Stable Isotope Ecology - Theory, Data and Effective Applications

 

Five days. Theory and R. From environmental baselines to Bayesian food web analysis.

 

FORMAT & PRACTICALITIES

Format: Live online · Zoom or equivalent · Small cohort (max ~15 participants)

Duration: 10:00–15:00 GMT with breaks

Daily structure: Morning session (theory/methods) + Afternoon session (R practical / Q&A)

Total contact time: ~25 hours across the week

Software: R and RStudio (free) — installation guide sent on registration

Materials: All R scripts, datasets, and session recordings provided

Prerequisites: Background in ecology or environmental science. Prior R experience helpful but not required. No prior isotope experience needed.

​

​

INTRODUCTION

Some researchers don't have a semester to spare. They have data on their desk, a paper in progress, or a grant proposal that requires isotope methods they haven't used before. The Intensive Week is designed for them.

Over five days, you'll cover the full scope of stable isotope ecology — environmental isotope systems, trophic applications, and a complete R-based data analysis pipeline — at a pace that suits researchers who already know their way around ecological data. The course assumes a working background in ecology, but prior experience with stable isotopes is not required. Each day combines conceptual sessions with hands-on R practicals, and every session includes dedicated Q&A time. The final afternoon is reserved entirely for participant data — bring your own dataset and we'll work through it together.-

 

WHO IS THIS FOR?

• Postdoctoral Researchers - Starting a project that involves stable isotopes, or adding isotope methods to an existing research programme. You need to get up to speed fast without sacrificing depth.

• Research Professionals - Government scientists, environmental consultants, agency ecologists, and industry researchers working with isotope data — or evaluating whether isotopes are the right tool for a question.

• Advanced Graduate Students - PhD students who are isotope-adjacent and need to move beyond the basics, or students approaching their analytical chapters who need the R skills now.

• Established Academics - Researchers supervising isotope work for the first time, or incorporating a new isotope system into their lab's toolkit.

​​​

THE WEEK — DAY BY DAY:

 

MONDAY — Isotope Foundations & Environmental Systems

Morning: The Science of Stable Isotopes - A focused primer that covers the material experienced researchers need without dwelling on what you already know. Delta notation, isotopic fractionation, and the international reference standards (VPDB, AIR, VSMOW, CDT) that make measurements comparable across labs. How isotopes are measured: EA-IRMS sample preparation, instrument principles, and what good analytical precision looks like.

Afternoon: Carbon and Nitrogen in the Environment - The two workhorses of isotope ecology in depth. Carbon: photosynthetic pathway discrimination (C3/C4, ~13‰ difference), the Suess effect, and how δ¹³C varies across terrestrial, freshwater, and marine systems — including the distinct isotopic zones of lakes. Nitrogen: the global N cycle, Haber-Bosch and its isotopic fingerprint, how δ¹⁵N varies across ecosystems, and dual isotope approaches (δ¹⁵N + δ¹⁸O) for pollution and nitrate source tracing.---**

 

TUESDAY — H, O, S + Isotopes in Organisms

Morning: Hydrogen, Oxygen, and Sulphur - Water isotopologues, Rayleigh distillation, and the Global Meteoric Water Line. How precipitation isotopes create geographic patterns — and how those patterns are mapped in isoscapes for migration research, hydrology, and forensic applications. Palaeoclimate reconstruction from ice core records. Sulphur cycling in marine, freshwater, and terrestrial systems; δ³⁴S as a tracer of marine-terrestrial boundaries, chemotrophic energy pathways, and environmental change.*Afternoon: Isotopes in Organisms*"You are what you eat, plus or minus a little bit." Trophic enrichment factors, isotope routing, and how fractionation varies across tissue types. The critical distinction between inert tissues (keratin, bone, enamel) and continuously-turning tissues (muscle, liver, blood) — and the half-lives that determine what each tissue represents temporally. Multi-tissue approaches for diet history and movement reconstruction. Individual dietary specialisation: population generalists vs populations of specialists, and how to tell them apart with isotopes.---**

 

WEDNESDAY — Trophic Applications + R Foundations

Morning: The Trophic Toolkit — Concepts and Critical Thinking - Biplots as the foundation of food web isotope analysis: what the axes mean, what shapes the isotope space, and how to generate — and test — ecological hypotheses from biplot structure. Mixing models: why they're powerful, why they're frequently misused, and the assumptions that must be satisfied before you run one. Conceptual walkthrough from two-source linear models to Bayesian approaches. Trophic position: the multiple-baseline problem and why it matters. Isotopic niche: what SIBER ellipses represent, and what they don't.

Afternoon: R Setup + Data QC + Biplots - RStudio, R Projects, and R Markdown for reproducible isotope analysis. Importing lab output and understanding what you're looking at. Data quality control: evaluating reference material precision, lipid corrections using C:N ratios, checking for inorganic carbon contamination in aquatic samples. Building publication-quality biplots in ggplot2 and interpreting them ecologically.---**

 

THURSDAY — Mixing Models + Trophic Position

Morning: Mixing Models in R - Hands-on progression through four levels of mixing model complexity, using a real Finnish lakes dataset (whitefish and perch). Two-source mixing models from scratch — understanding every term before the Bayesian packages take over. simmr: Bayesian mixing models with MCMC (JAGS backend), setting priors, running chains, checking convergence, and interpreting posterior distributions rather than point estimates. CoSimmr: incorporating individual or group-level covariates — lake, species, body size — directly into the mixing model.

Afternoon: Hierarchical Models + Trophic Position - MixSIAR for complex hierarchical study designs: individuals nested within groups nested within sites. When to use it and how to structure your data. Trophic position in R: the two-source baseline model implemented from first principles, then the trophicPosition Bayesian R package (Harrod & Quezada-Romegialli) for full uncertainty propagation. Discussion of bulk vs compound-specific approaches (AA-CSIA, Chikaraishi equation) and when they matter.

 

FRIDAY — Niche, Food Webs + Your Data

Morning: Isotopic Niche + Food Web Metrics - SIBER in R: calculating standard ellipse areas (SEAb), niche overlap between species and sites, and nicheTools for additional niche metrics. Interpreting niche results critically — what drives isotopic niche width beyond diet. Layman food web metrics: all six metrics (NR, CR, TA, CD, MNND, SDNND) calculated in R with Bayesian credibility intervals, compared across the Finnish lake communities. What each metric captures ecologically, and what changes in those metrics mean.

Afternoon: Participant Data Clinic - The final session belongs to you. Bring your own dataset — raw lab output, a half-finished analysis, a problematic biplot, or a mixing model that won't converge — and we'll work through it together as a group. No prepared slides, no set agenda: just applied problem-solving with your real data, guided by 20 years of isotope experience.Can't bring data yet? This session also works as an extended Q&A and study design workshop — bring your research questions and we'll discuss which methods are appropriate, what data you'll need, and how to avoid the most common isotope pitfalls before you collect a single sample.

 

​

​