The effects of urbanization on the avian gut microbiome

The gut microbiome influences and is influenced by the host, and can affect the host organism by contributing to health, development and immunity. Similarly, the host can influence this community; it’s makeup can vary with host species, locality, diet, social stressors, and environmental stressors. Some of these environmental stressors have arisen due to human-induced rapid environmental change, like urbanization. The physiology and behaviors of organisms that are able to persist in urban environments are often different from their non-urban congeners. Nutrition, development, and immunity—all of which are affected by the gut microbiome—are important factors that can determine survival in urban environments. Ecologists are therefore asking new questions about how an urban environment shapes gut microbial communities, and how the numerous services gut fauna provide affect host success in an urban context. My dissertation research demonstrated that urbanization changes the bacterial communities of birds as well as provided correlational and experimental evidence for the biotic and abiotic traits driving these changes. Urban birds differed from rural ones by multiple measures. I also found evidence that noise pollution explains some variation in alpha diversity among urban and rural birds. Building upon this finding, I experimentally showed that the gut microbiome changes with exposure to noise, as does food intake and plasma corticosterone. However, contrary to my hypothesis, food intake and corticosterone were not the mediating factors between noise and the gut microbiome. All of this work was accomplished using noninvasive cloacal swabs to measure the gut microbiome, which my dissertation research found are reflective of the large intestine and capture individual variation in the microbiome. The work that comprised my dissertation will impact methods decisions in future microbiome studies in both free-living and captive birds. It will also contribute to the way we look at the relationships between host environment, host, and the gut microbiome, as well as influence how we think about urban ecology as a whole. Altogether, my dissertation research accomplished my goal to work in an emerging field at the interface of urban and microbial ecology

The Class Action As Political Theory

We have two goals in this Article. Initially, we seek to alter the nature of the class action debate, by expressly inserting the perspective of political theory. Recognizing how the modern class action is structured may have significant consequences for the foundations of normative political theory, we hope to remove the theoretical superficiality that has characterized much of the modern scholarly debate concerning class actions. While on occasion that debate has touched on questions of political theory, those references are generally superficial or misguided. At the very least, then, we hope to establish that acceptance of one or the other of the scholarly models of the class action necessarily brings with it significant political baggage. Second, we hope to convince the reader that, when viewed from this perspective, all class action models that have been proposed to this point should be rejected because they ignore, undermine, or dilute fundamental notions of process-based individual autonomy

A comprehensive weighted evolving network model

Many social, technological, biological, and economical systems are best described by weighted networks, whose properties and dynamics depend not only on their structures but also on the connection weights among their nodes. However, most existing research work on complex network models are concentrated on network structures, with connection weights among their nodes being either 1 or 0. In this paper, we propose a new weighted evolving network model. Numerical simulations indicate that this network model yields three power-law distributions of the node degrees, connection weights and node strengths. Particularly, some other properties of the distributions, such as the droop-head and heavy-tail effects, can also be reflected by this model.Comment: 6 pages, 4 figures, accepted by Physica

Consumption-Based Conservation Targeting: Linking Biodiversity Loss to Upstream Demand through a Global Wildlife Footprint.

Although most conservation efforts address the direct, local causes of biodiversity loss, effective long-term conservation will require complementary efforts to reduce the upstream economic pressures, such as demands for food and forest products, which ultimately drive these downstream losses. Here, we present a wildlife footprint analysis that links global losses of wild birds to consumer purchases across 57 economic sectors in 129 regions. The United States, India, China, and Brazil have the largest regional wildlife footprints, while per-person footprints are highest in Mongolia, Australia, Botswana, and the United Arab Emirates. A US$100 purchase of bovine meat or rice products occupies approximately 0.1 km2 of wild bird ranges, displacing 1-2 individual birds, for 1 year. Globally significant importer regions, including Japan, the United Kingdom, Germany, Italy, and France, have large footprints that drive wildlife losses elsewhere in the world and represent important targets for consumption-focused conservation attention

Intersection Bodies of Polytopes

We investigate the intersection body of a convex polytope using tools from combinatorics and real algebraic geometry. In particular, we show that the intersection body of a polytope is always a semialgebraic set and provide an algorithm for its computation. Moreover, we compute the irreducible components of the algebraic boundary and provide an upper bound for the degree of these components.Comment: As published in Beitr\"age zur Algebra und Geometrie. Correction of a scaling factor from previous versio

Predicting invasion success in complex ecological networks

A central and perhaps insurmountable challenge of invasion ecology is to predict which combinations of species and habitats most effectively promote and prevent biological invasions. Here, we integrate models of network structure and nonlinear population dynamics to search for potential generalities among trophic factors that may drive invasion success and failure. We simulate invasions where 100 different species attempt to invade 150 different food webs with 15–26 species and a wide range (0.06–0.32) of connectance. These simulations yield 11 438 invasion attempts by non-basal species, 47 per cent of which are successful. At the time of introduction, whether or not the invader is a generalist best predicts final invasion success; however, once the invader establishes itself, it is best distinguished from unsuccessful invaders by occupying a lower trophic position and being relatively invulnerable to predation. In general, variables that reflect the interaction between an invading species and its new community, such as generality and trophic position, best predict invasion success; however, for some trophic categories of invaders, fundamental species traits, such as having the centre of the feeding range low on the theoretical niche axis (for non-omnivorous and omnivorous herbivores), or the topology of the food web (for tertiary carnivores), best predict invasion success. Across all invasion scenarios, a discriminant analysis model predicted successful and failed invasions with 76.5 per cent accuracy for properties at the time of introduction or 100 per cent accuracy for properties at the time of establishment. More generally, our results suggest that tackling the challenge of predicting the properties of species and habitats that promote or inhibit invasions from food web perspective may aid ecologists in identifying rules that govern invasions in natural ecosystems

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 unifies 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.Comment: 23 pages, 6 figures, minor rewrite