A better future for MN lakesPerspectives – Future work • New lakes sampled in 2016 • Chains of...

Post on 12-Oct-2020

0 views 0 download

transcript

A better future for MN lakesAnalyzing the footprints of invasions past and present, hidden in the DNA of zebra mussels

Sophie Mallez & Michael McCartneysmallez@umn.edu/mmccartn@umn.edu

September 12th, 2016

The zebra mussel invasion

• Native to the Ponto-Caspian region• Estuaries of the Black, Caspian and Azov seas

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

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

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

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

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

Sampling zebra mussels

• Sampling of infested waterbodies in 2014 – 2015

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

Analysis of genetic diversity

High level of polymorphism within populations

Analysis of genetic diversity

Waterbodies were colonized by a large number of individuals

Analysis of differentiation/structure

• Between-lake analyses

Some well-defined clusters distinguish important lake infestations

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

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

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

Analysis of invasion models – Clustered Invasion

Invasion in Alexandria-area Lakes

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

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

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

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

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

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

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

• 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

• 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

Perspectives – Future work

• New lakes sampled in 2016• Chains of lakes – Clustered invasions

Alexandria-area lakes Pelican Rapids-area lakes Brainerd-area lakes

Perspectives – Future work

• New lakes sampled in 2016• Chains of lakes – Clustered invasions

Process of dispersion of connected lakesSet of recently infested lakes increased

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

Perspectives – Future work

• New lakes sampled in 2016• Chains of lakes – Clustered invasions• Lower Great Lakes

Set of potential sources for Minnesota’spopulations increased

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

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

• 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

For more information on MAISRC, please visit:http://www.maisrc.umn.edu

Sign up for our newsletterAnd like us on Facebook!