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Training videos

Workshop 1: An Introduction to the HE Toolkit

This workshop is aimed at hydro-ecologists who have some basic experience with the R software package and wish to analyse open-source environmental monitoring data. The training covers:

  • An introduction to the HE Toolkit
  • Data import
  • Flow processing
  • Biological data processing
  • Data exploration

Workshop 2: An Introduction to Hydro-ecological Modelling using the HE Toolkit

This workshop is aimed at more experienced data analysists who are interested in developing statistical models for understanding and predicting ecological responses to changes in river flow. Building on Workshop 1, it covers:

  • Mixed effects models
  • Data assembly
  • Data exploration
  • Model fitting
  • Model selection
  • Model diagnostics
  • Applications

The videos can be accessed through APEMs YouTube channel on the links below.

Workshop 1

Workshop 2

Training project

Two example projects are hosted on PositCloud.

The workshop 1 project includes example code covering data import, processing and exploration

The workshop 2 project includes example code covering flow statistics, additional data exploration and model selection.

To access the projects, you first need to set up an account for PositCloud. Then navigate to the projects using the links below. This will open a temporary copy of the project. Please ensure you select “Take a Permanent Copy” at the top to move a copy of the project into your own workspace before making any changes to the project.

Links to the projects can be found below:

Workshop 1

Workshop 2

Further Reading

Accessible introductions to linear mixed-effects modelling

  • Harrison, X.A. et al. (2018). A brief introduction to mixed effects modelling and multi-model inference in ecology. PeerJ, 6, p.e4794.
  • Zuur, A. F., Ieno, E. N., Walker, N. J., Saveliev, A. A. and Smith, G. M. (2009). Mixed effects models and extensions in ecology with R. London, UK: Springer
  • Lots more online e.g. GLMM FAQ

Accessible introductions to generalised additive modelling

  • Pedersen, E.J., Miller, D.L., Simpson, G.L. and Ross, N. (2019). Hierarchical generalized additive models in ecology: an introduction with mgcv. PeerJ, 7:e6876, https://doi.org/10.7717/peerj.6876 Wood, S.N. (2017). Generalised Additive Models: An Introduction with R. Chapman and Hall, New York.

Example applications to macroinvertebrate data

  • Dunbar, M.J., Lauge Pedersen, M., Cadman, D., Extence, C., Waddingham, J, Chadd, R. and Larsen, S.E. (2009). River discharge and local scale habitat influence macroinvertebrate LIFE scores. Freshwater Biology, 55, 226–242. doi:10.1111/j.1365-2427.2009.02306.x
  • Dunbar, M.J., Warren, M., Extence, C., Baker, L., Cadman, D., Mould, D.J., Hall, J. and Chadd, R. (2010). Interaction between macroinvertebrates, discharge and physical habitat in upland rivers. Aquatic Conservation: Marine and Freshwater Ecosystems, 20(S1), S31-S44.
  • England, J., Chadd, R., Dunbar, M.J., Sarremejane, R., Stubbington, R., Westwood, C.G. and Leeming, D.J. 2019. An invertebrate-based index to characterize ecological responses to flow intermittence in rivers. Fundamental and Applied Limnology, DOI: 10.1127/fal/2019/1206
  • Sarremejane, R., England, J., Dunbar, M.J., Brown, R., Naura, M. and Stubbington, R. (2024). Human impacts mediate freshwater invertebrate community responses to and recovery from drought. Journal of Applied Ecology, 61, 2616–2627, https://doi.org/10.1111/1365-2664.14771