PE&RC Postgraduate courses

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Modelling population dynamics with Physiologically Structured Population Models (PSPM) | Concepts, formulation and analysis
Sunday 29 April - Friday 4 May 2018
Physiologically structured population models (PSPMs) constitute a subset of structured models in which both the life histories of individuals and the emerging population dynamics unfold in continuous time, and individual states may be continuous or discrete. PSPMs have been very successful in describing and explaining the mechanisms that drive dynamics of natural populations and communities. Moreover, PSPMs form a powerful tool for understanding how population and community dynamics emerge from individual life histories, and equally important, how population and community processes feed back to shape the life histories of individuals.
Resilience of living systems: From fundamental concepts to interdisciplinary applications
Sunday 29 April – Friday 4 May 2018
During the course, the participants will learn about the basic concepts of resilience and their application, from an interdisciplinary perspective (micro-biome to socio-ecological systems). Accordingly, we will address how resilience theory can be used to tackle fundamental and societal issues from a socio-economic and bio-physical perspective and will provide a critical reflection on the relevance, use, and applicability of the concept of resilience. The course is organised by the Graduate Schools WIAS and PE&RC.
Basic Statistics
Tuesday 8, Wednesday 9, Monday 14 - Wednesday 16 May 2018
This is a refresher course. The level is that of a second course in Statistics. We will refresh basic knowledge of Probability, Statistical Inference (Estimation and Testing), t-tests, simple cases of Regression and ANOVA, Experimental Design, Nonparametric Tests, and Chi-square Tests. Some time is reserved to discuss statistical problems of the participants.
Plant Nutrients in Terrestrial Ecosystems - acquisition and turnover
Monday 14 - Friday 18 May 2018
This course focuses on concepts and theories underlying nutrient use efficiency and sustainable use of plant nutrients, concepts and methodologies used for studying plant nutrition and soil fertility, processes that determine acquisition and utilization of plant nutrients and their turnover and bio-availability in soils and fertilizers. This course is offered by University of Copenhagen. Participation is free of charge for PhD candidates of Wageningen University.
Introduction to R for Statistical Analysis
Thursday 17 & Friday 18 May 2018
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.
Design of Experiments
Wednesday 23 - Friday 25 May 2018
The design and analysis of experiments, using plants, animals, or humans, are an important part of the scientific process. Proper design of an experiment, apart from its proper analysis and interpretation, is important to convince a researcher that your results are valid and that your conclusions are meaningful.
World Soils and their Assessment
Monday 28 May - Friday 1 June 2018 (coordinated by ISRIC)
This is a course on international standards for soils classification and assessment. It will provide an introduction to the soils of the world and their diversity, their main forming factors, classification (according to the World Reference Base for Soil Resources 2014), and management. The course will include lectures and hands-on exercises. PE&RC PhD candidates are entitled to the reduced fee.
Machine learning for spatial data
Monday 28 May - Friday 1 June 2018
In this course participants will learn how to model patterns and structures contained in data. The course will be focused on statistical and machine learning approaches, where the relationships between the observed data and the phenomenon under study are learned directly from observations. Through a series of lectures and practical exercises (in Matlab), the participants will learn about different strategies and their pertinence for specific problems in environmental sciences. Most applications considered in the course will be remote sensing-based, but the course will remain general for a broader audience.
Hands on Digital Soil Mapping
Monday 28 May - Friday 1 June 2018
This course introduces methods and software for management, analysis and mapping of soil variables within the R environment for statistical computing. The course alternates between lectures and computer practicals and covers a variety of subjects, such as geostatistics, linear regression and machine learning for soil mapping, quantification of uncertainty and soil map validation.
Fundamentals of Crop Physiology in a Changing World
Sunday 3 - Friday 8 June 2018
The course focusses on the fundamental knowledge and insight one must have about crops to be able to adapt agronomic practices to the changing world. Here the changing world refers to the environment, increased demands on sustainable production and food quality.
Linear Models
Friday 8, Monday 11 and Tuesday 12 June 2018
In this module we continue with Regression, ANOVA, and ANCOVA, set in the general framework of Linear Models. We look at topics like parameter estimation and interpretation, checking model assumptions, regression diagnostics, analysis of unbalanced designs and multiple comparisons.
Generalized Linear Models
Thursday 14 & Friday 15 June 2018
In this module we study how to analyse data that are not normally distributed. We look at fractions (logistic regression), counts (Poisson regression, log-linear models), ordinal data (threshold models), and overdispersion. We discuss (quasi-) maximum likelihood estimation and the deviance.
Mixed Linear Models
Thursday 21 & Friday 22 June 2018
In this module we discuss how to analyse data for which the assumption of independence is violated. So: Do you have a nested experimental set-up? Or repeated measurements? Or weight of the same animal over time? Or pseudo-replication? Then, you are likely to need Mixed Models. In this course, you will learn all about it!
Conflicting demands in European Forests: a wicked problem?
Sunday 24 June - Monday 2 July 2018
More and more, we are confronted with conflicting demands when trying to develop sustainable land-use strategies, resulting in so-called wicked problems. Scientists working on such wicked problems need to be trained to work in trans-, multi- and interdisciplinary teams of experts with various scientific backgrounds, such as ecologists, economists, political, and social scientists. This course aims to teach them the skills they need for working in such diverse teams, by means of a real-life case. The course is focused around Gällivare, a small town in the north of Sweden, where one can find the “last wilderness of Boreal Europe”, part of an UNESCO World Heritage Site with large nature reserves and national parks. At the same time, it has an active mining industry, forestry, reindeer herding and tourism. It is a perfect place for land use and land use change discussions. A travel subsidy is available for PE&RC PhD candidates.
Meta-analysis
4 - 5 July 2018
Researchers trying to summarize the constantly growing body of published research are increasingly using meta-analysis. The focus of this 2-day course will be on concepts of linear models and mixed linear models in meta-analysis. The statistical software R will be used.
Farming Systems and Rural Livelihoods: Pathways to sustainable development
Saturday 15 - Saturday 29 September 2018
Through the adoption of the Sustainable Development Goals (SDGs) the world has set ambitious aims, of which many are related to and affected by agriculture. SDG-2 is particularly relevant for rural livelihoods in sub-Saharan Africa as it aims to end hunger, achieve food security and improved nutrition, and promote sustainable agriculture. In this course, you will acquire skills and learn methods to deal with the complexity of smallholder agriculture and the many interlinkages with other SDGs towards carving out pathways for sustainable development of smallholder farming systems.
Uncertainty Propagation in Modelling
Monday 10 - Friday 14 December 2018
The purpose of this course is to familiarize participants with statistical methods to analyse uncertainty propagation in spatial modelling, such that they can apply these methods to their own models and data. Both attribute and positional errors are considered. Attention is also given to the effects of spatial auto- and cross-correlations on the results of an uncertainty propagation analysis. Computer practicals make use of the R language for statistical computing.