Stable Isotope Mixing Models for Dietary Reconstruction

Introduction & Theoretical Foundations

Chronologies

10 April 2026

Introduction & Theoretical Foundations

Stable Isotope Mixing Models for Dietary Reconstruction | Module 1

This module establishes the conceptual and mathematical foundations on which all subsequent mixing-model work rests.

Learning Outcomes

By the end of this session you should be able to:

  • Describe the physical basis of stable isotope fractionation
  • Explain how trophic enrichment is quantified
  • Discuss tissue-specific isotopic routing
  • Apply collagen quality criteria to evaluate specimens
  • Articulate the link between dietary isotope mixing models and the Marine Reservoir Effect

Principles of Stable Isotope Analysis

What Is a Stable Isotope?

Isotopes are atoms of the same element differing in neutron number and therefore atomic mass.

Stable isotopes do not undergo radioactive decay — unlike 14C in radiocarbon dating, they are permanent constituents of the biosphere.


System Light isotope Heavy isotope Abundance (heavy)
Carbon 12C 13C 1.11 %
Nitrogen 14N 15N 0.37 %
Sulphur 32S 34S 4.25 %


The 1 Da (atomic) mass difference is sufficient to produce measurable fractionation at every trophic transfer and biochemical transformation involving bond formation or breakage.

The Physics of Fractionation

Heavier isotopes form slightly stronger bonds & react slightly more slowly.

At every bond-breaking or bond-forming event the lighter isotope is preferentially processed.

The heavier isotope becomes:

  • Enriched in the consumer or product
  • Depleted in what is left behind

Because this repeats at every trophic step, the isotopic signal accumulates predictably up a food chain.

The Delta (δ) Notation

Absolute heavy-isotope abundances are tiny (~1 %), so ratios are reported as per-mil (‰) deviations from an international standard:

\[ \delta X\ (\text{‰}) = \left[\frac{R_{\text{sample}}}{R_{\text{standard}}} - 1\right] \times 1000 \]

where \(R\) = heavy/light isotope abundance ratio.

δ13C — reference: Vienna Pee Dee Belemnite (VPDB)

Values: −35 ‰ (C3 plants) to −7 ‰ (marine fish)

δ15N — reference: atmospheric N2 (AIR = 0 ‰)

Values: ~+2 ‰ (legumes) to +20 ‰+ (apex marine predators)

Analytical Measurement

Stable isotope ratios are measured by Isotope Ratio Mass Spectrometry (IRMS).

In continuous-flow (CF-IRMS) configurations, sample combustion and MS introduction are integrated:

  • As little as 0.3–1.0 mg of collagen required
  • Typical precision: ±0.1–0.2 ‰ (1σ) for both δ13C and δ15N
  • δ13C and δ15N measured simultaneously on a single run

±0.1–0.2 ‰ precision is sufficient to resolve trophic-level differences, which are typically 3–5 ‰ per level for nitrogen.

The δ¹³C / δ¹⁵N Biplot

Figure 1

Why δ13C and δ15N? (and if you have the money δ34S)

δ13C discriminates:

  • C3 vs. C4 plant consumers
  • Terrestrial vs. marine protein sources

δ15N tracks trophic level:

  • Each step up enriches 15N by ~3–5 ‰
  • Apex marine predators ≈ +18–20 ‰

δ13C and δ15N place individuals in a 2-D isotope space reflecting the main axes of dietary variation — and both can be measured simultaneously from a few milligrams of collagen in a single IRMS run.

Sulphur (δ34S) adds a third isotopic axis to dietary mixing models, which is particularly valuable because its fractionation pathway is largely independent of C and N metabolism — meaning it responds to different environmental and dietary signals. It’s especially useful for distinguishing marine from terrestrial protein sources (since oceanic sulphur has a distinct signature around +20‰ compared to terrestrial values nearer 0–10‰), and for separating foodwebs that overlap in δ¹³C/δ¹⁵N space but occupy geologically distinct landscapes with different bedrock sulphur inputs.

Isotopic Fractionation and Trophic Level Effects

Two Types of Fractionation

Equilibrium fractionation

Heavy and light isotopes have slightly different bond energies → temperature-dependent → primary driver of 13C partitioning during carbonate precipitation.

Kinetic fractionation

Lighter isotopes react faster → drives trophic enrichment: every time an enzyme breaks or forms a bond, the lighter isotope is processed preferentially, leaving the heavier isotope enriched in consumer tissue.

For most archaeological and ecological applications, kinetic fractionation dominates. Its predictable, stepwise nature is what makes stable isotopes such a powerful dietary tool.

Trophic Enrichment Factors (TEFs)

When an organism synthesises tissue from diet, fractionation produces systematic isotopic enrichment. These offsets are TEFs (also: discrimination factors), denoted Δ (capital delta):

\[\Delta^{13}C = \delta^{13}C_{\text{tissue}} - \delta^{13}C_{\text{diet}}\]

\[\Delta^{15}N = \delta^{15}N_{\text{tissue}} - \delta^{15}N_{\text{diet}}\]

When an animal eats food and builds tissue from it, the biochemical processes involved (transamination, deamination, protein synthesis etc.) are not isotopically neutral. Lighter isotopes tend to be preferentially lost or excreted, meaning the tissue ends up slightly enriched in the heavier isotope relative to what was consumed. The TEF (or Δ) simply quantifies that offset.

Published TEF Estimates for Human Bone Collagen

Source Δ¹³C (‰) Δ¹⁵N (‰)
Ambrose & Norr 1993 +1.0 +3.4
Bownes et al. 2017 1+1.0 +5.5±0.5
O’Connell et al. 2012 n/a ~+6.0
Fernandes et al. 2015 +4.8 ± 0.5 +5.5±0.5
Common mixing-model default +4.8 ± 0.5 +5.5±0.5

TEF values are not universal constants. They vary with tissue type, metabolic state, protein quality, latitude, and season. Always justify your choice, propagate its uncertainty using the reported SD, and conduct sensitivity analyses before drawing dietary conclusions.

The Trophic Step Effect on δ¹⁵N

At each trophic level, δ15N increases ~3–5 ‰ because:

  • Animals digest protein → lighter 14N preferentially lost in urine as urea/ammonia
  • Heavier 15N retained in body tissue
  • Effect repeats at every predation event → staircase pattern through the food web
Dietary group Approx. δ¹⁵N range (‰)
Legumes (N2-fixing) 0 – 2
C3 terrestrial herbivores 4 – 8
Omnivorous humans (mixed plant/animal) 8 – 12
Marine or freshwater fish consumers 13 – 18

⚠️ Archaeological Confounders of δ¹⁵N

Elevated δ15N is not always diagnostic of high-status meat consumption:

  • Manured soils elevate baseline plant δ15N, cascading up the food web
  • Breastfed neonates show apparent trophic elevation (~+2–3 ‰) relative to their mothers
  • Physiological stress (starvation, illness) can increase tissue δ15N through net protein catabolism
  • Arid environments tend to have systematically elevated δ15N baselines throughout the ecosystem

Isotopic Routing and Tissue-Specific Considerations

What Is Isotopic Routing?

Isotopic routing = the differential biochemical fate of dietary macronutrients — proteins, lipids, and carbohydrates — during tissue synthesis.

It has profound implications for interpreting collagen isotope data and for constructing mixing models, because collagen does not reflect bulk diet uniformly across all macronutrient classes.

Carbon Routing to Bone Collagen

Bone collagen is synthesised almost entirely from amino acids, and these are preferentially sourced from dietary protein:

  • Dietary protein carbon contributes ~60–80 % of collagen carbon (Ambrose & Norr 1993)
  • Dietary carbohydrate and lipid contribute relatively little, even when they dominate caloric intake
  • Bone collagen δ13C is therefore a better proxy for dietary protein source than for total diet

Practical consequence: end-member values in a collagen-based mixing model should reflect the protein-derived signal from each food source, not the bulk food δ13C. Especially critical for protein-poor, high-carbohydrate diets (millet- or maize-dependent communities).

Tissue Turnover Rates

Different tissues record dietary signals over different timescales — directly analogous to the integration window concept in radiocarbon dating.

Tissue Integration period Dietary window
Bone collagen 10–30+ years (remodelling-dependent) Long-term adult average
Bone carbonate Similar to collagen Long-term whole-diet average
Dentine collagen Childhood; minimal turnover Diet during crown formation (age 0–12 yr)
Enamel carbonate Childhood; no remodelling Diet during enamel formation
Hair keratin ~1–3 months per cm Recent / seasonal diet
Nail ~6 months (fingernail) Recent diet
Muscle (soft tissue) ~180 days Recent diet (rarely preserved)

Comparing adult bone collagen with dentine collagen from the same individual provides a longitudinal perspective on dietary change across the life course — useful for studying weaning, migration, and social transitions.

Archaeological Applications

Historical Development of the Field

Year Milestone
1978 van der Merwe & Vogel — δ13C as a diet tracer; maize adoption in North America
1984 Schoeninger & DeNiro — global reference dataset; marine vs. terrestrial signatures
1993 Ambrose & Norr — controlled diet experiments; isotopic routing to collagen
2008 Parnell et al. — Bayesian mixing models (SIAR)
2010s– MixSIAR, FRUITS, ReSources — probabilistic frameworks with formal uncertainty

Research Questions Addressed

Research question Primary signal Context
C3 vs. C4 plant staple adoption δ13C collagen + apatite Agricultural transitions
Marine vs. terrestrial protein δ13C + δ15N collagen Coastal/island populations
Trophic level & animal protein quantity δ15N collagen Social differentiation studies
Breastfeeding and weaning age δ15N in infant/juvenile dentine Infant burials
Freshwater fish reliance δ13C + δ15N (aquatic reservoir) Riparian settlements
Geographic mobility & migration δ87Sr + δ18O + δ13C combined Multi-isotope provenance models
Social status & dietary differentiation δ13C + δ15N + δ34S Cemetery analyses

Relevance to Radiocarbon Practitioners

The Marine Reservoir Effect connection

Stable isotope data are routinely collected from specimens submitted for 14C dating — the δ13C used to correct for isotopic fractionation in AMS dating comes from the same collagen extract.

High marine protein intake (elevated δ13C and δ15N) is directly implicated in the Marine Reservoir Effect, which can cause apparent age offsets of several centuries if unaccounted for.

Mixing-model dietary estimates are increasingly used to quantify the proportion of marine protein in diet and thereby calculate a site-specific 14C offset (ΔR correction).

Collagen Quality Assessment

Why Quality Assessment Matters

Before any mixing model can be constructed, collagen extract quality must be assessed. Degraded collagen introduces systematic bias because isotope ratios shift with diagenetic alteration.

Standard acceptance criteria:

Criterion Acceptable range Reference
C:N atomic ratio 2.9 – 3.6 DeNiro 1985
Carbon content (%C) 30 – 45 % van Klinken 1999
Nitrogen content (%N) 11 – 16 % van Klinken 1999
Collagen yield ≥ 1 % of bone dry weight Longin 1971

The C:N ratio is the most widely used single criterion in practice.

The DeNiro Acceptance Window

Figure 2

Learning Outcomes Checklist

  1. Define the delta notation and explain why it is used in preference to absolute isotope ratios
  2. Describe the physical basis for 13C fractionation during C3 and C4 photosynthesis, and explain its dietary significance
  3. Explain the TEF for δ15N and describe the range of values expected across a terrestrial food web
  4. Define isotopic routing and explain why bone collagen δ13C preferentially reflects dietary protein carbon
  5. Distinguish the dietary integration windows of bone collagen, dentine, and soft tissues
  6. Outline at least four distinct archaeological research questions amenable to isotope mixing-model analysis
  7. Apply collagen quality criteria to evaluate whether a specimen is suitable for dietary isotope analysis
  8. Articulate the link between dietary isotope mixing models and the Marine Reservoir Effect in radiocarbon dating