This course is being provided through a collaboration of PR statistics and Proteus and will be delivered by Dr. Darryl MacKenzie Course Overview: The presence or absence of a species across a set of landscape units is a fundamental concept widely used in ecology (e.g., species range or distribution, epidemiology, habitat modeling, resource selection probability functions, as a monitoring metric, metapopulation studies, biodiversity and species co-occurrence). An important sampling issue, however, is that a species may not always be detected…

Course Overview: This workshop will provide students with the opportunity to learn how to use social network analysis to analyze social relational datasets such as human friendship networks or animal social networks. Attendees will learn how to use R and several R packages including igraph, sna, network, asnipe, timeordered, tsna to create network graphs, calculate descriptive network metrics, use randomization and random models to evaluate the significance of these metrics, determine graph structural properties including community structures, use QAP and…

Course Overview: This course will provide an introduction to modern multivariate techniques, with a special focus on the analysis of abundance or presence/absence data. Multivariate analysis in ecology has been changing rapidly in recent years, with a focus now on formulating a statistical model to capture key properties of the observed data, rather than transformation of data using a dissimilarity-based framework. In recent years, model-based techniques have been developed for hypothesis testing, identifying indicator species, ordination, clustering, predictive modelling, and…

Course Overview: Metabarcoding techniques are a set of novel genetic tools for assessing biodiversity of natural communities. Their potential applications include (but are not limited to) accurate water quality, soil diversity assessment, trophic analyses of digestive contents, early detection of non-indigenous species, studies of global ecological patterns and biomonitoring of anthropogenic impacts. This course will give an overview of metabarcoding procedures with an emphasis on practical problem-solving and hands-on work using analysis pipelines on real datasets. After completing the course,…

About The next International Seabird Group Conference is being organised by Jon Green and Samantha Patrick and colleagues from the University of Liverpool. The conference promises to provide an exciting showcase of the latest seabird research, located within the heart of the city of Liverpool, famous for its maritime history and cultural diversity. Keynote speakers and early career events will compliment two and a half days of talks and posters, covering all aspects of seabird research. The Seabird Group registered…

Course Overview: Most high-throughput bioinformatics work these days takes place on the Linux command line. The programs which do the majority of the computational heavy lifting — genome assemblers, read mappers, and annotation tools — are designed to work best when used with a command-line interface. Because the command line can be an intimidating environment, many biologists learn the bare minimum needed to get their analysis tools working. This means that they miss out on the power of Linux to…

Course Overview: This course will cover time series analysis with a particular focus on applications in ecology. All methods will be illustrated using the free, open-source software package R. The course is designed for attendees that have a basic knowledge of R and elementary statistics but not necessarily time series. Time Series data are ubiquitous in the physical sciences, and models for their behaviour enable scientists to understand temporal dynamics and predict future values. The course will cover a range…

Course Overview: This course will cover introductory mixed or hierarchical modelling (fixed and random effects models) for real-world data sets from both a Frequentist and Bayesian perspective. These methods lie at the forefront of statistics research and are a vital tool in the scientist’s toolbox. The course focuses on introducing concepts and demonstrating good practice in mixed modelling. All methods are demonstrated with data sets which participants can run themselves. Participants will be taught how to fit hierarchical models using both the standard lme4…

Course Overview: This application-driven course will provide a founding in the basic theory & practice of Bayesian statistics, with a focus on MCMC modeling for ecological & epidemiological problems. Starting from a refresher on probability & likelihood, the course will take students all the way to cutting-edge applications such as state-space population modelling & spatial point-process modelling. By the end of the week, you should have a basic understanding of how common MCMC samplers work and how to program them,…

Course Overview: Analysis of high throughput genome and transcriptome data is major component of many research projects ranging from large-scale precision medicine efforts to focused investigations in model systems. This analysis involves the identification of specific genome or transcriptome features that predispose individuals to disease, predict response to therapies, influence diagnosis/prognosis, or provide mechanistic insights into disease models. During this course (PMBI01), students will perform an example end-to-end bioinformatics analysis of genome (WGS and Exome) and transcriptome (RNA-seq) data. Students…

Course overview:  The course will consist of a series of 8 modules each lasting roughly half a day, and designed to build required skills for subsequent modules and more advanced courses. At its conclusion, participants will have acquired basic skills in coding with R, and will be able to perform and interpret simple analyses, and critically evaluate similar analyses from the scientific literature and technical reports. Intended Audience The course is aimed at biologists with no experience using the software…

Course Overview: Phylogenetic comparative methods are commonly used nowadays to investigate how species diversification occurs and to test hypotheses about the mechanisms that drive phenotypic evolution, e.g. to model speciation and extinction, to understand why some groups are more diverse than others, to test whether phenotypic traits have evolved under neutral, directional or diversifying selection, to investigate how evolutionary rates are modified across the evolutionary history of a group etc. In all these cases, a phylogenetic hypothesis for the group…

This theoretical course on stable isotope geochemistry in earth and life sciences will take place from the 6th -7th  November 2018 at the SUERC facility (https://www.gla.ac.uk/research/az/suerc/), Rankine Avenue, Scottish Enterprise Technology Park, East Kilbride, UK. Further information can be found at https://www.gla.ac.uk/research/az/suerc/contactus/ Or email Rona McGill (rona.mcgill@glasgow.ac.uk) or Jason Newton (jason.newton@glasgow.ac.uk). Please do not direct questions to PR statistics   “This was by far the most useful statistic-related course I’ve done to date and I enjoyed all aspects of the course.…

Course Overview: The course will describe different aspects and methods in the field of functional ecology, combining theoretical lessons with hands-on real data. Lectures will provide the theoretical and mathematical basis for different applications of functional traits at organismal, community and ecosystem levels, with examples across different trophic levels. This will serve as a basis for exploring the practical tools to connect the effect of land-use and climate change on biodiversity to the effect of biodiversity on to multiple ecosystem…

Course Overview: This course provides a general introduction to Bayesian data analysis using R and the Bayesian probabilistic programming language Stan. We begin with a gentle introduction to all the fundamental principles and concepts of Bayesian data analysis: the likelihood function, prior distributions, posterior distributions, high posterior density intervals, posterior predictive distributions, marginal likelihoods, Bayes factors, etc. We will do this using some simple probabilistic models that are easy to understand and easy to work with. We then proceed to…

Course Overview: Survival analysis is a set of statistical methods initially designed to analyse data giving the times at which individuals die, and assess the effect that different predictor variables have on the rate of death. However, its applications are much broader than this: it can be used to analyse any time-to-event data. Ecologists and evolutionary biologists often encounter data of this kind. Often factors influencing survival itself will be of interest. But there are many other cases, e.g. what…

Course Overview: This course will provide an introduction to working with real-life data typical of those encountered in the field of evolutionary biology and ecology. The course will be delivered by Dr. Luc Bussiere, Dr. Tom Houslay and Dr. Ane Timenes Laugen who are all practicing academics in the field of evolutionary biology.  This five day course will consist of series of modules (each lasting roughly half a day) covering model selection and simplification, generalised linear models, mixed effects models,  and non-linear models. Along…

Course Overview: Acoustic telemetry has become increasingly popular as a method of choice for monitoring the movements and behaviour of aquatic animals globally.  Increasingly smaller tags along with improvements in battery technology have allowed for tagging a wide variety of species and life stages, enabling monitoring of individuals as small as salmon smolts and as large as whale sharks for periods from 30 days to 10 years.  Receiver technology also continues to evolve and increasingly allows for data to be…