Michael Begon

Bio: Michael Begon is an academic researcher from University of Liverpool. The author has contributed to research in topics: Population & Field vole. The author has an hindex of 67, co-authored 255 publications receiving 21625 citations. Previous affiliations of Michael Begon include University of Oslo & New York Botanical Garden.

Ecology: Individuals Populations and Communities

Abstract: A revised and updated edition of this textbook. As before the study of plant and animal ecology is fully integrated and mathematical and laborotory studies are described where necessary. Examples drawn from real ecological systems ilustrate the complexity of this subject and the involvement of diverse areas: descriptive natural history, physiology, behaviour, field experimentation and mathematical modelling. The authors attempt to encourage the reader to combine all the above facets, so that a balanced view emerges. Emphasis is placed on the clear presentation of mathematical aspects and the material aims to be accessible to the undergraduate with little experience and also stimulating to practising ecologists. This new edition contains two new chapters both of which consider areas of applied ecology which are relevant to contemporary global issues. The first considers the control of abundance; on the one hand the limiting of pest and weed populations, on the other, maintaining the biological diversity of endangered species. The second considers large areas as an extension of the discussion of communities. These "ecosystems" in the newest sense of the word are an important field of study when considering some of the important environmental problems facing mankind.

Ecology: From Individuals to Ecosystems

Abstract: Preface.Introduction.Part 1. ORGANISMS .1. Organisms in their environments: the evolutionary backdrop.2. Conditions.3. Resources.4. Life, death and life histories.5. Intraspecific competition.6. Dispersal, dormancy and metapopulations.7. Ecological applications at the level of organisms and single-species populations Part 2. SPECIES INTERACTIONS.8. Interspecific competition.9. The nature of predation.10. The population dynamics of predation.11. Decomposers and detritivores.12. Parasitism and disease.13. Symbiosis and mutualism.14. Abundance.15. Ecological applications at the level of population interactions Part 3. COMMUNITIES AND ECOSYSTEMS .16. The nature of the community.17. The flux of energy through ecosystems.18. The flux of matter through ecosystems.19. The influence of population interactions on community structure.20. Food webs.21. Patterns in species richness.22. Ecological applications at the level of communities and ecosystems.References.Organism Index.Subject Index

Optimal egg size and clutch size: effects of environment and maternal phenotype

Abstract: In this paper, we develop a series of models for predicting optimal egg size and clutch size in different environments and for different maternal phenotypes. The models investigate the interaction between three components of fitness: (1) the intrinsic effect of egg size, (2) the density effect, the effect of the density of competing offspring (including competition with sibs and with non-sibs), and (3) the hierarchy effect, the effect of egg size relative to the sizes of competing eggs laid by other females. The environmental effects that we consider are the intensities of sib and non-sib competition, the number of egg-laying females, and some aspects of seasonal development. The particular aspects of maternal phenotype examined are foraging efficiency and the gametic reserve available at the time of egg laying (broadly equivalent to female size). Regarding environmental effects, increasing intensities of sib competition select for the production of smaller clutches of larger eggs, and increasing intensit...

Species interactions in a parasite community drive infection risk in a wildlife population

Abstract: Most hosts, including humans, are simultaneously or sequentially infected with several parasites. A key question is whether patterns of coinfection arise because infection by one parasite species affects susceptibility to others or because of inherent differences between hosts. We used time-series data from individual hosts in natural populations to analyze patterns of infection risk for a microparasite community, detecting large positive and negative effects of other infections. Patterns remain once variations in host susceptibility and exposure are accounted for. Indeed, effects are typically of greater magnitude, and explain more variation in infection risk, than the effects associated with host and environmental factors more commonly considered in disease studies. We highlight the danger of mistaken inference when considering parasite species in isolation rather than parasite communities.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

Experimental Design and Data Analysis for Biologists

Abstract: An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models Multivariate techniques, including classification and ordination, are then introduced Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature The book is supported by a website that provides all data sets, questions for each chapter and links to software

Generalized linear mixed models: a practical guide for ecology and evolution

Abstract: How should ecologists and evolutionary biologists analyze nonnormal data that involve random effects? Nonnormal data such as counts or proportions often defy classical statistical procedures. Generalized linear mixed models (GLMMs) provide a more flexible approach for analyzing nonnormal data when random effects are present. The explosion of research on GLMMs in the last decade has generated considerable uncertainty for practitioners in ecology and evolution. Despite the availability of accurate techniques for estimating GLMM parameters in simple cases, complex GLMMs are challenging to fit and statistical inference such as hypothesis testing remains difficult. We review the use (and misuse) of GLMMs in ecology and evolution, discuss estimation and inference and summarize 'best-practice' data analysis procedures for scientists facing this challenge.

Pharmaceuticals, hormones, and other organic wastewater contaminants in U.S. streams, 1999-2000: a national reconnaissance.

Abstract: To provide the first nationwide reconnaissance of the occurrence of pharmaceuticals, hormones, and other organic wastewater contaminants (OWCs) in water resources, the U.S. Geological Survey used five newly developed analytical methods to measure concentrations of 95 OWCs in water samples from a network of 139 streams across 30 states during 1999 and 2000. The selection of sampling sites was biased toward streams susceptible to contamination (i.e. downstream of intense urbanization and livestock production). OWCs were prevalent during this study, being found in 80% of the streams sampled. The compounds detected represent a wide range of residential, industrial, and agricultural origins and uses with 82 of the 95 OWCs being found during this study. The most frequently detected compounds were coprostanol (fecal steroid), cholesterol (plant and animal steroid), N,N-diethyltoluamide (insect repellant), caffeine (stimulant), triclosan (antimicrobial disinfectant), tri(2-chloroethyl)phosphate (fire retardant), and 4-nonylphenol (nonionic detergent metabolite). Measured concentrations for this study were generally low and rarely exceeded drinking-water guidelines, drinking-water health advisories, or aquatic-life criteria. Many compounds, however, do not have such guidelines established. The detection of multiple OWCs was common for this study, with a median of seven and as many as 38 OWCs being found in a given water sample. Little is known about the potential interactive effects (such as synergistic or antagonistic toxicity) that may occur from complex mixtures of OWCs in the environment. In addition, results of this study demonstrate the importance of obtaining data on metabolites to fully understand not only the fate and transport of OWCs in the hydrologic system but also their ultimate overall effect on human health and the environment.