INF.06290.04 - Modelling species distribution and biodiversity patterns (Complete module description)

INF.06290.04	15 CP
Module label	Modelling species distribution and biodiversity patterns
Module code	INF.06290.04
Semester of first implementation
Faculty/Institute	Institut für Informatik
Module used in courses of study / semesters	Biodiversity Sciences (MA120 LP) (Master) > Biologie BiodiversityMA120, Version of accreditation valid from SS 2021 > Project modules offered by the Institute of Computer Science (Nat Sci III) Bioinformatik (MA120 LP) (Master) > Bioinformatik BioinformatikMA120, Version of accreditation valid from SoSe 2023 > Bioinformatik (HB) (Anteil gem. § 5 Abs. 4-6, Anlage 2) Bioinformatik (MA120 LP) (Master) > Bioinformatik BioinformatikMA120, Version of accreditation (WS 2016/17 - WS 2022/23) > Bioinformatik (HB) Biologie (MA120 LP) (Master) > Biologie BiologieMA120, Version of accreditation valid from SoSe 2023 > B2 Biologie (MA120 LP) (Master) > Biologie BiologieMA120, Version of accreditation (WS 2010/11 - SoSe 2024) > Wahlpflichtmodule
Responsible person for this module
Further responsible persons	Prof. Dr. Jonathan Chase; Prof. Dr. Helge Bruelheide; Dr. Erik Welk
Prerequisites
Skills to be acquired in this module	Develop a comprehensive understanding of the models used to describe species distribution and species richness, including their strengths, limitations, and underlying assumptions. Demonstrate the ability to critically analyze and compare models results with empirical data, effectively interpret and communicate the implications of these results. Acquire a proficient command of the R programming language, enabling the student to write and execute simple programs for processing and analyzing species distribution and biodiversity data. Gain competence in the use of GIS software to integrate and manipulate spatial data, create informative maps and analyze spatial patterns in species distribution and biodiversity. Develop the skills to effectively read, critically evaluate and engage in discussions about research articles with a strong theoretical or modeling component related to species distribution and biodiversity patterns.
Module contents	Part I, Introduction to species distribution pattern analysis Introduction into GIS: vectorial and raster data; visualizing vectorial and raster data; projections and choice of datum; the attribute table for vectorial data and basic database operations; importing, editing and exporting data; basic spatial operations in GIS (geometric operations and spatial interpolation). Mapping methods for plant distribution data; sources, compilation and gathering of plant distribution data; storage and organization of data. Introduction to current plant biogeography and macroecological research and the relevant literature; revisiting the niche concept of large scale species distribution ranges Introduction to Species Distribution Models; applications and use of plant distribution data; Specifics of spatial data in statistical analyses; data preparation and transformations; assumptions of and conditions for spatial analyses of ecological data Visualizing spatial data in R Practical exercises in plant chorology and macroecology Part II, Measuring and comparing patterns of biodiversity Introduction to biodiversity measures and metrics (e.g., alpha, beta, gamma diversity) Species area curves, endemics area curves, other macroecological patterns R code for building spatial diversity patterns R code for dissecting species richness scaling relationships Functional and phylogenetic diversity measures; genetic and network diversity Practical exercises for comparing biodiversity variation across natural and anthropogenic gradients
Forms of instruction	Lecture Course Lecture Course Seminar Course Course Course Exercises (1 SWS) Lecture Course Lecture Course Seminar Course Seminar Course Lecture Course Exercises (1 SWS)
Languages of instruction	German, English
Duration (semesters)	6 Wochen Semester
Module frequency	jedes Wintersemester
Module capacity	unlimited
Time of examination
Credit points	15 CP
Share on module final degree	Course 1: %; Course 2: %; Course 3: %; Course 4: %; Course 5: %; Course 6: %; Course 7: %; Course 8: %; Course 9: %; Course 10: %; Course 11: %; Course 12: %; Course 13: %; Course 14: %; Course 15: %; Course 16: %; Course 17: %; Course 18: %; Course 19: %; Course 20: %.
Share of module grade on the course of study's final grade	1

Module course label	Course type	Course title	SWS	Workload of independent learning	Sum workload
Course 1	Lecture	Part I.1 Lecture Introduction to GIS			0
Course 2	Course	Part I.2 Pre and post lecture self study and literature work			0
Course 3	Lecture	Part I.3 Lecture Plant biogeography			0
Course 4	Course	Part I.4 Pre and post lecture self study and literature work			0
Course 5	Seminar	Part I.5 Seminar Current topics in plant biogeography and macroecology			0
Course 6	Course	Part I.6 Pre and post lecture self study and literature work			0
Course 7	Course	Part I.7 Practical course Species distribution modelling			0
Course 8	Course	Part I.8 Pre and post lecture self study and literature work			0
Course 9	Exercises	Part I.9 Practical exercises and independent projects for analyzing species distribution data	1		0
Course 10	Lecture	Part II.1 Lecture and discussion Measuring and comparing patterns of Biodiversity across scales			0
Course 11	Course	Part II.2 Pre and post lecture self study and literature work			0
Course 12	Lecture	Part II.3 Lecture and discussion Species area curves, endemics area curves, other macroecological patterns			0
Course 13	Course	Part II.4 Pre and post lecture self study and literature work			0
Course 14	Seminar	Part II.5 Seminar R code for building spatial diversity patterns			0
Course 15	Course	Part II.6 Pre and post lecture self study and literature work			0
Course 16	Seminar	Part II.7 Seminar R code for dissecting species richness scaling relationships			0
Course 17	Course	Part II.8 Pre and post lecture self study and literature work			0
Course 18	Lecture	Part II.9 Lecture and discussion Functional and phylogenetic diversity measures; genetic and network diversity			0
Course 19	Course	Part II.10 Pre and post lecture self study and literature work			0
Course 20	Exercises	Part II.11 Practical exercises and independent projects for comparing biodiversity variation across natural and anthropogenic gradients	1		0
Workload by module				450	450
Total module workload					450

Examination	Exam prerequisites	Type of examination
Course 1
Course 2
Course 3
Course 4
Course 5
Course 6
Course 7
Course 8
Course 9
Course 10
Course 11
Course 12
Course 13
Course 14
Course 15
Course 16
Course 17
Course 18
Course 19
Course 20
Final exam of module	Part I: Presentation and talks, written report, presentation of statistics and graphs,presentation of own results, Part II: independent project with paper and presentation	Wissenschaftlicher Vortrag Teil I, Wissenschaftlicher Vortrag Teil II, Protokoll, Wissenschaftlicher Vortrag (eigenständiges Projekt)
Exam repetition information

Prerequisites and conditions	Frequency	Compulsory attendance	Share on module grade in percent
Course 1	Winter semester	No	%
Course 2	Winter semester	No	%
Course 3	Winter semester	No	%
Course 4	Winter semester	No	%
Course 5	Winter semester	No	%
Course 6	Winter semester	No	%
Course 7	Winter semester	No	%
Course 8	Winter semester	No	%
Course 9	Winter semester	No	%
Course 10	Winter semester	No	%
Course 11	Winter semester	No	%
Course 12	Winter semester	No	%
Course 13	Winter semester	No	%
Course 14	Winter semester	No	%
Course 15	Winter semester	No	%
Course 16	Winter semester	No	%
Course 17	Winter semester	No	%
Course 18	Winter semester	No	%
Course 19	Winter semester	No	%
Course 20	Winter semester	No	%