BIO.05948.03 - Projektmodul Spatial Ecology and Modeling (MA) (Complete module description)

MLU

BIO.05948.03	15 CP
Module label	Projektmodul Spatial Ecology and Modeling (MA)
Module code	BIO.05948.03
Semester of first implementation
Faculty/Institute	Institut für Biologie
Module used in courses of study / semesters	Bioinformatik (MA120 LP) (Master) > Bioinformatik BioinformatikMA120, Version of accreditation valid from SoSe 2023 > Biologie (Anteil gem. § 5 Abs. 4-6, Anlage 2) Bioinformatik (MA120 LP) (Master) > Bioinformatik BioinformatikMA120, Version of accreditation (WS 2016/17 - WS 2022/23) > Biologie Biologie (MA120 LP) (Master) > Biologie BiologieMA120, Version of accreditation valid from WS 2010/11 > Wahlpflichtmodule
Responsible person for this module
Further responsible persons	Prof. Dr. H. M. Pereira, Prof. Dr. T. Knight, Prof. Dr. S. Harpole, Prof. Dr. I. Kühn
Prerequisites
Skills to be acquired in this module	Have a basic understanding of the models used in ecology including: differential and difference equations; individual based models and grid simulations; statistical models, particularly species distribution models. Ability to create and parameterize models, and to evaluate uncertainty in model results. Ability to determine the type of model needed for the ecological question of interest. Ability to compare models results with empirical data, to interpret model results, and to assess the quality and relevance of the models. Have a basic command of the R language, including the ability to write simple programs. Ability to read a research article with a strong theoretical or modeling component.
Module contents	Part I: Theoretical Ecology and Modeling: Introduction to programming in R: scripts and the command line, variables, data structures (vectors and matrices); numerical operations; matrix operations; plots; logical expressions and conditional operations, functions. - Basic statistical operations with R: descriptive statistics and histograms, regression, and hypothesis testing. - Ecophysiology: a model of thermoregulation and the concept of climate space; modeling the impacts of climate change using ecophysiological models. - Behavioral ecology: introduction to economic analysis of behavior; models for optimal foraging; game theory and evolutionary stable strategies; habitat selection and the ideal free distribution; affinity of species to natural and human-dominated habitats. - Social-ecological models: coupling social models of decision-making with ecological models; introduction to regime shifts and multiple stable states. Part II: Introduction to Population Ecology: Introduction to modeling the dynamics of populations using mathematical models (difference equations and individual based models). - Focus on conservation application of modeling for preserving natural populations and for ecological restoration. - Incorporating environmental stochasticity and density dependence into the exponential growth model. - Stage-structured population growth using matrix population models. - Integral projection models. - Metapopulation models and individual-based population models. Part III: Community Ecology (Theory, reading and modeling in R): Competition and coexistence (phenomenological). - Competition and coexistence (mechanistic). - Other coexistence mechanisms (predation). - Coexistence in space. - Niche, neutral and stochasticity. Part IV: Analyzing Spatial data with R: 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. - Reviving Generalized Linear Models; calibration, validation, prediction and projection; accounting for spatial autocorrelation. - Introduction to Species Distribution Models; overview on different algorithms (e.g. Generalized Additive Models, Boosted Regression Trees) and available R packages.
Forms of instruction	Lecture (1 SWS) Lecture Lecture Lecture Practical training (8 SWS) Course Course
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: %.
Share of module grade on the course of study's final grade	1
Reference text	Maximum number of students (with focus ecology): 16; Calendar: The four parts take place in Halle (Institute for Biology - Geobotany and Botanical Garden, MLU, Halle and/or Helmholtz Centre for Environmental Research, UFZ, Halle) and in Leipzig (German Center for Integrative Biodiversity Research - iDiv), respectively.

Module course label	Course type	Course title	SWS	Workload of independent learning	Sum workload
Course 1	Lecture	Lecture 'Theoretical Ecology and Modeling'	1		0
Course 2	Lecture	Lecture 'Introduction to Population Ecology'			0
Course 3	Lecture	Lecture 'Community Ecology'			0
Course 4	Lecture	Lecture 'Analyzing spatial data with R'			0
Course 5	Practical training	Practical course 'Spatial Ecology/Ecological Modeling'	8		0
Course 6	Course	Lab assignment reports			0
Course 7	Course	Pre- and post-lecture self-study and literature work			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
Final exam of module	Practical course reports 'Plant chorology/macroecology', Literature review 'Current research in spatial ecology', Mini-paper 'Spatial modeling', Computational lab assignment reports (8 reports), Development, report and presentation of an ecological model	Hausarbeit, Klausur
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	%