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Name JC Douma

Job details
DescriptionAssistant professor
OrganizationDepartment of Plant Sciences
Organization UnitCentre for Crop Systems Analysis
Phone+31 317 482 140
Secretarial phone+31 317 485 315
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Visiting addressBornsesteeg 48
Postal addressPostbus 430
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Dr. Bob (J.C.) Douma is assistant professor at Centre for Crop Systems Analysis at Wageningen University. He studies the ecology of plant in the context of pests and diseases and uses advanced modelling tools to unravel the interaction between pests/pathogens and plants.

Bob Douma did his BSc in Groningen and Wageningen, and obtained his MSc at Wageningen University. He obtained his PhD at the VU University, Amsterdam in 2011, and moved to Wageningen University in 2012 to work on a project funded by the European Food and Safety Authority on models that predicts the entry of alien plant pests. In 2014 he obtained a NWO VENI grant to study the role of plant-plant communication through volatiles when subjected to herbivory through modelling and experimetation.

His current research focuses on plant-pest interactions with particular emphasis on i) understanding the drivers of the introduction, establishment and spread of alien plants pest. He is currently co-leading a work package in the European project HOMED; ii) the performance of plants when subject to multiple stressors such as plant-plant competition and insect herbivory. He seeks to do research that has implications for practice. For example, in one of his projects he tries to find out how crop mixtures can be used to suppress diseases, and which factors contribute to this diseases suppressive effect of crop mixtures.

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I have three research lines that are described below in more detail:

First, to understand plants' responses in an enviroment when challenged by neigbouring plants and pests and diseases. I want to unravel these processes and relationships through the application of models, field and greenhouse experiments and analysis of large datasets.

Here a couple of examples of the work I did in this context:

  • Ratios of red to far-red light are used by the plant as indicator of upcoming shade. A lowered R:FR ratio leads to shoot elongation and makes the plant more competitive in dense stands. Interestingly, lowered R:FR also downregulates plant defence. Why? In this paper we explored through 3D plant modelling the benefit of reducing defence in response to R:FR.
  • Plant subjected to insect herbivory emit a blend of volatile organic compounds. The natural enemies of these herbivores (e.g. parasitoids) can use this blend to locate their host. However, they appear to use only a small number of compounds to locate their host. In this study, we model the emission of these compounds and their fate in the canopy. We show that the physico-chemical characteristics of volatile organic compounds determine for a large part whether they can serve as reliable indicators of herbivory.


Secondly, I am interested in the introduction, establishment and spread of alien plant pests. Through increasing trade and travel, alien plant pests and pathogens arrive at unprecedented rates. For risk managers, it is important to know when where new species will arrive. The models that I have developed in this context are used by the European Food and Safety Authority for risk assessment (see e.g. here and here). I am co-leading a modelling work package of a European Horizon Research program, HOMED on invasive plant pests and pathogens.


Finally, I love the application of models and novel statistical tools to answer intruiging ecological questions. Historically, statistics has focussed on univariate analysis, while multivariate techniques are less well developed. Those techniques out there, such a ordination techniques (PCA, RDA), hammer down the multivariate structure to a number of dimensions that we can visualize. I am interested in stastistical techniques that deal with the multivariate of the data, withouth collapsing this multidimensionality.

  • For example, here I have described with Dr. James Weedon (VU University Amsterdam) the use of Dirichlet regression to deal with proportions partitioned over multiple categories, such as %leaf,%stem,%root biomass.
  • With Prof. Bill Shipley (University of Sherbrooke, Canada) I work on causal inference techniques (structural equation modelling). See examples here.


I am involved in the following courses:

  1. Ecological Modelling and Data Analysis in R (CSA-50306).

    This course prepares the student for a future of lifelong learning. For this course, we use a reverse format where students present and discuss theory, and apply the concepts in case studies. Every two years we choose a new book about modelling or statistical modelling. For example, we discussed "Ecological models and Data in R  by Bolker, Mixed effects model and extensions in Ecology with R - by Zuur, and A practical guide to Ecological modelling by Soetaert and Herman. The teachers guide the students through the process of getting acquainted with new statistical techniques and a new programming language. Students are expected to participate actively in class discussion and each student should give a presentation on the theory from the book. The book comes with ecological data sets that will be analyzed during practicals and discussed thereafter. Students will carry out two projects to apply and demonstrate acquired knowledge, skills and insight. The project outcomes are presented orally, and R codes are shared.

  2. Poulation and Systems Ecology (CSA-20806).
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