Vorlesungsverzeichnis

Suchen Sie hier über ein Suchformular im Vorlesungsverzeichnis der Leuphana.

Veranstaltungen von Dr Benjamin Delory


Lehrveranstaltungen

Field Exercise 1 - Introduction to Ecology (for GESS) (Übung)

Dozent/in: Benjamin Delory, Vicky Temperton

Termin:
Einzeltermin | Mo, 17.05.2021, 17:00 - Mo, 17.05.2021, 17:30 | Online-Veranstaltung | preliminary meeting
Einzeltermin | Fr, 04.06.2021, 09:00 - Fr, 04.06.2021, 18:00 | Online-Veranstaltung | preparation of field exercise
Einzeltermin | Sa, 05.06.2021, 09:00 - Sa, 05.06.2021, 18:00 | extern | one-day field exercice, Elbe river, by bike (train from Lüneburg to Lauenburg)
Einzeltermin | So, 06.06.2021, 09:00 - So, 06.06.2021, 18:00 | Online-Veranstaltung | work on data + presentation of results

Inhalt: Dear students, We are attempting to still adhere to the Corona regulations but allow you to have some kind of a field experience this summer. As such the plan now is to have one full field day (Saturday) at the Elbe, where we assess the diversity of the vegetation across a couple of different sites. We will be then using the cover estimates and species lists to calculate biodiversity indices and then we can compare and contrast how well the different indices and ways of measuring plant diversity compare to each other (strengths and weaknesses). The Friday will be a preparation for the field Saturday and occur online, and presentations of results will happen online on Sunday pm, giving you Sunday morning to work on your data and preparations.

Designing and Analysing Ecological Experiments (Seminar)

Dozent/in: Benjamin Delory

Termin:
14-täglich | Freitag | 09:00 - 12:00 | 06.04.2021 - 09.07.2021 | Online-Veranstaltung

Inhalt: Doing experiments in ecology and environmental sciences well is an art that needs to be learned. There are good and bad ways to perform experiments. One can either bumble ones way through, without considering key aspects of experimental design and analysis or one can learn and internalize the key factors that ensure your experiment has the best chances of success in terms of results and impact. If you want to learn the key tools and characteristics of the successful design and analysis of experiments, this is the course for you. There is no prerequisite needed to be able to attend this seminar (if you have never used R before, this seminar is a very good place to start). THIS COURSE WILL TAKE PLACE IN A VIRTUAL FORMAT. The organisation of this seminar will rely on two main platforms: Moodle and Zoom. In Moodle, detailed videos and tutorials will be provided on a regular basis (typically every two weeks). Students that will be officially registered for this course are strongly encouraged to watch the videos, read the key papers that will be featured in the videos and tutorials (the papers will be provided by the lecturer), and repeat the examples that will be provided in the tutorials. These tutorials will mainly focus on data exploration and analysis using the R statistical environment. An introduction to R programming will also be provided. Using Zoom, a video conference with all students will be organised for oral presentations (students will work in groups to present the experimental design and main results of published studies selected by B. Delory). In the videos and tutorials, the following topics will be discussed: - Introduction to ecological experiments: this seminar will show numerous examples of experiments performed to answer ecological questions; - Posing questions and using experiments to test hypotheses: this seminar will illustrate complementary ways to perform experiments in ecology and will review important considerations that researchers have to think of when designing manipulative experiments; - Data exploration using R - Data analysis using R - Introduction to R programming - Communicating with others about experimental design and analysis During the seminar, students will also work individually on a specific problem related to plant sciences. The main objective of this exercise is to allow students to practise data exploration and analysis using R.