Numerical Ecology Unit

We develop and use statistical and AI (machine learning) tools to study plankton and to teach biological data science in a modern hybrid pedagogy including digital technology.

The UMONS Numerical Ecology Unit studies marine plankton using digital imaging techniques combined with automated and semi-automated machine learning classification. We develop and maintain the ZooImage software for these analyses.

We also develop extensions to the R software, such as SciViews for a homogenisation of its user interface, pastecs for the analysis of spatio-temporal series in ecology, aurelhy for the spatial interpolation of hydro-climatic variables, or charts for graphs to be directly used for publication.

We teach data science in the biology curriculum in the Faculty of Science using a hybrid approach (part flipped classroom, part classroom). Digital tools, such as Moodle, Wooclap, H5P, learnr, git, GitHub (Classroom) and bookdown, form the basis of our online interactive teaching material (see https://wp.sciviews.org). Assessment is continuous through the recording of student activities in online exercises - and is based on the use of the Internet.