Jan Freund

contact

+49 441 798 - 3231

+49 441 798 - 3404

W15 1-101

Carl von Ossietzky Str. 9-11
D-26111 Oldenburg

by arrangement

Jan Freund

Jan Freund

Research interests

My overarching interest is the transfer of paradigmatic models and methods from the field of theoretical physics and complex systems to other scientific fields, such as marine biology, ecology or neuroscience. In addition to the possibility of tracing observable phenomena from the aforementioned neighbouring sciences back to fundamental principles and mechanisms, there is often also a practical benefit, such as the optimisation or control of processes through the elucidation and quantification of causal mechanisms of action. My repertoire of methods often includes a stochastic component, whether in model formulation through stochastic processes or in empirical data analysis through statistical concepts.

Selected publications

  • Hillebrand H, Donohue I, Harpole WS,Hodapp D, Kucera M, Lewandowska AM, Merder J, Montoya JM, Freund JA. Thresholds for ecological responses to global change do not emerge from empirical data.
    Nature Ecology & Evolution, 2020, 4 (11), pp.1502-1509.
    doi.org/10.1038/s41559-020-1256-9
     
  • Merder J, Freund JA, Feudel U, Hansen CT, Hawkes JA, Jacob B, Klaproth K, Niggemann J, Noriega-Ortega BE, Osterholz H, Rossel PE, Seidel M, Singer G, Stubbins A, Waska H, Dittmar T. ICBM-OCEAN: Processing Ultrahigh-Resolution Mass Spectrometry Data of Complex Molecular Mixtures.
    Analytical Chemistry, 2020, 92 (10), pp.6832-6838.
    doi: 10.1021/acs.analchem.9b05659
     
  • Lewandowska AM, Jonkers L, Auel H, Freund JA, Hagen W, Kucera M, Hillebrand H . Scale dependence of temporal biodiversity change in modern and fossil marine plankton.
    Global Ecology and Biogeography, 2020, 29 (6), pp.1008-1019.
    doi: 10.1111/geb.13078
     
  • Freund JA, Mieruch S, Scholze B, Wiltshire K, Feudel, U. Bloom dynamics in a seasonally forced phytoplankton-zooplankton model: trigger mechanisms and timing effects.
    Ecological Complexity, 2006, 3 (2), pp.129-139.
    doi.org/10.1016/j.ecocom.2005.11.001
     
  • Freund JA, Schimansky-Geier L, Hänggi P. Frequency and phase synchronization in stochastic systems.
    Chaos: An Interdisciplinary Journal of Nonlinear Science, 2003, 13 (1), pp.225-238.
    doi.org/10.1063/1.1500497
     

Teaching

Winter semester

Statistical Ecology

Felddaten: 3 Arten in 9 FeldernType of course: VL & UE SWS: 2 & 2
ECTS: 6
Target group: Environmental modellers (M.Sc.)

Content:

  1. Basic concepts and introduction
  2. Random variables and probability distributions
  3. Estimation of population proportions
  4. Estimation of population densities
  5. Statistical description of communities

Population dynamics

together with Ulrike Feudel

Type of course: VL & UE SWS: 2 & 2
ECTS: 6
Target group: Environmental modellers (M.Sc.)

Content:

  1. Growth dynamics of individual species in continuous (flow) and discrete (maps) time.
  2. Dynamics of interacting populations (competition and predator-prey models, trophic networks)
  3. Matrix models for age- and stage-structured populations
  4. Non-linear matrix models and populations in space
  5. Stochastic population dynamics

Summer semester

Stochastic processes

Ensemblestatistik des OU-ProzessesType of course: VL & UE SWS: 2 & 2
ECTS: 6
Target group: Environmental modellers (M.Sc.)

Content:

  1. Basic concepts of stochastics
  2. Characterisation of stochastic processes
  3. Fundamental equations for the ensemble description of stochastic processes
  4. Stochastic differential equations for the description and simulation of realisations of stochastic processes
  5. Applications: Random motion, stochastic neuron models, stochastic population dynamics.

Time series analysis

multivariate ZeitreiheType of course: VL & UE SWS: 2 & 2
ECTS: 6
Target group: Environmental modellers (M.Sc.)

Content:

  1. Time series as realisations of stochastic processes
  2. Process variables and their estimators
  3. Component models: trends, rhythms and residuals
  4. Spectral characterisation of time series
  5. Non-stationary processes: Time-frequency methods
  6. Linear filters and discrete-time linear stochastic processes
  7. Non-linear processes: State space and attractor
  8. Embedding theorem, reconstructed attractor and invariants
  9. Lyapunov exponents
  10. Generalised dimensions

Applied Statistics

together with Helmut Hillebrand, Michael Winklhofer, Gerhard Zotz

Zwei-faktorielle ANOVA

Type of course: VL & UE SWS: 2 & 2
ECTS: 6
Target group: Environmental scientists (B.Sc.)
                               & Biologists (B.Sc.)

Content:

  1. Why statistics at all?
  2. Random variables, distributions, position and shape parameters
  3. Empirical parameters, estimators, robustness
  4. Covariance and correlations
  5. Statistical tests, null hypothesis, errors of 1st & 2nd kind
  6. t-test, ANOVA, Kruskal-Wallis
  7. Post-hoc tests, multiple testing
  8. Regression
  9. ANCOVA
  10. Supplements (pseudo-random numbers, transformations, resampling techniques)

The lectures are supplemented and deepened by practical work with data in the programming environment R. An introduction to R is given in the first exercises. Homework will be set and assessed - only a sufficient performance here entitles the student to take the exam.

(Changed: 20 Jun 2024)  | 
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