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Background
Environmental sciences by definition is concerned with a highly heterogeneous range of processes, organisms and systems. Empirical studies in environmental sciences therefore are often highly contingent on the ecosystem or species studied and their temporal and physical setting. Observations or experimental manipulations of a certain factor may yield divergent – even contradictory – results when repeated at a different place or at a different time. The variation in outcomes has been ubiquitous in many areas of the environmental sciences. As a consequence, robust methods for collecting and synthesizing research results across studies have been essential for advancing the discipline. Quantitative syntheses of ecological research are crucial to derive central tendencies from existing knowledge, to determine whether modifying factors (such as the conditions under which an experiment was conducted) can account for differences in study outcomes, to distinguish true heterogeneity in results from sampling variance due to small sample sizes, and to identify and characterize knowledge gaps and research needs. Furthermore, the accumulation of dozens, hundreds or even thousands of studies addressing particular questions in the environmental sciences has presented a compelling need for robust, replicable and unbiased methods for synthesizing results across studies. Research synthesis methodology provides a tool kit of powerful procedures to accomplish these goals.
Speaker
Bild: Universität Oldenburg
Prof. Dr. Helmut Hillebrand is Director Helmholtz Institute for Functional Marine Biodiversity at the University of Oldenburg, HIFMB and Professor for Plankton Ecology.
Course
Within the SynCom activities for research synthesis, Helmut Hillebrand (University of Oldenburg & HIFMB) offers a Research Meta-Analysis Workshop in Summer & Fall 2023. The aim of the workshop is to provide an overview on quantitative synthesis methods including systematic reviews and meta-analyses. It comprises information on how to screen the literature for a meta-analyses, informs of potential bias sources, and then continuous to detail approaches to quantitative analysis of data using effect metrics. The course runs in a flipped classroom format.
Procedure
The course is composed of two interrelated parts:
1) Interested participants need to register here. After registration, they will receive a link to an online course that needs to be fully completed before September 15th 2023. The course consists of four video sessions and explicit exercises in R on data sets included in the package.
2) In a virtual classroom session on Sep 21st (1 pm CEST, max 2 hrs) participants can ask questions on the online part. It will also be possible to present own synthesis ideas or get feedback on running meta-analyses. The classroom is here: https://meeting.uol.de/b/hel-3br-xw4.