Martin-Luther-Universität Halle-Wittenberg
Seminar: Foundations of Quantitative Biodiversity Sciences - Details
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Allgemeine Informationen

Semester SS 2015
Aktuelle Anzahl der Teilnehmenden 5
Heimat-Einrichtung Praktische Informatik (Bioinformatik)
Veranstaltungstyp Seminar in der Kategorie Offizielle Lehrveranstaltungen
Erster Termin Fr , 10.04.2015 12:00 - 16:00
Studiengänge (für) Computer Science students
Biology students
Bioinformatics students
1st-3rd semester, elective module, graded, 5/120
SWS 2+2
Sonstiges Language: English
ECTS-Punkte 5

Veranstaltungsort / Veranstaltungszeiten

k.A. Freitag: 12:00 - 16:00, wöchentlich(14x)

Kommentar/Beschreibung

Biodiversity science is experiencing a ‘Renaissance’ and is poised to address some of the most critical problems facing humanity in an increasingly human dominated world. Recent advances in biodiversity science lie at the nexus of complexity theory, data collation and pattern analysis at the global scale, and connections to socio-economic systems, epidemiology, and (meta) genomics. Clearly, the next generation of biodiversity scientists will need be adept at a diversity of complex quantitative approaches. However, equally necessary, though often overlooked, is that prudent use of these quantitative tools will require an in depth understanding of the conceptual and theoretical foundations of the discipline.
This course will trace the development of major concepts and approaches in biodiversity science. Readings will include foundational pieces by Darwin, Lotka, Volterra, Elton, Lindeman, Hutchinson and MacArthur, and others, as well as more contemporary studies that represent the ‘state-of-the-art’. The role of theory will be emphasized throughout, building on a set of foundational principles, including evolutionary process, thermodynamics and stoichiometry, birth-death processes, network theory and probability. In addition to reading and discussion, course work will include laboratory ‘practicums’ centered on incorporating these foundational principles into computational models (using the R program for statistical computing) that form the basis for addressing complex biodiversity problems.

Table of content:
• Biodiversity
• Coexistence
• Theory
• History of science
• Data analysis
• Stability
• Speciation
• Extinction
• Theory