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Funding
eDNA - a tool for efficient biodiversity monitoring
from rare species to communities and back
Bernd Hänfling
eDNA barcoding and metabarcoding eDNA barcoding:
• Targeted detection • Species-specific primers • Standard or qPCR • Traditional Sequencing
=
Free-floating DNA (from sloughed skin cells faeces/urine, gametes, decaying matter) and
microscopic taxa
Water sampled & filtered (>3 x 15 ml -2L samples)
eDNA metabarcoding: • Screen whole community • (Several) conserved primers • PCR • Next generation sequencing
= Extract DNA
eDNA metabarcoding of lake fish
Aim: • To develop and test eDNA metabarcoding
methods to describe lake fish communities. Motivation: • Water Framework Directive (WFD) lake fish
monitoring. • Currently not carried out to the degree
required by the WFD due to methodological considerations.
• Cost and time • Ethics (gill nets are destructive) • Practicalities on large lakes
Phase I: • Sampling: January 2015
Phase II: • Sampling: September 2015/January2016
eDNA metabarcoding of lake fish
Phase I – sampling: • Three Cumbrian lakes
• Windermere • Derwent Water • Bassenthwaite Lake
• 2L water samples along boat transect at
2m, 5m & 20m depths, as well as shore
sampling.
• Filtered on 0.45 μm membrane filters.
• Two mitochondrial gene fragments (12S
and Cytochrome b) sequenced at CEH on
an Illumina MiSeq
eDNA detects lake fish presence
Previously (ever) recorded species: 16 eDNA metabarcoding (Jan-15): 14 (88%)
Gill netting survey 2014: 4 (25%)
Gill netting survey 2015: 5 (31%)
0
0.2
0.4
0.6
0.8
1
12S freq
cytb freq
Prop
ortio
n of
site
s pre
sent
Lake Windermere, January 2015 (65 samples)
Hänfling et al. 2016, Molecular Ecology
Prop
ortio
n of
site
s pre
sent
0
0.2
0.4
0.6
0.8
1
12S freq
cytb freq
Lake Windermere, January 2015 (65 samples)
Species not previously recorded 12S: 6 species Cytb: 3 species
eDNA detects lake fish presence
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 2 4 6 8 10 12 14 16 18
January 2015
Long term rank (based on 30 years of established method surveys)
eDN
A ab
unda
nce
(site
occ
upan
cy)
eDNA reflects species abundance
Windermere both basins
r = - 0.77; P < 0.001
• Perch detected throughout lake
• Arctic charr predominantly North Basin
• Bream more common in South Basin
Spatial distribution of eDNA
Occupancy data demonstrate that species are not equally distributed across the lake e.g.
eDNA distribution reflects fish ecology
Oligotrophic association
Eutrophic association
No association
0
5
10
15
20
25
30
1945 1955 1965 1975 1985 1995 2005Year
Mea
n SR
P in
firs
t 4 w
eeks
(mg
m-3
)North basin
South basin
Hänfling et al. 2016, Molecular Ecology
Mesotrophic
Eutrophic-mesotrophic
eDNA distribution reflects fish ecology
• Large and common species found consistently across transects
• Small littoral species predominantly in shallower habitats
• Arctic charr was only found in midwater and bottom samples
Shore-west 5m
20m Midline
Shore-East
0
0.2
0.4
0.6
0.8
1
eDN
A ab
unda
nce
(12S
)
Windermere North Basin
Sampling in Phase 2
eDNA detection of rare species Vendace (Coregonus albula) in Cumbrian lakes
• Five offshore and one shore line sample in each lake
• Positive detection in two Derwent Water sites, but none in Bassenthwaite Lake (only three individuals caught since 2000)
• Is qPCR more sensitive compared to metabarcoding? Ongoing work with Glenn Rhodes (CEH)
PhD studentship available (UoH collaboration with CEH and SNH): “eDNA monitoring of conservation priority fish in UK freshwaters” Deadline for applications 3rd June 2016
Derwent Water
Bassenthwaite Lake
Summary
• eDNA metabarcoding is highly sensitive for fish species detection and outperforms established methods even in oligotrophic lakes
• Relative abundance estimates from eDNA and long term data correlate strongly.
• eDNA can tell us about species distribution on a small geographical scale and provide important ecological information
• Some differences between shore and offshore sampling… important for monitoring strategies
• Metabarcoding may just be as powerful as single species approaches for detecting rare species
• eDNA based metabarcoding has a huge potential for large scale biodiversity monitoring and to provide data to answer fundamental ecological questions
So long and thanks for all the fish help … UoH team: Dr. Lori Lawson-Handley PostDocs: Dr. Christoph Hahn Dr. Helen Kimbell Dr. Paul Nichols Dr. Harriet Johnson Dr. Hayley Watson Dr. Rose Wilcox Dr. Rob Donnelly PhD students: Joe Li Rosie Blackman Marco Benucci Lynsey Harper
CEH team: Dr. Ian Winfield Dr. Dan Read Dr. Anna Oliver Ben James Janice Fletcher
FBA and MEFGL Bangor for use of facilities!
EA, SEPA and NRW team: Dr. Kerry Walsh Dr. Graeme Peirson Dr. Willie Duncan Dr. Alistair Duguid Dr. Tristan Hatton Ellis