Seaweed meadows in the light of global climate change
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Seaweed in the light of global climate change
Alexander [email protected]
Marine Ecology Research GroupFaculty of Biosciences and Aquaculture
University of NordlandNorway
53rd NEAS SymposiumAlgae as Model Systems
27.04.2014
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Contributors
Galice Hoarau
Irina Smolina
Jorge Fernandes
James A. Coyer
Spyros Kollias
Jeanine L. Olsen
Heroen Verbruggen Lennert TybergheinHavkyst projects: 196505, 203839, 216484
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
CO2 increase since the industrial revolution
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Recent land and ocean warming
Christiansen, J.; Scientific American (2013)
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Climate change responses
..
Temperaturerise
.
Heat waves
.
Seasonalityshi
.
Oceanacidifica on
.
Migra on
.
Acclima on
.
Adapta on
.Species
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
High sensitivity of intertidal species
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Seaweeds as model systemsto investigate climate change
Seaweeds provide an excellent system to investigate climate changeimpact
Intertidal key species
Distribution directly limited by temperature tolerance
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Seaweeds are key species in temperateNorth Atlantic regions
© Hoarau, G., 20108 / 60
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Seaweeds are key species in temperateNorth Atlantic regions
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Seaweeds as model systemsto investigate climate change
Seaweeds provide an excellent system to investigate climate changeimpact
Intertidal key species
Distribution directly limited by temperature tolerance
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Temperate seaweed distribution limited by the10℃ summer and the 20℃ winter isotherm
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Seaweeds as model systemsto investigate climate change
Seaweeds provide an excellent system to investigate climate changeimpact
Intertidal key species
Distribution directly limited by temperature tolerance
Range shifts of seaweeds in response to SST-shifts cantrigger major ecological changes
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Recent warming in the North Atlantic
Shift of the 15°C isotherm330 km north
1985 2000
[McMahon & Hays, 2006; Global Change Biol.]
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Predicted northward shift of SST isotherms
Poleward migration of SST isotherms underIPCC scenario A2 until 2100:
30-90 km/decade along North Atlantic shores
[Hansen et al., 2006; PNAS]
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Predicting seaweed range shifts under climate change
..
Migra on
.
Acclima on
.
Adapta on
.Inter dalseaweed
Predominant seaweeds in the North-Atlantic
Fucus serratus Fucusvesiculosus
Ascophyllumnodosum
Shores with biggest ecological change?
Assemblage shift?
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Ecological Niche ModelingPresent-day conditions
Bio-ORACLE database[Tyberghein et al., 2011; Global Ecol. Biogeogr.].
Georeferenced Occurrences
DA (m−1)SST (℃)
SAT (℃)
Ecological Niche Model (Maxent [Phillips et al., 2006; Ecol. Model.])
2000 2100 ? 2200 ?15 / 60
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Ecological Niche ModelingPresent-day conditions
Bio-ORACLE database[Tyberghein et al., 2011; Global Ecol. Biogeogr.].
Georeferenced Occurrences
DA (m−1)SST (℃)
SAT (℃)
Ecological Niche Model (Maxent [Phillips et al., 2006; Ecol. Model.])
2000 2100 ? 2200 ?CO2 emission scenario changes
SST (℃)SAT (℃)
SST (℃)SAT (℃)
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Predicted Niche ShiftsBased on the intermediate IPCC scenario A1B
[Jueterbock et al., 2013; Ecol. Evol.]
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Predicted Niche ShiftsBased on the intermediate IPCC scenario A1B
Habitat gain in the Arctic
[Jueterbock et al., 2013; Ecol. Evol.]
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Predicted Niche ShiftsBased on the intermediate IPCC scenario A1B
Habitat loss in warm temperate areas
[Jueterbock et al., 2013; Ecol. Evol.]
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Predominant seaweeds shift northward as anassemblage
West-Atlantic East-Atlantic
F. serratus F. vesiculosus A. nodosum[Jueterbock et al., 2013; Ecol. Evol.]
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Conclusions from prediced niche shifts
..
Migra on
.
Acclima on
.
Adapta on
.Inter dalseaweed
Biggest ecological change inwarm temperate and Arctic areas
Assemblage shift
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Conclusions from prediced niche shifts
..
Migra on
.
Acclima on
.
Adapta on
.Inter dalseaweed
Biggest ecological change inwarm temperate and Arctic areas
Assemblage shift
18 / 60
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Colonization of Arctic shores
The poleward shift of temperate intertidal seaweeds depends onthree key factors
Dispersal and invasive potentialDark periodCompetitive interactions
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Colonization of Arctic shores
The poleward shift of temperate intertidal seaweeds depends onthree key factors
Dispersal and invasive potentialDark periodCompetitive interactions
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Dispersal and invasive potentialLow dispersal of juvenile stages in fucoid algae
[Braune, 2008; Meeresalgen]
♂ ♀ dioecious
zygote dispersal: <10m
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Dispersal and invasive potential
Flotation vesiclesFucus vesiculosus
Ascophyllum nodosumlow invasive potential
Shipping transport
Fucus serratus
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Dispersal and invasive potentialShipping transport introduced F. serratus to Canada
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Colonization of Arctic shores
The poleward shift of temperate intertidal seaweeds depends onthree key factors
Dispersal and invasive potentialDark periodCompetitive interactions
23 / 60
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Dark period
Poleward shift of Laminaria hyperborea in progress
[Müller et al., 2009; Bot. Mar.]
Recent records
Hiscock, K.
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Colonization of Arctic shores
The poleward shift of temperate intertidal seaweeds depends onthree key factors
Dispersal and invasive potentialDark periodCompetitive interactions
25 / 60
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Competitive interactions
Fucus distichus predominates the Arctic intertidal
Habitat suitability ofF. distichus
based on ENM [Smolina, I., 2012]
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Competitive interactions
[Smolina, I., 2012]
Increase of sympatryzones/hybridization
Competition
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Conclusions from prediced niche shifts
..
Migra on
.
Acclima on
.
Adapta on
.Inter dalseaweed
Biggest ecological change inwarm temperate and Arctic areas
Assemblage shift
27 / 60
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Climate change impact also on subtidal kelp
[Raybaud et al., 2013; PLOS ONE]
Percentage of models forecasting adisappearance of Laminaria digitata
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Ecological Niche Models neglect biotic interactions
Ecological Niche Models do not takebiotic interactions into account
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Biotic interactionsIncreasing mussel recruitment due to rising sea temperatures
replaces rockweed (A. nodosum) beds in Canada
[Ugarte, 2009; J. Appl. Phycol.]
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Biotic interactionsGrazing pressure
[Harley et al., 2012; J. Phycol]31 / 60
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Biotic interactionsGrazing pressure
[Harley et al., 2012; J. Phycol]31 / 60
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Ecological Niche Models neglect species responses
Ecological Niche Models do not takethe plastic or adaptive potential
of species into account
..
Migra on
.
Acclima on
.
Adapta on
.Inter dalseaweed
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Acclimation potential of Fucus serratus
..
Migra on
.
Acclima on
.
Adapta on
.Fucusserratus
Local thermal adaptation?
Areas under highest extinction risk?
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Common-garden heat stress experiments
Norway
Denmark
BrittanySpain
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Common-garden heat stress experiments
Norway
Denmark
BrittanySpain
Bodø
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Common-garden heat stress experiments
Norway
Denmark
BrittanySpain
Bodø
Acclimation at 9℃
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Common garden heat stress experiments
Heat stress, > 6 ind./pop
MeasurementsPhotosynthetic performancehsp gene expression (hsp70, hsp90, shsp)
1h Stress 24h Recovery
9℃
20℃24℃28℃32℃36℃
T (°C)
Time
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Photosynthetic performance
0 4 8 12 16 20 24 28 32 36 ℃
NorwayDenmarkBrittanySpain
Thermal range in year 2200
Measured response
1
1. Performancein 2200
2
2. Resilience
[Jueterbock et al., 2014; Mar. Genomics]36 / 60
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Photosynthetic performance
0 4 8 12 16 20 24 28 32 36 ℃
NorwayDenmarkBrittanySpain
Thermal range in year 2200
Measured response
1
1. Performancein 2200
2
2. Resilience
[Jueterbock et al., 2014; Mar. Genomics]36 / 60
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Photosynthetic performance
0 4 8 12 16 20 24 28 32 36 ℃
NorwayDenmarkBrittanySpain
Thermal range in year 2200
Measured response
1
1. Performancein 2200
2
2. Resilience
[Jueterbock et al., 2014; Mar. Genomics]36 / 60
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Photosynthetic performance
0 4 8 12 16 20 24 28 32 36 ℃
NorwayDenmarkBrittanySpain
Thermal range in year 2200
Measured response
1
1. Performancein 2200
2
2. Resilience
[Jueterbock et al., 2014; Mar. Genomics]36 / 60
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Photosynthetic performance
0 4 8 12 16 20 24 28 32 36 ℃
NorwayDenmarkBrittanySpain
Thermal range in year 2200
Measured response
1
1. Performancein 2200
2
2. Resilience
[Jueterbock et al., 2014; Mar. Genomics]36 / 60
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Heat shock responseConstitutive shsp gene expression before heat shock
23 weeks acclimation
7 weeks acclimation
Normalize
dexpressio
n
High constitutivestress
Norway
DenmarkBrittanySpain
Heat shock response of shsp gene expression after 24h recovery
Fold
change
Reducedresponsiveness
Norway
DenmarkBrittanySpain
[Jueterbock et al., 2014; Mar. Genomics] 37 / 60
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Heat shock responseConstitutive shsp gene expression before heat shock
23 weeks acclimation
7 weeks acclimation
Normalize
dexpressio
n
High constitutivestress
Norway
DenmarkBrittanySpain
Heat shock response of shsp gene expression after 24h recovery
Fold
change
Reducedresponsiveness
Norway
DenmarkBrittanySpain
[Jueterbock et al., 2014; Mar. Genomics] 37 / 60
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
ConclusionsAcclimation
..
Migra on
.
Acclima on
.
Adapta on
.Fucusserratus
Local thermal adaptation
Areas under highest extinction risk?
Brittany and Spain
Confirms predicted habitat loss
[Jueterbock et al., 2013; Ecol. Evol.]
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Ribadeo, Spain © Coyer, J.A., 1999[Jueterbock et al., 2013; Ecol. Evol., Fig. S6]
1999: extensive F. serratus meadows
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Ribadeo, Spain © Jueterbock, A., 2010[Jueterbock et al., 2013; Ecol. Evol., Fig. S6]
90% abundance decline in 11 years
[Viejo et al., 2011; Ecography]
Dwarf forms withreduced reproductivecapacity in Spain
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Threatened refugial populations
Ice cover during the Last Glacial Maximum (18-20 kya)
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Genetically diverse refugia under threatFucus serratus
Glacial refugia identified by mtDNA haplotype diversity[Hoarau et al., 2007; Mol. Ecol.]
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Genetically diverse refugia under threatFucus serratus
[Hoarau et al., 2007; Mol. Ecol.]42 / 60
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Genetically diverse refugia under threatChondrus crispus
Based on mitochondrial SNPs
[Provan & Maggs, 2012; Proc. R. Soc. London, Ser. B]
180 km retreat since 1971from a Portuguese refugium
Interglacial distribution
Glacial distribution
Stable refugiumunder threat
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Remaining key question
Can ancient refugial populationsadapt to climate change
orwill temperate seaweeds
lose their centers of genetic diversity?
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Adaptation
..
Migra on
.
Acclima on
.
Adapta on
.Fucusserratus
Effective population size Ne? Genetic changes (past 10 yrs)?
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Sampling scheme (50–75 ind./pop)
∼ 2000 ∼ 2010
Spatial
(enviro
nmental)eff
ects
Temporal changes
1 decadeof selection
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Methods and analysis
∼ 2000 ∼ 2010
Spatial
(enviro
nmental)eff
ects
Temporal changes
1 decadeof selection
Genotyping31 microsatellite markers (20 EST-linked)
AnalysisEffective population size (Ne)Allelic richness (α)Temporal outlier loci
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Methods and analysis
∼ 2000 ∼ 2010
Spatial
(enviro
nmental)eff
ects
Temporal changes
1 decadeof selection
Genotyping31 microsatellite markers (20 EST-linked)
AnalysisEffective population size (Ne)Allelic richness (α)Temporal outlier loci
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Effective population size NeReflecting adaptive capacity
∼ 2000 ∼ 2010
18
6320723
Norway
DenmarkBrittanySpain
32
6121026
Estimates excluding outlier loci
[Jueterbock, 2013; PhD Thesis]
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Methods
∼ 2000 ∼ 2010
Spatial
(enviro
nmental)eff
ects
Temporal changes
1 decadeof selection
Genotyping31 microsatellite markers (20 EST-linked)
AnalysisEffective population size (Ne)Allelic richness (α)Temporal outlier loci
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Changes in allelic richness
∼ 2000 ∼ 2010
3.1
4.68.04.0
Norway
DenmarkBrittanySpain
3.3
4.87.94.6
Significantdecline
[Jueterbock, 2013; PhD Thesis]
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Methods
∼ 2000 ∼ 2010
Spatial
(enviro
nmental)eff
ects
Temporal changes
1 decadeof selection
Genotyping31 microsatellite markers (20 EST-linked)
AnalysisEffective population size (Ne)Allelic richness (α)Genetic differentiation (Dest)Temporal outlier loci
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Temporal outlier loci indicate selective sweeps
Before Selection After Selection
Selective Sweep
based on [Vitti et al., 2012; Trends in Genetics]
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Outlier loci
Temporal outlier loci
0%
6%23%13%
Norway
DenmarkBrittanySpain
Strongest selection pressure in the SouthAdaptive to climate change?
[Jueterbock, 2013; PhD Thesis]
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
ConclusionsAdaptation
..
Migra on
.
Acclima on
.
Adapta on
.Fucusserratus
Adaptive responsivenesshighest in Brittany
and likely insufficient in Spain
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Fucus in the tree of lifedistantly related to other taxa
The genome of Ectocarpus siliculosus is sequenced but Fucalesand Ectocarpales diverged in the Cretaceous (ca. 125 Ma)
[Cock et al., 2010; Nature]
De novo Fucus vesiculosus genome until 2017, part of IMAGOMarine Genome project (University of Gothenburg, Sweden)
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Summary
..
Migra on
.
Acclima on
.
Adapta on
.Fucusserratus
Highest responsivenessin Brittany
Adaptive value re-mains unknown
Seaweed meadows:Loss in warm-
temperate regionsArctic invasion?
Ancient refugiaunder threat:
stress in BrittanyExtinction risk in Spain
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Integrative niche modeling
Futuredistribution
Niche modeling
Phenotypicplasticity
Adaptation
DispersalBiotic
interactions
Eco- evolutionary responding potential
Present-day occurrence
Heat shock response Outlier loci
Occurrence records Environmental conditions
Stable realized niche
Niche shift/evolutionMitigation of habitat-lossIncreased invasive potential
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
Overall conclusionSeaweeds as model systems to investigate climate change
Seaweeds provide an excellent system to investigate climate changeimpact on North Atlantic rocky shores
Intertidal key speciesDistribution directly limited by temperature toleranceAnnotated genome of Fucus sp. needed (IMAGO)
Remaining key question: Adaptation or extinction in geneticallydiverse ancient glacial refugia?
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Introduction Distributional changes Acclimation Adaptation Overall conclusions
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References I
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Berteaux, D.; Reale, D.; McAdam, A.G.; Boutin, S. (2004)Keeping pace with fast climate change: can arctic life count on evolution?Integrative and Comparative Biology 44(2):140–151.
Bierne, N. (2010)The distinctive footprints of local hitchhiking in a varied environment and global hitchhiking in a subdividedpopulationEvolution 64(11):3254–3272.
Bierne, N.; Welch, J.; Loire E.; Bonhomme, F.; David, P. (2011)The coupling hypothesis: why genome scans may fail to map local adaptation genesMolecular Ecology 20(10):2044–2072.
Bierne, N.; Roze, D.; Welch, J. (2013)Pervasive selection or is itâĂę? why are FST outliers sometimes so frequent?Molecular Ecology 22(8):2061–2064.
Bradshaw, W. E. and Holzapfel, C. M. (2006)Climate change - Evolutionary response to rapid climate changeScience 312(5779):1477–1478.
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References II
Braune, W. (2008)MeeresalgenKoeltz Scientific Books Königstein, Germany.
Bussotti, F.; Desotgiu, R; Pollastrini, M.; Cascio, C. (2010)The JIP test: a tool to screen the capacity of plant adaptation to climate changeScandinavian Journal of Forest Research 25(Suppl 8): 43–50.
Charlesworth, B.; Nordborg, M.; Charlesworth, D. (1997)The effects of local selection, balanced polymorphism and background selection on equilibrium patterns ofgenetic diversity in subdivided populationsGenetic Research 70:155–174.
Cock, J.M.; Sterck, L.; Rouzé, P. et al. (2010)The Ectocarpus genome and the independent evolution of multicellularity in brown algaeNature 465(3):617–621.
Coyer, J. A.; Peters, A.F.; Stam, W.T.; Olsen, J.L. (2003)Post-ice age recolonization and differentiation of Fucus serratus L. (Phaeophyceae; Fucaceae) populationsin Northern EuropeMolecular Ecology 12:1817–1829.
Coyer, J. A.; Hoarau, G.; Oudot-Le Secq, M.-P.; Stam, W.T. (2006)A mtDNA-based phylogeny of the brown algal genus Fucus (Heterokontophyta; Phaeophyta)Molecular Phylogenetics and Evolution 39:209–222.
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References III
Cock, J.M.; Sterck, L.; Rouzé, P. et al. (2010)The Ectocarpus genome and the independent evolution of multicellularity in brown algaeNature 465(3):617–621.
Duarte L.; Viejo R.M.; Martínez B.; deCastro M.; Gómez-Gesteira M.; Gallardo T.(2013)Recent and historical range shifts of two canopy-forming seaweeds in North Spain and the link with trendsin sea surface temperatureActa Oecologica 51:1–10.
Ehlers, A.; Worm, B. & Reusch, T. B. H. (2008): Importance of genetic diversity in eelgrass Zostera marinafor its resilience to global warming.Mar. Ecol. Prog. Ser. 355:1–7.
Excoffier, L.; Foll, M.; Petit, R.J. (2009)Genetic Consequences of Range ExpansionsAnnual Review of Ecology, Evolution, and Systematics 40:481–501.
Excoffier, L.; Lischer, H.E.L. (2010)Arlequin suite ver 3. 5: a new series of programs to perform population genetics analyses under Linux andWindowsMolecular Ecology Resources 10(3):564–567.
Fredriksen, S.; Christie, H.; Saethre, B.A. (2005)Species richness in macroalgae and macrofauna assemblages on Fucus serratus L. (Phaeophyceae) andZostera marina L. (Angiospermae) in Skagerrak, Norway.Marine Biology Research 1(1):2–19.
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References IV
Fourcade, Y.; Chaput-Bardy, A.; Secondi, J.; Fleurant, C.; Lemaire, C. (2013)Is local selection so widespread in river organisms? Fractal geometry of river networks leads to high bias inoutlier detectionMolecular Ecology 22(8):2065–2073.
Halpern, B.S.; Walbridge, S.; Selkoe, K.A.; Kappel, C.V.; Micheli, F.; D’Agrosa, C.; Bruno, J.F.; Casey,K.S.; Ebert, C.; Fox, H.E. and others (2010)A global map of human impact on marine ecosystemsScience 319(5856):948–952.
Hansen, J.; Sato, M.; Ruedy, R.; Lo, K.; Lea, D.W.; Medina-Elizade, M. (2006)Global temperature changeProceedings of the National Academy of Sciences 103(39):14288–14293.
Harley, C.D.G.; Anderson, K.M; Demes, K.W; Jorve, J.P.; Kordas, R.L.; Coyle, T.A.; Graham, M.H. (2012)Effects of Climate Change on Global Seaweed CommunitiesJournal of Phycology 48:1064–1078.
Hoarau, G.; Coyer, J.A.; Veldsink, J.H.; Stam, W.T.; Olsen, J.L. (2007)Glacial refugia and recolonization pathways in the brown seaweed Fucus serratusMolecular Ecology 16(17):3606–3616.
Hofer, T.; Ray, N.; Wegmann, D.; Excoffier, L. (2009)Large Allele Frequency Differences between Human Continental Groups are more Likely to have Occurred byDrift During range Expansions than by SelectionAnnals of Human Genetics 73(1):95–108.
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References V
Jimenez-Valverde, Alberto (2012)Insights into the area under the receiver operating characteristic curve (AUC) as a discrimination measure inspecies distribution modellingGlobal Ecology and Biogeography 21:498–507.
Jueterbock, A.; Tyberghein, L.; Verbruggen, H.; Coyer, J.A.; Olsen, J.L.; Hoarau, G. (2013)Climate change impact on seaweed meadow distribution in the North Atlantic rocky intertidalEcology and Evolution 3(5):1356–1373.
Jueterbock, A. (2013)Climate change impact on the seaweed Fucus serratus a key foundational species on North Atlantic rockyshores (2013)PhD Thesis in Aquatic Biosciences no.10 Faculty of Biosciences and Aquaculture, University of Nordland,Bodø, Norway
Jueterbock, A.; Kollias, S.; Smolina, I.; Fernandes, J.O.; Coyer, J.A.; Olsen, J.L.; Hoarau G. (2014)Thermal stress resistance of the brown alga Fucus serratus along the North Atlantic coast: acclimatizationpotential to climate changeMarine Genomics 13:27-36.
Knight, M.; Parke, M. (1950)A biological study of Fucus vesiculosus L. and F. serratus L.Journal of the Marine Biological Association of the UK 29:439–514.
Køie, M.; Kristiansen, A.; Weitemeyer, S. (2001)Der große Kosmos Strandführer.Kosmos.
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References VI
Luikart, G.; England, P. R.; Tallmon, D.; Jordan, S.; Taberlet, P. (2003)The power and promise of population genomics: from genotyping to genome typingNature Reviews Genetics 4(12):981–994.
Maggs, C. A.; Castilho, R.; Foltz, D.; Henzler, C.; Jolly, M. T.; Kelly, J.; Olsen, J.; Perez, K. E.; Stam, W.;Väinölä, R. et al. (2008): Evaluating signatures of glacial refugia for North Atlantic benthic marine taxa.Ecology 89:108–122.
McMahon, C.R. & Hays, G.C. (2006)Thermal niche, large-scale movements and implications of climate change for a critically endangered marinevertebrate.Global Change Biology 12(7):1330–1338.
Meehl, G.A.; Stocker, T.F.; Collins, W.D.; Friedlingstein, P.; Gaye, A.T.; Gregory, JM.; Kitoh, A.; Knutti,R.; Murphy, J.M.; Noda, A.; Raper, S.C.B.; Watterson, I.G and Weaver, A.J.; Zhao, Z.-C. (2007)Global Climate Projections.Climate Change 2007: the physical science basis: contribution of Working Group I to the FourthAssessment Report of the Intergovernmental Panel on Climate Change Eds: Solomon S. et al.
Müller, R.; Laepple, T.; Bartsch, I.; Wiencke, C. (2009)Impact of oceanic warming on the distribution of seaweeds in polar and cold-temperate waters.Botanica Marina 52:617–638.
Neiva, J; Pearson, G.,A.; Valero, M.; Serrão, E. A. (2010): Surfing the wave on a borrowed board: rangeexpansion and spread of introgressed organellar genomes in the seaweed Fucus ceranoides L.Molecular Ecology 19(21):4812–4822.
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References VII
Nicastro, K.R.; Zardi, G.I.; Teixeira, S.; Neiva, J.; Serrao, E.A.; Pearson, G.A. (2013)Shift happens: trailing edge contraction associated with recent warming trends threatens a distinct geneticlineage in the marine macroalga Fucus vesiculosus.BMC Biology 11(6).
Nolan, T.; Hands, R.E.; Bustin, S.A. (2006)Quantification of mRNA using realtime RT-PCRNature Protocols 1(3)1559–1582.
Pannell, J. R.; Charlesworth, B. (2000)Effects of metapopulation processes on measures of genetic diversityPhilosophical Transactions of the Royal Society of London B 355(1404):1851-1864.
Pearson, G.A.; Lago-Leston, A.; Mota, C. (2009)Frayed at the edges: selective pressure and adaptive response to abiotic stressors are mismatched in lowdiversity edge populations.Journal of Ecology 97(3):450–462.
Pereyra, R. T.; Bergström, L.; Kautsky, L. & Johannesson, K. (????): Rapid speciation in a newly openedpostglacial marine environment, the Baltic Sea.BMC Evol. Biol. 9(1):70.
Pespeni, M.H.; Sanford, E.; Gaylord, B.; Hill, T.M; Hosfelt, J.D. et al. (2013)Evolutionary change during experimental ocean acidificationProceedings of the National Academy of Sciences 110(17):6937–6924.
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References VIII
Smolina S. (2012)Climate change in the Arctic intertidal: Response of the seaweed Fucus distichus to rising temperatureMaster Thesis Faculty of Biosciences and Aquaculture, University of Nordland, Norway
Smolina I., Coyer J.A., Jueterbock A., Hoarau, G.The fate of arctic Fucus distichus under climate change: an ecological niche modeling approach.
Smolina I., Coyer J.A., Kollias S., Jueterbock A., Hoarau, G.Variation in heat stress response in two populations of the seaweed, Fucus distichus, from the arctic andsubarctic intertidal: implication for climate change.
Phillips, S.J.; Anderson, R.P.; Schapire, R.E. (2006)Maximum entropy modeling of species geographic distributions.Ecological Modelling 190(3-4):231–259.
Pounds, J. A.; Bustamante, M.R.; Coloma, L.A.; Consuegra, J.A.; Fogden, M.P.L.; Foster, P.N.; La Marca,E.; Masters, K.L.; Merino-Viteri, A.; Puschendorf, R.; Ron, S.R.; Sanchez-Azofeifa, G.A.; Still, C.J.; Young,B.E. (2006)Widespread amphibian extinctions from epidemic disease driven by global warmingNature 7073:161–167.
Provan, J. & Maggs, C. A. (2012): Unique genetic variation at a species’ rear edge is under threat fromglobal climate change.Proc. R. Soc. London, Ser. B 279(1726):39–47.
Provan, J.; Beatty, G. E.; Keating, S. L.; Maggs, C. A.; Savidge, G. (2009): High dispersal potential hasmaintained long-term population stability in the North Atlantic copepod Calanus finmarchicusProc. R. Soc. London, Ser. B 276(1655):301–307.
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References IX
Raybaud, V.; Beaugrand, G.; Goberville, E.; Delebecq, G.; Destombe, C.; Valero, M.; Davoult, D.; Morin,P.; Gevaert, F. (2013)Decline in Kelp in West Europe and ClimatePLOS ONE 8:e66044.
Reusch, T.; Ehlers, A.; Hammerli, A. & Worm, B. (2005): Ecosystem recovery after climatic extremesenhanced by genotypic diversity.Proc. Natl. Acad. Sci. U.S.A. 102(8):2826–2831.
Sturm, M.; Schimel, J.; Michaelson, G.; Welker, J.M.; Oberbauer, S.F.; Liston, G.E.; Fahnestock, J.;Romanovsky, V. (2005)Winter biological processes could help convert Arctic tundra to shrubland.Bioscience55(1):17–26.
Tyberghein, L.; Verbruggen, H.; Pauly, K.; Troupin, C.; Mineur, F.; De Clerck, O. (2011)Bio-ORACLE: a global environmental dataset for marine species distribution modelling.Global Ecology and Biogeography.
Ugarte, R.A.; Critchley, A.; Serdynska, A.R.; Deveau, J.P (2009)Changes in composition of rockweed (Ascophyllum nodosum) beds due to possible recent increase in seatemperature in Eastern Canada.Journal of Applied Phycology 21:591âĂŞ598.
van Asch, M.; Salis, L.; Holleman, L.J.M.; van Lith, B.; Visser, M.E. (2013)Evolutionary response of the egg hatching date of a herbivorous insect under climate change.Ecography 3:244–248.
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References X
Verbruggen, H. (2012)Occurrence Thinner version 1.04.http://www.phycoweb.net/software.
Verbruggen, H. (2012)Maxent Model Surveyor v1.01.http://www.phycoweb.net/software.
Viejo, R.M.; Martínez, B.; Arrontes, J.; Astudillo, C.; Hernández, L. (2011)Reproductive patterns in central and marginal populations of a large brown seaweed: drastic changes at thesouthern range limit.Ecography 34(1):75–84.
Vitti, J.J.; Cho, M.K.; Tishkoff, S.A.; Sabeti, P.C. (2012)Human evolutionary genomics: ethical and interpretive issuesTrends in Genetics 28(3):137–145.
Walther, G.-R.; Post, E.; Convey, P.; Menzel, A.; Parmesan, C.; Beebee, T.J.C.; Fromentin, J.-M.;Hoegh-Guldberg, O.; Bairlein, F. (2002)Ecological responses to recent climate change.Nature 416(6879):389–395.
Warren, D. L.; Seifert, S. N. (2011)Ecological niche modeling in Maxent: the importance of model complexity and the performance of modelselection criteriaEcological Applications 21(2):335–342.
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References XI
Wernberg, T.; Russell, B.D.; Thomsen, M.S.; Gurgel, F.D.; Bradshaw, C.J.A.; Poloczanska, E.S., Connell,S.D. (2011)Seaweed Communities in Retreat from Ocean Warming.Current Biology 21(21):1828–1832.
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