Portfolio

Here is a summary of rfrelat Github public repositories. The ressources are organized in three sections: tutorial and workshops; dashboards/shiny apps; and companion scripts from published scientific articles.

All scripts were developed by R. Frelat and are under GNU General Public Licence v3.

Last update: February 2026.

Tutorials

All tutorials below suppose basic knowledge of the statistical software R.

• Spatial analysis in R for marine scientists
  Full day workshop, divided in two session of approx. 2h.
  Guidelines and dataset can be download here (67Mb).

  • How to load, extract and analyse spatial data in R?
  • Hands-on multidimensional examples
    
    

• Introduction to food webs metrics
  2h tutorial introducing marine food web analyses and how to compute weighted and unweighted food web metrics.

• Fish morphometrics

  • Fish outline analysis with R
    2h tutorial introducing outline analysis on pictures of fish and how to interpret the output from Elliptical Fourier Transform.
  • Morphometric comparison with R
    Introduction and comparison of 3 morphometric methods: traditional morphometric, geometric morphometric and outline analysis.
    
    

• Applied multivariate analysis

  • Introduction to multivariate analysis : from 2D to 3D
    2h tutorial introducing classic Principal Component Analysis and its extensions in 3 dimensions called Tensor Decomposition. Guidelines and dataset can be download here
    
  • Methods to study traits-environment relationship
    Including advanced multivariate analysis (RLQ analysis), and Bayesian modeling (Hierarchical Modelling of Species Communities).
  • Introduction to principal component analysis for measuring gender context
    2h tutorial introducing Principal Component Analysis and its interpretation in the gender perspective
    
    

• Resilience Assessment
  R vignette to introduce the cuspra R-package for the quantification of resilience based on empirical data using the stochastic cusp model

• Version control with git and GitHub
  Short introduction to reproducible research practices for international research groups

Dashboards and Shiny Apps

• Farm household exploration dashboard: https://startistic.shinyapps.io/farmhousehold_explo/
  Interactive dashboard to help understand the diversity of farming systems.
  The dashboard is part of the farmhoushold R package that provides tools to analyse farm household data.

• CUSPRA Dashboard: https://rfrelat.shinyapps.io/CUSPRA/
  Interactive dashboard to quantify the resilience based on empirical data using the stochastic cusp model (Sguotti et al. 2024)

• GAIA Dashboard: https://startistic.shinyapps.io/GAIA_Dashboard/
  Interactive dashboard to Guiding Acid Soil Investments in sub-Saharan Africa DOI: 10.5281/zenodo.7242765

• COMITA: https://rfrelat.shinyapps.io/comita
  Comparative tools for Integrative Trend Analysis developed as an R-package for the ICES working group COMEDA. More explanations can be found in the report of the working group:
  ICES. 2019. Working Group on Comparative Analyses between European Atlantic and Mediterranean marine ecosystems to move towards an Ecosystem-based Approach to Fisheries (WGCOMEDA). ICES Scientific Reports. 1:49. 30 pp. DOI 10.17895/ices.pub.5542

• MetaBTS: https://rfrelat.shinyapps.io/metabts
  Interactive map of the inventory of bottom trawl surveys (Maureaud A. et al. in 2020).

Open science

Below is a list of companion data and scripts from published articles, ordered chronologically:

• Börner, G., Frelat, R., Akimova, A., van Damme, C., Peck, M. A., & Moyano, M. (2025). “Autumn and winter plankton composition and size structure in the North Sea”. Marine Ecology Progress Series, 753, 1-18. DOI 10.3354/meps14767 data+script: https://github.com/rfrelat/Plankton_Size_NorthSea_Dynamics DOI 10.5281/zenodo.13616726

• Sguotti, C., Vasilakopoulos, P., Tzanatos, E., & Frelat, R. (2024). “Resilience assessment in complex natural systems”. Proceedings of the Royal Society B, 291, 20240089. DOI 10.1098/rspb.2024.0089
  data+script: DOI 10.5281/zenodo.10912017
  R-package: https://github.com/rfrelat/cuspra
  tutorial: https://rfrelat.github.io/cuspra.html

• Frelat, R., Kortsch, S., Kröncke, I., Neumann, H., Nordström, M. C., Olivier, P. E., & Sell, A. F. (2022). “Food web structure and community composition: a comparison across space and time in the North Sea”. Ecography, 2: e05945. DOI 10.1111/ecog.05945
  data+script: https://github.com/rfrelat/NorthSeaFoodWeb

• Lopez, D. E., Frelat, R., & Badstue, L. B. (2022). “Towards gender-inclusive innovation: Assessing local conditions for agricultural targeting“. Plos one, 17(3), e0263771. DOI 10.1371/journal.pone.0263771
  data+script: https://github.com/rfrelat/GenderClimate
  tutorial: https://rfrelat.github.io/GenderClimate.html

• Quitzau, M., Frelat, R., Bonhomme, V., Möllmann, C., Nagelkerke, L., & Bejarano, S. (2022). “Traits, landmarks and outlines: Three congruent sides of a tale on coral reef fish morphology.” Ecology and Evolution, 12, e8787. DOI 10.1002/ece3.8787
  data+script: https://github.com/rfrelat/CoralFish
  tutorial: https://rfrelat.github.io/CoralFishes.html

• Emblemsvåg, M., Werner, K. M., Núñez-Riboni, I., Frelat, R., Torp Christensen, H., Fock, H. O., & Primicerio, R. (2022). “Deep demersal fish communities respond rapidly to warming in a frontal region between Arctic and Atlantic waters“. Global Change Biology, 28(9), 2979-2990. DOI 10.1111/gcb.16113
  data+script: https://github.com/rfrelat/GreenlandFish

• Kortsch, S., Frelat, R., Pecuchet, L., Olivier, P., Putnis, I., Bonsdorff, E., … & Nordström, M. C. (2021). Disentangling temporal food web dynamics facilitates understanding of ecosystem functioning. Journal of Animal Ecology. 90: 1205– 1216. DOI: 10.1111/1365-2656.13447
  raw data: DOI:10.5061/dryad.6t1g1jwwn
  data+script+tutorial: https://rfrelat.github.io/BalticFoodWeb.html

• Maureaud, A., Frelat, R., Pécuchet, L., Shackell, N., Mérigot, B., Pinsky, M. L., … & T Thorson, J. (2021). “Are we ready to track climate‐driven shifts in marine species across international boundaries?‐A global survey of scientific bottom trawl data”. Global change biology, 27(2), 220-236. DOI 10.1111/gcb.15404
  data+script+updated database: https://github.com/AquaAuma/TrawlSurveyMetadata
  Shiny app: https://rfrelat.shinyapps.io/metabts

• Beukhof E, Frelat R, Pécuchet L, Maureaud A, Dencker TS, Sólmundsson J, Punzon A, Primicerio R, Hidalgo M, Möllmann C and Lindegren M. “Marine fish traits follow fast-slow continuum along coastal-offshore gradient.”, Scientific Report, 9: 17878 DOI: 10.1038/s41598-019-53998-2
  data+script: Deposited in Dryad Digital Repository: https://doi.org/10.5061/dryad.ttdz08kt8.

• Olivier, P., Frelat, R., Bonsdorff, E., Kortsch, S., Kröncke, I., Möllmann, C., … and Nordström, M. C. (2019). “Exploring the temporal variability of a food web using long‐term biomonitoring data”. Ecography, 42(12):1-19, DOI 10.1111/ecog.04461.
  data: Deposited in Dryad Digital Repository: https://doi.org/10.5061/dryad.9tg3t75

• Caillon F., Bonhomme V., Möllmann C. and Frelat R. (2018). “A morphometric dive into fish diversity”, Ecosphere, 9(5): e02220. DOI 10.1002/ecs2.2220
  data+script+tutorial: https://rfrelat.github.io/FishMorpho.html

• Frelat R, Orio A, Casini M, Lehmann A, Mérigot B, Otto SA, Sguotti C, Möllmann , (2018). “A three-dimensional view on biodiversity changes: spatial, temporal and functional perspectives on fish communities in the Baltic Sea”, ICES Journal of Marine Science, 75(7): 2463–2475. DOI 10.1093/icesjms/fsy027
  data+script: Deposited as Supplemetary material

• Frelat R, Lindegren M, Dencker TS, Floeter J, Fock HO, Sguotti C, Stäbler M, Otto SA and Möllmann C (2017). Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities. PLoS ONE, 12(11): e0188205. DOI 10.1371/journal.pone.0188205
  data+script+tutorial: https://rfrelat.github.io/Multivariate2D3D.html