a better future for mn lakesperspectives – future work • new lakes sampled in 2016 • chains of...
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A better future for MN lakesAnalyzing the footprints of invasions past and present, hidden in the DNA of zebra mussels
Sophie Mallez & Michael [email protected]/[email protected]
September 12th, 2016
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The zebra mussel invasion
• Native to the Ponto-Caspian region• Estuaries of the Black, Caspian and Azov seas
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The zebra mussel invasion
• Native to the Ponto-Caspian region• Estuaries of the Black, Caspian and Azov seas
• Introduced in Europe (1800) and North America (1985)• Due to the creation of canals, shipping traffic,…• Severe economic and ecological damages
© Dan Swanson
© Dan Swanson
© ruthlakecsd.org
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The zebra mussel invasion
• Native to the Ponto-Caspian region• Estuaries of the Black, Caspian and Azov seas
• Introduced in Europe (1800) and North America (1985)• Due to the creation of canals, shipping traffic,…• Severe economic and important damages
• In Minnesota…• Introduced in 1989, in Lake Superior• Spread through the Mississippi and St Croix rivers• First inland lake infested in 2003: Ossawinnamakee• New infestations occurred yearly but < 2 % lakes infested
Great benefits of targeted prevention
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Pattern of spread – Key step
Preventing = Understanding the pattern of spread
Identifying the routes of invasionPath(s) followed by an organism/propagule between its native population and the invasive
population(s) it has formed.
Pinpointing lakes/riversplaying a key role
Characterizing major vectors of dispersion
Improved vigilance and monitoring of key populations/vectorsControl of the expansion and new introductions
One precious ally: DNA
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Mussels do not speak + Rarely at the right time at the right placeBut…
We can make the mussels speak!
Genetic markers
Genes or polymorphic fragments of DNA whose location is known
Characterization of individualsLittle ID’s for each individual
DNA – Precious ally
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Genetic markers for zebra mussel
• Microsatellite markers• Repeated motifs – GTTAGTCCAGAGAG….AGAGAGTTCGATCT• Polymorphic – numerous alleles
• Genotyping of 9 microsatellite markers• Obtained from the literature • Optimized for this study
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Sampling zebra mussels
• Sampling of infested waterbodies in 2014 – 2015
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Analyzing the invasion in Minnesota
1281 individuals genotyped at 9 microsatellite markers
Studying different aspects of the invasion:
= The features of the introduction• Founder effects / Number of introduced individuals
= The relationship between samples• Functioning of the populations
• Which lake is close/different to which lake
= The most likely scenario of invasion• Routes of invasion
• Origin of the invasive populations
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Analysis of genetic diversity
High level of polymorphism within populations
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Analysis of genetic diversity
Waterbodies were colonized by a large number of individuals
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Analysis of differentiation/structure
• Between-lake analyses
Some well-defined clusters distinguish important lake infestations
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Analysis of invasion models
• Comparisons of scenarios of invasion• Approximate Bayesian Computation• Selection of the most likely scenario of invasion based on probabilities
Focus on distinguishable lakes
“Super-spreader” lakes Clustered invasion
Mille Lacs LakePrior Lake
Alexandria-area Lakes
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Mille Lacs Lake – Secondary source for inland lakes?
Analysis of invasion models – “Super-spreader” lakes
Scenario 1 Scenario 2
Mille Lacs Lake
vs
Mille Lacs Lake
Gull Lake
Mille Lacs Lake
Gull Lake
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Mille Lacs Lake – Secondary source for inland lakes?
Independent introductions scenario selected in almost all cases (posterior probabilities from 0.86 to 0.99)
Results robust to changes in priors and samples
Mille Lacs Lake was not a secondary source
Analysis of invasion models – “Super-spreader” lakes
Scenario 1 Scenario 2
Mille Lacs Lake
vs
Mille Lacs Lake
Gull Lake
Mille Lacs Lake
Gull Lake
Pr. = 0.89
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Analysis of invasion models – Clustered Invasion
Invasion in Alexandria-area Lakes
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Analysis of invasion models – Clustered Invasion
Invasion in Alexandria-area Lakes
Lake Carlos
LeHommeDieu Lake
Lake Carlos
LeHommeDieu Lake
Lake Carlos
Scenario 2 Scenario 2Scenario 1
vs or
• Lake Carlos – LeHomme Dieu Lake
Lake Carlos
LeHommeDieu Lake
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Analysis of invasion models – Clustered Invasion
Invasion in Alexandria-area Lakes
Lake Carlos
LeHommeDieu Lake
Lake Carlos
LeHommeDieu Lake
Lake Carlos
Scenario 2 Scenario 2Scenario 1
vs or
Pr. = 0.77 Pr. = 0.72
• Lake Carlos – LeHomme Dieu Lake
Scenario of successive introductions selected
Lake Carlos
LeHommeDieu Lake
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Analysis of invasion models – Clustered Invasion
Invasion in Alexandria-area Lakes
Scenario 2 Scenario 2Scenario 1
vs or
• LeHomme Dieu Lake – Lake Carlos: successive introductions• LeHomme Dieu Lake – Lake Darling
LeHommeDieu Lake
Lake Darling
LeHommeDieu Lake
Lake Darling
LeHommeDieu Lake
Lake Darling
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Analysis of invasion models – Clustered Invasion
Invasion in Alexandria-area Lakes
Scenario 2 Scenario 2Scenario 1
vs or
• LeHomme Dieu Lake – Lake Carlos: successive introductions• LeHomme Dieu Lake – Lake Darling
LeHommeDieu Lake
Lake Darling
LeHommeDieu Lake
Lake Darling
Pr. > 0.86
Scenario of independent introductions selected
LeHommeDieu Lake
Lake Darling
Pr. > 0.86
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Analysis of invasion models – Clustered Invasion
Invasion in Alexandria-area Lakes
• LeHomme Dieu Lake – Lake Carlos: successive introductions• LeHomme Dieu Lake – Lake Darling: independent introductions• Lake Carlos – Lake Darling: independent introductions
Stepping-stone scenario alone cannot account for this
clustered invasion
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Results summary
• Large number of individuals being introduced• Important lake infestations stood out• “Super-spreader” hypothesis not supported• Complex pattern of spread in clustered invasion
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Results summary – Implications
• Large number of individuals being introduced• Important lake infestations stood out• “Super-spreader” hypothesis not supported• Complex pattern of spread in clustered invasion
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• Large number of individuals being introduced• Important lake infestations stood out• “Super-spreader” hypothesis not supported• Complex pattern of spread in clustered invasion
Results summary – Implications
© www.nps.gov© www.marinedocklift.com© www.thinglink.com
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• Large number of individuals being introduced• Important lake infestations stood out• “Super-spreader” hypothesis not supported• Complex pattern of spread in clustered invasion
Results summary – Implications
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Perspectives – Future work
• New lakes sampled in 2016• Chains of lakes – Clustered invasions
Alexandria-area lakes Pelican Rapids-area lakes Brainerd-area lakes
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Perspectives – Future work
• New lakes sampled in 2016• Chains of lakes – Clustered invasions
Process of dispersion of connected lakesSet of recently infested lakes increased
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Perspectives – Future work
• New lakes sampled in 2016• Chains of lakes – Clustered invasions• Lower Great Lakes
Lake Erie
Lake Huron
Lake Michigan
Lake St. Clair
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Perspectives – Future work
• New lakes sampled in 2016• Chains of lakes – Clustered invasions• Lower Great Lakes
Set of potential sources for Minnesota’spopulations increased
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Perspectives – Future work
• New lakes sampled in 2016• Chains of lakes – Clustered invasions• Lower Great Lakes
• Genomic resources being developed• SNP markers• Much higher number of markers
More information gathered from genetic dataHigher resolution for identifying the pattern of spread
© www.100thmeridian.org© www.100thmeridian.org© www.100thmeridian.org© www.100thmeridian.org© www.100thmeridian.org
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Perspectives – Future work
• New lakes sampled in 2016• Chains of lakes – Clustered invasions• Lower Great Lakes
• Genomic resources being developed• SNP markers• Much higher number of markers
Lake Minnetonka
Gull Lake
> 5,500 markers
Coor
d. 2
Coord. 1
9 markers
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• UMN: Grace Van Susteren, Sarah Peterson, Maxwell Kleinhausand Melody Truong for sampling and lab support
• NPS: Byron Karn and Michelle Prosser for field/sampling support and advice
• MnDNR: Daniel Swanson and Richard Rezanka for field/sampling support and advice
• USGS: Mary-Anne Evans• Clear Water Fund, ENRTF for funding
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For more information on MAISRC, please visit:http://www.maisrc.umn.edu
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