Applied causal analysis methods for ecologists

The WSL-Eawag Biodiversity Center is pleased to announce a three-day workshop on causal analysis methods for ecologists. The workshop is open to WSL and Eawag staff working with observational data, including MSc and PhD students.

Applications are accepted on a rolling basis until the course is full. The first round of application reviews will take place on 31 July.

A core group of participants will have the opportunity to work with Jim Grace in advance of the workshop to help tailor the course to their research questions. If you are interested in joining the core group, please apply and contact us by 31 July.

James Grace, Affiliate professor at Concordia University

https://www.jbgrace.com

The ability to propose causal interpretations of research findings is central to scientific progress. The weighing of mechanistic knowledge and statistical evidence towards this endeavor has historically been largely informal and left to the judgement of subject matter experts. In recent years, statistical formalizations have described evidential requirements for causal interpretations of non-experimental data without acknowledgement or consideration of mechanistic causal knowledge. The widespread promotion of this incomplete approach has created a crisis that is beginning to be addressed. The US National Academies of Science, Engineering, and Medicine have now (in 2022) described the need for a multi-evidence approach that considers evidence from mechanistic, statistical, and manipulative studies. They further endorse that assessments be based on weight-of-evidence as judged by subject matter experts. Most recently, a multi-evidence paradigm for causal investigations has been described and a formal approach to documenting and accumulating causal knowledge has been developed. The key to success in causal analysis is now seen to require (1) a recognition of the multiple forms of evidence relevant to real-world causation, (2) a need to document and consider existing causal knowledge prior to deciding the most appropriate statistical techniques, and (3) a need to develop and demonstrate approaches to integrating forms of evidence.

This workshop will include the following:

1. Description of foundational principles for causal analysis and illustration of the terms and semantics needed to convey critical distinctions of importance, which have been badly neglected leading to great confusion of the in the literature. 
2. Application of the new formal procedures of causal knowledge analysis to individual projects so work can be aligned with the requirements for building causal knowledge. 
3. Discussions of new evidence to consider, including direct observations, mechanistic interpretations, available data, and suitable data analysis choices (e.g., Grace et al. 2025a).
4. The afternoon of the final day will be reserved for individual presentations and discussions.

Early career researchers and other researchers at WSL and Eawag working with observational data. Ten places are reserved for PhD and MSc students.

• Prepare your own research questions and associated data (if available) that you would be interested in pursuing in the practical part of the course
• Presence at input lectures and active participation in exercises.
• Read the recent literature (Grace et al., 2025, Ecology Letters⁴)
• Own computer with an up-to-date version of R and of the packages lavaan and piecewiseSEM.

• Optional: familiarize themselves with SEMs through https://jslefche.github.io/sem_book/

   

MSc/PhD Student participation:

• Students are expected to present their group work at a causal analyses-themed biodiversity seminar following the course.

The course is free of charge, but participants are expected to cover their travel, accommodation, and meals during the course. 

If you are interested in the course as a MSc/PhD student but your research group cannot cover your expenses, please get in touch with us.

Send an email to seraina.cappelli(at)slf.ch and noemie.pichon(at)wsl.ch with the subject line “Registration Causal Analyses in Ecology”. Please attach a brief description of what research question/s you are working on/interested in, and if you have data available to do so. Applications will be accepted until the course is full. The first round of applications will be reviewed on 31 July.

Important: Jim Grace will tailor the course to the participants' interests and research questions. We are looking for a core group of researchers who are interested in trying out the methods in advance to help shape the course content. This is a unique opportunity to get first-hand counselling and help you start/advance your analyses. If you are interested in being part of this core group, please apply to the course and contact us by 31 July (seraina.cappelli(at)slf.ch and noemie.pichon(at)wsl.ch).