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Application of stable isotopes in

trophic ecology: Importance of TEF and seasonal baseline

for robust interpretations

François REMY, Aurélie Melchior, Thibaud mascart & Gilles Lepoint

Laboratory of Oceanology University of Liège

Mixing Law in trophic ecology:

“You are what you eat,

plus a few permil…” (DeNiro &

Epstein 1976)

Why using stable isotopes in trophic ecology?

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δ15N

δ13C

>>>

<

« …plus a few permill… »

Trophic enrichment factor

TEF

QUESTION :

Can we calculate the contribution of each potential food source

of an animal diet from the isotopic compositions?

?

? ?

?

? ?

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Yes !! Using Mixing Models

𝜹𝒎 = 𝒇𝒂𝜹𝒂+ 𝒇𝒃𝜹𝒃 + 𝒇𝒄𝜹𝒄 +⋯ 𝒇𝒂𝜹𝒂+ 𝒇𝒃𝜹𝒃 + 𝒇𝒄𝜹𝒄+⋯ = 𝟏

For n sources the mixing equation is :

Complex Bayesian Mixing models : SIAR, MixSIAR, FRUITS…

See : Parnell et al. 2010; Fernandes et al. 2014…

Case study 1 : TEF determination for the amphipod

Gammarus aequicauda

1 cm

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50-90 % exported

Posidonia oceanica meadow

« Dead leaves litter »

François Remy ©

P.oceanica dead leaves

Macro-algae

Micro-organisms

François Remy ©

P.oceanica living leaves

EA-IRMS (Isoprime100® IRMS+Vario MicroCube®EA)

+

GC-MS (Agilent7890A ®)

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G. aequicauda : what we knew…

δ13C (‰)

δ1

5N

(‰

)

Litter consumer !

SIAR run with litterature TEF wrong !!

Litter S.algae Epiphytes Animal

Contr

ibution o

f each s

ourc

e

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3 different treatments : • Freshwater amphipod powder

• Green algae powder

• Dead P. oceanica powder

(1-2 mm powder)

Different carbon isotopic compositions Different quality (C/N) All potentially ingestible by G. aequicauda

Experimental design

Experimental design

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δ13C = -24.86 + 8.62e-0,0591t

t1/2 = 11.72 days

R² = 0,8019

P < 0.000001

Food source δ13C

Results

Trophic Enrichment Factors : TEFs or Δ

Treatment 1 typical of predator Treatments 2 & 3 typical of primary detritic-feeder

1 2 3

Amphipod treatment Algae treatment Litter treatment

Δ13

C (‰) 0.81 ± 0.39 / 1.19 ± 0.13

Δ15

N (‰) 2.91 ± 0.56 0.53 ± 0.44 0.96 ± 0.42

Results

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Litter S.algae Epiphytes Animal

Contr

ibution o

f each s

ourc

e

SIAR new run with custom TEF better !!

TEF = major parameter

Case study 2 - Isotopic composition modifications:

baseline variations vs. real diet shift?

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-20

24

68

ENTIRE COMMUNITY

d13C

d1

5N

δ15N

δ13C

Summer Harbor

Summer Oscelluccia

Autumn Harbor

Autumn Oscelluccia

Winter Harbor

Winter Oscelluccia

Spring Harbor

Spring Oscelluccia

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31/10/12 – 16:00h 01/11/12- 10:00h

Mean thickness: 53,4 cm

Cover : 100%

Mean thickness: 1,8 cm

Cover : < 5%

Litter patches are dynamic places!

Potential effect on food availability/type !!

Sampling design

• 4 seasons

• 2 sites

• Litter, macrofauna AND potential food sources

STARESO harbor

Oscelluccia

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Dead litter

Living Posidonia

Red algae

Epiphytes +

Green algae

Food sources :

Trophic level 1

Trophic level 2

Trophic level 3

Trophic level 4

Results

Isotopic niches

Ellipses metrics

…

For more information SIBER

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δ13C

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5 DOMINANT SPECIES

d13C

d1

5N

δ1

5N

δ13C

Gammarella fucicola

Gammarus aequicauda

Athanas nitescens

Palaemon xiphias

Melita hergensis

Interspecific

niches variations

Results

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24

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Gammarella fucicola

d13C

d1

5N

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Gammarus aequicauda

d13C

d1

5N

δ1

5N

δ13C δ13C

δ1

5N

Gammarus aequicauda Gammarella fucicola

Summer Harbor

Summer Oscelluccia

Autumn Harbor

Autumn Oscelluccia

Winter Harbor

Winter Oscelluccia

Spring Harbor

Spring Oscelluccia

Spatio-temporal intraspecific level niche variations

Results

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Palaemon xiphias

d13C

d1

5N

Palaemon xiphias

Summer Harbor

Summer Oscelluccia

Autumn Harbor

Autumn Oscelluccia

Winter Harbor

Winter Oscelluccia

Spring Harbor

Spring Oscelluccia

δ1

5N

δ13C

Also true for their predator…

Results

Question : are these clear variations due

to actual diet modifications or only to a

baseline shift of the food sources?

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C

S2 S1

C

S2 S1

C

S2 S1

δ1

5N

δ13C

δ1

5N

δ13C

δ1

5N

δ13C

≠

Highly simplified example…

Diet shift Baseline shift

How to answer that question?

Time to remember an old friend :

SIAR

Why?

It uses food sources compositions

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0.0

0.2

0.4

0.6

0.8

1.0

Proportions by group: 1

Source

Pro

po

rtio

n

L RA EA

0.0

0.2

0.4

0.6

0.8

1.0

Proportions by group: 1

Source

Pro

po

rtio

nL RA EA

0.20

0.78

0.02

0.86

Dead Litter

Red Algae

Epiphytes

+

Green Algae

Dead Litter

Red Algae

Epiphytes

+

Green Algae

Gammarus aequicauda, summer, site 1 Gammarus aequicauda, autumn, site 1

Pro

port

ion o

f fo

od s

ourc

e

Pro

port

ion o

f fo

od s

ourc

e

Real diet change independently of food sources isotopic composition!

Results Use of the custom TEF

from Case study 1 !! 0

.00

.20

.40

.60

.81

.0

Proportions by group: 1

Source

Pro

po

rtio

n

GA GF

0.0

0.2

0.4

0.6

0.8

1.0

Proportions by group: 1

Source

Pro

po

rtio

n

GA GF

0.05

0.95

0.04

0.96 Gammarus

aequicauda

Gammarella

fucicola

Gammarus

aequicauda

Gammarella

fucicola

Palaemon xiphias, summer, site 1 Palaemon xiphias, autumn, site 1

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Palaemon xiphias

d13C

d1

5N

For P. xiphias looks more like a baseline shift

BUT : warning…

Pro

port

ion o

f fo

od s

ourc

e

Pro

port

ion o

f fo

od s

ourc

e

Results

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SIBER+SIAR

Variations of “isotopic niche”

Potential origin of the changes

BUT…

Need to sample sources

Specific level data analysis when possible

TEF are a major parameter

Acknowledgment

The authors warmly thank the STARESO field station

staff for their support during the sampling campaign.

The first author acknowledges a PhD F.R.I.A. grant (Fund

for Research training in Industry and in Agriculture) of the

Belgian National Fund for Scientific Research (FRS-

FNRS).

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Thank you for your attention !