Courses open for registration

In this course we will investigate what key challenges lie in the domain of crop and pasture system sustainability and how these should be addressed. Mornings consist of short lectures and consequent discussions. Afternoons are spent on group assignments where each group of participants will be assigned to tackling a certain challenge in enhancing crop and pasture system sustainability, addressing agronomic, ecological and socio-economic aspects.

The Soil Biology Group of Wageningen University is organising a laboratory skills course to define which measurements of soil biology are relevant for which soil functions. This course will provide the participants with an overview of a range of methods related to the five soil functions and will provide detailed practical training in a subset of measures. The training will be a combination of lectures, laboratory and field sessions (interactive lectures and practical sessions each day). Assessing a range of measurement types, from simple visual assessments in the field, to training in microscope identification techniques for nematodes and earthworms, and functional measures in the lab such as MicroResp. All methods described in the course will be made available to participants as well as advice on how to analyse the data.

The aim of this course is to provide an introduction to R and R Studio. It introduces the participants to R language syntax, to enable them to write their own R code. They will also learn about R data-types and data-structures, and they will be taught how to explore the data and produce plots. The course will be a combination of lectures and practicals.

Intercropping is the next frontier for diversifying agriculture and increasing its productivity, resource use efficiency and resilience to abiotic and biotic stresses in a sustainable manner. Given the challenges of biodiversity decline and climate change it might well be that intercropping is one of the solutions to strengthen the resilience of cropping systems to these environmental threats and sustain food security.

This course focuses on theoretical concepts, such as autocatalytic loops and positive and negative feedbacks between organisms in ecological networks as well as the importance of non-trophic interactions by ecosystem engineers. The course will address how these principles can be used to link communities to ecosystems enabling a better understanding of how environmental changes affect community and ecosystem dynamics. Students will construct ecological networks of their own study system or based on literature data and analyse these using structural equation modelling.

This course is for participants who want to deepen their knowledge of R programming and be able to use R to deal efficiently with computational problems and programming tasks. Participants will also gain more knowledge on working with R data structures and solving common problems, like working with and manipulating factors, extracting information from statistical models, working with other types of data (textual, time and dates) and handling multiple data files.

In this workshop, participants will learn the principle of tidy data, how to transform and combine datasets using the tools from the tidyverse and how to generate advanced visualization with the ggplot2 package.

The main goal of the course will be achieved if the participants acquire novel ideas and techniques for their own research. The course is primarily aimed at PhD level students, but is also open to advanced Master level students with interest in microbial ecology.

In this two day workshop you will learn about two most common long read sequencing technologies: Pacific Bioscience an Oxford Nanopore Technology. You will learn how to work with the data, perform assembly, mapping, and compare the results of both technologies.

The purpose of this course is to make the participants familiar with general statistical concepts describing uncertainty, and methods to compute prediction uncertainty and sensitivity coming from uncertain parameter values. The course consists of lectures and computer practicals using RStudio.

Shiny is an R package (and ecosystem of packages) that allows the creation of web apps directly from R. It can be used to build standalone applications, mobile apps or embed interactive reports in your documents and presentations. Aim of this course is to introduce participants to the Shiny ecosystem and show them how to approach data exploration, storytelling and communication by going beyond static reports and graphs, and create engaging and interactive data stories.

The purpose of this course is to familiarize participants with statistical methods to analyse uncertainty propagation in spatial environmental modelling, such that they can apply these methods to their own models and data. It also teaches methods that quantify the contribution of individual uncertainty sources and statistical validation methods to assess the accuracy of spatial model outputs with independently sampled data. Quantification of model parameter uncertainty is covered using Bayesian calibration techniques.

This course is intended for those just embarking on genomics within an ecological setting and teaches the fundamentals of the discipline, while concentrating on ecological questions. The course focuses on four topics: population genomics, comparative genomics, metagenomics and functional genomics. Each of the topics is treated by lectures, case studies and participant presentations. Also, participants are encouraged to apply the principles of the course to their own research.