The landscape pathology and network epidemiology of Phytophthora ramorum
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Transcript of The landscape pathology and network epidemiology of Phytophthora ramorum
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Photo: Dave Rizzo, Univ. of California, Davis
Landscape pathology and network epidemiology of Phytophthora ramorum
Marco PautassoImperial College,
Silwood Park
York University, 19 June 2008
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From: Hufnagel, Brockmann & Geisel (2004) Forecast and control of epidemics in a globalized world. PNAS 101: 15124-15129
number of passengers per day
Disease spread in a globalized world
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Photo: Marin County Fire DepartmentMarin County, CA, US (north of San Francisco)
Sudden Oak Death1. Phytophthora ramorum and related species
3. The relevance of network epidemiology
2. The Sudden Oak Death outbreak in the US and the situation in the UK
4. Conclusions
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Photos: UC Davis & UC Berkeley
Phytophthora ramorum in culture
Sporangia releasing zoospores
Phytophthora ramorum
Chlamydospores
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P. ramorum: an aggressive AND generalist pathogen
Modified from: Pautasso, Holdenrieder & Stenlid (2005) In: Forest Diversity and Function: Temperate and Boreal Systems. Ecological Studies
Acer macrophyllum, Aesculuscalifornica, Lithocarpus densiflorus, Quercus agrifolia, Quercus kelloggii, Quercus chrysolepis, Quercus parvula,
Pseudotsuga menziesii, Sequoia sempervirens
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Super-connected nodes in the network of co-occurrences at infected sites (England & Wales, 2003-2005) of genera susceptible to P. ramorum
from: Pautasso, Harwood, Xu, Shaw & Jeger (2008) Proceedings SOD Science Symposium III
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Phytophthora is a Stramenopile/Straminipile
from: James et al. (2006) Nature
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Other Phytophthoras: P. infestans
Photo: William Fry, Cornell University
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Jarrah forest dieback due to Phytophthora cinnamomi
from: http://www.cmis.csiro.au/rsm/casestudies/flyers/dieback/bluffdie2.jpg
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from: Jeger & Pautasso (2008) New Phytologist
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Picture courtesy of Thomas Jung, http://www.baumkrankheiten.com/
Alnus dieback in Bavaria
due to Phytophthora
alni
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Phytophthora alni along water courses in Bavaria
Modified from: Holdenrieder et al. (2004) Trends in Ecology & Evolution
From: Jung & Blaschke (2004) Plant Pathology
10 km
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P. ramorumconfirmations on
the US West Coast vs. national risk
Map from www.suddenoakdeath.orgKelly, UC-Berkeley
Hazard map: Frank Koch & Bill Smith, 3rd SOD Science
Symposium (2007)
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from: Rizzo et al. (2005) Annual Reviews of Phytopathology, Photo: Susan Frankel
P. ramorum in Monterey County, California
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The Phytophthora ramorum outbreak in Curry Count, Oregon; from: Hansen (2007) SOD Science Symposium III
2001 2002 2003
2004 2005 2006
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from: Rizzo et al. (2005) Annual Reviews of Phytopathology, Photo: Clive Brasier
P. ramorum eradication in Oregon
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Phytophthora ramorum in England & Wales (2003-2006)
Outbreak maps courtesy of David Slawson, PHSI, DEFRA, UK
Climatic match courtesy of Richard Baker, CSL, UK
511 nurseries/ garden centres
85
426
168 historic gardens/ woodlands
46
122
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Dec/02 Jun/03 Dec/03 Jun/04 Dec/04 Jun/05 Dec/05 Jun/06 Dec/06
Num
ber o
f cas
es m
onth
ly (s
ite)
0
10
20
30
40
50
60Garden/Nursery Other lcoations
Phytophthora ramorum in the UK (2003-2006)
garden/nurserysemi-natural environment
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Spatial analysis of P. ramorum reported cases in the UK: garden/nurseries vs. semi-natural environment
O12(r) v
alue
s
0.00
0.06
0.12
0.18
0.24
0.30f: Garden/Nursery - SNE 04 - 05
Distance (km)0 2 4 6 8 10
0.0
0.1
0.2
0.3
0.4g: Garden/Nursery - SNE 05 - 06
0.00
0.05
0.10
0.15
0.20
Distance (km)0 2 4 6 8 10
0.00
0.05
0.10
0.15
0.20d: SNE - Garden/Nursery 05 - 06
c: SNE - Garden/Nursery 04 - 05
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from: McKelvey, Koch & Smith (2007) SOD Science Symposium III
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NATURAL
TECHNOLOGICAL SOCIAL
food webs
airport networks
cell metabolism
neural networks
railway networks
ant nests
WWWInternet
electrical power grids
software mapscomputing
gridsE-mail
patterns
innovation flows
telephone calls
co-authorship nets
family networks
committees
sexual partnerships DISEASE
SPREAD
Food web of Little Rock Lake, Wisconsin, US
Internet structure
Network pictures from: Newman (2003) SIAM Review
HIV spread
network
Epidemiology is just one of the many applications of network theory
urban road networks
modified from: Jeger, Pautasso, Holdenrieder & Shaw (2007) New Phytologist
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step 1
step 2
step 3
step n
…
Simple model of infection spread (e.g. P. ramorum) in a network
pt probability of infection transmission
pp probability of infection persistence
… 100node 1 2 3 4 5 6 7 8
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The four basic types of network structure used
local
random
small-world
scale-free
SIS Model, 100 Nodes, directed networks, p [i (x, t)] = Σ {p [s] * p [i (y, t-1)] + p [p] * p [i (x, t-1)]}
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0.0
0.2
0.4
0.6
0.8
1.0
1.2
1 26 51 760
10
20
30
40
50
60
70
80
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1 26 51 760
5
10
15
20
25
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1 26 51 760
10
20
30
40
50
60
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1 51 101 151 2010
5
10
15
20
25
30
35
40
Examples of epidemic development in four kinds of directed networks of small size (at threshold conditions)
local
sum
pro
babi
lity
of in
fect
ion
acro
ss a
ll no
des
randomscale-free
% n
odes
with
pro
babi
lity
of in
fect
ion
> 0.
01
from: Pautasso & Jeger (2008) Ecological Complexity
small-world
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0.00
0.25
0.50
0.75
1.00
0.00 0.05 0.10 0.15 0.20 0.25 0.30
probability of transmission
prob
abili
ty o
f per
sist
ence local
small-world
random
scale-free
Lower epidemic threshold for scale-free networks
from: Pautasso & Jeger (2008) Ecological Complexity
Epidemic does not develop
Epidemic develops
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Lower epidemic threshold for two-way scale-free networks (unless networks are sparsely connected)
N replicates = 100; error bars are St. Dev.; different letters show sign. different means
at p < 0.05
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probability of persistence = 0
Lower epidemic threshold for higher correlation coefficient between out- and in-degree
N = 100, links = 369, pp = 0
0.000
0.200
0.400
0.600
0.800
1.000
-0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0
correlation coefficient between links in and links out
thre
shol
d p
of tr
ansm
issi
on
localrandomsmall-worldscale-free 2scale-free 0scale-free 1
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scale-free network nr 8
0
25
50
75
100
0 25 50 75 100
local network nr 2
0
25
50
75
100
0 25 50 75 100
starting node
% n
odes
at e
quili
briu
m w
ith p
roba
bilit
y of
infe
ctio
n >
0.01
starting node
random network nr 9
0
25
50
75
100
0 25 50 75 100
small world network nr 6
0
25
50
75
100
0 25 50 75 100
Marked variations in the final size of the epidemic at threshold conditions depending on the starting node
a b
dc
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-1.0
0.0
1.0
-1 0 1 2 3
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0 2 4 6 8 10 12
0.0
0.5
1.0
1.5
2.0
0 1 2 3 4 5 6
sum
at e
quili
briu
m o
f pro
babi
lity
of in
fect
ion
acro
ss a
ll no
des
Variations in epidemic final size at threshold conditions are well explained by the number of links from the starting node
local
random scale-free (log-log scale)
n of links from starting node n of links from starting node
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0 2 4 6 8
small-world
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Correlation of epidemic final size with out-degree of starting node increases with network connectivity
N replicates = 100; error bars are St. Dev.; different letters show sign. different means at p < 0.05
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Connectivity loss in the North American power grid due to the removal of transmission substations
from: Albert, Albert & Nakarado (2004) Physical Review E
transmission nodes removed (%)
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Three main results:
1. lower epidemic threshold for scale-free networks compared with random, small-world and local
networks even if networks are of small size
2. but: targeting control towards super-connected nodes is potentially a more effective and efficient
eradication or management strategy
3. importance of trace-forward/-back data for better characterizing the structure of the UK horticultural
trade network
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Super-connected nodes in the network of co-occurrences at infected sites (England & Wales, 2003-2005) of genera susceptible to P. ramorum
from: Pautasso, Harwood, Xu, Shaw & Jeger (2008) Proc SOD Science Symposium III
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Source: Wikimedia Commons
Back to the P. ramorum epidemic in the US West Coast
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from: Prospero et al. (2007) Molecular Ecology
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from: Anacker et al. (2008) New Phytologist
Environmental parameters related to SOD disease expression
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Effect of landscape heterogeneity on sudden oak death
from: Condeso & Meentemeyer (2007) Journal of Ecology and: Mascheretti et al. (2008) Molecular Ecology
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from: Cushman & Meentemeyer (in press) Journal of Ecology
Multi-scale correlation of human presence and Phytophthora ramorum disease incidence
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Source: United States Department of Agriculture, 2004Animal and Plant Health Inspection Service, Plant Protection and Quarantine
Trace forward/back zipcode
Positive (Phytophthora ramorum) site
Hold released
Effect of nursery presence on likelihood of introduction
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Conclusions:
1. landscape pathology approach
2. disease spread in networks
3. implications for emerging diseases/invasive species/climate change
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What about horse chestnut bleeding canker? (not due to Pythophthora ramorum but to Pseudomonas syringae)
From: Report on the National Survey to Assess the Presence of Bleeding Canker of Horse Chestnut Trees in Great Britain, Forestry Commission (March 2008)
Bleeding canker ≠Cameraria ohridella rural
urban
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Acknowledgements
Ottmar Holdenrieder,
ETHZ, CH
Mike Shaw, University of
Reading
Alan Inman,
DEFRA
Joan Webber, Forest Research,
Farnham
Tom Harwood,
CEP, Imperial College
Mike Jeger, Wye & Silwood, Imperial College
Jennifer Parke, Univ. of Oregon
Xiangming Xu, East Malling
Research
Mathieu Moslonka-Lefebvre, Univ. Orsay & ENS Cachan, France
Richard Baker, CSL
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ReferencesDehnen-Schmutz K, Holdenrieder O, Jeger MJ & Pautasso M (2010) Structural change in the international horticultural industry: some implications for plant health. Scientia Horticulturae 125: 1-15Harwood TD, Xu XM, Pautasso M, Jeger MJ & Shaw M (2009) Epidemiological risk assessment using linked network and grid based modelling: Phytophthora ramorum and P. kernoviae in the UK. Ecological Modelling 220: 3353-3361 Jeger MJ & Pautasso M (2008) Comparative epidemiology of zoosporic plant pathogens. European Journal of Plant Pathology 122: 111-126MacLeod A, Pautasso M, Jeger MJ & Haines-Young R (2010) Evolution of the international regulation of plant pests and challenges for future plant health. Food Security 2: 49-70 Moslonka-Lefebvre M, Pautasso M & Jeger MJ (2009) Disease spread in small-size directed networks: epidemic threshold, correlation between links to and from nodes, and clustering. Journal of Theoretical Biology 260: 402-411Moslonka-Lefebvre M, Finley A, Dorigatti I, Dehnen-Schmutz K, Harwood T, Jeger MJ, Xu XM, Holdenrieder O & Pautasso M (2011) Networks in plant epidemiology: from genes to landscapes, countries and continents. Phytopathology 101: 392-403Pautasso M (2009) Geographical genetics and the conservation of forest trees. Perspectives in Plant Ecology, Systematics and Evolution 11: 157-189Pautasso M, Dehnen-Schmutz K, Holdenrieder O, Pietravalle S, Salama N, Jeger MJ, Lange E & Hehl-Lange S (2010) Plant health and global change – some implications for landscape management. Biological Reviews 85: 729-755Pautasso M, Moslonka-Lefebvre M & Jeger MJ (2010) The number of links to and from the starting node as a predictor of epidemic size in small-size directed networks. Ecological Complexity 7: 424-432 Pautasso M, Xu XM, Jeger MJ, Harwood T, Moslonka-Lefebvre M & Pellis L (2010) Disease spread in small-size directed trade networks: the role of hierarchical categories. Journal of Applied Ecology 47: 1300-1309Xu XM, Harwood TD, Pautasso M & Jeger MJ (2009) Spatio-temporal analysis of an invasive plant pathogen (Phytophthora ramorum) in England and Wales. Ecography 32: 504-516