Transcript Document

Incorporating DNA barcodes
into assessments of the
biological integrity of aquatic
ecosystems
Mark Bagley, United States Environmental Protection Agency
Charles Spooner, US EPA
Ronald Klauda Maryland Dept of Natural Resources
David Schindel, CBOL
Lee Weigt
Robert Hanner, University of Guelph
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Structure of Talk
1. Bioassessments, biological integrity
and taxonomy
2. Application of DNA barcodes to stream
bioassessments
3. From species to populations:
Expanding from barcodes in
bioassessments
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“Biological Integrity” and
Environmental regulations
Section 101 of the United States
Clean Water Act requires federal
and state governments to
"restore and maintain the
chemical, physical and
biological integrity of the
Nation's waters."
Physical
Integrity
Chemical
Integrity
Biological
Integrity
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Biological Integrity
The condition of an aquatic community inhabiting
unimpaired waterbodies of a specified habitat as
measured by an evaluation of multiple attributes of
the aquatic biota. Three critical components of
biological integrity are that the biota is
(1) the product of the evolutionary process for that locality,
or site
(2) inclusive of a broad range of biological and ecological
characteristics such as taxonomic richness and
composition, trophic structure
(3) found in the study biogeographic region.
» (USEPA 1996)
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Bioassessment
• An evaluation of the biological condition of a
waterbody using biological surveys and other direct
measurements of the resident living organisms
 Fish, macroinvertebrates, periphyton communities
 Important component of the majority of water quality
monitoring programs
 indicators of cumulative impacts on biological integrity from
aquatic stresses
• nonpoint source pollution and other stressors.
 Quantitative assessments of what the community looks like
compared to “what it is supposed to look like”
• Indicator species, multimetric indices, predictive models
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Bioassessments
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Bioassessments
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Biological Assessment and
the US Clean Water Act
Source: EPA822-F-02-006, 2002
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Bioassessments depends
critically on good
taxonomic identifications
• Accuracy
• Precision
• Comparability of
findings
• Credibility
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US EPA National
Stream Survey
Design
• National assessment of the condition of
wadeable streams
• 10 different taxonomic ID laboratories
• 749 stream macroinvertebrate samples
• Organisms identified to genus
• 10% random re-identification by
independent taxonomist
• Data quality objective – 85% repeatability
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US EPA National
Stream Survey
Data Quality
• 77% of random re-identifications
were to the same genus (1st try)
• 87% of random re-identifications
were to the same genus after
reassessment of data and
correction of systematic errors
– Good enough?
11
So many bugs, so few experts,
such a pain to identify
Taxonomy of North American Aquatic Flies (Diptera)
Family
Known
species
Probable
species
Known to
genus as
larvae
Known to
species as
larvae
Taxonomic
experts
Ceratopogonidae
600
>800
<20%
<5%
1-2
Thaumaleidae
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>30
100%
~20%
1-2
Psychodidae
70
>200
~30%
<5%
0
Tipuloidea
>1500
~2000
~80%
<3%
3-4
“Empidoids”
~1400
~2000
<20%
<3%
?
Chironomidae**
~1000
>2000
?
?
?
Sources:G. Courtney,
L. Ferrington
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And progress in identifying
aquatic larvae to species is slow
Taxonomy of North American caddisflies (Trichoptera)
1966 - 40% of species known to science as larvae
2006 - 38% of 1418 described species with larvae
known to science
Source: John Morse
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DNA Barcodes
• A short DNA sequence from a
standardized portion of the
genome that is used to identify
species
• DNA barcodes provide an objective
standard for species identification
• Yada yada yada
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Possible Advantages of DNA
Barcodes for Bioassessment
• Increased taxonomic resolution
• Provide a common QA standard
• Increase pool of expertise for
taxonomic identification
• Pathway towards more fully automated
analyses
• Objectivity, speed, cost (?)
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Advanced Monitoring
Initiative
Project Goals
•
Develop a DNA barcode library for important
aquatic indicator species (EPT)
•
•
•
•
Compare DNA barcodes to traditional
bioassessments for EPT taxa
•
•
•
Ephemeroptera (Mayflies)
Plecoptera (Stoneflies)
Trichoptera (Caddisflies)
Cost, Speed, Objectivity, Accuracy, Precision
How important is increased taxonomic
precision?
Determine how to efficiently incorporate DNA
barcodes into a state bioassessment program
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Barcode development
•
•
•
Develop barcode with COI sequences from
taxonomically resolved adult specimens
(Smithsonian collection)
Add COI sequences for larval samples collected
as part of Maryland’s state bioassessment
Link larval and adult forms by DNA and
incorporate ancillary data to complete barcode
record
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Repeatability and barcode
development
Maryland
DNR
Guelph
Smithsonian
EPA
Lab
EPA
Morphology
DNA
(taxonomic agreement)
(disagreement
or MOTU)
(adult specimens)
Repeatability
Precision
Cost
Repeatability
Accuracy
Precision
Cost
Reference
Barcode
Database
Taxon Experts
(Smithsonian)
Species
Description
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Tech Transfer is Important!
• End users are participants in the
project
 Maryland DNR, EPA-Water
• Tech transfer documents, hands-on
workshops, and protocols are key
products
• Chose end-users that will be
influential in “converting” others
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Trichoptera
Net spinning caddisflies (Hydropsychidae)
Diplectrona modesta
Parapsyche apicalis
Cheumatophyche sp.
Potamyia sp.
Hydropsyche betteni
Hydropsyche aerata
Hydropsyche simulans
677 bp COI
102 specimens
NJ tree
Hydropsyche betteni
Hydropsyche bidens/incomoda
Hydrophyche venularis/ scalaris
Symphitophyche sp.
Hydrophychidae sp.
0.1
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H 240
H 245
H 259
H 255
H 270
H 263
H 264
H 231
H 261
H 249
H 244
H 391
H 260
H 275
H 241
H 248
H 269
H 250
H 368
H 230
H 251
H 232
64
H 252
Diplectrona
modesta
H 268
H 239
H 247
99
H 243
H 253
99
H 256
H 390
100
100
92
H 387
H 432
H 246
H 433
H 420
100
H 274
59
99
“Hydropsychidae”
H 273
H 402
H 406
H 419
0.02
21
Hydropsyche aerata
H 703
H 485
99
Hydropsyche simulans
H 525
99
58
H 452
H 519
Symphitopsyche bronta/morosa
H 314
Hydropsyche betteni
H 517
62
H 518
53
99
Hydropsyche bidens/incommoda
Hydropsyche venularis
H 474
67 H 484
Hydropsyche scalaris
H 707
Symphitopsyche bronta/morosa
H 846
Symphitopsyche bifida
99 H 844
Symphitopsyche bronta/morosa
H 845
0.05
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Preliminary comparison of
sequence divergences
12
10
8
6
4
2
0.
02
0.
04
0.
06
0.
08
0.
1
0.
12
0.
14
0.
16
0.
18
0.
2
0.
22
0
0
w/in Species
w/in Genus
w/in Family
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Summary
• Bioassessments are critical
components of water quality
programs
• Their wider implementation is
hindered by lack of taxonomic
expertise, poor resolving power of
morphology, and expense.
• DNA barcodes can revolutionize
biaossessments, removing
previous roadblocks and bringing
new sophistication to the field
• One key to success will be
partnership with morphological
taxonomists to find efficient ways
forward
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But why stop at barcodes?
• The hard part is getting buy-in
from bioassessment programs to
transition to DNA surveys
• Once DNA is analyzed and
archived for barcodes, it is
available for more complex
analyses of population structure
and dynamics
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Mill Creek
Watershed,
Cincinnati, OH, USA
Ohio EPA aquatic habitat assessment
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Environmental characterization of
mainstem sites
8
6
4
2
0
Tanner
MC1
fish abundance/100
MC2
MC3
PAH (mg/l)
MC5
Pesticide (ug/l)
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Genetic Analysis
•
•
•
•
4 mainstem, 3 tributary, and
one ‘control’ site sampled
for central stonerollers
(Campostoma anomalum) in
2001-2002
4 mainstem sites also
sampled in 1994-1995
Sample sizes ranged from
n=10 to n=103
All samples genotyped at 10
microsatellite loci
28
Population structure
analysis
MC1
MC2 MC6 MC7
MC3
MC8
MC5
TC
29
Estimation of effective population sizes
and connectivity (MLNE)
Site MC1, t-1
(Resident Pool)
Genetic
drift
migration
Site MC1, t-2
Immigrant
Pool
~ m, Ne
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Estimates of local effective
sizes and immigration rates
Site
Ne (95% CI)
m (95% CI)
MC1
85 (55-140)a
0.29 (0.21-0.46)
MC2
12 (8-21)b
0.99 (0.53-1.00)
MC3
39 (28-105)a
0.99 (0.24-1.00)
MC5
86 (47-112)a
0.99 (0.43-1.00)
Source-sink dynamics?
31
A genetic tool for watershed
management?
Mill Creek Watershed, Cincinnati, OH
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Acknowledgements
• Advanced Monitoring Initiative Coinvestigators and Collaborators
 Chuck Spooner, Suzanne Jackson, Eric
Waits, Mike Blum, US EPA
 Lee Weigt, Amy Driscoll, Smithsonian
Institution
 David Schindel, CBOL
 Ron Kluida, Ellen Friedman, Maryland DNR
 Robert Hanner, University of Guelph
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