dapivirine ring currently being evaluated in a Phase III clinical study. However, there is a strong clinical rationale for combining antiretrovirals with different mechanisms of action in a bid to increase breadth of protection and limit the emergence of resistant strains. Here we report the development of a combination antiretroviral silicone elastomer matrix-type vaginal ring for simultaneous controlled release of dapivirine, a non-nucleoside reverse transcriptase inhibitor, and maraviroc, a CCR5-targeted HIV-1 entry inhibitor. Vaginal rings loaded with 25 mg dapivirine and various quantities of maraviroc (50– 400 mg) were manufactured and in vitro release assessed. The 25 mg dapivirine and 100 mg maraviroc formulation was selected for further study. A 24-month pharmaceutical stability evaluation was conducted, indicating good product stability in terms of in vitro release, content assay, mechanical properties and related substances. This combination ring product has now progressed to Phase I clinical testing.

Incorporating uncertainty in predictive species distribution modelling

Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.

Hierarchical Bayesian models in ecology: Reconstructing species interaction networks from non-homogeneous species abundance data

The relationships among organisms and their surroundings can be of immense complexity. To describe and understand an ecosystem as a tangled bank, multiple ways of interaction and their effects have to be considered, such as predation, competition, mutualism and facilitation. Understanding the resulting interaction networks is a challenge in changing environments, e.g. to predict knock-on effects of invasive species and to understand how climate change impacts biodiversity. The elucidation of complex ecological systems with their interactions will benefit enormously from the development of new machine learning tools that aim to infer the structure of interaction networks from field data. In the present study, we propose a novel Bayesian regression and multiple changepoint model (BRAM) for reconstructing species interaction networks from observed species distributions. The model has been devised to allow robust inference in the presence of spatial autocorrelation and distributional heterogeneity. We have evaluated the model on simulated data that combines a trophic niche model with a stochastic population model on a 2-dimensional lattice, and we have compared the performance of our model with L1-penalized sparse regression (LASSO) and non-linear Bayesian networks with the BDe scoring scheme. In addition, we have applied our method to plant ground coverage data from the western shore of the Outer Hebrides with the objective to infer the ecological interactions. (C) 2012 Elsevier B.V. All rights reserved.

An integrated transcriptomics and proteomics analysis of the secretome of the helminth pathogen Fasciola hepatica: Proteins associated with invasion and infection of the mammalian host

To infect their mammalian hosts, Fasciola hepatica larvae must penetrate and traverse the intestinal wall of the duodenum, move through the peritoneum, and penetrate the liver. After migrating through and feeding on the liver, causing extensive tissue damage, the parasites move to their final niche in the bile ducts where they mature and produce eggs. Here we integrated a transcriptomics and proteomics approach to profile Fasciola secretory proteins that are involved in host-pathogen interactions and to correlate changes in their expression with the migration of the parasite. Prediction of F. hepatica secretory proteins from 14,031 expressed sequence tags (ESTs) available from the Wellcome Trust Sanger Centre using the semiautomated EST2Secretome pipeline showed that the major components of adult parasite secretions are proteolytic enzymes including cathepsin L, cathepsin B, and asparaginyl endopeptidase cysteine proteases as well as novel trypsin-like serine proteases and carboxypeptidases. Proteomics analysis of proteins secreted by infective larvae, immature flukes, and adult F. hepatica showed that these proteases are developmentally regulated and correlate with the passage of the parasite through host tissues and its encounters with different host macromolecules. Proteases such as FhCL3 and cathepsin B have specific functions in larvae activation and intestinal wall penetration, whereas FhCL1, FhCL2, and FhCL5 are required for liver penetration and tissue and blood feeding. Besides proteases, the parasites secrete an array of antioxidants that are also highly regulated according to their migration through host tissues. However, whereas the proteases of F. hepatica are secreted into the parasite gut via a classical endoplasmic reticulum/Golgi pathway, we speculate that the antioxidants, which all lack a signal sequence, are released via a non-classical trans-tegumental pathway.

Predicting the impacts of climate change on the distribution of threatened forest-restricted birds in Madagascar

The greatest common threat to birds in Madagascar has historically been from anthropogenic deforestation. During recent decades, global climate change is now also regarded as a significant threat to biodiversity. This study uses Maximum Entropy species distribution modeling to explore how potential climate change could affect the distribution of 17 threatened forest endemic bird species, using a range of climate variables from the Hadley Center's HadCM3 climate change model, for IPCC scenario B2a, for 2050. We explore the importance of forest cover as a modeling variable and we test the use of pseudo-presences drawn from extent of occurrence distributions. Inclusion of the forest cover variable improves the models and models derived from real-presence data with forest layer are better predictors than those from pseudo-presence data. Using real-presence data, we analyzed the impacts of climate change on the distribution of nine species. We could not predict the impact of climate change on eight species because of low numbers of occurrences. All nine species were predicted to experience reductions in their total range areas, and their maximum modeled probabilities of occurrence. In general, species range and altitudinal contractions follow the reductive trend of the Maximum presence probability. Only two species (Tyto soumagnei and Newtonia fanovanae) are expected to expand their altitude range. These results indicate that future availability of suitable habitat at different elevations is likely to be critical for species persistence through climate change. Five species (Eutriorchis astur, Neodrepanis hypoxantha, Mesitornis unicolor, Euryceros prevostii, and Oriola bernieri) are probably the most vulnerable to climate change. Four of them (E. astur, M. unicolor, E. prevostii, and O. bernieri) were found vulnerable to the forest fragmentation during previous research. Combination of these two threats in the future could negatively affect these species in a drastic way. Climate change is expected to act differently on each species and it is important to incorporate complex ecological variables into species distribution models.

Live Project love: building a framework for Live Projects

Live projects adopt a wide range of approaches: design/ build, community engagement, participation, protest, analysis, etc. They are driven by tutors with passion, expertise and the ability to manage risk, in ways that exhibit fluency and high levels of skill. They also offer sites of student-led and community co-learning, can support research, demonstrate ‘impact’ and satisfy universities’ policies on outreach. Whilst the breadth and reach of Live Projects is now demonstrably wide, we still fail to fully locate Live Projects within a pedagogical context, tending instead to limit our descriptions and hence analysis to the architectural process and outcome. This failure to locate Live Projects within a pedagogical framework means we still struggle to encapsulate, critique, progress, and indeed, elevate the work.

This chapter draws on some of the case studies presented in recent papers and international conferences in order to provide educators with signposts and important overviews around which and in respect to they can develop their own pedagogical frameworks.