Andrew Lowe - Plants Plenary

DNA barcoding for Rapid Biodiversity Inventory, Conservation Prioritisation,

and Control of Illegal Logging

Andrew Lowe,

Craig Costion, Hugh Cross, Bernd Degen

Darren Crayn, Jonathan Geach

• Barcoding Australian wet tropics trees – rapid biodiversity inventory – conservation prioritisation – biogeographic understanding

• Barcoding Australian plants and soils– Terrestrial Ecosystem Research Network– biodiversity surveillance and monitoring

• Barcoding and DNA fingerprinting tropical timber species for control of illegal logging

Costion et al. (2011) Plant DNA barcodes can accurately estimate species richness in poorly known floras. PLoS ONE: In press

Why barcode plants in the tropics?• High percentage of flora is undescribed• Fertile material for accurate field ID’s• Rapid habitat loss, increasing threats• Rapid biodiversity assessments needed

DNA barcoding can help

Australia’s ever-wet tropical rainforestLockerbie Scrub

Wet Tropics

McIlwraith/Iron Ranges

BARCODING PROGRESS

Wet tropics has 2,144 vascular plants

1,200-1,400 species w/ at least 1 barcode

500 species – have 2-3 replicate barcodes

40% - 50%

Cambium extraction• Rapid and easy tissue collection for DNA extraction• DNA from cambium shown to be less hampered by

defensive chemicals in leaves (Colpaert et al 2005)

• Can we use DNA –barcodes to estimate the diversity of an area where species are unknown?

E1

E15

F05

F44

E2

F11

E10

F22

F41

F54

F20

F26

F67

F36

F45

F53

F09

F35

F03

F66

E17

F28

F01

F02

E9

F40

F19

F27

F48

F51

F38

F rbcL57 R A08

F52

F56

E3

F29

F07

F17

F60

F68

F69

F64

99

99

9999

99

99

99

99

82

50

44

36

98

98

63

40

31

23

33

38

37

26

Discriminate Species: Assessing accuracy of barcoding loci to discriminate species

vs.Estimate Species: Using plant DNA barcodes to estimate species richness

Sample all individuals present then contruct distance trees

Costion et al. (2011) PLoS ONE: In press

Distance tree of DNA samples


Identities confirmed

http://www.pbase.com/conroy11/austplants&page=4�

• No gain in in discrimination accuracy by adding matK

• Estimation accuracy decreases with matK

With addition of 3rd locus trnH psbA discrimination accuracy remains same ~ 70%

Estimation accuracy increases to 89%


Biodiversity assessments possible!~ poorly known areas~ tree saplings/seedlings~ high canopy~ roots or other cryptic samples


89% accuracy of species ID with rbcL & trnH psbA combination

Plot Network of 2500.1 hectare plots

Using barcode data to assess phylogenetic diversity

Where are the hotspots of evolutionary history?

Costion, C. (PhD Thesis)

All angiosperm genera supertree – largest phylogeny of a tropical bioregion to date (660 species)


PD Genus RichnessRainforest stability indexHilbert et. al (2007)


PD v GR at different spatial resolutions

GR

0 100 200 300 400 500

PD

0

2

4

6

8

10

12

14

16

18

GR0.1 vs PD0.1 GR0.065 vs PD0.065 GR0.125 vs PD0.125 GR0.25 vs PD0.25

Phylogenetic Diversity (PD)/ Genus Richness (GR)

However, when affects of GR are removed through regression a biogeographic pattern emerges


Ancient Gondwana

Extant rainforest

Gondwanan lineages

Indomalayanlineages

Lowlands

Uplands0

10

20

30

40

50

60

70

0 200 400 600 800 1000 1200 1400 1600 1800

elevation

Laur

asia

n R

ichn

ess

Indo

mal

ayan

line

ages

Elevation (m)

Indomalayan lineages higher frequency in lowlands. Areas with higher PD than expected can be explained by higher proportion of non-Australian (Gondwanan) elements present.


Life Impact The University of AdelaideSlide 16

Australian Centre for Evolutionary Biology and Biodiversity

The Terrestrial Ecosystem Research Network

$45M Research Infrastructure Facility for Australia

The objectives of TERN are to:

• network for terrestrial ecosystem research;

• Coordinate national observation networks;

• Improved access to observational data;

• Identify future needs for research.





Rangelands plot network

Forestry plots

Forestry plots

Forestry plots

Forestry plots

Multi-scale Plot activities-AusPlots



CSIRO plotsNATT transect

SWATTtransect TREND

transect

Alpine plots

Forestry plots

Multi-scale Plot activities-AusPlots-Long Term Ecological Research Network



Multi-scale Plot activities-AusPlots-Long Term Ecological Research Network-Supersites


Australian Centre for Evolutionary Biology and BiodiversityData collection and distribution: Ecoinformatics facility

Soils SupersitesPlot networksAusPlots

Multi-Scale Plot Network

Scaling/Modelling

Ecoinformatics

ACEAS TERN Portal

Coasts OzFluxAusCover



Rangelands plot network

Forestry plots

AusPlots Continental stratification to group bioregions to establish biodiversity monitoring plots



1,000 (approx) permanent biodiversity survey plots being established across the Australian Continent

Combine traditional and cutting edge techniques – modular– baseline surveys of vegetation and soil diversity and structure– collect leaf and soil samples for analysis

• Taxonomy, carbon, nutrients, isotopes, • DNA barcoding, phylogeography, genomics

– Photo points, image interpretation and remote sensing cal/val.

AusPlots – site methodology



CSIRO plotsNATT transect

SWATTtransect TREND

transect

Alpine plots

Lindenmayerand NSW plots

Long term ecological research network


Australian Centre for Evolutionary Biology and BiodiversityTRENDTRENDTransect for Environmental monitoring and Decision making

How to inform ecosystem management decisions in a variable and changing climate:

Access historical information on changeEstablish monitoring program to track changeUse ‘space as a proxy time’ for predicted changesModel predictions of changes and compare


Australian Centre for Evolutionary Biology and BiodiversityTemperature gradients

Rainfall gradients





Plot-based information – flora, veg structure, soils - field & remote sensed



Plot-based DNA analysis

DNA barcoding to understand taxonomy, phylogenetic diversity, community composition and turnover (IBOL)

Dick and Kress (2009)



Plot-based DNA analysis

DNA barcoding to understand taxonomy, phylogenetic diversity, community composition and turnover (IBOL)

Genomic analysis to examine soil communities (metabarcoding, amplicon COX, RBCL, ITS) and plant gene expression changes along selection pressures (ARC, BGI, BPA)

Dick and Kress (2009)Callistemon teretifolius

VERIFYING TIMBER SOURCES

Range of levels of DNA discrimination

Individual log tracking

– Verify integrity of supply chain

Regional origin

– Verify country source

Species origin

– Verify species

DNA Fingerprinting

Phylogeography

DNA barcoding

Application to dateIndividual log tracking with Certisource

Primary

With funding support from the International Tropical Timber Organisation

Lowe et al., 2010

Primary


At concession 2627 logs sampled


Lowe et al., 2010

Primary



At saw mill32 logs randomly

sampled


Lowe et al., 2010

Primary



At saw mill32 logs randomly

sampled

Matched back


Lowe et al., 2010

Timber Tracking

Forest and sawmill samples profiled with 14 microsatellites

Example Test 1 Test2Forest sample 236, 238 240,248Sawmill sample 236, 238 238,246

No. loci match? Substitution?Sample 1 6 exact 1 in 50 million

Lowe et al., 2010

Timber Tracking

Forest and sawmill samples profiled with 14 microsatellites

Example Test 1 Test2Forest sample 236, 238 240,248Sawmill sample 236, 238 238,246

No. loci match? Substitution?Sample 1 6 exact 1 in 50 million

Of 32 samples, 27 exact match, 5 did not amplifyProbability of substitution very low

Lowe et al., 2010




Regional origin


Species origin

– Verify species

DNA Fingerprinting

Phylogeography

DNA barcoding

Practical test with 20 mahogany wood samples of German timber trader + 11 wood samples from South America

Score for Guatemala: 100%

Score for Bolivia: 98.7%

Checking country of origin

33 populations2038 trees genotypedDegen et al, subm.

Mahogany

Checking region of origin

Merbau – valuable timber tree

Intsia bijugaSingapore and New Guinea

Intsia palembanicaSabah and Papua

>1000 individuals screened

6 chloroplast loci

Checking region of origin

Merbau – valuable timber tree

Intsia bijugaSingapore and New Guinea

Intsia palembanicaSabah and Papua

>1000 individuals screened

6 chloroplast loci




Regional origin


Species origin

– Verify species

DNA Fingerprinting

Phylogeography

DNA barcoding

Checking species identityMahogany

Swietenia macrophylla

S. mahagoniSwietenia macrophylla

Specific projects with focus on CITES protected tree species => vTI + University of Hamburg (Aki Höltken and Elisabeth Magel)

Approach:• sequencing of cpDNA-

fragments

• searching for SNPs

• new primer design for short PCR amplification products (< 350 bp)

45

Source: http://africamap.harvard.edu/Center for Geographic Analysis

Seven target countriesNew project in Africa

Species identityCountry of originChain of custody

http://africamap.harvard.edu/�

DNA extraction from wood

DNA + other compounds

Wood contains many secondary compounds that affect success of DNA extraction and PCR Including: cellulose, lignin, hemicellulose, resins, waxes, trace elements

DNA extraction from woodBoundaries of possibility

Raw timber

Sawn timber

Solid wood product

Ancient wood(Mary Rose)

Composite products

(veneer, ply)Pulp and

paper

Intact DNA Highly degraded

DNA

Technology frontier

Acknowledgements

• Wet tropics barcoding– Australian Tropical Herbarium, James Cook University, TRIN, CSIRO, – Craig Costion, Darren Crayn, Gary Sankowsky, Andrew Ford,

Dan Metcalfe, Will Edwards, James Richardson, Hugh Cross

• TERN/TREND– Jeff Foulkes, Ben Sparrow, Andrew White, Nikki Thurgate, – Greg Guerin, Hugh Cross, Ed Biffin, Kimberly McCallum

• Illegal logging– von Thunen Institute, Double Helix Tracking Technologies– Bernd Degen, Hugh Cross, Aki Höltken, Darren Thomas, Jonathan Geach

Andrew Lowe - Plants Plenary

Education

evolutionary biology

dna extraction dna

species w

accuracy of species

vs pd0

species f48 26f51 vs

plant dna barcodes36f56e3to

craig costion