How can we fully exploit the multifunctional potential of soils? And how is the soil’s functionality impacted by land-use intensification and climate change? This is the theme for the 7th edition of the international PhD course on Soil Ecology.

GIS is commonly used as a tool to deal with spatial information. Although GIS packages are becoming increasingly user-friendly, the conceptual model behind the storage, analysis, and display is still essential to properly deal with these systems. This course aims to give an overview of this conceptual model, after which it will go in-depth in the use of ArcGIS using a number of practical cases.

The aim of this course is to provide an introduction to R, a language and environment for statistical computing and graphics. Focus of the course will be on getting familiar with the R environment, to use R for manipulation and exploration of data, and to perform simple statistical analyses. Hands-on exercises will form a large part of the workshop.

Ecological modelling, based on field data, has become an indispensable tool in ecological research. This course presents a conceptual framework for ecological modelling: covering elementary growth models and probability distributions needed to mathematically model processes.

To date, many different scientific concepts and approaches of sustainability exist. What are the differences and what do they entail? What is your role as a scientist in achieving sustainable develop-ment? How can you apply sustainability in your own research? And in doing so, how can you deal with facts, uncertainty, values and opinions? This on-site course will enable you to think about the ‘bigger picture’, grasp sustainability and to apply concepts and approaches to your own research, in a collaborative learning environment, away from ‘office’. This course is organised by the Research School for Socio-Economic and Natural Sciences of the Environment (SENSE) and PE&RC, but coordinated by SENSE.

This course will provide an overview of concepts and tools that can contribute to the design of multifunctional landscapes that are better suited to capitalize on ecosystem services in conjunction with other land-use functions. The focus of the course will be on consumer-resource interactions underlying pollination and biocontrol services, the spatial ecology of pollinators and natural enemies, the impact of pest management practices on arthropod-mediated ecosystem services, and the design of multifunctional landscapes that support arthropod-mediated ecosystem services as well as other land-use functions.

Survival analysis, or time-to-event analysis, was originally developed in medical statistics to analyse the effects of covariates on survival times of patients (hence its name). Techniques from survival analysis can be applied in a variety of biological contexts, whenever data consist of time until occurrence of a certain event. Examples are many types of behavioural data, times until recapture, and latency data.

The course is mainly based on the book "Multivariate Analysis of Ecological Data Using CANOCO 5" by Petr Smilauer and Jan Leps (2014). Practical exercises, the use of Canoco for Windows (4.5) and GenStat for Windows and interpretation of the output are important elements of the course.

Modelling is a crucial part of today's science. Among other things, models are used for assessing sensitivity of systems to disturbances or changes in external factors, and for predictions of future system states. This course provides an introduction to modelling with a focus on systems analysis using dynamic simulation models.

From 20 - 24 May 2019, ISRIC - World Soil Information will organise a Spring School on digital soil mapping, classification and assessment for soil and environmental scientists, students, soil experts and professionals in natural resources management. The spring school will take place at the Wageningen Campus in the Netherlands and will consist of two five-day courses that are run in parallel.

This course introduces methods and software for management, analysis and mapping of soil type and soil properties within the R environment for statistical computing. After this course participants will be able to apply the methods learnt to their own datasets.