ICBM Summer School 2017 Introduction to Data Analysis and Ecosystem ModelingExternal

Activity Overview

Type: Course
Start Date: July 30, 2017
End Date: August 12, 2017
Website: Summer school info
Contact: Dr. Jürgen Köster
E-mail: icbm.summerschool [at] uni-oldenburg.de

Application/registration deadline: March 31, 2017

The Institute for Chemistry and Biology of the Marine Environment (ICBM, University of Oldenburg) is hosting a summer school in 2017, titled 'Introduction to Data Analysis'. The course, running from July 30 - August 12, will focus on mathematical and numerical methods used in marine and environmental sciences. The school is specifically addressed to early career scientists (advanced masters students/ early stage PhD students). Since data acquisition will be an integral part of the summer school a focus will be on marine conditions met in the southern North Sea and Wadden Sea, one of  the largest tidal systems world-wide and UNESCO World Heritage since 2009.

Skills in data analysis and experience with modeling approaches are gaining more and more importance also for researchers in disciplines that are traditionally further way from mathematical theory building. While a firm background of very basic math and some experience in any programming environment (e.g. Matlab or R) is expected, this summer school is intended for marine scientists from all scientific disciplines.

The summer school will introduce participants into various modeling approaches to marine ecosystem dynamics. Relevant processes in the marine environment range from oceanography (hydrodynamic transport, bentho-pelagic coupling, eddie dynamics), over biogeochemistry (nutrient cycling, stoichiometry) to biological populations (regular or harmful algal blooms, biological growth inside eddies) and eventually reach the level of ecological communities (marine food web, biodiversity and its relation to ecosystem functions and services). This wide range of processes is paralleled by a rich arsenal of mathematical modeling methods (discrete vs. continuous in time/space, deterministic vs. stochastic, process-oriented vs. statistical, conceptual vs. comprehensive).