Course Overview: Python is a dynamic, readable language that is a popular platform for all types of bioinformatics work, from simple one-off scripts to large, complex software projects. It gives an overview of the language with an emphasis on practical problem-solving, using examples and exercises drawn from various aspects of bioinformatics work. After completing the workshop, students should be in a position to (1) apply the skills they have learned to tackle problems in their own research and (2) continue…

Course overview: Python is a dynamic, readable language that is a popular platform for all types of bioinformatics work, from simple one-off scripts to large, complex software projects. This workshop is aimed at people who already have a basic knowledge of Python and are interested in using the language to tackle larger problems. In it, we will look in detail at the parts of the language which are particularly useful in scientific programming, and at the tools Python offers for…

Course Overview: This course will provide a theoretical, analytical and practical introduction to QIIME 2 (canonically pronounced ‘chime two’), which stands for Quantitative Insights into Microbial Ecology 2, and Qiita (canonically pronounced ‘cheetah’), a multiomics and multi-study online tool. QIIME 2 and Qiita are open source software packages for comparison and analysis of microbial communities, primarily based on high-throughput amplicon sequencing data (such as SSU rRNA) generated on a variety of platforms, but also supporting analysis of other types of…

Course Overview: This course will introduce and explain the different applications for bioacoustics to answer ecological questions. Starting with a detailed overview of the correct and most efficient methods of data collecting in the field, this course will then go on to show delegates cutting edge methods for analysing and interpreting different types of bioacoustic data. By the end of this 5-day practical course, attendees will have the capacity to set up and deploy recording devices, download acoustic data, how…

Course Overview: This course will cover introductory hierarchical modelling for real-world data sets from a 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 hierarchical models. All methods are demonstrated with data sets which participants can run themselves. Participants will be taught how to fit hierarchical models using the Bayesian modelling software Jags and Stan through the R…

Course Overview: Local adaptation to climate and other environmental drivers increasingly is being studied at the molecular level using high-throughput sequencing methods, with applications spanning both model and non-model organisms. At the same time, statistical tools for modeling and mapping patterns of biodiversity have seen increasing application, including to the challenge of understanding the drivers of spatial variation in adaptive genomic variation and mapping these patterns under current and future climate. This 5-day course will provide the skill set necessary…

Course Overview: This 5-day workshop will introduce the development and application of Marxan type spatial planning tools to prioritize land acquisition, easements and incentives in favor of conservation. We are going to use the prioritizr framework (https://prioritizr.github.io/prioritizr/) and an example developed for the Coastal Douglas Fir Conservation Partnership (CDFCP) region by the group of Peter Arcese at UBC (http://arcese.forestry.ubc.ca/marxan-tool-cdfcp/) The reserve design problem will be introduced using examples from the BC Central Coast, Georgia Basin-Willamette Valley of BC, WA and…

Course Overview: Coming soon... To find out more or to book online via our sister company (PS statistics) use the link below… https://www.psstatistics.com/course/introduction-to-behavioural-data-analysis-using-r-ibda01/ “This was by far the most useful statistic-related course I’ve done to date and I enjoyed all aspects of the course. The course was useful because it put into prospective the ecology aspect within the statistics. All parameters were explained in an ecological manner which made the math aspect much clearer. It helped to change the view…

Course Overview: This 5-day course will cover the concepts, methods, and R tools that can be used to analyse community ecology data. The course will review data processing techniques relevant to multivariate data sets. We will cover diversity and null-model analysis, distance measures and distance based multivariate methods, clustering, classification, and dimension reduction techniques using the vegan R extension package. We will use real world data sets to motivate the analyses, e.g. describing patterns along environmental or anthropogenic disturbance gradients,…

Course Overview: This 5-day course will involve a combination of lectures and practical sessions. Students will learn to build and fit custom models for analysing behavioural data using maximum likelihood techniques in R. This flexible approach allows a researcher to a) use a statistical model that directly represents their hypothesis, in cases where standard models are not appropriate and b) better understand how standard statistical models (e.g. GLMs) are fitted, many of which are fitted by maximum likelihood. Students will…

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 Structured population models have become a central tool to explore evolutionary and ecological processes, such as selection gradients or responses to climate change, based on field demographic data. With recent advances in theoretical ecology and computing power, these models have further evolved. Over the last decade, Integral Projection Models (IPMs), a generalization of Matrix Populations Models, have gained popularity because of their simplicity, robustness, and flexibility. This course will draw on the connections between these approaches to help…

Course Overview Range modeling, also known as niche, distribution, or habitat use modeling, is among the most widely used tools in ecology. Its popularity is evidenced by the wide range of conceptual and statistical approaches that have been developed over the last two decades for quantifying ranges. We will spend much of our time on the most popular approach to range modeling - presence-only models - however we will draw connections to other data types and general principles for any…